Modeling a hierarchical structure of factors influencing exploitation policy for water distribution systems using ISM approach

NASA Astrophysics Data System (ADS)

Jasiulewicz-Kaczmarek, Małgorzata; Wyczółkowski, Ryszard; Gładysiak, Violetta

2017-12-01

Water distribution systems are one of the basic elements of contemporary technical infrastructure of urban and rural areas. It is a complex engineering system composed of transmission networks and auxiliary equipment (e.g. controllers, checkouts etc.), scattered territorially over a large area. From the water distribution system operation point of view, its basic features are: functional variability, resulting from the need to adjust the system to temporary fluctuations in demand for water and territorial dispersion. The main research questions are: What external factors should be taken into account when developing an effective water distribution policy? Does the size and nature of the water distribution system significantly affect the exploitation policy implemented? These questions have shaped the objectives of research and the method of research implementation.

Highly dynamic animal contact network and implications on disease transmission

PubMed Central

Chen, Shi; White, Brad J.; Sanderson, Michael W.; Amrine, David E.; Ilany, Amiyaal; Lanzas, Cristina

2014-01-01

Contact patterns among hosts are considered as one of the most critical factors contributing to unequal pathogen transmission. Consequently, networks have been widely applied in infectious disease modeling. However most studies assume static network structure due to lack of accurate observation and appropriate analytic tools. In this study we used high temporal and spatial resolution animal position data to construct a high-resolution contact network relevant to infectious disease transmission. The animal contact network aggregated at hourly level was highly variable and dynamic within and between days, for both network structure (network degree distribution) and individual rank of degree distribution in the network (degree order). We integrated network degree distribution and degree order heterogeneities with a commonly used contact-based, directly transmitted disease model to quantify the effect of these two sources of heterogeneity on the infectious disease dynamics. Four conditions were simulated based on the combination of these two heterogeneities. Simulation results indicated that disease dynamics and individual contribution to new infections varied substantially among these four conditions under both parameter settings. Changes in the contact network had a greater effect on disease dynamics for pathogens with smaller basic reproduction number (i.e. R0 < 2). PMID:24667241

Chinese Mainland Movie Network

NASA Astrophysics Data System (ADS)

Liu, Ai-Fen; Xue, Yu-Hua; He, Da-Ren

2008-03-01

We propose describing a large kind of cooperation-competition networks by bipartite graphs and their unipartite projections. In the graphs the topological structure describe the cooperation-competition configuration of the basic elements, and the vertex weight describe their different roles in cooperation or results of competition. This complex network description may be helpful for finding and understanding common properties of cooperation-competition systems. In order to show an example, we performed an empirical investigation on the movie cooperation-competition network within recent 80 years in the Chinese mainland. In the net the movies are defined as nodes, and two nodes are connected by a link if a common main movie actor performs in them. The edge represents the competition relationship between two movies for more audience among a special audience colony. We obtained the statistical properties, such as the degree distribution, act degree distribution, act size distribution, and distribution of the total node weight, and explored the influence factors of Chinese mainland movie competition intensity.

Effect of node attributes on the temporal dynamics of network structure

NASA Astrophysics Data System (ADS)

Momeni, Naghmeh; Fotouhi, Babak

2017-03-01

Many natural and social networks evolve in time and their structures are dynamic. In most networks, nodes are heterogeneous, and their roles in the evolution of structure differ. This paper focuses on the role of individual attributes on the temporal dynamics of network structure. We focus on a basic model for growing networks that incorporates node attributes (which we call "quality"), and we focus on the problem of forecasting the structural properties of the network in arbitrary times for an arbitrary initial network. That is, we address the following question: If we are given a certain initial network with given arbitrary structure and known node attributes, then how does the structure change in time as new nodes with given distribution of attributes join the network? We solve the model analytically and obtain the quality-degree joint distribution and degree correlations. We characterize the role of individual attributes in the position of individual nodes in the hierarchy of connections. We confirm the theoretical findings with Monte Carlo simulations.

An Architecture for Controlling Multiple Robots

NASA Technical Reports Server (NTRS)

Aghazarian, Hrand; Pirjanian, Paolo; Schenker, Paul; Huntsberger, Terrance

2004-01-01

The Control Architecture for Multirobot Outpost (CAMPOUT) is a distributed-control architecture for coordinating the activities of multiple robots. In the CAMPOUT, multiple-agent activities and sensor-based controls are derived as group compositions and involve coordination of more basic controllers denoted, for present purposes, as behaviors. The CAMPOUT provides basic mechanistic concepts for representation and execution of distributed group activities. One considers a network of nodes that comprise behaviors (self-contained controllers) augmented with hyper-links, which are used to exchange information between the nodes to achieve coordinated activities. Group behavior is guided by a scripted plan, which encodes a conditional sequence of single-agent activities. Thus, higher-level functionality is composed by coordination of more basic behaviors under the downward task decomposition of a multi-agent planner

Delay decomposition at a single server queue with constant service time and multiple inputs. [Waiting time on computer network

NASA Technical Reports Server (NTRS)

Ziegler, C.; Schilling, D. L.

1977-01-01

Two networks consisting of single server queues, each with a constant service time, are considered. The external inputs to each network are assumed to follow some general probability distribution. Several interesting equivalencies that exist between the two networks considered are derived. This leads to the introduction of an important concept in delay decomposition. It is shown that the waiting time experienced by a customer can be decomposed into two basic components called self delay and interference delay.

A model of individualized canonical microcircuits supporting cognitive operations

PubMed Central

Peterson, Andre D. H.; Haueisen, Jens; Knösche, Thomas R.

2017-01-01

Major cognitive functions such as language, memory, and decision-making are thought to rely on distributed networks of a large number of basic elements, called canonical microcircuits. In this theoretical study we propose a novel canonical microcircuit model and find that it supports two basic computational operations: a gating mechanism and working memory. By means of bifurcation analysis we systematically investigate the dynamical behavior of the canonical microcircuit with respect to parameters that govern the local network balance, that is, the relationship between excitation and inhibition, and key intrinsic feedback architectures of canonical microcircuits. We relate the local behavior of the canonical microcircuit to cognitive processing and demonstrate how a network of interacting canonical microcircuits enables the establishment of spatiotemporal sequences in the context of syntax parsing during sentence comprehension. This study provides a framework for using individualized canonical microcircuits for the construction of biologically realistic networks supporting cognitive operations. PMID:29200435

Exponential Arithmetic Based Self-Healing Group Key Distribution Scheme with Backward Secrecy under the Resource-Constrained Wireless Networks

PubMed Central

Guo, Hua; Zheng, Yandong; Zhang, Xiyong; Li, Zhoujun

2016-01-01

In resource-constrained wireless networks, resources such as storage space and communication bandwidth are limited. To guarantee secure communication in resource-constrained wireless networks, group keys should be distributed to users. The self-healing group key distribution (SGKD) scheme is a promising cryptographic tool, which can be used to distribute and update the group key for the secure group communication over unreliable wireless networks. Among all known SGKD schemes, exponential arithmetic based SGKD (E-SGKD) schemes reduce the storage overhead to constant, thus is suitable for the the resource-constrained wireless networks. In this paper, we provide a new mechanism to achieve E-SGKD schemes with backward secrecy. We first propose a basic E-SGKD scheme based on a known polynomial-based SGKD, where it has optimal storage overhead while having no backward secrecy. To obtain the backward secrecy and reduce the communication overhead, we introduce a novel approach for message broadcasting and self-healing. Compared with other E-SGKD schemes, our new E-SGKD scheme has the optimal storage overhead, high communication efficiency and satisfactory security. The simulation results in Zigbee-based networks show that the proposed scheme is suitable for the resource-restrained wireless networks. Finally, we show the application of our proposed scheme. PMID:27136550

Delay decomposition at a single server queue with constant service time and multiple inputs

NASA Technical Reports Server (NTRS)

Ziegler, C.; Schilling, D. L.

1978-01-01

Two network consisting of single server queues, each with a constant service time, are considered. The external inputs to each network are assumed to follow some general probability distribution. Several interesting equivalencies that exist between the two networks considered are derived. This leads to the introduction of an important concept in delay decomposition. It is shown that the waiting time experienced by a customer can be decomposed into two basic components called self-delay and interference delay.

Computer simulation of CaSiO3 glass under compression: correlation between Si-Si pair radial distribution function and intermediate range order structure

NASA Astrophysics Data System (ADS)

Lan, Mai Thi; Thuy Duong, Tran; Iitaka, Toshiaki; Van Hong, Nguyen

2017-06-01

The structural organization of CaSiO3 glass at 600 K and under pressure of 0-100 GPa is investigated by molecular dynamics simulation (MDS). Results show that the atomic structure of CaSiO3 comprises SiO n and CaO m units considered as basic structural polyhedra. At low pressure, most of the basic structural polyhedra are SiO4, CaO5, CaO6 and CaO7. At high pressure most of the basic structural polyhedra are SiO5, SiO6 and CaO9, CaO10 and CaO11. The distribution of basic structural polyhedra is not uniform resulting in formation of Ca-rich and Si-rich regions. The distribution of SiO4, SiO5 and SiO6 polyhedra is also not uniform, but it tends to form SiO4-, SiO5-, and SiO6-clusters. For the Si-O network, under compression there is a gradual transition from the tetrahedral network (SiO4) to the octahedral network (SiO6) via SiO5 polyhedra. The SiO5-clusters are the same as immediate-phase in the transformation process. The size and shape of SiO4 tetrahedra change strongly under compression. While the size of SiO5 and SiO6 has also changed significantly, but the shape is almost unchanged under compression. The SiO n polyhedra can connect to each other via one common oxygen ion (corner-sharing bond), two common oxygen ions (edge-sharing bond) or three common oxygen ions (face-sharing bond). The Si-Si bond length in corner-sharing bonds is much longer than the ones in edge-sharing and face-sharing bonds. The change of intermediate range order (IRO) structure under compression relating to edge- and face-sharing bonds amongst SiO n at high pressure is the origin of the first peak splitting of the radial distribution functions of Si-Si pair. Under compression, the number of non-bridging oxygen (NBO) decreases. This makes the Si-O network more polymerized. At low pressure, most of the Ca2+ ions incorporate into the Si-O network via NBOs. At high pressure, the amount of NBO decreases, Ca2+ ions mainly incorporate into the Si-O network via bridging oxygen (BO) that belongs to SiO5 and SiO6 with a negative charge. And this is the principle for immobilization of heavy metal as well as fissile materials in hazardous waste (nuclear waste).

Macro-Econophysics

NASA Astrophysics Data System (ADS)

Aoyama, Hideaki; Fujiwara, Yoshi; Ikeda, Yuichi; Iyetomi, Hiroshi; Souma, Wataru; Yoshikawa, Hiroshi

2017-07-01

Preface; Foreword, Acknowledgements, List of tables; List of figures, prologue, 1. Introduction: reconstructing macroeconomics; 2. Basic concepts in statistical physics and stochastic models; 3. Income and firm-size distributions; 4. Productivity distribution and related topics; 5. Multivariate time-series analysis; 6. Business cycles; 7. Price dynamics and inflation/deflation; 8. Complex network, community analysis, visualization; 9. Systemic risks; Appendix A: computer program for beginners; Epilogue; Bibliography; Index.

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

2017-04-01

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.

Introducing FNCS: Framework for Network Co-Simulation

ScienceCinema

None

2018-06-07

This video provides a basic overview of the PNNL Future Power Grid Initiative-developed Framework for Network Co-Simulation (FNCS). It discusses the increasing amounts of data coming from the power grid, and the need for a tool like FNCS that brings together data, transmission and distribution simulators. Included is a description of the FNCS architecture, and the advantages this new open source tool can bring to grid research and development efforts.

Introducing FNCS: Framework for Network Co-Simulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2014-10-23

This video provides a basic overview of the PNNL Future Power Grid Initiative-developed Framework for Network Co-Simulation (FNCS). It discusses the increasing amounts of data coming from the power grid, and the need for a tool like FNCS that brings together data, transmission and distribution simulators. Included is a description of the FNCS architecture, and the advantages this new open source tool can bring to grid research and development efforts.

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks.

PubMed

Filho, Humberto A; Machicao, Jeaneth; Bruno, Odemir M

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology.

A hierarchical model of metabolic machinery based on the kcore decomposition of plant metabolic networks

PubMed Central

Filho, Humberto A.; Machicao, Jeaneth

2018-01-01

Modeling the basic structure of metabolic machinery is a challenge for modern biology. Some models based on complex networks have provided important information regarding this machinery. In this paper, we constructed metabolic networks of 17 plants covering unicellular organisms to more complex dicotyledonous plants. The metabolic networks were built based on the substrate-product model and a topological percolation was performed using the kcore decomposition. The distribution of metabolites across the percolation layers showed correlations between the metabolic integration hierarchy and the network topology. We show that metabolites concentrated in the internal network (maximum kcore) only comprise molecules of the primary basal metabolism. Moreover, we found a high proportion of a set of common metabolites, among the 17 plants, centered at the inner kcore layers. Meanwhile, the metabolites recognized as participants in the secondary metabolism of plants are concentrated in the outermost layers of the network. This data suggests that the metabolites in the central layer form a basic molecular module in which the whole plant metabolism is anchored. The elements from this central core participate in almost all plant metabolic reactions, which suggests that plant metabolic networks follows a centralized topology. PMID:29734359

Distributed Mission Operations: Training Today’s Warfighters for Tomorrow’s Conflicts

DTIC Science & Technology

2016-02-01

systems or include dissimilar weapons systems to rehearse more complex mission sets. In addition to networking geographically separated simulators...over the past decade. Today, distributed mission operations can facilitate the rehearsal of theater wide operations, integrating all the anticipated...effective that many aviators earn their basic aircraft qualification before their first flight in the airplane.11 Computer memory was once a

Insights into a spatially embedded social network from a large-scale snowball sample

NASA Astrophysics Data System (ADS)

Illenberger, J.; Kowald, M.; Axhausen, K. W.; Nagel, K.

2011-12-01

Much research has been conducted to obtain insights into the basic laws governing human travel behaviour. While the traditional travel survey has been for a long time the main source of travel data, recent approaches to use GPS data, mobile phone data, or the circulation of bank notes as a proxy for human travel behaviour are promising. The present study proposes a further source of such proxy-data: the social network. We collect data using an innovative snowball sampling technique to obtain details on the structure of a leisure-contacts network. We analyse the network with respect to its topology, the individuals' characteristics, and its spatial structure. We further show that a multiplication of the functions describing the spatial distribution of leisure contacts and the frequency of physical contacts results in a trip distribution that is consistent with data from the Swiss travel survey.

[Buying and distribution of drugs: perceptions of officers of a network of primary health care in the interior of the state of Sao Paulo].

PubMed

Juliani, C M

1995-12-01

The study present analyse the process to buy and distribution of medicaments for the Basic Unit of Health in municipal district of state São Paulo. To achieve some general considerations about the National Politic of Medicaments in Brazil, to emphasize feature relative the its structuration in the Unique System of Health.

Modular and hierarchical structure of social contact networks

NASA Astrophysics Data System (ADS)

Ge, Yuanzheng; Song, Zhichao; Qiu, Xiaogang; Song, Hongbin; Wang, Yong

2013-10-01

Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.

A Network Pump

DTIC Science & Technology

1996-05-01

introduced as shown in Fig. 3. Pump ~ y { ~ ~ ~ = ~ messages ACK buffer Fig. 3. The Basic Pump The basic Pump [6] places a buffer (size n ) between...exponential distribution with mean x. Define Q = fY(MAll - T,) + k . ( N - Fair size) where N is the number of messages in buffer, at the time the...message is placed in buffer,,, and k . ( N - Fair size) is a feedback term. Both k and Fair size can be chosen by a sys- tem designer. Note that the moving

Metabolic networks evolve towards states of maximum entropy production.

PubMed

Unrean, Pornkamol; Srienc, Friedrich

2011-11-01

A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles. Copyright © 2011 Elsevier Inc. All rights reserved.

Interactions Between Structure and Processing that Control Moisture Uptake in High-Performance Polycyanurates (Briefing Charts)

DTIC Science & Technology

2015-03-24

distribution is unlimited.  . Interactions Between Structure and Processing that Control Moisture Uptake in High-Performance Polycyanurates Presenter: Dr...Edwards AFB, CA 4 California State University, Long Beach, CA 90840 2 Outline: Basic Studies of Moisture Uptake in Cyanate Ester Networks • Background...Motivation • SOTA Theories of Moisture Uptake in Thermosetting Networks • New Tools and New Discoveries • Unresolved Issues and Ways to Address Them

The spreading dynamics of sexually transmitted diseases with birth and death on heterogeneous networks

NASA Astrophysics Data System (ADS)

Wang, Yi; Cao, Jinde; Alsaedi, Ahmed; Hayat, Tasawar

2017-02-01

In this paper, we formulate a deterministic model by including the vacant sites, which represent inactive individuals or potential contacts, to investigate the spreading dynamics of sexually transmitted diseases in heterogeneous networks. We first analytically derive the basic reproduction number R 0, which completely determines global dynamics of the system in the long run. Specifically, if R 0  <  1, the disease-free equilibrium is globally asymptotically stable, i.e. disease disappears from the network irrespective of initial infected numbers and distributions, whereas if R 0  >  1, the system is uniformly persistent around a unique endemic equilibrium, i.e. disease persists in the network. Furthermore, by using a suitable Lyapunov function the global stability of endemic equilibrium for low/high-risk infected individuals only is proved. Finally, the effects of three immunization schemes are studied and compared, and extensive numerical simulations are performed to investigate the effect of network topology and population turnover on disease spread. Our results suggest that population turnover could have great impact on the sexually transmitted disease system in heterogeneous networks, including the basic reproduction number and infection prevalence.

Quantifying randomness in real networks

NASA Astrophysics Data System (ADS)

Orsini, Chiara; Dankulov, Marija M.; Colomer-de-Simón, Pol; Jamakovic, Almerima; Mahadevan, Priya; Vahdat, Amin; Bassler, Kevin E.; Toroczkai, Zoltán; Boguñá, Marián; Caldarelli, Guido; Fortunato, Santo; Krioukov, Dmitri

2015-10-01

Represented as graphs, real networks are intricate combinations of order and disorder. Fixing some of the structural properties of network models to their values observed in real networks, many other properties appear as statistical consequences of these fixed observables, plus randomness in other respects. Here we employ the dk-series, a complete set of basic characteristics of the network structure, to study the statistical dependencies between different network properties. We consider six real networks--the Internet, US airport network, human protein interactions, technosocial web of trust, English word network, and an fMRI map of the human brain--and find that many important local and global structural properties of these networks are closely reproduced by dk-random graphs whose degree distributions, degree correlations and clustering are as in the corresponding real network. We discuss important conceptual, methodological, and practical implications of this evaluation of network randomness, and release software to generate dk-random graphs.

Combined effect of CVR and penetration of DG in the voltage profile and losses of lowvoltage secondary distribution networks

NASA Astrophysics Data System (ADS)

Bokhari, Abdullah

Demarcations between traditional distribution power systems and distributed generation (DG) architectures are increasingly evolving as higher DG penetration is introduced in the system. The concerns in existing electric power systems (EPSs) to accommodate less restrictive interconnection policies while maintaining reliability and performance of power delivery have been the major challenge for DG growth. In this dissertation, the work is aimed to study power quality, energy saving and losses in a low voltage distributed network under various DG penetration cases. Simulation platform suite that includes electric power system, distributed generation and ZIP load models is implemented to determine the impact of DGs on power system steady state performance and the voltage profile of the customers/loads in the network under the voltage reduction events. The investigation designed to test the DG impact on power system starting with one type of DG, then moves on multiple DG types distributed in a random case and realistic/balanced case. The functionality of the proposed DG interconnection is designed to meet the basic requirements imposed by the various interconnection standards, most notably IEEE 1547, public service commission, and local utility regulation. It is found that implementation of DGs on the low voltage secondary network would improve customer's voltage profile, system losses and significantly provide energy savings and economics for utilities. In a network populated with DGs, utility would have a uniform voltage profile at the customers end as the voltage profile becomes more concentrated around targeted voltage level. The study further reinforced the concept that the behavior of DG in distributed network would improve voltage regulation as certain percentage reduction on utility side would ensure uniform percentage reduction seen by all customers and reduce number of voltage violations.

A system for distributed intrusion detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snapp, S.R.; Brentano, J.; Dias, G.V.

1991-01-01

The study of providing security in computer networks is a rapidly growing area of interest because the network is the medium over which most attacks or intrusions on computer systems are launched. One approach to solving this problem is the intrusion-detection concept, whose basic premise is that not only abandoning the existing and huge infrastructure of possibly-insecure computer and network systems is impossible, but also replacing them by totally-secure systems may not be feasible or cost effective. Previous work on intrusion-detection systems were performed on stand-alone hosts and on a broadcast local area network (LAN) environment. The focus of ourmore » present research is to extend our network intrusion-detection concept from the LAN environment to arbitarily wider areas with the network topology being arbitrary as well. The generalized distributed environment is heterogeneous, i.e., the network nodes can be hosts or servers from different vendors, or some of them could be LAN managers, like our previous work, a network security monitor (NSM), as well. The proposed architecture for this distributed intrusion-detection system consists of the following components: a host manager in each host; a LAN manager for monitoring each LAN in the system; and a central manager which is placed at a single secure location and which receives reports from various host and LAN managers to process these reports, correlate them, and detect intrusions. 11 refs., 2 figs.« less

A Predictive Analysis of the Department of Defense Distribution System Utilizing Random Forests

DTIC Science & Technology

2016-06-01

resources capable of meeting both customer and individual resource constraints and goals while also maximizing the global benefit to the supply...and probability rules to determine the optimal red wine distribution network for an Italian-based wine producer. The decision support model for...combinations of factors that will result in delivery of the highest quality wines . The model’s first stage inputs basic logistics information to look

The influence of utility-interactive PV system characteristics to ac power networks

NASA Astrophysics Data System (ADS)

Takeda, Y.; Takigawa, K.; Kaminosono, H.

Two basic experimental photovoltaic (PV) systems have been built for the study of variation of power quality, aspects of safety, and technical problems. One system uses a line-commutated inverter, while the other system uses a self-commutated inverter. A description is presented of the operating and generating characteristics of the two systems. The systems were connected to an ac simulated network which simulates an actual power distribution system. Attention is given to power generation characteristics, the control characteristics, the harmonics characteristics, aspects of coordination with the power network, and questions regarding the reliability of photovoltaic modules.

Recurrent neural network approach to quantum signal: coherent state restoration for continuous-variable quantum key distribution

NASA Astrophysics Data System (ADS)

Lu, Weizhao; Huang, Chunhui; Hou, Kun; Shi, Liting; Zhao, Huihui; Li, Zhengmei; Qiu, Jianfeng

2018-05-01

In continuous-variable quantum key distribution (CV-QKD), weak signal carrying information transmits from Alice to Bob; during this process it is easily influenced by unknown noise which reduces signal-to-noise ratio, and strongly impacts reliability and stability of the communication. Recurrent quantum neural network (RQNN) is an artificial neural network model which can perform stochastic filtering without any prior knowledge of the signal and noise. In this paper, a modified RQNN algorithm with expectation maximization algorithm is proposed to process the signal in CV-QKD, which follows the basic rule of quantum mechanics. After RQNN, noise power decreases about 15 dBm, coherent signal recognition rate of RQNN is 96%, quantum bit error rate (QBER) drops to 4%, which is 6.9% lower than original QBER, and channel capacity is notably enlarged.

Cross over of recurrence networks to random graphs and random geometric graphs

NASA Astrophysics Data System (ADS)

Jacob, Rinku; Harikrishnan, K. P.; Misra, R.; Ambika, G.

2017-02-01

Recurrence networks are complex networks constructed from the time series of chaotic dynamical systems where the connection between two nodes is limited by the recurrence threshold. This condition makes the topology of every recurrence network unique with the degree distribution determined by the probability density variations of the representative attractor from which it is constructed. Here we numerically investigate the properties of recurrence networks from standard low-dimensional chaotic attractors using some basic network measures and show how the recurrence networks are different from random and scale-free networks. In particular, we show that all recurrence networks can cross over to random geometric graphs by adding sufficient amount of noise to the time series and into the classical random graphs by increasing the range of interaction to the system size. We also highlight the effectiveness of a combined plot of characteristic path length and clustering coefficient in capturing the small changes in the network characteristics.

Infant Joint Attention, Neural Networks and Social Cognition

PubMed Central

Mundy, Peter; Jarrold, William

2010-01-01

Neural network models of attention can provide a unifying approach to the study of human cognitive and emotional development (Posner & Rothbart, 2007). This paper we argue that a neural networks approach to the infant development of joint attention can inform our understanding of the nature of human social learning, symbolic thought process and social cognition. At its most basic, joint attention involves the capacity to coordinate one’s own visual attention with that of another person. We propose that joint attention development involves increments in the capacity to engage in simultaneous or parallel processing of information about one’s own attention and the attention of other people. Infant practice with joint attention is both a consequence and organizer of the development of a distributed and integrated brain network involving frontal and parietal cortical systems. This executive distributed network first serves to regulate the capacity of infants to respond to and direct the overt behavior of other people in order to share experience with others through the social coordination of visual attention. In this paper we describe this parallel and distributed neural network model of joint attention development and discuss two hypotheses that stem from this model. One is that activation of this distributed network during coordinated attention enhances to depth of information processing and encoding beginning in the first year of life. We also propose that with development joint attention becomes internalized as the capacity to socially coordinate mental attention to internal representations. As this occurs the executive joint attention network makes vital contributions to the development of human symbolic thinking and social cognition. PMID:20884172

High Speed All-Optical Data Distribution Network

NASA Astrophysics Data System (ADS)

Braun, Steve; Hodara, Henri

2017-11-01

This article describes the performance and capabilities of an all-optical network featuring low latency, high speed file transfer between serially connected optical nodes. A basic component of the network is a network interface card (NIC) implemented through a unique planar lightwave circuit (PLC) that performs add/drop data and optical signal amplification. The network uses a linear bus topology with nodes in a "T" configuration, as described in the text. The signal is sent optically (hence, no latency) to all nodes via wavelength division multiplexing (WDM), with each node receiver tuned to wavelength of choice via an optical de-multiplexer. Each "T" node routes a portion of the signal to/from the bus through optical couplers, embedded in the network interface card (NIC), to each of the 1 through n computers.

Hierarchical structural health monitoring system combining a fiber optic spinal cord network and distributed nerve cell devices

NASA Astrophysics Data System (ADS)

Minakuchi, Shu; Tsukamoto, Haruka; Takeda, Nobuo

2009-03-01

This study proposes novel hierarchical sensing concept for detecting damages in composite structures. In the hierarchical system, numerous three-dimensionally structured sensor devices are distributed throughout the whole structural area and connected with the optical fiber network through transducing mechanisms. The distributed "sensory nerve cell" devices detect the damage, and the fiber optic "spinal cord" network gathers damage signals and transmits the information to a measuring instrument. This study began by discussing the basic concept of the hierarchical sensing system thorough comparison with existing fiber optic based systems and nerve systems in the animal kingdom. Then, in order to validate the proposed sensing concept, impact damage detection system for the composite structure was proposed. The sensor devices were developed based on Comparative Vacuum Monitoring (CVM) system and the Brillouin based distributed strain sensing was utilized to gather the damage signals from the distributed devices. Finally a verification test was conducted using prototype devices. Occurrence of barely visible impact damage was successfully detected and it was clearly indicated that the hierarchical system has better repairability, higher robustness, and wider monitorable area compared to existing systems utilizing embedded optical fiber sensors.

Models and algorithm of optimization launch and deployment of virtual network functions in the virtual data center

NASA Astrophysics Data System (ADS)

Bolodurina, I. P.; Parfenov, D. I.

2017-10-01

The goal of our investigation is optimization of network work in virtual data center. The advantage of modern infrastructure virtualization lies in the possibility to use software-defined networks. However, the existing optimization of algorithmic solutions does not take into account specific features working with multiple classes of virtual network functions. The current paper describes models characterizing the basic structures of object of virtual data center. They including: a level distribution model of software-defined infrastructure virtual data center, a generalized model of a virtual network function, a neural network model of the identification of virtual network functions. We also developed an efficient algorithm for the optimization technology of containerization of virtual network functions in virtual data center. We propose an efficient algorithm for placing virtual network functions. In our investigation we also generalize the well renowned heuristic and deterministic algorithms of Karmakar-Karp.

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

An object-oriented framework for distributed hydrologic and geomorphic modeling using triangulated irregular networks

NASA Astrophysics Data System (ADS)

Tucker, Gregory E.; Lancaster, Stephen T.; Gasparini, Nicole M.; Bras, Rafael L.; Rybarczyk, Scott M.

2001-10-01

We describe a new set of data structures and algorithms for dynamic terrain modeling using a triangulated irregular network (TINs). The framework provides an efficient method for storing, accessing, and updating a Delaunay triangulation and its associated Voronoi diagram. The basic data structure consists of three interconnected data objects: triangles, nodes, and directed edges. Encapsulating each of these geometric elements within a data object makes it possible to essentially decouple the TIN representation from the modeling applications that make use of it. Both the triangulation and its corresponding Voronoi diagram can be rapidly retrieved or updated, making these methods well suited to adaptive remeshing schemes. We develop a set of algorithms for defining drainage networks and identifying closed depressions (e.g., lakes) for hydrologic and geomorphic modeling applications. We also outline simple numerical algorithms for solving network routing and 2D transport equations within the TIN framework. The methods are illustrated with two example applications, a landscape evolution model and a distributed rainfall-runoff model.

A Hybrid Key Management Scheme for WSNs Based on PPBR and a Tree-Based Path Key Establishment Method

PubMed Central

Zhang, Ying; Liang, Jixing; Zheng, Bingxin; Chen, Wei

2016-01-01

With the development of wireless sensor networks (WSNs), in most application scenarios traditional WSNs with static sink nodes will be gradually replaced by Mobile Sinks (MSs), and the corresponding application requires a secure communication environment. Current key management researches pay less attention to the security of sensor networks with MS. This paper proposes a hybrid key management schemes based on a Polynomial Pool-based key pre-distribution and Basic Random key pre-distribution (PPBR) to be used in WSNs with MS. The scheme takes full advantages of these two kinds of methods to improve the cracking difficulty of the key system. The storage effectiveness and the network resilience can be significantly enhanced as well. The tree-based path key establishment method is introduced to effectively solve the problem of communication link connectivity. Simulation clearly shows that the proposed scheme performs better in terms of network resilience, connectivity and storage effectiveness compared to other widely used schemes. PMID:27070624

Efficient Management of Certificate Revocation Lists in Smart Grid Advanced Metering Infrastructure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cebe, Mumin; Akkaya, Kemal

Advanced Metering Infrastructure (AMI) forms a communication network for the collection of power data from smart meters in Smart Grid. As the communication within an AMI needs to be secure, key management becomes an issue due to overhead and limited resources. While using public-keys eliminate some of the overhead of key management, there is still challenges regarding certificates that store and certify the publickeys. In particular, distribution and storage of certificate revocation list (CRL) is major a challenge due to cost of distribution and storage in AMI networks which typically consist of wireless multi-hop networks. Motivated by the need ofmore » keeping the CRL distribution and storage cost effective and scalable, in this paper, we present a distributed CRL management model utilizing the idea of distributed hash trees (DHTs) from peer-to-peer (P2P) networks. The basic idea is to share the burden of storage of CRLs among all the smart meters by exploiting the meshing capability of the smart meters among each other. Thus, using DHTs not only reduces the space requirements for CRLs but also makes the CRL updates more convenient. We implemented this structure on ns-3 using IEEE 802.11s mesh standard as a model for AMI and demonstrated its superior performance with respect to traditional methods of CRL management through extensive simulations.« less

Splitting nodes and linking channels: A method for assembling biocircuits from stochastic elementary units

NASA Astrophysics Data System (ADS)

Ferwerda, Cameron; Lipan, Ovidiu

2016-11-01

Akin to electric circuits, we construct biocircuits that are manipulated by cutting and assembling channels through which stochastic information flows. This diagrammatic manipulation allows us to create a method which constructs networks by joining building blocks selected so that (a) they cover only basic processes; (b) it is scalable to large networks; (c) the mean and variance-covariance from the Pauli master equation form a closed system; and (d) given the initial probability distribution, no special boundary conditions are necessary to solve the master equation. The method aims to help with both designing new synthetic signaling pathways and quantifying naturally existing regulatory networks.

Avalanches and generalized memory associativity in a network model for conscious and unconscious mental functioning

NASA Astrophysics Data System (ADS)

Siddiqui, Maheen; Wedemann, Roseli S.; Jensen, Henrik Jeldtoft

2018-01-01

We explore statistical characteristics of avalanches associated with the dynamics of a complex-network model, where two modules corresponding to sensorial and symbolic memories interact, representing unconscious and conscious mental processes. The model illustrates Freud's ideas regarding the neuroses and that consciousness is related with symbolic and linguistic memory activity in the brain. It incorporates the Stariolo-Tsallis generalization of the Boltzmann Machine in order to model memory retrieval and associativity. In the present work, we define and measure avalanche size distributions during memory retrieval, in order to gain insight regarding basic aspects of the functioning of these complex networks. The avalanche sizes defined for our model should be related to the time consumed and also to the size of the neuronal region which is activated, during memory retrieval. This allows the qualitative comparison of the behaviour of the distribution of cluster sizes, obtained during fMRI measurements of the propagation of signals in the brain, with the distribution of avalanche sizes obtained in our simulation experiments. This comparison corroborates the indication that the Nonextensive Statistical Mechanics formalism may indeed be more well suited to model the complex networks which constitute brain and mental structure.

Infant joint attention, neural networks and social cognition.

PubMed

Mundy, Peter; Jarrold, William

2010-01-01

Neural network models of attention can provide a unifying approach to the study of human cognitive and emotional development (Posner & Rothbart, 2007). In this paper we argue that a neural network approach to the infant development of joint attention can inform our understanding of the nature of human social learning, symbolic thought process and social cognition. At its most basic, joint attention involves the capacity to coordinate one's own visual attention with that of another person. We propose that joint attention development involves increments in the capacity to engage in simultaneous or parallel processing of information about one's own attention and the attention of other people. Infant practice with joint attention is both a consequence and an organizer of the development of a distributed and integrated brain network involving frontal and parietal cortical systems. This executive distributed network first serves to regulate the capacity of infants to respond to and direct the overt behavior of other people in order to share experience with others through the social coordination of visual attention. In this paper we describe this parallel and distributed neural network model of joint attention development and discuss two hypotheses that stem from this model. One is that activation of this distributed network during coordinated attention enhances the depth of information processing and encoding beginning in the first year of life. We also propose that with development, joint attention becomes internalized as the capacity to socially coordinate mental attention to internal representations. As this occurs the executive joint attention network makes vital contributions to the development of human symbolic thinking and social cognition. Copyright © 2010 Elsevier Ltd. All rights reserved.

Bayesian models: A statistical primer for ecologists

USGS Publications Warehouse

Hobbs, N. Thompson; Hooten, Mevin B.

2015-01-01

Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods—in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach.Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals.This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management.Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticiansCovers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and moreDeemphasizes computer coding in favor of basic principlesExplains how to write out properly factored statistical expressions representing Bayesian models

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

Plant conservation progress in the United States

Treesearch

Kayri Havens; Andrea Kramer; Ed. Guerrant

2017-01-01

Effective national plant conservation has several basic needs, including: 1) accessible, up-to-date information on species distribution and rarity; 2) research and management capacity to mitigate the impact of threats that make plants rare; 3) effective networks for conserving species in situ and ex situ; 4) education and training to make sure the right people are...

Dividing the Self: Distinct Neural Substrates of Task-Based and Automatic Self-Prioritization after Brain Damage

ERIC Educational Resources Information Center

Sui, Jie; Chechlacz, Magdalena; Humphreys, Glyn W.

2012-01-01

Facial self-awareness is a basic human ability dependent on a distributed bilateral neural network and revealed through prioritized processing of our own over other faces. Using non-prosopagnosic patients we show, for the first time, that facial self-awareness can be fractionated into different component processes. Patients performed two face…

Information resources at the National Center for Biotechnology Information.

PubMed Central

Woodsmall, R M; Benson, D A

1993-01-01

The National Center for Biotechnology Information (NCBI), part of the National Library of Medicine, was established in 1988 to perform basic research in the field of computational molecular biology as well as build and distribute molecular biology databases. The basic research has led to new algorithms and analysis tools for interpreting genomic data and has been instrumental in the discovery of human disease genes for neurofibromatosis and Kallmann syndrome. The principal database responsibility is the National Institutes of Health (NIH) genetic sequence database, GenBank. NCBI, in collaboration with international partners, builds, distributes, and provides online and CD-ROM access to over 112,000 DNA sequences. Another major program is the integration of multiple sequences databases and related bibliographic information and the development of network-based retrieval systems for Internet access. PMID:8374583

Network architecture test-beds as platforms for ubiquitous computing.

PubMed

Roscoe, Timothy

2008-10-28

Distributed systems research, and in particular ubiquitous computing, has traditionally assumed the Internet as a basic underlying communications substrate. Recently, however, the networking research community has come to question the fundamental design or 'architecture' of the Internet. This has been led by two observations: first, that the Internet as it stands is now almost impossible to evolve to support new functionality; and second, that modern applications of all kinds now use the Internet rather differently, and frequently implement their own 'overlay' networks above it to work around its perceived deficiencies. In this paper, I discuss recent academic projects to allow disruptive change to the Internet architecture, and also outline a radically different view of networking for ubiquitous computing that such proposals might facilitate.

Fault detection and diagnosis using neural network approaches

NASA Technical Reports Server (NTRS)

Kramer, Mark A.

1992-01-01

Neural networks can be used to detect and identify abnormalities in real-time process data. Two basic approaches can be used, the first based on training networks using data representing both normal and abnormal modes of process behavior, and the second based on statistical characterization of the normal mode only. Given data representative of process faults, radial basis function networks can effectively identify failures. This approach is often limited by the lack of fault data, but can be facilitated by process simulation. The second approach employs elliptical and radial basis function neural networks and other models to learn the statistical distributions of process observables under normal conditions. Analytical models of failure modes can then be applied in combination with the neural network models to identify faults. Special methods can be applied to compensate for sensor failures, to produce real-time estimation of missing or failed sensors based on the correlations codified in the neural network.

Accelerator infrastructure in Europe: EuCARD 2011

NASA Astrophysics Data System (ADS)

Romaniuk, Ryszard S.

2011-10-01

The paper presents a digest of the research results in the domain of accelerator science and technology in Europe, shown during the annual meeting of the EuCARD - European Coordination of Accelerator Research and Development. The conference concerns building of the research infrastructure, including in this advanced photonic and electronic systems for servicing large high energy physics experiments. There are debated a few basic groups of such systems like: measurement - control networks of large geometrical extent, multichannel systems for large amounts of metrological data acquisition, precision photonic networks of reference time, frequency and phase distribution.

Polarization-interference Jones-matrix mapping of biological crystal networks

NASA Astrophysics Data System (ADS)

Ushenko, O. G.; Dubolazov, O. V.; Pidkamin, L. Y.; Sidor, M. I.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of Jones-matrix mapping with the help of reference wave. It was provided experimentally measured coordinate distributions of modulus of Jones-matrix elements of polycrystalline film of bile. It was defined the values and ranges of changing of statistic moments, which characterize such distributions. The second part presents the data of statistic analysis of the distributions of matrix elements of polycrystalline film of urine of donors and patients with albuminuria. It was defined the objective criteria of differentiation of albuminuria.

Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)

PubMed Central

Dowd, Scot E; Zaragoza, Joaquin; Rodriguez, Javier R; Oliver, Melvin J; Payton, Paxton R

2005-01-01

Background BLAST is one of the most common and useful tools for Genetic Research. This paper describes a software application we have termed Windows .NET Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST), which enhances the BLAST utility by improving usability, fault recovery, and scalability in a Windows desktop environment. Our goal was to develop an easy to use, fault tolerant, high-throughput BLAST solution that incorporates a comprehensive BLAST result viewer with curation and annotation functionality. Results W.ND-BLAST is a comprehensive Windows-based software toolkit that targets researchers, including those with minimal computer skills, and provides the ability increase the performance of BLAST by distributing BLAST queries to any number of Windows based machines across local area networks (LAN). W.ND-BLAST provides intuitive Graphic User Interfaces (GUI) for BLAST database creation, BLAST execution, BLAST output evaluation and BLAST result exportation. This software also provides several layers of fault tolerance and fault recovery to prevent loss of data if nodes or master machines fail. This paper lays out the functionality of W.ND-BLAST. W.ND-BLAST displays close to 100% performance efficiency when distributing tasks to 12 remote computers of the same performance class. A high throughput BLAST job which took 662.68 minutes (11 hours) on one average machine was completed in 44.97 minutes when distributed to 17 nodes, which included lower performance class machines. Finally, there is a comprehensive high-throughput BLAST Output Viewer (BOV) and Annotation Engine components, which provides comprehensive exportation of BLAST hits to text files, annotated fasta files, tables, or association files. Conclusion W.ND-BLAST provides an interactive tool that allows scientists to easily utilizing their available computing resources for high throughput and comprehensive sequence analyses. The install package for W.ND-BLAST is freely downloadable from . With registration the software is free, installation, networking, and usage instructions are provided as well as a support forum. PMID:15819992

Dynamic Changes in Amygdala Psychophysiological Connectivity Reveal Distinct Neural Networks for Facial Expressions of Basic Emotions.

PubMed

Diano, Matteo; Tamietto, Marco; Celeghin, Alessia; Weiskrantz, Lawrence; Tatu, Mona-Karina; Bagnis, Arianna; Duca, Sergio; Geminiani, Giuliano; Cauda, Franco; Costa, Tommaso

2017-03-27

The quest to characterize the neural signature distinctive of different basic emotions has recently come under renewed scrutiny. Here we investigated whether facial expressions of different basic emotions modulate the functional connectivity of the amygdala with the rest of the brain. To this end, we presented seventeen healthy participants (8 females) with facial expressions of anger, disgust, fear, happiness, sadness and emotional neutrality and analyzed amygdala's psychophysiological interaction (PPI). In fact, PPI can reveal how inter-regional amygdala communications change dynamically depending on perception of various emotional expressions to recruit different brain networks, compared to the functional interactions it entertains during perception of neutral expressions. We found that for each emotion the amygdala recruited a distinctive and spatially distributed set of structures to interact with. These changes in amygdala connectional patters characterize the dynamic signature prototypical of individual emotion processing, and seemingly represent a neural mechanism that serves to implement the distinctive influence that each emotion exerts on perceptual, cognitive, and motor responses. Besides these differences, all emotions enhanced amygdala functional integration with premotor cortices compared to neutral faces. The present findings thus concur to reconceptualise the structure-function relation between brain-emotion from the traditional one-to-one mapping toward a network-based and dynamic perspective.

Measuring Networking as an Outcome Variable in Undergraduate Research Experiences.

PubMed

Hanauer, David I; Hatfull, Graham

2015-01-01

The aim of this paper is to propose, present, and validate a simple survey instrument to measure student conversational networking. The tool consists of five items that cover personal and professional social networks, and its basic principle is the self-reporting of degrees of conversation, with a range of specific discussion partners. The networking instrument was validated in three studies. The basic psychometric characteristics of the scales were established by conducting a factor analysis and evaluating internal consistency using Cronbach's alpha. The second study used a known-groups comparison and involved comparing outcomes for networking scales between two different undergraduate laboratory courses (one involving a specific effort to enhance networking). The final study looked at potential relationships between specific networking items and the established psychosocial variable of project ownership through a series of binary logistic regressions. Overall, the data from the three studies indicate that the networking scales have high internal consistency (α = 0.88), consist of a unitary dimension, can significantly differentiate between research experiences with low and high networking designs, and are related to project ownership scales. The ramifications of the networking instrument for student retention, the enhancement of public scientific literacy, and the differentiation of laboratory courses are discussed. © 2015 D. I. Hanauer and G. Hatfull. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Genome-wide network of regulatory genes for construction of a chordate embryo.

PubMed

Shoguchi, Eiichi; Hamaguchi, Makoto; Satoh, Nori

2008-04-15

Animal development is controlled by gene regulation networks that are composed of sequence-specific transcription factors (TF) and cell signaling molecules (ST). Although housekeeping genes have been reported to show clustering in the animal genomes, whether the genes comprising a given regulatory network are physically clustered on a chromosome is uncertain. We examined this question in the present study. Ascidians are the closest living relatives of vertebrates, and their tadpole-type larva represents the basic body plan of chordates. The Ciona intestinalis genome contains 390 core TF genes and 119 major ST genes. Previous gene disruption assays led to the formulation of a basic chordate embryonic blueprint, based on over 3000 genetic interactions among 79 zygotic regulatory genes. Here, we mapped the regulatory genes, including all 79 regulatory genes, on the 14 pairs of Ciona chromosomes by fluorescent in situ hybridization (FISH). Chromosomal localization of upstream and downstream regulatory genes demonstrates that the components of coherent developmental gene networks are evenly distributed over the 14 chromosomes. Thus, this study provides the first comprehensive evidence that the physical clustering of regulatory genes, or their target genes, is not relevant for the genome-wide control of gene expression during development.

Modular decomposition of metabolic reaction networks based on flux analysis and pathway projection.

PubMed

Yoon, Jeongah; Si, Yaguang; Nolan, Ryan; Lee, Kyongbum

2007-09-15

The rational decomposition of biochemical networks into sub-structures has emerged as a useful approach to study the design of these complex systems. A biochemical network is characterized by an inhomogeneous connectivity distribution, which gives rise to several organizational features, including modularity. To what extent the connectivity-based modules reflect the functional organization of the network remains to be further explored. In this work, we examine the influence of physiological perturbations on the modular organization of cellular metabolism. Modules were characterized for two model systems, liver and adipocyte primary metabolism, by applying an algorithm for top-down partition of directed graphs with non-uniform edge weights. The weights were set by the engagement of the corresponding reactions as expressed by the flux distribution. For the base case of the fasted rat liver, three modules were found, carrying out the following biochemical transformations: ketone body production, glucose synthesis and transamination. This basic organization was further modified when different flux distributions were applied that describe the liver's metabolic response to whole body inflammation. For the fully mature adipocyte, only a single module was observed, integrating all of the major pathways needed for lipid storage. Weaker levels of integration between the pathways were found for the early stages of adipocyte differentiation. Our results underscore the inhomogeneous distribution of both connectivity and connection strengths, and suggest that global activity data such as the flux distribution can be used to study the organizational flexibility of cellular metabolism. Supplementary data are available at Bioinformatics online.

Role of Network Science in the Study of Anesthetic State Transitions.

PubMed

Lee, UnCheol; Mashour, George A

2018-04-23

The heterogeneity of molecular mechanisms, target neural circuits, and neurophysiologic effects of general anesthetics makes it difficult to develop a reliable and drug-invariant index of general anesthesia. No single brain region or mechanism has been identified as the neural correlate of consciousness, suggesting that consciousness might emerge through complex interactions of spatially and temporally distributed brain functions. The goal of this review article is to introduce the basic concepts of networks and explain why the application of network science to general anesthesia could be a pathway to discover a fundamental mechanism of anesthetic-induced unconsciousness. This article reviews data suggesting that reduced network efficiency, constrained network repertoires, and changes in cortical dynamics create inhospitable conditions for information processing and transfer, which lead to unconsciousness. This review proposes that network science is not just a useful tool but a necessary theoretical framework and method to uncover common principles of anesthetic-induced unconsciousness.

75 FR 65363 - Basic Behavioral and Social Science Opportunity Network (OppNet)

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-22

... public meeting to promote and publicize the Basic Behavioral and Social Science Opportunity Network (Opp... . Background: The Basic Behavioral and Social Science Opportunity Network (OppNet) is a trans-NIH initiative to expand the agency's funding of basic behavioral and social sciences research (b-BSSR). OppNet prioritizes...

Fisher's geometrical model emerges as a property of complex integrated phenotypic networks.

PubMed

Martin, Guillaume

2014-05-01

Models relating phenotype space to fitness (phenotype-fitness landscapes) have seen important developments recently. They can roughly be divided into mechanistic models (e.g., metabolic networks) and more heuristic models like Fisher's geometrical model. Each has its own drawbacks, but both yield testable predictions on how the context (genomic background or environment) affects the distribution of mutation effects on fitness and thus adaptation. Both have received some empirical validation. This article aims at bridging the gap between these approaches. A derivation of the Fisher model "from first principles" is proposed, where the basic assumptions emerge from a more general model, inspired by mechanistic networks. I start from a general phenotypic network relating unspecified phenotypic traits and fitness. A limited set of qualitative assumptions is then imposed, mostly corresponding to known features of phenotypic networks: a large set of traits is pleiotropically affected by mutations and determines a much smaller set of traits under optimizing selection. Otherwise, the model remains fairly general regarding the phenotypic processes involved or the distribution of mutation effects affecting the network. A statistical treatment and a local approximation close to a fitness optimum yield a landscape that is effectively the isotropic Fisher model or its extension with a single dominant phenotypic direction. The fit of the resulting alternative distributions is illustrated in an empirical data set. These results bear implications on the validity of Fisher's model's assumptions and on which features of mutation fitness effects may vary (or not) across genomic or environmental contexts.

Unattended network operations technology assessment study. Technical support for defining advanced satellite systems concepts

NASA Technical Reports Server (NTRS)

Price, Kent M.; Holdridge, Mark; Odubiyi, Jide; Jaworski, Allan; Morgan, Herbert K.

1991-01-01

The results are summarized of an unattended network operations technology assessment study for the Space Exploration Initiative (SEI). The scope of the work included: (1) identified possible enhancements due to the proposed Mars communications network; (2) identified network operations on Mars; (3) performed a technology assessment of possible supporting technologies based on current and future approaches to network operations; and (4) developed a plan for the testing and development of these technologies. The most important results obtained are as follows: (1) addition of a third Mars Relay Satellite (MRS) and MRS cross link capabilities will enhance the network's fault tolerance capabilities through improved connectivity; (2) network functions can be divided into the six basic ISO network functional groups; (3) distributed artificial intelligence technologies will augment more traditional network management technologies to form the technological infrastructure of a virtually unattended network; and (4) a great effort is required to bring the current network technology levels for manned space communications up to the level needed for an automated fault tolerance Mars communications network.

Distinct pathways of neural coupling for different basic emotions.

PubMed

Tettamanti, Marco; Rognoni, Elena; Cafiero, Riccardo; Costa, Tommaso; Galati, Dario; Perani, Daniela

2012-01-16

Emotions are complex events recruiting distributed cortical and subcortical cerebral structures, where the functional integration dynamics within the involved neural circuits in relation to the nature of the different emotions are still unknown. Using fMRI, we measured the neural responses elicited by films representing basic emotions (fear, disgust, sadness, happiness). The amygdala and the associative cortex were conjointly activated by all basic emotions. Furthermore, distinct arrays of cortical and subcortical brain regions were additionally activated by each emotion, with the exception of sadness. Such findings informed the definition of three effective connectivity models, testing for the functional integration of visual cortex and amygdala, as regions processing all emotions, with domain-specific regions, namely: i) for fear, the frontoparietal system involved in preparing adaptive motor responses; ii) for disgust, the somatosensory system, reflecting protective responses against contaminating stimuli; iii) for happiness: medial prefrontal and temporoparietal cortices involved in understanding joyful interactions. Consistently with these domain-specific models, the results of the effective connectivity analysis indicate that the amygdala is involved in distinct functional integration effects with cortical networks processing sensorimotor, somatosensory, or cognitive aspects of basic emotions. The resulting effective connectivity networks may serve to regulate motor and cognitive behavior based on the quality of the induced emotional experience. Copyright © 2011. Published by Elsevier Inc.

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.

«Smart Grid» Concept As A Modern Technology For The Power Industry Development

NASA Astrophysics Data System (ADS)

Vidyaev, Igor G.; Ivashutenko, Alexandr S.; Samburskaya, Maria A.

2017-01-01

The article discusses the main problems of the power industry and energy supply to the distribution networks. One of the suggested solutions for these problems is the use of intelligent energy networks on the basis of digital reality simulation, in particular, the concept of «SMART GRID». The article presents the basic points of the concept and the peculiarities of its application at the enterprises. It was demonstrated that the use of this technology eliminates power shortage, reduces the energy intensity and improves the energy efficiency throughout the operation of an enterprise as a whole.

A universal quantum information processor for scalable quantum communication and networks

PubMed Central

Yang, Xihua; Xue, Bolin; Zhang, Junxiang; Zhu, Shiyao

2014-01-01

Entanglement provides an essential resource for quantum computation, quantum communication, and quantum networks. How to conveniently and efficiently realize the generation, distribution, storage, retrieval, and control of multipartite entanglement is the basic requirement for realistic quantum information processing. Here, we present a theoretical proposal to efficiently and conveniently achieve a universal quantum information processor (QIP) via atomic coherence in an atomic ensemble. The atomic coherence, produced through electromagnetically induced transparency (EIT) in the Λ-type configuration, acts as the QIP and has full functions of quantum beam splitter, quantum frequency converter, quantum entangler, and quantum repeater. By employing EIT-based nondegenerate four-wave mixing processes, the generation, exchange, distribution, and manipulation of light-light, atom-light, and atom-atom multipartite entanglement can be efficiently and flexibly achieved in a deterministic way with only coherent light fields. This method greatly facilitates the operations in quantum information processing, and holds promising applications in realistic scalable quantum communication and quantum networks. PMID:25316514

Possible Brain Mechanisms of Creativity.

PubMed

Heilman, Kenneth M

2016-06-01

Creativity is the new discovery, understanding, development and expression of orderly and meaningful relationships. Creativity has three major stages: preparation, the development (nature and nurture) of critical knowledge and skills; innovation, the development of a creative solution; and creative production. Successful preparation requires a basic level of general intelligence and domain specific knowledge and skills and highly creative people may have anatomic alterations of specific neocortical regions. Innovation requires disengagement and divergent thinking primarily mediated by frontal networks. Creative people are often risk-takers and novelty seekers, behaviors that activate their ventral striatal reward system. Innovation also requires associative and convergent thinking, activities that are dependent on the integration of highly distributed networks. People are often most creative when they are in mental states associated with reduced levels of brain norepinephrine, which may enhance the communication between distributed networks. We, however, need to learn more about the brain mechanisms of creativity. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Modeling and dynamical topology properties of VANET based on complex networks theory

NASA Astrophysics Data System (ADS)

Zhang, Hong; Li, Jie

2015-01-01

Vehicular Ad hoc Network (VANET) is a special subset of multi-hop Mobile Ad hoc Networks in which vehicles can not only communicate with each other but also with the fixed equipments along the roads through wireless interfaces. Recently, it has been discovered that essential systems in real world share similar properties. When they are regarded as networks, among which the dynamic topology structure of VANET system is an important issue. Many real world networks are actually growing with preferential attachment like Internet, transportation system and telephone network. Those phenomena have brought great possibility in finding a strategy to calibrate and control the topology parameters which can help find VANET topology change regulation to relieve traffic jam, prevent traffic accident and improve traffic safety. VANET is a typical complex network which has its basic characteristics. In this paper, we focus on the macroscopic Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) inter-vehicle communication network with complex network theory. In particular, this paper is the first one to propose a method analyzing the topological structure and performance of VANET and present the communications in VANET from a new perspective. Accordingly, we propose degree distribution, clustering coefficient and the short path length of complex network to implement our strategy by numerical example and simulation. All the results demonstrate that VANET shows small world network features and is characterized by a truncated scale-free degree distribution with power-law degree distribution. The average path length of the network is simulated numerically, which indicates that the network shows small-world property and is rarely affected by the randomness. What's more, we carry out extensive simulations of information propagation and mathematically prove the power law property when γ > 2. The results of this study provide useful information for VANET optimization from a macroscopic perspective.

Modeling and dynamical topology properties of VANET based on complex networks theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Hong; Li, Jie, E-mail: prof.li@foxmail.com

2015-01-15

Vehicular Ad hoc Network (VANET) is a special subset of multi-hop Mobile Ad hoc Networks in which vehicles can not only communicate with each other but also with the fixed equipments along the roads through wireless interfaces. Recently, it has been discovered that essential systems in real world share similar properties. When they are regarded as networks, among which the dynamic topology structure of VANET system is an important issue. Many real world networks are actually growing with preferential attachment like Internet, transportation system and telephone network. Those phenomena have brought great possibility in finding a strategy to calibrate andmore » control the topology parameters which can help find VANET topology change regulation to relieve traffic jam, prevent traffic accident and improve traffic safety. VANET is a typical complex network which has its basic characteristics. In this paper, we focus on the macroscopic Vehicle-to-Infrastructure (V2I) and Vehicle-to-Vehicle (V2V) inter-vehicle communication network with complex network theory. In particular, this paper is the first one to propose a method analyzing the topological structure and performance of VANET and present the communications in VANET from a new perspective. Accordingly, we propose degree distribution, clustering coefficient and the short path length of complex network to implement our strategy by numerical example and simulation. All the results demonstrate that VANET shows small world network features and is characterized by a truncated scale-free degree distribution with power-law degree distribution. The average path length of the network is simulated numerically, which indicates that the network shows small-world property and is rarely affected by the randomness. What’s more, we carry out extensive simulations of information propagation and mathematically prove the power law property when γ > 2. The results of this study provide useful information for VANET optimization from a macroscopic perspective.« less

Statistical Analysis of Bus Networks in India

PubMed Central

2016-01-01

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

Limitations of demand- and pressure-driven modeling for large deficient networks

NASA Astrophysics Data System (ADS)

Braun, Mathias; Piller, Olivier; Deuerlein, Jochen; Mortazavi, Iraj

2017-10-01

The calculation of hydraulic state variables for a network is an important task in managing the distribution of potable water. Over the years the mathematical modeling process has been improved by numerous researchers for utilization in new computer applications and the more realistic modeling of water distribution networks. But, in spite of these continuous advances, there are still a number of physical phenomena that may not be tackled correctly by current models. This paper will take a closer look at the two modeling paradigms given by demand- and pressure-driven modeling. The basic equations are introduced and parallels are drawn with the optimization formulations from electrical engineering. These formulations guarantee the existence and uniqueness of the solution. One of the central questions of the French and German research project ResiWater is the investigation of the network resilience in the case of extreme events or disasters. Under such extraordinary conditions where models are pushed beyond their limits, we talk about deficient network models. Examples of deficient networks are given by highly regulated flow, leakage or pipe bursts and cases where pressure falls below the vapor pressure of water. These examples will be presented and analyzed on the solvability and physical correctness of the solution with respect to demand- and pressure-driven models.

A Computer Model of Insect Traps in a Landscape

NASA Astrophysics Data System (ADS)

Manoukis, Nicholas C.; Hall, Brian; Geib, Scott M.

2014-11-01

Attractant-based trap networks are important elements of invasive insect detection, pest control, and basic research programs. We present a landscape-level, spatially explicit model of trap networks, focused on detection, that incorporates variable attractiveness of traps and a movement model for insect dispersion. We describe the model and validate its behavior using field trap data on networks targeting two species, Ceratitis capitata and Anoplophora glabripennis. Our model will assist efforts to optimize trap networks by 1) introducing an accessible and realistic mathematical characterization of the operation of a single trap that lends itself easily to parametrization via field experiments and 2) allowing direct quantification and comparison of sensitivity between trap networks. Results from the two case studies indicate that the relationship between number of traps and their spatial distribution and capture probability under the model is qualitatively dependent on the attractiveness of the traps, a result with important practical consequences.

Body area network--a key infrastructure element for patient-centered telemedicine.

PubMed

Norgall, Thomas; Schmidt, Robert; von der Grün, Thomas

2004-01-01

The Body Area Network (BAN) extends the range of existing wireless network technologies by an ultra-low range, ultra-low power network solution optimised for long-term or continuous healthcare applications. It enables wireless radio communication between several miniaturised, intelligent Body Sensor (or actor) Units (BSU) and a single Body Central Unit (BCU) worn at the human body. A separate wireless transmission link from the BCU to a network access point--using different technology--provides for online access to BAN components via usual network infrastructure. The BAN network protocol maintains dynamic ad-hoc network configuration scenarios and co-existence of multiple networks.BAN is expected to become a basic infrastructure element for electronic health services: By integrating patient-attached sensors and mobile actor units, distributed information and data processing systems, the range of medical workflow can be extended to include applications like wireless multi-parameter patient monitoring and therapy support. Beyond clinical use and professional disease management environments, private personal health assistance scenarios (without financial reimbursement by health agencies / insurance companies) enable a wide range of applications and services in future pervasive computing and networking environments.

BOREAS AFM-5 Level-2 Upper Air Network Standard Pressure Level Data

NASA Technical Reports Server (NTRS)

Barr, Alan; Hrynkiw, Charmaine; Hall, Forrest G. (Editor); Newcomer, Jeffrey A. (Editor); Smith, David E. (Technical Monitor)

2000-01-01

The BOREAS AFM-5 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large-scale definition of the atmosphere by supplementing the existing AES aerological network, both temporally and spatially. This data set includes basic upper-air parameters interpolated at 0.5 kiloPascal increments of atmospheric pressure from data collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. The data are contained in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Robust and Cost-Efficient Communication Based on SNMP in Mobile Networks

NASA Astrophysics Data System (ADS)

Ryu, Sang-Hoon; Baik, Doo-Kwon

A main challenge in the design of this mobile network is the development of dynamic routing protocols that can efficiently find routes between two communicating nodes. Multimedia streaming services are receiving considerable interest in the mobile network business. An entire mobile network may change its point of attachment to the Internet. The mobile network is operated by a basic specification to support network mobility called Network Mobility (NEMO) Basic Support. However, NEMO basic Support mechanism has some problem in continuous communication. In this paper, we propose robust and cost-efficient algorithm. And we simulate proposed method and conclude some remarks.

New approaches to model and study social networks

NASA Astrophysics Data System (ADS)

Lind, P. G.; Herrmann, H. J.

2007-07-01

We describe and develop three recent novelties in network research which are particularly useful for studying social systems. The first one concerns the discovery of some basic dynamical laws that enable the emergence of the fundamental features observed in social networks, namely the nontrivial clustering properties, the existence of positive degree correlations and the subdivision into communities. To reproduce all these features, we describe a simple model of mobile colliding agents, whose collisions define the connections between the agents which are the nodes in the underlying network, and develop some analytical considerations. The second point addresses the particular feature of clustering and its relationship with global network measures, namely with the distribution of the size of cycles in the network. Since in social bipartite networks it is not possible to measure the clustering from standard procedures, we propose an alternative clustering coefficient that can be used to extract an improved normalized cycle distribution in any network. Finally, the third point addresses dynamical processes occurring on networks, namely when studying the propagation of information in them. In particular, we focus on the particular features of gossip propagation which impose some restrictions in the propagation rules. To this end we introduce a quantity, the spread factor, which measures the average maximal fraction of nearest neighbours which get in contact with the gossip, and find the striking result that there is an optimal non-trivial number of friends for which the spread factor is minimized, decreasing the danger of being gossiped about.

Optogenetic dissection reveals multiple rhythmogenic modules underlying locomotion

PubMed Central

Hägglund, Martin; Dougherty, Kimberly J.; Borgius, Lotta; Itohara, Shigeyoshi; Iwasato, Takuji; Kiehn, Ole

2013-01-01

Neural networks in the spinal cord known as central pattern generators produce the sequential activation of muscles needed for locomotion. The overall locomotor network architectures in limbed vertebrates have been much debated, and no consensus exists as to how they are structured. Here, we use optogenetics to dissect the excitatory and inhibitory neuronal populations and probe the organization of the mammalian central pattern generator. We find that locomotor-like rhythmic bursting can be induced unilaterally or independently in flexor or extensor networks. Furthermore, we show that individual flexor motor neuron pools can be recruited into bursting without any activity in other nearby flexor motor neuron pools. Our experiments differentiate among several proposed models for rhythm generation in the vertebrates and show that the basic structure underlying the locomotor network has a distributed organization with many intrinsically rhythmogenic modules. PMID:23798384

BOREAS AFM-5 Level-1 Upper Air Network Data

NASA Technical Reports Server (NTRS)

Barr, Alan; Hrynkiw, Charmaine; Newcomer, Jeffrey A. (Editor); Hall, Forrest G. (Editor); Smith, David E. (Technical Monitor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-5 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large-scale definition of the atmosphere by supplementing the existing Atmospheric Environment Service (AES) aerological network, both temporally and spatially. This data set includes basic upper-air parameters collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. The data are contained in tabular ASCII files. The level-1 upper-air network data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files also are available on a CD-ROM (see document number 20010000884).

3D Mueller-matrix mapping of biological optically anisotropic networks

NASA Astrophysics Data System (ADS)

Ushenko, O. G.; Ushenko, V. O.; Bodnar, G. B.; Zhytaryuk, V. G.; Prydiy, O. G.; Koval, G.; Lukashevich, I.; Vanchuliak, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of azimuthally-invariant Mueller-matrix description of optical anisotropy of biological tissues. It was provided experimentally measured coordinate distributions of Mueller-matrix invariants (MMI) of linear and circular birefringences of skeletal muscle tissue. It was defined the values of statistic moments, which characterize the distributions of amplitudes of wavelet coefficients of MMI at different scales of scanning. The second part presents the data of statistic analysis of the distributions of amplitude of wavelet coefficients of the distributions of linear birefringence of myocardium tissue died after the infarction and ischemic heart disease. It was defined the objective criteria of differentiation of the cause of death.

Multiscale polarization diagnostics of birefringent networks in problems of necrotic changes diagnostics

NASA Astrophysics Data System (ADS)

Sakhnovskiy, M. Yu.; Ushenko, Yu. O.; Ushenko, V. O.; Besaha, R. N.; Pavlyukovich, N.; Pavlyukovich, O.

2018-01-01

The paper consists of two parts. The first part presents short theoretical basics of the method of azimuthally-invariant Mueller-matrix description of optical anisotropy of biological tissues. It was provided experimentally measured coordinate distributions of Mueller-matrix invariants (MMI) of linear and circular birefringences of skeletal muscle tissue. It was defined the values of statistic moments, which characterize the distributions of amplitudes of wavelet coefficients of MMI at different scales of scanning. The second part presents the data of statistic analysis of the distributions of amplitude of wavelet coefficients of the distributions of linear birefringence of myocardium tissue died after the infarction and ischemic heart disease. It was defined the objective criteria of differentiation of the cause of death.

Including metabolite concentrations into flux balance analysis: thermodynamic realizability as a constraint on flux distributions in metabolic networks

PubMed Central

Hoppe, Andreas; Hoffmann, Sabrina; Holzhütter, Hermann-Georg

2007-01-01

Background In recent years, constrained optimization – usually referred to as flux balance analysis (FBA) – has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions. Results To augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of Escherichia coli (931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state. Conclusion Our method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered. PMID:17543097

Communication performance analysis and comparison of two patterns for data exchange between nodes in WorldFIP fieldbus network.

PubMed

Liang, Geng; Wang, Hong; Li, Wen; Li, Dazhong

2010-10-01

Data exchange patterns between nodes in WorldFIP fieldbus network are quite important and meaningful in improving the communication performance of WorldFIP network. Based on the basic communication ways supported in WorldFIP protocol, we propose two patterns for implementation of data exchange between peer nodes over WorldFIP network. Effects on communication performance of WorldFIP network in terms of some network parameters, such as number of bytes in user's data and turn-around time, in both the proposed patterns, are analyzed at length when different network speeds are applied. Such effects with the patterns of periodic message transmission using acknowledged and non-acknowledged messages, are also studied. Communication performance in both the proposed patterns are analyzed and compared. Practical applications of the research are presented. Through the study, it can be seen that different data exchange patterns make a great difference in improving communication efficiency with different network parameters, which is quite useful and helpful in the practical design of distributed systems based on WorldFIP network. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

A comparative study of deep learning models for medical image classification

NASA Astrophysics Data System (ADS)

Dutta, Suvajit; Manideep, B. C. S.; Rai, Shalva; Vijayarajan, V.

2017-11-01

Deep Learning(DL) techniques are conquering over the prevailing traditional approaches of neural network, when it comes to the huge amount of dataset, applications requiring complex functions demanding increase accuracy with lower time complexities. Neurosciences has already exploited DL techniques, thus portrayed itself as an inspirational source for researchers exploring the domain of Machine learning. DL enthusiasts cover the areas of vision, speech recognition, motion planning and NLP as well, moving back and forth among fields. This concerns with building models that can successfully solve variety of tasks requiring intelligence and distributed representation. The accessibility to faster CPUs, introduction of GPUs-performing complex vector and matrix computations, supported agile connectivity to network. Enhanced software infrastructures for distributed computing worked in strengthening the thought that made researchers suffice DL methodologies. The paper emphases on the following DL procedures to traditional approaches which are performed manually for classifying medical images. The medical images are used for the study Diabetic Retinopathy(DR) and computed tomography (CT) emphysema data. Both DR and CT data diagnosis is difficult task for normal image classification methods. The initial work was carried out with basic image processing along with K-means clustering for identification of image severity levels. After determining image severity levels ANN has been applied on the data to get the basic classification result, then it is compared with the result of DNNs (Deep Neural Networks), which performed efficiently because of its multiple hidden layer features basically which increases accuracy factors, but the problem of vanishing gradient in DNNs made to consider Convolution Neural Networks (CNNs) as well for better results. The CNNs are found to be providing better outcomes when compared to other learning models aimed at classification of images. CNNs are favoured as they provide better visual processing models successfully classifying the noisy data as well. The work centres on the detection on Diabetic Retinopathy-loss in vision and recognition of computed tomography (CT) emphysema data measuring the severity levels for both cases. The paper discovers how various Machine Learning algorithms can be implemented ensuing a supervised approach, so as to get accurate results with less complexity possible.

Optical interconnection and packaging technologies for advanced avionics systems

NASA Astrophysics Data System (ADS)

Schroeder, J. E.; Christian, N. L.; Cotti, B.

1992-09-01

An optical backplane developed to demonstrate the advantages of high-performance optical interconnections and supporting technologies and designed to be compatible with standard avionics racks is described. The hardware demonstrates the three basic components of optical interconnects: optical sources, an optical signal distribution network, and optical receivers. Results from characterization and environmental tests, including a demonstration of the reliable transmission of serial data at a 1 Gb/s, are reported.

Methodology development for quantitative optimization of security enhancement in medical information systems -Case study in a PACS and a multi-institutional radiotherapy database-.

PubMed

Haneda, Kiyofumi; Umeda, Tokuo; Koyama, Tadashi; Harauchi, Hajime; Inamura, Kiyonari

2002-01-01

The target of our study is to establish the methodology for analyzing level of security requirements, for searching suitable security measures and for optimizing security distribution to every portion of medical practice. Quantitative expression must be introduced to our study as possible for the purpose of easy follow up of security procedures and easy evaluation of security outcomes or results. Results of system analysis by fault tree analysis (FTA) clarified that subdivided system elements in detail contribute to much more accurate analysis. Such subdivided composition factors very much depended on behavior of staff, interactive terminal devices, kinds of service, and routes of network. As conclusion, we found the methods to analyze levels of security requirements for each medical information systems employing FTA, basic events for each composition factor and combination of basic events. Methods for searching suitable security measures were found. Namely risk factors for each basic event, number of elements for each composition factor and candidates of security measure elements were found. Method to optimize the security measures for each medical information system was proposed. Namely optimum distribution of risk factors in terms of basic events were figured out, and comparison of them between each medical information systems became possible.

A simple model of bipartite cooperation for ecological and organizational networks.

PubMed

Saavedra, Serguei; Reed-Tsochas, Felix; Uzzi, Brian

2009-01-22

In theoretical ecology, simple stochastic models that satisfy two basic conditions about the distribution of niche values and feeding ranges have proved successful in reproducing the overall structural properties of real food webs, using species richness and connectance as the only input parameters. Recently, more detailed models have incorporated higher levels of constraint in order to reproduce the actual links observed in real food webs. Here, building on previous stochastic models of consumer-resource interactions between species, we propose a highly parsimonious model that can reproduce the overall bipartite structure of cooperative partner-partner interactions, as exemplified by plant-animal mutualistic networks. Our stochastic model of bipartite cooperation uses simple specialization and interaction rules, and only requires three empirical input parameters. We test the bipartite cooperation model on ten large pollination data sets that have been compiled in the literature, and find that it successfully replicates the degree distribution, nestedness and modularity of the empirical networks. These properties are regarded as key to understanding cooperation in mutualistic networks. We also apply our model to an extensive data set of two classes of company engaged in joint production in the garment industry. Using the same metrics, we find that the network of manufacturer-contractor interactions exhibits similar structural patterns to plant-animal pollination networks. This surprising correspondence between ecological and organizational networks suggests that the simple rules of cooperation that generate bipartite networks may be generic, and could prove relevant in many different domains, ranging from biological systems to human society.

BOREAS AFM-04 Twin Otter Aircraft Flux Data

NASA Technical Reports Server (NTRS)

MacPherson, J. Ian; Hall, Forrest G. (Editor); Knapp, David E. (Editor); Desjardins, Raymond L.; Smith, David E. (Technical Monitor)

2000-01-01

The BOREAS AFM-5 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large-scale definition of the atmosphere by supplementing the existing AES aerological network, both temporally and spatially. This data set includes basic upper-air parameters collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. The data are contained in tabular ASCII files. The data files are available on a CD-ROM (see document number 20010000884) or from the Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC).

Distributed network management in the flat structured mobile communities

NASA Astrophysics Data System (ADS)

Balandina, Elena

2005-10-01

Delivering proper management into the flat structured mobile communities is crucial for improving users experience and increase applications diversity in mobile networks. The available P2P applications do application-centric management, but it cannot replace network-wide management, especially when a number of different applications are used simultaneously in the network. The network-wide management is the key element required for a smooth transition from standalone P2P applications to the self-organizing mobile communities that maintain various services with quality and security guaranties. The classical centralized network management solutions are not applicable in the flat structured mobile communities due to the decentralized nature and high mobility of the underlying networks. Also the basic network management tasks have to be revised taking into account specialties of the flat structured mobile communities. The network performance management becomes more dependent on the current nodes' context, which also requires extension of the configuration management functionality. The fault management has to take into account high mobility of the network nodes. The performance and accounting managements are mainly targeted in maintain an efficient and fair access to the resources within the community, however they also allow unbalanced resource use of the nodes that explicitly permit it, e.g. as a voluntary donation to the community or due to the profession (commercial) reasons. The security management must implement the new trust models, which are based on the community feedback, professional authorization, and a mix of both. For fulfilling these and another specialties of the flat structured mobile communities, a new network management solution is demanded. The paper presents a distributed network management solution for flat structured mobile communities. Also the paper points out possible network management roles for the different parties (e.g. operators, service providing hubs/super nodes, etc.) involved in a service providing chain.

Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment

PubMed Central

Legenstein, Robert; Maass, Wolfgang

2014-01-01

It has recently been shown that networks of spiking neurons with noise can emulate simple forms of probabilistic inference through “neural sampling”, i.e., by treating spikes as samples from a probability distribution of network states that is encoded in the network. Deficiencies of the existing model are its reliance on single neurons for sampling from each random variable, and the resulting limitation in representing quickly varying probabilistic information. We show that both deficiencies can be overcome by moving to a biologically more realistic encoding of each salient random variable through the stochastic firing activity of an ensemble of neurons. The resulting model demonstrates that networks of spiking neurons with noise can easily track and carry out basic computational operations on rapidly varying probability distributions, such as the odds of getting rewarded for a specific behavior. We demonstrate the viability of this new approach towards neural coding and computation, which makes use of the inherent parallelism of generic neural circuits, by showing that this model can explain experimentally observed firing activity of cortical neurons for a variety of tasks that require rapid temporal integration of sensory information. PMID:25340749

Research on NGN network control technology

NASA Astrophysics Data System (ADS)

Li, WenYao; Zhou, Fang; Wu, JianXue; Li, ZhiGuang

2004-04-01

Nowadays NGN (Next Generation Network) is the hotspot for discussion and research in IT section. The NGN core technology is the network control technology. The key goal of NGN is to realize the network convergence and evolution. Referring to overlay network model core on Softswitch technology, circuit switch network and IP network convergence realized. Referring to the optical transmission network core on ASTN/ASON, service layer (i.e. IP layer) and optical transmission convergence realized. Together with the distributing feature of NGN network control technology, on NGN platform, overview of combining Softswitch and ASTN/ASON control technology, the solution whether IP should be the NGN core carrier platform attracts general attention, and this is also a QoS problem on NGN end to end. This solution produces the significant practical meaning on equipment development, network deployment, network design and optimization, especially on realizing present network smooth evolving to the NGN. This is why this paper puts forward the research topic on the NGN network control technology. This paper introduces basics on NGN network control technology, then proposes NGN network control reference model, at the same time describes a realizable network structure of NGN. Based on above, from the view of function realization, NGN network control technology is discussed and its work mechanism is analyzed.

Internal services simulation control in 220/110kV power transformer station Mintia

NASA Astrophysics Data System (ADS)

Ciulica, D.; Rob, R.

2018-01-01

The main objectives in developing the electric transport and distribution networks infrastructure are satisfying the electric energy demand, ensuring the continuity of supply to customers, minimizing electricity losses in the transmission and distribution networks of public interest. This paper presents simulations in functioning of the internal services system 400/230 V ac in the 220/110 kV power transformer station Mintia. Using simulations in Visual Basic, the following premises are taken into consideration. All the ac consumers of the 220/110 kV power transformer station Mintia will be supplied by three 400/230 V transformers for internal services which can mutual reserve. In case of damaging at one transformer, the others are able to assume the entire consumption using automatic release of reserves. The simulation program studies three variants in which the continuity of supply to customers are ensured. As well, by simulations, all the functioning situations are analyzed in detail.

Living on the edge of chaos: minimally nonlinear models of genetic regulatory dynamics.

PubMed

Hanel, Rudolf; Pöchacker, Manfred; Thurner, Stefan

2010-12-28

Linearized catalytic reaction equations (modelling, for example, the dynamics of genetic regulatory networks), under the constraint that expression levels, i.e. molecular concentrations of nucleic material, are positive, exhibit non-trivial dynamical properties, which depend on the average connectivity of the reaction network. In these systems, an inflation of the edge of chaos and multi-stability have been demonstrated to exist. The positivity constraint introduces a nonlinearity, which makes chaotic dynamics possible. Despite the simplicity of such minimally nonlinear systems, their basic properties allow us to understand the fundamental dynamical properties of complex biological reaction networks. We analyse the Lyapunov spectrum, determine the probability of finding stationary oscillating solutions, demonstrate the effect of the nonlinearity on the effective in- and out-degree of the active interaction network, and study how the frequency distributions of oscillatory modes of such a system depend on the average connectivity.

Modelling students' knowledge organisation: Genealogical conceptual networks

NASA Astrophysics Data System (ADS)

Koponen, Ismo T.; Nousiainen, Maija

2018-04-01

Learning scientific knowledge is largely based on understanding what are its key concepts and how they are related. The relational structure of concepts also affects how concepts are introduced in teaching scientific knowledge. We model here how students organise their knowledge when they represent their understanding of how physics concepts are related. The model is based on assumptions that students use simple basic linking-motifs in introducing new concepts and mostly relate them to concepts that were introduced a few steps earlier, i.e. following a genealogical ordering. The resulting genealogical networks have relatively high local clustering coefficients of nodes but otherwise resemble networks obtained with an identical degree distribution of nodes but with random linking between them (i.e. the configuration-model). However, a few key nodes having a special structural role emerge and these nodes have a higher than average communicability betweenness centralities. These features agree with the empirically found properties of students' concept networks.

Self-organization in Balanced State Networks by STDP and Homeostatic Plasticity

PubMed Central

Effenberger, Felix; Jost, Jürgen; Levina, Anna

2015-01-01

Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a balanced neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network. PMID:26335425

Road screening and distribution route multi-objective robust optimization for hazardous materials based on neural network and genetic algorithm.

PubMed

Ma, Changxi; Hao, Wei; Pan, Fuquan; Xiang, Wang

2018-01-01

Route optimization of hazardous materials transportation is one of the basic steps in ensuring the safety of hazardous materials transportation. The optimization scheme may be a security risk if road screening is not completed before the distribution route is optimized. For road screening issues of hazardous materials transportation, a road screening algorithm of hazardous materials transportation is built based on genetic algorithm and Levenberg-Marquardt neural network (GA-LM-NN) by analyzing 15 attributes data of each road network section. A multi-objective robust optimization model with adjustable robustness is constructed for the hazardous materials transportation problem of single distribution center to minimize transportation risk and time. A multi-objective genetic algorithm is designed to solve the problem according to the characteristics of the model. The algorithm uses an improved strategy to complete the selection operation, applies partial matching cross shift and single ortho swap methods to complete the crossover and mutation operation, and employs an exclusive method to construct Pareto optimal solutions. Studies show that the sets of hazardous materials transportation road can be found quickly through the proposed road screening algorithm based on GA-LM-NN, whereas the distribution route Pareto solutions with different levels of robustness can be found rapidly through the proposed multi-objective robust optimization model and algorithm.

Impact of uniform electrode current distribution on ETF. [Engineering Test Facility MHD generator

NASA Technical Reports Server (NTRS)

Bents, D. J.

1982-01-01

A basic reason for the complexity and sheer volume of electrode consolidation hardware in the MHD ETF Powertrain system is the channel electrode current distribution, which is non-uniform. If the channel design is altered to provide uniform electrode current distribution, the amount of hardware required decreases considerably, but at the possible expense of degraded channel performance. This paper explains the design impacts on the ETF electrode consolidation network associated with uniform channel electrode current distribution, and presents the alternate consolidation designs which occur. They are compared to the baseline (non-uniform current) design with respect to performance, and hardware requirements. A rational basis is presented for comparing the requirements for the different designs and the savings that result from uniform current distribution. Performance and cost impacts upon the combined cycle plant are discussed.

Natural Gas Basics

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

2016-06-08

Natural gas powers about 150,000 vehicles in the United States and roughly 22 million vehicles worldwide. Natural gas vehicles (NGVs) are a good choice for high-mileage fleets -- such as buses, taxis, and refuse vehicles -- that are centrally fueled or operate within a limited area or along a route with natural gas fueling stations. This brochure highlights the advantages of natural gas as an alternative fuel, including its domestic availability, established distribution network, relatively low cost, and emissions benefits.

Natural Gas Basics

DOE Office of Scientific and Technical Information (OSTI.GOV)

2016-06-01

Natural gas powers about 150,000 vehicles in the United States and roughly 22 million vehicles worldwide. Natural gas vehicles (NGVs) are a good choice for high-mileage fleets -- such as buses, taxis, and refuse vehicles -- that are centrally fueled or operate within a limited area or along a route with natural gas fueling stations. This brochure highlights the advantages of natural gas as an alternative fuel, including its domestic availability, established distribution network, relatively low cost, and emissions benefits.

Synchrony-optimized networks of Kuramoto oscillators with inertia

NASA Astrophysics Data System (ADS)

Pinto, Rafael S.; Saa, Alberto

2016-12-01

We investigate synchronization in networks of Kuramoto oscillators with inertia. More specifically, we introduce a rewiring algorithm consisting basically in a hill climb scheme in which the edges of the network are swapped in order to enhance its synchronization capacity. We show that the synchrony-optimized networks generated by our algorithm have some interesting topological and dynamical properties. In particular, they typically exhibit an anticipation of the synchronization onset and are more robust against certain types of perturbations. We consider synthetic random networks and also a network with a topology based on an approximated model of the (high voltage) power grid of Spain, since networks of Kuramoto oscillators with inertia have been used recently as simplified models for power grids, for which synchronization is obviously a crucial issue. Despite the extreme simplifications adopted in these models, our results, among others recently obtained in the literature, may provide interesting principles to guide the future growth and development of real-world grids, specially in the case of a change of the current paradigm of centralized towards distributed generation power grids.

Control networks and hubs.

PubMed

Gratton, Caterina; Sun, Haoxin; Petersen, Steven E

2018-03-01

Executive control functions are associated with frontal, parietal, cingulate, and insular brain regions that interact through distributed large-scale networks. Here, we discuss how fMRI functional connectivity can shed light on the organization of control networks and how they interact with other parts of the brain. In the first section of our review, we present convergent evidence from fMRI functional connectivity, activation, and lesion studies that there are multiple dissociable control networks in the brain with distinct functional properties. In the second section, we discuss how graph theoretical concepts can help illuminate the mechanisms by which control networks interact with other brain regions to carry out goal-directed functions, focusing on the role of specialized hub regions for mediating cross-network interactions. Again, we use a combination of functional connectivity, lesion, and task activation studies to bolster this claim. We conclude that a large-scale network perspective provides important neurobiological constraints on the neural underpinnings of executive control, which will guide future basic and translational research into executive function and its disruption in disease. © 2017 Society for Psychophysiological Research.

Design of the National Trends Network for monitoring the chemistry of atmospheric precipitation

USGS Publications Warehouse

Robertson, J.K.; Wilson, J.W.

1985-01-01

Long-term monitoring (10 years minimum) of the chemistry of wet deposition will be conducted at National Trends Network (NTN) sites across the United States. Precipitation samples will be collected at sites that represent broad regional characteristics. Design of the NTN considered four basic elements during construction of a model to distribute 50, 75, 100, 125 or 150 sites. The modeling oriented design was supplemented with guidance developed during the course of the site selection process. Ultimately, a network of 151 sites was proposed. The basic elements of the design are: (1) Assurance that all areas of the country are represented in the network on the basis of regional ecological properties (96 sites); (2) Placement of additional sites east of the Rocky Mountains to better define high deposition gradients (27 sites); (3) Placement of sites to assure that potentially sensitive regions are represented (15 sites); (4) Placement of sites to allow for other considerations, such as urban area effects (5 sites), intercomparison with Canada (3 sites), and apparent disparities in regional coverage (5 sites). Site selection stressed areas away from urban centers, large point sources, or ocean influences. Local factors, such as stable land ownership, nearby small emission sources (about 10 km), and close-by roads and fireplaces (about 0.5 km) were also considered. All proposed sites will be visited as part of the second phase of the study.

On Learning Cluster Coefficient of Private Networks

PubMed Central

Wang, Yue; Wu, Xintao; Zhu, Jun; Xiang, Yang

2013-01-01

Enabling accurate analysis of social network data while preserving differential privacy has been challenging since graph features such as clustering coefficient or modularity often have high sensitivity, which is different from traditional aggregate functions (e.g., count and sum) on tabular data. In this paper, we treat a graph statistics as a function f and develop a divide and conquer approach to enforce differential privacy. The basic procedure of this approach is to first decompose the target computation f into several less complex unit computations f1, …, fm connected by basic mathematical operations (e.g., addition, subtraction, multiplication, division), then perturb the output of each fi with Laplace noise derived from its own sensitivity value and the distributed privacy threshold εi, and finally combine those perturbed fi as the perturbed output of computation f. We examine how various operations affect the accuracy of complex computations. When unit computations have large global sensitivity values, we enforce the differential privacy by calibrating noise based on the smooth sensitivity, rather than the global sensitivity. By doing this, we achieve the strict differential privacy guarantee with smaller magnitude noise. We illustrate our approach by using clustering coefficient, which is a popular statistics used in social network analysis. Empirical evaluations on five real social networks and various synthetic graphs generated from three random graph models show the developed divide and conquer approach outperforms the direct approach. PMID:24429843

Space industrialization - Education. [via communication satellites

NASA Technical Reports Server (NTRS)

Joels, K. M.

1978-01-01

The components of an educational system based on, and perhaps enhanced by, space industrialization communications technology are considered. Satellite technology has introduced a synoptic distribution system for various transmittable educational media. The cost of communications satellite distribution for educational programming has been high. It has, therefore, been proposed to utilize Space Shuttle related technology and Large Space Structures (LSS) to construct a system with a quantum advancement in communication capability and a quantum reduction in user cost. LSS for communications purposes have three basic advantages for both developed and emerging nations, including the ability to distribute signals over wide geographic areas, the reduced cost of satellite communications systems versus installation of land based systems, and the ability of a communication satellite system to create instant educational networks.

Stream Width Dynamics in a Small Headwater Catchment

NASA Astrophysics Data System (ADS)

Barefoot, E. A.; Pavelsky, T.; Allen, G. H.; Zimmer, M. A.; McGlynn, B. L.

2016-12-01

Changing streamflow conditions cause small, ephemeral and intermittent stream networks to expand and contract, while simultaneously driving widening and narrowing of streams. The resulting dynamic surface area of ephemeral streams impacts critical hydrological and biogeochemical processes, including air-water gas exchange, solute transport, and sediment transport. Despite the importance of these dynamics, to our knowledge there exists no complete study of how stream widths vary throughout an entire catchment in response to changing streamflow conditions. Here we present the first characterization of how variable hydrologic conditions impact the distribution of stream widths in a 48 ha headwater catchment in the Stony Creek Research Watershed, NC, USA. We surveyed stream widths longitudinally every 5 m on 12 occasions over a range of stream discharge from 7 L/s to 128 L/s at the catchment outlet. We hypothesize that the shape and location of the stream width distribution are driven by the action of two interrelated mechanisms, network extension and at-a-station widening, both of which increase with discharge. We observe that during very low flow conditions, network extension more significantly influences distribution location, and during high flow conditions stream widening is the dominant driver. During moderate flows, we observe an approximately 1 cm rightward shift in the distribution peak with every additional 10 L/s of increased discharge, which we attribute to a greater impact of at-a-station widening on distribution location. Aside from this small shift, the qualitative location and shape of the stream width distribution are largely invariant with changing streamflow. We suggest that the basic characteristics of stream width distributions constitute an equilibrium between the two described mechanisms across variable hydrologic conditions.

A universal quantum module for quantum communication, computation, and metrology

NASA Astrophysics Data System (ADS)

Hanks, Michael; Lo Piparo, Nicolò; Trupke, Michael; Schmiedmayer, Jorg; Munro, William J.; Nemoto, Kae

2017-08-01

In this work, we describe a simple module that could be ubiquitous for quantum information based applications. The basic modules comprises a single NV- center in diamond embedded in an optical cavity, where the cavity mediates interactions between photons and the electron spin (enabling entanglement distribution and efficient readout), while the nuclear spins constitutes a long-lived quantum memories capable of storing and processing quantum information. We discuss how a network of connected modules can be used for distributed metrology, communication and computation applications. Finally, we investigate the possible use of alternative diamond centers (SiV/GeV) within the module and illustrate potential advantages.

Dexmedetomidine Disrupts the Local and Global Efficiencies of Large-scale Brain Networks.

PubMed

Hashmi, Javeria A; Loggia, Marco L; Khan, Sheraz; Gao, Lei; Kim, Jieun; Napadow, Vitaly; Brown, Emery N; Akeju, Oluwaseun

2017-03-01

A clear understanding of the neural basis of consciousness is fundamental to research in clinical and basic neuroscience disciplines and anesthesia. Recently, decreased efficiency of information integration was suggested as a core network feature of propofol-induced unconsciousness. However, it is unclear whether this finding can be generalized to dexmedetomidine, which has a different molecular target. Dexmedetomidine was administered as a 1-μg/kg bolus over 10 min, followed by a 0.7-μg · kg · h infusion to healthy human volunteers (age range, 18 to 36 yr; n = 15). Resting-state functional magnetic resonance imaging data were acquired during baseline, dexmedetomidine-induced altered arousal, and recovery states. Zero-lag correlations between resting-state functional magnetic resonance imaging signals extracted from 131 brain parcellations were used to construct weighted brain networks. Network efficiency, degree distribution, and node strength were computed using graph analysis. Parcellated brain regions were also mapped to known resting-state networks to study functional connectivity changes. Dexmedetomidine significantly reduced the local and global efficiencies of graph theory-derived networks. Dexmedetomidine also reduced the average brain connectivity strength without impairing the degree distribution. Functional connectivity within and between all resting-state networks was modulated by dexmedetomidine. Dexmedetomidine is associated with a significant drop in the capacity for efficient information transmission at both the local and global levels. These changes result from reductions in the strength of connectivity and also manifest as reduced within and between resting-state network connectivity. These findings strengthen the hypothesis that conscious processing relies on an efficient system of information transfer in the brain.

An Overview of the CERC ARTEMIS Project

PubMed Central

Jagannathan, V.; Reddy, Y. V.; Srinivas, K.; Karinthi, R.; Shank, R.; Reddy, S.; Almasi, G.; Davis, T.; Raman, R.; Qiu, S.; Friedman, S.; Merkin, B.; Kilkenny, M.

1995-01-01

The basic premise of this effort is that health care can be made more effective and affordable by applying modern computer technology to improve collaboration among diverse and distributed health care providers. Information sharing, communication, and coordination are basic elements of any collaborative endeavor. In the health care domain, collaboration is characterized by cooperative activities by health care providers to deliver total and real-time care for their patients. Communication between providers and managed access to distributed patient records should enable health care providers to make informed decisions about their patients in a timely manner. With an effective medical information infrastructure in place, a patient will be able to visit any health care provider with access to the network, and the provider will be able to use relevant information from even the last episode of care in the patient record. Such a patient-centered perspective is in keeping with the real mission of health care providers. Today, an easy-to-use, integrated health care network is not in place in any community, even though current technology makes such a network possible. Large health care systems have deployed partial and disparate systems that address different elements of collaboration. But these islands of automation have not been integrated to facilitate cooperation among health care providers in large communities or nationally. CERC and its team members at Valley Health Systems, Inc., St. Marys Hospital and Cabell Huntington Hospital form a consortium committed to improving collaboration among the diverse and distributed providers in the health care arena. As the first contract recipient of the multi-agency High Performance Computing and Communications (HPCC) Initiative, this team of computer system developers, practicing rural physicians, community care groups, health care researchers, and tertiary care providers are using research prototypes and commercial off-the-shelf technologies to develop an open collaboration environment for the health care domain. This environment is called ARTEMIS — Advanced Research TEstbed for Medical InformaticS. PMID:8563249

Laser SRS tracker for reverse prototyping tasks

NASA Astrophysics Data System (ADS)

Kolmakov, Egor; Redka, Dmitriy; Grishkanich, Aleksandr; Tsvetkov, Konstantin

2017-10-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of chip and microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

Practice brief. Securing wireless technology for healthcare.

PubMed

Retterer, John; Casto, Brian W

2004-05-01

Wireless networking can be a very complex science, requiring an understanding of physics and the electromagnetic spectrum. While the radio theory behind the technology can be challenging, a basic understanding of wireless networking can be sufficient for small-scale deployment. Numerous security mechanisms are available to wireless technologies, making it practical, scalable, and affordable for healthcare organizations. The decision on the selected security model should take into account the needs for additional server hardware and administrative costs. Where wide area network connections exist between cooperative organizations, deployment of a distributed security model can be considered to reduce administrative overhead. The wireless approach chosen should be dynamic and concentrate on the organization's specific environmental needs. Aspects of organizational mission, operations, service level, and budget allotment as well as an organization's risk tolerance are all part of the balance in the decision to deploy wireless technology.

Hotspots for allosteric regulation on protein surfaces

PubMed Central

Reynolds, Kimberly A.; McLaughlin, Richard N.; Ranganathan, Rama

2012-01-01

Recent work indicates a general architecture for proteins in which sparse networks of physically contiguous and co-evolving amino acids underlie basic aspects of structure and function. These networks, termed sectors, are spatially organized such that active sites are linked to many surface sites distributed throughout the structure. Using the metabolic enzyme dihydrofolate reductase as a model system, we show that (1) the sector is strongly correlated to a network of residues undergoing millisecond conformational fluctuations associated with enzyme catalysis and (2) sector-connected surface sites are statistically preferred locations for the emergence of allosteric control in vivo. Thus, sectors represent an evolutionarily conserved “wiring” mechanism that can enable perturbations at specific surface positions to rapidly initiate conformational control over protein function. These findings suggest that sectors enable the evolution of intermolecular communication and regulation. PMID:22196731

The high speed interconnect system architecture and operation

NASA Astrophysics Data System (ADS)

Anderson, Steven C.

The design and operation of a fiber-optic high-speed interconnect system (HSIS) being developed to meet the requirements of future avionics and flight-control hardware with distributed-system architectures are discussed. The HSIS is intended for 100-Mb/s operation of a local-area network with up to 256 stations. It comprises a bus transmission system (passive star couplers and linear media linked by active elements) and network interface units (NIUs). Each NIU is designed to perform the physical, data link, network, and transport functions defined by the ISO OSI Basic Reference Model (1982 and 1983) and incorporates a fiber-optic transceiver, a high-speed protocol based on the SAE AE-9B linear token-passing data bus (1986), and a specialized application interface unit. The operating modes and capabilities of HSIS are described in detail and illustrated with diagrams.

A Multi Agent System for Flow-Based Intrusion Detection Using Reputation and Evolutionary Computation

DTIC Science & Technology

2011-03-01

the actions of malicious and benign users of the Internet, as well as the engi- neering decisions giving rise to observed network topologies. Say and...with resilience, which is particularly important in the domain of quickly-evolving cyber threats. “Self-organization,” says Meadows, “is basically the...system design paradigm is to leverage the advantages of a distributed approach? What is meant by saying the witness conceptually rates the target

Extraction of drainage networks from large terrain datasets using high throughput computing

NASA Astrophysics Data System (ADS)

Gong, Jianya; Xie, Jibo

2009-02-01

Advanced digital photogrammetry and remote sensing technology produces large terrain datasets (LTD). How to process and use these LTD has become a big challenge for GIS users. Extracting drainage networks, which are basic for hydrological applications, from LTD is one of the typical applications of digital terrain analysis (DTA) in geographical information applications. Existing serial drainage algorithms cannot deal with large data volumes in a timely fashion, and few GIS platforms can process LTD beyond the GB size. High throughput computing (HTC), a distributed parallel computing mode, is proposed to improve the efficiency of drainage networks extraction from LTD. Drainage network extraction using HTC involves two key issues: (1) how to decompose the large DEM datasets into independent computing units and (2) how to merge the separate outputs into a final result. A new decomposition method is presented in which the large datasets are partitioned into independent computing units using natural watershed boundaries instead of using regular 1-dimensional (strip-wise) and 2-dimensional (block-wise) decomposition. Because the distribution of drainage networks is strongly related to watershed boundaries, the new decomposition method is more effective and natural. The method to extract natural watershed boundaries was improved by using multi-scale DEMs instead of single-scale DEMs. A HTC environment is employed to test the proposed methods with real datasets.

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

NASA Astrophysics Data System (ADS)

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

2013-10-01

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

Two-Point Resistance of a Non-Regular Cylindrical Network with a Zero Resistor Axis and Two Arbitrary Boundaries

NASA Astrophysics Data System (ADS)

Tan, Zhi-Zhong

2017-03-01

We study a problem of two-point resistance in a non-regular m × n cylindrical network with a zero resistor axis and two arbitrary boundaries by means of the Recursion-Transform method. This is a new problem never solved before, the Green’s function technique and the Laplacian matrix approach are invalid in this case. A disordered network with arbitrary boundaries is a basic model in many physical systems or real world systems, however looking for the exact calculation of the resistance of a binary resistor network is important but difficult in the case of the arbitrary boundaries, the boundary is like a wall or trap which affects the behavior of finite network. In this paper we obtain a general resistance formula of a non-regular m × n cylindrical network, which is composed of a single summation. Further, the current distribution is given explicitly as a byproduct of the method. As applications, several interesting results are derived by making special cases from the general formula. Supported by the Natural Science Foundation of Jiangsu Province under Grant No. BK20161278

Network analysis for a network disorder: The emerging role of graph theory in the study of epilepsy.

PubMed

Bernhardt, Boris C; Bonilha, Leonardo; Gross, Donald W

2015-09-01

Recent years have witnessed a paradigm shift in the study and conceptualization of epilepsy, which is increasingly understood as a network-level disorder. An emblematic case is temporal lobe epilepsy (TLE), the most common drug-resistant epilepsy that is electroclinically defined as a focal epilepsy and pathologically associated with hippocampal sclerosis. In this review, we will summarize histopathological, electrophysiological, and neuroimaging evidence supporting the concept that the substrate of TLE is not limited to the hippocampus alone, but rather is broadly distributed across multiple brain regions and interconnecting white matter pathways. We will introduce basic concepts of graph theory, a formalism to quantify topological properties of complex systems that has recently been widely applied to study networks derived from brain imaging and electrophysiology. We will discuss converging graph theoretical evidence indicating that networks in TLE show marked shifts in their overall topology, providing insight into the neurobiology of TLE as a network-level disorder. Our review will conclude by discussing methodological challenges and future clinical applications of this powerful analytical approach. Copyright © 2015 Elsevier Inc. All rights reserved.

The application of the multi-alternative approach in active neural network models

NASA Astrophysics Data System (ADS)

Podvalny, S.; Vasiljev, E.

2017-02-01

The article refers to the construction of intelligent systems based artificial neuron networks are used. We discuss the basic properties of the non-compliance of artificial neuron networks and their biological prototypes. It is shown here that the main reason for these discrepancies is the structural immutability of the neuron network models in the learning process, that is, their passivity. Based on the modern understanding of the biological nervous system as a structured ensemble of nerve cells, it is proposed to abandon the attempts to simulate its work at the level of the elementary neurons functioning processes and proceed to the reproduction of the information structure of data storage and processing on the basis of the general enough evolutionary principles of multialternativity, i.e. the multi-level structural model, diversity and modularity. The implementation method of these principles is offered, using the faceted memory organization in the neuron network with the rearranging active structure. An example of the implementation of the active facet-type neuron network in the intellectual decision-making system in the conditions of critical events development in the electrical distribution system.

Mechanisms of stochastic focusing and defocusing in biological reaction networks: insight from accurate chemical master equation (ACME) solutions.

PubMed

Gursoy, Gamze; Terebus, Anna; Youfang Cao; Jie Liang

2016-08-01

Stochasticity plays important roles in regulation of biochemical reaction networks when the copy numbers of molecular species are small. Studies based on Stochastic Simulation Algorithm (SSA) has shown that a basic reaction system can display stochastic focusing (SF) by increasing the sensitivity of the network as a result of the signal noise. Although SSA has been widely used to study stochastic networks, it is ineffective in examining rare events and this becomes a significant issue when the tails of probability distributions are relevant as is the case of SF. Here we use the ACME method to solve the exact solution of the discrete Chemical Master Equations and to study a network where SF was reported. We showed that the level of SF depends on the degree of the fluctuations of signal molecule. We discovered that signaling noise under certain conditions in the same reaction network can lead to a decrease in the system sensitivities, thus the network can experience stochastic defocusing. These results highlight the fundamental role of stochasticity in biological reaction networks and the need for exact computation of probability landscape of the molecules in the system.

Distributing File-Based Data to Remote Sites Within the BABAR Collaboration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gowdy, Stephen J.

BABAR [1] uses two formats for its data: Objectivity database and root [2] files. This poster concerns the distribution of the latter--for Objectivity data see [3]. The BABAR analysis data is stored in root files--one per physics run and analysis selection channel--maintained in a large directory tree. Currently BABAR has more than 4.5 TBytes in 200,000 root files. This data is (mostly) produced at SLAC, but is required for analysis at universities and research centers throughout the us and Europe. Two basic problems confront us when we seek to import bulk data from slac to an institute's local storage viamore » the network. We must determine which files must be imported (depending on the local site requirements and which files have already been imported), and we must make the optimum use of the network when transferring the data. Basic ftp-like tools (ftp, scp, etc) do not attempt to solve the first problem. More sophisticated tools like rsync [4], the widely-used mirror/synchronization program, compare local and remote file systems, checking for changes (based on file date, size and, if desired, an elaborate checksum) in order to only copy new or modified files. However rsync allows for only limited file selection. Also when, as in BABAR, an extremely large directory structure must be scanned, rsync can take several hours just to determine which files need to be copied. Although rsync (and scp) provides on-the-fly compression, it does not allow us to optimize the network transfer by using multiple streams, adjusting the tcp window size, or separating encrypted authentication from unencrypted data channels.« less

Adaptations in a hierarchical food web of southeastern Lake Michigan

USGS Publications Warehouse

Krause, Ann E.; Frank, Ken A.; Jones, Michael L.; Nalepa, Thomas F.; Barbiero, Richard P.; Madenjian, Charles P.; Agy, Megan; Evans, Marlene S.; Taylor, William W.; Mason, Doran M.; Léonard, Nancy J.

2009-01-01

Two issues in ecological network theory are: (1) how to construct an ecological network model and (2) how do entire networks (as opposed to individual species) adapt to changing conditions? We present a novel method for constructing an ecological network model for the food web of southeastern Lake Michigan (USA) and we identify changes in key system properties that are large relative to their uncertainty as this ecological network adapts from one time point to a second time point in response to multiple perturbations. To construct our food web for southeastern Lake Michigan, we followed the list of seven recommendations outlined in Cohen et al. [Cohen, J.E., et al., 1993. Improving food webs. Ecology 74, 252–258] for improving food webs. We explored two inter-related extensions of hierarchical system theory with our food web; the first one was that subsystems react to perturbations independently in the short-term and the second one was that a system's properties change at a slower rate than its subsystems’ properties. We used Shannon's equations to provide quantitative versions of the basic food web properties: number of prey, number of predators, number of feeding links, and connectance (or density). We then compared these properties between the two time-periods by developing distributions of each property for each time period that took uncertainty about the property into account. We compared these distributions, and concluded that non-overlapping distributions indicated changes in these properties that were large relative to their uncertainty. Two subsystems were identified within our food web system structure (p < 0.001). One subsystem had more non-overlapping distributions in food web properties between Time 1 and Time 2 than the other subsystem. The overall system had all overlapping distributions in food web properties between Time 1 and Time 2. These results supported both extensions of hierarchical systems theory. Interestingly, the subsystem with more non-overlapping distributions in food web properties was the subsystem that contained primarily benthic taxa, contrary to expectations that the identified major perturbations (lower phosphorous inputs and invasive species) would more greatly affect the subsystem containing primarily pelagic taxa. Future food-web research should employ rigorous statistical analysis and incorporate uncertainty in food web properties for a better understanding of how ecological networks adapt.

An Abstract Systolic Model and Its Application to the Design of Finite Element Systems.

DTIC Science & Technology

1983-01-01

networks as a collection of communicating. parallel :.,’-.processes, some of the techniques for the verification of distributed systems ,.woi (see for...item must be collected . even If there is no Interest In its value. In this case. the collection of the data is simply achieved by changing the state of...the appropriate data as well as for collecting the output data and performing some additional tasks that we will discuss later. A basic functional

Design and fabrication of a photovoltaic power system for the Papago Indian village of Schuchuli (Gunsight), Arizona

NASA Technical Reports Server (NTRS)

Bifano, W. J.; Ratajczak, A. F.; Ice, W. J.

1978-01-01

A stand alone photovoltaic power system for installation in the Papago Indian village of Schuchuli is being designed and fabricated to provide electricity for village water pumping and basic domestic needs. The system will consist of a 3.5 kW (peak) photovoltaic array; controls, instrumentations, and storage batteries located in an electrical equipment building and a 120 volt dc village distribution network. The system will power a 2 HP dc electric motor.

Fault identification and localization for Ethernet Passive Optical Network using L-band ASE source and various types of fiber Bragg grating

NASA Astrophysics Data System (ADS)

Naim, Nani Fadzlina; Bakar, A. Ashrif A.; Ab-Rahman, Mohammad Syuhaimi

2018-01-01

This paper presents a centralized and fault localization technique for Ethernet Passive Optical Access Network. This technique employs L-band Amplified Spontaneous Emission (ASE) as the monitoring source and various fiber Bragg Gratings (FBGs) as the fiber's identifier. An FBG with a unique combination of Bragg wavelength, reflectivity and bandwidth is inserted at each distribution fiber. The FBG reflection spectrum will be analyzed using an optical spectrum analyzer (OSA) to monitor the condition of the distribution fiber. Various FBGs reflection spectra is employed to optimize the limited bandwidth of monitoring source, thus allows more fibers to be monitored. Basically, one Bragg wavelength is shared by two distinct FBGs with different reflectivity and bandwidth. The experimental result shows that the system is capable to monitor up to 32 customers with OSNR value of ∼1.2 dB and monitoring power received of -24 dBm. This centralized and simple monitoring technique demonstrates a low power, cost efficient and low bandwidth requirement system.

Hypergraph topological quantities for tagged social networks.

PubMed

Zlatić, Vinko; Ghoshal, Gourab; Caldarelli, Guido

2009-09-01

Recent years have witnessed the emergence of a new class of social networks, which require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper, we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper, we extend our model by defining additional quantities such as edge distributions, vertex similarity and correlations as well as clustering. We then empirically measure these quantities on two real life folksonomies, the popular online photo sharing site Flickr and the bookmarking site CiteULike. We find that these systems share similar qualitative features with the majority of complex networks that have been previously studied. We propose that the quantities and methodology described here can be used as a standard tool in measuring the structure of tagged networks.

Hypergraph topological quantities for tagged social networks

NASA Astrophysics Data System (ADS)

Zlatić, Vinko; Ghoshal, Gourab; Caldarelli, Guido

2009-09-01

Recent years have witnessed the emergence of a new class of social networks, which require us to move beyond previously employed representations of complex graph structures. A notable example is that of the folksonomy, an online process where users collaboratively employ tags to resources to impart structure to an otherwise undifferentiated database. In a recent paper, we proposed a mathematical model that represents these structures as tripartite hypergraphs and defined basic topological quantities of interest. In this paper, we extend our model by defining additional quantities such as edge distributions, vertex similarity and correlations as well as clustering. We then empirically measure these quantities on two real life folksonomies, the popular online photo sharing site Flickr and the bookmarking site CiteULike. We find that these systems share similar qualitative features with the majority of complex networks that have been previously studied. We propose that the quantities and methodology described here can be used as a standard tool in measuring the structure of tagged networks.

Discrete Mathematical Approaches to Graph-Based Traffic Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joslyn, Cliff A.; Cowley, Wendy E.; Hogan, Emilie A.

2014-04-01

Modern cyber defense and anlaytics requires general, formal models of cyber systems. Multi-scale network models are prime candidates for such formalisms, using discrete mathematical methods based in hierarchically-structured directed multigraphs which also include rich sets of labels. An exemplar of an application of such an approach is traffic analysis, that is, observing and analyzing connections between clients, servers, hosts, and actors within IP networks, over time, to identify characteristic or suspicious patterns. Towards that end, NetFlow (or more generically, IPFLOW) data are available from routers and servers which summarize coherent groups of IP packets flowing through the network. In thismore » paper, we consider traffic analysis of Netflow using both basic graph statistics and two new mathematical measures involving labeled degree distributions and time interval overlap measures. We do all of this over the VAST test data set of 96M synthetic Netflow graph edges, against which we can identify characteristic patterns of simulated ground-truth network attacks.« less

Percolation dans des reseaux realistes de nanostructures de carbone

NASA Astrophysics Data System (ADS)

Simoneau, Louis-Philippe

Carbon nanotubes have very interesting mechanical and electrical properties for various applications in electronics. They are highly resistant to deformation and can be excellent conductors or semiconductors. However, manipulating individual nanotubes to build structured devices remains very difficult. There is no method for controlling all of the electrical properties, the orientation and the spatial positioning of a large number of nanotubes. The fabrication of disordered networks of nanotubes is much easier, and these systems have a good electrical conductivity which makes them very interesting, especially as materials of transparent and flexible electrodes. There are three main methods of production used to make networks of nanotubes: the solution deposition, the direct growth on substrate and the embedding in a polymer matrix. The solution deposition method can form networks of various densities on a variety of substrates, the direct growth of nanotubes allows the creation of very clean networks on substrates such as SiO2, and the embedding in a polymer matrix can give composite volumes containing varying amounts of nanotubes. Many parameters such as the length of the tubes, their orientation or their tortuosity influence the properties of these networks and the presence of structural disorder complicates the understanding of their interactions. Predicting the properties of a network, such as conductivity, from a few characteristics such as size and density of the tubes can be difficult. This task becomes even more complex if one wants to identify the parameters that will optimize the performance of a device containing the material. We chose to address the carbon nanotube networks problem by developing a series of computer simulation tools that are mainly based on the Monte Carlo method. We take into account a large number of parameters to describe the characteristics of the networks, which allows for a more reliable representation of real networks as well as versatility in the choice of network components that can be simulated. The tools we have developed, grouped together in the RPH-HPN software Reseaux percolatifs hybrides - Hybrid Percolation Networks, construct random networks, detect contact between the tubes, translate the systems to equivalent electrical circuits and calculate global properties. An infinity of networks can have the same basic characteristics (size, diameter, etc.) and therefore the properties of a particular random network are not necessarily representative of the average properties of all networks. To obtain those general properties, we simulate a large number of random networks with the same basic characteristics and the average of the quantities is determined. The network constituent elements can be spheres, rods or snakes. The use of such geometries for network elements makes contact detection simple and quick, and more faithfully reproduce the form of carbon nanotubes. We closely monitor the geometrical and electrical properties of these elements through stochastic distributions of our choice. We can choose the length, diameter, orientation, chirality, tortuosity and impenetrable nature of the elements in order to properly reproduce real networks characteristics. We have considered statistical distribution functions that are rectangular, Gaussian, and Lorentzian, but all other distributions that can be expressed mathematically can also be envisioned. During the creation of a particular network, we generate the elements one by one. Each of their properties is sampled from a preselected distribution. Efficient algorithms used in various fields were adapted to our needs to manage the detection of contacts, clusters and percolation. In addition, we model more realistic contact between rigid nanotubes using an original method used to create the network that does not require a relaxation phase. Finally, we use Kirchhoff's laws to solve the equivalent electrical circuit conventionally. First, we evaluated the impact of a simplification widely used in other nanotube networks simulations studies. Values of the contact resistance at the junction between two nanotubes that are reported in the literature vary over a wide range, while almost all the simulations use a unique value for this parameter. Therefore, we assessed the effect of the presence of various stochastic distributions of contact resistances on the electrical properties of the networks. To do this, we used the experimental results of our collaborators in order to reproduce them by simulation. Our results show that, despite the existence of a wide range of contact resistance values, the nature of the statistical distribution has little impact on the conductivity obtained by simulation. Use of a single value for all connections of a network gives a total conductivity comparable to the experimental conductivity, and similar to that obtained using Gaussian, Lorentzian and uniform rectangular distributions. In fact, the dominant factor is not the type of distribution used to represent the resistance, but the central value of the distribution. Furthermore, we showed by studying bimodal distributions that the presence of lower resistance paths, even in small proportion, can rapidly increase the conductivity of the network. However, the type of stochastic distribution used to sample the spatial orientation of the nanotubes has a significant impact. We observed different behaviors for each of the three forms of distribution of orientation angles that we studied. In each case, a different distribution width maximize the conductivity of the networks. To optimize the conductivity, this distribution width, which is actually the deviation from the main direction, should in general be narrow. The formation of conductive paths is greatly enhanced in the presence of a majority of tubes closely aligned with the conduction direction and a small portion of tubes randomly aligned. The portion of misaligned tubes strongly contributes to the connectivity of nanotubes network by linking several clusters of aligned tubes. In order to increase the realism of our simulations, we also studied the influence of the interpenetrability of nanotubes on the electrical properties of networks. To do this, we describe the nanotubes with mutually impenetrable rigid cores that are surrounded by permeable shells. Thus, by varying the radius of the rigid cores, we have shown that a decrease in the interpenetrability of the nanotubes can increase the conductivity of the networks up to five orders of magnitude. We attribute this increase in conductivity to a greater connectivity of the nanotubes in the network. The more tubes are impenetrable, the more they push back against each other, and the better is the spreading of connected clusters in space. The second parameter on which we focused to improve the realism is the tortuosity of the nanotubes. We investigated the electrical properties of networks where the nanotubes are segmented into ten sections joined end to end. The angle between two consecutive segments is sampled from a uniform rectangular distribution and the variation of the bounds of this distribution allows us to vary the general tortuosity of the network. We observe that the more the tubes are tortuous, the higher the percolation threshold is, and the lower is the total conductivity. This can be nearly two orders of magnitude lower for networks with twisted tubes. We further note that the increase of the percolation threshold is attenuated when the wavy nanotubes have rigid cores. As part of our project, we have developed tools that, to the best of our knowledge, offer the best physical representation of nanotubes in a network of carbon nanotubes to date. This allowed us to study networks of complex geometries and measure the importance of the statistical distributions of parameters in optimizing the conductivity of networks. We have also established that the rigid tube-tube contacts and the nanotube tortuosity have strong impacts on the percolation threshold and conductivity. This work has demonstrated the importance of modeling for the understanding and the adequate description of complex processes, and the development needed to accurately reproduce the behavior of real systems. These tools can now be used to guide the creation of nanotube networks with targeted properties, and also to explore even more complex systems containing for example mixtures of nanotubes and quantum dots.

A Wave Chaotic Study of Quantum Graphs with Microwave Networks

NASA Astrophysics Data System (ADS)

Fu, Ziyuan

Quantum graphs provide a setting to test the hypothesis that all ray-chaotic systems show universal wave chaotic properties. I study the quantum graphs with a wave chaotic approach. Here, an experimental setup consisting of a microwave coaxial cable network is used to simulate quantum graphs. Some basic features and the distributions of impedance statistics are analyzed from experimental data on an ensemble of tetrahedral networks. The random coupling model (RCM) is applied in an attempt to uncover the universal statistical properties of the system. Deviations from RCM predictions have been observed in that the statistics of diagonal and off-diagonal impedance elements are different. Waves trapped due to multiple reflections on bonds between nodes in the graph most likely cause the deviations from universal behavior in the finite-size realization of a quantum graph. In addition, I have done some investigations on the Random Coupling Model, which are useful for further research.

Photonic multipartite entanglement conversion using nonlocal operations

NASA Astrophysics Data System (ADS)

Tashima, T.; Tame, M. S.; Özdemir, Ş. K.; Nori, F.; Koashi, M.; Weinfurter, H.

2016-11-01

We propose a simple setup for the conversion of multipartite entangled states in a quantum network with restricted access. The scheme uses nonlocal operations to enable the preparation of states that are inequivalent under local operations and classical communication, but most importantly does not require full access to the states. It is based on a flexible linear optical conversion gate that uses photons, which are ideally suited for distributed quantum computation and quantum communication in extended networks. In order to show the basic working principles of the gate, we focus on converting a four-qubit entangled cluster state to other locally inequivalent four-qubit states, such as the Greenberger-Horne-Zeilinger and symmetric Dicke states. We also show how the gate can be incorporated into extended graph state networks and can be used to generate variable entanglement and quantum correlations without entanglement but nonvanishing quantum discord.

Non-Markovian Infection Spread Dramatically Alters the Susceptible-Infected-Susceptible Epidemic Threshold in Networks

NASA Astrophysics Data System (ADS)

Van Mieghem, P.; van de Bovenkamp, R.

2013-03-01

Most studies on susceptible-infected-susceptible epidemics in networks implicitly assume Markovian behavior: the time to infect a direct neighbor is exponentially distributed. Much effort so far has been devoted to characterize and precisely compute the epidemic threshold in susceptible-infected-susceptible Markovian epidemics on networks. Here, we report the rather dramatic effect of a nonexponential infection time (while still assuming an exponential curing time) on the epidemic threshold by considering Weibullean infection times with the same mean, but different power exponent α. For three basic classes of graphs, the Erdős-Rényi random graph, scale-free graphs and lattices, the average steady-state fraction of infected nodes is simulated from which the epidemic threshold is deduced. For all graph classes, the epidemic threshold significantly increases with the power exponents α. Hence, real epidemics that violate the exponential or Markovian assumption can behave seriously differently than anticipated based on Markov theory.

Accelerator science and technology in Europe: EuCARD 2012

NASA Astrophysics Data System (ADS)

Romaniuk, Ryszard S.

2012-05-01

Accelerator science and technology is one of a key enablers of the developments in the particle physic, photon physics and also applications in medicine and industry. The paper presents a digest of the research results in the domain of accelerator science and technology in Europe, shown during the third annual meeting of the EuCARD - European Coordination of Accelerator Research and Development. The conference concerns building of the research infrastructure, including in this advanced photonic and electronic systems for servicing large high energy physics experiments. There are debated a few basic groups of such systems like: measurement - control networks of large geometrical extent, multichannel systems for large amounts of metrological data acquisition, precision photonic networks of reference time, frequency and phase distribution.

Distributed numerical controllers

NASA Astrophysics Data System (ADS)

Orban, Peter E.

2001-12-01

While the basic principles of Numerical Controllers (NC) have not changed much during the years, the implementation of NCs' has changed tremendously. NC equipment has evolved from yesterday's hard-wired specialty control apparatus to today's graphics intensive, networked, increasingly PC based open systems, controlling a wide variety of industrial equipment with positioning needs. One of the newest trends in NC technology is the distributed implementation of the controllers. Distributed implementation promises to offer robustness, lower implementation costs, and a scalable architecture. Historically partitioning has been done along the hierarchical levels, moving individual modules into self contained units. The paper discusses various NC architectures, the underlying technology for distributed implementation, and relevant design issues. First the functional requirements of individual NC modules are analyzed. Module functionality, cycle times, and data requirements are examined. Next the infrastructure for distributed node implementation is reviewed. Various communication protocols and distributed real-time operating system issues are investigated and compared. Finally, a different, vertical system partitioning, offering true scalability and reconfigurability is presented.

Development of quantitative security optimization approach for the picture archives and carrying system between a clinic and a rehabilitation center

NASA Astrophysics Data System (ADS)

Haneda, Kiyofumi; Kajima, Toshio; Koyama, Tadashi; Muranaka, Hiroyuki; Dojo, Hirofumi; Aratani, Yasuhiko

2002-05-01

The target of our study is to analyze the level of necessary security requirements, to search for suitable security measures and to optimize security distribution to every portion of the medical practice. Quantitative expression must be introduced to our study, if possible, to enable simplified follow-up security procedures and easy evaluation of security outcomes or results. Using fault tree analysis (FTA), system analysis showed that system elements subdivided into groups by details result in a much more accurate analysis. Such subdivided composition factors greatly depend on behavior of staff, interactive terminal devices, kinds of services provided, and network routes. Security measures were then implemented based on the analysis results. In conclusion, we identified the methods needed to determine the required level of security and proposed security measures for each medical information system, and the basic events and combinations of events that comprise the threat composition factors. Methods for identifying suitable security measures were found and implemented. Risk factors for each basic event, a number of elements for each composition factor, and potential security measures were found. Methods to optimize the security measures for each medical information system were proposed, developing the most efficient distribution of risk factors for basic events.

The US nuclear reaction data network. Summary of the first meeting, March 13 & 14 1996

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1996-03-01

The first meeting of the US Nuclear Reaction Data Network (USNRDN) was held at the Colorado School of Mines, March 13-14, 1996 chaired by F. Edward Cecil. The Agenda of the meeting is attached. The Network, its mission, products and services; related nuclear data and data networks, members, and organization are described in Attachment 1. The following progress reports from the members of the USNRDN were distributed prior to the meeting and are given as Attachment 2. (1) Measurements and Development of Analytic Techniques for Basic Nuclear Physics and Nuclear Applications; (2) Nuclear Reaction Data Activities at the National Nuclearmore » Data Center; (3) Studies of nuclear reactions at very low energies; (4) Nuclear Reaction Data Activities, Nuclear Data Group; (5) Progress in Neutron Physics at Los Alamos - Experiments; (6) Nuclear Reaction Data Activities in Group T2; (7) Progress Report for the US Nuclear Reaction Data Network Meeting; (8) Nuclear Astrophysics Research Group (ORNL); (9) Progress Report from Ohio University; (10) Exciton Model Phenomenology; and (11) Progress Report for Coordination Meeting USNRDN.« less

Scaling Laws of Discrete-Fracture-Network Models

NASA Astrophysics Data System (ADS)

Philippe, D.; Olivier, B.; Caroline, D.; Jean-Raynald, D.

2006-12-01

The statistical description of fracture networks through scale still remains a concern for geologists, considering the complexity of fracture networks. A challenging task of the last 20-years studies has been to find a solid and rectifiable rationale to the trivial observation that fractures exist everywhere and at all sizes. The emergence of fractal models and power-law distributions quantifies this fact, and postulates in some ways that small-scale fractures are genetically linked to their larger-scale relatives. But the validation of these scaling concepts still remains an issue considering the unreachable amount of information that would be necessary with regards to the complexity of natural fracture networks. Beyond the theoretical interest, a scaling law is a basic and necessary ingredient of Discrete-Fracture-Network models (DFN) that are used for many environmental and industrial applications (groundwater resources, mining industry, assessment of the safety of deep waste disposal sites, ..). Indeed, such a function is necessary to assemble scattered data, taken at different scales, into a unified scaling model, and to interpolate fracture densities between observations. In this study, we discuss some important issues related to scaling laws of DFN: - We first describe a complete theoretical and mathematical framework that takes account of both the fracture- size distribution and the fracture clustering through scales (fractal dimension). - We review the scaling laws that have been obtained, and we discuss the ability of fracture datasets to really constrain the parameters of the DFN model. - And finally we discuss the limits of scaling models.

Arousal Rather than Basic Emotions Influence Long-Term Recognition Memory in Humans

PubMed Central

Marchewka, Artur; Wypych, Marek; Moslehi, Abnoos; Riegel, Monika; Michałowski, Jarosław M.; Jednoróg, Katarzyna

2016-01-01

Emotion can influence various cognitive processes, however its impact on memory has been traditionally studied over relatively short retention periods and in line with dimensional models of affect. The present study aimed to investigate emotional effects on long-term recognition memory according to a combined framework of affective dimensions and basic emotions. Images selected from the Nencki Affective Picture System were rated on the scale of affective dimensions and basic emotions. After 6 months, subjects took part in a surprise recognition test during an fMRI session. The more negative the pictures the better they were remembered, but also the more false recognitions they provoked. Similar effects were found for the arousal dimension. Recognition success was greater for pictures with lower intensity of happiness and with higher intensity of surprise, sadness, fear, and disgust. Consecutive fMRI analyses showed a significant activation for remembered (recognized) vs. forgotten (not recognized) images in anterior cingulate and bilateral anterior insula as well as in bilateral caudate nuclei and right thalamus. Further, arousal was found to be the only subjective rating significantly modulating brain activation. Higher subjective arousal evoked higher activation associated with memory recognition in the right caudate and the left cingulate gyrus. Notably, no significant modulation was observed for other subjective ratings, including basic emotion intensities. These results emphasize the crucial role of arousal for long-term recognition memory and support the hypothesis that the memorized material, over time, becomes stored in a distributed cortical network including the core salience network and basal ganglia. PMID:27818626

Arousal Rather than Basic Emotions Influence Long-Term Recognition Memory in Humans.

PubMed

Marchewka, Artur; Wypych, Marek; Moslehi, Abnoos; Riegel, Monika; Michałowski, Jarosław M; Jednoróg, Katarzyna

2016-01-01

Emotion can influence various cognitive processes, however its impact on memory has been traditionally studied over relatively short retention periods and in line with dimensional models of affect. The present study aimed to investigate emotional effects on long-term recognition memory according to a combined framework of affective dimensions and basic emotions. Images selected from the Nencki Affective Picture System were rated on the scale of affective dimensions and basic emotions. After 6 months, subjects took part in a surprise recognition test during an fMRI session. The more negative the pictures the better they were remembered, but also the more false recognitions they provoked. Similar effects were found for the arousal dimension. Recognition success was greater for pictures with lower intensity of happiness and with higher intensity of surprise, sadness, fear, and disgust. Consecutive fMRI analyses showed a significant activation for remembered (recognized) vs. forgotten (not recognized) images in anterior cingulate and bilateral anterior insula as well as in bilateral caudate nuclei and right thalamus. Further, arousal was found to be the only subjective rating significantly modulating brain activation. Higher subjective arousal evoked higher activation associated with memory recognition in the right caudate and the left cingulate gyrus. Notably, no significant modulation was observed for other subjective ratings, including basic emotion intensities. These results emphasize the crucial role of arousal for long-term recognition memory and support the hypothesis that the memorized material, over time, becomes stored in a distributed cortical network including the core salience network and basal ganglia.

CEREBRA: a 3-D visualization tool for brain network extracted from fMRI data.

PubMed

Nasir, Baris; Yarman Vural, Fatos T

2016-08-01

In this paper, we introduce a new tool, CEREBRA, to visualize the 3D network of human brain, extracted from the fMRI data. The tool aims to analyze the brain connectivity by representing the selected voxels as the nodes of the network. The edge weights among the voxels are estimated by considering the relationships among the voxel time series. The tool enables the researchers to observe the active brain regions and the interactions among them by using graph theoretic measures, such as, the edge weight and node degree distributions. CEREBRA provides an interactive interface with basic display and editing options for the researchers to study their hypotheses about the connectivity of the brain network. CEREBRA interactively simplifies the network by selecting the active voxels and the most correlated edge weights. The researchers may remove the voxels and edges by using local and global thresholds selected on the window. The built-in graph reduction algorithms are then eliminate the irrelevant regions, voxels and edges and display various properties of the network. The toolbox is capable of space-time representation of the voxel time series and estimated arc weights by using the animated heat maps.

Reaching Agreement in Quantum Hybrid Networks.

PubMed

Shi, Guodong; Li, Bo; Miao, Zibo; Dower, Peter M; James, Matthew R

2017-07-20

We consider a basic quantum hybrid network model consisting of a number of nodes each holding a qubit, for which the aim is to drive the network to a consensus in the sense that all qubits reach a common state. Projective measurements are applied serving as control means, and the measurement results are exchanged among the nodes via classical communication channels. In this way the quantum-opeartion/classical-communication nature of hybrid quantum networks is captured, although coherent states and joint operations are not taken into consideration in order to facilitate a clear and explicit analysis. We show how to carry out centralized optimal path planning for this network with all-to-all classical communications, in which case the problem becomes a stochastic optimal control problem with a continuous action space. To overcome the computation and communication obstacles facing the centralized solutions, we also develop a distributed Pairwise Qubit Projection (PQP) algorithm, where pairs of nodes meet at a given time and respectively perform measurements at their geometric average. We show that the qubit states are driven to a consensus almost surely along the proposed PQP algorithm, and that the expected qubit density operators converge to the average of the network's initial values.

Speed scanning system based on solid-state microchip laser for architectural planning

NASA Astrophysics Data System (ADS)

Redka, Dmitriy; Grishkanich, Alexsandr S.; Kolmakov, Egor; Tsvetkov, Konstantin

2017-10-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

Coordinate measuring system based on microchip lasers for reverse prototyping

NASA Astrophysics Data System (ADS)

Iakovlev, Alexey; Grishkanich, Alexsandr S.; Redka, Dmitriy; Tsvetkov, Konstantin

2017-02-01

According to the current great interest concerning Large-Scale Metrology applications in many different fields of manufacturing industry, technologies and techniques for dimensional measurement have recently shown a substantial improvement. Ease-of-use, logistic and economic issues, as well as metrological performance, are assuming a more and more important role among system requirements. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of chip and microlasers as radiators on the linear-angular characteristics of existing measurement systems. The project is planned to conduct experimental studies aimed at identifying the impact of the application of the basic laws of microlasers as radiators on the linear-angular characteristics of existing measurement systems. The system consists of a distributed network-based layout, whose modularity allows to fit differently sized and shaped working volumes by adequately increasing the number of sensing units. Differently from existing spatially distributed metrological instruments, the remote sensor devices are intended to provide embedded data elaboration capabilities, in order to share the overall computational load.

A compact model for electroosmotic flows in microfluidic devices

NASA Astrophysics Data System (ADS)

Qiao, R.; Aluru, N. R.

2002-09-01

A compact model to compute flow rate and pressure in microfluidic devices is presented. The microfluidic flow can be driven by either an applied electric field or a combined electric field and pressure gradient. A step change in the ζ-potential on a channel wall is treated by a pressure source in the compact model. The pressure source is obtained from the pressure Poisson equation and conservation of mass principle. In the proposed compact model, the complex fluidic network is simplified by an electrical circuit. The compact model can predict the flow rate, pressure distribution and other basic characteristics in microfluidic channels quickly with good accuracy when compared to detailed numerical simulation. Using the compact model, fluidic mixing and dispersion control are studied in a complex microfluidic network.

Working Memory: Maintenance, Updating, and the Realization of Intentions

PubMed Central

Nyberg, Lars; Eriksson, Johan

2016-01-01

“Working memory” refers to a vast set of mnemonic processes and associated brain networks, relates to basic intellectual abilities, and underlies many real-world functions. Working-memory maintenance involves frontoparietal regions and distributed representational areas, and can be based on persistent activity in reentrant loops, synchronous oscillations, or changes in synaptic strength. Manipulation of content of working memory depends on the dorsofrontal cortex, and updating is realized by a frontostriatal ‘“gating” function. Goals and intentions are represented as cognitive and motivational contexts in the rostrofrontal cortex. Different working-memory networks are linked via associative reinforcement-learning mechanisms into a self-organizing system. Normal capacity variation, as well as working-memory deficits, can largely be accounted for by the effectiveness and integrity of the basal ganglia and dopaminergic neurotransmission. PMID:26637287

Northeast Artificial Intelligence Consortium Annual Report - 1988. Volume 4. Distributed AI for Communications Network Management

DTIC Science & Technology

1989-10-01

apiots to rerlliii their los1 ’ at act ions iii Ilie rouist ’lirt iii of thle plain. Th’lis fast piece of iiiforiat liolu is plrovidied tlioiigli Ow 1use of...maximum compatible sets and delete subsets otherwise for every plan fragment pf, for g,. tile first goal in goals, if p.f- does not exceed resource... deletes an non-default assumption. 4.5.3.2 Data Structures The MATMS is a frame-based system in which there are five basic types of objects: beliefs

Simple Automatic File Exchange (SAFE) to Support Low-Cost Spacecraft Operation via the Internet

NASA Technical Reports Server (NTRS)

Baker, Paul; Repaci, Max; Sames, David

1998-01-01

Various issues associated with Simple Automatic File Exchange (SAFE) are presented in viewgraph form. Specific topics include: 1) Packet telemetry, Internet IP networks and cost reduction; 2) Basic functions and technical features of SAFE; 3) Project goals, including low-cost satellite transmission to data centers to be distributed via an Internet; 4) Operations with a replicated file protocol; 5) File exchange operation; 6) Ground stations as gateways; 7) Lessons learned from demonstrations and tests with SAFE; and 8) Feedback and future initiatives.

Achieving "organic compositionality" through self-organization: reviews on brain-inspired robotics experiments.

PubMed

Tani, Jun; Nishimoto, Ryunosuke; Paine, Rainer W

2008-05-01

The current paper examines how compositional structures can self-organize in given neuro-dynamical systems when robot agents are forced to learn multiple goal-directed behaviors simultaneously. Firstly, we propose a basic model accounting for the roles of parietal-premotor interactions for representing skills for goal-directed behaviors. The basic model had been implemented in a set of robotics experiments employing different neural network architectures. The comparative reviews among those experimental results address the issues of local vs distributed representations in representing behavior and the effectiveness of level structures associated with different sensory-motor articulation mechanisms. It is concluded that the compositional structures can be acquired "organically" by achieving generalization in learning and by capturing the contextual nature of skilled behaviors under specific conditions. Furthermore, the paper discusses possible feedback for empirical neuroscience studies in the future.

A new paradigm for the molecular basis of rubber elasticity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hanson, David E.; Barber, John L.

The molecular basis for rubber elasticity is arguably the oldest and one of the most important questions in the field of polymer physics. The theoretical investigation of rubber elasticity began in earnest almost a century ago with the development of analytic thermodynamic models, based on simple, highly-symmetric configurations of so-called Gaussian chains, i.e. polymer chains that obey Markov statistics. Numerous theories have been proposed over the past 90 years based on the ansatz that the elastic force for individual network chains arises from the entropy change associated with the distribution of end-to-end distances of a free polymer chain. There aremore » serious philosophical objections to this assumption and others, such as the assumption that all network nodes undergo affine motion and that all of the network chains have the same length. Recently, a new paradigm for elasticity in rubber networks has been proposed that is based on mechanisms that originate at the molecular level. Using conventional statistical mechanics analyses, quantum chemistry, and molecular dynamics simulations, the fundamental entropic and enthalpic chain extension forces for polyisoprene (natural rubber) have been determined, along with estimates for the basic force constants. Concurrently, the complex morphology of natural rubber networks (the joint probability density distributions that relate the chain end-to-end distance to its contour length) has also been captured in a numerical model. When molecular chain forces are merged with the network structure in this model, it is possible to study the mechanical response to tensile and compressive strains of a representative volume element of a polymer network. As strain is imposed on a network, pathways of connected taut chains, that completely span the network along strain axis, emerge. Although these chains represent only a few percent of the total, they account for nearly all of the elastic stress at high strain. Here we provide a brief review of previous elasticity theories and their deficiencies, and present a new paradigm with an emphasis on experimental comparisons.« less

A new paradigm for the molecular basis of rubber elasticity

DOE PAGES

Hanson, David E.; Barber, John L.

2015-02-19

The molecular basis for rubber elasticity is arguably the oldest and one of the most important questions in the field of polymer physics. The theoretical investigation of rubber elasticity began in earnest almost a century ago with the development of analytic thermodynamic models, based on simple, highly-symmetric configurations of so-called Gaussian chains, i.e. polymer chains that obey Markov statistics. Numerous theories have been proposed over the past 90 years based on the ansatz that the elastic force for individual network chains arises from the entropy change associated with the distribution of end-to-end distances of a free polymer chain. There aremore » serious philosophical objections to this assumption and others, such as the assumption that all network nodes undergo affine motion and that all of the network chains have the same length. Recently, a new paradigm for elasticity in rubber networks has been proposed that is based on mechanisms that originate at the molecular level. Using conventional statistical mechanics analyses, quantum chemistry, and molecular dynamics simulations, the fundamental entropic and enthalpic chain extension forces for polyisoprene (natural rubber) have been determined, along with estimates for the basic force constants. Concurrently, the complex morphology of natural rubber networks (the joint probability density distributions that relate the chain end-to-end distance to its contour length) has also been captured in a numerical model. When molecular chain forces are merged with the network structure in this model, it is possible to study the mechanical response to tensile and compressive strains of a representative volume element of a polymer network. As strain is imposed on a network, pathways of connected taut chains, that completely span the network along strain axis, emerge. Although these chains represent only a few percent of the total, they account for nearly all of the elastic stress at high strain. Here we provide a brief review of previous elasticity theories and their deficiencies, and present a new paradigm with an emphasis on experimental comparisons.« less

High Tech Educators Network Evaluation.

ERIC Educational Resources Information Center

O'Shea, Dan

A process evaluation was conducted to assess the High Tech Educators Network's (HTEN's) activities. Four basic components to the evaluation approach were documentation review, program logic model, written survey, and participant interviews. The model mapped the basic goals and objectives, assumptions, activities, outcome expectations, and…

Random noise effects in pulse-mode digital multilayer neural networks.

PubMed

Kim, Y C; Shanblatt, M A

1995-01-01

A pulse-mode digital multilayer neural network (DMNN) based on stochastic computing techniques is implemented with simple logic gates as basic computing elements. The pulse-mode signal representation and the use of simple logic gates for neural operations lead to a massively parallel yet compact and flexible network architecture, well suited for VLSI implementation. Algebraic neural operations are replaced by stochastic processes using pseudorandom pulse sequences. The distributions of the results from the stochastic processes are approximated using the hypergeometric distribution. Synaptic weights and neuron states are represented as probabilities and estimated as average pulse occurrence rates in corresponding pulse sequences. A statistical model of the noise (error) is developed to estimate the relative accuracy associated with stochastic computing in terms of mean and variance. Computational differences are then explained by comparison to deterministic neural computations. DMNN feedforward architectures are modeled in VHDL using character recognition problems as testbeds. Computational accuracy is analyzed, and the results of the statistical model are compared with the actual simulation results. Experiments show that the calculations performed in the DMNN are more accurate than those anticipated when Bernoulli sequences are assumed, as is common in the literature. Furthermore, the statistical model successfully predicts the accuracy of the operations performed in the DMNN.

The study of RMB exchange rate complex networks based on fluctuation mode

NASA Astrophysics Data System (ADS)

Yao, Can-Zhong; Lin, Ji-Nan; Zheng, Xu-Zhou; Liu, Xiao-Feng

2015-10-01

In the paper, we research on the characteristics of RMB exchange rate time series fluctuation with methods of symbolization and coarse gaining. First, based on fluctuation features of RMB exchange rate, we define the first type of fluctuation mode as one specific foreign currency against RMB in four days' fluctuating situations, and the second type as four different foreign currencies against RMB in one day's fluctuating situation. With the transforming method, we construct the unique-currency and multi-currency complex networks. Further, through analyzing the topological features including out-degree, betweenness centrality and clustering coefficient of fluctuation-mode complex networks, we find that the out-degree distribution of both types of fluctuation mode basically follows power-law distributions with exponents between 1 and 2. The further analysis reveals that the out-degree and the clustering coefficient generally obey the approximated negative correlation. With this result, we confirm previous observations showing that the RMB exchange rate exhibits a characteristic of long-range memory. Finally, we analyze the most probable transmission route of fluctuation modes, and provide probability prediction matrix. The transmission route for RMB exchange rate fluctuation modes exhibits the characteristics of partially closed loop, repeat and reversibility, which lays a solid foundation for predicting RMB exchange rate fluctuation patterns with large volume of data.

Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future.

PubMed

Bestmann, Sven; Feredoes, Eva

2013-08-01

Modern neurostimulation approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences. This enables causal structure-function inferences, and in combination with neuroimaging, has provided novel insights into the basic mechanisms of action of neurostimulation on distributed networks. For example, more recent work has established the capacity of transcranial magnetic stimulation (TMS) to probe causal interregional influences, and their interaction with cognitive state changes. Combinations of neurostimulation and neuroimaging now face the challenge of integrating the known physiological effects of neurostimulation with theoretical and biological models of cognition, for example, when theoretical stalemates between opposing cognitive theories need to be resolved. This will be driven by novel developments, including biologically informed computational network analyses for predicting the impact of neurostimulation on brain networks, as well as novel neuroimaging and neurostimulation techniques. Such future developments may offer an expanded set of tools with which to investigate structure-function relationships, and to formulate and reconceptualize testable hypotheses about complex neural network interactions and their causal roles in cognition. © 2013 New York Academy of Sciences.

The research and application of Ethernet over RPR technology

NASA Astrophysics Data System (ADS)

Feng, Xiancheng; Yun, Xiang

2008-11-01

With service competitions of carriers aggravating and client's higher service experience requirement, it urges the MAN technology develops forward. When the Core Layer and Distribution Layer technology are mature, all kinds of reliability technologies of MAN access Layer are proposed. EoRPR is one of reliability technologies for MAN access network service protection. This paper elaborates Ethernet over RPR technology's many advantages through analyzing basic principle, address learning and key technologies of Ethernet over RPR. EpRPR has quicker replacing speed, plug and play, stronger QoS ability, convenient service deployment, band fairly sharing, and so on. At the same time the paper proposed solution of Ethernet over RPR in MAN, NGN network and enterprise Private network. So, among many technologies of MAN access network, EoRPR technology has higher reliability and manageable and highly effectiveness and lower costive of Ethernet. It is not only suitable for enterprise interconnection, BTV and NGN access services and so on, but also can meet the requirement of carriers' reducing CAPEX and OPEX's and increase the rate of investment.

Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems

PubMed Central

Laftah Al-Yaseen, Wathiq; Ali Othman, Zulaiha; Ahmad Nazri, Mohd Zakree

2015-01-01

Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy. PMID:26161437

Hybrid Modified K-Means with C4.5 for Intrusion Detection Systems in Multiagent Systems.

PubMed

Laftah Al-Yaseen, Wathiq; Ali Othman, Zulaiha; Ahmad Nazri, Mohd Zakree

2015-01-01

Presently, the processing time and performance of intrusion detection systems are of great importance due to the increased speed of traffic data networks and a growing number of attacks on networks and computers. Several approaches have been proposed to address this issue, including hybridizing with several algorithms. However, this paper aims at proposing a hybrid of modified K-means with C4.5 intrusion detection system in a multiagent system (MAS-IDS). The MAS-IDS consists of three agents, namely, coordinator, analysis, and communication agent. The basic concept underpinning the utilized MAS is dividing the large captured network dataset into a number of subsets and distributing these to a number of agents depending on the data network size and core CPU availability. KDD Cup 1999 dataset is used for evaluation. The proposed hybrid modified K-means with C4.5 classification in MAS is developed in JADE platform. The results show that compared to the current methods, the MAS-IDS reduces the IDS processing time by up to 70%, while improving the detection accuracy.

Conceptual Hierarchies in a Flat Attractor Network

PubMed Central

O’Connor, Christopher M.; Cree, George S.; McRae, Ken

2009-01-01

The structure of people’s conceptual knowledge of concrete nouns has traditionally been viewed as hierarchical (Collins & Quillian, 1969). For example, superordinate concepts (vegetable) are assumed to reside at a higher level than basic-level concepts (carrot). A feature-based attractor network with a single layer of semantic features developed representations of both basic-level and superordinate concepts. No hierarchical structure was built into the network. In Experiment and Simulation 1, the graded structure of categories (typicality ratings) is accounted for by the flat attractor-network. Experiment and Simulation 2 show that, as with basic-level concepts, such a network predicts feature verification latencies for superordinate concepts (vegetable ). In Experiment and Simulation 3, counterintuitive results regarding the temporal dynamics of similarity in semantic priming are explained by the model. By treating both types of concepts the same in terms of representation, learning, and computations, the model provides new insights into semantic memory. PMID:19543434

Hand-waving and interpretive dance: an introductory course on tensor networks

NASA Astrophysics Data System (ADS)

Bridgeman, Jacob C.; Chubb, Christopher T.

2017-06-01

The curse of dimensionality associated with the Hilbert space of spin systems provides a significant obstruction to the study of condensed matter systems. Tensor networks have proven an important tool in attempting to overcome this difficulty in both the numerical and analytic regimes. These notes form the basis for a seven lecture course, introducing the basics of a range of common tensor networks and algorithms. In particular, we cover: introductory tensor network notation, applications to quantum information, basic properties of matrix product states, a classification of quantum phases using tensor networks, algorithms for finding matrix product states, basic properties of projected entangled pair states, and multiscale entanglement renormalisation ansatz states. The lectures are intended to be generally accessible, although the relevance of many of the examples may be lost on students without a background in many-body physics/quantum information. For each lecture, several problems are given, with worked solutions in an ancillary file.

Water-quality assessment of the Rio Grande Valley, Colorado, New Mexico, and Texas; summary and analysis of water-quality data for the basic-fixed-site network, 1993-95

USGS Publications Warehouse

Healy, D.F.

1997-01-01

The Rio Grande Valley study unit of the U.S. Geological Survey National Water-Quality Assessment Program collected monthly water- quality samples at a network of surface-water sites from April 1993 through September 1995. This basic-fixed-site network consisted of nine main-stem sites on the Rio Grande, five sites on tributaries of the Rio Grande, two sites on streams in the Rio Grande Valley study unit that are not directly tributary to the Rio Grande, and one site on a conveyance channel. During each monthly sampling, field properties were measured and samples were collected for the analysis of dissolved solids, major constituents, nutrients, selected trace elements, and suspended-sediment concentrations. During selected samplings, supplemental samples were collected for the analysis of additional trace elements, organic carbon, and/or pesticides. Spatial variations of dissolved-solids, major-constituent, and nutrient data were analyzed. The report presents summary statistics for the monthly water-quality data by sampling site and background information on the drainage basin upstream from each site. Regression equations are presented that relate dissolved-solids, major-constituent, and nutrient concentrations to streamflow, selected field properties, and time. Median instantaneous streamflow at each basic-fixed site ranged from 1.4 to 1,380 cubic feet per second. Median specific conductance at each basic-fixed site ranged from 84 to 1,680 microsiemens per centimeter at 25 degrees Celsius, and median pH values ranged from 7.8 to 8.5. The water sampled at the basic-fixed sites generally was well oxygenated and had a median dissolved-oxygen percent of saturation range from 89 to 108. With the exception of Rio Grande above mouth of Trinchera Creek, near Lasauses, Colorado, dissolved-solids concentrations in the main stem of the Rio Grande generally increased in a downstream direction. This increase is from natural sources such as ground-water inflow and evapotranspiration and from anthropogenic sources such as irrigation- return flows, urban runoff, and wastewater-treatment plant discharges. The smallest median dissolved-solids concentration detected at a basic- fixed site was 58 milligrams per liter and the largest was 1,240 milligrams per liter. The spatial distribution of calcium, magnesium, sodium, sulfate, chloride, and fluoride was similar to the spatial distribution of dissolved solids. The spatial distribution of potassium and bicarbonate varied slightly from that of dissolved solids. Median silica concentrations generally decreased in a downstream direction. Of all cations, calcium and sodium had the largest concentrations at most basic-fixed sites. Bicarbonate and sulfate were the anions having the largest concentrations at most sites. The largest median silica concentration was at Rito de los Frijoles in Bandelier National Monument, New Mexico, where silica composed approximately 50 percent of the dissolved solids. The largest concentrations and largest median concentrations of dissolved-nutrient analytes were detected at Santa Fe River above Cochiti Lake, New Mexico, and Rio Grande at Isleta, New Mexico. The relatively large dissolved-nutrient concentrations at these sites probably were due to discharges from wastewater-treatment plants and urban runoff. The largest concentrations and largest median concentrations of total ammonia plus organic nitrogen and total phosphorus were detected at Rio Puerco near Bernardo, New Mexico. The largest concentrations of these nutrients at this site were associated with runoff from summer thunderstorms. Dissolved-iron concentrations ranged from censored concentrations to 914 micrograms per liter. Median dissolved-iron concentrations ranged from 3 to 160 micrograms per liter. Dissolved-manganese concentrations ranged from censored concent

The application of the geography census data in seismic hazard assessment

NASA Astrophysics Data System (ADS)

Yuan, Shen; Ying, Zhang

2017-04-01

Limited by basic data timeliness to earthquake emergency database in Sichuan province, after the earthquake disaster assessment results and the actual damage there is a certain gap. In 2015, Sichuan completed the province census for the first time which including topography, traffic, vegetation coverage, water area, desert and bare ground, traffic network, the census residents and facilities, geographical unit, geological hazard as well as the Lushan earthquake-stricken area's town planning construction and ecological environment restoration. On this basis, combining with the existing achievements of basic geographic information data and high resolution image data, supplemented by remote sensing image interpretation and geological survey, Carried out distribution and change situation of statistical analysis and information extraction for earthquake disaster hazard-affected body elements such as surface coverage, roads, structures infrastructure in Lushan county before 2013 after 2015. At the same time, achieved the transformation and updating from geographical conditions census data to earthquake emergency basic data through research their data type, structure and relationship. Finally, based on multi-source disaster information including hazard-affected body changed data and Lushan 7.0 magnitude earthquake CORS network coseismal displacement field, etc. obtaining intensity control points through information fusion. Then completed the seismic influence field correction and assessed earthquake disaster again through Sichuan earthquake relief headquarters technology platform. Compared the new assessment result，original assessment result and actual earthquake disaster loss which shows that the revised evaluation result is more close to the actual earthquake disaster loss. In the future can realize geographical conditions census data to earthquake emergency basic data's normalized updates, ensure the timeliness to earthquake emergency database meanwhile improve the accuracy of assessment of earthquake disaster constantly.

Theme network in thematic learning in elementary school

NASA Astrophysics Data System (ADS)

Ain, N.; Rahutami, R.

2018-05-01

This research aimed at developing a network of a theme in the textbook. The method used is evaluation and development method. The source of this research data is textbook of class IV with the theme of “Care for Living Creatures” and sub-theme "Lets Love Our Environment”. The results show that there is a discrepancy between basic competence and sub-themes. Such disagreement is due to an inadequacy of basic competencies with sub-themes, and the choice of basic competencies of less appropriate to sub-themes. The results of this study can be used to developing theme network on other sub-themes as well as on other levels.

A reliability analysis tool for SpaceWire network

NASA Astrophysics Data System (ADS)

Zhou, Qiang; Zhu, Longjiang; Fei, Haidong; Wang, Xingyou

2017-04-01

A SpaceWire is a standard for on-board satellite networks as the basis for future data-handling architectures. It is becoming more and more popular in space applications due to its technical advantages, including reliability, low power and fault protection, etc. High reliability is the vital issue for spacecraft. Therefore, it is very important to analyze and improve the reliability performance of the SpaceWire network. This paper deals with the problem of reliability modeling and analysis with SpaceWire network. According to the function division of distributed network, a reliability analysis method based on a task is proposed, the reliability analysis of every task can lead to the system reliability matrix, the reliability result of the network system can be deduced by integrating these entire reliability indexes in the matrix. With the method, we develop a reliability analysis tool for SpaceWire Network based on VC, where the computation schemes for reliability matrix and the multi-path-task reliability are also implemented. By using this tool, we analyze several cases on typical architectures. And the analytic results indicate that redundancy architecture has better reliability performance than basic one. In practical, the dual redundancy scheme has been adopted for some key unit, to improve the reliability index of the system or task. Finally, this reliability analysis tool will has a directive influence on both task division and topology selection in the phase of SpaceWire network system design.

Information spread in networks: Games, optimal control, and stabilization

NASA Astrophysics Data System (ADS)

Khanafer, Ali

This thesis focuses on designing efficient mechanisms for controlling information spread in networks. We consider two models for information spread. The first one is the well-known distributed averaging dynamics. The second model is a nonlinear one that describes virus spread in computer and biological networks. We seek to design optimal, robust, and stabilizing controllers under practical constraints. For distributed averaging networks, we study the interaction between a network designer and an adversary. We consider two types of attacks on the network. In Attack-I, the adversary strategically disconnects a set of links to prevent the nodes from reaching consensus. Meanwhile, the network designer assists the nodes in reaching consensus by changing the weights of a limited number of links in the network. We formulate two problems to describe this competition where the order in which the players act is reversed in the two problems. Although the canonical equations provided by the Pontryagin's Maximum Principle (MP) seem to be intractable, we provide an alternative characterization for the optimal strategies that makes connection to potential theory. Further, we provide a sufficient condition for the existence of a saddle-point equilibrium (SPE) for the underlying zero-sum game. In Attack-II, the designer and the adversary are both capable of altering the measurements of all nodes in the network by injecting global signals. We impose two constraints on both players: a power constraint and an energy constraint. We assume that the available energy to each player is not sufficient to operate at maximum power throughout the horizon of the game. We show the existence of an SPE and derive the optimal strategies in closed form for this attack scenario. As an alternative to the "network designer vs. adversary" framework, we investigate the possibility of stabilizing unknown network diffusion processes using a distributed mechanism, where the uncertainty is due to an attack on the network. To this end, we propose a distributed version of the classical logic-based supervisory control scheme. Given a network of agents whose dynamics contain unknown parameters, the distributed supervisory control scheme is used to assist the agents to converge to a certain set-point without requiring them to have explicit knowledge of that set-point. Unlike the classical supervisory control scheme where a centralized supervisor makes switching decisions among the candidate controllers, in our scheme, each agent is equipped with a local supervisor that switches among the available controllers. The switching decisions made at a certain agent depend only on the information from its neighboring agents. We provide sufficient conditions for stabilization and apply our framework to the distributed averaging problem in the presence of large modeling uncertainty. For infected networks, we study the stability properties of a susceptible-infected-susceptible (SIS) diffusion model, so-called the n-intertwined Markov model, over arbitrary network topologies. Similar to the majority of infection spread dynamics, this model exhibits a threshold phenomenon. When the curing rates in the network are high, the all-healthy state is the unique equilibrium over the network. Otherwise, an endemic equilibrium state emerges, where some infection remains within the network. Using notions from positive systems theory, we provide conditions for the global asymptotic stability of the equilibrium points in both cases over strongly and weakly connected directed networks based on the value of the basic reproduction number, a fundamental quantity in the study of epidemics. Furthermore, we demonstrate that the n-intertwined Markov model can be viewed as a best-response dynamical system of a concave game among the nodes. This characterization allows us to cast new infection spread dynamics; additionally, we provide a sufficient condition, for the global convergence to the all-healthy state, that can be checked in a distributed fashion. Moreover, we investigate the problem of stabilizing the network when the curing rates of a limited number of nodes can be controlled. In particular, we characterize the number of controllers required for a class of undirected graphs. We also design optimal controllers capable of minimizing the total infection in the network at minimum cost. Finally, we outline a set of open problems in the area of information spread control.

Performance analysis for IEEE 802.11 distributed coordination function in radio-over-fiber-based distributed antenna systems.

PubMed

Fan, Yuting; Li, Jianqiang; Xu, Kun; Chen, Hao; Lu, Xun; Dai, Yitang; Yin, Feifei; Ji, Yuefeng; Lin, Jintong

2013-09-09

In this paper, we analyze the performance of IEEE 802.11 distributed coordination function in simulcast radio-over-fiber-based distributed antenna systems (RoF-DASs) where multiple remote antenna units (RAUs) are connected to one wireless local-area network (WLAN) access point (AP) with different-length fiber links. We also present an analytical model to evaluate the throughput of the systems in the presence of both the inter-RAU hidden-node problem and fiber-length difference effect. In the model, the unequal delay induced by different fiber length is involved both in the backoff stage and in the calculation of Ts and Tc, which are the period of time when the channel is sensed busy due to a successful transmission or a collision. The throughput performances of WLAN-RoF-DAS in both basic access and request to send/clear to send (RTS/CTS) exchange modes are evaluated with the help of the derived model.

Network-based Modeling of Mesoscale Catchments - The Hydrology Perspective of Glowa-danube

NASA Astrophysics Data System (ADS)

Ludwig, R.; Escher-Vetter, H.; Hennicker, R.; Mauser, W.; Niemeyer, S.; Reichstein, M.; Tenhunen, J.

Within the GLOWA initiative of the German Ministry for Research and Educa- tion (BMBF), the project GLOWA-Danube is funded to establish a transdisciplinary network-based decision support tool for water related issues in the Upper Danube wa- tershed. It aims to develop and validate integration techniques, integrated models and integrated monitoring procedures and to implement them in the network-based De- cision Support System DANUBIA. An accurate description of processes involved in energy, water and matter fluxes and turnovers requires an intense collaboration and exchange of water related expertise of different scientific disciplines. DANUBIA is conceived as a distributed expert network and is developed on the basis of re-useable, refineable, and documented sub-models. In order to synthesize a common understand- ing between the project partners, a standardized notation of parameters and functions and a platform-independent structure of computational methods and interfaces has been established using the Unified Modeling Language UML. DANUBIA is object- oriented, spatially distributed and raster-based at its core. It applies the concept of "proxels" (Process Pixel) as its basic object, which has different dimensions depend- ing on the viewing scale and connects to its environment through fluxes. The presented study excerpts the hydrological view point of GLOWA-Danube, its approach of model coupling and network based communication (using the Remote Method Invocation RMI), the object-oriented technology to simulate physical processes and interactions at the land surface and the methodology to treat the issue of spatial and temporal scal- ing in large, heterogeneous catchments. The mechanisms applied to communicate data and model parameters across the typical discipline borders will be demonstrated from the perspective of a land-surface object, which comprises the capabilities of interde- pendent expert models for snowmelt, soil water movement, runoff formation, plant growth and radiation balance in a distributed JAVA-based modeling environment. The coupling to the adjacent physical objects of atmosphere, groundwater and river net- work will also be addressed.

Feedback control stabilization of critical dynamics via resource transport on multilayer networks: How glia enable learning dynamics in the brain

NASA Astrophysics Data System (ADS)

Virkar, Yogesh S.; Shew, Woodrow L.; Restrepo, Juan G.; Ott, Edward

2016-10-01

Learning and memory are acquired through long-lasting changes in synapses. In the simplest models, such synaptic potentiation typically leads to runaway excitation, but in reality there must exist processes that robustly preserve overall stability of the neural system dynamics. How is this accomplished? Various approaches to this basic question have been considered. Here we propose a particularly compelling and natural mechanism for preserving stability of learning neural systems. This mechanism is based on the global processes by which metabolic resources are distributed to the neurons by glial cells. Specifically, we introduce and study a model composed of two interacting networks: a model neural network interconnected by synapses that undergo spike-timing-dependent plasticity; and a model glial network interconnected by gap junctions that diffusively transport metabolic resources among the glia and, ultimately, to neural synapses where they are consumed. Our main result is that the biophysical constraints imposed by diffusive transport of metabolic resources through the glial network can prevent runaway growth of synaptic strength, both during ongoing activity and during learning. Our findings suggest a previously unappreciated role for glial transport of metabolites in the feedback control stabilization of neural network dynamics during learning.

Basic Skills Resource Center: Documentation and Phaseover Report for the Military Educators Resource NETWORK

DTIC Science & Technology

1985-01-01

narrative form. 111. Describe the subject of your request in 3 or 4 precise terms (e.g., reading skills , computer assisted instruction, adult literacy ...00 Research Product 85-03 L’C £ BASIC SKILLS RESOURCE CENTER: DOCUMENTATION AND PHASEOVER REPORT FOR THE MILITARY EDUCATORS RESOURCE NETWORK... SKILLS RESOURCE CENTER: DOCUMENTATION AND Interim Report PHLASEOVER REPORT FOR THE MILITARY EDUCATORS Feb 1982 - Sept 1984 RESOURCE NETWORK 6

The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Krishnan, J.; Mois, Kristina; Suwanmajo, Thapanar

2014-11-07

In this paper, we examine the behaviour of basic autocatalytic feedback modules involving a species catalyzing its own production, either directly or indirectly. We first perform a systematic study of the autocatalytic feedback module in isolation, examining the effect of different factors, showing how this module is capable of exhibiting monostable threshold and bistable switch-like behaviour. We then study the behaviour of this module embedded in different kinds of basic networks including (essentially) irreversible cycles, open and closed reversible chains, and networks with additional feedback. We study the behaviour of the networks deterministically and also stochastically, using simulations, analytical work,more » and bifurcation analysis. We find that (i) there are significant differences between the behaviour of this module in isolation and in a network: thresholds may be altered or destroyed and bistability may be destroyed or even induced, even when the ambient network is simple. The global characteristics and topology of this network and the position of the module in the ambient network can play important and unexpected roles. (ii) There can be important differences between the deterministic and stochastic dynamics of the module embedded in networks, which may be accentuated by the ambient network. This provides new insights into the functioning of such enzymatic modules individually and as part of networks, with relevance to other enzymatic signalling modules as well.« less

The behaviour of basic autocatalytic signalling modules in isolation and embedded in networks

NASA Astrophysics Data System (ADS)

Krishnan, J.; Mois, Kristina; Suwanmajo, Thapanar

2014-11-01

In this paper, we examine the behaviour of basic autocatalytic feedback modules involving a species catalyzing its own production, either directly or indirectly. We first perform a systematic study of the autocatalytic feedback module in isolation, examining the effect of different factors, showing how this module is capable of exhibiting monostable threshold and bistable switch-like behaviour. We then study the behaviour of this module embedded in different kinds of basic networks including (essentially) irreversible cycles, open and closed reversible chains, and networks with additional feedback. We study the behaviour of the networks deterministically and also stochastically, using simulations, analytical work, and bifurcation analysis. We find that (i) there are significant differences between the behaviour of this module in isolation and in a network: thresholds may be altered or destroyed and bistability may be destroyed or even induced, even when the ambient network is simple. The global characteristics and topology of this network and the position of the module in the ambient network can play important and unexpected roles. (ii) There can be important differences between the deterministic and stochastic dynamics of the module embedded in networks, which may be accentuated by the ambient network. This provides new insights into the functioning of such enzymatic modules individually and as part of networks, with relevance to other enzymatic signalling modules as well.

A Comparison of Techniques for Camera Selection and Hand-Off in a Video Network

NASA Astrophysics Data System (ADS)

Li, Yiming; Bhanu, Bir

Video networks are becoming increasingly important for solving many real-world problems. Multiple video sensors require collaboration when performing various tasks. One of the most basic tasks is the tracking of objects, which requires mechanisms to select a camera for a certain object and hand-off this object from one camera to another so as to accomplish seamless tracking. In this chapter, we provide a comprehensive comparison of current and emerging camera selection and hand-off techniques. We consider geometry-, statistics-, and game theory-based approaches and provide both theoretical and experimental comparison using centralized and distributed computational models. We provide simulation and experimental results using real data for various scenarios of a large number of cameras and objects for in-depth understanding of strengths and weaknesses of these techniques.

Ensuring sustainability of non-networked sanitation technologies: an approach to standardization.

PubMed

Starkl, Markus; Brunner, Norbert; Feil, Magdalena; Hauser, Andreas

2015-06-02

Non-networked sanitation technologies use no sewer, water or electricity lines. Based on a review of 45 commercially distributed technologies, 12 (representing three concepts) were selected for a detailed audit. They were located in six countries of Africa and Asia. The safety of users was generally assured and the costs per use were not excessive, whereas costs were fully transparent for only one technology surveyed. A main drawback was insufficient quality of the byproducts from on-site treatment, making recycling in agriculture a hygienic and environmental risk. Further, no technology was sufficiently mature (requiring e.g. to shift wastes by hand). In order to promote further development and give producers of mature products a competitive advantage, the paper proposes a certification of technologies to confirm the fulfillment of basic requirements to make them attractive for future users.

An analog neural hardware implementation using charge-injection multipliers and neutron-specific gain control.

PubMed

Massengill, L W; Mundie, D B

1992-01-01

A neural network IC based on a dynamic charge injection is described. The hardware design is space and power efficient, and achieves massive parallelism of analog inner products via charge-based multipliers and spatially distributed summing buses. Basic synaptic cells are constructed of exponential pulse-decay modulation (EPDM) dynamic injection multipliers operating sequentially on propagating signal vectors and locally stored analog weights. Individually adjustable gain controls on each neutron reduce the effects of limited weight dynamic range. A hardware simulator/trainer has been developed which incorporates the physical (nonideal) characteristics of actual circuit components into the training process, thus absorbing nonlinearities and parametric deviations into the macroscopic performance of the network. Results show that charge-based techniques may achieve a high degree of neural density and throughput using standard CMOS processes.

Biological and Environmental Research Network Requirements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balaji, V.; Boden, Tom; Cowley, Dave

2013-09-01

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements of the instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet be a highly successful enabler of scientific discovery for over 25 years. In November 2012, ESnet and the Office of Biological and Environmental Research (BER) of the DOE SC organizedmore » a review to characterize the networking requirements of the programs funded by the BER program office. Several key findings resulted from the review. Among them: 1) The scale of data sets available to science collaborations continues to increase exponentially. This has broad impact, both on the network and on the computational and storage systems connected to the network. 2) Many science collaborations require assistance to cope with the systems and network engineering challenges inherent in managing the rapid growth in data scale. 3) Several science domains operate distributed facilities that rely on high-performance networking for success. Key examples illustrated in this report include the Earth System Grid Federation (ESGF) and the Systems Biology Knowledgebase (KBase). This report expands on these points, and addresses others as well. The report contains a findings section as well as the text of the case studies discussed at the review.« less

Chinese lexical networks: The structure, function and formation

NASA Astrophysics Data System (ADS)

Li, Jianyu; Zhou, Jie; Luo, Xiaoyue; Yang, Zhanxin

2012-11-01

In this paper Chinese phrases are modeled using complex networks theory. We analyze statistical properties of the networks and find that phrase networks display some important features: not only small world and the power-law distribution, but also hierarchical structure and disassortative mixing. These statistical traits display the global organization of Chinese phrases. The origin and formation of such traits are analyzed from a macroscopic Chinese culture and philosophy perspective. It is interesting to find that Chinese culture and philosophy may shape the formation and structure of Chinese phrases. To uncover the structural design principles of networks, network motif patterns are studied. It is shown that they serve as basic building blocks to form the whole phrase networks, especially triad 38 (feed forward loop) plays a more important role in forming most of the phrases and other motifs. The distinct structure may not only keep the networks stable and robust, but also be helpful for information processing. The results of the paper can give some insight into Chinese language learning and language acquisition. It strengthens the idea that learning the phrases helps to understand Chinese culture. On the other side, understanding Chinese culture and philosophy does help to learn Chinese phrases. The hub nodes in the networks show the close relationship with Chinese culture and philosophy. Learning or teaching the hub characters, hub-linking phrases and phrases which are meaning related based on motif feature should be very useful and important for Chinese learning and acquisition.

Intervention in gene regulatory networks with maximal phenotype alteration.

PubMed

Yousefi, Mohammadmahdi R; Dougherty, Edward R

2013-07-15

A basic issue for translational genomics is to model gene interaction via gene regulatory networks (GRNs) and thereby provide an informatics environment to study the effects of intervention (say, via drugs) and to derive effective intervention strategies. Taking the view that the phenotype is characterized by the long-run behavior (steady-state distribution) of the network, we desire interventions to optimally move the probability mass from undesirable to desirable states Heretofore, two external control approaches have been taken to shift the steady-state mass of a GRN: (i) use a user-defined cost function for which desirable shift of the steady-state mass is a by-product and (ii) use heuristics to design a greedy algorithm. Neither approach provides an optimal control policy relative to long-run behavior. We use a linear programming approach to optimally shift the steady-state mass from undesirable to desirable states, i.e. optimization is directly based on the amount of shift and therefore must outperform previously proposed methods. Moreover, the same basic linear programming structure is used for both unconstrained and constrained optimization, where in the latter case, constraints on the optimization limit the amount of mass that may be shifted to 'ambiguous' states, these being states that are not directly undesirable relative to the pathology of interest but which bear some perceived risk. We apply the method to probabilistic Boolean networks, but the theory applies to any Markovian GRN. Supplementary materials, including the simulation results, MATLAB source code and description of suboptimal methods are available at http://gsp.tamu.edu/Publications/supplementary/yousefi13b. edward@ece.tamu.edu Supplementary data are available at Bioinformatics online.

Functional evolution of new and expanded attention networks in humans

PubMed Central

Patel, Gaurav H.; Yang, Danica; Jamerson, Emery C.; Snyder, Lawrence H.; Corbetta, Maurizio; Ferrera, Vincent P.

2015-01-01

Macaques are often used as a model system for invasive investigations of the neural substrates of cognition. However, 25 million years of evolution separate humans and macaques from their last common ancestor, and this has likely substantially impacted the function of the cortical networks underlying cognitive processes, such as attention. We examined the homology of frontoparietal networks underlying attention by comparing functional MRI data from macaques and humans performing the same visual search task. Although there are broad similarities, we found fundamental differences between the species. First, humans have more dorsal attention network areas than macaques, indicating that in the course of evolution the human attention system has expanded compared with macaques. Second, potentially homologous areas in the dorsal attention network have markedly different biases toward representing the contralateral hemifield, indicating that the underlying neural architecture of these areas may differ in the most basic of properties, such as receptive field distribution. Third, despite clear evidence of the temporoparietal junction node of the ventral attention network in humans as elicited by this visual search task, we did not find functional evidence of a temporoparietal junction in macaques. None of these differences were the result of differences in training, experimental power, or anatomical variability between the two species. The results of this study indicate that macaque data should be applied to human models of cognition cautiously, and demonstrate how evolution may shape cortical networks. PMID:26170314

Functional evolution of new and expanded attention networks in humans.

PubMed

Patel, Gaurav H; Yang, Danica; Jamerson, Emery C; Snyder, Lawrence H; Corbetta, Maurizio; Ferrera, Vincent P

2015-07-28

Macaques are often used as a model system for invasive investigations of the neural substrates of cognition. However, 25 million years of evolution separate humans and macaques from their last common ancestor, and this has likely substantially impacted the function of the cortical networks underlying cognitive processes, such as attention. We examined the homology of frontoparietal networks underlying attention by comparing functional MRI data from macaques and humans performing the same visual search task. Although there are broad similarities, we found fundamental differences between the species. First, humans have more dorsal attention network areas than macaques, indicating that in the course of evolution the human attention system has expanded compared with macaques. Second, potentially homologous areas in the dorsal attention network have markedly different biases toward representing the contralateral hemifield, indicating that the underlying neural architecture of these areas may differ in the most basic of properties, such as receptive field distribution. Third, despite clear evidence of the temporoparietal junction node of the ventral attention network in humans as elicited by this visual search task, we did not find functional evidence of a temporoparietal junction in macaques. None of these differences were the result of differences in training, experimental power, or anatomical variability between the two species. The results of this study indicate that macaque data should be applied to human models of cognition cautiously, and demonstrate how evolution may shape cortical networks.

HF Interference, Procedures and Tools (Interferences HF, procedures et outils)

DTIC Science & Technology

2007-06-01

Systems 3-2 3.1.2 Medium (MV) and Low Voltage (LV) Systems 3-4 3.1.3 Access Systems 3-5 3.1.4 In-House Systems 3-7 3.1.5 Technical Characteristics...Grounded Monopole Antenna Figure 2.3-3 Low Natural Noise Measured in Germany 2-15 Figure 2.3-4 Minimum Natural Noise Measured in Germany 1985 and in...arrows) Figure 3.1.1-2 Basic BPL System 3-3 Figure 3.1.2-1 Power Line TN-C-S Network 3-5 Figure 3.1.3-1 Usual Low Voltage Electricity Distribution

National Diffusion/Adoption Network: A First Year Formative Look. Final Report.

ERIC Educational Resources Information Center

Magi Educational Services, Inc., Port Chester, NY.

A basic function of the Diffusion/Adoption Network is to assist interested school districts in becoming aware of successfully demonstrated, innovative educational ideas, products, and programs; and in aquiring, through training, the competencies necessary to adopt or adapt a proven educational program. There are five basic components of the…

Emergence, evolution and scaling of online social networks.

PubMed

Wang, Le-Zhi; Huang, Zi-Gang; Rong, Zhi-Hai; Wang, Xiao-Fan; Lai, Ying-Cheng

2014-01-01

Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China) with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

Evidence for a bimodal distribution in human communication.

PubMed

Wu, Ye; Zhou, Changsong; Xiao, Jinghua; Kurths, Jürgen; Schellnhuber, Hans Joachim

2010-11-02

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc.

Evidence for a bimodal distribution in human communication

PubMed Central

Wu, Ye; Zhou, Changsong; Xiao, Jinghua; Kurths, Jürgen; Schellnhuber, Hans Joachim

2010-01-01

Interacting human activities underlie the patterns of many social, technological, and economic phenomena. Here we present clear empirical evidence from Short Message correspondence that observed human actions are the result of the interplay of three basic ingredients: Poisson initiation of tasks and decision making for task execution in individual humans as well as interaction among individuals. This interplay leads to new types of interevent time distribution, neither completely Poisson nor power-law, but a bimodal combination of them. We show that the events can be separated into independent bursts which are generated by frequent mutual interactions in short times following random initiations of communications in longer times by the individuals. We introduce a minimal model of two interacting priority queues incorporating the three basic ingredients which fits well the distributions using the parameters extracted from the empirical data. The model can also embrace a range of realistic social interacting systems such as e-mail and letter communications when taking the time scale of processing into account. Our findings provide insight into various human activities both at the individual and network level. Our analysis and modeling of bimodal activity in human communication from the viewpoint of the interplay between processes of different time scales is likely to shed light on bimodal phenomena in other complex systems, such as interevent times in earthquakes, rainfall, forest fire, and economic systems, etc. PMID:20959414

Computer Networks and Networking: A Primer.

ERIC Educational Resources Information Center

Collins, Mauri P.

1993-01-01

Provides a basic introduction to computer networks and networking terminology. Topics addressed include modems; the Internet; TCP/IP (Transmission Control Protocol/Internet Protocol); transmission lines; Internet Protocol numbers; network traffic; Fidonet; file transfer protocol (FTP); TELNET; electronic mail; discussion groups; LISTSERV; USENET;…

On the Optimum Architecture of the Biologically Inspired Hierarchical Temporal Memory Model Applied to the Hand-Written Digit Recognition

NASA Astrophysics Data System (ADS)

Štolc, Svorad; Bajla, Ivan

2010-01-01

In the paper we describe basic functions of the Hierarchical Temporal Memory (HTM) network based on a novel biologically inspired model of the large-scale structure of the mammalian neocortex. The focus of this paper is in a systematic exploration of possibilities how to optimize important controlling parameters of the HTM model applied to the classification of hand-written digits from the USPS database. The statistical properties of this database are analyzed using the permutation test which employs a randomization distribution of the training and testing data. Based on a notion of the homogeneous usage of input image pixels, a methodology of the HTM parameter optimization is proposed. In order to study effects of two substantial parameters of the architecture: the patch size and the overlap in more details, we have restricted ourselves to the single-level HTM networks. A novel method for construction of the training sequences by ordering series of the static images is developed. A novel method for estimation of the parameter maxDist based on the box counting method is proposed. The parameter sigma of the inference Gaussian is optimized on the basis of the maximization of the belief distribution entropy. Both optimization algorithms can be equally applied to the multi-level HTM networks as well. The influences of the parameters transitionMemory and requestedGroupCount on the HTM network performance have been explored. Altogether, we have investigated 2736 different HTM network configurations. The obtained classification accuracy results have been benchmarked with the published results of several conventional classifiers.

Basic Principles of Electrical Network Reliability Optimization in Liberalised Electricity Market

NASA Astrophysics Data System (ADS)

Oleinikova, I.; Krishans, Z.; Mutule, A.

2008-01-01

The authors propose to select long-term solutions to the reliability problems of electrical networks in the stage of development planning. The guide lines or basic principles of such optimization are: 1) its dynamical nature; 2) development sustainability; 3) integrated solution of the problems of network development and electricity supply reliability; 4) consideration of information uncertainty; 5) concurrent consideration of the network and generation development problems; 6) application of specialized information technologies; 7) definition of requirements for independent electricity producers. In the article, the major aspects of liberalized electricity market, its functions and tasks are reviewed, with emphasis placed on the optimization of electrical network development as a significant component of sustainable management of power systems.

Betweenness centrality and its applications from modeling traffic flows to network community detection

NASA Astrophysics Data System (ADS)

Ren, Yihui

As real-world complex networks are heterogeneous structures, not all their components such as nodes, edges and subgraphs carry the same role or importance in the functions performed by the networks: some elements are more critical than others. Understanding the roles of the components of a network is crucial for understanding the behavior of the network as a whole. One the most basic function of networks is transport; transport of vehicles/people, information, materials, forces, etc., and these quantities are transported along edges between source and destination nodes. For this reason, network path-based importance measures, also called centralities, play a crucial role in the understanding of the transport functions of the network and the network's structural and dynamical behavior in general. In this thesis we study the notion of betweenness centrality, which measures the fraction of lowest-cost (or shortest) paths running through a network component, in particular through a node or an edge. High betweenness centrality nodes/edges are those that will be frequently used by the entities transported through the network and thus they play a key role in the overall transport properties of the network. In the first part of the thesis we present a first-principles based method for traffic prediction using a cost-based generalization of the radiation model (emission/absorbtion model) for human mobility, coupled with a cost-minimizing algorithm for efficient distribution of the mobility fluxes through the network. Using US census and highway traffic data, we show that traffic can efficiently and accurately be computed from a range-limited, network betweenness type calculation. The model based on travel time costs captures the log-normal distribution of the traffic and attains a high Pearson correlation coefficient (0.75) when compared with real traffic. We then focus on studying the extent of changes in traffic flows in the wake of a localized damage or alteration to the network and we demonstrate that the changes can propagate globally, affecting traffic several hundreds of miles away. Because of its principled nature, this method can inform many applications related to human mobility driven flows in spatial networks, ranging from transportation, through urban planning to mitigation of the effects of catastrophic events. In the second part of the thesis we focus on network deconstruction and community detection problems, both intensely studied topics in network science, using a weighted betweenness centrality approach. We present an algorithm that solves both problems efficiently and accurately and demonstrate that on both benchmark networks and data networks.

Robust/optimal temperature profile control of a high-speed aerospace vehicle using neural networks.

PubMed

Yadav, Vivek; Padhi, Radhakant; Balakrishnan, S N

2007-07-01

An approximate dynamic programming (ADP)-based suboptimal neurocontroller to obtain desired temperature for a high-speed aerospace vehicle is synthesized in this paper. A 1-D distributed parameter model of a fin is developed from basic thermal physics principles. "Snapshot" solutions of the dynamics are generated with a simple dynamic inversion-based feedback controller. Empirical basis functions are designed using the "proper orthogonal decomposition" (POD) technique and the snapshot solutions. A low-order nonlinear lumped parameter system to characterize the infinite dimensional system is obtained by carrying out a Galerkin projection. An ADP-based neurocontroller with a dual heuristic programming (DHP) formulation is obtained with a single-network-adaptive-critic (SNAC) controller for this approximate nonlinear model. Actual control in the original domain is calculated with the same POD basis functions through a reverse mapping. Further contribution of this paper includes development of an online robust neurocontroller to account for unmodeled dynamics and parametric uncertainties inherent in such a complex dynamic system. A neural network (NN) weight update rule that guarantees boundedness of the weights and relaxes the need for persistence of excitation (PE) condition is presented. Simulation studies show that in a fairly extensive but compact domain, any desired temperature profile can be achieved starting from any initial temperature profile. Therefore, the ADP and NN-based controllers appear to have the potential to become controller synthesis tools for nonlinear distributed parameter systems.

Introducing high performance distributed logging service for ACS

NASA Astrophysics Data System (ADS)

Avarias, Jorge A.; López, Joao S.; Maureira, Cristián; Sommer, Heiko; Chiozzi, Gianluca

2010-07-01

The ALMA Common Software (ACS) is a software framework that provides the infrastructure for the Atacama Large Millimeter Array and other projects. ACS, based on CORBA, offers basic services and common design patterns for distributed software. Every properly built system needs to be able to log status and error information. Logging in a single computer scenario can be as easy as using fprintf statements. However, in a distributed system, it must provide a way to centralize all logging data in a single place without overloading the network nor complicating the applications. ACS provides a complete logging service infrastructure in which every log has an associated priority and timestamp, allowing filtering at different levels of the system (application, service and clients). Currently the ACS logging service uses an implementation of the CORBA Telecom Log Service in a customized way, using only a minimal subset of the features provided by the standard. The most relevant feature used by ACS is the ability to treat the logs as event data that gets distributed over the network in a publisher-subscriber paradigm. For this purpose the CORBA Notification Service, which is resource intensive, is used. On the other hand, the Data Distribution Service (DDS) provides an alternative standard for publisher-subscriber communication for real-time systems, offering better performance and featuring decentralized message processing. The current document describes how the new high performance logging service of ACS has been modeled and developed using DDS, replacing the Telecom Log Service. Benefits and drawbacks are analyzed. A benchmark is presented comparing the differences between the implementations.

Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms

DOE PAGES

Pesce, Lorenzo L.; Lee, Hyong C.; Hereld, Mark; ...

2013-01-01

Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. Addressing this problem directly via experiments is impossibly complex; thus, we have been developing and studying medium-large-scale simulations of detailed neuronal networks to guide us. Flexibility in the connection schemas and a complete description of the cortical tissue seem necessary for this purpose. In this paper we examine some of the basic issues encountered in these multiscale simulations. We have determinedmore » the detailed behavior of two such simulators on parallel computer systems. The observed memory and computation-time scaling behavior for a distributed memory implementation were very good over the range studied, both in terms of network sizes (2,000 to 400,000 neurons) and processor pool sizes (1 to 256 processors). Our simulations required between a few megabytes and about 150 gigabytes of RAM and lasted between a few minutes and about a week, well within the capability of most multinode clusters. Therefore, simulations of epileptic seizures on networks with millions of cells should be feasible on current supercomputers.« less

Network analysis of corticocortical connections reveals ventral and dorsal processing streams in mouse visual cortex

PubMed Central

Wang, Quanxin; Sporns, Olaf; Burkhalter, Andreas

2012-01-01

Much of the information used for visual perception and visually guided actions is processed in complex networks of connections within the cortex. To understand how this works in the normal brain and to determine the impact of disease, mice are promising models. In primate visual cortex, information is processed in a dorsal stream specialized for visuospatial processing and guided action and a ventral stream for object recognition. Here, we traced the outputs of 10 visual areas and used quantitative graph analytic tools of modern network science to determine, from the projection strengths in 39 cortical targets, the community structure of the network. We found a high density of the cortical graph that exceeded that previously shown in monkey. Each source area showed a unique distribution of projection weights across its targets (i.e. connectivity profile) that was well-fit by a lognormal function. Importantly, the community structure was strongly dependent on the location of the source area: outputs from medial/anterior extrastriate areas were more strongly linked to parietal, motor and limbic cortex, whereas lateral extrastriate areas were preferentially connected to temporal and parahippocampal cortex. These two subnetworks resemble dorsal and ventral cortical streams in primates, demonstrating that the basic layout of cortical networks is conserved across species. PMID:22457489

Smart photonic networks and computer security for image data

NASA Astrophysics Data System (ADS)

Campello, Jorge; Gill, John T.; Morf, Martin; Flynn, Michael J.

1998-02-01

Work reported here is part of a larger project on 'Smart Photonic Networks and Computer Security for Image Data', studying the interactions of coding and security, switching architecture simulations, and basic technologies. Coding and security: coding methods that are appropriate for data security in data fusion networks were investigated. These networks have several characteristics that distinguish them form other currently employed networks, such as Ethernet LANs or the Internet. The most significant characteristics are very high maximum data rates; predominance of image data; narrowcasting - transmission of data form one source to a designated set of receivers; data fusion - combining related data from several sources; simple sensor nodes with limited buffering. These characteristics affect both the lower level network design and the higher level coding methods.Data security encompasses privacy, integrity, reliability, and availability. Privacy, integrity, and reliability can be provided through encryption and coding for error detection and correction. Availability is primarily a network issue; network nodes must be protected against failure or routed around in the case of failure. One of the more promising techniques is the use of 'secret sharing'. We consider this method as a special case of our new space-time code diversity based algorithms for secure communication. These algorithms enable us to exploit parallelism and scalable multiplexing schemes to build photonic network architectures. A number of very high-speed switching and routing architectures and their relationships with very high performance processor architectures were studied. Indications are that routers for very high speed photonic networks can be designed using the very robust and distributed TCP/IP protocol, if suitable processor architecture support is available.

NASA GISS Surface Temperature (GISTEMP) Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmidt, G.; Ruedy, R.; Persin, A

The NASA GISS Surface Temperature (GISTEMP) analysis provides a measure of the changing global surface temperature with monthly resolution for the period since 1880, when a reasonably global distribution of meteorological stations was established. The input data that the GISTEMP Team use for the analysis, collected by many national meteorological services around the world, are the adjusted data of the Global Historical Climatology Network (GHCN) Vs. 3 (this represents a change from prior use of unadjusted Vs. 2 data) (Peterson and Vose, 1997 and 1998), United States Historical Climatology Network (USHCN) data, and SCAR (Scientific Committee on Antarctic Research) datamore » from Antarctic stations. Documentation of the basic analysis method is provided by Hansen et al. (1999), with several modifications described by Hansen et al. (2001). The GISS analysis is updated monthly, however CDIAC's presentation of the data here is updated annually.« less

A Global Repository for Planet-Sized Experiments and Observations

NASA Technical Reports Server (NTRS)

Williams, Dean; Balaji, V.; Cinquini, Luca; Denvil, Sebastien; Duffy, Daniel; Evans, Ben; Ferraro, Robert D.; Hansen, Rose; Lautenschlager, Michael; Trenham, Claire

2016-01-01

Working across U.S. federal agencies, international agencies, and multiple worldwide data centers, and spanning seven international network organizations, the Earth System Grid Federation (ESGF) allows users to access, analyze, and visualize data using a globally federated collection of networks, computers, and software. Its architecture employs a system of geographically distributed peer nodes that are independently administered yet united by common federation protocols and application programming interfaces (APIs). The full ESGF infrastructure has now been adopted by multiple Earth science projects and allows access to petabytes of geophysical data, including the Coupled Model Intercomparison Project (CMIP) output used by the Intergovernmental Panel on Climate Change assessment reports. Data served by ESGF not only include model output (i.e., CMIP simulation runs) but also include observational data from satellites and instruments, reanalyses, and generated images. Metadata summarize basic information about the data for fast and easy data discovery.

Applications of artificial neural networks (ANNs) in food science.

PubMed

Huang, Yiqun; Kangas, Lars J; Rasco, Barbara A

2007-01-01

Artificial neural networks (ANNs) have been applied in almost every aspect of food science over the past two decades, although most applications are in the development stage. ANNs are useful tools for food safety and quality analyses, which include modeling of microbial growth and from this predicting food safety, interpreting spectroscopic data, and predicting physical, chemical, functional and sensory properties of various food products during processing and distribution. ANNs hold a great deal of promise for modeling complex tasks in process control and simulation and in applications of machine perception including machine vision and electronic nose for food safety and quality control. This review discusses the basic theory of the ANN technology and its applications in food science, providing food scientists and the research community an overview of the current research and future trend of the applications of ANN technology in the field.

Modelling road accident blackspots data with the discrete generalized Pareto distribution.

PubMed

Prieto, Faustino; Gómez-Déniz, Emilio; Sarabia, José María

2014-10-01

This study shows how road traffic networks events, in particular road accidents on blackspots, can be modelled with simple probabilistic distributions. We considered the number of crashes and the number of fatalities on Spanish blackspots in the period 2003-2007, from Spanish General Directorate of Traffic (DGT). We modelled those datasets, respectively, with the discrete generalized Pareto distribution (a discrete parametric model with three parameters) and with the discrete Lomax distribution (a discrete parametric model with two parameters, and particular case of the previous model). For that, we analyzed the basic properties of both parametric models: cumulative distribution, survival, probability mass, quantile and hazard functions, genesis and rth-order moments; applied two estimation methods of their parameters: the μ and (μ+1) frequency method and the maximum likelihood method; used two goodness-of-fit tests: Chi-square test and discrete Kolmogorov-Smirnov test based on bootstrap resampling; and compared them with the classical negative binomial distribution in terms of absolute probabilities and in models including covariates. We found that those probabilistic models can be useful to describe the road accident blackspots datasets analyzed. Copyright © 2014 Elsevier Ltd. All rights reserved.

A reevaluation of the vestibulo-ocular reflex: new ideas of its purpose, properties, neural substrate, and disorders

NASA Technical Reports Server (NTRS)

Leigh, R. J.; Brandt, T.

1993-01-01

Conventional views of the vestibulo-ocular reflex (VOR) have emphasized testing with caloric stimuli and by passively rotating patients at low frequencies in a chair. The properties of the VOR tested under these conditions differ from the performance of this reflex during the natural function for which it evolved--locomotion. Only the VOR (and not visually mediated eye movements) can cope with the high-frequency angular and linear perturbations of the head that occur during locomotion; this is achieved by generating eye movements at short latency (< 16 msec). Interpretation of vestibular testing is enhanced by the realization that, although the di- and trisynaptic components of the VOR are essential for this short-latency response, the overall accuracy and plasticity of the VOR depend upon a distributed, parallel network of neurons involving the vestibular nuclei. Neurons in this network variously upon a distributed, parallel network of neurons involving the vestibular nuclei. Neurons in this network variously encode inputs from the labyrinthine semicircular canals and otoliths, as well as from the visual and somatosensory systems. The central vestibular pathways branch to contact vestibular cortex (for perception) and the spinal cord (for control of posture). Thus, the vestibular nuclei basically coordinate the stabilization of gaze and posture, and contribute to the perception of verticality and self-motion. Consequently, brainstem disorders that disrupt the VOR cause not just only nystagmus, but also instability of posture (eg, increased fore-aft sway in patients with downbeat nystagmus) and disturbance of spatial orientation (eg, tilt of the subjective visual vertical in Wallenberg's syndrome).

Using Pathfinder networks to discover alignment between expert and consumer conceptual knowledge from online vaccine content.

PubMed

Amith, Muhammad; Cunningham, Rachel; Savas, Lara S; Boom, Julie; Schvaneveldt, Roger; Tao, Cui; Cohen, Trevor

2017-10-01

This study demonstrates the use of distributed vector representations and Pathfinder Network Scaling (PFNETS) to represent online vaccine content created by health experts and by laypeople. By analyzing a target audience's conceptualization of a topic, domain experts can develop targeted interventions to improve the basic health knowledge of consumers. The underlying assumption is that the content created by different groups reflects the mental organization of their knowledge. Applying automated text analysis to this content may elucidate differences between the knowledge structures of laypeople (heath consumers) and professionals (health experts). This paper utilizes vaccine information generated by laypeople and health experts to investigate the utility of this approach. We used an established technique from cognitive psychology, Pathfinder Network Scaling to infer the structure of the associational networks between concepts learned from online content using methods of distributional semantics. In doing so, we extend the original application of PFNETS to infer knowledge structures from individual participants, to infer the prevailing knowledge structures within communities of content authors. The resulting graphs reveal opportunities for public health and vaccination education experts to improve communication and intervention efforts directed towards health consumers. Our efforts demonstrate the feasibility of using an automated procedure to examine the manifestation of conceptual models within large bodies of free text, revealing evidence of conflicting understanding of vaccine concepts among health consumers as compared with health experts. Additionally, this study provides insight into the differences between consumer and expert abstraction of domain knowledge, revealing vaccine-related knowledge gaps that suggest opportunities to improve provider-patient communication. Copyright © 2017 Elsevier Inc. All rights reserved.

The Gain of Resource Delegation in Distributed Computing Environments

NASA Astrophysics Data System (ADS)

Fölling, Alexander; Grimme, Christian; Lepping, Joachim; Papaspyrou, Alexander

In this paper, we address job scheduling in Distributed Computing Infrastructures, that is a loosely coupled network of autonomous acting High Performance Computing systems. In contrast to the common approach of mutual workload exchange, we consider the more intuitive operator's viewpoint of load-dependent resource reconfiguration. In case of a site's over-utilization, the scheduling system is able to lease resources from other sites to keep up service quality for its local user community. Contrary, the granting of idle resources can increase utilization in times of low local workload and thus ensure higher efficiency. The evaluation considers real workload data and is done with respect to common service quality indicators. For two simple resource exchange policies and three basic setups we show the possible gain of this approach and analyze the dynamics in workload-adaptive reconfiguration behavior.

Ground-water quality in the Santa Rita, Buellton, and Los Olivos hydrologic subareas of the Santa Ynez River basin, Santa Barbara County, California

USGS Publications Warehouse

Hamlin, S.N.

1985-01-01

Groundwater quality in the upper Santa Ynez River Valley in Santa Barbara County has degraded due to both natural and anthropogenic causes. The semiarid climate and uneven distribution of rainfall has limited freshwater recharge and caused salt buildup in water supplies. Tertiary rocks supply mineralized water. Agricultural activities (irrigation return flow containing fertilizers and pesticides, cultivation, feedlot waste disposal) are a primary cause of water quality degradation. Urban development, which also causes water quality degradation (introduced contaminants, wastewater disposal, septic system discharge, and land fill disposal of waste), has imposed stricter requirements on water supply quality. A well network was designed to monitor changes in groundwater quality related to anthropogenic activities. Information from this network may aid in efficient management of the groundwater basins as public water supplies, centered around three basic goals. First is to increase freshwater recharge to the basins by conjunctive surface/groundwater use and surface-spreading techniques. Second is to optimize groundwater discharge by efficient timing and spacing of pumping. Third is to control and reduce sources of groundwater contamination by regulating wastewater quality and distribution and, preferably, by exporting wastewaters from the basin. (USGS)

A bipartite graph of Neuroendocrine System

NASA Astrophysics Data System (ADS)

Guo, Zhong-Wei; Zou, Sheng-Rong; Peng, Yu-Jing; Zhou, Ta; Gu, Chang-Gui; He, Da-Ren

2008-03-01

We present an empirical investigation on the neuroendocrine system and suggest describe it by a bipartite graph. In the net the cells can be regarded as collaboration acts and the mediators can be regarded as collaboration actors. The act degree stands for the number of the cells that secrete a single mediator. Among them bFGF (the basic fibroblast growth factor) has the largest node act degree. It is the most important mitogenic cytokine, followed by TGF-beta, IL-6, IL1-beta, VEGF, IGF-1and so on. They are critical in neuroendocrine system to maintain bodily healthiness, emotional stabilization and endocrine harmony. The act degree distribution shows a shifted power law (SPL) function forms [1]. The average act degree of neuroendocrine network is h=3.01, It means that each mediator is secreted by three cells on average. The similarity, which stands for the average probability of secreting the same mediators by all neuroendocrine cells, is observed as s=0.14. Our results may be used in the research of the medical treatment of neuroendocrine diseases. [1] Assortativity and act degree distribution of some collaboration networks, Hui Chang, Bei-Bei Su, Yue-Ping Zhou, Daren He, Physica A, 383 (2007) 687-702

The equipment access software for a distributed UNIX-based accelerator control system

NASA Astrophysics Data System (ADS)

Trofimov, Nikolai; Zelepoukine, Serguei; Zharkov, Eugeny; Charrue, Pierre; Gareyte, Claire; Poirier, Hervé

1994-12-01

This paper presents a generic equipment access software package for a distributed control system using computers with UNIX or UNIX-like operating systems. The package consists of three main components, an application Equipment Access Library, Message Handler and Equipment Data Base. An application task, which may run in any computer in the network, sends requests to access equipment through Equipment Library calls. The basic request is in the form Equipment-Action-Data and is routed via a remote procedure call to the computer to which the given equipment is connected. In this computer the request is received by the Message Handler. According to the type of the equipment connection, the Message Handler either passes the request to the specific process software in the same computer or forwards it to a lower level network of equipment controllers using MIL1553B, GPIB, RS232 or BITBUS communication. The answer is then returned to the calling application. Descriptive information required for request routing and processing is stored in the real-time Equipment Data Base. The package has been written to be portable and is currently available on DEC Ultrix, LynxOS, HPUX, XENIX, OS-9 and Apollo domain.

Substation Reactive Power Regulation Strategy

NASA Astrophysics Data System (ADS)

Zhang, Junfeng; Zhang, Chunwang; Ma, Daqing

2018-01-01

With the increasing requirements on the power supply quality and reliability of distribution network, voltage and reactive power regulation of substations has become one of the indispensable ways to ensure voltage quality and reactive power balance and to improve the economy and reliability of distribution network. Therefore, it is a general concern of the current power workers and operators that what kind of flexible and effective control method should be used to adjust the on-load tap-changer (OLTC) transformer and shunt compensation capacitor in a substation to achieve reactive power balance in situ, improve voltage pass rate, increase power factor and reduce active power loss. In this paper, based on the traditional nine-zone diagram and combining with the characteristics of substation, a fuzzy variable-center nine-zone diagram control method is proposed and used to make a comprehensive regulation of substation voltage and reactive power. Through the calculation and simulation of the example, this method is proved to have satisfactorily reconciled the contradiction between reactive power and voltage in real-time control and achieved the basic goal of real-time control of the substation, providing a reference value to the practical application of the substation real-time control method.

Space station common module network topology and hardware development

NASA Technical Reports Server (NTRS)

Anderson, P.; Braunagel, L.; Chwirka, S.; Fishman, M.; Freeman, K.; Eason, D.; Landis, D.; Lech, L.; Martin, J.; Mccorkle, J.

1990-01-01

Conceptual space station common module power management and distribution (SSM/PMAD) network layouts and detailed network evaluations were developed. Individual pieces of hardware to be developed for the SSM/PMAD test bed were identified. A technology assessment was developed to identify pieces of equipment requiring development effort. Equipment lists were developed from the previously selected network schematics. Additionally, functional requirements for the network equipment as well as other requirements which affected the suitability of specific items for use on the Space Station Program were identified. Assembly requirements were derived based on the SSM/PMAD developed requirements and on the selected SSM/PMAD network concepts. Basic requirements and simplified design block diagrams are included. DC remote power controllers were successfully integrated into the DC Marshall Space Flight Center breadboard. Two DC remote power controller (RPC) boards experienced mechanical failure of UES 706 stud-mounted diodes during mechanical installation of the boards into the system. These broken diodes caused input to output shorting of the RPC's. The UES 706 diodes were replaced on these RPC's which eliminated the problem. The DC RPC's as existing in the present breadboard configuration do not provide ground fault protection because the RPC was designed to only switch the hot side current. If ground fault protection were to be implemented, it would be necessary to design the system so the RPC switched both the hot and the return sides of power.

CAN A NANOFLARE MODEL OF EXTREME-ULTRAVIOLET IRRADIANCES DESCRIBE THE HEATING OF THE SOLAR CORONA?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tajfirouze, E.; Safari, H.

2012-01-10

Nanoflares, the basic units of impulsive energy release, may produce much of the solar background emission. Extrapolation of the energy frequency distribution of observed microflares, which follows a power law to lower energies, can give an estimation of the importance of nanoflares for heating the solar corona. If the power-law index is greater than 2, then the nanoflare contribution is dominant. We model a time series of extreme-ultraviolet emission radiance as random flares with a power-law exponent of the flare event distribution. The model is based on three key parameters: the flare rate, the flare duration, and the power-law exponentmore » of the flare intensity frequency distribution. We use this model to simulate emission line radiance detected in 171 A, observed by Solar Terrestrial Relation Observatory/Extreme-Ultraviolet Imager and Solar Dynamics Observatory/Atmospheric Imaging Assembly. The observed light curves are matched with simulated light curves using an Artificial Neural Network, and the parameter values are determined across the active region, quiet Sun, and coronal hole. The damping rate of nanoflares is compared with the radiative losses cooling time. The effect of background emission, data cadence, and network sensitivity on the key parameters of the model is studied. Most of the observed light curves have a power-law exponent, {alpha}, greater than the critical value 2. At these sites, nanoflare heating could be significant.« less

Exploration in free word association networks: models and experiment.

PubMed

Ludueña, Guillermo A; Behzad, Mehran Djalali; Gros, Claudius

2014-05-01

Free association is a task that requires a subject to express the first word to come to their mind when presented with a certain cue. It is a task which can be used to expose the basic mechanisms by which humans connect memories. In this work, we have made use of a publicly available database of free associations to model the exploration of the averaged network of associations using a statistical and the adaptive control of thought-rational (ACT-R) model. We performed, in addition, an online experiment asking participants to navigate the averaged network using their individual preferences for word associations. We have investigated the statistics of word repetitions in this guided association task. We find that the considered models mimic some of the statistical properties, viz the probability of word repetitions, the distance between repetitions and the distribution of association chain lengths, of the experiment, with the ACT-R model showing a particularly good fit to the experimental data for the more intricate properties as, for instance, the ratio of repetitions per length of association chains.

Internet Basics. ERIC Digest.

ERIC Educational Resources Information Center

Tennant, Roy

The Internet is a worldwide network of computer networks. In the United States, the National Science Foundation Network (NSFNet) serves as the Internet "backbone" (a very high speed network that connects key regions across the country). The NSFNet will likely evolve into the National Research and Education Network (NREN) as defined in…

Cooperative Learning for Distributed In-Network Traffic Classification

NASA Astrophysics Data System (ADS)

Joseph, S. B.; Loo, H. R.; Ismail, I.; Andromeda, T.; Marsono, M. N.

2017-04-01

Inspired by the concept of autonomic distributed/decentralized network management schemes, we consider the issue of information exchange among distributed network nodes to network performance and promote scalability for in-network monitoring. In this paper, we propose a cooperative learning algorithm for propagation and synchronization of network information among autonomic distributed network nodes for online traffic classification. The results show that network nodes with sharing capability perform better with a higher average accuracy of 89.21% (sharing data) and 88.37% (sharing clusters) compared to 88.06% for nodes without cooperative learning capability. The overall performance indicates that cooperative learning is promising for distributed in-network traffic classification.

Network Basics.

ERIC Educational Resources Information Center

Tennant, Roy

1992-01-01

Explains how users can find and access information resources available on the Internet. Highlights include network information centers (NICs); lists, both formal and informal; computer networking protocols, including international standards; electronic mail; remote log-in; and file transfer. (LRW)

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

PubMed

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

2014-01-01

Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA) provides the necessary tool kit for investigating questions involving relational data. We introduce basic concepts in SNA, along with methods for data collection, data processing, and data analysis, using a previously collected example study on an undergraduate biology classroom as a tutorial. We conduct descriptive analyses of the structure of the network of costudying relationships. We explore generative processes that create observed study networks between students and also test for an association between network position and success on exams. We also cover practical issues, such as the unique aspects of human subjects review for network studies. Our aims are to convince readers that using SNA in classroom environments allows rich and informative analyses to take place and to provide some initial tools for doing so, in the process inspiring future educational studies incorporating relational data. © 2014 D. Z. Grunspan et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

Development of user guidelines for ECAS display design. Volume 2: Tasks 9 and 10. [educating the public to the benefits of spacelab and the space transportation system

NASA Technical Reports Server (NTRS)

Bathurst, D. B.

1979-01-01

Lay-oriented speakers aids, articles, a booklet, and a press kit were developed to inform the press and the general public with background information on the space transportation system, Spacelab, and Spacelab 1 experiments. Educational materials relating to solar-terrestrial physics and its potential benefits to mankind were also written. A basic network for distributing audiovisual and printed materials to regional secondary schools and universities was developed. Suggested scripts to be used with visual aids describing materials science and technology and astronomy and solar physics are presented.

High-Bandwidth Tactical-Network Data Analysis in a High-Performance-Computing (HPC) Environment: Device Status Data

DTIC Science & Technology

2015-09-01

Figures iv List of Tables iv 1. Introduction 1 2. Device Status Data 1 2.1 SNMP 1 2.2 NMS 1 2.3 ICMP Ping 2 3. Data Collection 2 4. Hydra ...Configuration 3 4.1 Status Codes 4 4.2 Request Time 5 4.3 Hydra BLOb Metadata 6 5. Data Processing 6 5.1 Hydra Data Processing Framework 6 5.1.1...Basic Components 6 5.1.2 Map Component 7 5.1.3 Postmap Methods 8 5.1.4 Data Flow 9 5.1.5 Distributed Processing Considerations 9 5.2 Specific Hydra

Detecting hierarchical levels of connectivity in a population of Acacia tortilis at the northern edge of the species' global distribution: Combining classical population genetics and network analyses.

PubMed

Rodger, Yael S; Greenbaum, Gili; Silver, Micha; Bar-David, Shirli; Winters, Gidon

2018-01-01

Genetic diversity and structure of populations at the edge of the species' spatial distribution are important for potential adaptation to environmental changes and consequently, for the long-term survival of the species. Here, we combined classical population genetic methods with newly developed network analyses to gain complementary insights into the genetic structure and diversity of Acacia tortilis, a keystone desert tree, at the northern edge of its global distribution, where the population is under threat from climatic, ecological, and anthropogenic changes. We sampled A. tortilis from 14 sites along the Dead Sea region and the Arava Valley in Israel and in Jordan. In addition, we obtained samples from Egypt and Sudan, the hypothesized origin of the species. Samples from all sites were genotyped using six polymorphic microsatellite loci.Our results indicate a significant genetic structure in A. tortilis along the Arava Valley. This was detected at different hierarchical levels-from the basic unit of the subpopulation, corresponding to groups of trees within ephemeral rivers (wadis), to groups of subpopulations (communities) that are genetically more connected relative to others. The latter structure mostly corresponds to the partition of the major drainage basins in the area. Network analyses, combined with classical methods, allowed for the identification of key A. tortilis subpopulations in this region, characterized by their relatively high level of genetic diversity and centrality in maintaining gene flow in the population. Characterizing such key subpopulations may enable conservation managers to focus their efforts on certain subpopulations that might be particularly important for the population's long-term persistence, thus contributing to species conservation within its peripheral range.

A multihop key agreement scheme for wireless ad hoc networks based on channel characteristics.

PubMed

Hao, Zhuo; Zhong, Sheng; Yu, Nenghai

2013-01-01

A number of key agreement schemes based on wireless channel characteristics have been proposed recently. However, previous key agreement schemes require that two nodes which need to agree on a key are within the communication range of each other. Hence, they are not suitable for multihop wireless networks, in which nodes do not always have direct connections with each other. In this paper, we first propose a basic multihop key agreement scheme for wireless ad hoc networks. The proposed basic scheme is resistant to external eavesdroppers. Nevertheless, this basic scheme is not secure when there exist internal eavesdroppers or Man-in-the-Middle (MITM) adversaries. In order to cope with these adversaries, we propose an improved multihop key agreement scheme. We show that the improved scheme is secure against internal eavesdroppers and MITM adversaries in a single path. Both performance analysis and simulation results demonstrate that the improved scheme is efficient. Consequently, the improved key agreement scheme is suitable for multihop wireless ad hoc networks.

A Multihop Key Agreement Scheme for Wireless Ad Hoc Networks Based on Channel Characteristics

PubMed Central

Yu, Nenghai

2013-01-01

A number of key agreement schemes based on wireless channel characteristics have been proposed recently. However, previous key agreement schemes require that two nodes which need to agree on a key are within the communication range of each other. Hence, they are not suitable for multihop wireless networks, in which nodes do not always have direct connections with each other. In this paper, we first propose a basic multihop key agreement scheme for wireless ad hoc networks. The proposed basic scheme is resistant to external eavesdroppers. Nevertheless, this basic scheme is not secure when there exist internal eavesdroppers or Man-in-the-Middle (MITM) adversaries. In order to cope with these adversaries, we propose an improved multihop key agreement scheme. We show that the improved scheme is secure against internal eavesdroppers and MITM adversaries in a single path. Both performance analysis and simulation results demonstrate that the improved scheme is efficient. Consequently, the improved key agreement scheme is suitable for multihop wireless ad hoc networks. PMID:23766725

An Expedient Study on Back-Propagation (BPN) Neural Networks for Modeling Automated Evaluation of the Answers and Progress of Deaf Students' That Possess Basic Knowledge of the English Language and Computer Skills

NASA Astrophysics Data System (ADS)

Vrettaros, John; Vouros, George; Drigas, Athanasios S.

This article studies the expediency of using neural networks technology and the development of back-propagation networks (BPN) models for modeling automated evaluation of the answers and progress of deaf students' that possess basic knowledge of the English language and computer skills, within a virtual e-learning environment. The performance of the developed neural models is evaluated with the correlation factor between the neural networks' response values and the real value data as well as the percentage measurement of the error between the neural networks' estimate values and the real value data during its training process and afterwards with unknown data that weren't used in the training process.

A Guide to Networking for K-12 Schools.

ERIC Educational Resources Information Center

Northwest Regional Educational Lab., Portland, OR.

The purpose of this guide is to provide basic networking information and planning assistance for technology coordinators and others involved in building networks for K-12 schools. The information in this guide focuses on the first few steps in the networking process. It reviews planning considerations and network design issues facing educators who…

Dynamic Uncertain Causality Graph for Knowledge Representation and Probabilistic Reasoning: Directed Cyclic Graph and Joint Probability Distribution.

PubMed

Zhang, Qin

2015-07-01

Probabilistic graphical models (PGMs) such as Bayesian network (BN) have been widely applied in uncertain causality representation and probabilistic reasoning. Dynamic uncertain causality graph (DUCG) is a newly presented model of PGMs, which can be applied to fault diagnosis of large and complex industrial systems, disease diagnosis, and so on. The basic methodology of DUCG has been previously presented, in which only the directed acyclic graph (DAG) was addressed. However, the mathematical meaning of DUCG was not discussed. In this paper, the DUCG with directed cyclic graphs (DCGs) is addressed. In contrast, BN does not allow DCGs, as otherwise the conditional independence will not be satisfied. The inference algorithm for the DUCG with DCGs is presented, which not only extends the capabilities of DUCG from DAGs to DCGs but also enables users to decompose a large and complex DUCG into a set of small, simple sub-DUCGs, so that a large and complex knowledge base can be easily constructed, understood, and maintained. The basic mathematical definition of a complete DUCG with or without DCGs is proved to be a joint probability distribution (JPD) over a set of random variables. The incomplete DUCG as a part of a complete DUCG may represent a part of JPD. Examples are provided to illustrate the methodology.

Enhancing Basic Skill Levels of Marketing and Distributive Education Students Identified as Disadvantaged--A Tutorial Approach. Final Report, July 1, 1980-June 30, 1981.

ERIC Educational Resources Information Center

Wells, Randall L.

A project was undertaken to enhance the basic skill levels of marketing and distributive education students identified as disadvantaged by using a tutorial approach. After determining the basic skill competencies needed for students to succeed in marketing and distributive education, project staff identified existing materials in the areas of math…

Dynamics of epidemic spreading model with drug-resistant variation on scale-free networks

NASA Astrophysics Data System (ADS)

Wan, Chen; Li, Tao; Zhang, Wu; Dong, Jing

2018-03-01

Considering the influence of the virus' drug-resistant variation, a novel SIVRS (susceptible-infected-variant-recovered-susceptible) epidemic spreading model with variation characteristic on scale-free networks is proposed in this paper. By using the mean-field theory, the spreading dynamics of the model is analyzed in detail. Then, the basic reproductive number R0 and equilibriums are derived. Studies show that the existence of disease-free equilibrium is determined by the basic reproductive number R0. The relationships between the basic reproductive number R0, the variation characteristic and the topology of the underlying networks are studied in detail. Furthermore, our studies prove the global stability of the disease-free equilibrium, the permanence of epidemic and the global attractivity of endemic equilibrium. Numerical simulations are performed to confirm the analytical results.

Network complexity as a measure of information processing across resting-state networks: evidence from the Human Connectome Project

PubMed Central

McDonough, Ian M.; Nashiro, Kaoru

2014-01-01

An emerging field of research focused on fluctuations in brain signals has provided evidence that the complexity of those signals, as measured by entropy, conveys important information about network dynamics (e.g., local and distributed processing). While much research has focused on how neural complexity differs in populations with different age groups or clinical disorders, substantially less research has focused on the basic understanding of neural complexity in populations with young and healthy brain states. The present study used resting-state fMRI data from the Human Connectome Project (Van Essen et al., 2013) to test the extent that neural complexity in the BOLD signal, as measured by multiscale entropy (1) would differ from random noise, (2) would differ between four major resting-state networks previously associated with higher-order cognition, and (3) would be associated with the strength and extent of functional connectivity—a complementary method of estimating information processing. We found that complexity in the BOLD signal exhibited different patterns of complexity from white, pink, and red noise and that neural complexity was differentially expressed between resting-state networks, including the default mode, cingulo-opercular, left and right frontoparietal networks. Lastly, neural complexity across all networks was negatively associated with functional connectivity at fine scales, but was positively associated with functional connectivity at coarse scales. The present study is the first to characterize neural complexity in BOLD signals at a high temporal resolution and across different networks and might help clarify the inconsistencies between neural complexity and functional connectivity, thus informing the mechanisms underlying neural complexity. PMID:24959130

Acceptance of mixed scientific and clinical activities in a sub-speciality urology meeting.

PubMed

Buchholz, Noor N P; El Howairis, Mohammed El Fatih; Durner, Leopold; Harry, Damiete; Kachrilas, Stefanos; Rodgers, Allen L; Hakenberg, Oliver

2015-04-01

Basic urolithiasis research into the causes for stone formation has been stagnating for a long time. Emergence of effective stone treatment modalities has shifted the public and clinicians' focus away from basic research towards symptomatic treatment solutions. This has occurred in spite of urolithiasis being a highly recurrent disease with an enormous socio-economic impact warranting a prophylactic and recurrence-preventing approach. An integrated, multidisciplinary translational platform has been developed in the form of urolithiasis meetings bringing together urologists, radiologists, nephrologists, basic scientists, dieticians and other stake holders interested in stone disease, for an exchange of knowledge, mutual education and understanding, and professional networking. Traditionally, such combined meetings are split into sessions addressing the specific interests of clinicians and scientists. At the recent Experts in Stone Disease Symposium we devised and implemented a program which mixed clinical and basic science activities throughout. We interviewed delegates between sessions regarding their acceptance of this novel concept using a standardized questionnaire. Sessions were well-attended, alleviating our initial anxiety that delegates would not appreciate a "no-choice" program. Of the 74 delegates who were interviewed, 60 (81%) were urologists, and 14 (19%) were non-urologists such as nephrologists, dieticians, and students. This is representative of the overall distribution of delegates at the conference. 71% felt that a closer co-operation and understanding between clinicians and scientists will ultimately benefit both groups, as well as patients; 95% found the mixed session approach beneficial, with half appreciating it as very good and innovative; 94% believed that they had derived useful learnings from the "other side"; 94% found that such mixed sessions are useful for their future work and understanding of the urolithiasis field as a whole; 94% agreed that mixed meetings of this type are useful in enhancing networking between the different stake holders in urolithiasis treatment and research. Finally, 85% would like to visit future mixed session meetings, and 89% would encourage their juniors to attend, too. Not only was a platform created to facilitate multidisciplinary exchange and networking, but delegates from several different backgrounds were encouraged to attend presentations in disciplines other than their own. The results of our survey confirm an overwhelmingly positive acceptance of this integrated multidisciplinary concept for stone meetings. As such, we are encouraged to continue with this concept in future conferences.

Analysis of critical operating conditions for LV distribution networks with microgrids

NASA Astrophysics Data System (ADS)

Zehir, M. A.; Batman, A.; Sonmez, M. A.; Font, A.; Tsiamitros, D.; Stimoniaris, D.; Kollatou, T.; Bagriyanik, M.; Ozdemir, A.; Dialynas, E.

2016-11-01

Increase in the penetration of Distributed Generation (DG) in distribution networks, raises the risk of voltage limit violations while contributing to line losses. Especially in low voltage (LV) distribution networks (secondary distribution networks), impacts of active power flows on the bus voltages and on the network losses are more dominant. As network operators must meet regulatory limitations, they have to take into account the most critical operating conditions in their systems. In this study, it is aimed to present the impact of the worst operation cases of LV distribution networks comprising microgrids. Simulation studies are performed on a field data-based virtual test-bed. The simulations are repeated for several cases consisting different microgrid points of connection with different network loading and microgrid supply/demand conditions.

Revisiting the destination ranking procedure in development of an Intervening Opportunities Model for public transit trip distribution

NASA Astrophysics Data System (ADS)

Nazem, Mohsen; Trépanier, Martin; Morency, Catherine

2015-01-01

An Enhanced Intervening Opportunities Model (EIOM) is developed for Public Transit (PT). This is a distribution supply dependent model, with single constraints on trip production for work trips during morning peak hours (6:00 a.m.-9:00 a.m.) within the Island of Montreal, Canada. Different data sets, including the 2008 Origin-Destination (OD) survey of the Greater Montreal Area, the 2006 Census of Canada, GTFS network data, along with the geographical data of the study area, are used. EIOM is a nonlinear model composed of socio-demographics, PT supply data and work location attributes. An enhanced destination ranking procedure is used to calculate the number of spatially cumulative opportunities, the basic variable of EIOM. For comparison, a Basic Intervening Opportunities Model (BIOM) is developed by using the basic destination ranking procedure. The main difference between EIOM and BIOM is in the destination ranking procedure: EIOM considers the maximization of a utility function composed of PT Level Of Service and number of opportunities at the destination, along with the OD trip duration, whereas BIOM is based on a destination ranking derived only from OD trip durations. Analysis confirmed that EIOM is more accurate than BIOM. This study presents a new tool for PT analysts, planners and policy makers to study the potential changes in PT trip patterns due to changes in socio-demographic characteristics, PT supply, and other factors. Also it opens new opportunities for the development of more accurate PT demand models with new emergent data such as smart card validations.

Quid pro quo: a mechanism for fair collaboration in networked systems.

PubMed

Santos, Agustín; Fernández Anta, Antonio; López Fernández, Luis

2013-01-01

Collaboration may be understood as the execution of coordinated tasks (in the most general sense) by groups of users, who cooperate for achieving a common goal. Collaboration is a fundamental assumption and requirement for the correct operation of many communication systems. The main challenge when creating collaborative systems in a decentralized manner is dealing with the fact that users may behave in selfish ways, trying to obtain the benefits of the tasks but without participating in their execution. In this context, Game Theory has been instrumental to model collaborative systems and the task allocation problem, and to design mechanisms for optimal allocation of tasks. In this paper, we revise the classical assumptions of these models and propose a new approach to this problem. First, we establish a system model based on heterogenous nodes (users, players), and propose a basic distributed mechanism so that, when a new task appears, it is assigned to the most suitable node. The classical technique for compensating a node that executes a task is the use of payments (which in most networks are hard or impossible to implement). Instead, we propose a distributed mechanism for the optimal allocation of tasks without payments. We prove this mechanism to be robust evenevent in the presence of independent selfish or rationally limited players. Additionally, our model is based on very weak assumptions, which makes the proposed mechanisms susceptible to be implemented in networked systems (e.g., the Internet).

Probing and exploiting the chaotic dynamics of a hydrodynamic photochemical oscillator to implement all the basic binary logic functions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hayashi, Kenta; Department of Chemistry, Biology, and Biotechnology, University of Perugia, 06123 Perugia; Gotoda, Hiroshi

2016-05-15

The convective motions within a solution of a photochromic spiro-oxazine being irradiated by UV only on the bottom part of its volume, give rise to aperiodic spectrophotometric dynamics. In this paper, we study three nonlinear properties of the aperiodic time series: permutation entropy, short-term predictability and long-term unpredictability, and degree distribution of the visibility graph networks. After ascertaining the extracted chaotic features, we show how the aperiodic time series can be exploited to implement all the fundamental two-inputs binary logic functions (AND, OR, NAND, NOR, XOR, and XNOR) and some basic arithmetic operations (half-adder, full-adder, half-subtractor). This is possible duemore » to the wide range of states a nonlinear system accesses in the course of its evolution. Therefore, the solution of the convective photochemical oscillator results in hardware for chaos-computing alternative to conventional complementary metal-oxide semiconductor-based integrated circuits.« less

Reconfigurable logic via gate controlled domain wall trajectory in magnetic network structure

PubMed Central

Murapaka, C.; Sethi, P.; Goolaup, S.; Lew, W. S.

2016-01-01

An all-magnetic logic scheme has the advantages of being non-volatile and energy efficient over the conventional transistor based logic devices. In this work, we present a reconfigurable magnetic logic device which is capable of performing all basic logic operations in a single device. The device exploits the deterministic trajectory of domain wall (DW) in ferromagnetic asymmetric branch structure for obtaining different output combinations. The programmability of the device is achieved by using a current-controlled magnetic gate, which generates a local Oersted field. The field generated at the magnetic gate influences the trajectory of the DW within the structure by exploiting its inherent transverse charge distribution. DW transformation from vortex to transverse configuration close to the output branch plays a pivotal role in governing the DW chirality and hence the output. By simply switching the current direction through the magnetic gate, two universal logic gate functionalities can be obtained in this device. Using magnetic force microscopy imaging and magnetoresistance measurements, all basic logic functionalities are demonstrated. PMID:26839036

Collaboration and decision making tools for mobile groups

NASA Astrophysics Data System (ADS)

Abrahamyan, Suren; Balyan, Serob; Ter-Minasyan, Harutyun; Degtyarev, Alexander

2017-12-01

Nowadays the use of distributed collaboration tools is widespread in many areas of people activity. But lack of mobility and certain equipment-dependency creates difficulties and decelerates development and integration of such technologies. Also mobile technologies allow individuals to interact with each other without need of traditional office spaces and regardless of location. Hence, realization of special infrastructures on mobile platforms with help of ad-hoc wireless local networks could eliminate hardware-attachment and be useful also in terms of scientific approach. Solutions from basic internet-messengers to complex software for online collaboration equipment in large-scale workgroups are implementations of tools based on mobile infrastructures. Despite growth of mobile infrastructures, applied distributed solutions in group decisionmaking and e-collaboration are not common. In this article we propose software complex for real-time collaboration and decision-making based on mobile devices, describe its architecture and evaluate performance.

Sparse distributed memory and related models

NASA Technical Reports Server (NTRS)

Kanerva, Pentti

1992-01-01

Described here is sparse distributed memory (SDM) as a neural-net associative memory. It is characterized by two weight matrices and by a large internal dimension - the number of hidden units is much larger than the number of input or output units. The first matrix, A, is fixed and possibly random, and the second matrix, C, is modifiable. The SDM is compared and contrasted to (1) computer memory, (2) correlation-matrix memory, (3) feet-forward artificial neural network, (4) cortex of the cerebellum, (5) Marr and Albus models of the cerebellum, and (6) Albus' cerebellar model arithmetic computer (CMAC). Several variations of the basic SDM design are discussed: the selected-coordinate and hyperplane designs of Jaeckel, the pseudorandom associative neural memory of Hassoun, and SDM with real-valued input variables by Prager and Fallside. SDM research conducted mainly at the Research Institute for Advanced Computer Science (RIACS) in 1986-1991 is highlighted.

ISTP CDF Skeleton Editor

NASA Technical Reports Server (NTRS)

Chimiak, Reine; Harris, Bernard; Williams, Phillip

2013-01-01

Basic Common Data Format (CDF) tools (e.g., cdfedit) provide no specific support for creating International Solar-Terrestrial Physics/Space Physics Data Facility (ISTP/SPDF) standard files. While it is possible for someone who is familiar with the ISTP/SPDF metadata guidelines to create compliant files using just the basic tools, the process is error-prone and unreasonable for someone without ISTP/SPDF expertise. The key problem is the lack of a tool with specific support for creating files that comply with the ISTP/SPDF guidelines. There are basic CDF tools such as cdfedit and skeletoncdf for creating CDF files, but these have no specific support for creating ISTP/ SPDF compliant files. The SPDF ISTP CDF skeleton editor is a cross-platform, Java-based GUI editor program that allows someone with only a basic understanding of the ISTP/SPDF guidelines to easily create compliant files. The editor is a simple graphical user interface (GUI) application for creating and editing ISTP/SPDF guideline-compliant skeleton CDF files. The SPDF ISTP CDF skeleton editor consists of the following components: A swing-based Java GUI program, JavaHelp-based manual/ tutorial, Image/Icon files, and HTML Web page for distribution. The editor is available as a traditional Java desktop application as well as a Java Network Launching Protocol (JNLP) application. Once started, it functions like a typical Java GUI file editor application for creating/editing application-unique files.

40 CFR 51.353 - Network type and program evaluation.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 2 2011-07-01 2011-07-01 false Network type and program evaluation. 51... Requirements § 51.353 Network type and program evaluation. Basic and enhanced I/M programs can be centralized.... (a) Presumptive equivalency. A decentralized network consisting of stations that only perform...

Environmental Design for a Structured Network Learning Society

ERIC Educational Resources Information Center

Chang, Ben; Cheng, Nien-Heng; Deng, Yi-Chan; Chan, Tak-Wai

2007-01-01

Social interactions profoundly impact the learning processes of learners in traditional societies. The rapid rise of the Internet using population has been the establishment of numerous different styles of network communities. Network societies form when more Internet communities are established, but the basic form of a network society, especially…

Voltage regulation in distribution networks with distributed generation

NASA Astrophysics Data System (ADS)

Blažič, B.; Uljanić, B.; Papič, I.

2012-11-01

The paper deals with the topic of voltage regulation in distribution networks with relatively high distributed energy resources (DER) penetration. The problem of voltage rise is described and different options for voltage regulation are given. The influence of DER on voltage profile and the effectiveness of the investigated solutions are evaluated by means of simulation in DIgSILENT. The simulated network is an actual distribution network in Slovenia with a relatively high penetration of distributed generation. Recommendations for voltage control in networks with DER penetration are given at the end.

Systemic risk and spatiotemporal dynamics of the consumer market of China

NASA Astrophysics Data System (ADS)

Wang, Minggang; Tian, Lixin; Xu, Hua; Li, Weiyu; Du, Ruijin; Dong, Gaogao; Wang, Jie; Gu, Jiani

2017-05-01

The consumer price index (CPI) contains rich information of the consumer market, in order to characterize the essential characteristics of the consumer market of China, a novel method by using complex network theory is proposed to visualizing the evolution and transformation characteristics of correlated modes among the regional consumer markets. CPI data of 31 provinces and cities of China are selected as sample data. Underlying dynamics of time-evolving correlation networks are revealed. A formula to measure the systemic risk in the consumer market is designed. And the correlation modes transmission network of the regional consumer markets is obtained. Numerical simulations show that the consumer market network has co-movement, group-occurring and small-word property. Different regions played different roles in the consumer market of China. The risk in the consumer market presented a decreasing trend from April 2013 but remain at the high level. Different from the stochastic system, the consumer market of China both has the short-range correlation and the long-range correlation. The strength of correlation modes transmission network basically satisfies a power-law distribution. The correlation modes are transferred into each other conveniently, although the consumer market system is highly complicated. The transformation of the correlation patterns of the regional consumer markets mainly revolves around three core correlation modes and each transformation needs to undergo 4 non-core modes.

An Introduction to Neural Networks for Hearing Aid Noise Recognition.

ERIC Educational Resources Information Center

Kim, Jun W.; Tyler, Richard S.

1995-01-01

This article introduces the use of multilayered artificial neural networks in hearing aid noise recognition. It reviews basic principles of neural networks, and offers an example of an application in which a neural network is used to identify the presence or absence of noise in speech. The ability of neural networks to "learn" the…

Distribution of shortest cycle lengths in random networks

NASA Astrophysics Data System (ADS)

Bonneau, Haggai; Hassid, Aviv; Biham, Ofer; Kühn, Reimer; Katzav, Eytan

2017-12-01

We present analytical results for the distribution of shortest cycle lengths (DSCL) in random networks. The approach is based on the relation between the DSCL and the distribution of shortest path lengths (DSPL). We apply this approach to configuration model networks, for which analytical results for the DSPL were obtained before. We first calculate the fraction of nodes in the network which reside on at least one cycle. Conditioning on being on a cycle, we provide the DSCL over ensembles of configuration model networks with degree distributions which follow a Poisson distribution (Erdős-Rényi network), degenerate distribution (random regular graph), and a power-law distribution (scale-free network). The mean and variance of the DSCL are calculated. The analytical results are found to be in very good agreement with the results of computer simulations.

Active distribution network planning considering linearized system loss

NASA Astrophysics Data System (ADS)

Li, Xiao; Wang, Mingqiang; Xu, Hao

2018-02-01

In this paper, various distribution network planning techniques with DGs are reviewed, and a new distribution network planning method is proposed. It assumes that the location of DGs and the topology of the network are fixed. The proposed model optimizes the capacities of DG and the optimal distribution line capacity simultaneously by a cost/benefit analysis and the benefit is quantified by the reduction of the expected interruption cost. Besides, the network loss is explicitly analyzed in the paper. For simplicity, the network loss is appropriately simplified as a quadratic function of difference of voltage phase angle. Then it is further piecewise linearized. In this paper, a piecewise linearization technique with different segment lengths is proposed. To validate its effectiveness and superiority, the proposed distribution network planning model with elaborate linearization technique is tested on the IEEE 33-bus distribution network system.

Strawman Philosophical Guide for Developing International Network of GPM GV Sites

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2005-01-01

The creation of an international network of ground validation (GV) sites that will support the Global Precipitation Measurement (GPM) Mission's international science programme will require detailed planning of mechanisms for exchanging technical information, GV data products, and scientific results. An important component of the planning will be the philosophical guide under which the network will grow and emerge as a successful element of the GPM Mission. This philosophical guide should be able to serve the mission in developing scientific pathways for ground validation research which will ensure the highest possible quality measurement record of global precipitation products. The philosophical issues, in this regard, partly stem from the financial architecture under which the GV network will be developed, i.e., each participating country will provide its own financial support through committed institutions -- regardless of whether a national or international space agency is involved.At the 1st International GPM Ground Validation Workshop held in Abingdon, UK in November-2003, most of the basic tenants behind the development of the international GV network were identified and discussed. Therefore, with this progress in mind, this presentation is intended to put forth a strawman philosophical guide supporting the development of the international network of GPM GV sites, noting that the initial progress has been reported in the Proceedings of the 1st International GPM GV Workshop -- available online. The central philosophical issues themselves, all flow from the fact that each participating institution can only bring to the table, GV facilities and scientific personnel that are affordable to the sanctioning (funding) national agency (be that a research, research-support, or operational agency). This situation imposes on the network, heterogeneity in the measuring sensors, data collection periods, data collection procedures, data latencies, and data reporting capabilities. Therefore, in order for the network to be effective in supporting the central scientific goals of the GPM mission, there must be a basic agreed upon doctrine under which the network participants function vis-a-vis: (1) an overriding set of general scientific requirements, (2) a minimal set of policies governing the free flow of GV data between the scientific participants, (3) a few basic definitions concerning the prioritization of measurements and their respective value to the mission, (4) a few basic procedures concerning data formats, data reporting procedures, data access, and data archiving, and (5) a simple means to differentiate GV sites according to their level of effort and ability to perform near real-time data acquisition - data reporting tasks. Most important, in case they choose to operate as a near real-time data collection-data distribution site, they would be expected to operate under a fairly narrowly defined protocol needed to ensure smooth GV support operations. This presentation will suggest measures responsive to items (1) - (5) from which to proceed,. In addition, this presentation will seek to stimulate discussion and debate concerning how much heterogeneity is tolerable within the eventual GV site network, given that the any individual GV site can only be considered scientifically useful if it supports the achievement of the central GPM Mission goals. Only ground validation research that has a direct connection to the space mission should be considered justifiable given the overarching scientific goals of the mission. Therefore each site will have to seek some level of accommodation to what the GPM Mission requires in the way of retrieval error characterization, retrieval error detection and reporting, and generation of GV data products that support assessment and improvement of the mission's standard precipitation retrieval algorithms. These are all important scientific issues that will be best resolved in open scientific debate.

Learning spatially coherent properties of the visual world in connectionist networks

NASA Astrophysics Data System (ADS)

Becker, Suzanna; Hinton, Geoffrey E.

1991-10-01

In the unsupervised learning paradigm, a network of neuron-like units is presented with an ensemble of input patterns from a structured environment, such as the visual world, and learns to represent the regularities in that input. The major goal in developing unsupervised learning algorithms is to find objective functions that characterize the quality of the network's representation without explicitly specifying the desired outputs of any of the units. The sort of objective functions considered cause a unit to become tuned to spatially coherent features of visual images (such as texture, depth, shading, and surface orientation), by learning to predict the outputs of other units which have spatially adjacent receptive fields. Simulations show that using an information-theoretic algorithm called IMAX, a network can be trained to represent depth by observing random dot stereograms of surfaces with continuously varying disparities. Once a layer of depth-tuned units has developed, subsequent layers are trained to perform surface interpolation of curved surfaces, by learning to predict the depth of one image region based on depth measurements in surrounding regions. An extension of the basic model allows a population of competing neurons to learn a distributed code for disparity, which naturally gives rise to a representation of discontinuities.

A Model of Mental State Transition Network

NASA Astrophysics Data System (ADS)

Xiang, Hua; Jiang, Peilin; Xiao, Shuang; Ren, Fuji; Kuroiwa, Shingo

Emotion is one of the most essential and basic attributes of human intelligence. Current AI (Artificial Intelligence) research is concentrating on physical components of emotion, rarely is it carried out from the view of psychology directly(1). Study on the model of artificial psychology is the first step in the development of human-computer interaction. As affective computing remains unpredictable, creating a reasonable mental model becomes the primary task for building a hybrid system. A pragmatic mental model is also the fundament of some key topics such as recognition and synthesis of emotions. In this paper a Mental State Transition Network Model(2) is proposed to detect human emotions. By a series of psychological experiments, we present a new way to predict coming human's emotions depending on the various current emotional states under various stimuli. Besides, people in different genders and characters are taken into consideration in our investigation. According to the psychological experiments data derived from 200 questionnaires, a Mental State Transition Network Model for describing the transitions in distribution among the emotions and relationships between internal mental situations and external are concluded. Further more the coefficients of the mental transition network model were achieved. Comparing seven relative evaluating experiments, an average precision rate of 0.843 is achieved using a set of samples for the proposed model.

Spreading dynamics of an e-commerce preferential information model on scale-free networks

NASA Astrophysics Data System (ADS)

Wan, Chen; Li, Tao; Guan, Zhi-Hong; Wang, Yuanmei; Liu, Xiongding

2017-02-01

In order to study the influence of the preferential degree and the heterogeneity of underlying networks on the spread of preferential e-commerce information, we propose a novel susceptible-infected-beneficial model based on scale-free networks. The spreading dynamics of the preferential information are analyzed in detail using the mean-field theory. We determine the basic reproductive number and equilibria. The theoretical analysis indicates that the basic reproductive number depends mainly on the preferential degree and the topology of the underlying networks. We prove the global stability of the information-elimination equilibrium. The permanence of preferential information and the global attractivity of the information-prevailing equilibrium are also studied in detail. Some numerical simulations are presented to verify the theoretical results.

Representativeness of four precipitation observational networks of China

NASA Astrophysics Data System (ADS)

Ren, Yuyu; Ren, Guoyu

2012-08-01

Four precipitation observational networks with varied station densities are maintained in China. They are: the Global Climate Observation System (GCOS) Surface Network (GSN), the national Reference Climate Network (RCN), the national Basic Meteorological Network (BMN), and the national Ordinary Meteorological Network (OMN). The GSN, RCN, BMN, and the merged network of RCN and BMN (R&B) have been widely used in climatology and climate change studies. In this paper, the impact of the usage of different networks on the precipitation climatology of China is evaluated by using the merged dataset of All Station Network (ASN) as a benchmark. The results show that all networks can capture the main features of the country average precipitation and its changing trends. The differences of average annual precipitation of the various networks from that of the ASN are less than 50 mm (⩽ 10%). All networks can successfully detect the rising trend of the average annual precipitation during 1961-2009, with the R&B exhibiting the best representativeness (only 2.90% relative difference) and the GSN the poorest (39.77%). As to the change trends of country average monthly precipitation, the networks can be ranked in descending order as R&B (1.27%), RCN (2.35%), BMN (4.17%), and GSN (7.46%), and larger relative differences appear from August to November. The networks produce quite consistent spatial patterns of annual precipitation change trends, and all show an increasing trend of precipitation in Northwest and Southeast China, and a decreasing trend in North China, Northeast China, and parts of central China. However, the representativeness of the BMN and R&B are better in annual and seasonal precipitation trends, in spite of the fact that they are still far from satisfactory. The relative differences of trends in some months and regions even reach more than 50%. The results also show that the representativeness of the RCN for country average precipitation is higher than that of the BMN because the RCN has a more homogeneous distribution of stations.

Evaluation of QoS supported in Network Mobility NEMO environments

NASA Astrophysics Data System (ADS)

Hussien, L. F.; Abdalla, A. H.; Habaebi, M. H.; Khalifa, O. O.; Hassan, W. H.

2013-12-01

Network mobility basic support (NEMO BS) protocol is an entire network, roaming as a unit which changes its point of attachment to the Internet and consequently its reachability in the network topology. NEMO BS doesn't provide QoS guarantees to its users same as traditional Internet IP and Mobile IPv6 as well. Typically, all the users will have same level of services without considering about their application requirements. This poses a problem to real-time applications that required QoS guarantees. To gain more effective control of the network, incorporated QoS is needed. Within QoS-enabled network the traffic flow can be distributed to various priorities. Also, the network bandwidth and resources can be allocated to different applications and users. Internet Engineering Task Force (IETF) working group has proposed several QoS solutions for static network such as IntServ, DiffServ and MPLS. These QoS solutions are designed in the context of a static environment (i.e. fixed hosts and networks). However, they are not fully adapted to mobile environments. They essentially demands to be extended and adjusted to meet up various challenges involved in mobile environments. With existing QoS mechanisms many proposals have been developed to provide QoS for individual mobile nodes (i.e. host mobility). In contrary, research based on the movement of the whole mobile network in IPv6 is still undertaking by the IETF working groups (i.e. network mobility). Few researches have been done in the area of providing QoS for roaming networks. Therefore, this paper aims to review and investigate (previous /and current) related works that have been developed to provide QoS in mobile network. Consequently, a new proposed scheme will be introduced to enhance QoS within NEMO environment, achieving by which seamless mobility to users of mobile network node (MNN).

The Implementation and Results of the Academic Administration System in the Center for Education Quality Development Network under the Jurisdiction of the Office of the Basic Education Commission of Thailand

ERIC Educational Resources Information Center

Ruanglae, Phumiphat; Sirisuthi, Chaiyuth; Weangsamoot, Visoot

2017-01-01

This purpose of this study was twofold. The researcher aimed to investigate the implementation results of the academic administration system in the Center for Education Quality Development Network under the jurisdiction of the Office of the Basic Education Commission of Thailand and to design the Actions Research which can be effectively utilized…

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

Evaluation model of distribution network development based on ANP and grey correlation analysis

NASA Astrophysics Data System (ADS)

Ma, Kaiqiang; Zhan, Zhihong; Zhou, Ming; Wu, Qiang; Yan, Jun; Chen, Genyong

2018-06-01

The existing distribution network evaluation system cannot scientifically and comprehensively reflect the distribution network development status. Furthermore, the evaluation model is monotonous and it is not suitable for horizontal analysis of many regional power grids. For these reason, this paper constructs a set of universal adaptability evaluation index system and model of distribution network development. Firstly, distribution network evaluation system is set up by power supply capability, power grid structure, technical equipment, intelligent level, efficiency of the power grid and development benefit of power grid. Then the comprehensive weight of indices is calculated by combining the AHP with the grey correlation analysis. Finally, the index scoring function can be obtained by fitting the index evaluation criterion to the curve, and then using the multiply plus operator to get the result of sample evaluation. The example analysis shows that the model can reflect the development of distribution network and find out the advantages and disadvantages of distribution network development. Besides, the model provides suggestions for the development and construction of distribution network.

Ultrasensitive response motifs: basic amplifiers in molecular signalling networks

PubMed Central

Zhang, Qiang; Bhattacharya, Sudin; Andersen, Melvin E.

2013-01-01

Multi-component signal transduction pathways and gene regulatory circuits underpin integrated cellular responses to perturbations. A recurring set of network motifs serve as the basic building blocks of these molecular signalling networks. This review focuses on ultrasensitive response motifs (URMs) that amplify small percentage changes in the input signal into larger percentage changes in the output response. URMs generally possess a sigmoid input–output relationship that is steeper than the Michaelis–Menten type of response and is often approximated by the Hill function. Six types of URMs can be commonly found in intracellular molecular networks and each has a distinct kinetic mechanism for signal amplification. These URMs are: (i) positive cooperative binding, (ii) homo-multimerization, (iii) multistep signalling, (iv) molecular titration, (v) zero-order covalent modification cycle and (vi) positive feedback. Multiple URMs can be combined to generate highly switch-like responses. Serving as basic signal amplifiers, these URMs are essential for molecular circuits to produce complex nonlinear dynamics, including multistability, robust adaptation and oscillation. These dynamic properties are in turn responsible for higher-level cellular behaviours, such as cell fate determination, homeostasis and biological rhythm. PMID:23615029

Packets Distributing Evolutionary Algorithm Based on PSO for Ad Hoc Network

NASA Astrophysics Data System (ADS)

Xu, Xiao-Feng

2018-03-01

Wireless communication network has such features as limited bandwidth, changeful channel and dynamic topology, etc. Ad hoc network has lots of difficulties in accessing control, bandwidth distribution, resource assign and congestion control. Therefore, a wireless packets distributing Evolutionary algorithm based on PSO (DPSO)for Ad Hoc Network is proposed. Firstly, parameters impact on performance of network are analyzed and researched to obtain network performance effective function. Secondly, the improved PSO Evolutionary Algorithm is used to solve the optimization problem from local to global in the process of network packets distributing. The simulation results show that the algorithm can ensure fairness and timeliness of network transmission, as well as improve ad hoc network resource integrated utilization efficiency.

Measuring Networking as an Outcome Variable in Undergraduate Research Experiences

PubMed Central

Hanauer, David I.; Hatfull, Graham

2015-01-01

The aim of this paper is to propose, present, and validate a simple survey instrument to measure student conversational networking. The tool consists of five items that cover personal and professional social networks, and its basic principle is the self-reporting of degrees of conversation, with a range of specific discussion partners. The networking instrument was validated in three studies. The basic psychometric characteristics of the scales were established by conducting a factor analysis and evaluating internal consistency using Cronbach’s alpha. The second study used a known-groups comparison and involved comparing outcomes for networking scales between two different undergraduate laboratory courses (one involving a specific effort to enhance networking). The final study looked at potential relationships between specific networking items and the established psychosocial variable of project ownership through a series of binary logistic regressions. Overall, the data from the three studies indicate that the networking scales have high internal consistency (α = 0.88), consist of a unitary dimension, can significantly differentiate between research experiences with low and high networking designs, and are related to project ownership scales. The ramifications of the networking instrument for student retention, the enhancement of public scientific literacy, and the differentiation of laboratory courses are discussed. PMID:26538387

Networking Course Syllabus in Accredited Library and Information Science Programs: A Comparative Analysis Study

ERIC Educational Resources Information Center

Abouserie, Hossam Eldin Mohamed Refaat

2009-01-01

The study investigated networking courses offered in accredited Library and Information Science schools in the United States in 2009. The study analyzed and compared network syllabi according to Course Syllabus Evaluation Rubric to obtain in-depth understanding of basic features and characteristics of networking courses taught. The study embraced…

SNAP: A computer program for generating symbolic network functions

NASA Technical Reports Server (NTRS)

Lin, P. M.; Alderson, G. E.

1970-01-01

The computer program SNAP (symbolic network analysis program) generates symbolic network functions for networks containing R, L, and C type elements and all four types of controlled sources. The program is efficient with respect to program storage and execution time. A discussion of the basic algorithms is presented, together with user's and programmer's guides.

Traffic Driven Analysis of Cellular and WiFi Networks

ERIC Educational Resources Information Center

Paul, Utpal Kumar

2012-01-01

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

Analysis on Voltage Profile of Distribution Network with Distributed Generation

NASA Astrophysics Data System (ADS)

Shao, Hua; Shi, Yujie; Yuan, Jianpu; An, Jiakun; Yang, Jianhua

2018-02-01

Penetration of distributed generation has some impacts on a distribution network in load flow, voltage profile, reliability, power loss and so on. After the impacts and the typical structures of the grid-connected distributed generation are analyzed, the back/forward sweep method of the load flow calculation of the distribution network is modelled including distributed generation. The voltage profiles of the distribution network affected by the installation location and the capacity of distributed generation are thoroughly investigated and simulated. The impacts on the voltage profiles are summarized and some suggestions to the installation location and the capacity of distributed generation are given correspondingly.

A TCP/IP framework for ethernet-based measurement, control and experiment data distribution

NASA Astrophysics Data System (ADS)

Ocaya, R. O.; Minny, J.

2010-11-01

A complete modular but scalable TCP/IP based scientific instrument control and data distribution system has been designed and realized. The system features an IEEE 802.3 compliant 10 Mbps Medium Access Controller (MAC) and Physical Layer Device that is suitable for the full-duplex monitoring and control of various physically widespread measurement transducers in the presence of a local network infrastructure. The cumbersomeness of exchanging and synchronizing data between the various transducer units using physical storage media led to the choice of TCP/IP as a logical alternative. The system and methods developed are scalable for broader usage over the Internet. The system comprises a PIC18f2620 and ENC28j60 based hardware and a software component written in C, Java/Javascript and Visual Basic.NET programming languages for event-level monitoring and browser user-interfaces respectively. The system exchanges data with the host network through IPv4 packets requested and received on a HTTP page. It also responds to ICMP echo, UDP and ARP requests through a user selectable integrated DHCP and static IPv4 address allocation scheme. The round-trip time, throughput and polling frequency are estimated and reported. A typical application to temperature monitoring and logging is also presented.

The Central and Eastern U.S. Seismic Network: Legacy of USArray

NASA Astrophysics Data System (ADS)

Eakins, J. A.; Astiz, L.; Benz, H.; Busby, R. W.; Hafner, K.; Reyes, J. C.; Sharer, G.; Vernon, F.; Woodward, R.

2014-12-01

As the USArray Transportable Array entered the central and eastern United States, several Federal agencies (National Science Foundation, U.S. Geological Survey, U.S. Nuclear Regulatory Commission, and Department of Energy) recognized the unique opportunity to retain TA stations beyond the original timeline. The mission of the CEUSN is to produce data that enables researchers and Federal agencies alike to better understand the basic geologic questions, background earthquake rates and distribution, seismic hazard potential, and associated societal risks of this region. The selected long-term sub-array from Transportable Array (TA) stations includes nearly 200 sites, complemented by 100 broadband stations from the existing regional seismic networks to form the Central and Eastern United States Network (CEUSN). Multiple criteria for site selection were weighed by an inter-agency TA Station Selection (TASS) Working Group: seismic noise characteristics, data availability in real time, proximity to nuclear power plants, and homogeneous distribution throughout the region. The Array Network Facility (ANF) started collecting data for CEUSN network stations since late 2013, with all stations collected since May 2014. Regional seismic data streams are collected in real-time from the IRIS Data Management Center (DMC). TA stations selected to be part of CEUSN, retain the broadband sensor to which a 100 sps channel is added, the infrasound and environmental channels, and, at some stations, accelerometers are deployed. The upgraded sites become part of the N4 network for which ANF provides metadata and can issue remote commands to the station equipment. Stations still operated by TA, but planned for CEUSN, are included in the virtual network so all stations are currently available now. By the end of 2015, the remaining TA stations will be upgraded. Data quality control procedures developed for TA stations at ANF and at the DMC are currently performed on N4 data. However, teleseismic and regional events are only picked a few times a month to fulfill data quality checks on the data. The assembled CEUSN data sets can be requested from the DMC with the _CEUSN virtual network code. Acknowledgments to Seismic Regional Network Operators: C. Ammon, J. Ebel, D. Doser, R. Hermann, A. Holland, W-Y. Kim, C. Langston, T. Owens, and M. Withers.

Traffic Profiling in Wireless Sensor Networks

DTIC Science & Technology

2006-12-01

components, that can be used for traffic profiling and monitoring of a wireless sensor network . The work demostrates how the IDS should capture and...observed and analyzed. Finally, initial indications from basic analysis of wireless sensor network traffic demonstrated a high degree of self-similarity.

Impacts on the Voltage Profile of DC Distribution Network with DG Access

NASA Astrophysics Data System (ADS)

Tu, J. J.; Yin, Z. D.

2017-07-01

With the development of electronic, more and more distributed generations (DGs) access into grid and cause the research fever of direct current (DC) distribution network. Considering distributed generation (DG) location and capacity have great impacts on voltage profile, so use IEEE9 and IEEE33 typical circuit as examples, with DGs access in centralized and decentralized mode, to compare voltage profile in alternating and direct current (AC/DC) distribution network. Introducing the voltage change ratio as an evaluation index, so gets the general results on voltage profile of DC distributed network with DG access. Simulation shows that, in the premise of reasonable location and capacity, DC distribution network is more suitable for DG access.

Impact of Machine Virtualization on Timing Precision for Performance-critical Tasks

NASA Astrophysics Data System (ADS)

Karpov, Kirill; Fedotova, Irina; Siemens, Eduard

2017-07-01

In this paper we present a measurement study to characterize the impact of hardware virtualization on basic software timing, as well as on precise sleep operations of an operating system. We investigated how timer hardware is shared among heavily CPU-, I/O- and Network-bound tasks on a virtual machine as well as on the host machine. VMware ESXi and QEMU/KVM have been chosen as commonly used examples of hypervisor- and host-based models. Based on statistical parameters of retrieved distributions, our results provide a very good estimation of timing behavior. It is essential for real-time and performance-critical applications such as image processing or real-time control.

Research on key technology of planning and design for AC/DC hybrid distribution network

NASA Astrophysics Data System (ADS)

Shen, Yu; Wu, Guilian; Zheng, Huan; Deng, Junpeng; Shi, Pengjia

2018-04-01

With the increasing demand of DC generation and DC load, the development of DC technology, AC and DC distribution network integrating will become an important form of future distribution network. In this paper, the key technology of planning and design for AC/DC hybrid distribution network is proposed, including the selection of AC and DC voltage series, the design of typical grid structure and the comprehensive evaluation method of planning scheme. The research results provide some ideas and directions for the future development of AC/DC hybrid distribution network.

Constructing a Graph Database for Semantic Literature-Based Discovery.

PubMed

Hristovski, Dimitar; Kastrin, Andrej; Dinevski, Dejan; Rindflesch, Thomas C

2015-01-01

Literature-based discovery (LBD) generates discoveries, or hypotheses, by combining what is already known in the literature. Potential discoveries have the form of relations between biomedical concepts; for example, a drug may be determined to treat a disease other than the one for which it was intended. LBD views the knowledge in a domain as a network; a set of concepts along with the relations between them. As a starting point, we used SemMedDB, a database of semantic relations between biomedical concepts extracted with SemRep from Medline. SemMedDB is distributed as a MySQL relational database, which has some problems when dealing with network data. We transformed and uploaded SemMedDB into the Neo4j graph database, and implemented the basic LBD discovery algorithms with the Cypher query language. We conclude that storing the data needed for semantic LBD is more natural in a graph database. Also, implementing LBD discovery algorithms is conceptually simpler with a graph query language when compared with standard SQL.

Structure of alkali tellurite glasses from neutron diffraction and molecular orbital calculations

NASA Astrophysics Data System (ADS)

Niida, Haruki; Uchino, Takashi; Jin, Jisun; Kim, Sae-Hoon; Fukunaga, Toshiharu; Yoko, Toshinobu

2001-01-01

The structure of pure TeO2 and alkali tellurite glasses has been examined by neutron diffraction and ab initio molecular orbital methods. The experimental radial distribution functions along with the calculated results have demonstrated that the basic structural units in tellurite glasses change from highly strained TeO4 trigonal bipyramids to more regular TeO3 trigonal pyramids with increasing alkali content. It has also been shown that the TeO3 trigonal pyramids do not exist in the form of isolated units in the glass network but interact with each other to form intertrigonal Te⋯O linkages. The present results suggest that nonbridging oxygen (NBO) atoms in tellurite glasses do not exist in their "pure" form; that is, all the NBO atoms in TeO3 trigonal bipyramids will interact with the first- and/or second-neighbor Te atoms, resulting in the three-dimensional continuous random network even in tellurite glasses with over 30 mol % of alkali oxides.

A Mars environmental survey (MESUR) - Feasibility of a low cost global approach

NASA Technical Reports Server (NTRS)

Hubbard, G. S.; Wercinski, Paul F.; Sarver, George L.; Hanel, Robert P.; Ramos, Ruben

1991-01-01

In situ measurements of Mars' surface and atmosphere are the objectives of a novel network mission concept called the Mars Environmental SURvey (MESUR). As envisioned, the MESUR mission will emplace a pole-to-pole global distribution of 16 landers on the Martian surface over three launch opportunites using medium-lift (Delta-class) launch vehicles. The basic concept is to deploy small free-flying probes which would directly enter the Martian atmosphere, measure the upper atmospheric structure, image the local terrain before landing, and survive landing to perform meteorology, seismology, surface imaging, and soil chemistry measurements. Data will be returned via dedicated relay orbiter or direct-to-earth transmission. The mission philosophy is to: (1) 'grow' a network over a period of years using a series of launch opportunities; (2) develop a level-of-effort which is flexible and responsive to a broad set of objectives; (3) focus on Mars science while providing a solid basis for future human presence; and (4) minimize overall project cost and complexity wherever possible.

The spectral positioning algorithm of new spectrum vehicle based on convex programming in wireless sensor network

NASA Astrophysics Data System (ADS)

Zhang, Yongjun; Lu, Zhixin

2017-10-01

Spectrum resources are very precious, so it is increasingly important to locate interference signals rapidly. Convex programming algorithms in wireless sensor networks are often used as localization algorithms. But in view of the traditional convex programming algorithm is too much overlap of wireless sensor nodes that bring low positioning accuracy, the paper proposed a new algorithm. Which is mainly based on the traditional convex programming algorithm, the spectrum car sends unmanned aerial vehicles (uses) that can be used to record data periodically along different trajectories. According to the probability density distribution, the positioning area is segmented to further reduce the location area. Because the algorithm only increases the communication process of the power value of the unknown node and the sensor node, the advantages of the convex programming algorithm are basically preserved to realize the simple and real-time performance. The experimental results show that the improved algorithm has a better positioning accuracy than the original convex programming algorithm.

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.

Lewis Information Network (LINK): Background and overview

NASA Technical Reports Server (NTRS)

Schulte, Roger R.

1987-01-01

The NASA Lewis Research Center supports many research facilities with many isolated buildings, including wind tunnels, test cells, and research laboratories. These facilities are all located on a 350 acre campus adjacent to the Cleveland Hopkins Airport. The function of NASA-Lewis is to do basic and applied research in all areas of aeronautics, fluid mechanics, materials and structures, space propulsion, and energy systems. These functions require a great variety of remote high speed, high volume data communications for computing and interactive graphic capabilities. In addition, new requirements for local distribution of intercenter video teleconferencing and data communications via satellite have developed. To address these and future communications requirements for the next 15 yrs, a project team was organized to design and implement a new high speed communication system that would handle both data and video information in a common lab-wide Local Area Network. The project team selected cable television broadband coaxial cable technology as the communications medium and first installation of in-ground cable began in the summer of 1980. The Lewis Information Network (LINK) became operational in August 1982 and has become the backbone of all data communications and video.

Spatial and temporal dynamics of cortical networks engaged in memory encoding and retrieval

PubMed Central

Miller, Brian T.; D'Esposito, Mark

2012-01-01

Memory operations such as encoding and retrieval require the coordinated interplay of cortical regions with distinct functional contributions. The mechanistic nature of these interactions, however, remains unspecified. During the performance of a face memory task during fMRI scanning, we measured the magnitude (a measure of the strength of coupling between areas) and phase (a measure of the relative timing across areas) of coherence between regions of interest and the rest of the brain. The fusiform face area (FFA) showed robust coherence with a distributed network of subregions in the prefrontal cortex (PFC), posterior parietal cortex (PPC), precuneus, and hippocampus across both memory operations. While these findings reveal significant overlap in the cortical networks underlying mnemonic encoding and retrieval, coherence phase analyses revealed context-dependent differences in cortical dynamics. During both encoding and retrieval, PFC and PPC exhibited earlier activity than in the FFA and hippocampus. Also, during retrieval, PFC activity preceded PPC activity. These findings are consistent with prior physiology studies suggesting an early contribution of PFC and PPC in mnemonic control. Together, these findings contribute to the growing literature exploring the spatio-temporal dynamics of basic memory operations. PMID:22557959

Pleistocene megafaunal interaction networks became more vulnerable after human arrival.

PubMed

Pires, Mathias M; Koch, Paul L; Fariña, Richard A; de Aguiar, Marcus A M; dos Reis, Sérgio F; Guimarães, Paulo R

2015-09-07

The end of the Pleistocene was marked by the extinction of almost all large land mammals worldwide except in Africa. Although the debate on Pleistocene extinctions has focused on the roles of climate change and humans, the impact of perturbations depends on properties of ecological communities, such as species composition and the organization of ecological interactions. Here, we combined palaeoecological and ecological data, food-web models and community stability analysis to investigate if differences between Pleistocene and modern mammalian assemblages help us understand why the megafauna died out in the Americas while persisting in Africa. We show Pleistocene and modern assemblages share similar network topology, but differences in richness and body size distributions made Pleistocene communities significantly more vulnerable to the effects of human arrival. The structural changes promoted by humans in Pleistocene networks would have increased the likelihood of unstable dynamics, which may favour extinction cascades in communities facing extrinsic perturbations. Our findings suggest that the basic aspects of the organization of ecological communities may have played an important role in major extinction events in the past. Knowledge of community-level properties and their consequences to dynamics may be critical to understand past and future extinctions. © 2015 The Author(s).

Pleistocene megafaunal interaction networks became more vulnerable after human arrival

PubMed Central

Pires, Mathias M.; Koch, Paul L.; Fariña, Richard A.; de Aguiar, Marcus A. M.; dos Reis, Sérgio F.; Guimarães, Paulo R.

2015-01-01

The end of the Pleistocene was marked by the extinction of almost all large land mammals worldwide except in Africa. Although the debate on Pleistocene extinctions has focused on the roles of climate change and humans, the impact of perturbations depends on properties of ecological communities, such as species composition and the organization of ecological interactions. Here, we combined palaeoecological and ecological data, food-web models and community stability analysis to investigate if differences between Pleistocene and modern mammalian assemblages help us understand why the megafauna died out in the Americas while persisting in Africa. We show Pleistocene and modern assemblages share similar network topology, but differences in richness and body size distributions made Pleistocene communities significantly more vulnerable to the effects of human arrival. The structural changes promoted by humans in Pleistocene networks would have increased the likelihood of unstable dynamics, which may favour extinction cascades in communities facing extrinsic perturbations. Our findings suggest that the basic aspects of the organization of ecological communities may have played an important role in major extinction events in the past. Knowledge of community-level properties and their consequences to dynamics may be critical to understand past and future extinctions. PMID:26336175

Brain imaging research in autism spectrum disorders: in search of neuropathology and health across the lifespan.

PubMed

Lainhart, Janet E

2015-03-01

Advances in brain imaging research in autism spectrum disorders (ASD) are rapidly occurring, and the amount of neuroimaging research has dramatically increased over the past 5 years. In this review, advances during the past 12 months and longitudinal studies are highlighted. Cross-sectional neuroimaging research provides evidence that the neural underpinnings of the behavioral signs of ASD involve not only dysfunctional integration of information across distributed brain networks but also basic dysfunction in primary cortices.Longitudinal studies of ASD show abnormally enlarged brain volumes and increased rates of brain growth during early childhood in only a small minority of ASD children. There is evidence of disordered development of white matter microstructure and amygdala growth, and at 2 years of age, network inefficiencies in posterior cerebral regions.From older childhood into adulthood, atypical age-variant and age-invariant changes in the trajectories of total and regional brain volumes and cortical thickness are apparent at the group level. There is evidence of abnormalities in posterior lobes and posterior brain networks during the first 2 years of life in ASD and, even in older children and adults, dysfunction in primary cortical areas.

An overload behavior detection system for engineering transport vehicles based on deep learning

NASA Astrophysics Data System (ADS)

Zhou, Libo; Wu, Gang

2018-04-01

This paper builds an overloaded truck detect system called ITMD to help traffic department automatically identify the engineering transport vehicles (commonly known as `dirt truck') in CCTV and determine whether the truck is overloaded or not. We build the ITMD system based on the Single Shot MultiBox Detector (SSD) model. By constructing the image dataset of the truck and adjusting hyper-parameters of the original SSD neural network, we successfully trained a basic network model which the ITMD system depends on. The basic ITMD system achieves 83.01% mAP on classifying overload/non-overload truck, which is a not bad result. Still, some shortcomings of basic ITMD system have been targeted to enhance: it is easy for the ITMD system to misclassify other similar vehicle as truck. In response to this problem, we optimized the basic ITMD system, which effectively reduced basic model's false recognition rate. The optimized ITMD system achieved 86.18% mAP on the test set, which is better than the 83.01% mAP of the basic ITMD system.

Blueprint for multimedia telemedicine networks in the Rocky Mountain Veterans Integrated Service Network (VISN-19).

PubMed

Terreros, D A; Martinez, R

1997-01-01

A multimedia telemedicine network is proposed for a VISN-19 test bed and it will include picture archiving and communication systems (PACS). Initial tests have been performed, and the technical feasibility of the basic plan has been demonstrated.

Mobile Computing and Ubiquitous Networking: Concepts, Technologies and Challenges.

ERIC Educational Resources Information Center

Pierre, Samuel

2001-01-01

Analyzes concepts, technologies and challenges related to mobile computing and networking. Defines basic concepts of cellular systems. Describes the evolution of wireless technologies that constitute the foundations of mobile computing and ubiquitous networking. Presents characterization and issues of mobile computing. Analyzes economical and…

Tips for Implementing a Wireless Network

ERIC Educational Resources Information Center

Walery, Darrell

2005-01-01

This article provides a quick start guide to provide educators with the basic points to consider before installing a wireless network in the school. Since many school districts have already implemented wireless networks, there is a lot of information available online to assist in the process.

Probabilistic graphs as a conceptual and computational tool in hydrology and water management

NASA Astrophysics Data System (ADS)

Schoups, Gerrit

2014-05-01

Originally developed in the fields of machine learning and artificial intelligence, probabilistic graphs constitute a general framework for modeling complex systems in the presence of uncertainty. The framework consists of three components: 1. Representation of the model as a graph (or network), with nodes depicting random variables in the model (e.g. parameters, states, etc), which are joined together by factors. Factors are local probabilistic or deterministic relations between subsets of variables, which, when multiplied together, yield the joint distribution over all variables. 2. Consistent use of probability theory for quantifying uncertainty, relying on basic rules of probability for assimilating data into the model and expressing unknown variables as a function of observations (via the posterior distribution). 3. Efficient, distributed approximation of the posterior distribution using general-purpose algorithms that exploit model structure encoded in the graph. These attributes make probabilistic graphs potentially useful as a conceptual and computational tool in hydrology and water management (and beyond). Conceptually, they can provide a common framework for existing and new probabilistic modeling approaches (e.g. by drawing inspiration from other fields of application), while computationally they can make probabilistic inference feasible in larger hydrological models. The presentation explores, via examples, some of these benefits.

Visual Network Asymmetry and Default Mode Network Function in ADHD: An fMRI Study

PubMed Central

Hale, T. Sigi; Kane, Andrea M.; Kaminsky, Olivia; Tung, Kelly L.; Wiley, Joshua F.; McGough, James J.; Loo, Sandra K.; Kaplan, Jonas T.

2014-01-01

Background: A growing body of research has identified abnormal visual information processing in attention-deficit hyperactivity disorder (ADHD). In particular, slow processing speed and increased reliance on visuo-perceptual strategies have become evident. Objective: The current study used recently developed fMRI methods to replicate and further examine abnormal rightward biased visual information processing in ADHD and to further characterize the nature of this effect; we tested its association with several large-scale distributed network systems. Method: We examined fMRI BOLD response during letter and location judgment tasks, and directly assessed visual network asymmetry and its association with large-scale networks using both a voxelwise and an averaged signal approach. Results: Initial within-group analyses revealed a pattern of left-lateralized visual cortical activity in controls but right-lateralized visual cortical activity in ADHD children. Direct analyses of visual network asymmetry confirmed atypical rightward bias in ADHD children compared to controls. This ADHD characteristic was atypically associated with reduced activation across several extra-visual networks, including the default mode network (DMN). We also found atypical associations between DMN activation and ADHD subjects’ inattentive symptoms and task performance. Conclusion: The current study demonstrated rightward VNA in ADHD during a simple letter discrimination task. This result adds an important novel consideration to the growing literature identifying abnormal visual processing in ADHD. We postulate that this characteristic reflects greater perceptual engagement of task-extraneous content, and that it may be a basic feature of less efficient top-down task-directed control over visual processing. We additionally argue that abnormal DMN function may contribute to this characteristic. PMID:25076915

Uni10: an open-source library for tensor network algorithms

NASA Astrophysics Data System (ADS)

Kao, Ying-Jer; Hsieh, Yun-Da; Chen, Pochung

2015-09-01

We present an object-oriented open-source library for developing tensor network algorithms written in C++ called Uni10. With Uni10, users can build a symmetric tensor from a collection of bonds, while the bonds are constructed from a list of quantum numbers associated with different quantum states. It is easy to label and permute the indices of the tensors and access a block associated with a particular quantum number. Furthermore a network class is used to describe arbitrary tensor network structure and to perform network contractions efficiently. We give an overview of the basic structure of the library and the hierarchy of the classes. We present examples of the construction of a spin-1 Heisenberg Hamiltonian and the implementation of the tensor renormalization group algorithm to illustrate the basic usage of the library. The library described here is particularly well suited to explore and fast prototype novel tensor network algorithms and to implement highly efficient codes for existing algorithms.

Model for disease dynamics of a waterborne pathogen on a random network.

PubMed

Li, Meili; Ma, Junling; van den Driessche, P

2015-10-01

A network epidemic SIWR model for cholera and other diseases that can be transmitted via the environment is developed and analyzed. The person-to-person contacts are modeled by a random contact network, and the contagious environment is modeled by an external node that connects to every individual. The model is adapted from the Miller network SIR model, and in the homogeneous mixing limit becomes the Tien and Earn deterministic cholera model without births and deaths. The dynamics of our model shows excellent agreement with stochastic simulations. The basic reproduction number [Formula: see text] is computed, and on a Poisson network shown to be the sum of the basic reproduction numbers of the person-to-person and person-to-water-to-person transmission pathways. However, on other networks, [Formula: see text] depends nonlinearly on the transmission along the two pathways. Type reproduction numbers are computed and quantify measures to control the disease. Equations giving the final epidemic size are obtained.

Training Data Requirement for a Neural Network to Predict Aerodynamic Coefficients

NASA Technical Reports Server (NTRS)

Korsmeyer, David (Technical Monitor); Rajkumar, T.; Bardina, Jorge

2003-01-01

Basic aerodynamic coefficients are modeled as functions of angle of attack, speed brake deflection angle, Mach number, and side slip angle. Most of the aerodynamic parameters can be well-fitted using polynomial functions. We previously demonstrated that a neural network is a fast, reliable way of predicting aerodynamic coefficients. We encountered few under fitted and/or over fitted results during prediction. The training data for the neural network are derived from wind tunnel test measurements and numerical simulations. The basic questions that arise are: how many training data points are required to produce an efficient neural network prediction, and which type of transfer functions should be used between the input-hidden layer and hidden-output layer. In this paper, a comparative study of the efficiency of neural network prediction based on different transfer functions and training dataset sizes is presented. The results of the neural network prediction reflect the sensitivity of the architecture, transfer functions, and training dataset size.

Organization of the secure distributed computing based on multi-agent system

NASA Astrophysics Data System (ADS)

Khovanskov, Sergey; Rumyantsev, Konstantin; Khovanskova, Vera

2018-04-01

Nowadays developing methods for distributed computing is received much attention. One of the methods of distributed computing is using of multi-agent systems. The organization of distributed computing based on the conventional network computers can experience security threats performed by computational processes. Authors have developed the unified agent algorithm of control system of computing network nodes operation. Network PCs is used as computing nodes. The proposed multi-agent control system for the implementation of distributed computing allows in a short time to organize using of the processing power of computers any existing network to solve large-task by creating a distributed computing. Agents based on a computer network can: configure a distributed computing system; to distribute the computational load among computers operated agents; perform optimization distributed computing system according to the computing power of computers on the network. The number of computers connected to the network can be increased by connecting computers to the new computer system, which leads to an increase in overall processing power. Adding multi-agent system in the central agent increases the security of distributed computing. This organization of the distributed computing system reduces the problem solving time and increase fault tolerance (vitality) of computing processes in a changing computing environment (dynamic change of the number of computers on the network). Developed a multi-agent system detects cases of falsification of the results of a distributed system, which may lead to wrong decisions. In addition, the system checks and corrects wrong results.

Basic dynamics from a pulse-coupled network of autonomous integrate-and-fire chaotic circuits.

PubMed

Nakano, H; Saito, T

2002-01-01

This paper studies basic dynamics from a novel pulse-coupled network (PCN). The unit element of the PCN is an integrate-and-fire circuit (IFC) that exhibits chaos. We an give an iff condition for the chaos generation. Using two IFC, we construct a master-slave PCN. It exhibits interesting chaos synchronous phenomena and their breakdown phenomena. We give basic classification of the phenomena and their existence regions can be elucidated in the parameter space. We then construct a ring-type PCN and elucidate that the PCN exhibits interesting grouping phenomena based on the chaos synchronization patterns. Using a simple test circuit, some of typical phenomena can be verified in the laboratory.

An overview to networks and its applications

NASA Astrophysics Data System (ADS)

Huerta-Quintanilla, Rodrigo; Sanabria M., Christian H.

2010-07-01

We present an introduction to the basics on networks and their application to econo-physics. In particular we study a model in which agents interact through a network chosen in a very specific way and the exchange they make of a given asset. We study different types of exchange interactions and also the effect of the network on the dynamics.

Design of a national distributed health data network.

PubMed

Maro, Judith C; Platt, Richard; Holmes, John H; Strom, Brian L; Hennessy, Sean; Lazarus, Ross; Brown, Jeffrey S

2009-09-01

A distributed health data network is a system that allows secure remote analysis of separate data sets, each comprising a different medical organization's or health plan's records. Distributed health data networks are currently being planned that could cover millions of people, permitting studies of comparative clinical effectiveness, best practices, diffusion of medical technologies, and quality of care. These networks could also support assessment of medical product safety and other public health needs. Distributed network technologies allow data holders to control all uses of their data, which overcomes many practical obstacles related to confidentiality, regulation, and proprietary interests. Some of the challenges and potential methods of operation of a multipurpose, multi-institutional distributed health data network are described.

The Value of Information in Distributed Decision Networks

DTIC Science & Technology

2016-03-04

formulation, and then we describe the various results at- tained. 1 Mathematical description of Distributed Decision Network un- der Information...Constraints We now define a mathematical framework for networks. Let G = (V,E) be an undirected random network (graph) drawn from a known distribution pG, 1

Wireless Wide Area Networks for School Districts.

ERIC Educational Resources Information Center

Nair, Prakash

This paper considers a basic question that many schools districts face in attempting to develop affordable, expandable district-wide computer networks that are resistant to obsolescence: Should these wide area networks (WANs) employ wireless technology, stick to venerable hard-wired solutions, or combine both. This publication explores the…

Recommendations for a service framework to access astronomical archives

NASA Technical Reports Server (NTRS)

Travisano, J. J.; Pollizzi, J.

1992-01-01

There are a large number of astronomical archives and catalogs on-line for network access, with many different user interfaces and features. Some systems are moving towards distributed access, supplying users with client software for their home sites which connects to servers at the archive site. Many of the issues involved in defining a standard framework of services that archive/catalog suppliers can use to achieve a basic level of interoperability are described. Such a framework would simplify the development of client and server programs to access the wide variety of astronomical archive systems. The primary services that are supplied by current systems include: catalog browsing, dataset retrieval, name resolution, and data analysis. The following issues (and probably more) need to be considered in establishing a standard set of client/server interfaces and protocols: Archive Access - dataset retrieval, delivery, file formats, data browsing, analysis, etc.; Catalog Access - database management systems, query languages, data formats, synchronous/asynchronous mode of operation, etc.; Interoperability - transaction/message protocols, distributed processing mechanisms (DCE, ONC/SunRPC, etc), networking protocols, etc.; Security - user registration, authorization/authentication mechanisms, etc.; Service Directory - service registration, lookup, port/task mapping, parameters, etc.; Software - public vs proprietary, client/server software, standard interfaces to client/server functions, software distribution, operating system portability, data portability, etc. Several archive/catalog groups, notably the Astrophysics Data System (ADS), are already working in many of these areas. In the process of developing StarView, which is the user interface to the Space Telescope Data Archive and Distribution Service (ST-DADS), these issues and the work of others were analyzed. A framework of standard interfaces for accessing services on any archive system which would benefit archive user and supplier alike is proposed.

BrainBrowser: distributed, web-based neurological data visualization.

PubMed

Sherif, Tarek; Kassis, Nicolas; Rousseau, Marc-Étienne; Adalat, Reza; Evans, Alan C

2014-01-01

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible.

BrainBrowser: distributed, web-based neurological data visualization

PubMed Central

Sherif, Tarek; Kassis, Nicolas; Rousseau, Marc-Étienne; Adalat, Reza; Evans, Alan C.

2015-01-01

Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used to analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible. PMID:25628562

A Multi-level Fuzzy Evaluation Method for Smart Distribution Network Based on Entropy Weight

NASA Astrophysics Data System (ADS)

Li, Jianfang; Song, Xiaohui; Gao, Fei; Zhang, Yu

2017-05-01

Smart distribution network is considered as the future trend of distribution network. In order to comprehensive evaluate smart distribution construction level and give guidance to the practice of smart distribution construction, a multi-level fuzzy evaluation method based on entropy weight is proposed. Firstly, focus on both the conventional characteristics of distribution network and new characteristics of smart distribution network such as self-healing and interaction, a multi-level evaluation index system which contains power supply capability, power quality, economy, reliability and interaction is established. Then, a combination weighting method based on Delphi method and entropy weight method is put forward, which take into account not only the importance of the evaluation index in the experts’ subjective view, but also the objective and different information from the index values. Thirdly, a multi-level evaluation method based on fuzzy theory is put forward. Lastly, an example is conducted based on the statistical data of some cites’ distribution network and the evaluation method is proved effective and rational.

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…

User-Friendly Interface Developed for a Web-Based Service for SpaceCAL Emulations

NASA Technical Reports Server (NTRS)

Liszka, Kathy J.; Holtz, Allen P.

2004-01-01

A team at the NASA Glenn Research Center is developing a Space Communications Architecture Laboratory (SpaceCAL) for protocol development activities for coordinated satellite missions. SpaceCAL will provide a multiuser, distributed system to emulate space-based Internet architectures, backbone networks, formation clusters, and constellations. As part of a new effort in 2003, building blocks are being defined for an open distributed system to make the satellite emulation test bed accessible through an Internet connection. The first step in creating a Web-based service to control the emulation remotely is providing a user-friendly interface for encoding the data into a well-formed and complete Extensible Markup Language (XML) document. XML provides coding that allows data to be transferred between dissimilar systems. Scenario specifications include control parameters, network routes, interface bandwidths, delay, and bit error rate. Specifications for all satellite, instruments, and ground stations in a given scenario are also included in the XML document. For the SpaceCAL emulation, the XML document can be created using XForms, a Webbased forms language for data collection. Contrary to older forms technology, the interactive user interface makes the science prevalent, not the data representation. Required versus optional input fields, default values, automatic calculations, data validation, and reuse will help researchers quickly and accurately define missions. XForms can apply any XML schema defined for the test mission to validate data before forwarding it to the emulation facility. New instrument definitions, facilities, and mission types can be added to the existing schema. The first prototype user interface incorporates components for interactive input and form processing. Internet address, data rate, and the location of the facility are implemented with basic form controls with default values provided for convenience and efficiency using basic XForms operations. Because different emulation scenarios will vary widely in their component structure, more complex operations are used to add and delete facilities.

Research and Design of the Three-tier Distributed Network Management System Based on COM / COM + and DNA

NASA Astrophysics Data System (ADS)

Liang, Likai; Bi, Yushen

Considered on the distributed network management system's demand of high distributives, extensibility and reusability, a framework model of Three-tier distributed network management system based on COM/COM+ and DNA is proposed, which adopts software component technology and N-tier application software framework design idea. We also give the concrete design plan of each layer of this model. Finally, we discuss the internal running process of each layer in the distributed network management system's framework model.

NCI’s Cooperative Human Tissue Network

Cancer.gov

Quality biospecimens are a foundational resource for cancer research. One of NCI’s longest running biospecimen programs is the Cooperative Human Tissue Network, a resource mainly for basic discovery and early translational research.

Research and Simulation on Application of the Mobile IP Network

NASA Astrophysics Data System (ADS)

Yibing, Deng; Wei, Hu; Minghui, Li; Feng, Gao; Junyi, Shen

The paper analysed the mobile node, home agent, and foreign agent of mobile IP network firstly, some key technique, such as mobile IP network basical principle, protocol work principle, agent discovery, registration, and IP packet transmission, were discussed. Then a network simulation model was designed, validating the characteristic of mobile IP network, and some advantages, which were brought by mobile network, were testified. Finally, the conclusion is gained: mobile IP network could realize the expectation of consumer that they can communicate with others anywhere.

Implementation of the Brazilian Breastfeeding Network and prevalence of exclusive breastfeeding

PubMed Central

Passanha, Adriana; Benício, Maria Helena D'Aquino; Venâncio, Sônia Isoyama; dos Reis, Márcia Cristina Guerreiro

2013-01-01

OBJECTIVE To evaluate the association between the level of implementation of the Brazilian Breastfeeding Network and the prevalence of exclusive breastfeeding. METHODS Cross-sectional study of a representative sample of 916 infants < 6 months, in Ribeirao Preto, SP, Southeastern Brazil, in 2011. Data on breastfeeding, place of outpatient care and other characteristics were collected during the National Vaccination Campaign. The factor studied is where outpatient care took place: Private; Non-Network Public; Public with Network Workshop; and Public certified by Network. The individualized effect of the factor studied on the outcome was analyzed using Poisson regression with robust variance. RESULTS The comparison between private (reference category) and other outpatient care showed significant dose-response relationship with a progressive increase in the prevalence of exclusive breastfeeding in public non-Network, public with Network Workshop and public accredited by Network outpatient care (p = 0.047). As regards the Basic Health Units accredited by Network category, the Prevalence Ratio of exclusive breastfeeding was equal to 1.47 (95%CI 1.00;2.17), after adjustment for confounding variables. CONCLUSIONS The prevalence of exclusive breastfeeding for infants < 6 months was higher in places accredited by the Brazilian Breastfeeding Network, which evinces the importance of investing in accreditation of Basic Units of Health by this strategy. PMID:24626552

Controllability of complex networks for sustainable system dynamics

EPA Science Inventory

Successful implementation of sustainability ideas in ecosystem management requires a basic understanding of the often non-linear and non-intuitive relationships among different dimensions of sustainability, particularly the system-wide implications of human actions. This basic un...

Exploring the bZIP transcription factor regulatory network in Neurospora crassa

PubMed Central

Tian, Chaoguang; Li, Jingyi; Glass, N. Louise

2011-01-01

Transcription factors (TFs) are key nodes of regulatory networks in eukaryotic organisms, including filamentous fungi such as Neurospora crassa. The 178 predicted DNA-binding TFs in N. crassa are distributed primarily among six gene families, which represent an ancient expansion in filamentous ascomycete genomes; 98 TF genes show detectable expression levels during vegetative growth of N. crassa, including 35 that show a significant difference in expression level between hyphae at the periphery versus hyphae in the interior of a colony. Regulatory networks within a species genome include paralogous TFs and their respective target genes (TF regulon). To investigate TF network evolution in N. crassa, we focused on the basic leucine zipper (bZIP) TF family, which contains nine members. We performed baseline transcriptional profiling during vegetative growth of the wild-type and seven isogenic, viable bZIP deletion mutants. We further characterized the regulatory network of one member of the bZIP family, NCU03905. NCU03905 encodes an Ap1-like protein (NcAp-1), which is involved in resistance to multiple stress responses, including oxidative and heavy metal stress. Relocalization of NcAp-1 from the cytoplasm to the nucleus was associated with exposure to stress. A comparison of the NcAp-1 regulon with Ap1-like regulons in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Candida albicans and Aspergillus fumigatus showed both conservation and divergence. These data indicate how N. crassa responds to stress and provide information on pathway evolution. PMID:21081763

Exploring the bZIP transcription factor regulatory network in Neurospora crassa.

PubMed

Tian, Chaoguang; Li, Jingyi; Glass, N Louise

2011-03-01

Transcription factors (TFs) are key nodes of regulatory networks in eukaryotic organisms, including filamentous fungi such as Neurospora crassa. The 178 predicted DNA-binding TFs in N. crassa are distributed primarily among six gene families, which represent an ancient expansion in filamentous ascomycete genomes; 98 TF genes show detectable expression levels during vegetative growth of N. crassa, including 35 that show a significant difference in expression level between hyphae at the periphery versus hyphae in the interior of a colony. Regulatory networks within a species genome include paralogous TFs and their respective target genes (TF regulon). To investigate TF network evolution in N. crassa, we focused on the basic leucine zipper (bZIP) TF family, which contains nine members. We performed baseline transcriptional profiling during vegetative growth of the wild-type and seven isogenic, viable bZIP deletion mutants. We further characterized the regulatory network of one member of the bZIP family, NCU03905. NCU03905 encodes an Ap1-like protein (NcAp-1), which is involved in resistance to multiple stress responses, including oxidative and heavy metal stress. Relocalization of NcAp-1 from the cytoplasm to the nucleus was associated with exposure to stress. A comparison of the NcAp-1 regulon with Ap1-like regulons in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Candida albicans and Aspergillus fumigatus showed both conservation and divergence. These data indicate how N. crassa responds to stress and provide information on pathway evolution.

Routing in Networks with Random Topologies

NASA Technical Reports Server (NTRS)

Bambos, Nicholas

1997-01-01

We examine the problems of routing and server assignment in networks with random connectivities. In such a network the basic topology is fixed, but during each time slot and for each of tis input queues, each server (node) is either connected to or disconnected from each of its queues with some probability.

Synaptic Impairment and Robustness of Excitatory Neuronal Networks with Different Topologies

PubMed Central

Mirzakhalili, Ehsan; Gourgou, Eleni; Booth, Victoria; Epureanu, Bogdan

2017-01-01

Synaptic deficiencies are a known hallmark of neurodegenerative diseases, but the diagnosis of impaired synapses on the cellular level is not an easy task. Nonetheless, changes in the system-level dynamics of neuronal networks with damaged synapses can be detected using techniques that do not require high spatial resolution. This paper investigates how the structure/topology of neuronal networks influences their dynamics when they suffer from synaptic loss. We study different neuronal network structures/topologies by specifying their degree distributions. The modes of the degree distribution can be used to construct networks that consist of rich clubs and resemble small world networks, as well. We define two dynamical metrics to compare the activity of networks with different structures: persistent activity (namely, the self-sustained activity of the network upon removal of the initial stimulus) and quality of activity (namely, percentage of neurons that participate in the persistent activity of the network). Our results show that synaptic loss affects the persistent activity of networks with bimodal degree distributions less than it affects random networks. The robustness of neuronal networks enhances when the distance between the modes of the degree distribution increases, suggesting that the rich clubs of networks with distinct modes keep the whole network active. In addition, a tradeoff is observed between the quality of activity and the persistent activity. For a range of distributions, both of these dynamical metrics are considerably high for networks with bimodal degree distribution compared to random networks. We also propose three different scenarios of synaptic impairment, which may correspond to different pathological or biological conditions. Regardless of the network structure/topology, results demonstrate that synaptic loss has more severe effects on the activity of the network when impairments are correlated with the activity of the neurons. PMID:28659765

Structural diversity effects of multilayer networks on the threshold of interacting epidemics

NASA Astrophysics Data System (ADS)

Wang, Weihong; Chen, MingMing; Min, Yong; Jin, Xiaogang

2016-02-01

Foodborne diseases always spread through multiple vectors (e.g. fresh vegetables and fruits) and reveal that multilayer network could spread fatal pathogen with complex interactions. In this paper, first, we use a "top-down analysis framework that depends on only two distributions to describe a random multilayer network with any number of layers. These two distributions are the overlaid degree distribution and the edge-type distribution of the multilayer network. Second, based on the two distributions, we adopt three indicators of multilayer network diversity to measure the correlation between network layers, including network richness, likeness, and evenness. The network richness is the number of layers forming the multilayer network. The network likeness is the degree of different layers sharing the same edge. The network evenness is the variance of the number of edges in every layer. Third, based on a simple epidemic model, we analyze the influence of network diversity on the threshold of interacting epidemics with the coexistence of collaboration and competition. Our work extends the "top-down" analysis framework to deal with the more complex epidemic situation and more diversity indicators and quantifies the trade-off between thresholds of inter-layer collaboration and intra-layer transmission.

Distributed Detection with Collisions in a Random, Single-Hop Wireless Sensor Network

DTIC Science & Technology

2013-05-26

public release; distribution is unlimited. Distributed detection with collisions in a random, single-hop wireless sensor network The views, opinions...1274 2 ABSTRACT Distributed detection with collisions in a random, single-hop wireless sensor network Report Title We consider the problem of... WIRELESS SENSOR NETWORK Gene T. Whipps?† Emre Ertin† Randolph L. Moses† ?U.S. Army Research Laboratory, Adelphi, MD 20783 †The Ohio State University

What Is the Internet, Who Is Running It and How Is It Used?

ERIC Educational Resources Information Center

Eschbach, Darel

The Internet, for the purposes of this discussion, refers to the network that has the National Science Foundation Network (NSFNET) as its backbone. For this paper, internet is the larger connection of networks that provides a minimum basic connection for electronic mail. The network is made up of many segments structured in a multitiered hierarchy…

Networking CD-ROMs: The Decision Maker's Guide to Local Area Network Solutions.

ERIC Educational Resources Information Center

Elshami, Ahmed M.

In an era when patrons want access to CD-ROM resources but few libraries can afford to buy multiple copies, CD-ROM local area networks (LANs) are emerging as a cost-effective way to provide shared access. To help librarians make informed decisions, this manual offers information on: (1) the basics of LANs, a "local area network primer";…

Symmetry compression method for discovering network motifs.

PubMed

Wang, Jianxin; Huang, Yuannan; Wu, Fang-Xiang; Pan, Yi

2012-01-01

Discovering network motifs could provide a significant insight into systems biology. Interestingly, many biological networks have been found to have a high degree of symmetry (automorphism), which is inherent in biological network topologies. The symmetry due to the large number of basic symmetric subgraphs (BSSs) causes a certain redundant calculation in discovering network motifs. Therefore, we compress all basic symmetric subgraphs before extracting compressed subgraphs and propose an efficient decompression algorithm to decompress all compressed subgraphs without loss of any information. In contrast to previous approaches, the novel Symmetry Compression method for Motif Detection, named as SCMD, eliminates most redundant calculations caused by widespread symmetry of biological networks. We use SCMD to improve three notable exact algorithms and two efficient sampling algorithms. Results of all exact algorithms with SCMD are the same as those of the original algorithms, since SCMD is a lossless method. The sampling results show that the use of SCMD almost does not affect the quality of sampling results. For highly symmetric networks, we find that SCMD used in both exact and sampling algorithms can help get a remarkable speedup. Furthermore, SCMD enables us to find larger motifs in biological networks with notable symmetry than previously possible.

The evolution of cooperation on geographical networks

NASA Astrophysics Data System (ADS)

Li, Yixiao; Wang, Yi; Sheng, Jichuan

2017-11-01

We study evolutionary public goods game on geographical networks, i.e., complex networks which are located on a geographical plane. The geographical feature effects in two ways: In one way, the geographically-induced network structure influences the overall evolutionary dynamics, and, in the other way, the geographical length of an edge influences the cost when the two players at the two ends interact. For the latter effect, we design a new cost function of cooperators, which simply assumes that the longer the distance between two players, the higher cost the cooperator(s) of them have to pay. In this study, network substrates are generated by a previous spatial network model with a cost-benefit parameter controlling the network topology. Our simulations show that the greatest promotion of cooperation is achieved in the intermediate regime of the parameter, in which empirical estimates of various railway networks fall. Further, we investigate how the distribution of edges' geographical costs influences the evolutionary dynamics and consider three patterns of the distribution: an approximately-equal distribution, a diverse distribution, and a polarized distribution. For normal geographical networks which are generated using intermediate values of the cost-benefit parameter, a diverse distribution hinders the evolution of cooperation, whereas a polarized distribution lowers the threshold value of the amplification factor for cooperation in public goods game. These results are helpful for understanding the evolution of cooperation on real-world geographical networks.

Artificial synapse network on inorganic proton conductor for neuromorphic systems.

PubMed

Zhu, Li Qiang; Wan, Chang Jin; Guo, Li Qiang; Shi, Yi; Wan, Qing

2014-01-01

The basic units in our brain are neurons, and each neuron has more than 1,000 synapse connections. Synapse is the basic structure for information transfer in an ever-changing manner, and short-term plasticity allows synapses to perform critical computational functions in neural circuits. Therefore, the major challenge for the hardware implementation of neuromorphic computation is to develop artificial synapse network. Here in-plane lateral-coupled oxide-based artificial synapse network coupled by proton neurotransmitters are self-assembled on glass substrates at room-temperature. A strong lateral modulation is observed due to the proton-related electrical-double-layer effect. Short-term plasticity behaviours, including paired-pulse facilitation, dynamic filtering and spatiotemporally correlated signal processing are mimicked. Such laterally coupled oxide-based protonic/electronic hybrid artificial synapse network proposed here is interesting for building future neuromorphic systems.

Interactome Networks and Human Disease

PubMed Central

Vidal, Marc; Cusick, Michael E.; Barabási, Albert-László

2011-01-01

Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease. PMID:21414488

Flavylium network of chemical reactions in confined media: modulation of 3',4',7-trihydroxyflavilium reactions by host-guest interactions with cucurbit[7]uril.

PubMed

Basílio, Nuno; Pina, Fernando

2014-08-04

In moderately acidic aqueous solutions, flavylium compounds undergo a pH-, and in some cases, light-dependent array of reversible chemical reactions. This network can be described as a single acid-base reaction involving a flavylium cation (acidic form) and a mixture of basic forms (quinoidal base, hemiketal and cis and trans chalcones). The apparent pK'a of the system and the relative mole fractions of the basic forms can be modulated by the interaction with cucurbit[7]uril. The system is studied by using (1) H NMR spectroscopy, UV/Vis spectroscopy, flash photolysis, and steady-state irradiation. Of all the network species, the flavylium cation possesses the highest affinity for cucurbit[7]uril. The rate of interconversion between flavylium cation and the basic species (where trans-chalcone is dominant) is approximately nine times lower inside the cucurbit[7]uril. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Network-level reproduction number and extinction threshold for vector-borne diseases.

PubMed

Xue, Ling; Scoglio, Caterina

2015-06-01

The basic reproduction number of deterministic models is an essential quantity to predict whether an epidemic will spread or not. Thresholds for disease extinction contribute crucial knowledge of disease control, elimination, and mitigation of infectious diseases. Relationships between basic reproduction numbers of two deterministic network-based ordinary differential equation vector-host models, and extinction thresholds of corresponding stochastic continuous-time Markov chain models are derived under some assumptions. Numerical simulation results for malaria and Rift Valley fever transmission on heterogeneous networks are in agreement with analytical results without any assumptions, reinforcing that the relationships may always exist and proposing a mathematical problem for proving existence of the relationships in general. Moreover, numerical simulations show that the basic reproduction number does not monotonically increase or decrease with the extinction threshold. Consistent trends of extinction probability observed through numerical simulations provide novel insights into mitigation strategies to increase the disease extinction probability. Research findings may improve understandings of thresholds for disease persistence in order to control vector-borne diseases.

Software-Enabled Distributed Network Governance: The PopMedNet Experience.

PubMed

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

2016-01-01

The expanded availability of electronic health information has led to increased interest in distributed health data research networks. 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. 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. Four case studies describe how PopMedNet is used to enforce network governance models. 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. 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.

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

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-02

... POSTAL SERVICE 39 CFR Parts 111 and 121 Nomenclature Change Relating to the Network Distribution... (BMC) to network distribution centers (NDC), by replacing all text references to ``BMC'' with ``NDC...: Background: The BMC network was established in the 1970s to process Parcel Post[supreg], Bound Printed Matter...

Planning of distributed generation in distribution network based on improved particle swarm optimization algorithm

NASA Astrophysics Data System (ADS)

Li, Jinze; Qu, Zhi; He, Xiaoyang; Jin, Xiaoming; Li, Tie; Wang, Mingkai; Han, Qiu; Gao, Ziji; Jiang, Feng

2018-02-01

Large-scale access of distributed power can improve the current environmental pressure, at the same time, increasing the complexity and uncertainty of overall distribution system. Rational planning of distributed power can effectively improve the system voltage level. To this point, the specific impact on distribution network power quality caused by the access of typical distributed power was analyzed and from the point of improving the learning factor and the inertia weight, an improved particle swarm optimization algorithm (IPSO) was proposed which could solve distributed generation planning for distribution network to improve the local and global search performance of the algorithm. Results show that the proposed method can well reduce the system network loss and improve the economic performance of system operation with distributed generation.

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

PubMed

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

2016-08-18

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

Complex Network Theory Applied to the Growth of Kuala Lumpur's Public Urban Rail Transit Network.

PubMed

Ding, Rui; Ujang, Norsidah; Hamid, Hussain Bin; Wu, Jianjun

2015-01-01

Recently, the number of studies involving complex network applications in transportation has increased steadily as scholars from various fields analyze traffic networks. Nonetheless, research on rail network growth is relatively rare. This research examines the evolution of the Public Urban Rail Transit Networks of Kuala Lumpur (PURTNoKL) based on complex network theory and covers both the topological structure of the rail system and future trends in network growth. In addition, network performance when facing different attack strategies is also assessed. Three topological network characteristics are considered: connections, clustering and centrality. In PURTNoKL, we found that the total number of nodes and edges exhibit a linear relationship and that the average degree stays within the interval [2.0488, 2.6774] with heavy-tailed distributions. The evolutionary process shows that the cumulative probability distribution (CPD) of degree and the average shortest path length show good fit with exponential distribution and normal distribution, respectively. Moreover, PURTNoKL exhibits clear cluster characteristics; most of the nodes have a 2-core value, and the CPDs of the centrality's closeness and betweenness follow a normal distribution function and an exponential distribution, respectively. Finally, we discuss four different types of network growth styles and the line extension process, which reveal that the rail network's growth is likely based on the nodes with the biggest lengths of the shortest path and that network protection should emphasize those nodes with the largest degrees and the highest betweenness values. This research may enhance the networkability of the rail system and better shape the future growth of public rail networks.

Multiple-Ring Digital Communication Network

NASA Technical Reports Server (NTRS)

Kirkham, Harold

1992-01-01

Optical-fiber digital communication network to support data-acquisition and control functions of electric-power-distribution networks. Optical-fiber links of communication network follow power-distribution routes. Since fiber crosses open power switches, communication network includes multiple interconnected loops with occasional spurs. At each intersection node is needed. Nodes of communication network include power-distribution substations and power-controlling units. In addition to serving data acquisition and control functions, each node acts as repeater, passing on messages to next node(s). Multiple-ring communication network operates on new AbNET protocol and features fiber-optic communication.

Sustainable Improvement of Urban River Network Water Quality and Flood Control Capacity by a Hydrodynamic Control Approach-Case Study of Changshu City

NASA Astrophysics Data System (ADS)

Xie, Chen; Yang, Fan; Liu, Guoqing; Liu, Yang; Wang, Long; Fan, Ziwu

2017-01-01

Water environment of urban rivers suffers degradation with the impacts of urban expansion, especially in Yangtze River Delta. The water area in cites decreased sharply, and some rivers were cut off because of estate development, which brings the problems of urban flooding, flow stagnation and water deterioration. The approach aims to enhance flood control capability and improve the urban river water quality by planning gate-pump stations surrounding the cities and optimizing the locations and functions of the pumps, sluice gates, weirs in the urban river network. These gate-pump stations together with the sluice gates and weirs guarantee the ability to control the water level in the rivers and creating hydraulic gradient artificially according to mathematical model. Therefore the flow velocity increases, which increases the rate of water exchange, the DO concentration and water body self-purification ability. By site survey and prototype measurement, the river problems are evaluated and basic data are collected. The hydrodynamic model of the river network is established and calibrated to simulate the scenarios. The schemes of water quality improvement, including optimizing layout of the water distribution projects, improvement of the flow discharge in the river network and planning the drainage capacity are decided by comprehensive Analysis. Finally the paper introduces the case study of the approach in Changshu City, where the approach is successfully implemented.

The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding.

PubMed

Testolin, Alberto; De Filippo De Grazia, Michele; Zorzi, Marco

2017-01-01

The recent "deep learning revolution" in artificial neural networks had strong impact and widespread deployment for engineering applications, but the use of deep learning for neurocomputational modeling has been so far limited. In this article we argue that unsupervised deep learning represents an important step forward for improving neurocomputational models of perception and cognition, because it emphasizes the role of generative learning as opposed to discriminative (supervised) learning. As a case study, we present a series of simulations investigating the emergence of neural coding of visual space for sensorimotor transformations. We compare different network architectures commonly used as building blocks for unsupervised deep learning by systematically testing the type of receptive fields and gain modulation developed by the hidden neurons. In particular, we compare Restricted Boltzmann Machines (RBMs), which are stochastic, generative networks with bidirectional connections trained using contrastive divergence, with autoencoders, which are deterministic networks trained using error backpropagation. For both learning architectures we also explore the role of sparse coding, which has been identified as a fundamental principle of neural computation. The unsupervised models are then compared with supervised, feed-forward networks that learn an explicit mapping between different spatial reference frames. Our simulations show that both architectural and learning constraints strongly influenced the emergent coding of visual space in terms of distribution of tuning functions at the level of single neurons. Unsupervised models, and particularly RBMs, were found to more closely adhere to neurophysiological data from single-cell recordings in the primate parietal cortex. These results provide new insights into how basic properties of artificial neural networks might be relevant for modeling neural information processing in biological systems.

The Role of Architectural and Learning Constraints in Neural Network Models: A Case Study on Visual Space Coding

PubMed Central

Testolin, Alberto; De Filippo De Grazia, Michele; Zorzi, Marco

2017-01-01

The recent “deep learning revolution” in artificial neural networks had strong impact and widespread deployment for engineering applications, but the use of deep learning for neurocomputational modeling has been so far limited. In this article we argue that unsupervised deep learning represents an important step forward for improving neurocomputational models of perception and cognition, because it emphasizes the role of generative learning as opposed to discriminative (supervised) learning. As a case study, we present a series of simulations investigating the emergence of neural coding of visual space for sensorimotor transformations. We compare different network architectures commonly used as building blocks for unsupervised deep learning by systematically testing the type of receptive fields and gain modulation developed by the hidden neurons. In particular, we compare Restricted Boltzmann Machines (RBMs), which are stochastic, generative networks with bidirectional connections trained using contrastive divergence, with autoencoders, which are deterministic networks trained using error backpropagation. For both learning architectures we also explore the role of sparse coding, which has been identified as a fundamental principle of neural computation. The unsupervised models are then compared with supervised, feed-forward networks that learn an explicit mapping between different spatial reference frames. Our simulations show that both architectural and learning constraints strongly influenced the emergent coding of visual space in terms of distribution of tuning functions at the level of single neurons. Unsupervised models, and particularly RBMs, were found to more closely adhere to neurophysiological data from single-cell recordings in the primate parietal cortex. These results provide new insights into how basic properties of artificial neural networks might be relevant for modeling neural information processing in biological systems. PMID:28377709

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

The Role of Graphlets in Viral Processes on Networks

NASA Astrophysics Data System (ADS)

Khorshidi, Samira; Al Hasan, Mohammad; Mohler, George; Short, Martin B.

2018-05-01

Predicting the evolution of viral processes on networks is an important problem with applications arising in biology, the social sciences, and the study of the Internet. In existing works, mean-field analysis based upon degree distribution is used for the prediction of viral spreading across networks of different types. However, it has been shown that degree distribution alone fails to predict the behavior of viruses on some real-world networks and recent attempts have been made to use assortativity to address this shortcoming. In this paper, we show that adding assortativity does not fully explain the variance in the spread of viruses for a number of real-world networks. We propose using the graphlet frequency distribution in combination with assortativity to explain variations in the evolution of viral processes across networks with identical degree distribution. Using a data-driven approach by coupling predictive modeling with viral process simulation on real-world networks, we show that simple regression models based on graphlet frequency distribution can explain over 95% of the variance in virality on networks with the same degree distribution but different network topologies. Our results not only highlight the importance of graphlets but also identify a small collection of graphlets which may have the highest influence over the viral processes on a network.

Comprehensive evaluation of impacts of distributed generation integration in distribution network

NASA Astrophysics Data System (ADS)

Peng, Sujiang; Zhou, Erbiao; Ji, Fengkun; Cao, Xinhui; Liu, Lingshuang; Liu, Zifa; Wang, Xuyang; Cai, Xiaoyu

2018-04-01

All Distributed generation (DG) as the supplement to renewable energy centralized utilization, is becoming the focus of development direction of renewable energy utilization. With the increasing proportion of DG in distribution network, the network power structure, power flow distribution, operation plans and protection are affected to some extent. According to the main impacts of DG, a comprehensive evaluation model of distributed network with DG is proposed in this paper. A comprehensive evaluation index system including 7 aspects, along with their corresponding index calculation method is established for quantitative analysis. The indices under different access capacity of DG in distribution network are calculated based on the IEEE RBTS-Bus 6 system and the evaluation result is calculated by analytic hierarchy process (AHP). The proposed model and method are verified effective and validity through case study.

Research of the self-healing technologies in the optical communication network of distribution automation

NASA Astrophysics Data System (ADS)

Wang, Hao; Zhong, Guoxin

2018-03-01

Optical communication network is the mainstream technique of the communication networks for distribution automation, and self-healing technologies can improve the in reliability of the optical communication networks significantly. This paper discussed the technical characteristics and application scenarios of several network self-healing technologies in the access layer, the backbone layer and the core layer of the optical communication networks for distribution automation. On the base of the contrastive analysis, this paper gives an application suggestion of these self-healing technologies.

Strategy on energy saving reconstruction of distribution networks based on life cycle cost

NASA Astrophysics Data System (ADS)

Chen, Xiaofei; Qiu, Zejing; Xu, Zhaoyang; Xiao, Chupeng

2017-08-01

Because the actual distribution network reconstruction project funds are often limited, the cost-benefit model and the decision-making method are crucial for distribution network energy saving reconstruction project. From the perspective of life cycle cost (LCC), firstly the research life cycle is determined for the energy saving reconstruction of distribution networks with multi-devices. Then, a new life cycle cost-benefit model for energy-saving reconstruction of distribution network is developed, in which the modification schemes include distribution transformers replacement, lines replacement and reactive power compensation. In the operation loss cost and maintenance cost area, the operation cost model considering the influence of load season characteristics and the maintenance cost segmental model of transformers are proposed. Finally, aiming at the highest energy saving profit per LCC, a decision-making method is developed while considering financial and technical constraints as well. The model and method are applied to a real distribution network reconstruction, and the results prove that the model and method are effective.

Topology Counts: Force Distributions in Circular Spring Networks.

PubMed

Heidemann, Knut M; Sageman-Furnas, Andrew O; Sharma, Abhinav; Rehfeldt, Florian; Schmidt, Christoph F; Wardetzky, Max

2018-02-09

Filamentous polymer networks govern the mechanical properties of many biological materials. Force distributions within these networks are typically highly inhomogeneous, and, although the importance of force distributions for structural properties is well recognized, they are far from being understood quantitatively. Using a combination of probabilistic and graph-theoretical techniques, we derive force distributions in a model system consisting of ensembles of random linear spring networks on a circle. We show that characteristic quantities, such as the mean and variance of the force supported by individual springs, can be derived explicitly in terms of only two parameters: (i) average connectivity and (ii) number of nodes. Our analysis shows that a classical mean-field approach fails to capture these characteristic quantities correctly. In contrast, we demonstrate that network topology is a crucial determinant of force distributions in an elastic spring network. Our results for 1D linear spring networks readily generalize to arbitrary dimensions.

Epidemic extinction paths in complex networks

NASA Astrophysics Data System (ADS)

Hindes, Jason; Schwartz, Ira B.

2017-05-01

We study the extinction of long-lived epidemics on finite complex networks induced by intrinsic noise. Applying analytical techniques to the stochastic susceptible-infected-susceptible model, we predict the distribution of large fluctuations, the most probable or optimal path through a network that leads to a disease-free state from an endemic state, and the average extinction time in general configurations. Our predictions agree with Monte Carlo simulations on several networks, including synthetic weighted and degree-distributed networks with degree correlations, and an empirical high school contact network. In addition, our approach quantifies characteristic scaling patterns for the optimal path and distribution of large fluctuations, both near and away from the epidemic threshold, in networks with heterogeneous eigenvector centrality and degree distributions.

Epidemic extinction paths in complex networks.

PubMed

Hindes, Jason; Schwartz, Ira B

2017-05-01

We study the extinction of long-lived epidemics on finite complex networks induced by intrinsic noise. Applying analytical techniques to the stochastic susceptible-infected-susceptible model, we predict the distribution of large fluctuations, the most probable or optimal path through a network that leads to a disease-free state from an endemic state, and the average extinction time in general configurations. Our predictions agree with Monte Carlo simulations on several networks, including synthetic weighted and degree-distributed networks with degree correlations, and an empirical high school contact network. In addition, our approach quantifies characteristic scaling patterns for the optimal path and distribution of large fluctuations, both near and away from the epidemic threshold, in networks with heterogeneous eigenvector centrality and degree distributions.

40 CFR 51.373 - Implementation deadlines.

Code of Federal Regulations, 2011 CFR

2011-07-01

...-repair network to a test-only network may phase in the change between January of 1995 and January of 1996... 1999. (g) On-Board Diagnostic checks shall be implemented in all basic, low enhanced and high enhanced...

40 CFR 51.373 - Implementation deadlines.

Code of Federal Regulations, 2013 CFR

2013-07-01

...-repair network to a test-only network may phase in the change between January of 1995 and January of 1996... 1999. (g) On-Board Diagnostic checks shall be implemented in all basic, low enhanced and high enhanced...

40 CFR 51.373 - Implementation deadlines.

Code of Federal Regulations, 2010 CFR

2010-07-01

...-repair network to a test-only network may phase in the change between January of 1995 and January of 1996... 1999. (g) On-Board Diagnostic checks shall be implemented in all basic, low enhanced and high enhanced...

40 CFR 51.373 - Implementation deadlines.

Code of Federal Regulations, 2012 CFR

2012-07-01

...-repair network to a test-only network may phase in the change between January of 1995 and January of 1996... 1999. (g) On-Board Diagnostic checks shall be implemented in all basic, low enhanced and high enhanced...

40 CFR 51.373 - Implementation deadlines.

Code of Federal Regulations, 2014 CFR

2014-07-01

...-repair network to a test-only network may phase in the change between January of 1995 and January of 1996... 1999. (g) On-Board Diagnostic checks shall be implemented in all basic, low enhanced and high enhanced...

Measuring Social Networks for Medical Research in Lower-Income Settings

PubMed Central

Kelly, Laura; Patel, Shivani A.; Narayan, K. M. Venkat; Prabhakaran, Dorairaj; Cunningham, Solveig A.

2014-01-01

Social networks are believed to affect health-related behaviors and health. Data to examine the links between social relationships and health in low- and middle-income country settings are limited. We provide guidance for introducing an instrument to collect social network data as part of epidemiological surveys, drawing on experience in urban India. We describe development and fielding of an instrument to collect social network information relevant to health behaviors among adults participating in a large, population-based study of non-communicable diseases in Delhi, India. We discuss basic characteristics of social networks relevant to health including network size, health behaviors of network partners (i.e., network exposures), network homogeneity, network diversity, strength of ties, and multiplexity. Data on these characteristics can be collected using a short instrument of 11 items asked about up to 5 network members and 3 items about the network generally, administered in approximately 20 minutes. We found high willingness to respond to questions about social networks (97% response). Respondents identified an average of 3.8 network members, most often relatives (80% of network ties), particularly blood relationships. Ninety-one percent of respondents reported that their primary contacts for discussing health concerns were relatives. Among all listed ties, 91% of most frequent snack partners and 64% of exercise partners in the last two weeks were relatives. These results demonstrate that family relationships are the crux of social networks in some settings, including among adults in urban India. Collecting basic information about social networks can be feasibly and effectively done within ongoing epidemiological studies. PMID:25153127

Properties of four real world collaboration--competition networks

NASA Astrophysics Data System (ADS)

Fu, Chun-Hua; Xu, Xiu-Lian; He, Da-Ren

2009-03-01

Our research group has empirically investigated 9 real world collaboration networks and 25 real world cooperation-competition networks. Among the 34 real world systems, all the 9 real world collaboration networks and 6 real world cooperation-competition networks show the unimodal act-size distribution and the shifted power law distribution of degree and act-degree. We have proposed a collaboration network evolution model for an explanation of the rules [1]. The other 14 real world cooperation-competition networks show that the act-size distributions are not unimodal; instead, they take qualitatively the same shifted power law forms as the degree and act-degree distributions. The properties of four systems (the main land movie film network, Beijing restaurant network, 2004 Olympic network, and Tao-Bao notebook computer sale network) are reported in detail as examples. Via a numerical simulation, we show that the new rule can still be explained by the above-mentioned model. [1] H. Chang, B. B. Su, et al. Phsica A, 2007, 383: 687-702.

The design of IPv6's transitional scheme in university

NASA Astrophysics Data System (ADS)

Li, Biqing; Li, Zhao

2017-05-01

According to the current network environment of campus, the specific scheme of network transition is proposed, which has conducted detailed analyses for the basic concepts, the types of address, the necessary technology for transition and the agreement and principle of transition. According to the tunneling technology of IPv6, the IPv4 network and IPv6 network can communicate with each other, and the network of whole campus can operate well.

SU-E-T-23: A Developing Australian Network for Datamining and Modelling Routine Radiotherapy Clinical Data and Radiomics Information for Rapid Learning and Clinical Decision Support

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thwaites, D; Holloway, L; Bailey, M

2015-06-15

Purpose: Large amounts of routine radiotherapy (RT) data are available, which can potentially add clinical evidence to support better decisions. A developing collaborative Australian network, with a leading European partner, aims to validate, implement and extend European predictive models (PMs) for Australian practice and assess their impact on future patient decisions. Wider objectives include: developing multi-institutional rapid learning, using distributed learning approaches; and assessing and incorporating radiomics information into PMs. Methods: Two initial standalone pilots were conducted; one on NSCLC, the other on larynx, patient datasets in two different centres. Open-source rapid learning systems were installed, for data extraction andmore » mining to collect relevant clinical parameters from the centres’ databases. The European DSSs were learned (“training cohort”) and validated against local data sets (“clinical cohort”). Further NSCLC studies are underway in three more centres to pilot a wider distributed learning network. Initial radiomics work is underway. Results: For the NSCLC pilot, 159/419 patient datasets were identified meeting the PM criteria, and hence eligible for inclusion in the curative clinical cohort (for the larynx pilot, 109/125). Some missing data were imputed using Bayesian methods. For both, the European PMs successfully predicted prognosis groups, but with some differences in practice reflected. For example, the PM-predicted good prognosis NSCLC group was differentiated from a combined medium/poor prognosis group (2YOS 69% vs. 27%, p<0.001). Stage was less discriminatory in identifying prognostic groups. In the good prognosis group two-year overall survival was 65% in curatively and 18% in palliatively treated patients. Conclusion: The technical infrastructure and basic European PMs support prognosis prediction for these Australian patient groups, showing promise for supporting future personalized treatment decisions, improved treatment quality and potential practice changes. The early indications from the distributed learning and radiomics pilots strengthen this. Improved routine patient data quality should strengthen such rapid learning systems.« less

Robust quantum network architectures and topologies for entanglement distribution

NASA Astrophysics Data System (ADS)

Das, Siddhartha; Khatri, Sumeet; Dowling, Jonathan P.

2018-01-01

Entanglement distribution is a prerequisite for several important quantum information processing and computing tasks, such as quantum teleportation, quantum key distribution, and distributed quantum computing. In this work, we focus on two-dimensional quantum networks based on optical quantum technologies using dual-rail photonic qubits for the building of a fail-safe quantum internet. We lay out a quantum network architecture for entanglement distribution between distant parties using a Bravais lattice topology, with the technological constraint that quantum repeaters equipped with quantum memories are not easily accessible. We provide a robust protocol for simultaneous entanglement distribution between two distant groups of parties on this network. We also discuss a memory-based quantum network architecture that can be implemented on networks with an arbitrary topology. We examine networks with bow-tie lattice and Archimedean lattice topologies and use percolation theory to quantify the robustness of the networks. In particular, we provide figures of merit on the loss parameter of the optical medium that depend only on the topology of the network and quantify the robustness of the network against intermittent photon loss and intermittent failure of nodes. These figures of merit can be used to compare the robustness of different network topologies in order to determine the best topology in a given real-world scenario, which is critical in the realization of the quantum internet.

An exploration of alternative visualisations of the basic helix-loop-helix protein interaction network

PubMed Central

Holden, Brian J; Pinney, John W; Lovell, Simon C; Amoutzias, Grigoris D; Robertson, David L

2007-01-01

Background Alternative representations of biochemical networks emphasise different aspects of the data and contribute to the understanding of complex biological systems. In this study we present a variety of automated methods for visualisation of a protein-protein interaction network, using the basic helix-loop-helix (bHLH) family of transcription factors as an example. Results Network representations that arrange nodes (proteins) according to either continuous or discrete information are investigated, revealing the existence of protein sub-families and the retention of interactions following gene duplication events. Methods of network visualisation in conjunction with a phylogenetic tree are presented, highlighting the evolutionary relationships between proteins, and clarifying the context of network hubs and interaction clusters. Finally, an optimisation technique is used to create a three-dimensional layout of the phylogenetic tree upon which the protein-protein interactions may be projected. Conclusion We show that by incorporating secondary genomic, functional or phylogenetic information into network visualisation, it is possible to move beyond simple layout algorithms based on network topology towards more biologically meaningful representations. These new visualisations can give structure to complex networks and will greatly help in interpreting their evolutionary origins and functional implications. Three open source software packages (InterView, TVi and OptiMage) implementing our methods are available. PMID:17683601

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.

Radiological tele-immersion for next generation networks.

PubMed

Ai, Z; Dech, F; Rasmussen, M; Silverstein, J C

2000-01-01

Since the acquisition of high-resolution three-dimensional patient images has become widespread, medical volumetric datasets (CT or MR) larger than 100 MB and encompassing more than 250 slices are common. It is important to make this patient-specific data quickly available and usable to many specialists at different geographical sites. Web-based systems have been developed to provide volume or surface rendering of medical data over networks with low fidelity, but these cannot adequately handle stereoscopic visualization or huge datasets. State-of-the-art virtual reality techniques and high speed networks have made it possible to create an environment for clinicians geographically distributed to immersively share these massive datasets in real-time. An object-oriented method for instantaneously importing medical volumetric data into Tele-Immersive environments has been developed at the Virtual Reality in Medicine Laboratory (VRMedLab) at the University of Illinois at Chicago (UIC). This networked-VR setup is based on LIMBO, an application framework or template that provides the basic capabilities of Tele-Immersion. We have developed a modular general purpose Tele-Immersion program that automatically combines 3D medical data with the methods for handling the data. For this purpose a DICOM loader for IRIS Performer has been developed. The loader was designed for SGI machines as a shared object, which is executed at LIMBO's runtime. The loader loads not only the selected DICOM dataset, but also methods for rendering, handling, and interacting with the data, bringing networked, real-time, stereoscopic interaction with radiological data to reality. Collaborative, interactive methods currently implemented in the loader include cutting planes and windowing. The Tele-Immersive environment has been tested on the UIC campus over an ATM network. We tested the environment with 3 nodes; one ImmersaDesk at the VRMedLab, one CAVE at the Electronic Visualization Laboratory (EVL) on east campus, and a CT scan machine in UIC Hospital. CT data was pulled directly from the scan machine to the Tele-Immersion server in our Laboratory, and then the data was synchronously distributed by our Onyx2 Rack server to all the VR setups. Instead of permitting medical volume visualization at one VR device, by combining teleconferencing, tele-presence, and virtual reality, the Tele-Immersive environment will enable geographically distributed clinicians to intuitively interact with the same medical volumetric models, point, gesture, converse, and see each other. This environment will bring together clinicians at different geographic locations to participate in Tele-Immersive consultation and collaboration.

An improved AVC strategy applied in distributed wind power system

NASA Astrophysics Data System (ADS)

Zhao, Y. N.; Liu, Q. H.; Song, S. Y.; Mao, W.

2016-08-01

Traditional AVC strategy is mainly used in wind farm and only concerns about grid connection point, which is not suitable for distributed wind power system. Therefore, this paper comes up with an improved AVC strategy applied in distributed wind power system. The strategy takes all nodes of distribution network into consideration and chooses the node having the most serious voltage deviation as control point to calculate the reactive power reference. In addition, distribution principles can be divided into two conditions: when wind generators access to network on single node, the reactive power reference is distributed according to reactive power capacity; when wind generators access to network on multi-node, the reference is distributed according to sensitivity. Simulation results show the correctness and reliability of the strategy. Compared with traditional control strategy, the strategy described in this paper can make full use of generators reactive power output ability according to the distribution network voltage condition and improve the distribution network voltage level effectively.

Final Report - Cloud-Based Management Platform for Distributed, Multi-Domain Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chowdhury, Pulak; Mukherjee, Biswanath

2017-11-03

In this Department of Energy (DOE) Small Business Innovation Research (SBIR) Phase II project final report, Ennetix presents the development of a solution for end-to-end monitoring, analysis, and visualization of network performance for distributed networks. This solution benefits enterprises of all sizes, operators of distributed and federated networks, and service providers.

Neural networks and MIMD-multiprocessors

NASA Technical Reports Server (NTRS)

Vanhala, Jukka; Kaski, Kimmo

1990-01-01

Two artificial neural network models are compared. They are the Hopfield Neural Network Model and the Sparse Distributed Memory model. Distributed algorithms for both of them are designed and implemented. The run time characteristics of the algorithms are analyzed theoretically and tested in practice. The storage capacities of the networks are compared. Implementations are done using a distributed multiprocessor system.

10 CFR 431.385 - Cessation of distribution of a basic model of an electric motor.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 10 Energy 3 2010-01-01 2010-01-01 false Cessation of distribution of a basic model of an electric motor. 431.385 Section 431.385 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY EFFICIENCY PROGRAM FOR CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT Enforcement § 431.385 Cessation of distribution of a...

A practical introduction to tensor networks: Matrix product states and projected entangled pair states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Orús, Román, E-mail: roman.orus@uni-mainz.de

This is a partly non-technical introduction to selected topics on tensor network methods, based on several lectures and introductory seminars given on the subject. It should be a good place for newcomers to get familiarized with some of the key ideas in the field, specially regarding the numerics. After a very general introduction we motivate the concept of tensor network and provide several examples. We then move on to explain some basics about Matrix Product States (MPS) and Projected Entangled Pair States (PEPS). Selected details on some of the associated numerical methods for 1d and 2d quantum lattice systems aremore » also discussed. - Highlights: • A practical introduction to selected aspects of tensor network methods is presented. • We provide analytical examples of MPS and 2d PEPS. • We provide basic aspects on several numerical methods for MPS and 2d PEPS. • We discuss a number of applications of tensor network methods from a broad perspective.« less

Radio observations of the Milky Way from the classroom

NASA Astrophysics Data System (ADS)

Chyży, Krzysztof T.

2014-12-01

We present the project to introduce the first European network of radio telescopes for education. It enables pupils to detect spectral line emission of neutral hydrogen in the Milky Way at a wavelength of 21 cm. Any classroom connected to Internet via any web-browser can remotely control one of the radio-telescopes, observe and analyse obtained spectra: derive the Milky-Way rotation curve and recognise spiral arms in hydrogen distribution. Doing exercises pupils, guided by their teachers, learn the basics of radio astronomy research, use scientific method to explore and interpret the attained spectral data. A range of attractive educational materials are prepared to help in disseminating the scientific knowledge in the classroom and demonstrate the modern information technology.

Modelling Parameters Characterizing Selected Water Supply Systems in Lower Silesia Province

NASA Astrophysics Data System (ADS)

Nowogoński, Ireneusz; Ogiołda, Ewa

2017-12-01

The work presents issues of modelling water supply systems in the context of basic parameters characterizing their operation. In addition to typical parameters, such as water pressure and flow rate, assessing the age of the water is important, as a parameter of assessing the quality of the distributed medium. The analysis was based on two facilities, including one with a diverse spectrum of consumers, including residential housing and industry. The carried out simulations indicate the possibility of the occurrence of water quality degradation as a result of excessively long periods of storage in the water supply network. Also important is the influence of the irregularity of water use, especially in the case of supplying various kinds of consumers (in the analysed case - mining companies).

A broadband multimedia TeleLearning system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Ruiping; Karmouch, A.

1996-12-31

In this paper we discuss a broadband multimedia TeleLearning system under development in the Multimedia Information Research Laboratory at the University of Ottawa. The system aims at providing a seamless environment for TeleLearning using the latest telecommunication and multimedia information processing technology. It basically consists of a media production center, a courseware author site, a courseware database, a courseware user site, and an on-line facilitator site. All these components are distributed over an ATM network and work together to offer a multimedia interactive courseware service. An MHEG-based model is exploited in designing the system architecture to achieve the real-time, interactive,more » and reusable information interchange through heterogeneous platforms. The system architecture, courseware processing strategies, courseware document models are presented.« less

Integrating Biogeography with Contemporary Niche Theory.

PubMed

Godsoe, William; Jankowski, Jill; Holt, Robert D; Gravel, Dominique

2017-07-01

There is no consensus on when biotic interactions impact the range limits of species. Starting from MacArthur's use of invasibility to understand how biotic interactions influence coexistence, here we examine how biotic interactions shape species distributions. Range limits emerge from how birth, death, and movement rates vary with the environment. We clarify some basic issues revolving around niche definitions, illustrated with simple resource-consumer theory. We then highlight two different avenues for linking community theory and range theory; the first based on calculating the effects of biotic interactions on range limits across scales and landscape configurations, and the second based on aggregate measures of diffuse interactions and network strength. We conclude with suggestions for a future research agenda. Copyright © 2017 Elsevier Ltd. All rights reserved.

Preparation of Professional Training Teachers for Network Cooperation between Educational Establishments during Labor Preparation

ERIC Educational Resources Information Center

Tarasjuk, Olga V.; Fedulova, Ksenia A.; Fedulova, Marina A.; Kryukova, Polina S.; Yadretsov, Vyacheslav ?.

2016-01-01

Relevance of the problem being investigated is conditioned by the necessity to arrange network cooperation between educational institutions during labor force preparation in the conditions of informatization of educational and technological processes. The aim of the article is to prove the necessity of including basics of network cooperation…

Epidemic spreading on one-way-coupled networks

NASA Astrophysics Data System (ADS)

Wang, Lingna; Sun, Mengfeng; Chen, Shanshan; Fu, Xinchu

2016-09-01

Numerous real-world networks (e.g., social, communicational, and biological networks) have been observed to depend on each other, and this results in interconnected networks with different topology structures and dynamics functions. In this paper, we focus on the scenario of epidemic spreading on one-way-coupled networks comprised of two subnetworks, which can manifest the transmission of some zoonotic diseases. By proposing a mathematical model through mean-field approximation approach, we prove the global stability of the disease-free and endemic equilibria of this model. Through the theoretical and numerical analysis, we obtain interesting results: the basic reproduction number R0 of the whole network is the maximum of the basic reproduction numbers of the two subnetworks; R0 is independent of the cross-infection rate and cross contact pattern; R0 increases rapidly with the growth of inner infection rate if the inner contact pattern is scale-free; in order to eradicate zoonotic diseases from human beings, we must simultaneously eradicate them from animals; bird-to-bird infection rate has bigger impact on the human's average infected density than bird-to-human infection rate.

Distributed controller clustering in software defined networks.

PubMed

Abdelaziz, Ahmed; Fong, Ang Tan; Gani, Abdullah; Garba, Usman; Khan, Suleman; Akhunzada, Adnan; Talebian, Hamid; Choo, Kim-Kwang Raymond

2017-01-01

Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability.

Parameter Prediction of Hydraulic Fracture for Tight Reservoir Based on Micro-Seismic and History Matching

NASA Astrophysics Data System (ADS)

Zhang, Kai; Ma, Xiaopeng; Li, Yanlai; Wu, Haiyang; Cui, Chenyu; Zhang, Xiaoming; Zhang, Hao; Yao, Jun

Hydraulic fracturing is an important measure for the development of tight reservoirs. In order to describe the distribution of hydraulic fractures, micro-seismic diagnostic was introduced into petroleum fields. Micro-seismic events may reveal important information about static characteristics of hydraulic fracturing. However, this method is limited to reflect the distribution area of the hydraulic fractures and fails to provide specific parameters. Therefore, micro-seismic technology is integrated with history matching to predict the hydraulic fracture parameters in this paper. Micro-seismic source location is used to describe the basic shape of hydraulic fractures. After that, secondary modeling is considered to calibrate the parameters information of hydraulic fractures by using DFM (discrete fracture model) and history matching method. In consideration of fractal feature of hydraulic fracture, fractal fracture network model is established to evaluate this method in numerical experiment. The results clearly show the effectiveness of the proposed approach to estimate the parameters of hydraulic fractures.

New activity pattern in human interactive dynamics

NASA Astrophysics Data System (ADS)

Formentin, Marco; Lovison, Alberto; Maritan, Amos; Zanzotto, Giovanni

2015-09-01

We investigate the response function of human agents as demonstrated by written correspondence, uncovering a new pattern for how the reactive dynamics of individuals is distributed across the set of each agent’s contacts. In long-term empirical data on email, we find that the set of response times considered separately for the messages to each different correspondent of a given writer, generate a family of heavy-tailed distributions, which have largely the same features for all agents, and whose characteristic times grow exponentially with the rank of each correspondent. We furthermore show that this new behavioral pattern emerges robustly by considering weighted moving averages of the priority-conditioned response-time probabilities generated by a basic prioritization model. Our findings clarify how the range of priorities in the inputs from one’s environment underpin and shape the dynamics of agents embedded in a net of reactive relations. These newly revealed activity patterns might be universal, being present in other general interactive environments, and constrain future models of communication and interaction networks, affecting their architecture and evolution.

Constructing a Watts-Strogatz network from a small-world network with symmetric degree distribution.

PubMed

Menezes, Mozart B C; Kim, Seokjin; Huang, Rongbing

2017-01-01

Though the small-world phenomenon is widespread in many real networks, it is still challenging to replicate a large network at the full scale for further study on its structure and dynamics when sufficient data are not readily available. We propose a method to construct a Watts-Strogatz network using a sample from a small-world network with symmetric degree distribution. Our method yields an estimated degree distribution which fits closely with that of a Watts-Strogatz network and leads into accurate estimates of network metrics such as clustering coefficient and degree of separation. We observe that the accuracy of our method increases as network size increases.

Wealth distribution on complex networks

NASA Astrophysics Data System (ADS)

Ichinomiya, Takashi

2012-12-01

We study the wealth distribution of the Bouchaud-Mézard model on complex networks. It is known from numerical simulations that this distribution depends on the topology of the network; however, no one has succeeded in explaining it. Using “adiabatic” and “independent” assumptions along with the central-limit theorem, we derive equations that determine the probability distribution function. The results are compared to those of simulations for various networks. We find good agreement between our theory and the simulations, except for the case of Watts-Strogatz networks with a low rewiring rate due to the breakdown of independent assumption.

DNA-Based Dynamic Reaction Networks.

PubMed

Fu, Ting; Lyu, Yifan; Liu, Hui; Peng, Ruizi; Zhang, Xiaobing; Ye, Mao; Tan, Weihong

2018-05-21

Deriving from logical and mechanical interactions between DNA strands and complexes, DNA-based artificial reaction networks (RNs) are attractive for their high programmability, as well as cascading and fan-out ability, which are similar to the basic principles of electronic logic gates. Arising from the dream of creating novel computing mechanisms, researchers have placed high hopes on the development of DNA-based dynamic RNs and have strived to establish the basic theories and operative strategies of these networks. This review starts by looking back on the evolution of DNA dynamic RNs; in particular' the most significant applications in biochemistry occurring in recent years. Finally, we discuss the perspectives of DNA dynamic RNs and give a possible direction for the development of DNA circuits. Copyright © 2018. Published by Elsevier Ltd.

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.

A cascade reaction network mimicking the basic functional steps of adaptive immune response

NASA Astrophysics Data System (ADS)

Han, Da; Wu, Cuichen; You, Mingxu; Zhang, Tao; Wan, Shuo; Chen, Tao; Qiu, Liping; Zheng, Zheng; Liang, Hao; Tan, Weihong

2015-10-01

Biological systems use complex ‘information-processing cores’ composed of molecular networks to coordinate their external environment and internal states. An example of this is the acquired, or adaptive, immune system (AIS), which is composed of both humoral and cell-mediated components. Here we report the step-by-step construction of a prototype mimic of the AIS that we call an adaptive immune response simulator (AIRS). DNA and enzymes are used as simple artificial analogues of the components of the AIS to create a system that responds to specific molecular stimuli in vitro. We show that this network of reactions can function in a manner that is superficially similar to the most basic responses of the vertebrate AIS, including reaction sequences that mimic both humoral and cellular responses. As such, AIRS provides guidelines for the design and engineering of artificial reaction networks and molecular devices.

Empirical Reference Distributions for Networks of Different Size

PubMed Central

Smith, Anna; Calder, Catherine A.; Browning, Christopher R.

2016-01-01

Network analysis has become an increasingly prevalent research tool across a vast range of scientific fields. Here, we focus on the particular issue of comparing network statistics, i.e. graph-level measures of network structural features, across multiple networks that differ in size. Although “normalized” versions of some network statistics exist, we demonstrate via simulation why direct comparison is often inappropriate. We consider normalizing network statistics relative to a simple fully parameterized reference distribution and demonstrate via simulation how this is an improvement over direct comparison, but still sometimes problematic. We propose a new adjustment method based on a reference distribution constructed as a mixture model of random graphs which reflect the dependence structure exhibited in the observed networks. We show that using simple Bernoulli models as mixture components in this reference distribution can provide adjusted network statistics that are relatively comparable across different network sizes but still describe interesting features of networks, and that this can be accomplished at relatively low computational expense. Finally, we apply this methodology to a collection of ecological networks derived from the Los Angeles Family and Neighborhood Survey activity location data. PMID:27721556

[Emission Characteristics of Vehicle Exhaust in Beijing Based on Actual Traffic Flow Information].

PubMed

Fan, Shou-bin; Tian, Ling-di; Zhang, Dong-xu; Qu, Song

2015-08-01

The basic data of traffic volume, vehicle type constitute and speed on road networks in Beijing was obtained fly modei simulation and field survey. Based on actual traffic flow information and. emission factors data with temporal and spatial distribution features, emission inventory of motor vehicle exhaust in Beijing was built on the ArcGIS platform, meanwhile, the actual road emission characteristics and spatial distribution of the pollutant emissions were analyzed. The results showed that the proportion of passenger car was higher than 89% on each type of road in the urban, and the proportion of passenger car was the highest in suburban roads as well while the pickup truck, medium truck, heavy truck, motorbus, tractor and motorcycle also occupied a certain proportion. There was a positive correlation between the pollutant emission intensity and traffic volume, and the emission intensity was generally higher in daytime than nighttime, but the diurnal variation trend of PM emission was not clear for suburban roads and the emission intensity was higher in nighttime than daytime for highway. The emission intensities in urban area, south, southeast and northeast areas near urban were higher than those in the western and northern mountainous areas with lower density of road network. The ring roads in urban and highways in suburban had higher emission intensity because of the heavy traffic volume.

Multi-equilibrium property of metabolic networks: SSI module.

PubMed

Lei, Hong-Bo; Zhang, Ji-Feng; Chen, Luonan

2011-06-20

Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI) metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module.

Multi-equilibrium property of metabolic networks: SSI module

PubMed Central

2011-01-01

Background Revealing the multi-equilibrium property of a metabolic network is a fundamental and important topic in systems biology. Due to the complexity of the metabolic network, it is generally a difficult task to study the problem as a whole from both analytical and numerical viewpoint. On the other hand, the structure-oriented modularization idea is a good choice to overcome such a difficulty, i.e. decomposing the network into several basic building blocks and then studying the whole network through investigating the dynamical characteristics of the basic building blocks and their interactions. Single substrate and single product with inhibition (SSI) metabolic module is one type of the basic building blocks of metabolic networks, and its multi-equilibrium property has important influence on that of the whole metabolic networks. Results In this paper, we describe what the SSI metabolic module is, characterize the rates of the metabolic reactions by Hill kinetics and give a unified model for SSI modules by using a set of nonlinear ordinary differential equations with multi-variables. Specifically, a sufficient and necessary condition is first given to describe the injectivity of a class of nonlinear systems, and then, the sufficient condition is used to study the multi-equilibrium property of SSI modules. As a main theoretical result, for the SSI modules in which each reaction has no more than one inhibitor, a sufficient condition is derived to rule out multiple equilibria, i.e. the Jacobian matrix of its rate function is nonsingular everywhere. Conclusions In summary, we describe SSI modules and give a general modeling framework based on Hill kinetics, and provide a sufficient condition for ruling out multiple equilibria of a key type of SSI module. PMID:21689474

A distributed lumped active all-pass network configuration.

NASA Technical Reports Server (NTRS)

Huelsman, L. P.; Raghunath, S.

1972-01-01

In this correspondence a new and interesting distributed lumped active network configuration that realizes an all-pass network function is described. A design chart for determining the values of the network elements is included.

Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and Navigation Support

DTIC Science & Technology

2014-09-30

underwater acoustic communication technologies for autonomous distributed underwater networks , through innovative signal processing, coding, and...4. TITLE AND SUBTITLE Advancing Underwater Acoustic Communication for Autonomous Distributed Networks via Sparse Channel Sensing, Coding, and...coding: 3) OFDM modulated dynamic coded cooperation in underwater acoustic channels; 3 Localization, Networking , and Testbed: 4) On-demand

The Development of the Command and Control Centre for Trial Kondari

DTIC Science & Technology

2010-07-01

the C2 centre inside a blue bubble whose modems have privately assigned IP addresses which are authenticated by Telstra’s radius server. No other sim...cards can communicate on this private network unless authorised by the radius server. The Next IP network is a network bubble within the larger Next...for all machines on the network.  EPLRS Network Manager (ENM) radio – authenticates and manages all the EPLRS radios. The basic plan’s final

Brain network dysfunction in youth with obsessive-compulsive disorder induced by simple uni-manual behavior: The role of the dorsal anterior cingulate cortex

PubMed Central

Friedman, Amy L.; Burgess, Ashley; Ramaseshan, Karthik; Easter, Phil; Khatib, Dalal; Chowdury, Asadur; Arnold, Paul D.; Hanna, Gregory L.; Rosenberg, David R.; Diwadkar, Vaibhav A.

2017-01-01

In an effort to elucidate differences in functioning brain networks between youth with obsessive-compulsive disorder and controls, we used fMRI signals to analyze brain network interactions of the dorsal anterior cingulate cortex (dACC) during visually coordinated motor responses. Subjects made a uni-manual response to briefly presented probes, at periodic (allowing participants to maintain a “motor set”) or random intervals (demanding reactive responses). Network interactions were assessed using psycho-physiological interaction (PPI), a basic model of functional connectivity evaluating modulatory effects of the dACC in the context of each task condition. Across conditions, OCD were characterized by hyper-modulation by the dACC, with loci alternatively observed as both condition-general and condition-specific. Thus, dynamically driven task demands during simple uni-manual motor control induce compensatory network interactions in cortical-thalamic regions in OCD. These findings support previous research in OCD showing compensatory network interactions during complex memory tasks, but establish that these network effects are observed during basic sensorimotor processing. Thus, these patterns of network dysfunction may in fact be independent of the complexity of tasks used to induce brain network activity. Hypothesis-driven approaches coupled with sophisticated network analyses are a highly valuable approach in using fMRI to uncover mechanisms in disorders like OCD. PMID:27992792

Distributed Processing System for Restoration of Electric Power Distribution Network Using Two-Layered Contract Net Protocol

NASA Astrophysics Data System (ADS)

Kodama, Yu; Hamagami, Tomoki

Distributed processing system for restoration of electric power distribution network using two-layered CNP is proposed. The goal of this study is to develop the restoration system which adjusts to the future power network with distributed generators. The state of the art of this study is that the two-layered CNP is applied for the distributed computing environment in practical use. The two-layered CNP has two classes of agents, named field agent and operating agent in the network. In order to avoid conflicts of tasks, operating agent controls privilege for managers to send the task announcement messages in CNP. This technique realizes the coordination between agents which work asynchronously in parallel with others. Moreover, this study implements the distributed processing system using a de-fact standard multi-agent framework, JADE(Java Agent DEvelopment framework). This study conducts the simulation experiments of power distribution network restoration and compares the proposed system with the previous system. We confirmed the results show effectiveness of the proposed system.

High Voltage Distribution System (HVDS) as a better system compared to Low Voltage Distribution System (LVDS) applied at Medan city power network

NASA Astrophysics Data System (ADS)

Dinzi, R.; Hamonangan, TS; Fahmi, F.

2018-02-01

In the current distribution system, a large-capacity distribution transformer supplies loads to remote locations. The use of 220/380 V network is nowadays less common compared to 20 kV network. This results in losses due to the non-optimal distribution transformer, which neglected the load location, poor consumer profile, and large power losses along the carrier. This paper discusses how high voltage distribution systems (HVDS) can be a better system used in distribution networks than the currently used distribution system (Low Voltage Distribution System, LVDS). The proposed change of the system into the new configuration is done by replacing a large-capacity distribution transformer with some smaller-capacity distribution transformers and installed them in positions that closest to the load. The use of high voltage distribution systems will result in better voltage profiles and fewer power losses. From the non-technical side, the annual savings and payback periods on high voltage distribution systems will also be the advantage.

Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data.

PubMed

Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang

2017-01-01

Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam's scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals.

Exploring Vietnamese co-authorship patterns in social sciences with basic network measures of 2008-2017 Scopus data

PubMed Central

Ho, Tung Manh; Nguyen, Ha Viet; Vuong, Thu-Trang; Dam, Quang-Minh; Pham, Hiep-Hung; Vuong, Quan-Hoang

2017-01-01

Background: Collaboration is a common occurrence among Vietnamese scientists; however, insights into Vietnamese scientific collaborations have been scarce. On the other hand, the application of social network analysis in studying science collaboration has gained much attention all over the world. The technique could be employed to explore Vietnam’s scientific community. Methods: This paper employs network theory to explore characteristics of a network of 412 Vietnamese social scientists whose papers can be found indexed in the Scopus database. Two basic network measures, density and clustering coefficient, were taken, and the entire network was studied in comparison with two of its largest components. Results: The networks connections are very sparse, with a density of only 0.47%, while the clustering coefficient is very high (58.64%). This suggests an inefficient dissemination of information, knowledge, and expertise in the network. Secondly, the disparity in levels of connection among individuals indicates that the network would easily fall apart if a few highly-connected nodes are removed. Finally, the two largest components of the network were found to differ from the entire networks in terms of measures and were both led by the most productive and well-connected researchers. Conclusions: High clustering and low density seems to be tied to inefficient dissemination of expertise among Vietnamese social scientists, and consequently low scientific output. Also low in robustness, the network shows the potential of an intellectual elite composed of well-connected, productive, and socially significant individuals. PMID:28928958

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 classical communication required for key distillation, manages the generated key material, determines a communication path between any destinations in the network, and realizes end-to-end secure transport of key material between these destinations. The paper also illustrates the operation of the network in a number of typical exploitation regimes and gives an initial estimate of the network transmission capacity, defined as the maximum amount of key that can be exchanged, or alternatively the amount of information that can be transmitted with information theoretic security, between two arbitrary nodes.

Empirical research on complex networks modeling of combat SoS based on data from real war-game, Part I: Statistical characteristics

NASA Astrophysics Data System (ADS)

Chen, Lei; Kou, Yingxin; Li, Zhanwu; Xu, An; Wu, Cheng

2018-01-01

We build a complex networks model of combat System-of-Systems (SoS) based on empirical data from a real war-game, this model is a combination of command & control (C2) subnetwork, sensors subnetwork, influencers subnetwork and logistical support subnetwork, each subnetwork has idiographic components and statistical characteristics. The C2 subnetwork is the core of whole combat SoS, it has a hierarchical structure with no modularity, of which robustness is strong enough to maintain normal operation after any two nodes is destroyed; the sensors subnetwork and influencers subnetwork are like sense organ and limbs of whole combat SoS, they are both flat modular networks of which degree distribution obey GEV distribution and power-law distribution respectively. The communication network is the combination of all subnetworks, it is an assortative Small-World network with core-periphery structure, the Intelligence & Communication Stations/Command Center integrated with C2 nodes in the first three level act as the hub nodes in communication network, and all the fourth-level C2 nodes, sensors, influencers and logistical support nodes have communication capability, they act as the periphery nodes in communication network, its degree distribution obeys exponential distribution in the beginning, Gaussian distribution in the middle, and power-law distribution in the end, and its path length obeys GEV distribution. The betweenness centrality distribution, closeness centrality distribution and eigenvector centrality are also been analyzed to measure the vulnerability of nodes.

Research on the framework and key technologies of panoramic visualization for smart distribution network

NASA Astrophysics Data System (ADS)

Du, Jian; Sheng, Wanxing; Lin, Tao; Lv, Guangxian

2018-05-01

Nowadays, the smart distribution network has made tremendous progress, and the business visualization becomes even more significant and indispensable. Based on the summarization of traditional visualization technologies and demands of smart distribution network, a panoramic visualization application is proposed in this paper. The overall architecture, integrated architecture and service architecture of panoramic visualization application is firstly presented. Then, the architecture design and main functions of panoramic visualization system are elaborated in depth. In addition, the key technologies related to the application is discussed briefly. At last, two typical visualization scenarios in smart distribution network, which are risk warning and fault self-healing, proves that the panoramic visualization application is valuable for the operation and maintenance of the distribution network.

Distributed health data networks: a practical and preferred approach to multi-institutional evaluations of comparative effectiveness, safety, and quality of care.

PubMed

Brown, Jeffrey S; Holmes, John H; Shah, Kiran; Hall, Ken; Lazarus, Ross; Platt, Richard

2010-06-01

Comparative effectiveness research, medical product safety evaluation, and quality measurement will require the ability to use electronic health data held by multiple organizations. There is no consensus about whether to create regional or national combined (eg, "all payer") databases for these purposes, or distributed data networks that leave most Protected Health Information and proprietary data in the possession of the original data holders. Demonstrate functions of a distributed research network that supports research needs and also address data holders concerns about participation. Key design functions included strong local control of data uses and a centralized web-based querying interface. We implemented a pilot distributed research network and evaluated the design considerations, utility for research, and the acceptability to data holders of methods for menu-driven querying. We developed and tested a central, web-based interface with supporting network software. Specific functions assessed include query formation and distribution, query execution and review, and aggregation of results. This pilot successfully evaluated temporal trends in medication use and diagnoses at 5 separate sites, demonstrating some of the possibilities of using a distributed research network. The pilot demonstrated the potential utility of the design, which addressed the major concerns of both users and data holders. No serious obstacles were identified that would prevent development of a fully functional, scalable network. Distributed networks are capable of addressing nearly all anticipated uses of routinely collected electronic healthcare data. Distributed networks would obviate the need for centralized databases, thus avoiding numerous obstacles.

Program Helps Simulate Neural Networks

NASA Technical Reports Server (NTRS)

Villarreal, James; Mcintire, Gary

1993-01-01

Neural Network Environment on Transputer System (NNETS) computer program provides users high degree of flexibility in creating and manipulating wide variety of neural-network topologies at processing speeds not found in conventional computing environments. Supports back-propagation and back-propagation-related algorithms. Back-propagation algorithm used is implementation of Rumelhart's generalized delta rule. NNETS developed on INMOS Transputer(R). Predefines back-propagation network, Jordan network, and reinforcement network to assist users in learning and defining own networks. Also enables users to configure other neural-network paradigms from NNETS basic architecture. Small portion of software written in OCCAM(R) language.

A functional connectivity-based neuromarker of sustained attention generalizes to predict recall in a reading task.

PubMed

Jangraw, David C; Gonzalez-Castillo, Javier; Handwerker, Daniel A; Ghane, Merage; Rosenberg, Monica D; Panwar, Puja; Bandettini, Peter A

2018-02-01

Sustaining attention to the task at hand is a crucial part of everyday life, from following a lecture at school to maintaining focus while driving. Lapses in sustained attention are frequent and often problematic, with conditions such as attention deficit hyperactivity disorder affecting millions of people worldwide. Recent work has had some success in finding signatures of sustained attention in whole-brain functional connectivity (FC) measures during basic tasks, but since FC can be dynamic and task-dependent, it remains unclear how fully these signatures would generalize to a more complex and naturalistic scenario. To this end, we used a previously defined whole-brain FC network - a marker of attention that was derived from a sustained attention task - to predict the ability of participants to recall material during a free-viewing reading task. Though the predictive network was trained on a different task and set of participants, the strength of FC in the sustained attention network predicted reading recall significantly better than permutation tests where behavior was scrambled to simulate chance performance. To test the generalization of the method used to derive the sustained attention network, we applied the same method to our reading task data to find a new FC network whose strength specifically predicts reading recall. Even though the sustained attention network provided significant prediction of recall, the reading network was more predictive of recall accuracy. The new reading network's spatial distribution indicates that reading recall is highest when temporal pole regions have higher FC with left occipital regions and lower FC with bilateral supramarginal gyrus. Right cerebellar to right frontal connectivity is also indicative of poor reading recall. We examine these and other differences between the two predictive FC networks, providing new insight into the task-dependent nature of FC-based performance metrics. Published by Elsevier Inc.

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

PubMed Central

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ding, Tao; Li, Cheng; Huang, Can

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

A Hierarchical Modeling for Reactive Power Optimization With Joint Transmission and Distribution Networks by Curve Fitting

DOE PAGES

Ding, Tao; Li, Cheng; Huang, Can; ...

2017-01-09

Here, in order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost function of the slave model for the master model, which reflects the impacts of each slave model. Second,more » the transmission and distribution networks are decoupled at feeder buses, and all the distribution networks are coordinated by the master reactive power optimization model to achieve the global optimality. Finally, numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods.« less

Molecular heterogeneity at the network level: high-dimensional testing, clustering and a TCGA case study | Office of Cancer Genomics

Cancer.gov

Motivation: Molecular pathways and networks play a key role in basic and disease biology. An emerging notion is that networks encoding patterns of molecular interplay may themselves differ between contexts, such as cell type, tissue or disease (sub)type. However, while statistical testing of differences in mean expression levels has been extensively studied, testing of network differences remains challenging.

Calculating a checksum with inactive networking components in a computing system

DOEpatents

Aho, Michael E; Chen, Dong; Eisley, Noel A; Gooding, Thomas M; Heidelberger, Philip; Tauferner, Andrew T

2014-12-16

Calculating a checksum utilizing inactive networking components in a computing system, including: identifying, by a checksum distribution manager, an inactive networking component, wherein the inactive networking component includes a checksum calculation engine for computing a checksum; sending, to the inactive networking component by the checksum distribution manager, metadata describing a block of data to be transmitted by an active networking component; calculating, by the inactive networking component, a checksum for the block of data; transmitting, to the checksum distribution manager from the inactive networking component, the checksum for the block of data; and sending, by the active networking component, a data communications message that includes the block of data and the checksum for the block of data.

Calculating a checksum with inactive networking components in a computing system

DOEpatents

Aho, Michael E; Chen, Dong; Eisley, Noel A; Gooding, Thomas M; Heidelberger, Philip; Tauferner, Andrew T

2015-01-27

Calculating a checksum utilizing inactive networking components in a computing system, including: identifying, by a checksum distribution manager, an inactive networking component, wherein the inactive networking component includes a checksum calculation engine for computing a checksum; sending, to the inactive networking component by the checksum distribution manager, metadata describing a block of data to be transmitted by an active networking component; calculating, by the inactive networking component, a checksum for the block of data; transmitting, to the checksum distribution manager from the inactive networking component, the checksum for the block of data; and sending, by the active networking component, a data communications message that includes the block of data and the checksum for the block of data.

Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta

NASA Astrophysics Data System (ADS)

Zeng, Y.

2017-09-01

Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.

Mean-field equations for neuronal networks with arbitrary degree distributions.

PubMed

Nykamp, Duane Q; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex

2017-04-01

The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.

Mean-field equations for neuronal networks with arbitrary degree distributions

NASA Astrophysics Data System (ADS)

Nykamp, Duane Q.; Friedman, Daniel; Shaker, Sammy; Shinn, Maxwell; Vella, Michael; Compte, Albert; Roxin, Alex

2017-04-01

The emergent dynamics in networks of recurrently coupled spiking neurons depends on the interplay between single-cell dynamics and network topology. Most theoretical studies on network dynamics have assumed simple topologies, such as connections that are made randomly and independently with a fixed probability (Erdös-Rényi network) (ER) or all-to-all connected networks. However, recent findings from slice experiments suggest that the actual patterns of connectivity between cortical neurons are more structured than in the ER random network. Here we explore how introducing additional higher-order statistical structure into the connectivity can affect the dynamics in neuronal networks. Specifically, we consider networks in which the number of presynaptic and postsynaptic contacts for each neuron, the degrees, are drawn from a joint degree distribution. We derive mean-field equations for a single population of homogeneous neurons and for a network of excitatory and inhibitory neurons, where the neurons can have arbitrary degree distributions. Through analysis of the mean-field equations and simulation of networks of integrate-and-fire neurons, we show that such networks have potentially much richer dynamics than an equivalent ER network. Finally, we relate the degree distributions to so-called cortical motifs.

Modeling complexity in engineered infrastructure system: Water distribution network as an example

NASA Astrophysics Data System (ADS)

Zeng, Fang; Li, Xiang; Li, Ke

2017-02-01

The complex topology and adaptive behavior of infrastructure systems are driven by both self-organization of the demand and rigid engineering solutions. Therefore, engineering complex systems requires a method balancing holism and reductionism. To model the growth of water distribution networks, a complex network model was developed following the combination of local optimization rules and engineering considerations. The demand node generation is dynamic and follows the scaling law of urban growth. The proposed model can generate a water distribution network (WDN) similar to reported real-world WDNs on some structural properties. Comparison with different modeling approaches indicates that a realistic demand node distribution and co-evolvement of demand node and network are important for the simulation of real complex networks. The simulation results indicate that the efficiency of water distribution networks is exponentially affected by the urban growth pattern. On the contrary, the improvement of efficiency by engineering optimization is limited and relatively insignificant. The redundancy and robustness, on another aspect, can be significantly improved through engineering methods.

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

Playing distributed two-party quantum games on quantum networks

NASA Astrophysics Data System (ADS)

Liu, Bo-Yang; Dai, Hong-Yi; Zhang, Ming

2017-12-01

This paper investigates quantum games between two remote players on quantum networks. We propose two schemes for distributed remote quantum games: the client-server scheme based on states transmission between nodes of the network and the peer-to-peer scheme devised upon remote quantum operations. Following these schemes, we construct two designs of the distributed prisoners' dilemma game on quantum entangling networks, where concrete methods are employed for teleportation and nonlocal two-qubits unitary gates, respectively. It seems to us that the requirement for playing distributed quantum games on networks is still an open problem. We explore this problem by comparing and characterizing the two schemes from the viewpoints of network structures, quantum and classical operations, experimental realization and simplification.

The Military Theater Distribution Network Design Problem

DTIC Science & Technology

2015-03-26

The Military Theater Distribution Network Design Problem THESIS MARCH 2015 Robert R. Craig, MAJ, USA AFIT-ENS-MS-15-M-137 DEPARTMENT OF THE AIR FORCE...subject to copyright protection in the United States. AFIT-ENS-MS-15-M-137 THE MILITARY THEATER DISTRIBUTION NETWORK DESIGN PROBLEM THESIS Presented...B.S., M.S. MAJ, USA MARCH 2015 DISTRIBUTION STATEMENT A APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. AFIT-ENS-MS-15-M-137 THE MILITARY THEATER

Source Localization in Wireless Sensor Networks with Randomly Distributed Elements under Multipath Propagation Conditions

DTIC Science & Technology

2009-03-01

IN WIRELESS SENSOR NETWORKS WITH RANDOMLY DISTRIBUTED ELEMENTS UNDER MULTIPATH PROPAGATION CONDITIONS by Georgios Tsivgoulis March 2009...COVERED Engineer’s Thesis 4. TITLE Source Localization in Wireless Sensor Networks with Randomly Distributed Elements under Multipath Propagation...the non-line-of-sight information. 15. NUMBER OF PAGES 111 14. SUBJECT TERMS Wireless Sensor Network , Direction of Arrival, DOA, Random

Degree and wealth distribution in a network induced by wealth

NASA Astrophysics Data System (ADS)

Lee, Gyemin; Kim, Gwang Il

2007-09-01

A network induced by wealth is a social network model in which wealth induces individuals to participate as nodes, and every node in the network produces and accumulates wealth utilizing its links. More specifically, at every time step a new node is added to the network, and a link is created between one of the existing nodes and the new node. Innate wealth-producing ability is randomly assigned to every new node, and the node to be connected to the new node is chosen randomly, with odds proportional to the accumulated wealth of each existing node. Analyzing this network using the mean value and continuous flow approaches, we derive a relation between the conditional expectations of the degree and the accumulated wealth of each node. From this relation, we show that the degree distribution of the network induced by wealth is scale-free. We also show that the wealth distribution has a power-law tail and satisfies the 80/20 rule. We also show that, over the whole range, the cumulative wealth distribution exhibits the same topological characteristics as the wealth distributions of several networks based on the Bouchaud-Mèzard model, even though the mechanism for producing wealth is quite different in our model. Further, we show that the cumulative wealth distribution for the poor and middle class seems likely to follow by a log-normal distribution, while for the richest, the cumulative wealth distribution has a power-law behavior.

A Brief Historical Introduction to Euler's Formula for Polyhedra, Topology, Graph Theory and Networks

ERIC Educational Resources Information Center

Debnath, Lokenath

2010-01-01

This article is essentially devoted to a brief historical introduction to Euler's formula for polyhedra, topology, theory of graphs and networks with many examples from the real-world. Celebrated Konigsberg seven-bridge problem and some of the basic properties of graphs and networks for some understanding of the macroscopic behaviour of real…

Networking as a Strategic Tool, 1991

NASA Technical Reports Server (NTRS)

1991-01-01

This conference focuses on the technological advances, pitfalls, requirements, and trends involved in planning and implementing an effective computer network system. The basic theme of the conference is networking as a strategic tool. Tutorials and conference presentations explore the technology and methods involved in this rapidly changing field. Future directions are explored from a global, as well as local, perspective.

Home vs. Public Schoolers' Relationships: Differences in Social Networks.

ERIC Educational Resources Information Center

Chatham-Carpenter, April D.

Noting the lack of basic information necessary to begin to make conclusions about a home schooled child's social contacts, a study investigated the social networks of home vs. public schooled children (with a child's "social network" defined as all of the people who interact on a regular basis with the child at least once a month). The…

Marketing and population problems.

PubMed

Farley, J U; Leavitt, H J

1971-07-01

There are many elements in population programs that are more familiar to marketing men than to some population experts. Advertising is essential to reach the target population, and advertising evaluation techniques (e.g., surrogate indexes or audience measures) might be useful for evaluating both population information activities and the import of the entire program. Fundamental research on basid demand for fertility control is needed and a marketer's experience with planning and evaluating test markets can be useful in assessing potential selling targets and evaluating alternative promotional and distributional strategies. Special family planning clinics have certain disadvantages: expensive and scarce personnel are needed; red tape may be present; the network is based on the assumption that the client is willing to travel relatively great distances repeatedly; and clinics lack anonymity which may scare potential acceptors away. Most developing cultures have an intensively functioning distribution structure which delivers basic commodities to the most remote areas, providing relatively anonymous outlets that are physically close to the customs. Materials requiring a prescription might be distributed in exchange for script issued at and ultimately redeemed by clinics, this requiring only an occasional visit to a clinic. Mail-order service can be used to supplement a clinic's distribution of some contraceptives. It should be remembered that population administrators often have an antipathetic view toward business and marketing and "suspect" the profit motive.

Scale free effects in world currency exchange network

NASA Astrophysics Data System (ADS)

Górski, A. Z.; Drożdż, S.; Kwapień, J.

2008-11-01

A large collection of daily time series for 60 world currencies' exchange rates is considered. The correlation matrices are calculated and the corresponding Minimal Spanning Tree (MST) graphs are constructed for each of those currencies used as reference for the remaining ones. It is shown that multiplicity of the MST graphs' nodes to a good approximation develops a power like, scale free distribution with the scaling exponent similar as for several other complex systems studied so far. Furthermore, quantitative arguments in favor of the hierarchical organization of the world currency exchange network are provided by relating the structure of the above MST graphs and their scaling exponents to those that are derived from an exactly solvable hierarchical network model. A special status of the USD during the period considered can be attributed to some departures of the MST features, when this currency (or some other tied to it) is used as reference, from characteristics typical to such a hierarchical clustering of nodes towards those that correspond to the random graphs. Even though in general the basic structure of the MST is robust with respect to changing the reference currency some trace of a systematic transition from somewhat dispersed - like the USD case - towards more compact MST topology can be observed when correlations increase.

Graph Theoretic and Motif Analyses of the Hippocampal Neuron Type Potential Connectome.

PubMed

Rees, Christopher L; Wheeler, Diek W; Hamilton, David J; White, Charise M; Komendantov, Alexander O; Ascoli, Giorgio A

2016-01-01

We computed the potential connectivity map of all known neuron types in the rodent hippocampal formation by supplementing scantly available synaptic data with spatial distributions of axons and dendrites from the open-access knowledge base Hippocampome.org. The network that results from this endeavor, the broadest and most complete for a mammalian cortical region at the neuron-type level to date, contains more than 3200 connections among 122 neuron types across six subregions. Analyses of these data using graph theory metrics unveil the fundamental architectural principles of the hippocampal circuit. Globally, we identify a highly specialized topology minimizing communication cost; a modular structure underscoring the prominence of the trisynaptic loop; a core set of neuron types serving as information-processing hubs as well as a distinct group of particular antihub neurons; a nested, two-tier rich club managing much of the network traffic; and an innate resilience to random perturbations. At the local level, we uncover the basic building blocks, or connectivity patterns, that combine to produce complex global functionality, and we benchmark their utilization in the circuit relative to random networks. Taken together, these results provide a comprehensive connectivity profile of the hippocampus, yielding novel insights on its functional operations at the computationally crucial level of neuron types.

Identification of cancer-related miRNA-lncRNA biomarkers using a basic miRNA-lncRNA network.

PubMed

Zhang, Guangle; Pian, Cong; Chen, Zhi; Zhang, Jin; Xu, Mingmin; Zhang, Liangyun; Chen, Yuanyuan

2018-01-01

LncRNAs are regulatory noncoding RNAs that play crucial roles in many biological processes. The dysregulation of lncRNA is thought to be involved in many complex diseases; lncRNAs are often the targets of miRNAs in the indirect regulation of gene expression. Numerous studies have indicated that miRNA-lncRNA interactions are closely related to the occurrence and development of cancers. Thus, it is important to develop an effective method for the identification of cancer-related miRNA-lncRNA interactions. In this study, we compiled 155653 experimentally validated and predicted miRNA-lncRNA associations, which we defined as basic interactions. We next constructed an individual-specific miRNA-lncRNA network (ISMLN) for each cancer sample and a basic miRNA-lncRNA network (BMLN) for each type of cancer by examining the expression profiles of miRNAs and lncRNAs in the TCGA (The Cancer Genome Atlas) database. We then selected potential miRNA-lncRNA biomarkers based on the BLMN. Using this method, we identified cancer-related miRNA-lncRNA biomarkers and modules specific to a certain cancer. This method of profiling will contribute to the diagnosis and treatment of cancers at the level of gene regulatory networks.

IEEE 342 Node Low Voltage Networked Test System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schneider, Kevin P.; Phanivong, Phillippe K.; Lacroix, Jean-Sebastian

The IEEE Distribution Test Feeders provide a benchmark for new algorithms to the distribution analyses community. The low voltage network test feeder represents a moderate size urban system that is unbalanced and highly networked. This is the first distribution test feeder developed by the IEEE that contains unbalanced networked components. The 342 node Low Voltage Networked Test System includes many elements that may be found in a networked system: multiple 13.2kV primary feeders, network protectors, a 120/208V grid network, and multiple 277/480V spot networks. This paper presents a brief review of the history of low voltage networks and how theymore » evolved into the modern systems. This paper will then present a description of the 342 Node IEEE Low Voltage Network Test System and power flow results.« less

Distributed controller clustering in software defined networks

PubMed Central

Gani, Abdullah; Akhunzada, Adnan; Talebian, Hamid; Choo, Kim-Kwang Raymond

2017-01-01

Software Defined Networking (SDN) is an emerging promising paradigm for network management because of its centralized network intelligence. However, the centralized control architecture of the software-defined networks (SDNs) brings novel challenges of reliability, scalability, fault tolerance and interoperability. In this paper, we proposed a novel clustered distributed controller architecture in the real setting of SDNs. The distributed cluster implementation comprises of multiple popular SDN controllers. The proposed mechanism is evaluated using a real world network topology running on top of an emulated SDN environment. The result shows that the proposed distributed controller clustering mechanism is able to significantly reduce the average latency from 8.1% to 1.6%, the packet loss from 5.22% to 4.15%, compared to distributed controller without clustering running on HP Virtual Application Network (VAN) SDN and Open Network Operating System (ONOS) controllers respectively. Moreover, proposed method also shows reasonable CPU utilization results. Furthermore, the proposed mechanism makes possible to handle unexpected load fluctuations while maintaining a continuous network operation, even when there is a controller failure. The paper is a potential contribution stepping towards addressing the issues of reliability, scalability, fault tolerance, and inter-operability. PMID:28384312

Community Seismic Network

NASA Astrophysics Data System (ADS)

Clayton, R. W.; Kohler, M. D.; Massari, A.; Heaton, T. H.; Guy, R.; Chandy, M.; Bunn, J.; Strand, L.

2014-12-01

The CSN is now in its 3rdyear of operation and has expanded to 400 stations in the Los Angeles region. The goal of the network is to produce a map of strong shaking immediately following a major earthquake as a proxy for damage and a guide for first responders. We have also instrumented a number of buildings with the goal of determining the state of health of these structures before and after they have been shaken. In one 15-story structure, our sensors distributed two per floor, and show body waves propagating in the structure after a moderate local earthquake (M4.4 in Encino, CA). Sensors in a 52-story structure, which we plan to instrument with two sensors per floor as well, show the modes of the building (see Figure) down to the fundamental mode at 5 sec due to a M5.1 earthquake in La Habra, CA. The CSN utilizes a number of technologies that will likely be important in building robust low-cost networks. These include: Distributed computing - the sensors themselves are smart-sensors that perform the basic detection and size estimation in the onboard computers and send the results immediately (without packetization latency) to the central facility. Cloud computing - the central facility is housed in the cloud, which means it is more robust than a local site, and has expandable computing resources available so that it can operate with minimal resources during quiet times but still be able to exploit an very large computing facility during an earthquake. Low-cost/low-maintenance sensors - the MEM sensors are capable of staying onscale to +/- 2g, and can measure events in the Los Angeles Basin a low as magnitude 3.

Characterizing the topology of probabilistic biological networks.

PubMed

Todor, Andrei; Dobra, Alin; Kahveci, Tamer

2013-01-01

Biological interactions are often uncertain events, that may or may not take place with some probability. This uncertainty leads to a massive number of alternative interaction topologies for each such network. The existing studies analyze the degree distribution of biological networks by assuming that all the given interactions take place under all circumstances. This strong and often incorrect assumption can lead to misleading results. In this paper, we address this problem and develop a sound mathematical basis to characterize networks in the presence of uncertain interactions. Using our mathematical representation, we develop a method that can accurately describe the degree distribution of such networks. We also take one more step and extend our method to accurately compute the joint-degree distributions of node pairs connected by edges. The number of possible network topologies grows exponentially with the number of uncertain interactions. However, the mathematical model we develop allows us to compute these degree distributions in polynomial time in the number of interactions. Our method works quickly even for entire protein-protein interaction (PPI) networks. It also helps us find an adequate mathematical model using MLE. We perform a comparative study of node-degree and joint-degree distributions in two types of biological networks: the classical deterministic networks and the more flexible probabilistic networks. Our results confirm that power-law and log-normal models best describe degree distributions for both probabilistic and deterministic networks. Moreover, the inverse correlation of degrees of neighboring nodes shows that, in probabilistic networks, nodes with large number of interactions prefer to interact with those with small number of interactions more frequently than expected. We also show that probabilistic networks are more robust for node-degree distribution computation than the deterministic ones. all the data sets used, the software implemented and the alignments found in this paper are available at http://bioinformatics.cise.ufl.edu/projects/probNet/.

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.

A highly accurate absolute gravimetric network for Albania, Kosovo and Montenegro

NASA Astrophysics Data System (ADS)

Ullrich, Christian; Ruess, Diethard; Butta, Hubert; Qirko, Kristaq; Pavicevic, Bozidar; Murat, Meha

2016-04-01

The objective of this project is to establish a basic gravity network in Albania, Kosovo and Montenegro to enable further investigations in geodetic and geophysical issues. Therefore the first time in history absolute gravity measurements were performed in these countries. The Norwegian mapping authority Kartverket is assisting the national mapping authorities in Kosovo (KCA) (Kosovo Cadastral Agency - Agjencia Kadastrale e Kosovës), Albania (ASIG) (Autoriteti Shtetëror i Informacionit Gjeohapësinor) and in Montenegro (REA) (Real Estate Administration of Montenegro - Uprava za nekretnine Crne Gore) in improving the geodetic frameworks. The gravity measurements are funded by Kartverket. The absolute gravimetric measurements were performed from BEV (Federal Office of Metrology and Surveying) with the absolute gravimeter FG5-242. As a national metrology institute (NMI) the Metrology Service of the BEV maintains the national standards for the realisation of the legal units of measurement and ensures their international equivalence and recognition. Laser and clock of the absolute gravimeter were calibrated before and after the measurements. The absolute gravimetric survey was carried out from September to October 2015. Finally all 8 scheduled stations were successfully measured: there are three stations located in Montenegro, two stations in Kosovo and three stations in Albania. The stations are distributed over the countries to establish a gravity network for each country. The vertical gradients were measured at all 8 stations with the relative gravimeter Scintrex CG5. The high class quality of some absolute gravity stations can be used for gravity monitoring activities in future. The measurement uncertainties of the absolute gravity measurements range around 2.5 micro Gal at all stations (1 microgal = 10-8 m/s2). In Montenegro the large gravity difference of 200 MilliGal between station Zabljak and Podgorica can be even used for calibration of relative gravimeters. The complete basic gravimetric network of these countries will be tied to these absolute stations. In this presentation all the stations and results will be presented in detail and some special results analysed.

Assessing the nation's earthquakes

NASA Technical Reports Server (NTRS)

1990-01-01

The basic purposes of this report are: (1) to make a convincing case for the intrinsic value of regional seismic networks; (2) to describe the seriousness of persistent problems in the current configuration and operation of these networks; (3) to outline recommendations for their modernization and future evolution, in particular, their short-term integration and long-term affiliation with the U.S. National Seismic Network. Important supplementary information is included in two appendices: a survey of regional seismic networks and implementation strategies for revitalization of regional seismic networks.

Dynamics analysis of epidemic and information spreading in overlay networks.

PubMed

Liu, Guirong; Liu, Zhimei; Jin, Zhen

2018-05-07

We establish an SIS-UAU model to present the dynamics of epidemic and information spreading in overlay networks. The overlay network is represented by two layers: one where the dynamics of the epidemic evolves and another where the information spreads. We theoretically derive the explicit formulas for the basic reproduction number of awareness R 0 a by analyzing the self-consistent equation and the basic reproduction number of disease R 0 d by using the next generation matrix. The formula of R 0 d shows that the effect of awareness can reduce the basic reproduction number of disease. In particular, when awareness does not affect epidemic spreading, R 0 d is shown to match the existing theoretical results. Furthermore, we demonstrate that the disease-free equilibrium is globally asymptotically stable if R 0 d <1; and the endemic equilibrium is globally asymptotically stable if R 0 d >1. Finally, numerical simulations show that information plays a vital role in preventing and controlling disease and effectively reduces the final disease scale. Copyright © 2018 Elsevier Ltd. All rights reserved.

Looking for robust properties in the growth of an academic network: the case of the Uruguayan biological research community.

PubMed

Cabana, Alvaro; Mizraji, Eduardo; Pomi, Andrés; Valle-Lisboa, Juan Carlos

2008-04-01

Graph-theoretical methods have recently been used to analyze certain properties of natural and social networks. In this work, we have investigated the early stages in the growth of a Uruguayan academic network, the Biology Area of the Programme for the Development of Basic Science (PEDECIBA). This transparent social network is a territory for the exploration of the reliability of clustering methods that can potentially be used when we are confronted with opaque natural systems that provide us with a limited spectrum of observables (happens in research on the relations between brain, thought and language). From our social net, we constructed two different graph representations based on the relationships among researchers revealed by their co-participation in Master's thesis committees. We studied these networks at different times and found that they achieve connectedness early in their evolution and exhibit the small-world property (i.e. high clustering with short path lengths). The data seem compatible with power law distributions of connectivity, clustering coefficients and betweenness centrality. Evidence of preferential attachment of new nodes and of new links between old nodes was also found in both representations. These results suggest that there are topological properties observed throughout the growth of the network that do not depend on the representations we have chosen but reflect intrinsic properties of the academic collective under study. Researchers in PEDECIBA are classified according to their specialties. We analysed the community structure detected by a standard algorithm in both representations. We found that much of the pre-specified structure is recovered and part of the mismatches can be attributed to convergent interests between scientists from different sub-disciplines. This result shows the potentiality of some clustering methods for the analysis of partially known natural systems.

On the ability of consumer electronics microphones for environmental noise monitoring.

PubMed

Van Renterghem, Timothy; Thomas, Pieter; Dominguez, Frederico; Dauwe, Samuel; Touhafi, Abdellah; Dhoedt, Bart; Botteldooren, Dick

2011-03-01

The massive production of microphones for consumer electronics, and the shift from dedicated processing hardware to PC-based systems, opens the way to build affordable, extensive noise measurement networks. Applications include e.g. noise limit and urban soundscape monitoring, and validation of calculated noise maps. Microphones are the critical components of such a network. Therefore, in a first step, some basic characteristics of 8 microphones, distributed over a wide range of price classes, were measured in a standardized way in an anechoic chamber. In a next step, a thorough evaluation was made of the ability of these microphones to be used for environmental noise monitoring. This was done during a continuous, half-year lasting outdoor experiment, characterized by a wide variety of meteorological conditions. While some microphones failed during the course of this test, it was shown that it is possible to identify cheap microphones that highly correlate to the reference microphone during the full test period. When the deviations are expressed in total A-weighted (road traffic) noise levels, values of less than 1 dBA are obtained, in excess to the deviation amongst reference microphones themselves.

The SysMan monitoring service and its management environment

NASA Astrophysics Data System (ADS)

Debski, Andrzej; Janas, Ekkehard

1996-06-01

Management of modern information systems is becoming more and more complex. There is a growing need for powerful, flexible and affordable management tools to assist system managers in maintaining such systems. It is at the same time evident that effective management should integrate network management, system management and application management in a uniform way. Object oriented OSI management architecture with its four basic modelling concepts (information, organization, communication and functional models) together with widely accepted distribution platforms such as ANSA/CORBA, constitutes a reliable and modern framework for the implementation of a management toolset. This paper focuses on the presentation of concepts and implementation results of an object oriented management toolset developed and implemented within the framework of the ESPRIT project 7026 SysMan. An overview is given of the implemented SysMan management services including the System Management Service, Monitoring Service, Network Management Service, Knowledge Service, Domain and Policy Service, and the User Interface. Special attention is paid to the Monitoring Service which incorporates the architectural key entity responsible for event management. Its architecture and building components, especially filters, are emphasized and presented in detail.

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.

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.

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

PubMed

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

2015-07-01

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.

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

NetMOD v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Merchant, Bion J

2015-12-22

NetMOD is a tool to model the performance of global ground-based explosion monitoring systems. The version 2.0 of the software supports the simulation of seismic, hydroacoustic, and infrasonic detection capability. The tool provides a user interface to execute simulations based upon a hypothetical definition of the monitoring system configuration, geophysical properties of the Earth, and detection analysis criteria. NetMOD will be distributed with a project file defining the basic performance characteristics of the International Monitoring System (IMS), a network of sensors operated by the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO). Network modeling is needed to be able to assess and explainmore » the potential effect of changes to the IMS, to prioritize station deployment and repair, and to assess the overall CTBTO monitoring capability currently and in the future. Currently the CTBTO uses version 1.0 of NetMOD, provided to them in early 2014. NetMOD will provide a modern tool that will cover all the simulations currently available and allow for the development of additional simulation capabilities of the IMS in the future. NetMOD simulates the performance of monitoring networks by estimating the relative amplitudes of the signal and noise measured at each of the stations within the network based upon known geophysical principles. From these signal and noise estimates, a probability of detection may be determined for each of the stations. The detection probabilities at each of the stations may then be combined to produce an estimate of the detection probability for the entire monitoring network.« less

Large-scale topology and the default mode network in the mouse connectome

PubMed Central

Stafford, James M.; Jarrett, Benjamin R.; Miranda-Dominguez, Oscar; Mills, Brian D.; Cain, Nicholas; Mihalas, Stefan; Lahvis, Garet P.; Lattal, K. Matthew; Mitchell, Suzanne H.; David, Stephen V.; Fryer, John D.; Nigg, Joel T.; Fair, Damien A.

2014-01-01

Noninvasive functional imaging holds great promise for serving as a translational bridge between human and animal models of various neurological and psychiatric disorders. However, despite a depth of knowledge of the cellular and molecular underpinnings of atypical processes in mouse models, little is known about the large-scale functional architecture measured by functional brain imaging, limiting translation to human conditions. Here, we provide a robust processing pipeline to generate high-resolution, whole-brain resting-state functional connectivity MRI (rs-fcMRI) images in the mouse. Using a mesoscale structural connectome (i.e., an anterograde tracer mapping of axonal projections across the mouse CNS), we show that rs-fcMRI in the mouse has strong structural underpinnings, validating our procedures. We next directly show that large-scale network properties previously identified in primates are present in rodents, although they differ in several ways. Last, we examine the existence of the so-called default mode network (DMN)—a distributed functional brain system identified in primates as being highly important for social cognition and overall brain function and atypically functionally connected across a multitude of disorders. We show the presence of a potential DMN in the mouse brain both structurally and functionally. Together, these studies confirm the presence of basic network properties and functional networks of high translational importance in structural and functional systems in the mouse brain. This work clears the way for an important bridge measurement between human and rodent models, enabling us to make stronger conclusions about how regionally specific cellular and molecular manipulations in mice relate back to humans. PMID:25512496

Networked gamma radiation detection system for tactical deployment

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sanjoy; Maurer, Richard; Wolff, Ronald; Smith, Ethan; Guss, Paul; Mitchell, Stephen

2015-08-01

A networked gamma radiation detection system with directional sensitivity and energy spectral data acquisition capability is being developed by the National Security Technologies, LLC, Remote Sensing Laboratory to support the close and intense tactical engagement of law enforcement who carry out counterterrorism missions. In the proposed design, three clusters of 2″ × 4″ × 16″ sodium iodide crystals (4 each) with digiBASE-E (for list mode data collection) would be placed on the passenger side of a minivan. To enhance localization and facilitate rapid identification of isotopes, advanced smart real-time localization and radioisotope identification algorithms like WAVRAD (wavelet-assisted variance reduction for anomaly detection) and NSCRAD (nuisance-rejection spectral comparison ratio anomaly detection) will be incorporated. We will test a collection of algorithms and analysis that centers on the problem of radiation detection with a distributed sensor network. We will study the basic characteristics of a radiation sensor network and focus on the trade-offs between false positive alarm rates, true positive alarm rates, and time to detect multiple radiation sources in a large area. Empirical and simulation analyses of critical system parameters, such as number of sensors, sensor placement, and sensor response functions, will be examined. This networked system will provide an integrated radiation detection architecture and framework with (i) a large nationally recognized search database equivalent that would help generate a common operational picture in a major radiological crisis; (ii) a robust reach back connectivity for search data to be evaluated by home teams; and, finally, (iii) a possibility of integrating search data from multi-agency responders.

Distributed and collaborative synthetic environments

NASA Technical Reports Server (NTRS)

Bajaj, Chandrajit L.; Bernardini, Fausto

1995-01-01

Fast graphics workstations and increased computing power, together with improved interface technologies, have created new and diverse possibilities for developing and interacting with synthetic environments. A synthetic environment system is generally characterized by input/output devices that constitute the interface between the human senses and the synthetic environment generated by the computer; and a computation system running a real-time simulation of the environment. A basic need of a synthetic environment system is that of giving the user a plausible reproduction of the visual aspect of the objects with which he is interacting. The goal of our Shastra research project is to provide a substrate of geometric data structures and algorithms which allow the distributed construction and modification of the environment, efficient querying of objects attributes, collaborative interaction with the environment, fast computation of collision detection and visibility information for efficient dynamic simulation and real-time scene display. In particular, we address the following issues: (1) A geometric framework for modeling and visualizing synthetic environments and interacting with them. We highlight the functions required for the geometric engine of a synthetic environment system. (2) A distribution and collaboration substrate that supports construction, modification, and interaction with synthetic environments on networked desktop machines.

Dynamic Load-Balancing for Distributed Heterogeneous Computing of Parallel CFD Problems

NASA Technical Reports Server (NTRS)

Ecer, A.; Chien, Y. P.; Boenisch, T.; Akay, H. U.

2000-01-01

The developed methodology is aimed at improving the efficiency of executing block-structured algorithms on parallel, distributed, heterogeneous computers. The basic approach of these algorithms is to divide the flow domain into many sub- domains called blocks, and solve the governing equations over these blocks. Dynamic load balancing problem is defined as the efficient distribution of the blocks among the available processors over a period of several hours of computations. In environments with computers of different architecture, operating systems, CPU speed, memory size, load, and network speed, balancing the loads and managing the communication between processors becomes crucial. Load balancing software tools for mutually dependent parallel processes have been created to efficiently utilize an advanced computation environment and algorithms. These tools are dynamic in nature because of the chances in the computer environment during execution time. More recently, these tools were extended to a second operating system: NT. In this paper, the problems associated with this application will be discussed. Also, the developed algorithms were combined with the load sharing capability of LSF to efficiently utilize workstation clusters for parallel computing. Finally, results will be presented on running a NASA based code ADPAC to demonstrate the developed tools for dynamic load balancing.

The energy balance in coronal holes and average quiet-sun regions

NASA Technical Reports Server (NTRS)

Raymond, J. C.; Doyle, J. G.

1981-01-01

Emission measure curves are presented for average coronal hole and quiet-sun spectra taken during the Skylab mission by Vernazza and Reeves (1978), and the curves are used to discuss the energy balance in each region. Close-coupling calculations are used for the Be sequence, assuming a 10 level ion; for B sequence ions mainly distorted wave calculations in an 11 level ion are used, but close-coupling cross sections are used for some ions; for C and Mg sequence ions, distorted wave calculations are used with 15 and 10 level ions, respectively, and close-coupling results are used for Li-like ions with two levels. Results are presented and include the following: the coronal hole spectrum shows a smaller slope in the emission measure distribution, consistent with the expected outflow effects. It is concluded that the simple constant pressure models of static coronal loops of constant cross section are basically able to match the observed emission measure distribution of the average quiet sun between 1,000,000 and 10,000,000 K. However, the cell center and network distributions are respectively steeper and shallower than predicted by the detailed cooling curve.

Multi-parametric centrality method for graph network models

NASA Astrophysics Data System (ADS)

Ivanov, Sergei Evgenievich; Gorlushkina, Natalia Nikolaevna; Ivanova, Lubov Nikolaevna

2018-04-01

The graph model networks are investigated to determine centrality, weights and the significance of vertices. For centrality analysis appliesa typical method that includesany one of the properties of graph vertices. In graph theory, methods of analyzing centrality are used: in terms by degree, closeness, betweenness, radiality, eccentricity, page-rank, status, Katz and eigenvector. We have proposed a new method of multi-parametric centrality, which includes a number of basic properties of the network member. The mathematical model of multi-parametric centrality method is developed. Comparison of results for the presented method with the centrality methods is carried out. For evaluate the results for the multi-parametric centrality methodthe graph model with hundreds of vertices is analyzed. The comparative analysis showed the accuracy of presented method, includes simultaneously a number of basic properties of vertices.

Bistability induces episodic spike communication by inhibitory neurons in neuronal networks.

PubMed

Kazantsev, V B; Asatryan, S Yu

2011-09-01

Bistability is one of the important features of nonlinear dynamical systems. In neurodynamics, bistability has been found in basic Hodgkin-Huxley equations describing the cell membrane dynamics. When the neuron is clamped near its threshold, the stable rest potential may coexist with the stable limit cycle describing periodic spiking. However, this effect is often neglected in network computations where the neurons are typically reduced to threshold firing units (e.g., integrate-and-fire models). We found that the bistability may induce spike communication by inhibitory coupled neurons in the spiking network. The communication is realized in the form of episodic discharges with synchronous (correlated) spikes during the episodes. A spiking phase map is constructed to describe the synchronization and to estimate basic spike phase locking modes.

The European Network for Research, Action and Training in Adult Literacy and Basic Education (Dublin, Ireland, May 25-30, 1991). A Seminar Organised by EUROALPHA. Adult Basic Education in Prisons.

ERIC Educational Resources Information Center

1991

This conference report on adult basic education in European prisons contains the following introductory materials: a list of participants, the program, and introductions to the seminar by Frank Dunne and Pierre Freynet. "Keynote Address" (Robert Suvaal) discusses five items a prison educator must deal with: philosophy, position of…

Topology determines force distributions in one-dimensional random spring networks.

PubMed

Heidemann, Knut M; Sageman-Furnas, Andrew O; Sharma, Abhinav; Rehfeldt, Florian; Schmidt, Christoph F; Wardetzky, Max

2018-02-01

Networks of elastic fibers are ubiquitous in biological systems and often provide mechanical stability to cells and tissues. Fiber-reinforced materials are also common in technology. An important characteristic of such materials is their resistance to failure under load. Rupture occurs when fibers break under excessive force and when that failure propagates. Therefore, it is crucial to understand force distributions. Force distributions within such networks are typically highly inhomogeneous and are not well understood. Here we construct a simple one-dimensional model system with periodic boundary conditions by randomly placing linear springs on a circle. We consider ensembles of such networks that consist of N nodes and have an average degree of connectivity z but vary in topology. Using a graph-theoretical approach that accounts for the full topology of each network in the ensemble, we show that, surprisingly, the force distributions can be fully characterized in terms of the parameters (N,z). Despite the universal properties of such (N,z) ensembles, our analysis further reveals that a classical mean-field approach fails to capture force distributions correctly. We demonstrate that network topology is a crucial determinant of force distributions in elastic spring networks.

Topology determines force distributions in one-dimensional random spring networks

NASA Astrophysics Data System (ADS)

Heidemann, Knut M.; Sageman-Furnas, Andrew O.; Sharma, Abhinav; Rehfeldt, Florian; Schmidt, Christoph F.; Wardetzky, Max

2018-02-01

Networks of elastic fibers are ubiquitous in biological systems and often provide mechanical stability to cells and tissues. Fiber-reinforced materials are also common in technology. An important characteristic of such materials is their resistance to failure under load. Rupture occurs when fibers break under excessive force and when that failure propagates. Therefore, it is crucial to understand force distributions. Force distributions within such networks are typically highly inhomogeneous and are not well understood. Here we construct a simple one-dimensional model system with periodic boundary conditions by randomly placing linear springs on a circle. We consider ensembles of such networks that consist of N nodes and have an average degree of connectivity z but vary in topology. Using a graph-theoretical approach that accounts for the full topology of each network in the ensemble, we show that, surprisingly, the force distributions can be fully characterized in terms of the parameters (N ,z ) . Despite the universal properties of such (N ,z ) ensembles, our analysis further reveals that a classical mean-field approach fails to capture force distributions correctly. We demonstrate that network topology is a crucial determinant of force distributions in elastic spring networks.

Real-time distributed multimedia systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rahurkar, S.S.; Bourbakis, N.G.

1996-12-31

This paper presents a survey on distributed multimedia systems and discusses real-time issues. In particular, different subsystems are reviewed that impact on multimedia networking, the networking for multimedia, the networked multimedia systems, and the leading edge research and developments efforts and issues in networking.

Architectures and protocols for an integrated satellite-terrestrial mobile system

NASA Technical Reports Server (NTRS)

Delre, E.; Dellipriscoli, F.; Iannucci, P.; Menolascino, R.; Settimo, F.

1993-01-01

This paper aims to depict some basic concepts related to the definition of an integrated system for mobile communications, consisting of a satellite network and a terrestrial cellular network. In particular three aspects are discussed: (1) architecture definition for the satellite network; (2) assignment strategy of the satellite channels; and (3) definition of 'internetworking procedures' between cellular and satellite network, according to the selected architecture and the satellite channel assignment strategy.

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-source-software (OSS) project-project dependency within a cluster, package-package dependency within a project and class-class dependency within a package. We conclude that indegree and outdegree dependencies do not lead to similar type of degree distributions, implying that indegree dependencies follow overall power-law distribution (or power-law with flat-top or exponential cut-off in some cases), while outdegree dependencies do not follow heavy-tailed distribution.

Basic Internet Software Toolkit.

ERIC Educational Resources Information Center

Buchanan, Larry

1998-01-01

Once schools are connected to the Internet, the next step is getting network workstations configured for Internet access. This article describes a basic toolkit comprising software currently available on the Internet for free or modest cost. Lists URLs for Web browser, Telnet, FTP, file decompression, portable document format (PDF) reader,…

A conceptual network model of the air transportation system. the basic level 1 model.

DOT National Transportation Integrated Search

1971-04-01

A basic conceptual model of the entire Air Transportation System is being developed to serve as an analytical tool for studying the interactions among the system elements. The model is being designed to function in an interactive computer graphics en...

Weighted Scaling in Non-growth Random Networks

NASA Astrophysics Data System (ADS)

Chen, Guang; Yang, Xu-Hua; Xu, Xin-Li

2012-09-01

We propose a weighted model to explain the self-organizing formation of scale-free phenomenon in non-growth random networks. In this model, we use multiple-edges to represent the connections between vertices and define the weight of a multiple-edge as the total weights of all single-edges within it and the strength of a vertex as the sum of weights for those multiple-edges attached to it. The network evolves according to a vertex strength preferential selection mechanism. During the evolution process, the network always holds its total number of vertices and its total number of single-edges constantly. We show analytically and numerically that a network will form steady scale-free distributions with our model. The results show that a weighted non-growth random network can evolve into scale-free state. It is interesting that the network also obtains the character of an exponential edge weight distribution. Namely, coexistence of scale-free distribution and exponential distribution emerges.

10 CFR 431.36 - Compliance Certification.

Code of Federal Regulations, 2010 CFR

2010-01-01

... EQUIPMENT Electric Motors Certification § 431.36 Compliance Certification. (a) General. Beginning April 26, 2003, a manufacturer or private labeler shall not distribute in commerce any basic model of an electric...: (i) The nominal full load efficiency for each basic model of electric motor distributed is not less...

10 CFR 431.36 - Compliance Certification.

Code of Federal Regulations, 2012 CFR

2012-01-01

... EQUIPMENT Electric Motors Certification § 431.36 Compliance Certification. (a) General. Beginning April 26, 2003, a manufacturer or private labeler shall not distribute in commerce any basic model of an electric...: (i) The nominal full load efficiency for each basic model of electric motor distributed is not less...

A Neural Network Aero Design System for Advanced Turbo-Engines

NASA Technical Reports Server (NTRS)

Sanz, Jose M.

1999-01-01

An inverse design method calculates the blade shape that produces a prescribed input pressure distribution. By controlling this input pressure distribution the aerodynamic design objectives can easily be met. Because of the intrinsic relationship between pressure distribution and airfoil physical properties, a Neural Network can be trained to choose the optimal pressure distribution that would meet a set of physical requirements. Neural network systems have been attempted in the context of direct design methods. From properties ascribed to a set of blades the neural network is trained to infer the properties of an 'interpolated' blade shape. The problem is that, especially in transonic regimes where we deal with intrinsically non linear and ill posed problems, small perturbations of the blade shape can produce very large variations of the flow parameters. It is very unlikely that, under these circumstances, a neural network will be able to find the proper solution. The unique situation in the present method is that the neural network can be trained to extract the required input pressure distribution from a database of pressure distributions while the inverse method will still compute the exact blade shape that corresponds to this 'interpolated' input pressure distribution. In other words, the interpolation process is transferred to a smoother problem, namely, finding what pressure distribution would produce the required flow conditions and, once this is done, the inverse method will compute the exact solution for this problem. The use of neural network is, in this context, highly related to the use of proper optimization techniques. The optimization is used essentially as an automation procedure to force the input pressure distributions to achieve the required aero and structural design parameters. A multilayered feed forward network with back-propagation is used to train the system for pattern association and classification.

On a growth model for complex networks capable of producing power-law out-degree distributions with wide range exponents

PubMed Central

Esquivel-Gómez, J.; Arjona-Villicaña, P. D.; Stevens-Navarro, E.; Pineda-Rico, U.; Balderas-Navarro, R. E.; Acosta-Elias, J.

2015-01-01

The out-degree distribution is one of the most reported topological properties to characterize real complex networks. This property describes the probability that a node in the network has a particular number of outgoing links. It has been found that in many real complex networks the out-degree has a behavior similar to a power-law distribution, therefore some network growth models have been proposed to approximate this behavior. This paper introduces a new growth model that allows to produce out-degree distributions that decay as a power-law with an exponent in the range from 1 to ∞. PMID:25765763

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.

Sampling from complex networks using distributed learning automata

NASA Astrophysics Data System (ADS)

Rezvanian, Alireza; Rahmati, Mohammad; Meybodi, Mohammad Reza

2014-02-01

A complex network provides a framework for modeling many real-world phenomena in the form of a network. In general, a complex network is considered as a graph of real world phenomena such as biological networks, ecological networks, technological networks, information networks and particularly social networks. Recently, major studies are reported for the characterization of social networks due to a growing trend in analysis of online social networks as dynamic complex large-scale graphs. Due to the large scale and limited access of real networks, the network model is characterized using an appropriate part of a network by sampling approaches. In this paper, a new sampling algorithm based on distributed learning automata has been proposed for sampling from complex networks. In the proposed algorithm, a set of distributed learning automata cooperate with each other in order to take appropriate samples from the given network. To investigate the performance of the proposed algorithm, several simulation experiments are conducted on well-known complex networks. Experimental results are compared with several sampling methods in terms of different measures. The experimental results demonstrate the superiority of the proposed algorithm over the others.

The medical libraries of Vietnam--a service in transition.

PubMed

Brennen, P W

1992-07-01

The medical libraries of Vietnam maintain high profiles within their institutions and are recognized by health care professionals and administrators as an important part of the health care system. Despite the multitude of problems in providing even a minimal level of medical library services, librarians, clinicians, and researchers nevertheless are determined that enhanced services be made available. Currently, services can be described as basic and unsophisticated, yet viable and surprisingly well organized. The lack of hard western currency required to buy materials and the lack of library technology will be major obstacles to improving information services. Vietnam, like many developing nations, is about to enter a period of technological upheaval, which ultimately will result in a transition from the traditional library limited by walls to a national resource that will rely increasingly on electronic access to international knowledge networks. Technology such as CD-ROM, Integrated Services Digital Network (ISDN), and satellite telecommunication networks such as Internet can provide the technical backbone to provide access to remote and widely distributed electronic databases to support the information needs of the health care community. Over the long term, access to such databases likely will be cost-effective, in contrast to the assuredly astronomical cost of building a comparable domestic print collection. The advent of new, low-cost electronic technologies probably will revolutionize health care information services in developing nations. However, for the immediate future, the medical libraries of Vietnam will require ongoing sustained support from the international community, so that minimal levels of resources will be available to support the information needs of the health care community. It is remarkable, and a credit to the determination of Vietnam's librarians that, in a country with a legacy of war, economic deprivation, and international isolation, they have somehow managed to provide a sound basic level of information services for health care professionals.

The medical libraries of Vietnam--a service in transition.

PubMed Central

Brennen, P W

1992-01-01

The medical libraries of Vietnam maintain high profiles within their institutions and are recognized by health care professionals and administrators as an important part of the health care system. Despite the multitude of problems in providing even a minimal level of medical library services, librarians, clinicians, and researchers nevertheless are determined that enhanced services be made available. Currently, services can be described as basic and unsophisticated, yet viable and surprisingly well organized. The lack of hard western currency required to buy materials and the lack of library technology will be major obstacles to improving information services. Vietnam, like many developing nations, is about to enter a period of technological upheaval, which ultimately will result in a transition from the traditional library limited by walls to a national resource that will rely increasingly on electronic access to international knowledge networks. Technology such as CD-ROM, Integrated Services Digital Network (ISDN), and satellite telecommunication networks such as Internet can provide the technical backbone to provide access to remote and widely distributed electronic databases to support the information needs of the health care community. Over the long term, access to such databases likely will be cost-effective, in contrast to the assuredly astronomical cost of building a comparable domestic print collection. The advent of new, low-cost electronic technologies probably will revolutionize health care information services in developing nations. However, for the immediate future, the medical libraries of Vietnam will require ongoing sustained support from the international community, so that minimal levels of resources will be available to support the information needs of the health care community. It is remarkable, and a credit to the determination of Vietnam's librarians that, in a country with a legacy of war, economic deprivation, and international isolation, they have somehow managed to provide a sound basic level of information services for health care professionals. PMID:1525617

The New Generation Russian VLBI Network

NASA Technical Reports Server (NTRS)

Finkelstein, Andrey; Ipatov, Alexander; Smolentsev, Sergey; Mardyshkin, Vyacheslav; Fedotov, Leonid; Surkis, Igor; Ivanov, Dmitrij; Gayazov, Iskander

2010-01-01

This paper deals with a new project of the Russian VLBI Network dedicated for Universal Time determinations in quasi on-line mode. The basic principles of the network design and location of antennas are explained. Variants of constructing receiving devices, digital data acquisition system, and phase calibration system are specially considered. The frequency ranges and expected values of noise temperature are given.

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

ERIC Educational Resources Information Center

Ruthven, Kenneth

2014-01-01

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

Group Centric Networking: A New Approach for Wireless Multi-Hop Networking to Enable the Internet of Things

DTIC Science & Technology

2016-01-22

basic mechanism of link-based routing schemes is the broadcasting of a control message (called a “ hello ”) to all of its neighbors. If a response is...to a destination by using the set of ex- changed hello messages between users of the network. With suciently high frequency, hello messages are suc

The Center for Collegiate Mental Health: An Example of a Practice-Research Network in University Counseling Centers

ERIC Educational Resources Information Center

Castonguay, Louis G.; Locke, Benjamin D.; Hayes, Jeffrey A.

2011-01-01

This article presents a model of a practice-research network that offers benefits for clinicians working at college and university counseling centers. We briefly describe the basic components of this practice-research network, challenges in developing it, and some of the empirical studies that have resulted from this initiative. We also describe…

Engineering of Sensor Network Structure for Dependable Fusion

DTIC Science & Technology

2014-08-15

Lossy Wireless Sensor Networks , IEEE/ACM Transactions on Networking , (04 2013): 0. doi: 10.1109/TNET.2013.2256795 Soumik Sarkar, Kushal Mukherjee...Phoha, Bharat B. Madan, Asok Ray. Distributed Network Control for Mobile Multi-Modal Wireless Sensor Networks , Journal of Parallel and Distributed...Deadline Constraints, IEEE Transactions on Automatic Control special issue on Wireless Sensor and Actuator Networks , (01 2011): 1. doi: Eric Keller

Dynamics of an epidemic model with quarantine on scale-free networks

NASA Astrophysics Data System (ADS)

Kang, Huiyan; Liu, Kaihui; Fu, Xinchu

2017-12-01

Quarantine strategies are frequently used to control or reduce the transmission risks of epidemic diseases such as SARS, tuberculosis and cholera. In this paper, we formulate a susceptible-exposed-infected-quarantined-recovered model on a scale-free network incorporating the births and deaths of individuals. Considering that the infectivity is related to the degrees of infectious nodes, we introduce quarantined rate as a function of degree into the model, and quantify the basic reproduction number, which is shown to be dependent on some parameters, such as quarantined rate, infectivity and network structures. A theoretical result further indicates the heterogeneity of networks and higher infectivity will raise the disease transmission risk while quarantine measure will contribute to the prevention of epidemic spreading. Meanwhile, the contact assumption between susceptibles and infectives may impact the disease transmission. Furthermore, we prove that the basic reproduction number serves as a threshold value for the global stability of the disease-free and endemic equilibria and the uniform persistence of the disease on the network by constructing appropriate Lyapunov functions. Finally, some numerical simulations are illustrated to perform and complement our analytical results.

Performance Parameters Analysis of an XD3P Peugeot Engine Using Artificial Neural Networks (ANN) Concept in MATLAB

NASA Astrophysics Data System (ADS)

Rangaswamy, T.; Vidhyashankar, S.; Madhusudan, M.; Bharath Shekar, H. R.

2015-04-01

The current trends of engineering follow the basic rule of innovation in mechanical engineering aspects. For the engineers to be efficient, problem solving aspects need to be viewed in a multidimensional perspective. One such methodology implemented is the fusion of technologies from other disciplines in order to solve the problems. This paper mainly deals with the application of Neural Networks in order to analyze the performance parameters of an XD3P Peugeot engine (used in Ministry of Defence). The basic propaganda of the work is divided into two main working stages. In the former stage, experimentation of an IC engine is carried out in order to obtain the primary data. In the latter stage the primary database formed is used to design and implement a predictive neural network in order to analyze the output parameters variation with respect to each other. A mathematical governing equation for the neural network is obtained. The obtained polynomial equation describes the characteristic behavior of the built neural network system. Finally, a comparative study of the results is carried out.

The basic reproduction number as a predictor for epidemic outbreaks in temporal networks.

PubMed

Holme, Petter; Masuda, Naoki

2015-01-01

The basic reproduction number R0--the number of individuals directly infected by an infectious person in an otherwise susceptible population--is arguably the most widely used estimator of how severe an epidemic outbreak can be. This severity can be more directly measured as the fraction of people infected once the outbreak is over, Ω. In traditional mathematical epidemiology and common formulations of static network epidemiology, there is a deterministic relationship between R0 and Ω. However, if one considers disease spreading on a temporal contact network--where one knows when contacts happen, not only between whom--then larger R0 does not necessarily imply larger Ω. In this paper, we numerically investigate the relationship between R0 and Ω for a set of empirical temporal networks of human contacts. Among 31 explanatory descriptors of temporal network structure, we identify those that make R0 an imperfect predictor of Ω. We find that descriptors related to both temporal and topological aspects affect the relationship between R0 and Ω, but in different ways.

Disease invasion risk in a growing population.

PubMed

Yuan, Sanling; van den Driessche, P; Willeboordse, Frederick H; Shuai, Zhisheng; Ma, Junling

2016-09-01

The spread of an infectious disease may depend on the population size. For simplicity, classic epidemic models assume homogeneous mixing, usually standard incidence or mass action. For standard incidence, the contact rate between any pair of individuals is inversely proportional to the population size, and so the basic reproduction number (and thus the initial exponential growth rate of the disease) is independent of the population size. For mass action, this contact rate remains constant, predicting that the basic reproduction number increases linearly with the population size, meaning that disease invasion is easiest when the population is largest. In this paper, we show that neither of these may be true on a slowly evolving contact network: the basic reproduction number of a short epidemic can reach its maximum while the population is still growing. The basic reproduction number is proportional to the spectral radius of a contact matrix, which is shown numerically to be well approximated by the average excess degree of the contact network. We base our analysis on modeling the dynamics of the average excess degree of a random contact network with constant population input, proportional deaths, and preferential attachment for contacts brought in by incoming individuals (i.e., individuals with more contacts attract more incoming contacts). In addition, we show that our result also holds for uniform attachment of incoming contacts (i.e., every individual has the same chance of attracting incoming contacts), and much more general population dynamics. Our results show that a disease spreading in a growing population may evade control if disease control planning is based on the basic reproduction number at maximum population size.

Increased functional connectivity with puberty in the mentalising network involved in social emotion processing

PubMed Central

Klapwijk, Eduard T.; Goddings, Anne-Lise; Heyes, Stephanie Burnett; Bird, Geoffrey; Viner, Russell M.; Blakemore, Sarah-Jayne

2015-01-01

There is increasing evidence that puberty plays an important role in the structural and functional brain development seen in adolescence, but little is known of the pubertal influence on changes in functional connectivity. We explored how pubertal indicators (salivary concentrations of testosterone, oestradiol and DHEA; pubertal stage; menarcheal status) relate to functional connectivity between components of a mentalising network identified to be engaged in social emotion processing by our prior work, using psychophysiological interaction (PPI) analysis. Female adolescents aged 11 to 13 years were scanned whilst silently reading scenarios designed to evoke either social emotions (guilt and embarrassment) or basic emotions (disgust and fear), of which only social compared to basic emotions require the representation of another person’s mental states. Pubertal stage and menarcheal status were used to assign participants to pre/early or mid/late puberty groups. We found increased functional connectivity between the dorsomedial prefrontal cortex (DMPFC) and the right posterior superior temporal sulcus (pSTS) and right temporo-parietal junction (TPJ) during social relative to basic emotion processing. Moreover, increasing oestradiol concentrations were associated with increased functional connectivity between the DMPFC and the right TPJ during social relative to basic emotion processing, independent of age. Our analysis of the PPI data by phenotypic pubertal status showed that more advanced puberty stage was associated with enhanced functional connectivity between the DMPFC and the left anterior temporal cortex (ATC) during social relative to basic emotion processing, also independent of age. Our results suggest increased functional maturation of the social brain network with the advancement of puberty in girls. PMID:23998674

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

Intrinsic connectivity in the human brain does not reveal networks for ‘basic’ emotions

PubMed Central

Lindquist, Kristen A.; Dickerson, Bradford C.; Barrett, Lisa Feldman

2015-01-01

We tested two competing models for the brain basis of emotion, the basic emotion theory and the conceptual act theory of emotion, using resting-state functional connectivity magnetic resonance imaging (rs-fcMRI). The basic emotion view hypothesizes that anger, sadness, fear, disgust and happiness each arise from a brain network that is innate, anatomically constrained and homologous in other animals. The conceptual act theory of emotion hypothesizes that an instance of emotion is a brain state constructed from the interaction of domain-general, core systems within the brain such as the salience, default mode and frontoparietal control networks. Using peak coordinates derived from a meta-analysis of task-evoked emotion fMRI studies, we generated a set of whole-brain rs-fcMRI ‘discovery’ maps for each emotion category and examined the spatial overlap in their conjunctions. Instead of discovering a specific network for each emotion category, variance in the discovery maps was accounted for by the known domain-general network. Furthermore, the salience network is observed as part of every emotion category. These results indicate that specific networks for each emotion do not exist within the intrinsic architecture of the human brain and instead support the conceptual act theory of emotion. PMID:25680990

Formation of contractile networks and fibers in the medial cell cortex through myosin-II turnover, contraction, and stress-stabilization

PubMed Central

Nie, Wei; Wei, Ming-Tzo; Ou-Yang, Daniel H.; Jedlicka, Sabrina S.; Vavylonis, Dimitrios

2015-01-01

The morphology of adhered cells depends crucially on the formation of a contractile meshwork of parallel and cross-linked fibers along the contacting surface. The motor activity and minifilament assembly of non-muscle myosin-II is an important component of cortical cytoskeletal remodeling during mechanosensing. We used experiments and computational modeling to study cortical myosin-II dynamics in adhered cells. Confocal microscopy was used to image the medial cell cortex of HeLa cells stably expressing myosin regulatory light chain tagged with GFP (MRLC-GFP). The distribution of MRLC-GFP fibers and focal adhesions was classified into three types of network morphologies. Time-lapse movies show: myosin foci appearance and disappearance; aligning and contraction; stabilization upon alignment. Addition of blebbistatin, which perturbs myosin motor activity, leads to a reorganization of the cortical networks and to a reduction of contractile motions. We quantified the kinetics of contraction, disassembly and reassembly of myosin networks using spatio-temporal image correlation spectroscopy (STICS). Coarse-grained numerical simulations include bipolar minifilaments that contract and align through specified interactions as basic elements. After assuming that minifilament turnover decreases with increasing contractile stress, the simulations reproduce stress-dependent fiber formation in between focal adhesions above a threshold myosin concentration. The STICS correlation function in simulations matches the function measured in experiments. This study provides a framework to help interpret how different cortical myosin remodeling kinetics may contribute to different cell shape and rigidity depending on substrate stiffness. PMID:25641802

Application of artificial intelligence to the management of urological cancer.

PubMed

Abbod, Maysam F; Catto, James W F; Linkens, Derek A; Hamdy, Freddie C

2007-10-01

Artificial intelligence techniques, such as artificial neural networks, Bayesian belief networks and neuro-fuzzy modeling systems, are complex mathematical models based on the human neuronal structure and thinking. Such tools are capable of generating data driven models of biological systems without making assumptions based on statistical distributions. A large amount of study has been reported of the use of artificial intelligence in urology. We reviewed the basic concepts behind artificial intelligence techniques and explored the applications of this new dynamic technology in various aspects of urological cancer management. A detailed and systematic review of the literature was performed using the MEDLINE and Inspec databases to discover reports using artificial intelligence in urological cancer. The characteristics of machine learning and their implementation were described and reports of artificial intelligence use in urological cancer were reviewed. While most researchers in this field were found to focus on artificial neural networks to improve the diagnosis, staging and prognostic prediction of urological cancers, some groups are exploring other techniques, such as expert systems and neuro-fuzzy modeling systems. Compared to traditional regression statistics artificial intelligence methods appear to be accurate and more explorative for analyzing large data cohorts. Furthermore, they allow individualized prediction of disease behavior. Each artificial intelligence method has characteristics that make it suitable for different tasks. The lack of transparency of artificial neural networks hinders global scientific community acceptance of this method but this can be overcome by neuro-fuzzy modeling systems.

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.

Research on Some Bus Transport Networks with Random Overlapping Clique Structure

NASA Astrophysics Data System (ADS)

Yang, Xu-Hua; Wang, Bo; Wang, Wan-Liang; Sun, You-Xian

2008-11-01

On the basis of investigating the statistical data of bus transport networks of three big cities in China, we propose that each bus route is a clique (maximal complete subgraph) and a bus transport network (BTN) consists of a lot of cliques, which intensively connect and overlap with each other. We study the network properties, which include the degree distribution, multiple edges' overlapping time distribution, distribution of the overlap size between any two overlapping cliques, distribution of the number of cliques that a node belongs to. Naturally, the cliques also constitute a network, with the overlapping nodes being their multiple links. We also research its network properties such as degree distribution, clustering, average path length, and so on. We propose that a BTN has the properties of random clique increment and random overlapping clique, at the same time, a BTN is a small-world network with highly clique-clustered and highly clique-overlapped. Finally, we introduce a BTN evolution model, whose simulation results agree well with the statistical laws that emerge in real BTNs.

Spatial and Temporal Variability of CO2 and CH4 Concentrations in the Atmospheric Surface Layer over West Siberia

NASA Astrophysics Data System (ADS)

Belan, Boris D.; Machida, Toshinobu; Sasakawa, Motoki; Davydov, Denis K.; Fofonov, Alexander V.; Krasnov, Oleg A.; Maksyutov, Shamil; Arshinov, Mikhail Yu.

2015-04-01

The investigation of greenhouse gas behavior in the atmosphere plays a key role in predicting the global changes of Earth's climate. In this connection, of particular importance is the study of the distribution of sources/sinks of trace gases in the atmospheric surface layer over the different regions of the globe. In order to fill a gap in the data on greenhouse gas concentrations in Russia, National Institute for Environmental Studies (NIES, Japan) and Institute of Atmospheric Optics (IAO SB RAS, Russia) established a network for GHG monitoring (JR-STATION, Japan-Russia Siberian Tall Tower Inland Observation Network). Gas analyzers and meteorological sensors were mounted at radio relay towers located in different regions of West Siberia. The checking equipment was placed in containers at the tower base. In the containers, the climatic parameters optimal for gas analyzer operation were maintained. The work on the network development started in 2001. Since at each of the sites the measurement duration could be different, in this paper we present the data of the greenhouse gas monitoring for eight sites which give the primary idea on the spatial distribution and temporal dynamics of CO2 and CH4 in the atmospheric surface layer over West Siberia. The analysis of the data showed that the average increase in concentration of carbon dioxide by results of our measurements in this territory increases within 1.95 - 2.53 ppm/year, depending on the area. The analysis of long-term data testifies about existence of growth of concentration of methane within 3.2 - 7.2 ppb / year. The presence of a distributed network of the sites operating in the monitoring regime makes it possible not only to investigate the temporal dynamics of CO2 and CH4 at each site and to determine the spatial differences between the concentrations by comparing the data, but also to plot the distribution charts for different moments of time. This work was supported by the Global Environment Research Account for National Institutes of the Ministry of the Environment (Japan), the Branch of Geology, Geophysics and Mining Sciences of RAS (Program No. 5); State contracts of the Ministry of Education and Science of Russia No. 14.604.21.0100, (RFMTFIBBB210290) and No. 14.613.21.0013 (RFMEFI61314X0013); Interdisciplinary integration projects of the Siberian Branch of the Russian Academy of Science No. 35, No. 70 and No. 131; and Russian Foundation for Basic Research (grants No. 14-05-00526 and 14-05-00590).

Family of new operations equivalency of neuro-fuzzy logic: optoelectronic realization and applications

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Nikolsky, Alexander I.; Yatskovsky, Victor I.; Ogorodnik, K. V.; Lischenko, Sergey

2002-07-01

The perspective of neural networks equivalental models (EM) base on vector-matrix procedure with basic operations of continuous and neuro-fuzzy logic (equivalence, absolute difference) are shown. Capacity on base EMs exceeded the amount of neurons in 2.5 times. This is larger than others neural networks paradigms. Amount neurons of this neural networks on base EMs may be 10 - 20 thousands. The base operations in EMs are normalized equivalency operations. The family of new operations equivalency and non-equivalency of neuro-fuzzy logic's, which we have elaborated on the based of such generalized operations of fuzzy-logic's as fuzzy negation, t-norm and s-norm are shown. Generalized rules of construction of new functions (operations) equivalency which uses relations of t-norm and s-norm to fuzzy negation are proposed. Among these elements the following should be underlined: (1) the element which fulfills the operation of limited difference; (2) the element which algebraic product (intensifier with controlled coefficient of transmission or multiplier of analog signals); (3) the element which fulfills a sample summarizing (uniting) of signals (including the one during normalizing). Synthesized structures which realize on the basic of these elements the whole spectrum of required operations: t-norm, s-norm and new operations equivalency are shown. These realization on the basic of new multifunctional optoelectronical BISPIN- devices (MOEBD) represent the circuit with constant and pulse optical input signals. They are modeling the operation of limited difference. These circuits realize frequency- dynamic neuron models and neural networks. Experimental results of these MOEBD and equivalency circuits, which fulfill the limited difference operation are discussed. For effective realization of neural networks on the basic of EMs as it is shown in report, picture elements are required as main nodes to implement element operations equivalence ('non-equivalence') of neuro-fuzzy logic's.

Analysis of Road Network Pattern Considering Population Distribution and Central Business District

PubMed Central

Zhao, Fangxia; Sun, Huijun; Wu, Jianjun; Gao, Ziyou; Liu, Ronghui

2016-01-01

This paper proposes a road network growing model with the consideration of population distribution and central business district (CBD) attraction. In the model, the relative neighborhood graph (RNG) is introduced as the connection mechanism to capture the characteristics of road network topology. The simulation experiment is set up to illustrate the effects of population distribution and CBD attraction on the characteristics of road network. Moreover, several topological attributes of road network is evaluated by using coverage, circuitness, treeness and total length in the experiment. Finally, the suggested model is verified in the simulation of China and Beijing Highway networks. PMID:26981857

10 CFR 431.36 - Compliance Certification.

Code of Federal Regulations, 2014 CFR

2014-01-01

... EQUIPMENT Electric Motors Certification § 431.36 Compliance Certification. (a) General. A manufacturer or private labeler shall not distribute in commerce any basic model of an electric motor which is subject to... efficiency for each basic model of electric motor distributed is not less than the minimum nominal full load...

10 CFR 431.36 - Compliance Certification.

Code of Federal Regulations, 2013 CFR

2013-01-01

... EQUIPMENT Electric Motors Certification § 431.36 Compliance Certification. (a) General. A manufacturer or private labeler shall not distribute in commerce any basic model of an electric motor which is subject to... efficiency for each basic model of electric motor distributed is not less than the minimum nominal full load...

A tangent-ring optical TWDM-MAN enabling three-level transregional reconfigurations and shared protections by multipoint distributed control

NASA Astrophysics Data System (ADS)

Gou, Kaiyu; Gan, Chaoqin; Zhang, Xiaoyu; Zhang, Yuchao

2018-03-01

An optical time-and-wavelength-division-multiplexing metro-access network (TWDM-MAN) is proposed and demonstrated in this paper. By the reuse of tangent-ring optical distribution network and the design of distributed control mechanism, ONUs needing to communicate with each other can be flexibly accessed to successfully make up three kinds of reconfigurable networks. By the nature advantage of ring topology in protection, three-level comprehensive protections covering both feeder and distribution fibers are also achieved. Besides, a distributed wavelength allocation (DWA) is designed to support efficient parallel upstream transmission. The analyses including capacity, congestion and transmission simulation show that this network has a great performance.

Design of Distributed Engine Control Systems with Uncertain Delay.

PubMed

Liu, Xiaofeng; Li, Yanxi; Sun, Xu

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method.

Design of Distributed Engine Control Systems with Uncertain Delay

PubMed Central

Li, Yanxi; Sun, Xu

2016-01-01

Future gas turbine engine control systems will be based on distributed architecture, in which, the sensors and actuators will be connected to the controllers via a communication network. The performance of the distributed engine control (DEC) is dependent on the network performance. This study introduces a distributed control system architecture based on a networked cascade control system (NCCS). Typical turboshaft engine-distributed controllers are designed based on the NCCS framework with a H∞ output feedback under network-induced time delays and uncertain disturbances. The sufficient conditions for robust stability are derived via the Lyapunov stability theory and linear matrix inequality approach. Both numerical and hardware-in-loop simulations illustrate the effectiveness of the presented method. PMID:27669005

Design framework for entanglement-distribution switching networks

NASA Astrophysics Data System (ADS)

Drost, Robert J.; Brodsky, Michael

2016-09-01

The distribution of quantum entanglement appears to be an important component of applications of quantum communications and networks. The ability to centralize the sourcing of entanglement in a quantum network can provide for improved efficiency and enable a variety of network structures. A necessary feature of an entanglement-sourcing network node comprising several sources of entangled photons is the ability to reconfigurably route the generated pairs of photons to network neighbors depending on the desired entanglement sharing of the network users at a given time. One approach to such routing is the use of a photonic switching network. The requirements for an entanglement distribution switching network are less restrictive than for typical conventional applications, leading to design freedom that can be leveraged to optimize additional criteria. In this paper, we present a mathematical framework defining the requirements of an entanglement-distribution switching network. We then consider the design of such a switching network using a number of 2 × 2 crossbar switches, addressing the interconnection of these switches and efficient routing algorithms. In particular, we define a worst-case loss metric and consider 6 × 6, 8 × 8, and 10 × 10 network designs that optimize both this metric and the number of crossbar switches composing the network. We pay particular attention to the 10 × 10 network, detailing novel results proving the optimality of the proposed design. These optimized network designs have great potential for use in practical quantum networks, thus advancing the concept of quantum networks toward reality.

California Basic Skills Initiative (BSI) Regional Networks as Self-Sustaining Communities of Practice

ERIC Educational Resources Information Center

Mullen, Adrienne Ann

2011-01-01

The Basic Skills Report for California Community Colleges (2007) stresses the importance of comprehensive training and development opportunities for all faculty (tenured and part-time), administrators and staff members who work with underprepared students. With such a large number of academically underprepared students entering the community…

Literacy and Basic Education: A Selected, Annotated Bibliography. Annotated Bibliography #3.

ERIC Educational Resources Information Center

Michigan State Univ., East Lansing. Non-Formal Education Information Center.

A selected annotated bibliography on literacy and basic education, including contributions from practitioners in the worldwide non-formal education network and compiled for them, has three interrelated themes: integration of literacy programs with broader development efforts; the learner-centered or "psycho-social" approach to literacy,…

The Computer as a Tutorial Laboratory: The Stanford BIP Project.

ERIC Educational Resources Information Center

Barr, Avron; And Others

The BASIC Instructional Program (BIP) is an interactive problem-solving laboratory that offers tutorial assistance to students solving introductory programing problems in the BASIC language. After a brief review of the rationale and origins of the BIP instructional system, the design and implementation of BIP's curriculum information network are…

Applications of Coding in Network Communications

ERIC Educational Resources Information Center

Chang, Christopher SungWook

2012-01-01

This thesis uses the tool of network coding to investigate fast peer-to-peer file distribution, anonymous communication, robust network construction under uncertainty, and prioritized transmission. In a peer-to-peer file distribution system, we use a linear optimization approach to show that the network coding framework significantly simplifies…

Epidemic spreading in weighted networks: an edge-based mean-field solution.

PubMed

Yang, Zimo; Zhou, Tao

2012-05-01

Weight distribution greatly impacts the epidemic spreading taking place on top of networks. This paper presents a study of a susceptible-infected-susceptible model on regular random networks with different kinds of weight distributions. Simulation results show that the more homogeneous weight distribution leads to higher epidemic prevalence, which, unfortunately, could not be captured by the traditional mean-field approximation. This paper gives an edge-based mean-field solution for general weight distribution, which can quantitatively reproduce the simulation results. This method could be applied to characterize the nonequilibrium steady states of dynamical processes on weighted networks.

System and method for islanding detection and prevention in distributed generation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhowmik, Shibashis; Mazhari, Iman; Parkhideh, Babak

Various examples are directed to systems and methods for detecting an islanding condition at an inverter configured to couple a distributed generation system to an electrical grid network. A controller may determine a command frequency and a command frequency variation. The controller may determine that the command frequency variation indicates a potential islanding condition and send to the inverter an instruction to disconnect the distributed generation system from the electrical grid network. When the distributed generation system is disconnected from the electrical grid network, the controller may determine whether the grid network is valid.

Analysis and Application of Microgrids

NASA Astrophysics Data System (ADS)

Yue, Lu

New trends of generating electricity locally and utilizing non-conventional or renewable energy sources have attracted increasing interests due to the gradual depletion of conventional fossil fuel energy sources. The new type of power generation is called Distributed Generation (DG) and the energy sources utilized by Distributed Generation are termed Distributed Energy Sources (DERs). With DGs embedded in the distribution networks, they evolve from passive distribution networks to active distribution networks enabling bidirectional power flows in the networks. Further incorporating flexible and intelligent controllers and employing future technologies, active distribution networks will turn to a Microgrid. A Microgrid is a small-scale, low voltage Combined with Heat and Power (CHP) supply network designed to supply electrical and heat loads for a small community. To further implement Microgrids, a sophisticated Microgrid Management System must be integrated. However, due to the fact that a Microgrid has multiple DERs integrated and is likely to be deregulated, the ability to perform real-time OPF and economic dispatch with fast speed advanced communication network is necessary. In this thesis, first, problems such as, power system modelling, power flow solving and power system optimization, are studied. Then, Distributed Generation and Microgrid are studied and reviewed, including a comprehensive review over current distributed generation technologies and Microgrid Management Systems, etc. Finally, a computer-based AC optimization method which minimizes the total transmission loss and generation cost of a Microgrid is proposed and a wireless communication scheme based on synchronized Code Division Multiple Access (sCDMA) is proposed. The algorithm is tested with a 6-bus power system and a 9-bus power system.

Structural factoring approach for analyzing stochastic networks

NASA Technical Reports Server (NTRS)

Hayhurst, Kelly J.; Shier, Douglas R.

1991-01-01

The problem of finding the distribution of the shortest path length through a stochastic network is investigated. A general algorithm for determining the exact distribution of the shortest path length is developed based on the concept of conditional factoring, in which a directed, stochastic network is decomposed into an equivalent set of smaller, generally less complex subnetworks. Several network constructs are identified and exploited to reduce significantly the computational effort required to solve a network problem relative to complete enumeration. This algorithm can be applied to two important classes of stochastic path problems: determining the critical path distribution for acyclic networks and the exact two-terminal reliability for probabilistic networks. Computational experience with the algorithm was encouraging and allowed the exact solution of networks that have been previously analyzed only by approximation techniques.

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.

A Review of Power Distribution Test Feeders in the United States and the Need for Synthetic Representative Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Postigo Marcos, Fernando E.; Domingo, Carlos Mateo; San Roman, Tomas Gomez

Under the increasing penetration of distributed energy resources and new smart network technologies, distribution utilities face new challenges and opportunities to ensure reliable operations, manage service quality, and reduce operational and investment costs. Simultaneously, the research community is developing algorithms for advanced controls and distribution automation that can help to address some of these challenges. However, there is a shortage of realistic test systems that are publically available for development, testing, and evaluation of such new algorithms. Concerns around revealing critical infrastructure details and customer privacy have severely limited the number of actual networks published and that are available formore » testing. In recent decades, several distribution test feeders and US-featured representative networks have been published, but the scale, complexity, and control data vary widely. This paper presents a first-of-a-kind structured literature review of published distribution test networks with a special emphasis on classifying their main characteristics and identifying the types of studies for which they have been used. As a result, this both aids researchers in choosing suitable test networks for their needs and highlights the opportunities and directions for further test system development. In particular, we highlight the need for building large-scale synthetic networks to overcome the identified drawbacks of current distribution test feeders.« less

A Review of Power Distribution Test Feeders in the United States and the Need for Synthetic Representative Networks

DOE PAGES

Postigo Marcos, Fernando E.; Domingo, Carlos Mateo; San Roman, Tomas Gomez; ...

2017-11-18

Under the increasing penetration of distributed energy resources and new smart network technologies, distribution utilities face new challenges and opportunities to ensure reliable operations, manage service quality, and reduce operational and investment costs. Simultaneously, the research community is developing algorithms for advanced controls and distribution automation that can help to address some of these challenges. However, there is a shortage of realistic test systems that are publically available for development, testing, and evaluation of such new algorithms. Concerns around revealing critical infrastructure details and customer privacy have severely limited the number of actual networks published and that are available formore » testing. In recent decades, several distribution test feeders and US-featured representative networks have been published, but the scale, complexity, and control data vary widely. This paper presents a first-of-a-kind structured literature review of published distribution test networks with a special emphasis on classifying their main characteristics and identifying the types of studies for which they have been used. As a result, this both aids researchers in choosing suitable test networks for their needs and highlights the opportunities and directions for further test system development. In particular, we highlight the need for building large-scale synthetic networks to overcome the identified drawbacks of current distribution test feeders.« less

Adaptive Topological Configuration of an Integrated Circuit/Packet-Switched Computer Network.

DTIC Science & Technology

1984-01-01

Gitman et al. [45] state that there are basically two approaches to the integrated network design problem: (1) solve the link/capacity problem for...1972), 1385-1397. 33. Frank, H., and Gitman , I. Economic analysis of integrated voice and data networks: a case study. Proc. of IEEE 66 , 11 (Nov. 1978...1974), 1074-1079. 45. Gitman , I., Hsieh, W., and Occhiogrosso, B. J. Analysis and design of hybrid switching networks. IEEE Trans. on Comm. Com-29

Distributed Localization of Active Transmitters in a Wireless Sensor Network

DTIC Science & Technology

2012-03-01

Distributed Localization of Active Transmitters in a Wireless Sensor Network THESIS Oba L. Vincent, 2nd Lieutenant, USAF AFIT/GE/ENG/12-41 DEPARTMENT...protection in the United States. AFIT/GE/ENG/12-41 Distributed Localization of Active Transmitters in a Wireless Sensor Network THESIS Presented to the...Transmitters in a Wireless Sensor Network Oba L. Vincent, B.S.E.E. 2nd Lieutenant, USAF Approved: /signed/ 29 Feb 2012 Maj. Mark D. Silvius, Ph.D. (Chairman

Resilience-based optimal design of water distribution network

NASA Astrophysics Data System (ADS)

Suribabu, C. R.

2017-11-01

Optimal design of water distribution network is generally aimed to minimize the capital cost of the investments on tanks, pipes, pumps, and other appurtenances. Minimizing the cost of pipes is usually considered as a prime objective as its proportion in capital cost of the water distribution system project is very high. However, minimizing the capital cost of the pipeline alone may result in economical network configuration, but it may not be a promising solution in terms of resilience point of view. Resilience of the water distribution network has been considered as one of the popular surrogate measures to address ability of network to withstand failure scenarios. To improve the resiliency of the network, the pipe network optimization can be performed with two objectives, namely minimizing the capital cost as first objective and maximizing resilience measure of the configuration as secondary objective. In the present work, these two objectives are combined as single objective and optimization problem is solved by differential evolution technique. The paper illustrates the procedure for normalizing the objective functions having distinct metrics. Two of the existing resilience indices and power efficiency are considered for optimal design of water distribution network. The proposed normalized objective function is found to be efficient under weighted method of handling multi-objective water distribution design problem. The numerical results of the design indicate the importance of sizing pipe telescopically along shortest path of flow to have enhanced resiliency indices.

Valid approximation of spatially distributed grain size distributions - A priori information encoded to a feedforward network

NASA Astrophysics Data System (ADS)

Berthold, T.; Milbradt, P.; Berkhahn, V.

2018-04-01

This paper presents a model for the approximation of multiple, spatially distributed grain size distributions based on a feedforward neural network. Since a classical feedforward network does not guarantee to produce valid cumulative distribution functions, a priori information is incor porated into the model by applying weight and architecture constraints. The model is derived in two steps. First, a model is presented that is able to produce a valid distribution function for a single sediment sample. Although initially developed for sediment samples, the model is not limited in its application; it can also be used to approximate any other multimodal continuous distribution function. In the second part, the network is extended in order to capture the spatial variation of the sediment samples that have been obtained from 48 locations in the investigation area. Results show that the model provides an adequate approximation of grain size distributions, satisfying the requirements of a cumulative distribution function.

A hybrid approach to advancing quantitative prediction of tissue distribution of basic drugs in human

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poulin, Patrick, E-mail: patrick-poulin@videotron.ca; Ekins, Sean; Department of Pharmaceutical Sciences, School of Pharmacy, University of Maryland, 20 Penn Street, Baltimore, MD 21201

A general toxicity of basic drugs is related to phospholipidosis in tissues. Therefore, it is essential to predict the tissue distribution of basic drugs to facilitate an initial estimate of that toxicity. The objective of the present study was to further assess the original prediction method that consisted of using the binding to red blood cells measured in vitro for the unbound drug (RBCu) as a surrogate for tissue distribution, by correlating it to unbound tissue:plasma partition coefficients (Kpu) of several tissues, and finally to predict volume of distribution at steady-state (V{sub ss}) in humans under in vivo conditions. Thismore » correlation method demonstrated inaccurate predictions of V{sub ss} for particular basic drugs that did not follow the original correlation principle. Therefore, the novelty of this study is to provide clarity on the actual hypotheses to identify i) the impact of pharmacological mode of action on the generic correlation of RBCu-Kpu, ii) additional mechanisms of tissue distribution for the outlier drugs, iii) molecular features and properties that differentiate compounds as outliers in the original correlation analysis in order to facilitate its applicability domain alongside the properties already used so far, and finally iv) to present a novel and refined correlation method that is superior to what has been previously published for the prediction of human V{sub ss} of basic drugs. Applying a refined correlation method after identifying outliers would facilitate the prediction of more accurate distribution parameters as key inputs used in physiologically based pharmacokinetic (PBPK) and phospholipidosis models.« less

60-Hz electric and magnetic fields generated by a distribution network.

PubMed

Héroux, P

1987-01-01

From a mobile unit, 60-Hz electric and magnetic fields generated by Hydro-Québec's distribution network were measured. Nine runs, representative of various human environments, were investigated. Typical values were 32 V/m and 0.16 microT. The electrical distribution networks investigated were major contributors to the electric and magnetic environments.

Secure NFV Orchestration Over an SDN-Controlled Optical Network With Time-Shared Quantum Key Distribution Resources

NASA Astrophysics Data System (ADS)

Aguado, Alejandro; Hugues-Salas, Emilio; Haigh, Paul Anthony; Marhuenda, Jaume; Price, Alasdair B.; Sibson, Philip; Kennard, Jake E.; Erven, Chris; Rarity, John G.; Thompson, Mark Gerard; Lord, Andrew; Nejabati, Reza; Simeonidou, Dimitra

2017-04-01

We demonstrate, for the first time, a secure optical network architecture that combines NFV orchestration and SDN control with quantum key distribution (QKD) technology. A novel time-shared QKD network design is presented as a cost-effective solution for practical networks.

Network Computing for Distributed Underwater Acoustic Sensors

DTIC Science & Technology

2014-03-31

underwater sensor network with mobility. In preparation. [3] EvoLogics (2013), Underwater Acoustic Modems, (Product Information Guide... Wireless Communications, 9(9), 2934–2944. [21] Pompili, D. and Akyildiz, I. (2010), A multimedia cross-layer protocol for underwater acoustic sensor networks ... Network Computing for Distributed Underwater Acoustic Sensors M. Barbeau E. Kranakis

Hegemonic structure of basic, clinical and patented knowledge on Ebola research: a US army reductionist initiative.

PubMed

Fajardo-Ortiz, David; Ortega-Sánchez-de-Tagle, José; Castaño, Victor M

2015-04-19

Ebola hemorrhagic fever (Ebola) is still a highly lethal infectious disease long affecting mainly neglected populations in sub-Saharan Africa. Moreover, this disease is now considered a potential worldwide threat. In this paper, we present an approach to understand how the basic, clinical and patent knowledge on Ebola is organized and intercommunicated and what leading factor could be shaping the evolution of the knowledge translation process for this disease. A combination of citation network analysis; analysis of Medical heading Subject (MeSH) and Gene Ontology (GO) terms, and quantitative content analysis for patents and scientific literature, aimed to map the organization of Ebola research was carried out. We found six putative research fronts (i.e. clusters of high interconnected papers). Three research fronts are basic research on Ebola virus structural proteins: glycoprotein, VP40 and VP35, respectively. There is a fourth research front of basic research papers on pathogenesis, which is the organizing hub of Ebola research. A fifth research front is pre-clinical research focused on vaccines and glycoproteins. Finally, a clinical-epidemiology research front related to the disease outbreaks was identified. The network structure of patent families shows that the dominant design is the use of Ebola virus proteins as targets of vaccines and other immunological treatments. Therefore, patents network organization resembles the organization of the scientific literature. Specifically, the knowledge on Ebola would flow from higher (clinical-epidemiology) to intermediated (cellular-tissular pathogenesis) to lower (molecular interactions) levels of organization. Our results suggest a strong reductionist approach for Ebola research probably influenced by the lethality of the disease. On the other hand, the ownership profile of the patent families network and the main researches relationship with the United State Army suggest a strong involvement of this military institution in Ebola research.

Comparison of theoretical proteomes: identification of COGs with conserved and variable pI within the multimodal pI distribution.

PubMed

Nandi, Soumyadeep; Mehra, Nipun; Lynn, Andrew M; Bhattacharya, Alok

2005-09-09

Theoretical proteome analysis, generated by plotting theoretical isoelectric points (pI) against molecular masses of all proteins encoded by the genome show a multimodal distribution for pI. This multimodal distribution is an effect of allowed combinations of the charged amino acids, and not due to evolutionary causes. The variation in this distribution can be correlated to the organisms ecological niche. Contributions to this variation maybe mapped to individual proteins by studying the variation in pI of orthologs across microorganism genomes. The distribution of ortholog pI values showed trimodal distributions for all prokaryotic genomes analyzed, similar to whole proteome plots. Pairwise analysis of pI variation show that a few COGs are conserved within, but most vary between, the acidic and basic regions of the distribution, while molecular mass is more highly conserved. At the level of functional grouping of orthologs, five groups vary significantly from the population of orthologs, which is attributed to either conservation at the level of sequences or a bias for either positively or negatively charged residues contributing to the function. Individual COGs conserved in both the acidic and basic regions of the trimodal distribution are identified, and orthologs that best represent the variation in levels of the acidic and basic regions are listed. The analysis of pI distribution by using orthologs provides a basis for resolution of theoretical proteome comparison at the level of individual proteins. Orthologs identified that significantly vary between the major acidic and basic regions maybe used as representative of the variation of the entire proteome.