Analyzing complex networks evolution through Information Theory quantifiers

Energy Technology Data Exchange (ETDEWEB)

Carpi, Laura C., E-mail: Laura.Carpi@studentmail.newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Rosso, Osvaldo A., E-mail: rosso@fisica.ufmg.b [Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Chaos and Biology Group, Instituto de Calculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellon II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires (Argentina); Saco, Patricia M., E-mail: Patricia.Saco@newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Hidraulica, Facultad de Ciencias Exactas, Ingenieria y Agrimensura, Universidad Nacional de Rosario, Avenida Pellegrini 250, Rosario (Argentina); Ravetti, Martin Gomez, E-mail: martin.ravetti@dep.ufmg.b [Departamento de Engenharia de Producao, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, Belo Horizonte (31270-901), MG (Brazil)

2011-01-24

A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Nino/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

Structural factoring approach for analyzing stochastic networks

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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.

Analyzing Bullwhip Effect in Supply Networks under Exogenous Uncertainty

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Mitra Darvish

2014-05-01

Full Text Available This paper explains a model for analyzing and measuring the propagation of order amplifications (i.e. bullwhip effect for a single-product supply network topology considering exogenous uncertainty and linear and time-invariant inventory management policies for network entities. The stream of orders placed by each entity of the network is characterized assuming customer demand is ergodic. In fact, we propose an exact formula in order to measure the bullwhip effect in the addressed supply network topology considering the system in Markovian chain framework and presenting a matrix of network member relationships and relevant order sequences. The formula turns out using a mathematical method called frequency domain analysis. The major contribution of this paper is analyzing the bullwhip effect considering exogenous uncertainty in supply networks and using the Fourier transform in order to simplify the relevant calculations. We present a number of numerical examples to assess the analytical results accuracy in quantifying the bullwhip effect.

System, apparatus and methods to implement high-speed network analyzers

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Ezick, James; Lethin, Richard; Ros-Giralt, Jordi; Szilagyi, Peter; Wohlford, David E

2015-11-10

Systems, apparatus and methods for the implementation of high-speed network analyzers are provided. A set of high-level specifications is used to define the behavior of the network analyzer emitted by a compiler. An optimized inline workflow to process regular expressions is presented without sacrificing the semantic capabilities of the processing engine. An optimized packet dispatcher implements a subset of the functions implemented by the network analyzer, providing a fast and slow path workflow used to accelerate specific processing units. Such dispatcher facility can also be used as a cache of policies, wherein if a policy is found, then packet manipulations associated with the policy can be quickly performed. An optimized method of generating DFA specifications for network signatures is also presented. The method accepts several optimization criteria, such as min-max allocations or optimal allocations based on the probability of occurrence of each signature input bit.

Systems and methods for modeling and analyzing networks

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Hill, Colin C; Church, Bruce W; McDonagh, Paul D; Khalil, Iya G; Neyarapally, Thomas A; Pitluk, Zachary W

2013-10-29

The systems and methods described herein utilize a probabilistic modeling framework for reverse engineering an ensemble of causal models, from data and then forward simulating the ensemble of models to analyze and predict the behavior of the network. In certain embodiments, the systems and methods described herein include data-driven techniques for developing causal models for biological networks. Causal network models include computational representations of the causal relationships between independent variables such as a compound of interest and dependent variables such as measured DNA alterations, changes in mRNA, protein, and metabolites to phenotypic readouts of efficacy and toxicity.

Network public opinion space sentiment tendency analyze based on recurrent convolution neural network

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Zhang, Gaowei; Xu, Lingyu; Wang, Lei

2018-04-01

The purpose of this chapter is to analyze the investor's psychological characteristics and investment decision-making behavior characteristics, to study the investor sentiment under the network public opinion, and then analyze from three aspects: First, investor sentiment analysis and how to spread in the online media; The influence mechanism of investor's emotion on the stock market and its effect; the third one is to measure the investor's emotion based on the degree of attention, trying hard to sort out the internal relations between the investor's sentiment and the network public opinion and the stock market, in order to lay the theoretical foundation of this article.

Analyzing the Bitcoin Network: The First Four Years

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Matthias Lischke

2016-03-01

Full Text Available In this explorative study, we examine the economy and transaction network of the decentralized digital currency Bitcoin during the first four years of its existence. The objective is to develop insights into the evolution of the Bitcoin economy during this period. For this, we establish and analyze a novel integrated dataset that enriches data from the Bitcoin blockchain with off-network data such as business categories and geo-locations. Our analyses reveal the major Bitcoin businesses and markets. Our results also give insights on the business distribution by countries and how businesses evolve over time. We also show that there is a gambling network that features many very small transactions. Furthermore, regional differences in the adoption and business distribution could be found. In the network analysis, the small world phenomenon is investigated and confirmed for several subgraphs of the Bitcoin network.

Microwave Impedance Measurement for Nanoelectronics

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M. Randus

2011-04-01

Full Text Available The rapid progress in nanoelectronics showed an urgent need for microwave measurement of impedances extremely different from the 50Ω reference impedance of measurement instruments. In commonly used methods input impedance or admittance of a device under test (DUT is derived from measured value of its reflection coefficient causing serious accuracy problems for very high and very low impedances due to insufficient sensitivity of the reflection coefficient to impedance of the DUT. This paper brings theoretical description and experimental verification of a method developed especially for measurement of extreme impedances. The method can significantly improve measurement sensitivity and reduce errors caused by the VNA. It is based on subtraction (or addition of a reference reflection coefficient and the reflection coefficient of the DUT by a passive network, amplifying the resulting signal by an amplifier and measuring the amplified signal as a transmission coefficient by a common vector network analyzer (VNA. A suitable calibration technique is also presented.

How to Analyze Company Using Social Network?

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Palus, Sebastian; Bródka, Piotr; Kazienko, Przemysław

Every single company or institution wants to utilize its resources in the most efficient way. In order to do so they have to be have good structure. The new way to analyze company structure by utilizing existing within company natural social network and example of its usage on Enron company are presented in this paper.

The wireshark field guide analyzing and troubleshooting network traffic

CERN Document Server

Shimonski, Robert

2013-01-01

The Wireshark Field Guide provides hackers, pen testers, and network administrators with practical guidance on capturing and interactively browsing computer network traffic. Wireshark is the world's foremost network protocol analyzer, with a rich feature set that includes deep inspection of hundreds of protocols, live capture, offline analysis and many other features. The Wireshark Field Guide covers the installation, configuration and use of this powerful multi-platform tool. The book give readers the hands-on skills to be more productive with Wireshark as they drill

Rozšírenie frekvenčného rozsahu VNA do pásma X

CERN Document Server

Durica, Milan

This thesis focuses on measurement of microwave circuits in the X- band. It briefly introduces the reader to the basic distribution of the electromagnetic spectrum and the fundamentals of high-frequency measurement using a microwave vector network analyzer. The main topic of this thesis is to design and implement a microwave circuit that will be able to expand the frequency range of a "low frequency" vector network analyzer HP8752 into the X-band and demonstrate its function by measuring some standard microwave components.

Analyzing energy consumption of wireless networks. A model-based approach

Energy Technology Data Exchange (ETDEWEB)

Yue, Haidi

2013-03-04

During the last decades, wireless networking has been continuously a hot topic both in academy and in industry. Many different wireless networks have been introduced like wireless local area networks, wireless personal networks, wireless ad hoc networks, and wireless sensor networks. If these networks want to have a long term usability, the power consumed by the wireless devices in each of these networks needs to be managed efficiently. Hence, a lot of effort has been carried out for the analysis and improvement of energy efficiency, either for a specific network layer (protocol), or new cross-layer designs. In this thesis, we apply model-based approach for the analysis of energy consumption of different wireless protocols. The protocols under consideration are: one leader election protocol, one routing protocol, and two medium access control protocols. By model-based approach we mean that all these four protocols are formalized as some formal models, more precisely, as discrete-time Markov chains (DTMCs), Markov decision processes (MDPs), or stochastic timed automata (STA). For the first two models, DTMCs and MDPs, we model them in PRISM, a prominent model checker for probabilistic model checking, and apply model checking technique to analyze them. Model checking belongs to the family of formal methods. It discovers exhaustively all possible (reachable) states of the models, and checks whether these models meet a given specification. Specifications are system properties that we want to study, usually expressed by some logics, for instance, probabilistic computer tree logic (PCTL). However, while model checking relies on rigorous mathematical foundations and automatically explores the entire state space of a model, its applicability is also limited by the so-called state space explosion problem -- even systems of moderate size often yield models with an exponentially larger state space that thwart their analysis. Hence for the STA models in this thesis, since there

Accuracy assessment of the scalar network analyzer using sliding termination techniques

DEFF Research Database (Denmark)

Knudsen, Bent; Engen, Glenn F.; Guldbrandsen, Birthe

1989-01-01

In the absence of phase response the major, if not the primary, sources of error in the scalar network analyzer are the imperfect directivity, etc., associated with its internal and frequently inaccessible test set or measurement network. An explicit expression is obtained for this error in terms...

Program for Analyzing Flows in a Complex Network

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Majumdar, Alok Kumar

2006-01-01

Generalized Fluid System Simulation Program (GFSSP) version 4 is a general-purpose computer program for analyzing steady-state and transient flows in a complex fluid network. The program is capable of modeling compressibility, fluid transients (e.g., water hammers), phase changes, mixtures of chemical species, and such externally applied body forces as gravitational and centrifugal ones. A graphical user interface enables the user to interactively develop a simulation of a fluid network consisting of nodes and branches. The user can also run the simulation and view the results in the interface. The system of equations for conservation of mass, energy, chemical species, and momentum is solved numerically by a combination of the Newton-Raphson and successive-substitution methods.

Innovation Networks New Approaches in Modelling and Analyzing

CERN Document Server

Pyka, Andreas

2009-01-01

The science of graphs and networks has become by now a well-established tool for modelling and analyzing a variety of systems with a large number of interacting components. Starting from the physical sciences, applications have spread rapidly to the natural and social sciences, as well as to economics, and are now further extended, in this volume, to the concept of innovations, viewed broadly. In an abstract, systems-theoretical approach, innovation can be understood as a critical event which destabilizes the current state of the system, and results in a new process of self-organization leading to a new stable state. The contributions to this anthology address different aspects of the relationship between innovation and networks. The various chapters incorporate approaches in evolutionary economics, agent-based modeling, social network analysis and econophysics and explore the epistemic tension between insights into economics and society-related processes, and the insights into new forms of complex dynamics.

Development of a new software for analyzing 3-D fracture network

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Um, Jeong-Gi; Noh, Young-Hwan; Choi, Yosoon

2014-05-01

A new software is presented to analyze fracture network in 3-D. Recently, we completed the software package based on information given in EGU2013. The software consists of several modules that play roles in management of borehole data, stochastic modelling of fracture network, construction of analysis domain, visualization of fracture geometry in 3-D, calculation of equivalent pipes and production of cross-section diagrams. Intel Parallel Studio XE 2013, Visual Studio.NET 2010 and the open source VTK library were utilized as development tools to efficiently implement the modules and the graphical user interface of the software. A case study was performed to analyze 3-D fracture network system at the Upper Devonian Grosmont Formation in Alberta, Canada. The results have suggested that the developed software is effective in modelling and visualizing 3-D fracture network system, and can provide useful information to tackle the geomechanical problems related to strength, deformability and hydraulic behaviours of the fractured rock masses. This presentation describes the concept and details of the development and implementation of the software.

Characteristics of visiting nurse agencies with high home death rates: A prefecture-wide study in Japan.

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Kashiwagi, Masayo; Tamiya, Nanako; Murata, Masako

2015-08-01

The purpose of the present study was to identify characteristics of visiting nurse agencies (VNA) in Japan with high home death rates by a prefecture-wide survey. A cross-sectional study of visiting nurse agencies (n = 101) in Ibaraki Prefecture, Japan, was completed. Data included the basic characteristics of each VNA, the type of services provided, level of coordination with other service providers, total number of VNA patients who died per year and place of death and contractual relationship with home-care supporting clinics providing end-of-life care services in the home 24 h a day. The VNA characteristics were analyzed by logistic regression, using the home death rate per VNA as a dependent variable. A total 69 agencies, excluding those that did not report number of deaths (n = 14) and those without deaths during the year (n = 6), were analyzed. The median home death rate of the 69 VNA was 29.8%. The results of logistic regression analysis showed that higher home death rate was significantly associated with lack of attachment to a hospital, existence of a contractual relationship with home-care supporting clinics and existence of an interactive information exchange through telephone/face-to-face communication with attending physicians. In order to increase the home death rate of people using VNA, policymakers must consider establishing home-based service systems within the community that can provide home end-of-life care services 24 h a day, and support the interactive exchange of information between the visiting nurse and the attending physician. © 2014 The Authors. Geriatrics & Gerontology International published by Wiley Publishing Asia Pty Ltd on behalf of Japanese Geriatrics Society.

Analyzing the multilevel structure of the European airport network

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Oriol Lordan

2017-04-01

Full Text Available The multilayered structure of the European airport network (EAN, composed of connections and flights between European cities, is analyzed through the k-core decomposition of the connections network. This decomposition allows to identify the core, bridge and periphery layers of the EAN. The core layer includes the best-connected cities, which include important business air traffic destinations. The periphery layer includes cities with lesser connections, which serve low populated areas where air travel is an economic alternative. The remaining cities form the bridge of the EAN, including important leisure travel origins and destinations. The multilayered structure of the EAN affects network robustness, as the EAN is more robust to isolation of nodes of the core, than to the isolation of a combination of core and bridge nodes.

PerturbationAnalyzer: a tool for investigating the effects of concentration perturbation on protein interaction networks.

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Li, Fei; Li, Peng; Xu, Wenjian; Peng, Yuxing; Bo, Xiaochen; Wang, Shengqi

2010-01-15

The propagation of perturbations in protein concentration through a protein interaction network (PIN) can shed light on network dynamics and function. In order to facilitate this type of study, PerturbationAnalyzer, which is an open source plugin for Cytoscape, has been developed. PerturbationAnalyzer can be used in manual mode for simulating user-defined perturbations, as well as in batch mode for evaluating network robustness and identifying significant proteins that cause large propagation effects in the PINs when their concentrations are perturbed. Results from PerturbationAnalyzer can be represented in an intuitive and customizable way and can also be exported for further exploration. PerturbationAnalyzer has great potential in mining the design principles of protein networks, and may be a useful tool for identifying drug targets. PerturbationAnalyzer can be accessed from the Cytoscape web site http://www.cytoscape.org/plugins/index.php or http://biotech.bmi.ac.cn/PerturbationAnalyzer. Supplementary data are available at Bioinformatics online.

A Comparison of Geographic Information Systems, Complex Networks, and Other Models for Analyzing Transportation Network Topologies

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Alexandrov, Natalia (Technical Monitor); Kuby, Michael; Tierney, Sean; Roberts, Tyler; Upchurch, Christopher

2005-01-01

This report reviews six classes of models that are used for studying transportation network topologies. The report is motivated by two main questions. First, what can the "new science" of complex networks (scale-free, small-world networks) contribute to our understanding of transport network structure, compared to more traditional methods? Second, how can geographic information systems (GIS) contribute to studying transport networks? The report defines terms that can be used to classify different kinds of models by their function, composition, mechanism, spatial and temporal dimensions, certainty, linearity, and resolution. Six broad classes of models for analyzing transport network topologies are then explored: GIS; static graph theory; complex networks; mathematical programming; simulation; and agent-based modeling. Each class of models is defined and classified according to the attributes introduced earlier. The paper identifies some typical types of research questions about network structure that have been addressed by each class of model in the literature.

Novel topological descriptors for analyzing biological networks

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Varmuza Kurt K

2010-06-01

Full Text Available Abstract Background Topological descriptors, other graph measures, and in a broader sense, graph-theoretical methods, have been proven as powerful tools to perform biological network analysis. However, the majority of the developed descriptors and graph-theoretical methods does not have the ability to take vertex- and edge-labels into account, e.g., atom- and bond-types when considering molecular graphs. Indeed, this feature is important to characterize biological networks more meaningfully instead of only considering pure topological information. Results In this paper, we put the emphasis on analyzing a special type of biological networks, namely bio-chemical structures. First, we derive entropic measures to calculate the information content of vertex- and edge-labeled graphs and investigate some useful properties thereof. Second, we apply the mentioned measures combined with other well-known descriptors to supervised machine learning methods for predicting Ames mutagenicity. Moreover, we investigate the influence of our topological descriptors - measures for only unlabeled vs. measures for labeled graphs - on the prediction performance of the underlying graph classification problem. Conclusions Our study demonstrates that the application of entropic measures to molecules representing graphs is useful to characterize such structures meaningfully. For instance, we have found that if one extends the measures for determining the structural information content of unlabeled graphs to labeled graphs, the uniqueness of the resulting indices is higher. Because measures to structurally characterize labeled graphs are clearly underrepresented so far, the further development of such methods might be valuable and fruitful for solving problems within biological network analysis.

Analyzing topological characteristics of neuronal functional networks in the rat brain

International Nuclear Information System (INIS)

Lu, Hu; Yang, Shengtao; Song, Yuqing; Wei, Hui

2014-01-01

In this study, we recorded spike trains from brain cortical neurons of several behavioral rats in vivo by using multi-electrode recordings. An NFN was constructed in each trial, obtaining a total of 150 NFNs in this study. The topological characteristics of NFNs were analyzed by using the two most important characteristics of complex networks, namely, small-world structure and community structure. We found that the small-world properties exist in different NFNs constructed in this study. Modular function Q was used to determine the existence of community structure in NFNs, through which we found that community-structure characteristics, which are related to recorded spike train data sets, are more evident in the Y-maze task than in the DM-GM task. Our results can also be used to analyze further the relationship between small-world characteristics and the cognitive behavioral responses of rats. - Highlights: • We constructed the neuronal function networks based on the recorded neurons. • We analyzed the two main complex network characteristics, namely, small-world structure and community structure. • NFNs which were constructed based on the recorded neurons in this study exhibit small-world properties. • Some NFNs have community structure characteristics

Analyzing topological characteristics of neuronal functional networks in the rat brain

Energy Technology Data Exchange (ETDEWEB)

Lu, Hu [School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu 212003 (China); School of Computer Science, Fudan University, Shanghai 200433 (China); Yang, Shengtao [Institutes of Brain Science, Fudan University, Shanghai 200433 (China); Song, Yuqing [School of Computer Science and Communication Engineering, Jiangsu University, Jiangsu 212003 (China); Wei, Hui [School of Computer Science, Fudan University, Shanghai 200433 (China)

2014-08-28

In this study, we recorded spike trains from brain cortical neurons of several behavioral rats in vivo by using multi-electrode recordings. An NFN was constructed in each trial, obtaining a total of 150 NFNs in this study. The topological characteristics of NFNs were analyzed by using the two most important characteristics of complex networks, namely, small-world structure and community structure. We found that the small-world properties exist in different NFNs constructed in this study. Modular function Q was used to determine the existence of community structure in NFNs, through which we found that community-structure characteristics, which are related to recorded spike train data sets, are more evident in the Y-maze task than in the DM-GM task. Our results can also be used to analyze further the relationship between small-world characteristics and the cognitive behavioral responses of rats. - Highlights: • We constructed the neuronal function networks based on the recorded neurons. • We analyzed the two main complex network characteristics, namely, small-world structure and community structure. • NFNs which were constructed based on the recorded neurons in this study exhibit small-world properties. • Some NFNs have community structure characteristics.

Wireless network of stand-alone end effect probes for soil in situ permittivity measurements over the 100MHZ-6GHz frequency range

Science.gov (United States)

Demontoux, François; Bircher, Simone; Ruffié, Gilles; Bonnaudiin, Fabrice; Wigneron, Jean-Pierre; Kerr, Yann

2017-04-01

Microwave remote sensing and non-destructive analysis are a powerful way to provide properties estimation of materials. Numerous applications using microwave frequency behavior of materials (remote sensing above land surfaces, non-destructive analysis…) are strongly dependent on the material's permittivity (i.e. dielectric properties). This permittivity depends on numerous parameters such as moisture, texture, temperature, frequency or bulk density. Permittivity measurements are generally carried out in the laboratory. Additionally, dielectric mixing models allow, over a restricted range of conditions, the assessment of a material's permittivity. in-situ measurements are more difficult to obtain. Some in situ measurement probes based on permittivity properties of soil exist (e.g. Time Domain Reflectometers and Transmissometers, capacitance and impedance sensors). They are dedicated to the acquisition of soil moisture data based on permittivity (mainly the real part) estimations over a range of frequencies from around 50 MHz to 1 or 2 GHz. Other Dielectric Assessment Kits exist but they are expensive and they are rather dedicated to laboratory measurements. Furthermore, the user can't address specific issues related to particular materials (e.g. organic soils) or specific measurement conditions (in situ long time records). At the IMS Laboratory we develop probes for in situ soil permittivity measurements (real and imaginary parts) in the 0.5 - 6 GHz frequency range. They are based on the end effect phenomenon of a coaxial waveguide and so are called end effect probes in this paper. The probes can be connected to a portable Vector Network Analyzer (VNA, ANRITSU MS2026A) for the S11 coefficient measurements needed to compute permittivity. It is connected to a PC to record data using an USB connection. This measurement set-up is already used for in situ measurement of soil properties in the framework of the European Space Agency's (ESA) SMOS space mission. However

Analyzing the reliability of shuffle-exchange networks using reliability block diagrams

International Nuclear Information System (INIS)

Bistouni, Fathollah; Jahanshahi, Mohsen

2014-01-01

Supercomputers and multi-processor systems are comprised of thousands of processors that need to communicate in an efficient way. One reasonable solution would be the utilization of multistage interconnection networks (MINs), where the challenge is to analyze the reliability of such networks. One of the methods to increase the reliability and fault-tolerance of the MINs is use of various switching stages. Therefore, recently, the reliability of one of the most common MINs namely shuffle-exchange network (SEN) has been evaluated through the investigation on the impact of increasing the number of switching stage. Also, it is concluded that the reliability of SEN with one additional stage (SEN+) is better than SEN or SEN with two additional stages (SEN+2), even so, the reliability of SEN is better compared to SEN with two additional stages (SEN+2). Here we re-evaluate the reliability of these networks where the results of the terminal, broadcast, and network reliability analysis demonstrate that SEN+ and SEN+2 continuously outperform SEN and are very alike in terms of reliability. - Highlights: • The impact of increasing the number of stages on reliability of MINs is investigated. • The RBD method as an accurate method is used for the reliability analysis of MINs. • Complex series–parallel RBDs are used to determine the reliability of the MINs. • All measures of the reliability (i.e. terminal, broadcast, and network reliability) are analyzed. • All reliability equations will be calculated for different size N×N

Limitation of degree information for analyzing the interaction evolution in online social networks

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Shang, Ke-Ke; Yan, Wei-Sheng; Xu, Xiao-Ke

2014-04-01

Previously many studies on online social networks simply analyze the static topology in which the friend relationship once established, then the links and nodes will not disappear, but this kind of static topology may not accurately reflect temporal interactions on online social services. In this study, we define four types of users and interactions in the interaction (dynamic) network. We found that active, disappeared, new and super nodes (users) have obviously different strength distribution properties and this result also can be revealed by the degree characteristics of the unweighted interaction and friendship (static) networks. However, the active, disappeared, new and super links (interactions) only can be reflected by the strength distribution in the weighted interaction network. This result indicates the limitation of the static topology data on analyzing social network evolutions. In addition, our study uncovers the approximately stable statistics for the dynamic social network in which there are a large variation for users and interaction intensity. Our findings not only verify the correctness of our definitions, but also helped to study the customer churn and evaluate the commercial value of valuable customers in online social networks.

Analyzing the Social Networks of High- and Low-Performing Students in Online Discussion Forums

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Ghadirian, Hajar; Salehi, Keyvan; Ayub, Ahmad Fauzi Mohd

2018-01-01

An ego network is an individual's social network relationships with core members. In this study, the ego network parameters in online discussion spaces of high- and low-performing students were compared. The extent to which students' ego networks changed over the course were also analyzed. Participation in 7 weeks of online discussions were…

Characterization of leadership styles by analyzing social networks

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Enrique Saravia Vergara

2015-12-01

Full Text Available The study presents an analysis of networks to characterize the leadership styles in an institution volunteer, complementary or alternative to classic questionnaires to measure leadership. The study raises test questions to identify friendly relations and prominent leaders in the leadership dimensions of transformational, transactional and passive / avoidant and analyzes, for each of them, the metrics of the network structure as a whole and the role each individual actor. The study exploratory level, based on the opinion of 9 members of a specific project, allowed to show the benefits of network analysis applied to the subject of leadership: (i identified that the climate of "respect and trust", "enthusiasm" and "concern for the welfare of the people" dominate the organization; and (ii the individual role of each leader was identified. Three leaders who are considered as the best friends and care about the welfare of others were identified, but one of them stands for broadcasting "greater respect and trust" and is "an example to follow"; while the other two leaders stand out as being more "enthusiastic and optimistic" and "promote innovation and creativity," among other findings.

Analyzing Enterprise Networks Needs: Action Research from the Mechatronics Sector

Science.gov (United States)

Cagnazzo, Luca; Taticchi, Paolo; Bidini, Gianni; Baglieri, Enzo

New business models and theories are developing nowadays towards collaborative environments direction, and many new tools in sustaining companies involved in these organizations are emerging. Among them, a plethora of methodologies to analyze their needs are already developed for single companies. Few academic works are available about Enterprise Networks (ENs) need analysis. This paper presents the learning from an action research (AR) in the mechatronics sector: AR has been used in order to experience the issue of evaluating network needs and therefore define, develop, and test a complete framework for network evaluation. Reflection on the story in the light of the experience and the theory is presented, as well as extrapolation to a broader context and articulation of usable knowledge.

Application of Microwave Moisture Sensor for Determination of Oil Palm Fruit Ripeness

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Yeow, You Kok; Abbas, Zulkifly; Khalid, Kaida

2010-01-01

This paper describes the development of a low cost coaxial moisture sensor for the determination of moisture content (30 % to 80 % wet-weight basis) of the oil palm fruits of various degree of fruit ripeness. The sensor operating between 1 GHz and 5 GHz was fabricated from an inexpensive 4.1 mm outer diameter SMA coaxial stub contact panel which is suitable for single fruit measurement. The measurement system consists of the sensor and a PC-controlled vector network analyzer (VNA). The actual moisture content was determined by standard oven drying method and compared with predicted value of fruit moisture content obtained using the studied sensor. The sensor was used to monitor fruit ripeness based on the measurement of the phase or magnitude of reflection coefficient and the dielectric measurement software was developed to control and acquire data from the VNA using Agilent VEE. This software was used to calculate the complex relative permittivity from the measured reflection coefficient between 1GHz and 5 GHz.

Analyzing security protocols in hierarchical networks

DEFF Research Database (Denmark)

Zhang, Ye; Nielson, Hanne Riis

2006-01-01

Validating security protocols is a well-known hard problem even in a simple setting of a single global network. But a real network often consists of, besides the public-accessed part, several sub-networks and thereby forms a hierarchical structure. In this paper we first present a process calculus...... capturing the characteristics of hierarchical networks and describe the behavior of protocols on such networks. We then develop a static analysis to automate the validation. Finally we demonstrate how the technique can benefit the protocol development and the design of network systems by presenting a series...

Analyzing, Modeling, and Simulation for Human Dynamics in Social Network

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Yunpeng Xiao

2012-01-01

Full Text Available This paper studies the human behavior in the top-one social network system in China (Sina Microblog system. By analyzing real-life data at a large scale, we find that the message releasing interval (intermessage time obeys power law distribution both at individual level and at group level. Statistical analysis also reveals that human behavior in social network is mainly driven by four basic elements: social pressure, social identity, social participation, and social relation between individuals. Empirical results present the four elements' impact on the human behavior and the relation between these elements. To further understand the mechanism of such dynamic phenomena, a hybrid human dynamic model which combines “interest” of individual and “interaction” among people is introduced, incorporating the four elements simultaneously. To provide a solid evaluation, we simulate both two-agent and multiagent interactions with real-life social network topology. We achieve the consistent results between empirical studies and the simulations. The model can provide a good understanding of human dynamics in social network.

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

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T. Sigi eHale

2014-07-01

Full Text Available Background: A growing body of research has identified abnormal visual information processing in 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 to 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 to 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.

Study of spin dynamics and damping on the magnetic nanowire arrays with various nanowire widths

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Cho, Jaehun [Department of Physics, Inha University, Incheon, 402-751 (Korea, Republic of); Fujii, Yuya; Konioshi, Katsunori [Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka 560-8531 (Japan); Yoon, Jungbum [Department of Electrical and Computer Engineering, National University of Singapore, Singapore 117576 (Singapore); Kim, Nam-Hui; Jung, Jinyong [Department of Physics, Inha University, Incheon, 402-751 (Korea, Republic of); Miwa, Shinji [Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka 560-8531 (Japan); Jung, Myung-Hwa [Department of Physics, Sogang University, Seoul, 121-742 (Korea, Republic of); Suzuki, Yoshishige [Graduate School of Engineering Science, Osaka University, Toyonaka, Osaka 560-8531 (Japan); You, Chun-Yeol, E-mail: cyyou@inha.ac.kr [Department of Physics, Inha University, Incheon, 402-751 (Korea, Republic of)

2016-07-01

We investigate the spin dynamics including Gilbert damping in the ferromagnetic nanowire arrays. We have measured the ferromagnetic resonance of ferromagnetic nanowire arrays using vector-network analyzer ferromagnetic resonance (VNA-FMR) and analyzed the results with the micromagnetic simulations. We find excellent agreement between the experimental VNA-FMR spectra and micromagnetic simulations result for various applied magnetic fields. We find that the same tendency of the demagnetization factor for longitudinal and transverse conditions, N{sub z} (N{sub y}) increases (decreases) as increasing the nanowire width in the micromagnetic simulations while N{sub x} is almost zero value in transverse case. We also find that the Gilbert damping constant increases from 0.018 to 0.051 as the increasing nanowire width for the transverse case, while it is almost constant as 0.021 for the longitudinal case. - Highlights: • We investigate the spin dynamic properties in the ferromagnetic nanowire arrays. • The demagnetization factors have similar tendency with the prism geometry results. • The Gilbert damping constant is increased from 0.018 to 0.051 as the increasing nanowire width for the transverse. • The Gilbert damping constant is almost constant as 0.021 for the longitudinal case.

Tiny Integrated Network Analyzer for Noninvasive Measurements of Electrically Small Antennas

DEFF Research Database (Denmark)

Buskgaard, Emil Feldborg; Krøyer, Ben; Tatomirescu, Alexandru

2016-01-01

the system. The tiny integrated network analyzer is a stand-alone Arduino-based measurement system that utilizes the transmit signal of the system under test as its reference. It features a power meter with triggering ability, on-board memory, universal serial bus, and easy extendibility with general...

Theoretical and Numerical Approaches for Determining the Reflection and Transmission Coefficients of OPEFB-PCL Composites at X-Band Frequencies.

Science.gov (United States)

Ahmad, Ahmad F; Abbas, Zulkifly; Obaiys, Suzan J; Ibrahim, Norazowa; Hashim, Mansor; Khaleel, Haider

2015-01-01

Bio-composites of oil palm empty fruit bunch (OPEFB) fibres and polycaprolactones (PCL) with a thickness of 1 mm were prepared and characterized. The composites produced from these materials are low in density, inexpensive, environmentally friendly, and possess good dielectric characteristics. The magnitudes of the reflection and transmission coefficients of OPEFB fibre-reinforced PCL composites with different percentages of filler were measured using a rectangular waveguide in conjunction with a microwave vector network analyzer (VNA) in the X-band frequency range. In contrast to the effective medium theory, which states that polymer-based composites with a high dielectric constant can be obtained by doping a filler with a high dielectric constant into a host material with a low dielectric constant, this paper demonstrates that the use of a low filler percentage (12.2%OPEFB) and a high matrix percentage (87.8%PCL) provides excellent results for the dielectric constant and loss factor, whereas 63.8% filler material with 36.2% host material results in lower values for both the dielectric constant and loss factor. The open-ended probe technique (OEC), connected with the Agilent vector network analyzer (VNA), is used to determine the dielectric properties of the materials under investigation. The comparative approach indicates that the mean relative error of FEM is smaller than that of NRW in terms of the corresponding S21 magnitude. The present calculation of the matrix/filler percentages endorses the exact amounts of substrate utilized in various physics applications.

Theoretical and Numerical Approaches for Determining the Reflection and Transmission Coefficients of OPEFB-PCL Composites at X-Band Frequencies.

Directory of Open Access Journals (Sweden)

Ahmad F Ahmad

Full Text Available Bio-composites of oil palm empty fruit bunch (OPEFB fibres and polycaprolactones (PCL with a thickness of 1 mm were prepared and characterized. The composites produced from these materials are low in density, inexpensive, environmentally friendly, and possess good dielectric characteristics. The magnitudes of the reflection and transmission coefficients of OPEFB fibre-reinforced PCL composites with different percentages of filler were measured using a rectangular waveguide in conjunction with a microwave vector network analyzer (VNA in the X-band frequency range. In contrast to the effective medium theory, which states that polymer-based composites with a high dielectric constant can be obtained by doping a filler with a high dielectric constant into a host material with a low dielectric constant, this paper demonstrates that the use of a low filler percentage (12.2%OPEFB and a high matrix percentage (87.8%PCL provides excellent results for the dielectric constant and loss factor, whereas 63.8% filler material with 36.2% host material results in lower values for both the dielectric constant and loss factor. The open-ended probe technique (OEC, connected with the Agilent vector network analyzer (VNA, is used to determine the dielectric properties of the materials under investigation. The comparative approach indicates that the mean relative error of FEM is smaller than that of NRW in terms of the corresponding S21 magnitude. The present calculation of the matrix/filler percentages endorses the exact amounts of substrate utilized in various physics applications.

Sensing across large-scale cognitive radio networks: Data processing, algorithms, and testbed for wireless tomography and moving target tracking

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Bonior, Jason David

As the use of wireless devices has become more widespread so has the potential for utilizing wireless networks for remote sensing applications. Regular wireless communication devices are not typically designed for remote sensing. Remote sensing techniques must be carefully tailored to the capabilities of these networks before they can be applied. Experimental verification of these techniques and algorithms requires robust yet flexible testbeds. In this dissertation, two experimental testbeds for the advancement of research into sensing across large-scale cognitive radio networks are presented. System architectures, implementations, capabilities, experimental verification, and performance are discussed. One testbed is designed for the collection of scattering data to be used in RF and wireless tomography research. This system is used to collect full complex scattering data using a vector network analyzer (VNA) and amplitude-only data using non-synchronous software-defined radios (SDRs). Collected data is used to experimentally validate a technique for phase reconstruction using semidefinite relaxation and demonstrate the feasibility of wireless tomography. The second testbed is a SDR network for the collection of experimental data. The development of tools for network maintenance and data collection is presented and discussed. A novel recursive weighted centroid algorithm for device-free target localization using the variance of received signal strength for wireless links is proposed. The signal variance resulting from a moving target is modeled as having contours related to Cassini ovals. This model is used to formulate recursive weights which reduce the influence of wireless links that are farther from the target location estimate. The algorithm and its implementation on this testbed are presented and experimental results discussed.

Scanning microwave microscopy applied to semiconducting GaAs structures

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Buchter, Arne; Hoffmann, Johannes; Delvallée, Alexandra; Brinciotti, Enrico; Hapiuk, Dimitri; Licitra, Christophe; Louarn, Kevin; Arnoult, Alexandre; Almuneau, Guilhem; Piquemal, François; Zeier, Markus; Kienberger, Ferry

2018-02-01

A calibration algorithm based on one-port vector network analyzer (VNA) calibration for scanning microwave microscopes (SMMs) is presented and used to extract quantitative carrier densities from a semiconducting n-doped GaAs multilayer sample. This robust and versatile algorithm is instrument and frequency independent, as we demonstrate by analyzing experimental data from two different, cantilever- and tuning fork-based, microscope setups operating in a wide frequency range up to 27.5 GHz. To benchmark the SMM results, comparison with secondary ion mass spectrometry is undertaken. Furthermore, we show SMM data on a GaAs p-n junction distinguishing p- and n-doped layers.

Comparing Models GRM, Refraction Tomography and Neural Network to Analyze Shallow Landslide

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Armstrong F. Sompotan

2011-11-01

Full Text Available Detailed investigations of landslides are essential to understand fundamental landslide mechanisms. Seismic refraction method has been proven as a useful geophysical tool for investigating shallow landslides. The objective of this study is to introduce a new workflow using neural network in analyzing seismic refraction data and to compare the result with some methods; that are general reciprocal method (GRM and refraction tomography. The GRM is effective when the velocity structure is relatively simple and refractors are gently dipping. Refraction tomography is capable of modeling the complex velocity structures of landslides. Neural network is found to be more potential in application especially in time consuming and complicated numerical methods. Neural network seem to have the ability to establish a relationship between an input and output space for mapping seismic velocity. Therefore, we made a preliminary attempt to evaluate the applicability of neural network to determine velocity and elevation of subsurface synthetic models corresponding to arrival times. The training and testing process of the neural network is successfully accomplished using the synthetic data. Furthermore, we evaluated the neural network using observed data. The result of the evaluation indicates that the neural network can compute velocity and elevation corresponding to arrival times. The similarity of those models shows the success of neural network as a new alternative in seismic refraction data interpretation.

Analyzing phase diagrams and phase transitions in networked competing populations

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Ni, Y.-C.; Yin, H. P.; Xu, C.; Hui, P. M.

2011-03-01

Phase diagrams exhibiting the extent of cooperation in an evolutionary snowdrift game implemented in different networks are studied in detail. We invoke two independent payoff parameters, unlike a single payoff often used in most previous works that restricts the two payoffs to vary in a correlated way. In addition to the phase transition points when a single payoff parameter is used, phase boundaries separating homogeneous phases consisting of agents using the same strategy and a mixed phase consisting of agents using different strategies are found. Analytic expressions of the phase boundaries are obtained by invoking the ideas of the last surviving patterns and the relative alignments of the spectra of payoff values to agents using different strategies. In a Watts-Strogatz regular network, there exists a re-entrant phenomenon in which the system goes from a homogeneous phase into a mixed phase and re-enters the homogeneous phase as one of the two payoff parameters is varied. The non-trivial phase diagram accompanying this re-entrant phenomenon is quantitatively analyzed. The effects of noise and cooperation in randomly rewired Watts-Strogatz networks are also studied. The transition between a mixed phase and a homogeneous phase is identify to belong to the directed percolation universality class. The methods used in the present work are applicable to a wide range of problems in competing populations of networked agents.

Quasi-Optical Network Analyzers and High-Reliability RF MEMS Switched Capacitors

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Grichener, Alexander

The thesis first presents a 2-port quasi-optical scalar network analyzer consisting of a transmitter and receiver both built in planar technology. The network analyzer is based on a Schottky-diode mixer integrated inside a planar antenna and fed differentially by a CPW transmission line. The antenna is placed on an extended hemispherical high-resistivity silicon substrate lens. The LO signal is swept from 3-5 GHz and high-order harmonic mixing in both up- and down- conversion mode is used to realize the 15-50 GHz RF bandwidth. The network analyzer resulted in a dynamic range of greater than 40 dB and was successfully used to measure a frequency selective surface with a second-order bandpass response. Furthermore, the system was built with circuits and components for easy scaling to millimeter-wave frequencies which is the primary motivation for this work. The application areas for a millimeter and submillimeter-wave network analyzer include material characterization and art diagnostics. The second project presents several RF MEMS switched capacitors designed for high-reliability operation and suitable for tunable filters and reconfigurable networks. The first switched-capacitor resulted in a digital capacitance ratio of 5 and an analog capacitance ratio of 5-9. The analog tuning of the down-state capacitance is enhanced by a positive vertical stress gradient in the the beam, making it ideal for applications that require precision tuning. A thick electroplated beam resulted in Q greater than 100 at C to X-band frequencies, and power handling of 0.6-1.1 W. The design also minimized charging in the dielectric, resulting in excellent reliability performance even under hot-switched and high power (1 W) conditions. The second switched-capacitor was designed without any dielectric to minimize charging. The device was hot-switched at 1 W of RF power for greater than 11 billion cycles with virtually no change in the C-V curve. The final project presents a 7-channel

Analyzing the factors affecting network lifetime cluster-based wireless sensor network

International Nuclear Information System (INIS)

Malik, A.S.; Qureshi, A.

2010-01-01

Cluster-based wireless sensor networks enable the efficient utilization of the limited energy resources of the deployed sensor nodes and hence prolong the node as well as network lifetime. Low Energy Adaptive Clustering Hierarchy (Leach) is one of the most promising clustering protocol proposed for wireless sensor networks. This paper provides the energy utilization and lifetime analysis for cluster-based wireless sensor networks based upon LEACH protocol. Simulation results identify some important factors that induce unbalanced energy utilization between the sensor nodes and hence affect the network lifetime in these types of networks. These results highlight the need for a standardized, adaptive and distributed clustering technique that can increase the network lifetime by further balancing the energy utilization among sensor nodes. (author)

Analysis of Few-Mode Multi-Core Fiber Splice Behavior Using an Optical Vector Network Analyzer

DEFF Research Database (Denmark)

Rommel, Simon; Mendinueta, Jose Manuel Delgado; Klaus, Werner

2017-01-01

The behavior of splices in a 3-mode 36-core fiber is analyzed using optical vector network analysis. Time-domain response analysis confirms splices may cause significant mode-mixing, while frequency-domain analysis shows splices may affect system level mode-dependent loss both positively and negativ......The behavior of splices in a 3-mode 36-core fiber is analyzed using optical vector network analysis. Time-domain response analysis confirms splices may cause significant mode-mixing, while frequency-domain analysis shows splices may affect system level mode-dependent loss both positively...

Analyzing complex networks through correlations in centrality measurements

International Nuclear Information System (INIS)

Ricardo Furlan Ronqui, José; Travieso, Gonzalo

2015-01-01

Many real world systems can be expressed as complex networks of interconnected nodes. It is frequently important to be able to quantify the relative importance of the various nodes in the network, a task accomplished by defining some centrality measures, with different centrality definitions stressing different aspects of the network. It is interesting to know to what extent these different centrality definitions are related for different networks. In this work, we study the correlation between pairs of a set of centrality measures for different real world networks and two network models. We show that the centralities are in general correlated, but with stronger correlations for network models than for real networks. We also show that the strength of the correlation of each pair of centralities varies from network to network. Taking this fact into account, we propose the use of a centrality correlation profile, consisting of the values of the correlation coefficients between all pairs of centralities of interest, as a way to characterize networks. Using the yeast protein interaction network as an example we show also that the centrality correlation profile can be used to assess the adequacy of a network model as a representation of a given real network. (paper)

Analyzing self-similar and fractal properties of the C. elegans neural network.

Directory of Open Access Journals (Sweden)

Tyler M Reese

Full Text Available The brain is one of the most studied and highly complex systems in the biological world. While much research has concentrated on studying the brain directly, our focus is the structure of the brain itself: at its core an interconnected network of nodes (neurons. A better understanding of the structural connectivity of the brain should elucidate some of its functional properties. In this paper we analyze the connectome of the nematode Caenorhabditis elegans. Consisting of only 302 neurons, it is one of the better-understood neural networks. Using a Laplacian Matrix of the 279-neuron "giant component" of the network, we use an eigenvalue counting function to look for fractal-like self similarity. This matrix representation is also used to plot visualizations of the neural network in eigenfunction coordinates. Small-world properties of the system are examined, including average path length and clustering coefficient. We test for localization of eigenfunctions, using graph energy and spacial variance on these functions. To better understand results, all calculations are also performed on random networks, branching trees, and known fractals, as well as fractals which have been "rewired" to have small-world properties. We propose algorithms for generating Laplacian matrices of each of these graphs.

Building and analyzing protein interactome networks by cross-species comparisons

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Blackman Barron

2010-03-01

Full Text Available Abstract Background A genomic catalogue of protein-protein interactions is a rich source of information, particularly for exploring the relationships between proteins. Numerous systems-wide and small-scale experiments have been conducted to identify interactions; however, our knowledge of all interactions for any one species is incomplete, and alternative means to expand these network maps is needed. We therefore took a comparative biology approach to predict protein-protein interactions across five species (human, mouse, fly, worm, and yeast and developed InterologFinder for research biologists to easily navigate this data. We also developed a confidence score for interactions based on available experimental evidence and conservation across species. Results The connectivity of the resultant networks was determined to have scale-free distribution, small-world properties, and increased local modularity, indicating that the added interactions do not disrupt our current understanding of protein network structures. We show examples of how these improved interactomes can be used to analyze a genome-scale dataset (RNAi screen and to assign new function to proteins. Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced. Conclusions Protein-protein interactions were predicted in five species, based on orthology. An InteroScore, a score accounting for homology, number of orthologues with evidence of interactions, and number of unique observations of interactions, is given to each known and predicted interaction. Our website http://www.interologfinder.org provides research biologists intuitive access to this data.

Identifying and Analyzing Strong Components of an Industrial Network Based on Cycle Degree

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Zhiying Zhang

2016-01-01

Full Text Available In the era of big data and cloud computing, data research focuses not only on describing the individual characteristics but also on depicting the relationships among individuals. Studying dependence and constraint relationships among industries has aroused significant interest in the academic field. From the network perspective, this paper tries to analyze industrial relational structures based on cycle degree. The cycle degree of a vertex, that is, the number of cycles through a vertex in an industrial network, can describe the roles of the vertices of strong components in industrial circulation. In most cases, different vertices in a strong component have different cycle degrees, and the one with a larger cycle degree plays more important roles. However, the concept of cycle degree does not involve the lengths of the cycles, which are also important for circulations. The more indirect the relationship between two industries is, the weaker it is. In order to analyze strong components thoroughly, this paper proposes the concept of circular centrality taking into consideration the influence by two factors: the lengths and the numbers of cycles through a vertex. Exemplification indicates that a profound analysis of strong components in an industrial network can reveal the features of an economy.

A Network Approach to Analyzing Highly Recombinant Malaria Parasite Genes

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Larremore, Daniel B.; Clauset, Aaron; Buckee, Caroline O.

2013-01-01

The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences. PMID:24130474

A network approach to analyzing highly recombinant malaria parasite genes.

Science.gov (United States)

Larremore, Daniel B; Clauset, Aaron; Buckee, Caroline O

2013-01-01

The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs), and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα) domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences.

A network approach to analyzing highly recombinant malaria parasite genes.

Directory of Open Access Journals (Sweden)

Daniel B Larremore

Full Text Available The var genes of the human malaria parasite Plasmodium falciparum present a challenge to population geneticists due to their extreme diversity, which is generated by high rates of recombination. These genes encode a primary antigen protein called PfEMP1, which is expressed on the surface of infected red blood cells and elicits protective immune responses. Var gene sequences are characterized by pronounced mosaicism, precluding the use of traditional phylogenetic tools that require bifurcating tree-like evolutionary relationships. We present a new method that identifies highly variable regions (HVRs, and then maps each HVR to a complex network in which each sequence is a node and two nodes are linked if they share an exact match of significant length. Here, networks of var genes that recombine freely are expected to have a uniformly random structure, but constraints on recombination will produce network communities that we identify using a stochastic block model. We validate this method on synthetic data, showing that it correctly recovers populations of constrained recombination, before applying it to the Duffy Binding Like-α (DBLα domain of var genes. We find nine HVRs whose network communities map in distinctive ways to known DBLα classifications and clinical phenotypes. We show that the recombinational constraints of some HVRs are correlated, while others are independent. These findings suggest that this micromodular structuring facilitates independent evolutionary trajectories of neighboring mosaic regions, allowing the parasite to retain protein function while generating enormous sequence diversity. Our approach therefore offers a rigorous method for analyzing evolutionary constraints in var genes, and is also flexible enough to be easily applied more generally to any highly recombinant sequences.

A deep convolutional neural network to analyze position averaged convergent beam electron diffraction patterns.

Science.gov (United States)

Xu, W; LeBeau, J M

2018-05-01

We establish a series of deep convolutional neural networks to automatically analyze position averaged convergent beam electron diffraction patterns. The networks first calibrate the zero-order disk size, center position, and rotation without the need for pretreating the data. With the aligned data, additional networks then measure the sample thickness and tilt. The performance of the network is explored as a function of a variety of variables including thickness, tilt, and dose. A methodology to explore the response of the neural network to various pattern features is also presented. Processing patterns at a rate of  ∼ 0.1 s/pattern, the network is shown to be orders of magnitude faster than a brute force method while maintaining accuracy. The approach is thus suitable for automatically processing big, 4D STEM data. We also discuss the generality of the method to other materials/orientations as well as a hybrid approach that combines the features of the neural network with least squares fitting for even more robust analysis. The source code is available at https://github.com/subangstrom/DeepDiffraction. Copyright © 2018 Elsevier B.V. All rights reserved.

One-port portable SAW sensor system

Science.gov (United States)

Hoa Nguyen, Vu; Peters, Oliver; Schnakenberg, Uwe

2018-01-01

A portable device using the SAW-based impedance sensor type based on one interdigital transducer simultaneously as SAW generator and sensor element (1-port approach) is introduced. As a novelty, the so far required expensive vector network analyzer (VNA) is replaced by a hand-held device to measure the impedance spectrum of the SAW sensor by RF-gain-phase meters. Hence, some of the best features from the conventional oscillator and VNA approaches are combined to develop a low-cost and self-contained measurement system, including signal in- and output ability for real-time measurements. The pivotal aspect of the portable system is the transfer of the sophisticated high frequency approach into a quasi-static one. This enables the use of simple lumped electronics without the need of impedance matching circuits. Proof-of-concept was carried out by measuring conductivities of phosphate-buffered solutions and viscosities of glycerin. Sensitivities for temperature of 0.3%/°C, viscosity of 10.1% (mPa s)-1 and conductivity of 0.5% (S cm)-1 have been determined, respectively, which are competitive results compared to the benchmark approaches.

Analyzing the causation of a railway accident based on a complex network

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Ma, Xin; Li, Ke-Ping; Luo, Zi-Yan; Zhou, Jin

2014-02-01

In this paper, a new model is constructed for the causation analysis of railway accident based on the complex network theory. In the model, the nodes are defined as various manifest or latent accident causal factors. By employing the complex network theory, especially its statistical indicators, the railway accident as well as its key causations can be analyzed from the overall perspective. As a case, the “7.23” China—Yongwen railway accident is illustrated based on this model. The results show that the inspection of signals and the checking of line conditions before trains run played an important role in this railway accident. In conclusion, the constructed model gives a theoretical clue for railway accident prediction and, hence, greatly reduces the occurrence of railway accidents.

Optical vector network analyzer based on double-sideband modulation.

Science.gov (United States)

Jun, Wen; Wang, Ling; Yang, Chengwu; Li, Ming; Zhu, Ning Hua; Guo, Jinjin; Xiong, Liangming; Li, Wei

2017-11-01

We report an optical vector network analyzer (OVNA) based on double-sideband (DSB) modulation using a dual-parallel Mach-Zehnder modulator. The device under test (DUT) is measured twice with different modulation schemes. By post-processing the measurement results, the response of the DUT can be obtained accurately. Since DSB modulation is used in our approach, the measurement range is doubled compared with conventional single-sideband (SSB) modulation-based OVNA. Moreover, the measurement accuracy is improved by eliminating the even-order sidebands. The key advantage of the proposed scheme is that the measurement of a DUT with bandpass response can also be simply realized, which is a big challenge for the SSB-based OVNA. The proposed method is theoretically and experimentally demonstrated.

When the Web meets the cell: using personalized PageRank for analyzing protein interaction networks.

Science.gov (United States)

Iván, Gábor; Grolmusz, Vince

2011-02-01

Enormous and constantly increasing quantity of biological information is represented in metabolic and in protein interaction network databases. Most of these data are freely accessible through large public depositories. The robust analysis of these resources needs novel technologies, being developed today. Here we demonstrate a technique, originating from the PageRank computation for the World Wide Web, for analyzing large interaction networks. The method is fast, scalable and robust, and its capabilities are demonstrated on metabolic network data of the tuberculosis bacterium and the proteomics analysis of the blood of melanoma patients. The Perl script for computing the personalized PageRank in protein networks is available for non-profit research applications (together with sample input files) at the address: http://uratim.com/pp.zip.

Analyzing the effect of introducing a kurtosis parameter in Gaussian Bayesian networks

International Nuclear Information System (INIS)

Main, P.; Navarro, H.

2009-01-01

Gaussian Bayesian networks are graphical models that represent the dependence structure of a multivariate normal random variable with a directed acyclic graph (DAG). In Gaussian Bayesian networks the output is usually the conditional distribution of some unknown variables of interest given a set of evidential nodes whose values are known. The problem of uncertainty about the assumption of normality is very common in applications. Thus a sensitivity analysis of the non-normality effect in our conclusions could be necessary. The aspect of non-normality to be considered is the tail behavior. In this line, the multivariate exponential power distribution is a family depending on a kurtosis parameter that goes from a leptokurtic to a platykurtic distribution with the normal as a mesokurtic distribution. Therefore a more general model can be considered using the multivariate exponential power distribution to describe the joint distribution of a Bayesian network, with a kurtosis parameter reflecting deviations from the normal distribution. The sensitivity of the conclusions to this perturbation is analyzed using the Kullback-Leibler divergence measure that provides an interesting formula to evaluate the effect

Analyzing the effect of introducing a kurtosis parameter in Gaussian Bayesian networks

Energy Technology Data Exchange (ETDEWEB)

Main, P. [Dpto. Estadistica e I.O., Fac. Ciencias Matematicas, Univ. Complutense de Madrid, 28040 Madrid (Spain)], E-mail: pmain@mat.ucm.es; Navarro, H. [Dpto. de Estadistica, I.O. y Calc. Numerico, Fac. Ciencias, UNED, 28040 Madrid (Spain)

2009-05-15

Gaussian Bayesian networks are graphical models that represent the dependence structure of a multivariate normal random variable with a directed acyclic graph (DAG). In Gaussian Bayesian networks the output is usually the conditional distribution of some unknown variables of interest given a set of evidential nodes whose values are known. The problem of uncertainty about the assumption of normality is very common in applications. Thus a sensitivity analysis of the non-normality effect in our conclusions could be necessary. The aspect of non-normality to be considered is the tail behavior. In this line, the multivariate exponential power distribution is a family depending on a kurtosis parameter that goes from a leptokurtic to a platykurtic distribution with the normal as a mesokurtic distribution. Therefore a more general model can be considered using the multivariate exponential power distribution to describe the joint distribution of a Bayesian network, with a kurtosis parameter reflecting deviations from the normal distribution. The sensitivity of the conclusions to this perturbation is analyzed using the Kullback-Leibler divergence measure that provides an interesting formula to evaluate the effect.

Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks.

Directory of Open Access Journals (Sweden)

Xiaoke Ma

2015-06-01

Full Text Available Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways. Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment. Currently, there is a lack of computational methods that enable analysis of multiple gene networks, each of which exhibits differential activity compared to the network of the baseline/healthy condition. We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks, termed M-DMs (multiple differential modules. We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes. We showed that iMDM achieves higher accuracy in inferring gene modules compared to using single or multiple co-expression networks. We found that condition-specific M-DMs exhibit differential activities, mediate different biological processes, and are enriched for genes with known cardiovascular phenotypes. By analyzing M-DMs that are present in multiple conditions, we revealed dynamic changes in pathway activity and connectivity across heart failure conditions. We further showed that module dynamics were correlated with the dynamics of disease phenotypes during the development of heart failure. Thus, pathway dynamics is a powerful measure for understanding pathogenesis. iMDM provides a principled way to dissect the dynamics of gene pathways and its relationship to the dynamics of disease phenotype. With the exponential growth of omics data, our method can aid in generating systems-level insights into disease progression.

Analyzing the causation of a railway accident based on a complex network

International Nuclear Information System (INIS)

Ma Xin; Li Ke-Ping; Luo Zi-Yan; Zhou Jin

2014-01-01

In this paper, a new model is constructed for the causation analysis of railway accident based on the complex network theory. In the model, the nodes are defined as various manifest or latent accident causal factors. By employing the complex network theory, especially its statistical indicators, the railway accident as well as its key causations can be analyzed from the overall perspective. As a case, the “7.23” China—Yongwen railway accident is illustrated based on this model. The results show that the inspection of signals and the checking of line conditions before trains run played an important role in this railway accident. In conclusion, the constructed model gives a theoretical clue for railway accident prediction and, hence, greatly reduces the occurrence of railway accidents. (interdisciplinary physics and related areas of science and technology)

Optimization of the kernel functions in a probabilistic neural network analyzing the local pattern distribution.

Science.gov (United States)

Galleske, I; Castellanos, J

2002-05-01

This article proposes a procedure for the automatic determination of the elements of the covariance matrix of the gaussian kernel function of probabilistic neural networks. Two matrices, a rotation matrix and a matrix of variances, can be calculated by analyzing the local environment of each training pattern. The combination of them will form the covariance matrix of each training pattern. This automation has two advantages: First, it will free the neural network designer from indicating the complete covariance matrix, and second, it will result in a network with better generalization ability than the original model. A variation of the famous two-spiral problem and real-world examples from the UCI Machine Learning Repository will show a classification rate not only better than the original probabilistic neural network but also that this model can outperform other well-known classification techniques.

How Unstable Are Complex Financial Systems? Analyzing an Inter-bank Network of Credit Relations

Science.gov (United States)

Sinha, Sitabhra; Thess, Maximilian; Markose, Sheri

The recent worldwide economic crisis of 2007-09 has focused attention on the need to analyze systemic risk in complex financial networks. We investigate the problem of robustness of such systems in the context of the general theory of dynamical stability in complex networks and, in particular, how the topology of connections influence the risk of the failure of a single institution triggering a cascade of successive collapses propagating through the network. We use data on bilateral liabilities (or exposure) in the derivatives market between 202 financial intermediaries based in USA and Europe in the last quarter of 2009 to empirically investigate the network structure of the over-the-counter (OTC) derivatives market. We observe that the network exhibits both heterogeneity in node properties and the existence of communities. It also has a prominent core-periphery organization and can resist large-scale collapse when subjected to individual bank defaults (however, failure of any bank in the core may result in localized collapse of the innermost core with substantial loss of capital) but is vulnerable to system-wide breakdown as a result of an accompanying liquidity crisis.

Random matrix theory for analyzing the brain functional network in attention deficit hyperactivity disorder

Science.gov (United States)

Wang, Rong; Wang, Li; Yang, Yong; Li, Jiajia; Wu, Ying; Lin, Pan

2016-11-01

Attention deficit hyperactivity disorder (ADHD) is the most common childhood neuropsychiatric disorder and affects approximately 6 -7 % of children worldwide. Here, we investigate the statistical properties of undirected and directed brain functional networks in ADHD patients based on random matrix theory (RMT), in which the undirected functional connectivity is constructed based on correlation coefficient and the directed functional connectivity is measured based on cross-correlation coefficient and mutual information. We first analyze the functional connectivity and the eigenvalues of the brain functional network. We find that ADHD patients have increased undirected functional connectivity, reflecting a higher degree of linear dependence between regions, and increased directed functional connectivity, indicating stronger causality and more transmission of information among brain regions. More importantly, we explore the randomness of the undirected and directed functional networks using RMT. We find that for ADHD patients, the undirected functional network is more orderly than that for normal subjects, which indicates an abnormal increase in undirected functional connectivity. In addition, we find that the directed functional networks are more random, which reveals greater disorder in causality and more chaotic information flow among brain regions in ADHD patients. Our results not only further confirm the efficacy of RMT in characterizing the intrinsic properties of brain functional networks but also provide insights into the possibilities RMT offers for improving clinical diagnoses and treatment evaluations for ADHD patients.

A network centrality measure framework for analyzing urban traffic flow: A case study of Wuhan, China

Science.gov (United States)

Zhao, Shuangming; Zhao, Pengxiang; Cui, Yunfan

2017-07-01

In this paper, we propose an improved network centrality measure framework that takes into account both the topological characteristics and the geometric properties of a road network in order to analyze urban traffic flow in relation to different modes: intersection, road, and community, which correspond to point mode, line mode, and area mode respectively. Degree, betweenness, and PageRank centralities are selected as the analysis measures, and GPS-enabled taxi trajectory data is used to evaluate urban traffic flow. The results show that the mean value of the correlation coefficients between the modified degree, the betweenness, and the PageRank centralities and the traffic flow in all periods are higher than the mean value of the correlation coefficients between the conventional degree, the betweenness, the PageRank centralities and the traffic flow at different modes; this indicates that the modified measurements, for analyzing traffic flow, are superior to conventional centrality measurements. This study helps to shed light into the understanding of urban traffic flow in relation to different modes from the perspective of complex networks.

Analyzing Evolving Social Network 2 (EVOLVE2)

Science.gov (United States)

2015-04-01

WORK UNIT NUMBER N2 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) University of Southern California 3720 S. Flower Street, Third Floor Los...score, and resource allocation. Below the double line are link prediction heuristics introduced in this paper. name symbol definition common neighbors...LIST OF SYMBOLS , ABBREVIATIONS AND ACRONYMS A adjacency matrix of a network D diagonal out-degree matrix DW out-degree matrix of the reweighted network

Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks

Directory of Open Access Journals (Sweden)

Kirouac Daniel C

2012-05-01

Full Text Available Abstract Background Understanding the information-processing capabilities of signal transduction networks, how those networks are disrupted in disease, and rationally designing therapies to manipulate diseased states require systematic and accurate reconstruction of network topology. Data on networks central to human physiology, such as the inflammatory signalling networks analyzed here, are found in a multiplicity of on-line resources of pathway and interactome databases (Cancer CellMap, GeneGo, KEGG, NCI-Pathway Interactome Database (NCI-PID, PANTHER, Reactome, I2D, and STRING. We sought to determine whether these databases contain overlapping information and whether they can be used to construct high reliability prior knowledge networks for subsequent modeling of experimental data. Results We have assembled an ensemble network from multiple on-line sources representing a significant portion of all machine-readable and reconcilable human knowledge on proteins and protein interactions involved in inflammation. This ensemble network has many features expected of complex signalling networks assembled from high-throughput data: a power law distribution of both node degree and edge annotations, and topological features of a “bow tie” architecture in which diverse pathways converge on a highly conserved set of enzymatic cascades focused around PI3K/AKT, MAPK/ERK, JAK/STAT, NFκB, and apoptotic signaling. Individual pathways exhibit “fuzzy” modularity that is statistically significant but still involving a majority of “cross-talk” interactions. However, we find that the most widely used pathway databases are highly inconsistent with respect to the actual constituents and interactions in this network. Using a set of growth factor signalling networks as examples (epidermal growth factor, transforming growth factor-beta, tumor necrosis factor, and wingless, we find a multiplicity of network topologies in which receptors couple to downstream

Identify and analyze the opportunities and threats of social networks for shahid Beheshti University students

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R. Tavalaee

2017-09-01

Full Text Available Due to the growth of information and communication technology in societies Especially among students, the use of these technologies has become as part of regular working people. Social networks as one of the most important and widely in cyberspace which is Used by many people in various fields. application of social network by students as young and educated population is important.In this regard, this study aimed to investigate and identify the opportunities and threats for shahid Beheshti University students in social network. This study aims to develop a practical and descriptive methodology. Information obtained from the questionnaires using SPSS statistical analysis software in two parts: descriptive and inferential statistics were analyzed.The results indicate that five variables related to social networking opportunities, including e-learning, leisure, organized social groups, the possibility of dialogue and culture, as well as five variables related to social networking threats, including transfer value unethical, abusive, spreading false information, internet & Communications destructive addiction, has a significant positive effect on students.

Optical vector network analyzer with improved accuracy based on polarization modulation and polarization pulling.

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Li, Wei; Liu, Jian Guo; Zhu, Ning Hua

2015-04-15

We report a novel optical vector network analyzer (OVNA) with improved accuracy based on polarization modulation and stimulated Brillouin scattering (SBS) assisted polarization pulling. The beating between adjacent higher-order optical sidebands which are generated because of the nonlinearity of an electro-optic modulator (EOM) introduces considerable error to the OVNA. In our scheme, the measurement error is significantly reduced by removing the even-order optical sidebands using polarization discrimination. The proposed approach is theoretically analyzed and experimentally verified. The experimental results show that the accuracy of the OVNA is greatly improved compared to a conventional OVNA.

Towards a theoretical framework for analyzing complex linguistic networks

CERN Document Server

Lücking, Andy; Banisch, Sven; Blanchard, Philippe; Job, Barbara

2016-01-01

The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities.This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statisticalmodels of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information scien...

Biana: a software framework for compiling biological interactions and analyzing networks.

Science.gov (United States)

Garcia-Garcia, Javier; Guney, Emre; Aragues, Ramon; Planas-Iglesias, Joan; Oliva, Baldo

2010-01-27

The analysis and usage of biological data is hindered by the spread of information across multiple repositories and the difficulties posed by different nomenclature systems and storage formats. In particular, there is an important need for data unification in the study and use of protein-protein interactions. Without good integration strategies, it is difficult to analyze the whole set of available data and its properties. We introduce BIANA (Biologic Interactions and Network Analysis), a tool for biological information integration and network management. BIANA is a Python framework designed to achieve two major goals: i) the integration of multiple sources of biological information, including biological entities and their relationships, and ii) the management of biological information as a network where entities are nodes and relationships are edges. Moreover, BIANA uses properties of proteins and genes to infer latent biomolecular relationships by transferring edges to entities sharing similar properties. BIANA is also provided as a plugin for Cytoscape, which allows users to visualize and interactively manage the data. A web interface to BIANA providing basic functionalities is also available. The software can be downloaded under GNU GPL license from http://sbi.imim.es/web/BIANA.php. BIANA's approach to data unification solves many of the nomenclature issues common to systems dealing with biological data. BIANA can easily be extended to handle new specific data repositories and new specific data types. The unification protocol allows BIANA to be a flexible tool suitable for different user requirements: non-expert users can use a suggested unification protocol while expert users can define their own specific unification rules.

A queueing network model to analyze the impact of parallelization of care on patient cycle time.

Science.gov (United States)

Jiang, Lixiang; Giachetti, Ronald E

2008-09-01

The total time a patient spends in an outpatient facility, called the patient cycle time, is a major contributor to overall patient satisfaction. A frequently recommended strategy to reduce the total time is to perform some activities in parallel thereby shortening patient cycle time. To analyze patient cycle time this paper extends and improves upon existing multi-class open queueing network model (MOQN) so that the patient flow in an urgent care center can be modeled. Results of the model are analyzed using data from an urgent care center contemplating greater parallelization of patient care activities. The results indicate that parallelization can reduce the cycle time for those patient classes which require more than one diagnostic and/ or treatment intervention. However, for many patient classes there would be little if any improvement, indicating the importance of tools to analyze business process reengineering rules. The paper makes contributions by implementing an approximation for fork/join queues in the network and by improving the approximation for multiple server queues in both low traffic and high traffic conditions. We demonstrate the accuracy of the MOQN results through comparisons to simulation results.

Social network analyzer on the example of Twitter

Science.gov (United States)

Gorodetskaia, Mariia; Khruslova, Diana

2017-09-01

Social networks are powerful sources of data due to their popularity. Twitter is one of the networks providing a lot of data. There is need to collect this data for future usage from linguistics to SMM and marketing. The report examines the existing software solutions and provides new ones. The study includes information about the software developed. Some future features are listed.

Improved equivalent magnetic network modeling for analyzing working points of PMs in interior permanent magnet machine

Science.gov (United States)

Guo, Liyan; Xia, Changliang; Wang, Huimin; Wang, Zhiqiang; Shi, Tingna

2018-05-01

As is well known, the armature current will be ahead of the back electromotive force (back-EMF) under load condition of the interior permanent magnet (PM) machine. This kind of advanced armature current will produce a demagnetizing field, which may make irreversible demagnetization appeared in PMs easily. To estimate the working points of PMs more accurately and take demagnetization under consideration in the early design stage of a machine, an improved equivalent magnetic network model is established in this paper. Each PM under each magnetic pole is segmented, and the networks in the rotor pole shoe are refined, which makes a more precise model of the flux path in the rotor pole shoe possible. The working point of each PM under each magnetic pole can be calculated accurately by the established improved equivalent magnetic network model. Meanwhile, the calculated results are compared with those calculated by FEM. And the effects of d-axis component and q-axis component of armature current, air-gap length and flux barrier size on working points of PMs are analyzed by the improved equivalent magnetic network model.

Presence of virus neutralizing antibodies in cerebral spinal fluid correlates with non-lethal rabies in dogs.

Directory of Open Access Journals (Sweden)

Clement W Gnanadurai

Full Text Available Rabies is traditionally considered a uniformly fatal disease after onset of clinical manifestations. However, increasing evidence indicates that non-lethal infection as well as recovery from flaccid paralysis and encephalitis occurs in laboratory animals as well as humans.Non-lethal rabies infection in dogs experimentally infected with wild type dog rabies virus (RABV, wt DRV-Mexico correlates with the presence of high level of virus neutralizing antibodies (VNA in the cerebral spinal fluid (CSF and mild immune cell accumulation in the central nervous system (CNS. By contrast, dogs that succumbed to rabies showed only little or no VNA in the serum or in the CSF and severe inflammation in the CNS. Dogs vaccinated with a rabies vaccine showed no clinical signs of rabies and survived challenge with a lethal dose of wild-type DRV. VNA was detected in the serum, but not in the CSF of immunized dogs. Thus the presence of VNA is critical for inhibiting virus spread within the CNS and eventually clearing the virus from the CNS.Non-lethal infection with wt RABV correlates with the presence of VNA in the CNS. Therefore production of VNA within the CNS or invasion of VNA from the periphery into the CNS via compromised blood-brain barrier is important for clearing the virus infection from CNS, thereby preventing an otherwise lethal rabies virus infection.

Analyzing Peace Pedagogies

Science.gov (United States)

Haavelsrud, Magnus; Stenberg, Oddbjorn

2012-01-01

Eleven articles on peace education published in the first volume of the Journal of Peace Education are analyzed. This selection comprises peace education programs that have been planned or carried out in different contexts. In analyzing peace pedagogies as proposed in the 11 contributions, we have chosen network analysis as our method--enabling…

Incorporation of Tin on copper clad laminate to increase the interface adhesion for signal loss reduction of high-frequency PCB lamination

Science.gov (United States)

Wang, Chong; Wen, Na; Zhou, Guoyun; Wang, Shouxu; He, Wei; Su, Xinhong; Hu, Yongsuan

2017-11-01

A novel method of improving the adhesion between copper and prepreg in high frequency PCB was proposed and studied in this work. This process which aimed to decrease the IEP (isoelectric point) of the copper to obtain higher adhesion, was achieved by depositing a thin tin layer with lower IEP on copper. It was characterized by scanning electron microscopy (SEM), 3D microscope, peel strength test, X-Ray thickness test, grazing incidence X-ray diffraction (GXRD), X-ray photoelectron spectroscopy (XPS), Agilent vector network analyzer (VNA), which confirmed its excellent adhesion performance and outstanding electrical properties in high-frequency signal transmission compared with traditional brown oxide method. Moreover, the mechanism of achieving high adhesion for this method was also investigated.

Hardware Realization of an Ethernet Packet Analyzer Search Engine

Science.gov (United States)

2000-06-30

specific for the home automation industry. This analyzer will be at the gateway of a network and analyze Ethernet packets as they go by. It will keep... home automation and not the computer network. This system is a stand-alone real-time network analyzer capable of decoding Ethernet protocols. The

An Artificial Neural Network for Analyzing Overall Uniformity in Outdoor Lighting Systems

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Antonio del Corte-Valiente

2017-02-01

Full Text Available Street lighting installations are an essential service for modern life due to their capability of creating a welcoming feeling at nighttime. Nevertheless, several studies have highlighted that it is possible to improve the quality of the light significantly improving the uniformity of the illuminance. The main difficulty arises when trying to improve some of the installation’s characteristics based only on statistical analysis of the light distribution. This paper presents a new algorithm that is able to obtain the overall illuminance uniformity in order to improve this sort of installations. To develop this algorithm it was necessary to perform a detailed study of all the elements which are part of street lighting installations. Because classification is one of the most important tasks in the application areas of artificial neural networks, we compared the performances of six types of training algorithms in a feed forward neural network for analyzing the overall uniformity in outdoor lighting systems. We found that the best algorithm that minimizes the error is “Levenberg-Marquardt back-propagation”, which approximates the desired output of the training pattern. By means of this kind of algorithm, it is possible to help to lighting professionals optimize the quality of street lighting installations.

Development of new process network for gas chromatograph and analyzers connected with SCADA system and Digital Control Computers at Cernavoda NPP Unit 1

International Nuclear Information System (INIS)

Deneanu, Cornel; Popa Nemoiu, Dragos; Nica, Dana; Bucur, Cosmin

2007-01-01

The continuous monitoring of gas mixture concentrations (deuterium/ hydrogen/oxygen/nitrogen) accumulated in 'Moderator Cover Gas', 'Liquid Control Zone' and 'Heat Transport D 2 O Storage Tank Cover Gas', as well as the continuous monitoring of Heavy Water into Light Water concentration in 'Boilers Steam', 'Boilers Blown Down', 'Moderator heat exchangers', and 'Recirculated Water System', sensing any leaks of Cernavoda NPP U1 led to requirement of developing a new process network for gas chromatograph and analyzers connected to the SCADA system and Digital Control Computers of Cernavoda NPP Unit 1. In 2005 it was designed and implemented the process network for gas chromatograph which connected the gas chromatograph equipment to the SCADA system and Digital Control Computers of the Cernavoda NPP Unit 1. Later this process network for gas chromatograph has been extended to connect the AE13 and AE14 Fourier Transform Infrared (FTIR) analyzers with either. The Gas Chromatograph equipment measures with best accuracy the mixture gases (deuterium/ hydrogen/oxygen/nitrogen) concentration. The Fourier Transform Infrared (FTIR) AE13 and AE14 Analyzers measure the Heavy Water into Light Water concentration in Boilers Steam, Boilers BlownDown, Moderator heat exchangers, and Recirculated Water System, monitoring and signaling any leaks. The Gas Chromatograph equipment and Fourier Transform Infrared (FTIR) AE13 and AE14 Analyzers use the new OPC (Object Link Embedded for Process Control) technologies available in ABB's VistaNet network for interoperability with automation equipment. This new process network has interconnected the ABB chromatograph and Fourier Transform Infrared analyzers with plant Digital Control Computers using new technology. The result was an increased reliability and capability for inspection and improved system safety

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

Science.gov (United States)

Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R

2012-01-01

In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

GAT: a graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks.

Directory of Open Access Journals (Sweden)

S M Hadi Hosseini

Full Text Available In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC and functional data analyses (FDA, in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL and healthy matched Controls (CON. The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.

ATHENA [Advanced Thermal Hydraulic Energy Network Analyzer] solutions to developmental assessment problems

International Nuclear Information System (INIS)

Carlson, K.E.; Ransom, V.H.; Roth, P.A.

1987-03-01

The ATHENA (Advanced Thermal Hydraulic Energy Network Analyzer) code has been developed to perform transient simulation of the thermal hydraulic systems that may be found in fusion reactors, space reactors, and other advanced systems. As an assessment of current capability the code was applied to a number of physical problems, both conceptual and actual experiments. Results indicate that the numerical solution to the basic conservation equations is technically sound, and that generally good agreement can be obtained when modeling relevant hydrodynamic experiments. The assessment also demonstrates basic fusion system modeling capability and verifies compatibility of the code with both CDC and CRAY mainframes. Areas where improvements could be made include constitutive modeling, which describes the interfacial exchange term. 13 refs., 84 figs

Framework based on communicability and flow to analyze complex network dynamics

Science.gov (United States)

Gilson, M.; Kouvaris, N. E.; Deco, G.; Zamora-López, G.

2018-05-01

Graph theory constitutes a widely used and established field providing powerful tools for the characterization of complex networks. The intricate topology of networks can also be investigated by means of the collective dynamics observed in the interactions of self-sustained oscillations (synchronization patterns) or propagationlike processes such as random walks. However, networks are often inferred from real-data-forming dynamic systems, which are different from those employed to reveal their topological characteristics. This stresses the necessity for a theoretical framework dedicated to the mutual relationship between the structure and dynamics in complex networks, as the two sides of the same coin. Here we propose a rigorous framework based on the network response over time (i.e., Green function) to study interactions between nodes across time. For this purpose we define the flow that describes the interplay between the network connectivity and external inputs. This multivariate measure relates to the concepts of graph communicability and the map equation. We illustrate our theory using the multivariate Ornstein-Uhlenbeck process, which describes stable and non-conservative dynamics, but the formalism can be adapted to other local dynamics for which the Green function is known. We provide applications to classical network examples, such as small-world ring and hierarchical networks. Our theory defines a comprehensive framework that is canonically related to directed and weighted networks, thus paving a way to revise the standards for network analysis, from the pairwise interactions between nodes to the global properties of networks including community detection.

Cisco Router and Switch Forensics Investigating and Analyzing Malicious Network Activity

CERN Document Server

Liu, Dale

2009-01-01

Cisco IOS (the software that runs the vast majority of Cisco routers and all Cisco network switches) is the dominant routing platform on the Internet and corporate networks. This widespread distribution, as well as its architectural deficiencies, makes it a valuable target for hackers looking to attack a corporate or private network infrastructure. Compromised devices can disrupt stability, introduce malicious modification, and endanger all communication on the network. For security of the network and investigation of attacks, in-depth analysis and diagnostics are critical, but no book current

Polycrystalline V2O5/Na0.33V2O5 electrode material for Li+ ion redox supercapacitor

International Nuclear Information System (INIS)

Manikandan, Ramu; Justin Raj, C.; Rajesh, Murugesan; Kim, Byung Chul; Park, Sang Yeup; Cho, Bo-Bae; Yu, Kook Hyun

2017-01-01

Highlights: • Different polycrystalline V 2 O 5 /Na 0.33 V 2 O 5 nanostructures were synthesized via simple co-precipitation technique. • The various molar ratios of NaOH precipitator determine the morphology, structural and electrochemical properties of V/Na. • The equimolar ratio of reactant and precipitator shows the formation of ∼96% of pure crystalline phase of V 2 O 5 . • Li + ions intercalation and deintercalation process enhanced the specific capacitance. - Abstract: This work essentially offers a new kind of V 2 O 5 /Na 0.33 V 2 O 5 as electrochemical active material for the development of Li + ion redox supercapacitors. Here, polycrystalline mixed phase of V 2 O 5 /Na 0.33 V 2 O 5 (V/Na) nanostructures are synthesized via simple co-precipitation technique. The various molar ratio of precipitator (NaOH) in the synthesis process displays different nanostructures of V/Na. The structural and morphological properties of V/Na samples are studied using physico-chemical analysis methods. The electrochemical properties of V/Na nanostructured samples are performed using cyclic voltammetry, galvanostatic charge/discharge test and electrochemical impedance spectroscopy techniques in 1 M LiClO 4 aqueous electrolyte. The sample V/Na synthesized using equimolar ratio of vanadium salt and precipitator displayed nanopellet morphology, which exhibited the highest capacitance value of 334 Fg −1 at 1 Ag −1 discharge current density. Moreover, these polycrystalline V/Na nanostructured electrodes show excellent electrochemical properties with comparable stability after 1000 charge/discharge cycles.

Singular value decomposition and artificial neutral network for analyzing bonner sphere data

International Nuclear Information System (INIS)

Zhu, Qingjun; Song, Gang; Song, Fengquan; Guo, Qian; Wu, Yican

2012-01-01

The objective of this study was to build an effective and reliable method based on the artificial neural network (ANN) model for unfolding neutron spectrum. The number of counts measured by 15 Bonner spheres and 281 neutron spectra were selected as the database. After singular value decomposition was used to determine the relationship between Bonner spheres, 11 Bonner spheres were chosen as input descriptors. The three-layer feedforward neural networks (11-5-1) were employed to predict the spectrum in each energy bin. Using information entropy theory and the results of the ANN calculations, the sensitivity of each sphere to the entropy of the spectrum was quantitatively analyzed. The spectra results were compared with the results obtained using the maximum entropy method (MEM). The averaged root mean-square-error (MSE) of the MEM output and the desired spectra was 0.012; the averaged MSE of the ANN calculations was 0.006. The MSE results indicate that the 11-5-1 ANN models are able to accurately and reliably predict neutron spectra. The ANN model developed in this study to unfold neutron spectra from the counts measured by 11 Bonner spheres provides an alternative method for unfolding spectrum. The singular value decomposition is an effective method for the analysis of data obtained from Bonner spheres and the neutron spectra.

Analyzing the genes related to Alzheimer's disease via a network and pathway-based approach.

Science.gov (United States)

Hu, Yan-Shi; Xin, Juncai; Hu, Ying; Zhang, Lei; Wang, Ju

2017-04-27

Our understanding of the molecular mechanisms underlying Alzheimer's disease (AD) remains incomplete. Previous studies have revealed that genetic factors provide a significant contribution to the pathogenesis and development of AD. In the past years, numerous genes implicated in this disease have been identified via genetic association studies on candidate genes or at the genome-wide level. However, in many cases, the roles of these genes and their interactions in AD are still unclear. A comprehensive and systematic analysis focusing on the biological function and interactions of these genes in the context of AD will therefore provide valuable insights to understand the molecular features of the disease. In this study, we collected genes potentially associated with AD by screening publications on genetic association studies deposited in PubMed. The major biological themes linked with these genes were then revealed by function and biochemical pathway enrichment analysis, and the relation between the pathways was explored by pathway crosstalk analysis. Furthermore, the network features of these AD-related genes were analyzed in the context of human interactome and an AD-specific network was inferred using the Steiner minimal tree algorithm. We compiled 430 human genes reported to be associated with AD from 823 publications. Biological theme analysis indicated that the biological processes and biochemical pathways related to neurodevelopment, metabolism, cell growth and/or survival, and immunology were enriched in these genes. Pathway crosstalk analysis then revealed that the significantly enriched pathways could be grouped into three interlinked modules-neuronal and metabolic module, cell growth/survival and neuroendocrine pathway module, and immune response-related module-indicating an AD-specific immune-endocrine-neuronal regulatory network. Furthermore, an AD-specific protein network was inferred and novel genes potentially associated with AD were identified. By

All-in-One Wafer-Level Solution for MMIC Automatic Testing

Directory of Open Access Journals (Sweden)

Xu Ding

2018-04-01

Full Text Available In this paper, we present an all-in-one wafer-level solution for MMIC (monolithic microwave integrated circuit automatic testing. The OSL (open short load two tier de-embedding, the calibration verification model, the accurate PAE (power added efficiency testing, and the optimized vector cold source NF (noise figure measurement techniques are integrated in this solution to improve the measurement accuracy. A dual-core topology formed by an IPC (industrial personal computer and a VNA (vector network analyzer, and an automatic test software based on a three-level driver architecture, are applied to enhance the test efficiency. The benefit from this solution is that all the data of a MMIC can be achieved in only one contact, which shows state-of-the-art accuracy and efficiency.

Comparison of Control Approaches in Genetic Regulatory Networks by Using Stochastic Master Equation Models, Probabilistic Boolean Network Models and Differential Equation Models and Estimated Error Analyzes

Science.gov (United States)

Caglar, Mehmet Umut; Pal, Ranadip

2011-03-01

Central dogma of molecular biology states that ``information cannot be transferred back from protein to either protein or nucleic acid''. However, this assumption is not exactly correct in most of the cases. There are a lot of feedback loops and interactions between different levels of systems. These types of interactions are hard to analyze due to the lack of cell level data and probabilistic - nonlinear nature of interactions. Several models widely used to analyze and simulate these types of nonlinear interactions. Stochastic Master Equation (SME) models give probabilistic nature of the interactions in a detailed manner, with a high calculation cost. On the other hand Probabilistic Boolean Network (PBN) models give a coarse scale picture of the stochastic processes, with a less calculation cost. Differential Equation (DE) models give the time evolution of mean values of processes in a highly cost effective way. The understanding of the relations between the predictions of these models is important to understand the reliability of the simulations of genetic regulatory networks. In this work the success of the mapping between SME, PBN and DE models is analyzed and the accuracy and affectivity of the control policies generated by using PBN and DE models is compared.

Representative volume element of asphalt pavement for electromagnetic measurements

Directory of Open Access Journals (Sweden)

Terhi Pellinen

2015-02-01

Full Text Available The motivation for this study was to investigate the representative volume element (RVE needed to correlate the nondestructive electromagnetic (EM measurements with the conventional destructive asphalt pavement quality control measurements. A large pavement rehabilitation contract was used as the test site for the experiment. Pavement cores were drilled from the same locations where the stationary and continuous Ground Penetrating Radar (GPR measurements were obtained. Laboratory measurements included testing the bulk density of cores using two methods, the surface-saturated dry method and determining bulk density by dimensions. Also, Vector Network Analyzer (VNA and the through specimen transmission configuration were employed at microwave frequencies to measure the reference dielectric constant of cores using two different footprint areas and therefore volume elements. The RVE for EM measurements turns out to be frequency dependent; therefore in addition to being dependent on asphalt mixture type and method of obtaining bulk density, it is dependent on the resolution of the EM method used. Then, although the average bulk property results agreed with theoretical formulations of higher core air void content giving a lower dielectric constant, for the individual cores there was no correlation for the VNA measurements because the volume element seizes deviated. Similarly, GPR technique was unable to capture the spatial variation of pavement air voids measured from the 150-mm drill cores. More research is needed to determine the usable RVE for asphalt.

A goat poxvirus-vectored peste-des-petits-ruminants vaccine induces long-lasting neutralization antibody to high levels in goats and sheep.

Science.gov (United States)

Chen, Weiye; Hu, Sen; Qu, Linmao; Hu, Qianqian; Zhang, Qian; Zhi, Haibing; Huang, Kehe; Bu, Zhigao

2010-07-05

Recombinant capripoxvirus (CPV) is a promising candidate differentiating infected from vaccinated animals (DIVA) vaccine against peste-des-petits-ruminants (PPR). In order for recombinant CPV to be successfully used in the field, there should exist dependable indicators for quality control of vaccine products, surveillance and vaccination evaluation. Viral neutralization antibody (VNA) is correlated to protection against PPR and is a technically feasible indicator for this purpose. The immunogenicity of this vectored vaccine in goats and sheep, however, has not been fully evaluated. In this study, we generated two recombinant CPV viruses, rCPV-PPRVH and rCPV-PPRVF, that express PPR virus (PPRV) glycoproteins H and F, respectively. Vaccination studies with different dosages of recombinant viruses showed that rCPV-PPRVH was a more potent inducer of PPRV VNA than rCPV-PPRVF. One dose of rCPV-PPRVH was enough to seroconvert 80% of immunized sheep. A second dose induced significantly higher PPRV VNA titers. There was no significant difference in PPRV VNA responses between goats and sheep. Subcutaneous inoculation also induced a significant PPRV VNA response. PPRV VNA could be detected for over 6 months in more than 80% of vaccinated goats and sheep. Boost vaccination at 6-month intervals induced significant re-boost efficacy of PPRV VNA in goats and sheep. More over, two doses of rCPV-PPRVH could completely overcome the interference caused by pre-existing immunity to the CPV vaccine backbone in animals. Vaccination with rCPV-PPRVH also protected goats from virulent CPV challenge. Our results demonstrate that VNA can serve as a dependent indicator for effective vaccination and immune protection of animals in the field. The recombinant CPV vaccine used in our studies could be a practical and useful candidate DIVA vaccine in countries where PPR newly emerges or where stamp-out plans are yet to be implemented. Copyright 2010 Elsevier Ltd. All rights reserved.

Summer Student Report 2014: Schottky component qualification and RF filter characterization

CERN Document Server

Egidos Plaja, Nuria

2014-01-01

This Summer Student project has been developed in BE-BI-QP department under the supervision of Manfred Wendt. Main goals of the task to be performed are the following: 1)\tFilter characterization: the student will get familiar with the Vector Network Analizer (VNA), S-parameter measurement and PSPICE modelling of low-pass filters. 2)\tFilter response matching: an algorithm to compare and classify filter responses into best-matching pairs will be developed. 3)\tSchottky monitor filter qualification: S-parameter and time domain measurements will be carried out with filters related to Schottky monitor and results will be benchmarked. 4)\tSchottky monitor amplifier measurement: noise figure and gain at a given frequency will be measured for a set of Low Noise Amplifiers related to Schottky monitor. -1dB compression point and 3rd order interception point will be measured too for education purposes. For the development of this project, the student will get familiar with RF measure devices (VNA, VSA), theoretical concep...

Software network analyzer for computer network performance measurement planning over heterogeneous services in higher educational institutes

OpenAIRE

Ismail, Mohd Nazri

2009-01-01

In 21st century, convergences of technologies and services in heterogeneous environment have contributed multi-traffic. This scenario will affect computer network on learning system in higher educational Institutes. Implementation of various services can produce different types of content and quality. Higher educational institutes should have a good computer network infrastructure to support usage of various services. The ability of computer network should consist of i) higher bandwidth; ii) ...

Investigations on the sensitivity of a stepped-frequency radar utilizing a vector network analyzer for Ground Penetrating Radar

Science.gov (United States)

Seyfried, Daniel; Schubert, Karsten; Schoebel, Joerg

2014-12-01

Employing a continuous-wave radar system, with the stepped-frequency radar being one type of this class, all reflections from the environment are present continuously and simultaneously at the receiver. Utilizing such a radar system for Ground Penetrating Radar purposes, antenna cross-talk and ground bounce reflection form an overall dominant signal contribution while reflections from objects buried in the ground are of quite weak amplitude due to attenuation in the ground. This requires a large dynamic range of the receiver which in turn requires high sensitivity of the radar system. In this paper we analyze the sensitivity of our vector network analyzer utilized as stepped-frequency radar system for GPR pipe detection. We furthermore investigate the performance of increasing the sensitivity of the radar by means of appropriate averaging and low-noise pre-amplification of the received signal. It turns out that the improvement in sensitivity actually achievable may differ significantly from theoretical expectations. In addition, we give a descriptive explanation why our appropriate experiments demonstrate that the sensitivity of the receiver is independent of the distance between the target object and the source of dominant signal contribution. Finally, our investigations presented in this paper lead to a preferred setting of operation for our vector network analyzer in order to achieve best detection capability for weak reflection amplitudes, hence making the radar system applicable for Ground Penetrating Radar purposes.

Analyzing Comprehensive QoS with Security Constraints for Services Composition Applications in Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Naixue Xiong

2014-12-01

Full Text Available Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs. The quality of service (QoS of services composition applications (SCAs are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique—vector universal generating function (VUGF—which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs.

Analyzing comprehensive QoS with security constraints for services composition applications in wireless sensor networks.

Science.gov (United States)

Xiong, Naixue; Wu, Zhao; Huang, Yannong; Xu, Degang

2014-12-01

Services composition is fundamental to software development in multi-service wireless sensor networks (WSNs). The quality of service (QoS) of services composition applications (SCAs) are confronted with severe challenges due to the open, dynamic, and complex natures of WSNs. Most previous research separated various QoS indices into different fields and studied them individually due to the computational complexity. This approach ignores the mutual influence between these QoS indices, and leads to a non-comprehensive and inaccurate analysis result. The universal generating function (UGF) shows the speediness and precision in QoS analysis. However, only one QoS index at a time can be analyzed by the classic UGF. In order to efficiently analyze the comprehensive QoS of SCAs, this paper proposes an improved UGF technique-vector universal generating function (VUGF)-which considers the relationship between multiple QoS indices, including security, and can simultaneously analyze multiple QoS indices. The numerical examples demonstrate that it can be used for the evaluation of the comprehensive QoS of SCAs subjected to the security constraint in WSNs. Therefore, it can be effectively applied to the optimal design of multi-service WSNs.

Evaluation of axial pile bearing capacity based on pile driving analyzer (PDA) test using Neural Network

Science.gov (United States)

Maizir, H.; Suryanita, R.

2018-01-01

A few decades, many methods have been developed to predict and evaluate the bearing capacity of driven piles. The problem of the predicting and assessing the bearing capacity of the pile is very complicated and not yet established, different soil testing and evaluation produce a widely different solution. However, the most important thing is to determine methods used to predict and evaluate the bearing capacity of the pile to the required degree of accuracy and consistency value. Accurate prediction and evaluation of axial bearing capacity depend on some variables, such as the type of soil, diameter, and length of pile, etc. The aims of the study of Artificial Neural Networks (ANNs) are utilized to obtain more accurate and consistent axial bearing capacity of a driven pile. ANNs can be described as mapping an input to the target output data. The method using the ANN model developed to predict and evaluate the axial bearing capacity of the pile based on the pile driving analyzer (PDA) test data for more than 200 selected data. The results of the predictions obtained by the ANN model and the PDA test were then compared. This research as the neural network models give a right prediction and evaluation of the axial bearing capacity of piles using neural networks.

Radar cross-section measurements of ice particles using vector network analyzer

Directory of Open Access Journals (Sweden)

Jinhu Wang

2016-09-01

Full Text Available We carried out radar cross-section (RSC measurements of ice particles in a microwave anechoic chamber at Nanjing University of Information Science and Technology. We used microwave similarity theory to enlarge the size of particle from the micrometer to millimeter scale and to reduce the testing frequency from 94 GHz to 10 GHz. The microwave similarity theory was validated using the method of moments for single metal sphere, single dielectric sphere, and spherical and non-spherical dielectric particle swarms. The differences between the retrieved and theoretical results at 94 GHz were 0.016117%, 0.0023029%, 0.027627%, and 0.0046053%, respectively. We proposed a device that can measure the RCS of ice particles in the chamber based on the S21 parameter obtained from vector network analyzer. On the basis of the measured S21 parameter of the calibration material (metal plates and their corresponding theoretical RCS values, the RCS values of a spherical Teflon particle swarm and cuboid candle particle swarm was retrieved at 10 GHz. In this case, the differences between the retrieved and theoretical results were 12.72% and 24.49% for the Teflon particle swarm and cuboid candle swarm, respectively.

Some of Physical Properties of Nanostructured (Mg1-xCoxFe2O4 Ferrites Prepared by Sol-Gel Method

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Muhammad Abdul Ammer Alsherefi

2018-01-01

Full Text Available Sol-gel auto combustion technique was used to prepare nanoparticles of magnesium-cobalt ferrites with the chemical formula Mg1-xCoxFe2O4 for  (x=0, 0.2, 0.4, 0.6, 0.8, 1, where x added as weight  percentages, and sintering  at temperature (1100 oC. The X-ray patterns of prepared powder has confirmed the structure of cubic spinel structure (fcc. The prepared samples were composed of nearly spherical nano particles .An average particle size of  magnesium-cobalt ferrite  were  calculated  using  Debye Scherer’s relation is equal 53.12 nm. The surface structure of the samples was investigated by Scanning Electron Microscope(SEM. The electromagnetic properties for prepared samples were investigated using Vector Network Analyzer (VNA in X-band microwave region.

Reflection and Transmission Coefficient of Yttrium Iron Garnet Filled Polyvinylidene Fluoride Composite Using Rectangular Waveguide at Microwave Frequencies

Science.gov (United States)

Soleimani, Hassan; Abbas, Zulkifly; Yahya, Noorhana; Shameli, Kamyar; Soleimani, Hojjatollah; Shabanzadeh, Parvaneh

2012-01-01

The sol-gel method was carried out to synthesize nanosized Yttrium Iron Garnet (YIG). The nanomaterials with ferrite structure were heat-treated at different temperatures from 500 to 1000 °C. The phase identification, morphology and functional groups of the prepared samples were characterized by powder X-ray diffraction (PXRD), scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FT-IR), respectively. The YIG ferrite nanopowder was composited with polyvinylidene fluoride (PVDF) by a solution casting method. The magnitudes of reflection and transmission coefficients of PVDF/YIG containing 6, 10 and 13% YIG, respectively, were measured using rectangular waveguide in conjunction with a microwave vector network analyzer (VNA) in X-band frequencies. The results indicate that the presence of YIG in polymer composites causes an increase in reflection coefficient and decrease in transmission coefficient of the polymer. PMID:22942718

Microstrip Cross-coupled Interdigital SIR Based Bandpass Filter

Directory of Open Access Journals (Sweden)

R. K. Maharjan

2012-09-01

Full Text Available A simple and compact 4.9 GHz bandpass filter for C-band applications is proposed. This paper presents a novel microstrip cross-coupled interdigital half-wavelength stepped impedance resonator (SIR based bandpass filter (BPF.The designed structure is similar to that of a combination of two parallel interdigital capacitors. The scattering parameters of the structure are measured using vector network analyzer (VNA. The self generated capacitive and inductive reactances within the interdigital resonators exhibited in a resonance frequency of 4.9 GHz. The resonant frequency and bandwidth of the capacitive cross-coupled resonator is directly optimized from the physical arrangement of the resonators. The measured insertion loss (S21 and return loss (S11 were 0.3 dB and 28 dB, respectively, at resonance frequency which were almost close to the simulation results.

Design optimization of a novel pMDI actuator for systemic drug delivery.

Science.gov (United States)

Kakade, Prashant P; Versteeg, Henk K; Hargrave, Graham K; Genova, Perry; Williams Iii, Robert C; Deaton, Daniel

2007-01-01

Pressurized metered dose inhalers (pMDIs) are the most widely prescribed and economical respiratory drug delivery systems. Conventional pMDI actuators-those based on "two-orifice-and-sump" designs-produce an aerosol with a reasonable respirable fraction, but with high aerosol velocity. The latter is responsible for high oropharyngeal deposition, and consequently low drug delivery efficiency. Kos' pMDI technology is based on a proprietary vortex nozzle actuator (VNA), an innovative actuator configuration that seeks to reduce aerosol plume velocity, thereby promoting deep lung deposition. Using VNA development as a case study, this paper presents a systematic design optimization process to improve the actuator performance through use of advanced optical characterization tools. The optimization effort mainly relied on laser-based optical diagnostics to provide an improved understanding of the fundamentals of aerosol formation and interplay of various geometrical factors. The performance of the optimized VNA design thus evolved was characterized using phase Doppler anemometry and cascade impaction. The aerosol velocities for both standard and optimized VNA designs were found to be comparable, with both notably less than conventional actuators. The optimized VNA design also significantly reduces drug deposition in the actuator as well as USP throat adapter, which in turn, leads to a significantly higher fine particle fraction than the standard design (78 +/- 3% vs. 63 +/- 2% on an ex valve basis). This improved drug delivery efficiency makes VNA technology a practical proposition as a systemic drug delivery platform. Thus, this paper demonstrates how advanced optical diagnostic and characterization tools can be used in the development of high efficiency aerosol drug delivery devices.

Analyzing the Dynamics of Communication in Online Social Networks

Science.gov (United States)

de Choudhury, Munmun; Sundaram, Hari; John, Ajita; Seligmann, Doree Duncan

This chapter deals with the analysis of interpersonal communication dynamics in online social networks and social media. Communication is central to the evolution of social systems. Today, the different online social sites feature variegated interactional affordances, ranging from blogging, micro-blogging, sharing media elements (i.e., image, video) as well as a rich set of social actions such as tagging, voting, commenting and so on. Consequently, these communication tools have begun to redefine the ways in which we exchange information or concepts, and how the media channels impact our online interactional behavior. Our central hypothesis is that such communication dynamics between individuals manifest themselves via two key aspects: the information or concept that is the content of communication, and the channel i.e., the media via which communication takes place. We present computational models and discuss large-scale quantitative observational studies for both these organizing ideas. First, we develop a computational framework to determine the "interestingness" property of conversations cented around rich media. Second, we present user models of diffusion of social actions and study the impact of homophily on the diffusion process. The outcome of this research is twofold. First, extensive empirical studies on datasets from YouTube have indicated that on rich media sites, the conversations that are deemed "interesting" appear to have consequential impact on the properties of the social network they are associated with: in terms of degree of participation of the individuals in future conversations, thematic diffusion as well as emergent cohesiveness in activity among the concerned participants in the network. Second, observational and computational studies on large social media datasets such as Twitter have indicated that diffusion of social actions in a network can be indicative of future information cascades. Besides, given a topic, these cascades are often a

ModelforAnalyzing Human Communication Network Based onAgent-Based Simulation

Science.gov (United States)

Matsuyama, Shinako; Terano, Takao

This paper discusses dynamic properties of human communications networks, which appears as a result of informationexchanges among people. We propose agent-based simulation (ABS) to examine implicit mechanisms behind the dynamics. The ABS enables us to reveal the characteristics and the differences of the networks regarding the specific communicationgroups. We perform experiments on the ABS with activity data from questionnaires survey and with virtual data which isdifferent from the activity data. We compare the difference between them and show the effectiveness of the ABS through theexperiments.

Optimization of traceable coaxial RF reflection standards with 7-mm-N-connector using genetic algorithms

Directory of Open Access Journals (Sweden)

T. Schrader

2003-01-01

Full Text Available A new coaxial device with 7-mm-N-connector was developed providing calculable complex reflection coefficients for traceable calibration of vector network analyzers (VNA. It was specifically designed to fill the gap between 0 Hz (DC, direct current and 250MHz, though the device was tested up to 10GHz. The frequency dependent reflection coefficient of this device can be described by a model, which is characterized by traceable measurements. It is therefore regarded as a “traceable model". The new idea of using such models for traceability has been verified, found to be valid and was used for these investigations. The DC resistance value was extracted from RF measurements up to 10 GHz by means of Genetic Algorithms (GA. The GA was used to obtain the elements of the model describing the reflection coefficient Γ of a network of SMD resistors. The DC values determined with the GA from RF measurements match the traceable value at DC within 3·10-3, which is in good agreement with measurements using reference air lines at GHz frequencies.

Southeast Asia Report.

Science.gov (United States)

1985-09-30

tennis, volleyball, wrestling, shooting and gymnastics . [Text] [Hanoi VNA in English 1529 GMT 12 Sept 85 OW] LE DUAN ATTENDS ANNIVERSARY—Hanoi...VNA 11 September—More than 200 cultural and artistic activists and cadres of cultural and information service have gathered here recently to mark the

Revealing and analyzing networks of environmental systems

Science.gov (United States)

Eveillard, D.; Bittner, L.; Chaffron, S.; Guidi, L.; Raes, J.; Karsenti, E.; Bowler, C.; Gorsky, G.

2015-12-01

Understanding the interactions between microbial communities and their environment well enough to be able to predict diversity on the basis of physicochemical parameters is a fundamental pursuit of microbial ecology that still eludes us. However, modeling microbial communities is a complicated task, because (i) communities are complex, (ii) most are described qualitatively, and (iii) quantitative understanding of the way communities interacts with their surroundings remains incomplete. Within this seminar, we will illustrate two complementary approaches that aim to overcome these points in different manners. First, we will present a network analysis that focus on the biological carbon pump in the global ocean. The biological carbon pump is the process by which photosynthesis transforms CO2 to organic carbon sinking to the deep-ocean as particles where it is sequestered. While the intensity of the pump correlate to plankton community composition, the underlying ecosystem structure and interactions driving this process remain largely uncharacterized Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve understanding of these drivers. We show that specific plankton communities correlate with carbon export and highlight unexpected and overlooked taxa such as Radiolaria, alveolate parasites and bacterial pathogens, as well as Synechococcus and their phages, as key players in the biological pump. Additionally, we show that the abundances of just a few bacterial and viral genes predict most of the global ocean carbon export's variability. Together these findings help elucidate ecosystem drivers of the biological carbon pump and present a case study for scaling from genes-to-ecosystems. Second, we will show preliminary results on a probabilistic modeling that predicts microbial community structure across observed physicochemical data, from a putative network and partial quantitative knowledge. This modeling shows that, despite

Percolation of interdependent network of networks

International Nuclear Information System (INIS)

Havlin, Shlomo; Stanley, H. Eugene; Bashan, Amir; Gao, Jianxi; Kenett, Dror Y.

2015-01-01

Complex networks appear in almost every aspect of science and technology. Previous work in network theory has focused primarily on analyzing single networks that do not interact with other networks, despite the fact that many real-world networks interact with and depend on each other. Very recently an analytical framework for studying the percolation properties of interacting networks has been introduced. Here we review the analytical framework and the results for percolation laws for a Network Of Networks (NONs) formed by n interdependent random networks. The percolation properties of a network of networks differ greatly from those of single isolated networks. In particular, because the constituent networks of a NON are connected by node dependencies, a NON is subject to cascading failure. When there is strong interdependent coupling between networks, the percolation transition is discontinuous (first-order) phase transition, unlike the well-known continuous second-order transition in single isolated networks. Moreover, although networks with broader degree distributions, e.g., scale-free networks, are more robust when analyzed as single networks, they become more vulnerable in a NON. We also review the effect of space embedding on network vulnerability. It is shown that for spatially embedded networks any finite fraction of dependency nodes will lead to abrupt transition

Measurement of Dielectric Properties at 75 - 325 GHz using a Vector Network Analyzer and Full Wave Simulator

Directory of Open Access Journals (Sweden)

S.Khanal

2012-06-01

Full Text Available This paper presents a fast and easy to use method to determine permittivity and loss tangent in the frequency range of 75 to 325 GHz. To obtain the permittivity and the loss tangent of the test material, the reflection and transmission S-parameters of a waveguide section filled with the test material are measured using a vector network analyzer and then compared with the simulated plots from a full wave simulator (HFSS, or alternatively the measurement results are used in mathematical formulas. The results are coherent over multiple waveguide bands.

Look Together: Analyzing Gaze Coordination with Epistemic Network Analysis

Directory of Open Access Journals (Sweden)

Sean eAndrist

2015-07-01

Full Text Available When conversing and collaborating in everyday situations, people naturally and interactively align their behaviors with each other across various communication channels, including speech, gesture, posture, and gaze. Having access to a partner's referential gaze behavior has been shown to be particularly important in achieving collaborative outcomes, but the process in which people's gaze behaviors unfold over the course of an interaction and become tightly coordinated is not well understood. In this paper, we present work to develop a deeper and more nuanced understanding of coordinated referential gaze in collaborating dyads. We recruited 13 dyads to participate in a collaborative sandwich-making task and used dual mobile eye tracking to synchronously record each participant's gaze behavior. We used a relatively new analysis technique—epistemic network analysis—to jointly model the gaze behaviors of both conversational participants. In this analysis, network nodes represent gaze targets for each participant, and edge strengths convey the likelihood of simultaneous gaze to the connected target nodes during a given time-slice. We divided collaborative task sequences into discrete phases to examine how the networks of shared gaze evolved over longer time windows. We conducted three separate analyses of the data to reveal (1 properties and patterns of how gaze coordination unfolds throughout an interaction sequence, (2 optimal time lags of gaze alignment within a dyad at different phases of the interaction, and (3 differences in gaze coordination patterns for interaction sequences that lead to breakdowns and repairs. In addition to contributing to the growing body of knowledge on the coordination of gaze behaviors in joint activities, this work has implications for the design of future technologies that engage in situated interactions with human users.

Real-time monitoring of sucrose, sorbitol, d-glucose and d-fructose concentration by electromagnetic sensing.

Science.gov (United States)

Harnsoongnoen, Supakorn; Wanthong, Anuwat

2017-10-01

Magnetic sensing at microwave frequencies for real-time monitoring of sucrose, sorbitol, d-glucose and d-fructose concentrations is reported. The sensing element was designed based on a coplanar waveguide (CPW) loaded with a split ring resonator (SRR), which was fabricated on a DiClad 880 substrate with a thickness of 1.6mm and relative permittivity (ε r ) of 2.2. The magnetic sensor was connected to a Vector Network Analyzer (VNA) and the electromagnetic interaction between the samples and sensor was analyzed. The magnitude of the transmission coefficient (S 21 ) was used as an indicator to detect the solution sample concentrations ranging from 0.04 to 0.20g/ml. The experimental results confirmed that the developed system using microwaves for the real-time monitoring of sucrose, sorbitol, d-glucose and d-fructose concentrations gave unique results for each solution type and concentration. Moreover, the proposed sensor has a wide dynamic range, high linearity, fast operation and low-cost. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analyzing the determinants of the UK consumer's engagement in Viral Marketing on Social Networking Sites : A university Student's perspective

OpenAIRE

Alkhateeb, Ali; Alli, Zahir; Moussa, Wissam

2012-01-01

Social media, especially the social networking sites (SNS) like Facebook.com, has experienced exponential growth all across the globe in the last decade. It is rapidly attracting the consumers and replacing the traditional media. Electronic word of mouth (eWOM) through social media has acquired substantial position in the marketing mix as well as integrated marketing communication of the business organizations. This research aimed at analyzing different social relationship factors or determin...

Antibodies induced by vaccination with purified chick embryo cell culture vaccine (PCECV) cross-neutralize non-classical bat lyssavirus strains.

Science.gov (United States)

Malerczyk, Claudius; Selhorst, Thomas; Tordo, Noël; Moore, Susan; Müller, Thomas

2009-08-27

Tissue-culture vaccines like purified chick embryo cell vaccine (PCECV) have been shown to provide protection against classical rabies virus (RABV) via pre-exposure or post-exposure prophylaxis. A cross-neutralization study was conducted using a panel of 100 human sera, to determine, to what extent after vaccination with PCECV protection exists against non-classical bat lyssavirus strains like European bat lyssavirus (EBLV) type 1 and 2 and Australian bat lyssavirus (ABLV). Virus neutralizing antibody (VNA) concentrations against the rabies virus variants CVS-11, ABLV, EBLV-1 and EBLV-2 were determined by using a modified rapid fluorescent focus inhibition test. For ABLV and EBLV-2, the comparison to CVS-11 revealed almost identical results (100% adequate VNA concentrations >or=0.5 IU/mL; correlation coefficient r(2)=0.69 and 0.77, respectively), while for EBLV-1 more scattering was observed (97% adequate VNA concentrations; r(2)=0.50). In conclusion, vaccination with PCECV produces adequate VNA concentrations against classical RABV as well as non-classical lyssavirus strains ABLV, EBLV-1, and EBLV-2.

Theoretical Neuroanatomy:Analyzing the Structure, Dynamics,and Function of Neuronal Networks

Science.gov (United States)

Seth, Anil K.; Edelman, Gerald M.

The mammalian brain is an extraordinary object: its networks give rise to our conscious experiences as well as to the generation of adaptive behavior for the organism within its environment. Progress in understanding the structure, dynamics and function of the brain faces many challenges. Biological neural networks change over time, their detailed structure is difficult to elucidate, and they are highly heterogeneous both in their neuronal units and synaptic connections. In facing these challenges, graph-theoretic and information-theoretic approaches have yielded a number of useful insights and promise many more.

A Network Traffic Control Enhancement Approach over Bluetooth Networks

DEFF Research Database (Denmark)

Son, L.T.; Schiøler, Henrik; Madsen, Ole Brun

2003-01-01

This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated solu...... as capacity limitations and flow requirements in the network. Simulation shows that the performance of Bluetooth networks could be improved by applying the adaptive distributed network traffic control scheme...... solution of the stated optimization problem that satisfies quality of service requirements and topologically induced constraints in Bluetooth networks, such as link capacity and node resource limitations. The proposed scheme is decentralized and complies with frequent changes of topology as well......This paper analyzes network traffic control issues in Bluetooth data networks as convex optimization problem. We formulate the problem of maximizing of total network flows and minimizing the costs of flows. An adaptive distributed network traffic control scheme is proposed as an approximated...

Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability

International Nuclear Information System (INIS)

Ouyang, Min; Zhao, Lijing; Hong, Liu; Pan, Zhezhe

2014-01-01

Recently numerous studies have applied complex network based models to study the performance and vulnerability of infrastructure systems under various types of attacks and hazards. But how effective are these models to capture their real performance response is still a question worthy of research. Taking the Chinese railway system as an example, this paper selects three typical complex network based models, including purely topological model (PTM), purely shortest path model (PSPM), and weight (link length) based shortest path model (WBSPM), to analyze railway accessibility and flow-based vulnerability and compare their results with those from the real train flow model (RTFM). The results show that the WBSPM can produce the train routines with 83% stations and 77% railway links identical to the real routines and can approach the RTFM the best for railway vulnerability under both single and multiple component failures. The correlation coefficient for accessibility vulnerability from WBSPM and RTFM under single station failures is 0.96 while it is 0.92 for flow-based vulnerability; under multiple station failures, where each station has the same failure probability fp, the WBSPM can produce almost identical vulnerability results with those from the RTFM under almost all failures scenarios when fp is larger than 0.62 for accessibility vulnerability and 0.86 for flow-based vulnerability

Analyzing Human Communication Networks in Organizations: Applications to Management Problems.

Science.gov (United States)

Farace, Richard V.; Danowski, James A.

Investigating the networks of communication in organizations leads to an understanding of efficient and inefficient information dissemination as practiced in large systems. Most important in organizational communication is the role of the "liaison person"--the coordinator of intercommunication. When functioning efficiently, coordinators maintain…

A Complex Network Model for Analyzing Railway Accidents Based on the Maximal Information Coefficient

International Nuclear Information System (INIS)

Shao Fu-Bo; Li Ke-Ping

2016-01-01

It is an important issue to identify important influencing factors in railway accident analysis. In this paper, employing the good measure of dependence for two-variable relationships, the maximal information coefficient (MIC), which can capture a wide range of associations, a complex network model for railway accident analysis is designed in which nodes denote factors of railway accidents and edges are generated between two factors of which MIC values are larger than or equal to the dependent criterion. The variety of network structure is studied. As the increasing of the dependent criterion, the network becomes to an approximate scale-free network. Moreover, employing the proposed network, important influencing factors are identified. And we find that the annual track density-gross tonnage factor is an important factor which is a cut vertex when the dependent criterion is equal to 0.3. From the network, it is found that the railway development is unbalanced for different states which is consistent with the fact. (paper)

Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences.

Science.gov (United States)

Lanza, Val F; de Toro, María; Garcillán-Barcia, M Pilar; Mora, Azucena; Blanco, Jorge; Coque, Teresa M; de la Cruz, Fernando

2014-12-01

Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ-proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

[Macromolecular aromatic network characteristics of Chinese power coal analyzed by synchronous fluorescence and X-ray diffraction].

Science.gov (United States)

Ye, Cui-Ping; Feng, Jie; Li, Wen-Ying

2012-07-01

Coal structure, especially the macromolecular aromatic skeleton structure, has a strong influence on coke reactivity and coal gasification, so it is the key to grasp the macromolecular aromatic skeleton coal structure for getting the reasonable high efficiency utilization of coal. However, it is difficult to acquire their information due to the complex compositions and structure of coal. It has been found that the macromolecular aromatic network coal structure would be most isolated if small molecular of coal was first extracted. Then the macromolecular aromatic skeleton coal structure would be clearly analyzed by instruments, such as X-ray diffraction (XRD), fluorescence spectroscopy with synchronous mode (Syn-F), Gel permeation chromatography (GPC) etc. Based on the previous results, according to the stepwise fractional liquid extraction, two Chinese typical power coals, PS and HDG, were extracted by silica gel as stationary phase and acetonitrile, tetrahydrofuran (THF), pyridine and 1-methyl-2-pyrollidinone (NMP) as a solvent group for sequential elution. GPC, Syn-F and XRD were applied to investigate molecular mass distribution, condensed aromatic structure and crystal characteristics. The results showed that the size of aromatic layers (La) is small (3-3.95 nm) and the stacking heights (Lc) are 0.8-1.2 nm. The molecular mass distribution of the macromolecular aromatic network structure is between 400 and 1 130 amu, with condensed aromatic numbers of 3-7 in the structure units.

Accurate optical vector network analyzer based on optical single-sideband modulation and balanced photodetection.

Science.gov (United States)

Xue, Min; Pan, Shilong; Zhao, Yongjiu

2015-02-15

A novel optical vector network analyzer (OVNA) based on optical single-sideband (OSSB) modulation and balanced photodetection is proposed and experimentally demonstrated, which can eliminate the measurement error induced by the high-order sidebands in the OSSB signal. According to the analytical model of the conventional OSSB-based OVNA, if the optical carrier in the OSSB signal is fully suppressed, the measurement result is exactly the high-order-sideband-induced measurement error. By splitting the OSSB signal after the optical device-under-test (ODUT) into two paths, removing the optical carrier in one path, and then detecting the two signals in the two paths using a balanced photodetector (BPD), high-order-sideband-induced measurement error can be ideally eliminated. As a result, accurate responses of the ODUT can be achieved without complex post-signal processing. A proof-of-concept experiment is carried out. The magnitude and phase responses of a fiber Bragg grating (FBG) measured by the proposed OVNA with different modulation indices are superimposed, showing that the high-order-sideband-induced measurement error is effectively removed.

Integrated Autonomous Network Management (IANM) Multi-Topology Route Manager and Analyzer

National Research Council Canada - National Science Library

Henderson, Thomas R; Bae, Kyle; Fang, Jin; Kushi, David M

2008-01-01

.... In a previous ONR research effort, Boeing and Cisco Systems had studied the applicability of MTR in the context of Navy network scenarios, and Boeing had produced a Linux-based prototype of MTR...

Full-waveform modeling of Zero-Offset Electromagnetic Induction for Accurate Characterization of Subsurface Electrical Properties

Science.gov (United States)

Moghadas, D.; André, F.; Vereecken, H.; Lambot, S.

2009-04-01

Water is a vital resource for human needs, agriculture, sanitation and industrial supply. The knowledge of soil water dynamics and solute transport is essential in agricultural and environmental engineering as it controls plant growth, hydrological processes, and the contamination of surface and subsurface water. Increased irrigation efficiency has also an important role for water conservation, reducing drainage and mitigating some of the water pollution and soil salinity. Geophysical methods are effective techniques for monitoring the vadose zone. In particular, electromagnetic induction (EMI) can provide in a non-invasive way important information about the soil electrical properties at the field scale, which are mainly correlated to important variables such as soil water content, salinity, and texture. EMI is based on the radiation of a VLF EM wave into the soil. Depending on its electrical conductivity, Foucault currents are generated and produce a secondary EM field which is then recorded by the EMI system. Advanced techniques for EMI data interpretation resort to inverse modeling. Yet, a major gap in current knowledge is the limited accuracy of the forward model used for describing the EMI-subsurface system, usually relying on strongly simplifying assumptions. We present a new low frequency EMI method based on Vector Network Analyzer (VNA) technology and advanced forward modeling using a linear system of complex transfer functions for describing the EMI loop antenna and a three-dimensional solution of Maxwell's equations for wave propagation in multilayered media. VNA permits simple, international standard calibration of the EMI system. We derived a Green's function for the zero-offset, off-ground horizontal loop antenna and also proposed an optimal integration path for faster evaluation of the spatial-domain Green's function from its spectral counterpart. This new integration path shows fewer oscillations compared with the real path and permits to avoid the

Analyzing Social Media Networks with NodeXL Insights from a Connected World

CERN Document Server

Hansen, Derek; Smith, Marc A

2010-01-01

Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft's NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools -- NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theor

Analyzing the role of networks in Middle East and North African ...

International Development Research Centre (IDRC) Digital Library (Canada)

2013-11-18

Nov 18, 2013 ... ... and the role it played in entrepreneurs' success were supported by IDRC. ... entrepreneurs depend mainly on close connections, such as family and ... of the benefits of networking, particularly women entrepreneurs who ...

Wideband optical vector network analyzer based on optical single-sideband modulation and optical frequency comb.

Science.gov (United States)

Xue, Min; Pan, Shilong; He, Chao; Guo, Ronghui; Zhao, Yongjiu

2013-11-15

A novel approach to increase the measurement range of the optical vector network analyzer (OVNA) based on optical single-sideband (OSSB) modulation is proposed and experimentally demonstrated. In the proposed system, each comb line in an optical frequency comb (OFC) is selected by an optical filter and used as the optical carrier for the OSSB-based OVNA. The frequency responses of an optical device-under-test (ODUT) are thus measured channel by channel. Because the comb lines in the OFC have fixed frequency spacing, by fitting the responses measured in all channels together, the magnitude and phase responses of the ODUT can be accurately achieved in a large range. A proof-of-concept experiment is performed. A measurement range of 105 GHz and a resolution of 1 MHz is achieved when a five-comb-line OFC with a frequency spacing of 20 GHz is applied to measure the magnitude and phase responses of a fiber Bragg grating.

Plasmid Flux in Escherichia coli ST131 Sublineages, Analyzed by Plasmid Constellation Network (PLACNET), a New Method for Plasmid Reconstruction from Whole Genome Sequences

Science.gov (United States)

Garcillán-Barcia, M. Pilar; Mora, Azucena; Blanco, Jorge; Coque, Teresa M.; de la Cruz, Fernando

2014-01-01

Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ–proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages. PMID:25522143

Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET, a new method for plasmid reconstruction from whole genome sequences.

Directory of Open Access Journals (Sweden)

Val F Lanza

2014-12-01

Full Text Available Bacterial whole genome sequence (WGS methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage, comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC, comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ-proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

SINDA, Systems Improved Numerical Differencing Analyzer

Science.gov (United States)

Fink, L. C.; Pan, H. M. Y.; Ishimoto, T.

1972-01-01

Computer program has been written to analyze group of 100-node areas and then provide for summation of any number of 100-node areas to obtain temperature profile. SINDA program options offer user variety of methods for solution of thermal analog modes presented in network format.

Let's Face(book) It: Analyzing Interactions in Social Network Groups for Chemistry Learning

Science.gov (United States)

Rap, Shelley; Blonder, Ron

2016-02-01

We examined how social network (SN) groups contribute to the learning of chemistry. The main goal was to determine whether chemistry learning could occur in the group discourse. The emphasis was on groups of students in the 11th and 12th grades who learn chemistry in preparation for their final external examination. A total of 1118 discourse events were tallied in the different groups. We analyzed the different events that were found in chemistry learning Facebook groups (CLFGs). The analysis revealed that seven types of interactions were observed in the CLFGs: The most common interaction (47 %) dealt with organizing learning (e.g., announcements regarding homework, the location of the next class); learning interactions were observed in 22 % of the posts, and links to learning materials and social interactions constituted about 20 % each. The learning events that were ascertained underwent a deeper examination and three different types of chemistry learning interactions were identified. This examination was based on the theoretical framework of the commognitive approach to learning (Sfard in Thinking as communicating. Cambridge University Press, Cambridge, 2008), which will be explained. The identified learning interactions that were observed in the Facebook groups illustrate the potential of SNs to serve as an additional tool for teachers to advance their students' learning of chemistry.

Research on Evolutionary Mechanism of Agile Supply Chain Network via Complex Network Theory

Directory of Open Access Journals (Sweden)

Nai-Ru Xu

2016-01-01

Full Text Available The paper establishes the evolutionary mechanism model of agile supply chain network by means of complex network theory which can be used to describe the growth process of the agile supply chain network and analyze the complexity of the agile supply chain network. After introducing the process and the suitability of taking complex network theory into supply chain network research, the paper applies complex network theory into the agile supply chain network research, analyzes the complexity of agile supply chain network, presents the evolutionary mechanism of agile supply chain network based on complex network theory, and uses Matlab to simulate degree distribution, average path length, clustering coefficient, and node betweenness. Simulation results show that the evolution result displays the scale-free property. It lays the foundations of further research on agile supply chain network based on complex network theory.

Using an agent-based model to analyze the dynamic communication network of the immune response

Directory of Open Access Journals (Sweden)

Doolittle John

2011-01-01

Full Text Available Abstract Background The immune system behaves like a complex, dynamic network with interacting elements including leukocytes, cytokines, and chemokines. While the immune system is broadly distributed, leukocytes must communicate effectively to respond to a pathological challenge. The Basic Immune Simulator 2010 contains agents representing leukocytes and tissue cells, signals representing cytokines, chemokines, and pathogens, and virtual spaces representing organ tissue, lymphoid tissue, and blood. Agents interact dynamically in the compartments in response to infection of the virtual tissue. Agent behavior is imposed by logical rules derived from the scientific literature. The model captured the agent-to-agent contact history, and from this the network topology and the interactions resulting in successful versus failed viral clearance were identified. This model served to integrate existing knowledge and allowed us to examine the immune response from a novel perspective directed at exploiting complex dynamics, ultimately for the design of therapeutic interventions. Results Analyzing the evolution of agent-agent interactions at incremental time points from identical initial conditions revealed novel features of immune communication associated with successful and failed outcomes. There were fewer contacts between agents for simulations ending in viral elimination (win versus persistent infection (loss, due to the removal of infected agents. However, early cellular interactions preceded successful clearance of infection. Specifically, more Dendritic Agent interactions with TCell and BCell Agents, and more BCell Agent interactions with TCell Agents early in the simulation were associated with the immune win outcome. The Dendritic Agents greatly influenced the outcome, confirming them as hub agents of the immune network. In addition, unexpectedly high frequencies of Dendritic Agent-self interactions occurred in the lymphoid compartment late in the

Dissemination Patterns and Associated Network Effects of Sentiments in Social Networks

DEFF Research Database (Denmark)

Hillmann, Robert; Trier, Matthias

2012-01-01

. The dissemination patterns analyzed in this study consist of network motifs based on triples of actors and the ties among them. These motifs are associated with common social network effects to derive meaningful insights about dissemination activities. The data basis includes several thousand social networks...... with textual messages classified according to embedded positive and negative sentiments. Based on this data, sub-networks are extracted and analyzed with a dynamic network motif analysis to determine dissemination patterns and associated network effects. Results indicate that the emergence of digital social...... networks exhibits a strong tendency towards reciprocity, followed by the dominance of hierarchy as an intermediate step leading to social clustering with hubs and transitivity effects for both positive and negative sentiments to the same extend. Sentiments embedded in exchanged textual messages do only...

Magnetic and microwave absorption properties of La-Nd-Fe alloys

Energy Technology Data Exchange (ETDEWEB)

Qiao, Ziqiang [School of Material Science and Engineering & Guangxi Key Laboratory of Information Materials, Guilin University of Electronic Technology, Guilin 541004 (China); Pan, Shunkang, E-mail: skpan88@163.com [School of Material Science and Engineering & Guangxi Key Laboratory of Information Materials, Guilin University of Electronic Technology, Guilin 541004 (China); Xiong, Jilei [Chinalco Guangxi Non Ferrous Jinyuan Rare Earth CO., LTD, Hezhou 542603 (China); Cheng, Lichun; Yao, Qingrong [School of Material Science and Engineering & Guangxi Key Laboratory of Information Materials, Guilin University of Electronic Technology, Guilin 541004 (China); School of Materials and Engineering, Central South University, Changsha 410083 (China); Lin, Peihao [School of Material Science and Engineering & Guangxi Key Laboratory of Information Materials, Guilin University of Electronic Technology, Guilin 541004 (China)

2017-02-01

Through arc smelting and high energy ball milling method to synthesized the powders of La{sub x}Nd{sub 2-x}Fe{sub 17} (x=0.0, 0.2, 0.4, 0.6). By x-ray diffraction (XRD), scanning electron microscopy (SEM) and laser particle analyzer (LPS) to study the structural, morphology, particle size distribution of the powders, respectively. The electromagnetic parameters and saturation magnetization of the powers were measured by a vector network analyzer (VNA) and vibrating sample magnetometer (VSM), respectively. The saturation magnetization decreases with the La increasing. The minimum absorption peak frequency shifts towards a lower frequency region with an increase of La concentration. The microwave absorbing properties of the composite with different ratios of La{sub 0.2}Nd{sub 1.8}Fe{sub 17}/Ni were studied. The microwave absorbing peaks of the composite shift to higher frequencies, and the microwave absorbing properties improved with the Ni content increase to 20%. The minimum reflection loss is −32.5 dB at 9.8 GHz and the bandwidth less than −10 dB (Microwave absorption rate 90%) reaches 3 GHz with a thickness of 1.8 mm.

The serological response of young dogs to the Flury LEP strain of rabies virus vaccine.

Science.gov (United States)

Aghomo, H O; Oduye, O O; Rupprecht, C E

1990-01-01

The serological response of puppies from Nigeria to live Flury low egg passage (LEP) rabies vaccine was determined. Two sets of puppies were used: one set from rabies-vaccinated bitches and another set from non-vaccinated bitches. Puppies were vaccinated intramuscularly with Flury LEP strain rabies vaccine and serially bled from the 4th week to the 30th week. Serum rabies virus neutralizing antibodies (VNA) were measured by a modified rapid fluorescent focus inhibition test (RFFIT). Puppies from non-vaccinated bitches responded well to vaccination after the 4th week and through to the 10th week of age, showing a progressive increase in VNA. In contrast, puppies from vaccinated bitches responded well to rabies vaccination only at 10 weeks of age, although detectable maternal rabies VNA and rabies anti-ribonucleoprotein (RNP) antibodies had decreased by 6 weeks post partum.

Analyzing Networked Learning Practices in HigherEducation and Continuing Professional Development

DEFF Research Database (Denmark)

Dirckinck-Holmfeld, Lone

Deliverable 28.5.4 reports on the preparation of the book "Analysing Networked Learning Practices in Higher Education and Continuing Professional Development", which consists of an Introduction, case studies and a concluding section, which presents the theoretical work and empirical work conducte...

Combining many interaction networks to predict gene function and analyze gene lists.

Science.gov (United States)

Mostafavi, Sara; Morris, Quaid

2012-05-01

In this article, we review how interaction networks can be used alone or in combination in an automated fashion to provide insight into gene and protein function. We describe the concept of a "gene-recommender system" that can be applied to any large collection of interaction networks to make predictions about gene or protein function based on a query list of proteins that share a function of interest. We discuss these systems in general and focus on one specific system, GeneMANIA, that has unique features and uses different algorithms from the majority of other systems. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

What Hold us Together? Analyzing Biotech Field Formation

Directory of Open Access Journals (Sweden)

Jackeline Amantino de Andrade

2011-03-01

Full Text Available This article proposes to analyze the formation of biotechnological field bringing actor-network theory’s lens as contribution. Based on conclusions of studies developed by Walter Powell and colleagues it was held a research to analyze the diversity of institutional relations that are active by hemophilia therapies, the principle of generalized symmetry adopted for actor-network theory is highlight to identify how socio-technical associations are assembled. Besides the interorganizational relations, research’s findings indicate the scientific and technological contents have a significant mediating role to create and sustain those connections of knowledge. So, it is emphasized the need of a boarder theoretical discussion to enlarge explanations about the dynamics of organizational fields as well as innovation processes.

Telecommunication networks

CERN Document Server

Iannone, Eugenio

2011-01-01

Many argue that telecommunications network infrastructure is the most impressive and important technology ever developed. Analyzing the telecom market's constantly evolving trends, research directions, infrastructure, and vital needs, Telecommunication Networks responds with revolutionized engineering strategies to optimize network construction. Omnipresent in society, telecom networks integrate a wide range of technologies. These include quantum field theory for the study of optical amplifiers, software architectures for network control, abstract algebra required to design error correction co

Analyzing 3D xylem networks in Vitis vinifera using High Resolution Computed Tomography (HRCT)

Science.gov (United States)

Recent developments in High Resolution Computed Tomography (HRCT) have made it possible to visualize three dimensional (3D) xylem networks without time consuming, labor intensive physical sectioning. Here we describe a new method to visualize complex vessel networks in plants and produce a quantitat...

Combining evolutionary game theory and network theory to analyze human cooperation patterns

International Nuclear Information System (INIS)

Scatà, Marialisa; Di Stefano, Alessandro; La Corte, Aurelio; Liò, Pietro; Catania, Emanuele; Guardo, Ermanno; Pagano, Salvatore

2016-01-01

Highlights: • We investigate the evolutionary dynamics of human cooperation in a social network. • We introduce the concepts of “Critical Mass”, centrality measure and homophily. • The emergence of cooperation is affected by the spatial choice of the “Critical Mass”. • Our findings show that homophily speeds up the convergence towards cooperation. • Centrality and “Critical Mass” spatial choice partially offset the impact of homophily. - Abstract: As natural systems continuously evolve, the human cooperation dilemma represents an increasingly more challenging question. Humans cooperate in natural and social systems, but how it happens and what are the mechanisms which rule the emergence of cooperation, represent an open and fascinating issue. In this work, we investigate the evolution of cooperation through the analysis of the evolutionary dynamics of behaviours within the social network, where nodes can choose to cooperate or defect following the classical social dilemmas represented by Prisoner’s Dilemma and Snowdrift games. To this aim, we introduce a sociological concept and statistical estimator, “Critical Mass”, to detect the minimum initial seed of cooperators able to trigger the diffusion process, and the centrality measure to select within the social network. Selecting different spatial configurations of the Critical Mass nodes, we highlight how the emergence of cooperation can be influenced by this spatial choice of the initial core in the network. Moreover, we target to shed light how the concept of homophily, a social shaping factor for which “birds of a feather flock together”, can affect the evolutionary process. Our findings show that homophily allows speeding up the diffusion process and make quicker the convergence towards human cooperation, while centrality measure and thus the Critical Mass selection, play a key role in the evolution showing how the spatial configurations can create some hidden patterns, partially

Networking for the Environment

DEFF Research Database (Denmark)

Dickel, Petra; Hörisch, Jacob; Ritter, Thomas

2018-01-01

Although the public debate on the environmental orientation of firms has intensified, there is a lack of understanding about the consequences of that orientation, especially in terms of its impact on firms' networking behavior. In order to fill this gap, this paper analyzes the impact of external...... and internal environmental orientation on start-ups’ network characteristics, because networks are both vital for the success of start-ups and resource demanding. More specifically, the effects of environmental orientation on networking frequency and network size among start-ups are analyzed. Empirical data...... from 248 technology-based start-ups shows that those firms with a strong external environmental orientation have significantly higher networking frequencies and build larger networks. Conversely, a strong internal environmental orientation is linked to smaller networks. Thus, the results highlight...

Grid and Data Analyzing and Security

Directory of Open Access Journals (Sweden)

Fatemeh SHOKRI

2012-12-01

Full Text Available This paper examines the importance of secure structures in the process of analyzing and distributing information with aid of Grid-based technologies. The advent of distributed network has provided many practical opportunities for detecting and recording the time of events, and made efforts to identify the events and solve problems of storing information such as being up-to-date and documented. In this regard, the data distribution systems in a network environment should be accurate. As a consequence, a series of continuous and updated data must be at hand. In this case, Grid is the best answer to use data and resource of organizations by common processing.

Livelihood diversification in tropical coastal communities: a network-based approach to analyzing 'livelihood landscapes'.

Directory of Open Access Journals (Sweden)

Joshua E Cinner

Full Text Available BACKGROUND: Diverse livelihood portfolios are frequently viewed as a critical component of household economies in developing countries. Within the context of natural resources governance in particular, the capacity of individual households to engage in multiple occupations has been shown to influence important issues such as whether fishers would exit a declining fishery, how people react to policy, the types of resource management systems that may be applicable, and other decisions about natural resource use. METHODOLOGY/PRINCIPAL FINDINGS: This paper uses network analysis to provide a novel methodological framework for detailed systemic analysis of household livelihood portfolios. Paying particular attention to the role of natural resource-based occupations such as fisheries, we use network analyses to map occupations and their interrelationships- what we refer to as 'livelihood landscapes'. This network approach allows for the visualization of complex information about dependence on natural resources that can be aggregated at different scales. We then examine how the role of natural resource-based occupations changes along spectra of socioeconomic development and population density in 27 communities in 5 western Indian Ocean countries. Network statistics, including in- and out-degree centrality, the density of the network, and the level of network centralization are compared along a multivariate index of community-level socioeconomic development and a gradient of human population density. The combination of network analyses suggests an increase in household-level specialization with development for most occupational sectors, including fishing and farming, but that at the community-level, economies remained diversified. CONCLUSIONS/SIGNIFICANCE: The novel modeling approach introduced here provides for various types of livelihood portfolio analyses at different scales of social aggregation. Our livelihood landscapes approach provides insights

Specifying Orchestrating Capability in Network Organization and Interfirm Innovation Networks

DEFF Research Database (Denmark)

Hu, Yimei; Sørensen, Olav Jull

-tech industry. Besides interfirm networks, some organizational researchers are interested in the internal network organizational design. Prospector firms putting innovation on top of the agenda usually has a network organization which is more flexible. This paper analyzes how an SME from a traditional industry...

Vulnerability and controllability of networks of networks

International Nuclear Information System (INIS)

Liu, Xueming; Peng, Hao; Gao, Jianxi

2015-01-01

Network science is a highly interdisciplinary field ranging from natural science to engineering technology and it has been applied to model complex systems and used to explain their behaviors. Most previous studies have been focus on isolated networks, but many real-world networks do in fact interact with and depend on other networks via dependency connectivities, forming “networks of networks” (NON). The interdependence between networks has been found to largely increase the vulnerability of interacting systems, when a node in one network fails, it usually causes dependent nodes in other networks to fail, which, in turn, may cause further damage on the first network and result in a cascade of failures with sometimes catastrophic consequences, e.g., electrical blackouts caused by the interdependence of power grids and communication networks. The vulnerability of a NON can be analyzed by percolation theory that can be used to predict the critical threshold where a NON collapses. We review here the analytic framework for analyzing the vulnerability of NON, which yields novel percolation laws for n-interdependent networks and also shows that percolation theory of a single network studied extensively in physics and mathematics in the last 50 years is a specific limited case of the more general case of n interacting networks. Understanding the mechanism behind the cascading failure in NON enables us finding methods to decrease the vulnerability of the natural systems and design of more robust infrastructure systems. By examining the vulnerability of NON under targeted attack and studying the real interdependent systems, we find two methods to decrease the systems vulnerability: (1) protect the high-degree nodes, and (2) increase the degree correlation between networks. Furthermore, the ultimate proof of our understanding of natural and technological systems is reflected in our ability to control them. We also review the recent studies and challenges on the

Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network

Science.gov (United States)

Li, Huajiao; An, Haizhong; Wang, Yue; Huang, Jiachen; Gao, Xiangyun

2016-05-01

Keeping abreast of trends in the articles and rapidly grasping a body of article's key points and relationship from a holistic perspective is a new challenge in both literature research and text mining. As the important component, keywords can present the core idea of the academic article. Usually, articles on a single theme or area could share one or some same keywords, and we can analyze topological features and evolution of the articles co-keyword networks and keywords co-occurrence networks to realize the in-depth analysis of the articles. This paper seeks to integrate statistics, text mining, complex networks and visualization to analyze all of the academic articles on one given theme, complex network(s). All 5944 ;complex networks; articles that were published between 1990 and 2013 and are available on the Web of Science are extracted. Based on the two-mode affiliation network theory, a new frontier of complex networks, we constructed two different networks, one taking the articles as nodes, the co-keyword relationships as edges and the quantity of co-keywords as the weight to construct articles co-keyword network, and another taking the articles' keywords as nodes, the co-occurrence relationships as edges and the quantity of simultaneous co-occurrences as the weight to construct keyword co-occurrence network. An integrated method for analyzing the topological features and evolution of the articles co-keyword network and keywords co-occurrence networks is proposed, and we also defined a new function to measure the innovation coefficient of the articles in annual level. This paper provides a useful tool and process for successfully achieving in-depth analysis and rapid understanding of the trends and relationships of articles in a holistic perspective.

Latent geometry of bipartite networks

Science.gov (United States)

Kitsak, Maksim; Papadopoulos, Fragkiskos; Krioukov, Dmitri

2017-03-01

Despite the abundance of bipartite networked systems, their organizing principles are less studied compared to unipartite networks. Bipartite networks are often analyzed after projecting them onto one of the two sets of nodes. As a result of the projection, nodes of the same set are linked together if they have at least one neighbor in common in the bipartite network. Even though these projections allow one to study bipartite networks using tools developed for unipartite networks, one-mode projections lead to significant loss of information and artificial inflation of the projected network with fully connected subgraphs. Here we pursue a different approach for analyzing bipartite systems that is based on the observation that such systems have a latent metric structure: network nodes are points in a latent metric space, while connections are more likely to form between nodes separated by shorter distances. This approach has been developed for unipartite networks, and relatively little is known about its applicability to bipartite systems. Here, we fully analyze a simple latent-geometric model of bipartite networks and show that this model explains the peculiar structural properties of many real bipartite systems, including the distributions of common neighbors and bipartite clustering. We also analyze the geometric information loss in one-mode projections in this model and propose an efficient method to infer the latent pairwise distances between nodes. Uncovering the latent geometry underlying real bipartite networks can find applications in diverse domains, ranging from constructing efficient recommender systems to understanding cell metabolism.

Analyzing the Facebook Friendship Graph

OpenAIRE

Catanese, Salvatore; De Meo, Pasquale; Ferrara, Emilio; Fiumara, Giacomo

2010-01-01

Online Social Networks (OSN) during last years acquired a huge and increasing popularity as one of the most important emerging Web phenomena, deeply modifying the behavior of users and contributing to build a solid substrate of connections and relationships among people using the Web. In this preliminary work paper, our purpose is to analyze Facebook, considering a significant sample of data reflecting relationships among subscribed users. Our goal is to extract, from this platform, relevant ...

Influence of degree correlations on network structure and stability in protein-protein interaction networks

Directory of Open Access Journals (Sweden)

Zimmer Ralf

2007-08-01

Full Text Available Abstract Background The existence of negative correlations between degrees of interacting proteins is being discussed since such negative degree correlations were found for the large-scale yeast protein-protein interaction (PPI network of Ito et al. More recent studies observed no such negative correlations for high-confidence interaction sets. In this article, we analyzed a range of experimentally derived interaction networks to understand the role and prevalence of degree correlations in PPI networks. We investigated how degree correlations influence the structure of networks and their tolerance against perturbations such as the targeted deletion of hubs. Results For each PPI network, we simulated uncorrelated, positively and negatively correlated reference networks. Here, a simple model was developed which can create different types of degree correlations in a network without changing the degree distribution. Differences in static properties associated with degree correlations were compared by analyzing the network characteristics of the original PPI and reference networks. Dynamics were compared by simulating the effect of a selective deletion of hubs in all networks. Conclusion Considerable differences between the network types were found for the number of components in the original networks. Negatively correlated networks are fragmented into significantly less components than observed for positively correlated networks. On the other hand, the selective deletion of hubs showed an increased structural tolerance to these deletions for the positively correlated networks. This results in a lower rate of interaction loss in these networks compared to the negatively correlated networks and a decreased disintegration rate. Interestingly, real PPI networks are most similar to the randomly correlated references with respect to all properties analyzed. Thus, although structural properties of networks can be modified considerably by degree

Regional modeling approach for analyzing harmonic stability in radial power electronics based power system

DEFF Research Database (Denmark)

Yoon, Changwoo; Bai, Haofeng; Wang, Xiongfei

2015-01-01

Stability analysis of distributed power generation system becomes complex when there are many numbers of grid inverters in the system. In order to analyze system stability, the overall network impedance will be lumped and needs to be analyzed one by one. However, using a unified bulky transfer-fu...... and then it is expanded for generalizing its concept to an overall radial structured network....

Dielectric loss property of strong acids doped polyaniline (PANi)

Science.gov (United States)

Amalia, Rianti; Hafizah, Mas Ayu Elita; Andreas, Manaf, Azwar

2018-04-01

In this study, strong acid doped polyaniline (PANi) has been successfully fabricated through the chemical oxidative polymerization process with various polymerization times. Nonconducting PANi resulting from the polymerization process at various polymerization times were then doped by a strong acid HClO4 to generate dielectric properties. Ammonium Persulfate (APS) as an initiator was used during Polymerization process to develop dark green precipitates which then called Emeraldine Base Polyaniline (PANi-EB). The PANi-EB was successively doped by strong acid HClO4 with dopant and PANi ratio 10:1 to enhance the electrical conductivity. The conductivity of doped PANi was evaluated by Four Point Probe. Results of evaluation showed that the conductivity values of HClO4 doped PANi were in the range 337-363 mS/cm. The dielectric properties of doped PANi were evaluated by Vector Network Analyzer (VNA) which suggested that an increase in the permittivity value in the conducting PANi. It is concluded that PANi could be a potential candidate for electromagnetic waves absorbing materials.

Network Transformations in Economy

Directory of Open Access Journals (Sweden)

Bolychev O.

2014-09-01

Full Text Available In the context of ever-increasing market competition, networked interactions play a special role in the economy. The network form of entrepreneurship is increasingly viewed as an effective organizational structure to create a market value embedded in innovative business solutions. The authors study the characteristics of a network as an economic category and emphasize certain similarities between Rus sian and international approaches to identifying interactions of economic systems based on the network principle. The paper focuses on the types of networks widely used in the economy. The authors analyze the transformation of business networks along two lines: from an intra- to an inter-firm network and from an inter-firm to an inter-organizational network. The possible forms of network formation are described depending on the strength of connections and the type of integration. The drivers and reasons behind process of transition from a hierarchical model of the organizational structure to a network type are identified. The authors analyze the advantages of creating inter-firm networks and discuss the features of inter-organizational networks as compares to inter-firm ones. The article summarizes the reasons for and advantages of participation in inter-rganizational networks and identifies the main barriers to the formation of inter-organizational network.

Techniques of collecting, controling and analyzing information about functioning LAN JINET

International Nuclear Information System (INIS)

Mazepa, E.Yu.; Parsadanyan, N.G.; Fariseev, V.Ya.; Modebadze, Z.S.

1992-01-01

The brief description of programming capability for controling and analyzing information about functioning LAN JINET is presented. Operating in the menu mode an administrator and engineer of JINET are consider a network temprorary state, tracing map of token and statistic of commands, used by users of the network. 5 refs.; 10 figs

Visualization and Analysis of the Co-authorship Network of Articles of National Congress on “Family Pathology” Using Social Network Analysis Indicators

OpenAIRE

امیررضا اصنافی; الهه حسینی; سارا آمایه

2017-01-01

The present paper aims to visualize and analyze the co-authorship network of articles of national congress on family pathology using social network analysis (SNA) indicators. The present paper employed the descriptive research method with scientometrics approach and analyzed social network by micro and macro indicators. UCINET software was used to visualize and analyze the co-authorship network, and VOS viewer software was utilized to visualize a density network of the co-authorship. The 6th ...

Spatial analysis of bus transport networks using network theory

Science.gov (United States)

Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong

2018-07-01

In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison

Controllability of Train Service Network

Directory of Open Access Journals (Sweden)

Xuelei Meng

2015-01-01

Full Text Available Train service network is a network form of train service plan. The controllability of the train service plan determines the recovery possibility of the train service plan in emergencies. We first build the small-world model for train service network and analyze the scale-free character of it. Then based on the linear network controllability theory, we discuss the LB model adaptability in train service network controllability analysis. The LB model is improved and we construct the train service network and define the connotation of the driver nodes based on the immune propagation and cascading failure in the train service network. An algorithm to search for the driver nodes, turning the train service network into a bipartite graph, is proposed and applied in the train service network. We analyze the controllability of the train service network of China with the method and the results of the computing case prove the feasibility of it.

Social network analysis as a method for analyzing interaction in collaborative online learning environments

Directory of Open Access Journals (Sweden)

Patricia Rice Doran

2011-12-01

Full Text Available Social network analysis software such as NodeXL has been used to describe participation and interaction in numerous social networks, but it has not yet been widely used to examine dynamics in online classes, where participation is frequently required rather than optional and participation patterns may be impacted by the requirements of the class, the instructor’s activities, or participants’ intrinsic engagement with the subject matter. Such social network analysis, which examines the dynamics and interactions among groups of participants in a social network or learning group, can be valuable in programs focused on teaching collaborative and communicative skills, including teacher preparation programs. Applied to these programs, social network analysis can provide information about instructional practices likely to facilitate student interaction and collaboration across diverse student populations. This exploratory study used NodeXL to visualize students’ participation in an online course, with the goal of identifying (1 ways in which NodeXL could be used to describe patterns in participant interaction within an instructional setting and (2 identifying specific patterns in participant interaction among students in this particular course. In this sample, general education teachers demonstrated higher measures of connection and interaction with other participants than did those from specialist (ESOL or special education backgrounds, and tended to interact more frequently with all participants than the majority of participants from specialist backgrounds. We recommend further research to delineate specific applications of NodeXL within an instructional context, particularly to identify potential patterns in student participation based on variables such as gender, background, cultural and linguistic heritage, prior training and education, and prior experience so that instructors can ensure their practice helps to facilitate student interaction

International research networks in pharmaceuticals

DEFF Research Database (Denmark)

Cantner, Uwe; Rake, Bastian

2014-01-01

of scientific publications related to pharmaceutical research and applying social network analysis, we find that both the number of countries and their connectivity increase in almost all disease group specific networks. The cores of the networks consist of high income OECD countries and remain rather stable......Knowledge production and scientific research have become increasingly more collaborative and international, particularly in pharmaceuticals. We analyze this tendency in general and tie formation in international research networks on the country level in particular. Based on a unique dataset...... over time. Using network regression techniques to analyze the network dynamics our results indicate that accumulative advantages based on connectedness and multi-connectivity are positively related to changes in the countries' collaboration intensity whereas various indicators on similarity between...

Open innovation in networks

DEFF Research Database (Denmark)

Hu, Yimei

and hierarchy can be analyzed from a network approach. Within a network perspective, there are different levels of network, and a firm may not always has the power to “manage” innovation networks due to different levels of power. Based on the strength of a firm’s power, its role may varies from manager...

Data Auditor: Analyzing Data Quality Using Pattern Tableaux

Science.gov (United States)

Srivastava, Divesh

Monitoring databases maintain configuration and measurement tables about computer systems, such as networks and computing clusters, and serve important business functions, such as troubleshooting customer problems, analyzing equipment failures, planning system upgrades, etc. These databases are prone to many data quality issues: configuration tables may be incorrect due to data entry errors, while measurement tables may be affected by incorrect, missing, duplicate and delayed polls. We describe Data Auditor, a tool for analyzing data quality and exploring data semantics of monitoring databases. Given a user-supplied constraint, such as a boolean predicate expected to be satisfied by every tuple, a functional dependency, or an inclusion dependency, Data Auditor computes "pattern tableaux", which are concise summaries of subsets of the data that satisfy or fail the constraint. We discuss the architecture of Data Auditor, including the supported types of constraints and the tableau generation mechanism. We also show the utility of our approach on an operational network monitoring database.

Game theory in communication networks cooperative resolution of interactive networking scenarios

CERN Document Server

Antoniou, Josephina

2012-01-01

A mathematical tool for scientists and researchers who work with computer and communication networks, Game Theory in Communication Networks: Cooperative Resolution of Interactive Networking Scenarios addresses the question of how to promote cooperative behavior in interactive situations between heterogeneous entities in communication networking scenarios. It explores network design and management from a theoretical perspective, using game theory and graph theory to analyze strategic situations and demonstrate profitable behaviors of the cooperative entities. The book promotes the use of Game T

Analyzing the effect of routing protocols on media access control protocols in radio networks

Energy Technology Data Exchange (ETDEWEB)

Barrett, C. L. (Christopher L.); Drozda, M. (Martin); Marathe, A. (Achla); Marathe, M. V. (Madhav V.)

2002-01-01

We study the effect of routing protocols on the performance of media access control (MAC) protocols in wireless radio networks. Three well known MAC protocols: 802.11, CSMA, and MACA are considered. Similarly three recently proposed routing protocols: AODV, DSR and LAR scheme 1 are considered. The experimental analysis was carried out using GloMoSim: a tool for simulating wireless networks. The main focus of our experiments was to study how the routing protocols affect the performance of the MAC protocols when the underlying network and traffic parameters are varied. The performance of the protocols was measured w.r.t. five important parameters: (i) number of received packets, (ii) average latency of each packet, (iii) throughput (iv) long term fairness and (v) number of control packets at the MAC layer level. Our results show that combinations of routing and MAC protocols yield varying performance under varying network topology and traffic situations. The result has an important implication; no combination of routing protocol and MAC protocol is the best over all situations. Also, the performance analysis of protocols at a given level in the protocol stack needs to be studied not locally in isolation but as a part of the complete protocol stack. A novel aspect of our work is the use of statistical technique, ANOVA (Analysis of Variance) to characterize the effect of routing protocols on MAC protocols. This technique is of independent interest and can be utilized in several other simulation and empirical studies.

Integrating Networking into ATLAS

CERN Document Server

Mc Kee, Shawn Patrick; The ATLAS collaboration

2018-01-01

Networking is foundational to the ATLAS distributed infrastructure and there are many ongoing activities related to networking both within and outside of ATLAS. We will report on the progress in a number of areas exploring ATLAS's use of networking and our ability to monitor the network, analyze metrics from the network, and tune and optimize application and end-host parameters to make the most effective use of the network. Specific topics will include work on Open vSwitch for production systems, network analytics, FTS testing and tuning, and network problem alerting and alarming.

[Social networks in drinking behaviors among Japanese: support network, drinking network, and intervening network].

Science.gov (United States)

Yoshihara, Chika; Shimizu, Shinji

2005-10-01

The national representative sample was analyzed to examine the relationship between respondents' drinking practice and the social network which was constructed of three different types of network: support network, drinking network, and intervening network. Non-parametric statistical analysis was conducted with chi square method and ANOVA analysis, due to the risk of small samples in some basic tabulation cells. The main results are as follows: (1) In the support network of workplace associates, moderate drinkers enjoyed much more sociable support care than both nondrinkers and hard drinkers, which might suggest a similar effect as the French paradox. Meanwhile in the familial and kinship network, the more intervening care support was provided, the harder respondents' drinking practice. (2) The drinking network among Japanese people for both sexes is likely to be convergent upon certain types of network categories and not decentralized in various categories. This might reflect of the drinking culture of Japan, which permits people to drink everyday as a practice, especially male drinkers. Subsequently, solitary drinking is not optional for female drinkers. (3) Intervening network analysis showed that the harder the respondents' drinking practices, the more frequently their drinking behaviors were checked in almost all the categories of network. A rather complicated gender double-standard was found in the network of hard drinkers with their friends, particularly for female drinkers. Medical professionals played a similar intervening role for men as family and kinship networks but to a less degree than friends for females. The social network is considerably associated with respondents' drinking, providing both sociability for moderate drinkers and intervention for hard drinkers, depending on network categories. To minimize the risk of hard drinking and advance self-healthy drinking there should be more research development on drinking practice and the social network.

Network analysis applications in hydrology

Science.gov (United States)

Price, Katie

2017-04-01

Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain under­explored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five long­term USGS streamflow and water quality gages, allowing network application of long­term flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long­ term and event­based hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwater­surface water interactions.

Content Propagation in Online Social Networks

NARCIS (Netherlands)

Blenn, N.

2014-01-01

This thesis presents methods and techniques to analyze content propagation within online social networks (OSNs) using a graph theoretical approach. Important factors and different techniques to analyze and describe content propagation, starting from the smallest entity in a network, representing a

Comparison analysis on vulnerability of metro networks based on complex network

Science.gov (United States)

Zhang, Jianhua; Wang, Shuliang; Wang, Xiaoyuan

2018-04-01

This paper analyzes the networked characteristics of three metro networks, and two malicious attacks are employed to investigate the vulnerability of metro networks based on connectivity vulnerability and functionality vulnerability. Meanwhile, the networked characteristics and vulnerability of three metro networks are compared with each other. The results show that Shanghai metro network has the largest transport capacity, Beijing metro network has the best local connectivity and Guangzhou metro network has the best global connectivity, moreover Beijing metro network has the best homogeneous degree distribution. Furthermore, we find that metro networks are very vulnerable subjected to malicious attacks, and Guangzhou metro network has the best topological structure and reliability among three metro networks. The results indicate that the proposed methodology is feasible and effective to investigate the vulnerability and to explore better topological structure of metro networks.

Analyzing Spread of Influence in Social Networks for Transportation Applications

Science.gov (United States)

2016-09-02

This project analyzed the spread of influence in social media, in particular, the Twitter social media site, and identified the individuals who exert the most influence to those they interact with. There are published studies that use social media to...

Analyzing Spread of Influence in Social Networks for Transportation Application.

Science.gov (United States)

2016-09-02

This project analyzed the spread of influence in social media, in particular, the Twitter social media site, and identified the individuals who exert the most influence to those they interact with. There are published studies that use social media to...

Fractional Hopfield Neural Networks: Fractional Dynamic Associative Recurrent Neural Networks.

Science.gov (United States)

Pu, Yi-Fei; Yi, Zhang; Zhou, Ji-Liu

2017-10-01

This paper mainly discusses a novel conceptual framework: fractional Hopfield neural networks (FHNN). As is commonly known, fractional calculus has been incorporated into artificial neural networks, mainly because of its long-term memory and nonlocality. Some researchers have made interesting attempts at fractional neural networks and gained competitive advantages over integer-order neural networks. Therefore, it is naturally makes one ponder how to generalize the first-order Hopfield neural networks to the fractional-order ones, and how to implement FHNN by means of fractional calculus. We propose to introduce a novel mathematical method: fractional calculus to implement FHNN. First, we implement fractor in the form of an analog circuit. Second, we implement FHNN by utilizing fractor and the fractional steepest descent approach, construct its Lyapunov function, and further analyze its attractors. Third, we perform experiments to analyze the stability and convergence of FHNN, and further discuss its applications to the defense against chip cloning attacks for anticounterfeiting. The main contribution of our work is to propose FHNN in the form of an analog circuit by utilizing a fractor and the fractional steepest descent approach, construct its Lyapunov function, prove its Lyapunov stability, analyze its attractors, and apply FHNN to the defense against chip cloning attacks for anticounterfeiting. A significant advantage of FHNN is that its attractors essentially relate to the neuron's fractional order. FHNN possesses the fractional-order-stability and fractional-order-sensitivity characteristics.

Analyzing big data in social media: Text and network analyses of an eating disorder forum.

Science.gov (United States)

Moessner, Markus; Feldhege, Johannes; Wolf, Markus; Bauer, Stephanie

2018-05-10

Social media plays an important role in everyday life of young people. Numerous studies claim negative effects of social media and media in general on eating disorder risk factors. Despite the availability of big data, only few studies have exploited the possibilities so far in the field of eating disorders. Methods for data extraction, computerized content analysis, and network analysis will be introduced. Strategies and methods will be exemplified for an ad-hoc dataset of 4,247 posts and 34,118 comments by 3,029 users of the proed forum on Reddit. Text analysis with latent Dirichlet allocation identified nine topics related to social support and eating disorder specific content. Social network analysis describes the overall communication patterns, and could identify community structures and most influential users. A linear network autocorrelation model was applied to estimate associations in language among network neighbors. The supplement contains R code for data extraction and analyses. This paper provides an introduction to investigating social media data, and will hopefully stimulate big data social media research in eating disorders. When applied in real-time, the methods presented in this manuscript could contribute to improving the safety of ED-related online communication. © 2018 Wiley Periodicals, Inc.

Vendor neutral archive in PACS

International Nuclear Information System (INIS)

Agarwal, Tapesh Kumar; Sanjeev

2012-01-01

An archive is a location containing a collection of records, documents, or other materials of historical importance. An integral part of Picture Archiving and Communication System (PACS) is archiving. When a hospital needs to migrate a PACS vendor, the complete earlier data need to be migrated in the format of the newly procured PACS. It is both time and money consuming. To address this issue, the new concept of vendor neutral archive (VNA) has emerged. A VNA simply decouples the PACS and workstations at the archival layer. This is achieved by developing an application engine that receives, integrates, and transmits the data using the different syntax of a Digital Imaging and Communication in Medicine (DICOM) format. Transferring the data belonging to the old PACS to a new one is performed by a process called migration of data. In VNA, a number of different data migration techniques are available to facilitate transfer from the old PACS to the new one, the choice depending on the speed of migration and the importance of data. The techniques include simple DICOM migration, prefetch-based DICOM migration, medium migration, and the expensive non-DICOM migration. “Vendor neutral” may not be a suitable term, and “architecture neutral,” “PACS neutral,” “content neutral,” or “third-party neutral” are probably better and preferred terms. Notwithstanding this, the VNA acronym has come to stay in both the medical IT user terminology and in vendor nomenclature, and radiologists need to be aware of its impact in PACS across the globe

Symmetry in Complex Networks

Directory of Open Access Journals (Sweden)

Angel Garrido

2011-01-01

Full Text Available In this paper, we analyze a few interrelated concepts about graphs, such as their degree, entropy, or their symmetry/asymmetry levels. These concepts prove useful in the study of different types of Systems, and particularly, in the analysis of Complex Networks. A System can be defined as any set of components functioning together as a whole. A systemic point of view allows us to isolate a part of the world, and so, we can focus on those aspects that interact more closely than others. Network Science analyzes the interconnections among diverse networks from different domains: physics, engineering, biology, semantics, and so on. Current developments in the quantitative analysis of Complex Networks, based on graph theory, have been rapidly translated to studies of brain network organization. The brain's systems have complex network features—such as the small-world topology, highly connected hubs and modularity. These networks are not random. The topology of many different networks shows striking similarities, such as the scale-free structure, with the degree distribution following a Power Law. How can very different systems have the same underlying topological features? Modeling and characterizing these networks, looking for their governing laws, are the current lines of research. So, we will dedicate this Special Issue paper to show measures of symmetry in Complex Networks, and highlight their close relation with measures of information and entropy.

Integration of genomic information with biological networks using Cytoscape.

Science.gov (United States)

Bauer-Mehren, Anna

2013-01-01

Cytoscape is an open-source software for visualizing, analyzing, and modeling biological networks. This chapter explains how to use Cytoscape to analyze the functional effect of sequence variations in the context of biological networks such as protein-protein interaction networks and signaling pathways. The chapter is divided into five parts: (1) obtaining information about the functional effect of sequence variation in a Cytoscape readable format, (2) loading and displaying different types of biological networks in Cytoscape, (3) integrating the genomic information (SNPs and mutations) with the biological networks, and (4) analyzing the effect of the genomic perturbation onto the network structure using Cytoscape built-in functions. Finally, we briefly outline how the integrated data can help in building mathematical network models for analyzing the effect of the sequence variation onto the dynamics of the biological system. Each part is illustrated by step-by-step instructions on an example use case and visualized by many screenshots and figures.

Network architecture in a converged optical + IP network

Science.gov (United States)

Wakim, Walid; Zottmann, Harald

2012-01-01

As demands on Provider Networks continue to grow at exponential rates, providers are forced to evaluate how to continue to grow the network while increasing service velocity, enhancing resiliency while decreasing the total cost of ownership (TCO). The bandwidth growth that networks are experiencing is in the form packet based multimedia services such as video, video conferencing, gaming, etc... mixed with Over the Top (OTT) content providers such as Netflix, and the customer's expectations that best effort is not enough you end up with a situation that forces the provider to analyze how to gain more out of the network with less cost. In this paper we will discuss changes in the network that are driving us to a tighter integration between packet and optical layers and how to improve on today's multi - layer inefficiencies to drive down network TCO and provide for a fully integrated and dynamic network that will decrease time to revenue.

Design principles in biological networks

Science.gov (United States)

Goyal, Sidhartha

Much of biology emerges from networks of interactions. Even in a single bacterium such as Escherichia coli, there are hundreds of coexisting gene and protein networks. Although biological networks are the outcome of evolution, various physical and biological constraints limit their functional capacity. The focus of this thesis is to understand how functional constraints such as optimal growth in mircoorganisms and information flow in signaling pathways shape the metabolic network of bacterium E. coli and the quorum sensing network of marine bacterium Vibrio harveyi, respectively. Metabolic networks convert basic elemental sources into complex building-blocks eventually leading to cell's growth. Therefore, typically, metabolic pathways are often coupled both by the use of a common substrate and by stoichiometric utilization of their products for cell growth. We showed that such a coupled network with product-feedback inhibition may exhibit limit-cycle oscillations which arise via a Hopf bifurcation. Furthermore, we analyzed several representative metabolic modules and find that, in all cases, simple product-feedback inhibition allows nearly optimal growth, in agreement with the predicted growth-rate by the flux-balance analysis (FBA). Bacteria have fascinating and diverse social lives. They display coordinated group behaviors regulated by quorum sensing (QS) systems. The QS circuit of V. harveyi integrates and funnels different ecological information through a common phosphorelay cascade to a set of small regulatory RNAs (sRNAs) that enables collective behavior. We analyzed the signaling properties and information flow in the QS circuit, which provides a model for information flow in signaling networks more generally. A comparative study of post-transcriptional and conventional transcriptional regulation suggest a niche for sRNAs in allowing cells to transition quickly yet reliably between distinct states. Furthermore, we develop a new framework for analyzing signal

Cascading Failures and Recovery in Networks of Networks

Science.gov (United States)

Havlin, Shlomo

Network science have been focused on the properties of a single isolated network that does not interact or depends on other networks. In reality, many real-networks, such as power grids, transportation and communication infrastructures interact and depend on other networks. I will present a framework for studying the vulnerability and the recovery of networks of interdependent networks. In interdependent networks, when nodes in one network fail, they cause dependent nodes in other networks to also fail. This is also the case when some nodes like certain locations play a role in two networks -multiplex. This may happen recursively and can lead to a cascade of failures and to a sudden fragmentation of the system. I will present analytical solutions for the critical threshold and the giant component of a network of n interdependent networks. I will show, that the general theory has many novel features that are not present in the classical network theory. When recovery of components is possible global spontaneous recovery of the networks and hysteresis phenomena occur and the theory suggests an optimal repairing strategy of system of systems. I will also show that interdependent networks embedded in space are significantly more vulnerable compared to non embedded networks. In particular, small localized attacks may lead to cascading failures and catastrophic consequences.Thus, analyzing data of real network of networks is highly required to understand the system vulnerability. DTRA, ONR, Israel Science Foundation.

Hydrogen Production by Steam Reforming of Natural Gas Over Vanadium-Nickel-Alumina Catalysts.

Science.gov (United States)

Yoo, Jaekyeong; Park, Seungwon; Song, Ji Hwan; Song, In Kyu

2018-09-01

A series of vanadium-nickel-alumina (xVNA) catalysts were prepared by a single-step sol-gel method with a variation of vanadium content (x, wt%) for use in the hydrogen production by steam reforming of natural gas. The effect of vanadium content on the physicochemical properties and catalytic activities of xVNA catalysts in the steam reforming of natural gas was investigated. It was found that natural gas conversion and hydrogen yield showed volcano-shaped trends with respect to vanadium content. It was also revealed that natural gas conversion and hydrogen yield increased with decreasing nickel crystallite size.

N-nitrosamines in processed meat products – analysis, occurrence, formation, mitigation and exposure

DEFF Research Database (Denmark)

Herrmann, Susan Strange

and NVNA in meat. Secondly data on the occurrence of VNA and NVNA in processed meat products on the Danish market were to be generated and used for an evaluation of the exposure level resulting from consumption of processed meat products. A method allowing for the simultaneous determination of both VNA......, NPIP, NTCA and NMTCA were inversely related to the amount of erythorbic acid (396-1104 mg kg-1). The levels of the individual NA were reduced with up to 20 to 75%. No additional protection against NA formation was obtained by also adding ascorbyl palmitate, a fat soluble antioxidant. Sodium chloride...

Studies on the ANN implementation in the macro BIM cost analyzes

Directory of Open Access Journals (Sweden)

Michał Juszczyk

2017-06-01

Full Text Available The paper presents an approach which combines the concept of macro-level BIM-based cost analyzes and application of artificial intelligence tools – namely artificial neural networks. Discussion and foundations of the proposed approach are introduced in the paper to clarify the problem’s core. An exemplary case study reports the results of initial studies on the application of neural networks for the purposes of BIM-based cost analysis of a buildings’ floor structural frame. The results obtained justify the proposal of application of neural networks as a supportive mathematical tool in the problem presented in the paper.

Optical network control plane for multi-domain networking

DEFF Research Database (Denmark)

Manolova, Anna Vasileva

This thesis focuses on multi-domain routing for traffice engineering and survivability support in optical transport networks under the Generalized Multi-Protocol Label Switching (GMPLS) control framework. First, different extensions to the Border Gateway Protocol for multi-domain Traffic...... process are not enough for efficient TE in mesh multi-domain networks. Enhancing the protocol with multi-path dissemination capability, combined with the employment of an end-to-end TE metric proves to be a highly efficient solution. Simulation results show good performance characteristics of the proposed...... is not as essential for improved network performance as the length of the provided paths. Second, the issue of multi-domain survivability support is analyzed. An AS-disjoint paths is beneficial not only for resilience support, but also for facilitating adequate network reactions to changes in the network, which...

Network Analysis Tools: from biological networks to clusters and pathways.

Science.gov (United States)

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Ecological network analysis: network construction

NARCIS (Netherlands)

Fath, B.D.; Scharler, U.M.; Ulanowicz, R.E.; Hannon, B.

2007-01-01

Ecological network analysis (ENA) is a systems-oriented methodology to analyze within system interactions used to identify holistic properties that are otherwise not evident from the direct observations. Like any analysis technique, the accuracy of the results is as good as the data available, but

Negatívna reklama a jej účinky na cieľové skupiny

OpenAIRE

Poništová, Jana

2009-01-01

The aim of my thesis is to analyze some advertisements based on negative emotion and to familiarize the reader with the fundamental consepts in regard to advertisement. I also tried to describe the basic principles how to make the good and effective advertisement Moreover I concentrated on some key-factors of advertisement analysis such as the psychology of advertisement. The last capture of my thesis discusses some concrete forms of propagation, which either evocate the negative emotions on ...

Analyzing the impact of relay station characteristics on uplink performance in cellular network

NARCIS (Netherlands)

Dimitrova, D.C.; van den Berg, Hans Leo; Heijenk, Geert

2009-01-01

Uplink users in cellular networks, such as UMTS/ HSPA, located at the edge of the cell generally suffer from poor channel conditions. Deploying intermediate relay nodes is seen as a promising approach towards extending cell coverage. This paper focuses on the role of packet scheduling in cellular

Analysis of interference performance of tactical radio network

Science.gov (United States)

Nie, Hao; Cai, Xiaoxia; Chen, Hong

2017-08-01

Mobile Ad hoc network has a strong military background for its development as the core technology of the backbone network of US tactical Internet. And which tactical radio network, is the war in today's tactical use of the Internet more mature form of networking, mainly used in brigade and brigade following forces. This paper analyzes the typical protocol AODV in the tactical radio network, and then carries on the networking. By adding the interference device to the whole network, the battlefield environment is simulated, and then the throughput, delay and packet loss rate are analyzed, and the performance of the whole network and the single node before and after the interference is obtained.

Retinal Capillary Network and Foveal Avascular Zone in Eyes with Vein Occlusion and Fellow Eyes Analyzed With Optical Coherence Tomography Angiography.

Science.gov (United States)

Adhi, Mehreen; Filho, Marco A Bonini; Louzada, Ricardo N; Kuehlewein, Laura; de Carlo, Talisa E; Baumal, Caroline R; Witkin, Andre J; Sadda, Srinivas R; Sarraf, David; Reichel, Elias; Duker, Jay S; Waheed, Nadia K

2016-07-01

To evaluate the perifoveolar retinal capillary network at different depths and to quantify the foveal avascular zone (FAZ) in eyes with retinal vein occlusion (RVO) compared with their fellow eyes and healthy controls using spectral-domain optical coherence tomography angiography (SD-OCTA). We prospectively recruited 23 patients with RVO including 15 eyes with central RVO (CRVO) and 8 eyes with branch RVO (BRVO), their fellow eyes, and 8 age-matched healthy controls (8 eyes) for imaging on prototype OCTA software within RTVue-XR Avanti. The 3 × 3 mm and 6 × 6 mm en face angiograms of superficial and deep retinal capillary plexuses were segmented. Perifoveolar retinal capillary network was analyzed and FAZ was quantified. Decrease in vascular perfusion at the deep plexus was observed in all eyes with CRVO (8/8, 100%) and BRVO (6/6, 100%) without cystoid macular edema, and in 8 of 15 (53%) and 2 of 8 (25%) of the fellow eyes, respectively. Vascular tortuosity was observed in 13 of 15 (87%) CRVO and 5 of 8 (63%) BRVO eyes. Collaterals were seen in 10 of 15 (67%) CRVO and 5 of 8 (63%) BRVO eyes. Mean FAZ area was larger in eyes with RVO than their fellow eyes (1.13 ± 0.25 mm2 versus 0.58 ± 0.28 mm2; P = 0.007) and controls (1.13 ± 0.25 mm2 versus 0.30 ± 0.09 mm2; P network and is able to quantify the FAZ in RVO. Longitudinal studies may be considered to evaluate the clinical utility of OCTA in RVO and other retinal vascular diseases.

Network Physics anounces first product to provide business-level management of the most complex and dynamic networks

CERN Multimedia

2003-01-01

Network Physics, provider of business-level, traffic flow-based network management solutions, today announced the introduction of the Network Physics NP/BizFlow-1000. With the NP/BizFlow-1000, Fortune 1000 companies with complex and dynamic networks can analyze the flows that link business groups, critical applications, and network software and hardware (1 page).

Analyzing the impact of global financial crisis on the interconnectedness of Asian stock markets using network science

OpenAIRE

Jitendra Aswani

2015-01-01

As importance of Asian Stock Markets (ASM) has increased after the globalization, it is become significant to know how this network of ASM behaves on the onset of financial crises. For this study, the Global Financial Crisis is considered whose origin was in the developed country, US, unlike the Asian crisis of 1997. To evaluate the impact of financial crisis on the ASM, network theory is used as a tool here. Network modeling of stock markets is useful as it can help to avert the spillover of...

Structural Behavioral Study on the General Aviation Network Based on Complex Network

Science.gov (United States)

Zhang, Liang; Lu, Na

2017-12-01

The general aviation system is an open and dissipative system with complex structures and behavioral features. This paper has established the system model and network model for general aviation. We have analyzed integral attributes and individual attributes by applying the complex network theory and concluded that the general aviation network has influential enterprise factors and node relations. We have checked whether the network has small world effect, scale-free property and network centrality property which a complex network should have by applying degree distribution of functions and proved that the general aviation network system is a complex network. Therefore, we propose to achieve the evolution process of the general aviation industrial chain to collaborative innovation cluster of advanced-form industries by strengthening network multiplication effect, stimulating innovation performance and spanning the structural hole path.

Robustness of weighted networks

Science.gov (United States)

Bellingeri, Michele; Cassi, Davide

2018-01-01

Complex network response to node loss is a central question in different fields of network science because node failure can cause the fragmentation of the network, thus compromising the system functioning. Previous studies considered binary networks where the intensity (weight) of the links is not accounted for, i.e. a link is either present or absent. However, in real-world networks the weights of connections, and thus their importance for network functioning, can be widely different. Here, we analyzed the response of real-world and model networks to node loss accounting for link intensity and the weighted structure of the network. We used both classic binary node properties and network functioning measure, introduced a weighted rank for node importance (node strength), and used a measure for network functioning that accounts for the weight of the links (weighted efficiency). We find that: (i) the efficiency of the attack strategies changed using binary or weighted network functioning measures, both for real-world or model networks; (ii) in some cases, removing nodes according to weighted rank produced the highest damage when functioning was measured by the weighted efficiency; (iii) adopting weighted measure for the network damage changed the efficacy of the attack strategy with respect the binary analyses. Our results show that if the weighted structure of complex networks is not taken into account, this may produce misleading models to forecast the system response to node failure, i.e. consider binary links may not unveil the real damage induced in the system. Last, once weighted measures are introduced, in order to discover the best attack strategy, it is important to analyze the network response to node loss using nodes rank accounting the intensity of the links to the node.

Function-Oriented Networking and On-Demand Routing System in Network Using Ant Colony Optimization Algorithm

Directory of Open Access Journals (Sweden)

Young-Bo Sim

2017-11-01

Full Text Available In this paper, we proposed and developed Function-Oriented Networking (FON, a platform for network users. It has a different philosophy as opposed to technologies for network managers of Software-Defined Networking technology, OpenFlow. It is a technology that can immediately reflect the demands of the network users in the network, unlike the existing OpenFlow and Network Functions Virtualization (NFV, which do not reflect directly the needs of the network users. It allows the network user to determine the policy of the direct network, so it can be applied more precisely than the policy applied by the network manager. This is expected to increase the satisfaction of the service users when the network users try to provide new services. We developed FON function that performs on-demand routing for Low-Delay Required service. We analyzed the characteristics of the Ant Colony Optimization (ACO algorithm and found that the algorithm is suitable for low-delay required services. It was also the first in the world to implement the routing software using ACO Algorithm in the real Ethernet network. In order to improve the routing performance, several algorithms of the ACO Algorithm have been developed to enable faster path search-routing and path recovery. The relationship between the network performance index and the ACO routing parameters is derived, and the results are compared and analyzed. Through this, it was possible to develop the ACO algorithm.

Secure positioning in wireless networks

DEFF Research Database (Denmark)

Capkun, Srdjan; Hubaux, Jean-Pierre

2006-01-01

So far, the problem of positioning in wireless networks has been studied mainly in a non-adversarial settings. In this work, we analyze the resistance of positioning techniques to position and distance spoofing attacks. We propose a mechanism for secure positioning of wireless devices, that we call...... Verifiable Multilateration. We then show how this mechanism can be used to secure positioning in sensor networks. We analyze our system through simulations....

Social Networks and Technology Adoption

OpenAIRE

Hogset, Heidi

2005-01-01

This study analyzes social network effects on Kenyan smallholders' decision to adopt improved natural resource management techniques. These effects are decomposed into effects from social influence and learning through networks (strong ties), group effects, weak ties effects, informal finance, and conflicts arising from technological externalities, controlling for non-network effects.

Maximum entropy networks are more controllable than preferential attachment networks

International Nuclear Information System (INIS)

Hou, Lvlin; Small, Michael; Lao, Songyang

2014-01-01

A maximum entropy (ME) method to generate typical scale-free networks has been recently introduced. We investigate the controllability of ME networks and Barabási–Albert preferential attachment networks. Our experimental results show that ME networks are significantly more easily controlled than BA networks of the same size and the same degree distribution. Moreover, the control profiles are used to provide insight into control properties of both classes of network. We identify and classify the driver nodes and analyze the connectivity of their neighbors. We find that driver nodes in ME networks have fewer mutual neighbors and that their neighbors have lower average degree. We conclude that the properties of the neighbors of driver node sensitively affect the network controllability. Hence, subtle and important structural differences exist between BA networks and typical scale-free networks of the same degree distribution. - Highlights: • The controllability of maximum entropy (ME) and Barabási–Albert (BA) networks is investigated. • ME networks are significantly more easily controlled than BA networks of the same degree distribution. • The properties of the neighbors of driver node sensitively affect the network controllability. • Subtle and important structural differences exist between BA networks and typical scale-free networks

Let's Face(book) It: Analyzing Interactions in Social Network Groups for Chemistry Learning

Science.gov (United States)

Rap, Shelley; Blonder, Ron

2016-01-01

We examined how social network (SN) groups contribute to the learning of chemistry. The main goal was to determine whether chemistry learning could occur in the group discourse. The emphasis was on groups of students in the 11th and 12th grades who learn chemistry in preparation for their final external examination. A total of 1118 discourse…

Link Prediction in Social Networks: the State-of-the-Art

OpenAIRE

Wang, Peng; Xu, Baowen; Wu, Yurong; Zhou, Xiaoyu

2014-01-01

In social networks, link prediction predicts missing links in current networks and new or dissolution links in future networks, is important for mining and analyzing the evolution of social networks. In the past decade, many works have been done about the link prediction in social networks. The goal of this paper is to comprehensively review, analyze and discuss the state-of-the-art of the link prediction in social networks. A systematical category for link prediction techniques and problems ...

Sulfur Dioxide Analyzer Instrument Handbook

Energy Technology Data Exchange (ETDEWEB)

Springston, Stephen R. [Brookhaven National Lab. (BNL), Upton, NY (United States)

2016-05-01

The Sulfur Dioxide Analyzer measures sulfur dioxide based on absorbance of UV light at one wavelength by SO₂ molecules which then decay to a lower energy state by emitting UV light at a longer wavelength. Specifically, SO₂ + hυ1 →SO₂ *→SO₂ + hυ2 The emitted light is proportional to the concentration of SO₂ in the optical cell. External communication with the analyzer is available through an Ethernet port configured through the instrument network of the AOS systems. The Model 43i-TLE is part of the i-series of Thermo Scientific instruments. The i-series instruments are designed to interface with external computers through the proprietary Thermo Scientific iPort Software. However, this software is somewhat cumbersome and inflexible. Brookhaven National Laboratory (BNL) has written an interface program in National Instruments LabView that both controls the Model 43i-TLE Analyzer AND queries the unit for all measurement and housekeeping data. The LabView vi (the software program written by BNL) ingests all raw data from the instrument and outputs raw data files in a uniform data format similar to other instruments in the AOS and described more fully in Section 6.0 below.

Preparation and investigation of structural, magnetic and microwave absorption properties of cerium doped barium hexaferrite

Directory of Open Access Journals (Sweden)

P Kameli

2015-01-01

Full Text Available In this study the structure, magnetic and microwave absorption properties of cerium (Ce doped barium hexaferrite with general formulae BaCexFe12-xO19 (x=0.0, 0.05, 0.1, 0.15, 0.2 have been investigated. These samples have been prepared by sol- gel method. Influence of replacing Fe+3 ion by rare- earth Ce+3 ion on the structural, magnetic and microwave absorption properties have been investigated by X- ray diffraction (XRD, Fourier transform infrared (FT-IR, Vibrating sample magnetometer (VSM and vector network analyzer (VNA. X-ray diffraction analysis indicated that the samples are of single phase with space group p63/mmc. The magnetic properties of samples indicated that with the Ce doping the saturation magnetization show no regular behavior. Moreover, coercivity (Hc first decreased and reached to the minimum value for x=0.1 sample and then increased with Ce content increasing. Also, measurement of electromagnetic wave absorption in X and Ku frequency bands indicated that the maximum of reflection loss obtained for x=0.15 sample. Moreover, result indicated that absorption peak shifted toward a lower frequency when thickness was increased.

Development Radar Absorber Material using Rice Husk Carbon for Anechoic Chamber Application

Science.gov (United States)

Zulpadrianto, Z.; Yohandri, Y.; Putra, A.

2018-04-01

The developments of radar technology in Indonesia are very strategic due to the vast territory and had a high-level cloud cover more than 55% of the time. The objective of this research is to develop radar technology facility in Indonesia using local natural resources. The target of this research is to present a low cost and satisfy quality of anechoic chambers. Anechoic chamber is a space designed to avoid reflection of EM waves from outside or from within the room. The reflection coefficient of the EM wave is influenced by the medium imposed by the EM wave. In laboratory experimental research has been done the development of material radar absorber using rice husk. The rice husk is activated using HCl and KOH by stirring using a magnetic stirrer for 1 Hours. The results of rice husk activation were measured using a Vector Network Analyzer by varying the thickness of the ingredients and the concentration of the activation agent. The VNA measurement is obtained reflection coefficient of -12dB and. -6.22dB for 1M HCL and KOH at thickness 10mm, respectively.

Low power RF measurements of travelling wave type linear accelerator

International Nuclear Information System (INIS)

Reddy, Sivananda; Wanmode, Yashwant; Bhisikar, A.; Shrivastava, Purushottam

2015-01-01

RRCAT is engaged in the development of travelling wave (TW) type linear accelerator for irradiation of industrial and agricultural products. TW accelerator designed for 2π/3 mode to operate at frequency of 2856 MHz. It consists of input coupler, buncher cells, regular cells and output coupler. Low power measurement of this structure includes measurement of resonant frequency of the cells for different resonant modes and quality factor, tuning of input-output coupler and measurement of phase advance per cell and electric field in the structure. Steele's non-resonant perturbation technique has been used for measurement of phase advance per cell and electric field in the structure. Kyhl's method has been used for the tuning of input-output coupler. Computer based automated bead pull set-up has been developed for measurement of phase advance per cell and electric field profile in the structure. All the codes are written in Python for interfacing of Vector Network Analyzer (VNA) , stepper motor with computer. These codes also automate the measurement process. This paper describes the test set- up for measurement and results of measurement of travelling wave type linear accelerating structure. (author)

Online Advertising in Social Networks

Science.gov (United States)

Bagherjeiran, Abraham; Bhatt, Rushi P.; Parekh, Rajesh; Chaoji, Vineet

Online social networks offer opportunities to analyze user behavior and social connectivity and leverage resulting insights for effective online advertising. This chapter focuses on the role of social network information in online display advertising.

A research on the application of software defined networking in satellite network architecture

Science.gov (United States)

Song, Huan; Chen, Jinqiang; Cao, Suzhi; Cui, Dandan; Li, Tong; Su, Yuxing

2017-10-01

Software defined network is a new type of network architecture, which decouples control plane and data plane of traditional network, has the feature of flexible configurations and is a direction of the next generation terrestrial Internet development. Satellite network is an important part of the space-ground integrated information network, while the traditional satellite network has the disadvantages of difficult network topology maintenance and slow configuration. The application of SDN technology in satellite network can solve these problems that traditional satellite network faces. At present, the research on the application of SDN technology in satellite network is still in the stage of preliminary study. In this paper, we start with introducing the SDN technology and satellite network architecture. Then we mainly introduce software defined satellite network architecture, as well as the comparison of different software defined satellite network architecture and satellite network virtualization. Finally, the present research status and development trend of SDN technology in satellite network are analyzed.

Analyzing the evolutionary mechanisms of the Air Transportation System-of-Systems using network theory and machine learning algorithms

Science.gov (United States)

Kotegawa, Tatsuya

Complexity in the Air Transportation System (ATS) arises from the intermingling of many independent physical resources, operational paradigms, and stakeholder interests, as well as the dynamic variation of these interactions over time. Currently, trade-offs and cost benefit analyses of new ATS concepts are carried out on system-wide evaluation simulations driven by air traffic forecasts that assume fixed airline routes. However, this does not well reflect reality as airlines regularly add and remove routes. A airline service route network evolution model that projects route addition and removal was created and combined with state-of-the-art air traffic forecast methods to better reflect the dynamic properties of the ATS in system-wide simulations. Guided by a system-of-systems framework, network theory metrics and machine learning algorithms were applied to develop the route network evolution models based on patterns extracted from historical data. Constructing the route addition section of the model posed the greatest challenge due to the large pool of new link candidates compared to the actual number of routes historically added to the network. Of the models explored, algorithms based on logistic regression, random forests, and support vector machines showed best route addition and removal forecast accuracies at approximately 20% and 40%, respectively, when validated with historical data. The combination of network evolution models and a system-wide evaluation tool quantified the impact of airline route network evolution on air traffic delay. The expected delay minutes when considering network evolution increased approximately 5% for a forecasted schedule on 3/19/2020. Performance trade-off studies between several airline route network topologies from the perspectives of passenger travel efficiency, fuel burn, and robustness were also conducted to provide bounds that could serve as targets for ATS transformation efforts. The series of analysis revealed that high

University of Tennessee deploys force10 C-series to analyze data from CERN's Large Hadron Collider

CERN Multimedia

2007-01-01

"Force20 networks, the pioneer in building and securing reliable networks, today announced that the University of Tennessee physics department has deployed the C300 resilient switch to analyze data form CERN's Large Hadron Collider." (1 page)

Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

Science.gov (United States)

Park, Chihyun; Ahn, Jaegyoon; Kim, Hyunjin; Park, Sanghyun

2014-01-01

The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

Integrative gene network construction to analyze cancer recurrence using semi-supervised learning.

Directory of Open Access Journals (Sweden)

Chihyun Park

Full Text Available BACKGROUND: The prognosis of cancer recurrence is an important research area in bioinformatics and is challenging due to the small sample sizes compared to the vast number of genes. There have been several attempts to predict cancer recurrence. Most studies employed a supervised approach, which uses only a few labeled samples. Semi-supervised learning can be a great alternative to solve this problem. There have been few attempts based on manifold assumptions to reveal the detailed roles of identified cancer genes in recurrence. RESULTS: In order to predict cancer recurrence, we proposed a novel semi-supervised learning algorithm based on a graph regularization approach. We transformed the gene expression data into a graph structure for semi-supervised learning and integrated protein interaction data with the gene expression data to select functionally-related gene pairs. Then, we predicted the recurrence of cancer by applying a regularization approach to the constructed graph containing both labeled and unlabeled nodes. CONCLUSIONS: The average improvement rate of accuracy for three different cancer datasets was 24.9% compared to existing supervised and semi-supervised methods. We performed functional enrichment on the gene networks used for learning. We identified that those gene networks are significantly associated with cancer-recurrence-related biological functions. Our algorithm was developed with standard C++ and is available in Linux and MS Windows formats in the STL library. The executable program is freely available at: http://embio.yonsei.ac.kr/~Park/ssl.php.

Design and implementation of dynamic hybrid Honeypot network

Science.gov (United States)

Qiao, Peili; Hu, Shan-Shan; Zhai, Ji-Qiang

2013-05-01

The method of constructing a dynamic and self-adaptive virtual network is suggested to puzzle adversaries, delay and divert attacks, exhaust attacker resources and collect attacking information. The concepts of Honeypot and Honeyd, which is the frame of virtual Honeypot are introduced. The techniques of network scanning including active fingerprint recognition are analyzed. Dynamic virtual network system is designed and implemented. A virtual network similar to real network topology is built according to the collected messages from real environments in this system. By doing this, the system can perplex the attackers when Hackers attack and can further analyze and research the attacks. The tests to this system prove that this design can successfully simulate real network environment and can be used in network security analysis.

Design of multi-channel amplitude analyzer base on LonWorks

International Nuclear Information System (INIS)

Zhang Ying; Zhao Lihong; Chen Aihua

2008-01-01

The paper introduces the multi-channel analyzer which adopts LonWorks technology. The system detects the pulse peak by hardware circuits and controls data acquisition and network communication by Micro Controller and Unit and Neuron chip. SCM is programmed by Keil C51; the communication between SCM and nerve cell is realized by Neron C language, and the computer program is written by VB language. Test results show that this analyzer is with fast conversion speed and low power consumption. (authors)

Analyzing collaboration networks and developmental patterns of nano-enabled drug delivery (NEDD for brain cancer

Directory of Open Access Journals (Sweden)

Ying Huang

2015-07-01

Full Text Available The rapid development of new and emerging science & technologies (NESTs brings unprecedented challenges, but also opportunities. In this paper, we use bibliometric and social network analyses, at country, institution, and individual levels, to explore the patterns of scientific networking for a key nano area – nano-enabled drug delivery (NEDD. NEDD has successfully been used clinically to modulate drug release and to target particular diseased tissues. The data for this research come from a global compilation of research publication information on NEDD directed at brain cancer. We derive a family of indicators that address multiple facets of research collaboration and knowledge transfer patterns. Results show that: (1 international cooperation is increasing, but networking characteristics change over time; (2 highly productive institutions also lead in influence, as measured by citation to their work, with American institutes leading; (3 research collaboration is dominated by local relationships, with interesting information available from authorship patterns that go well beyond journal impact factors. Results offer useful technical intelligence to help researchers identify potential collaborators and to help inform R&D management and science & innovation policy for such nanotechnologies.

The Analysis of SARDANA HPON Networks Using the HPON Network Configurator

Directory of Open Access Journals (Sweden)

Rastislav Roka

2013-01-01

Full Text Available NG-PON systems present optical access infrastructures to support various applications of the many service providers. In the near future, we can expect NG-PON technologies with different motivations for developing of HPON networks. The HPON is a hybrid passive optical network in a way that utilizes on a physical layer both TDM and WDM multiplexing principles together. The HPON network utilizes similar or soft revised topologies as TDM-PON architectures. In this second paper, requirements for the SARDANA HPON networks are introduced. A main part of the paper is dedicated to presentation of the HPON network configurator that allows configurating and analyzing the SARDANA HPON characteristics from a viewpoint of various specific network parameters. Finally, a short introduction to the comparison of the SARDANA and SUCCESS HPON networks based on simulation results is presented.

The Analysis of SUCCESS HPON Networks Using the HPON Network Configurator

Directory of Open Access Journals (Sweden)

Rastislav Roka

2013-01-01

Full Text Available NG-PON systems present optical access infrastructures to support various applications of the many service providers. In the near future, we can expect NG-PON technologies with different motivations for developing of HPON networks. The HPON is a hybrid passive optical network in a way that utilizes on a physical layer both TDM and WDM multiplexing principles together. The HPON network utilizes similar or soft revised topologies as TDM-PON architectures. In this first paper, design requirements for SUCCESS HPON networks are introduced. A main part of the paper is dedicated to presentation of the HPON network configurator that allows configurating and analyzing the SUCCESS HPON characteristics from a viewpoint of various specific network parameters. Finally, a short introduction to the comparison of the SUCCESS and SARDANA HPON networks based on simulation results is presented.

Robustness of airline route networks

Science.gov (United States)

Lordan, Oriol; Sallan, Jose M.; Escorihuela, Nuria; Gonzalez-Prieto, David

2016-03-01

Airlines shape their route network by defining their routes through supply and demand considerations, paying little attention to network performance indicators, such as network robustness. However, the collapse of an airline network can produce high financial costs for the airline and all its geographical area of influence. The aim of this study is to analyze the topology and robustness of the network route of airlines following Low Cost Carriers (LCCs) and Full Service Carriers (FSCs) business models. Results show that FSC hubs are more central than LCC bases in their route network. As a result, LCC route networks are more robust than FSC networks.

Integrating networks with Mathematica

NARCIS (Netherlands)

Strijkers, R.J.; Meijer, R.J.

2008-01-01

We have developed a concept that considers network behavior as a collection of software objects, which can be used or modified in computer programs. The interfaces of these software objects are exposed as web services and enable applications to analyze and manipulate networks, e.g. to find

Analysis of computer networks

CERN Document Server

Gebali, Fayez

2015-01-01

This textbook presents the mathematical theory and techniques necessary for analyzing and modeling high-performance global networks, such as the Internet. The three main building blocks of high-performance networks are links, switching equipment connecting the links together, and software employed at the end nodes and intermediate switches. This book provides the basic techniques for modeling and analyzing these last two components. Topics covered include, but are not limited to: Markov chains and queuing analysis, traffic modeling, interconnection networks and switch architectures and buffering strategies.   ·         Provides techniques for modeling and analysis of network software and switching equipment; ·         Discusses design options used to build efficient switching equipment; ·         Includes many worked examples of the application of discrete-time Markov chains to communication systems; ·         Covers the mathematical theory and techniques necessary for ana...

Why Failing Terrorist Groups Persist Revisited: A Social Network Approach to AQIM Network Resilience

Science.gov (United States)

2017-12-01

the approach and methods used in this analysis to organize, analyze, and explore the geospatial, statistical , and social network data...requirements for the degree of MASTER OF SCIENCE IN INFORMATION STRATEGY AND POLITICAL WARFARE from the NAVAL POSTGRADUATE SCHOOL December...research utilizes both descriptive statistics and regression analysis of social network data to explore the changes within the AQIM network 2012

Biomedical sensing analyzer (BSA) for mobile-health (mHealth)-LTE.

Science.gov (United States)

Adibi, Sasan

2014-01-01

The rapid expansion of mobile-based systems, the capabilities of smartphone devices, as well as the radio access and cellular network technologies are the wind beneath the wing of mobile health (mHealth). In this paper, the concept of biomedical sensing analyzer (BSA) is presented, which is a novel framework, devised for sensor-based mHealth applications. The BSA is capable of formulating the Quality of Service (QoS) measurements in an end-to-end sense, covering the entire communication path (wearable sensors, link-technology, smartphone, cell-towers, mobile-cloud, and the end-users). The characterization and formulation of BSA depend on a number of factors, including the deployment of application-specific biomedical sensors, generic link-technologies, collection, aggregation, and prioritization of mHealth data, cellular network based on the Long-Term Evolution (LTE) access technology, and extensive multidimensional delay analyses. The results are studied and analyzed in a LabView 8.5 programming environment.

Modeling online social signed networks

Science.gov (United States)

Li, Le; Gu, Ke; Zeng, An; Fan, Ying; Di, Zengru

2018-04-01

People's online rating behavior can be modeled by user-object bipartite networks directly. However, few works have been devoted to reveal the hidden relations between users, especially from the perspective of signed networks. We analyze the signed monopartite networks projected by the signed user-object bipartite networks, finding that the networks are highly clustered with obvious community structure. Interestingly, the positive clustering coefficient is remarkably higher than the negative clustering coefficient. Then, a Signed Growing Network model (SGN) based on local preferential attachment is proposed to generate a user's signed network that has community structure and high positive clustering coefficient. Other structural properties of the modeled networks are also found to be similar to the empirical networks.

Networks in biological systems: An investigation of the Gene Ontology as an evolving network

International Nuclear Information System (INIS)

Coronnello, C; Tumminello, M; Micciche, S; Mantegna, R.N.

2009-01-01

Many biological systems can be described as networks where different elements interact, in order to perform biological processes. We introduce a network associated with the Gene Ontology. Specifically, we construct a correlation-based network where the vertices are the terms of the Gene Ontology and the link between each two terms is weighted on the basis of the number of genes that they have in common. We analyze a filtered network obtained from the correlation-based network and we characterize its evolution over different releases of the Gene Ontology.

Using networking and communications software in business

CERN Document Server

McBride, PK

2014-01-01

Using Networking and Communications Software in Business covers the importance of networks in a business firm, the benefits of computer communications within a firm, and the cost-benefit in putting up networks in businesses. The book is divided into six parts. Part I looks into the nature and varieties of networks, networking standards, and network software. Part II discusses the planning of a networked system, which includes analyzing the requirements for the network system, the hardware for the network, and network management. The installation of the network system and the network managemen

TROVE: A User-friendly Tool for Visualizing and Analyzing Cancer Hallmarks in Signaling Networks.

Science.gov (United States)

Chua, Huey Eng; Bhowmick, Sourav S; Zheng, Jie

2017-09-22

Cancer hallmarks, a concept that seeks to explain the complexity of cancer initiation and development, provide a new perspective of studying cancer signaling which could lead to a greater understanding of this complex disease. However, to the best of our knowledge, there is currently a lack of tools that support such hallmark-based study of the cancer signaling network, thereby impeding the gain of knowledge in this area. We present TROVE, a user-friendly software that facilitates hallmark annotation, visualization and analysis in cancer signaling networks. In particular, TROVE facilitates hallmark analysis specific to particular cancer types. Available under the Eclipse Public License from: https://sites.google.com/site/cosbyntu/softwares/trove and https://github.com/trove2017/Trove. hechua@ntu.edu.sg or assourav@ntu.edu.sg. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Simulations of biopolymer networks under shear

NARCIS (Netherlands)

Huisman, Elisabeth Margaretha

2011-01-01

In this thesis we present a new method to simulate realistic three-dimensional networks of biopolymers under shear. These biopolymer networks are important for the structural functions of cells and tissues. We use the method to analyze these networks under shear, and consider the elastic modulus,

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

Science.gov (United States)

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.

Using Individualized Brain Network for Analyzing Structural Covariance of the Cerebral Cortex in Alzheimer's Patients.

Science.gov (United States)

Kim, Hee-Jong; Shin, Jeong-Hyeon; Han, Cheol E; Kim, Hee Jin; Na, Duk L; Seo, Sang Won; Seong, Joon-Kyung

2016-01-01

Cortical thinning patterns in Alzheimer's disease (AD) have been widely reported through conventional regional analysis. In addition, the coordinated variance of cortical thickness in different brain regions has been investigated both at the individual and group network levels. In this study, we aim to investigate network architectural characteristics of a structural covariance network (SCN) in AD, and further to show that the structural covariance connectivity becomes disorganized across the brain regions in AD, while the normal control (NC) subjects maintain more clustered and consistent coordination in cortical atrophy variations. We generated SCNs directly from T1-weighted MR images of individual patients using surface-based cortical thickness data, with structural connectivity defined as similarity in cortical thickness within different brain regions. Individual SCNs were constructed using morphometric data from the Samsung Medical Center (SMC) dataset. The structural covariance connectivity showed higher clustering than randomly generated networks, as well as similar minimum path lengths, indicating that the SCNs are "small world." There were significant difference between NC and AD group in characteristic path lengths (z = -2.97, p < 0.01) and small-worldness values (z = 4.05, p < 0.01). Clustering coefficients in AD was smaller than that of NC but there was no significant difference (z = 1.81, not significant). We further observed that the AD patients had significantly disrupted structural connectivity. We also show that the coordinated variance of cortical thickness is distributed more randomly from one region to other regions in AD patients when compared to NC subjects. Our proposed SCN may provide surface-based measures for understanding interaction between two brain regions with co-atrophy of the cerebral cortex due to normal aging or AD. We applied our method to the AD Neuroimaging Initiative (ADNI) data to show consistency in results with the SMC

Organization of complex networks

Science.gov (United States)

Kitsak, Maksim

Many large complex systems can be successfully analyzed using the language of graphs and networks. Interactions between the objects in a network are treated as links connecting nodes. This approach to understanding the structure of networks is an important step toward understanding the way corresponding complex systems function. Using the tools of statistical physics, we analyze the structure of networks as they are found in complex systems such as the Internet, the World Wide Web, and numerous industrial and social networks. In the first chapter we apply the concept of self-similarity to the study of transport properties in complex networks. Self-similar or fractal networks, unlike non-fractal networks, exhibit similarity on a range of scales. We find that these fractal networks have transport properties that differ from those of non-fractal networks. In non-fractal networks, transport flows primarily through the hubs. In fractal networks, the self-similar structure requires any transport to also flow through nodes that have only a few connections. We also study, in models and in real networks, the crossover from fractal to non-fractal networks that occurs when a small number of random interactions are added by means of scaling techniques. In the second chapter we use k-core techniques to study dynamic processes in networks. The k-core of a network is the network's largest component that, within itself, exhibits all nodes with at least k connections. We use this k-core analysis to estimate the relative leadership positions of firms in the Life Science (LS) and Information and Communication Technology (ICT) sectors of industry. We study the differences in the k-core structure between the LS and the ICT sectors. We find that the lead segment (highest k-core) of the LS sector, unlike that of the ICT sector, is remarkably stable over time: once a particular firm enters the lead segment, it is likely to remain there for many years. In the third chapter we study how

Internet of THings Area Coverage Analyzer (ITHACA for Complex Topographical Scenarios

Directory of Open Access Journals (Sweden)

Raúl Parada

2017-10-01

Full Text Available The number of connected devices is increasing worldwide. Not only in contexts like the Smart City, but also in rural areas, to provide advanced features like smart farming or smart logistics. Thus, wireless network technologies to efficiently allocate Internet of Things (IoT and Machine to Machine (M2M communications are necessary. Traditional cellular networks like Global System for Mobile communications (GSM are widely used worldwide for IoT environments. Nevertheless, Low Power Wide Area Networks (LP-WAN are becoming widespread as infrastructure for present and future IoT and M2M applications. Based also on a subscription service, the LP-WAN technology SIGFOXTM may compete with cellular networks in the M2M and IoT communications market, for instance in those projects where deploying the whole communications infrastructure is too complex or expensive. For decision makers to decide the most suitable technology for each specific application, signal coverage is within the key features. Unfortunately, besides simulated coverage maps, decision-makers do not have real coverage maps for SIGFOXTM, as they can be found for cellular networks. Thereby, we propose Internet of THings Area Coverage Analyzer (ITHACA, a signal analyzer prototype to provide automated signal coverage maps and analytics for LP-WAN. Experiments performed in the Gran Canaria Island, Spain (with both urban and complex topographic rural environments, returned a real SIGFOXTM service availability above 97% and above 11% more coverage with respect to the company-provided simulated maps. We expect that ITHACA may help decision makers to deploy the most suitable technologies for future IoT and M2M projects.

World Input-Output Network.

Directory of Open Access Journals (Sweden)

Federica Cerina

Full Text Available Production systems, traditionally analyzed as almost independent national systems, are increasingly connected on a global scale. Only recently becoming available, the World Input-Output Database (WIOD is one of the first efforts to construct the global multi-regional input-output (GMRIO tables. By viewing the world input-output system as an interdependent network where the nodes are the individual industries in different economies and the edges are the monetary goods flows between industries, we analyze respectively the global, regional, and local network properties of the so-called world input-output network (WION and document its evolution over time. At global level, we find that the industries are highly but asymmetrically connected, which implies that micro shocks can lead to macro fluctuations. At regional level, we find that the world production is still operated nationally or at most regionally as the communities detected are either individual economies or geographically well defined regions. Finally, at local level, for each industry we compare the network-based measures with the traditional methods of backward linkages. We find that the network-based measures such as PageRank centrality and community coreness measure can give valuable insights into identifying the key industries.

Bayesian Networks and Influence Diagrams

DEFF Research Database (Denmark)

Kjærulff, Uffe Bro; Madsen, Anders Læsø

Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition, provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new...

Analyzing the Impact of Storage Shortage on Data Availability in Decentralized Online Social Networks

Directory of Open Access Journals (Sweden)

Songling Fu

2014-01-01

Full Text Available Maintaining data availability is one of the biggest challenges in decentralized online social networks (DOSNs. The existing work often assumes that the friends of a user can always contribute to the sufficient storage capacity to store all data. However, this assumption is not always true in today’s online social networks (OSNs due to the fact that nowadays the users often use the smart mobile devices to access the OSNs. The limitation of the storage capacity in mobile devices may jeopardize the data availability. Therefore, it is desired to know the relation between the storage capacity contributed by the OSN users and the level of data availability that the OSNs can achieve. This paper addresses this issue. In this paper, the data availability model over storage capacity is established. Further, a novel method is proposed to predict the data availability on the fly. Extensive simulation experiments have been conducted to evaluate the effectiveness of the data availability model and the on-the-fly prediction.

Robustness of airline alliance route networks

Science.gov (United States)

Lordan, Oriol; Sallan, Jose M.; Simo, Pep; Gonzalez-Prieto, David

2015-05-01

The aim of this study is to analyze the robustness of the three major airline alliances' (i.e., Star Alliance, oneworld and SkyTeam) route networks. Firstly, the normalization of a multi-scale measure of vulnerability is proposed in order to perform the analysis in networks with different sizes, i.e., number of nodes. An alternative node selection criterion is also proposed in order to study robustness and vulnerability of such complex networks, based on network efficiency. And lastly, a new procedure - the inverted adaptive strategy - is presented to sort the nodes in order to anticipate network breakdown. Finally, the robustness of the three alliance networks are analyzed with (1) a normalized multi-scale measure of vulnerability, (2) an adaptive strategy based on four different criteria and (3) an inverted adaptive strategy based on the efficiency criterion. The results show that Star Alliance has the most resilient route network, followed by SkyTeam and then oneworld. It was also shown that the inverted adaptive strategy based on the efficiency criterion - inverted efficiency - shows a great success in quickly breaking networks similar to that found with betweenness criterion but with even better results.

Network Analysis, Architecture, and Design

CERN Document Server

McCabe, James D

2007-01-01

Traditionally, networking has had little or no basis in analysis or architectural development, with designers relying on technologies they are most familiar with or being influenced by vendors or consultants. However, the landscape of networking has changed so that network services have now become one of the most important factors to the success of many third generation networks. It has become an important feature of the designer's job to define the problems that exist in his network, choose and analyze several optimization parameters during the analysis process, and then prioritize and evalua

Bayesian Networks and Influence Diagrams

DEFF Research Database (Denmark)

Kjærulff, Uffe Bro; Madsen, Anders Læsø

 Probabilistic networks, also known as Bayesian networks and influence diagrams, have become one of the most promising technologies in the area of applied artificial intelligence, offering intuitive, efficient, and reliable methods for diagnosis, prediction, decision making, classification......, troubleshooting, and data mining under uncertainty. Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. Intended...

Two port network analysis for three impedance based oscillators

KAUST Repository

Said, Lobna A.

2011-12-01

Two-port network representations are applied to analyze complex networks which can be dissolved into sub-networks connected in series, parallel or cascade. In this paper, the concept of two-port network has been studied for oscillators. Three impedance oscillator based on two port concept has been analyzed using different impedance structures. The effect of each structure on the oscillation condition and the frequency of oscillation have been introduced. Two different implementations using MOS and BJT have been introduced. © 2011 IEEE.

Inferring Phylogenetic Networks Using PhyloNet.

Science.gov (United States)

Wen, Dingqiao; Yu, Yun; Zhu, Jiafan; Nakhleh, Luay

2018-07-01

PhyloNet was released in 2008 as a software package for representing and analyzing phylogenetic networks. At the time of its release, the main functionalities in PhyloNet consisted of measures for comparing network topologies and a single heuristic for reconciling gene trees with a species tree. Since then, PhyloNet has grown significantly. The software package now includes a wide array of methods for inferring phylogenetic networks from data sets of unlinked loci while accounting for both reticulation (e.g., hybridization) and incomplete lineage sorting. In particular, PhyloNet now allows for maximum parsimony, maximum likelihood, and Bayesian inference of phylogenetic networks from gene tree estimates. Furthermore, Bayesian inference directly from sequence data (sequence alignments or biallelic markers) is implemented. Maximum parsimony is based on an extension of the "minimizing deep coalescences" criterion to phylogenetic networks, whereas maximum likelihood and Bayesian inference are based on the multispecies network coalescent. All methods allow for multiple individuals per species. As computing the likelihood of a phylogenetic network is computationally hard, PhyloNet allows for evaluation and inference of networks using a pseudolikelihood measure. PhyloNet summarizes the results of the various analyzes and generates phylogenetic networks in the extended Newick format that is readily viewable by existing visualization software.

The Genome-Scale Integrated Networks in Microorganisms

Directory of Open Access Journals (Sweden)

Tong Hao

2018-02-01

Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

Social Network: a Cytoscape app for visualizing co-authorship networks.

Science.gov (United States)

Kofia, Victor; Isserlin, Ruth; Buchan, Alison M J; Bader, Gary D

2015-01-01

Networks that represent connections between individuals can be valuable analytic tools. The Social Network Cytoscape app is capable of creating a visual summary of connected individuals automatically. It does this by representing relationships as networks where each node denotes an individual and an edge linking two individuals represents a connection. The app focuses on creating visual summaries of individuals connected by co-authorship links in academia, created from bibliographic databases like PubMed, Scopus and InCites. The resulting co-authorship networks can be visualized and analyzed to better understand collaborative research networks or to communicate the extent of collaboration and publication productivity among a group of researchers, like in a grant application or departmental review report. It can also be useful as a research tool to identify important research topics, researchers and papers in a subject area.

A Process Management System for Networked Manufacturing

Science.gov (United States)

Liu, Tingting; Wang, Huifen; Liu, Linyan

With the development of computer, communication and network, networked manufacturing has become one of the main manufacturing paradigms in the 21st century. Under the networked manufacturing environment, there exist a large number of cooperative tasks susceptible to alterations, conflicts caused by resources and problems of cost and quality. This increases the complexity of administration. Process management is a technology used to design, enact, control, and analyze networked manufacturing processes. It supports efficient execution, effective management, conflict resolution, cost containment and quality control. In this paper we propose an integrated process management system for networked manufacturing. Requirements of process management are analyzed and architecture of the system is presented. And a process model considering process cost and quality is developed. Finally a case study is provided to explain how the system runs efficiently.

Vaccination intervention on epidemic dynamics in networks

Science.gov (United States)

Peng, Xiao-Long; Xu, Xin-Jian; Fu, Xinchu; Zhou, Tao

2013-02-01

Vaccination is an important measure available for preventing or reducing the spread of infectious diseases. In this paper, an epidemic model including susceptible, infected, and imperfectly vaccinated compartments is studied on Watts-Strogatz small-world, Barabási-Albert scale-free, and random scale-free networks. The epidemic threshold and prevalence are analyzed. For small-world networks, the effective vaccination intervention is suggested and its influence on the threshold and prevalence is analyzed. For scale-free networks, the threshold is found to be strongly dependent both on the effective vaccination rate and on the connectivity distribution. Moreover, so long as vaccination is effective, it can linearly decrease the epidemic prevalence in small-world networks, whereas for scale-free networks it acts exponentially. These results can help in adopting pragmatic treatment upon diseases in structured populations.

Network Traffic Features for Anomaly Detection in Specific Industrial Control System Network

Directory of Open Access Journals (Sweden)

Matti Mantere

2013-09-01

Full Text Available The deterministic and restricted nature of industrial control system networks sets them apart from more open networks, such as local area networks in office environments. This improves the usability of network security, monitoring approaches that would be less feasible in more open environments. One of such approaches is machine learning based anomaly detection. Without proper customization for the special requirements of the industrial control system network environment, many existing anomaly or misuse detection systems will perform sub-optimally. A machine learning based approach could reduce the amount of manual customization required for different industrial control system networks. In this paper we analyze a possible set of features to be used in a machine learning based anomaly detection system in the real world industrial control system network environment under investigation. The network under investigation is represented by architectural drawing and results derived from network trace analysis. The network trace is captured from a live running industrial process control network and includes both control data and the data flowing between the control network and the office network. We limit the investigation to the IP traffic in the traces.

An Extended N-Player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network.

Science.gov (United States)

Zhou, Wen; Koptyug, Nikita; Ye, Shutao; Jia, Yifan; Lu, Xiaolong

2016-01-01

As computer science and complex network theory develop, non-cooperative games and their formation and application on complex networks have been important research topics. In the inter-firm innovation network, it is a typical game behavior for firms to invest in their alliance partners. Accounting for the possibility that firms can be resource constrained, this paper analyzes a coordination game using the Nash bargaining solution as allocation rules between firms in an inter-firm innovation network. We build an extended inter-firm n-player game based on nonidealized conditions, describe four investment strategies and simulate the strategies on an inter-firm innovation network in order to compare their performance. By analyzing the results of our experiments, we find that our proposed greedy strategy is the best-performing in most situations. We hope this study provides a theoretical insight into how firms make investment decisions.

An Extended N-Player Network Game and Simulation of Four Investment Strategies on a Complex Innovation Network.

Directory of Open Access Journals (Sweden)

Wen Zhou

Full Text Available As computer science and complex network theory develop, non-cooperative games and their formation and application on complex networks have been important research topics. In the inter-firm innovation network, it is a typical game behavior for firms to invest in their alliance partners. Accounting for the possibility that firms can be resource constrained, this paper analyzes a coordination game using the Nash bargaining solution as allocation rules between firms in an inter-firm innovation network. We build an extended inter-firm n-player game based on nonidealized conditions, describe four investment strategies and simulate the strategies on an inter-firm innovation network in order to compare their performance. By analyzing the results of our experiments, we find that our proposed greedy strategy is the best-performing in most situations. We hope this study provides a theoretical insight into how firms make investment decisions.

Analyzing the role of social networks in mapping knowledge flows: A case of a pharmaceutical company in India

Directory of Open Access Journals (Sweden)

V. Murale

2014-03-01

Full Text Available Knowledge Management literature lays emphasis on the fact that a major chunk of knowledge dissemination occurs through the various forms of social networks that exist within the organizations. A social network is a simple structure comprising of set of actors or nodes that may have relationships ties with one another. The social network analysis (SNA will help in mapping and measuring formal and informal relationships to understand what facilitates or impedes the knowledge flows that bind interacting units. This paper aims at studying the knowledge flows that happen through the social networks. It first, provides a conceptual framework and review of literature on the recent research and application of knowledge mapping and SNA, followed by a discussion on application of SNA for mapping knowledge flows in a pharmaceutical firm. In the last part, Knowledge maps are presented to illustrate the actual knowledge flow in firm.

Stochastic Control of Multi-Scale Networks: Modeling, Analysis and Algorithms

Science.gov (United States)

2014-10-20

correlation, protocol behavior (e.g., retransmissions), and network congestion ; and statistically analyzed the properties of LRD traffic from empirical data...traffic correlation, protocol behavior (e.g., retransmissions), and network congestion ; and statistically analyzed the properties of LRD traffic...Maximization in Wireless Networks, IEEE Transactions on Vehicular Technology, (07 2011): 0. doi: 10.1109/TVT.2011.2157544 Sugumar Murugesan, Philip

Close encounters: Analyzing how social similarity and propinquity contribute to strong network connections.

OpenAIRE

Reagans, Ray Eugene

2010-01-01

Models of network formation emphasize the importance of social similarity and propinquity in producing strong interpersonal connections. The positive effect each factor can have on tie strength has been documented across a number of studies, and yet we know surprisingly very little about how the two factors combine to produce strong ties. Being in close proximity could either amplify or dampen the positive effect that social similarity can have on tie strength. Data on tie strength among teac...

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

Science.gov (United States)

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…

Brand Marketing Model on Social Networks

OpenAIRE

Jolita Jezukevičiūtė; Vida Davidavičienė

2014-01-01

The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalys...

Biological transportation networks: Modeling and simulation

KAUST Repository

Albi, Giacomo

2015-09-15

We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation and angiogenesis) and ion transportation networks (e.g., neural networks) is explained in detail and basic analytical features like the gradient flow structure of the fluid transportation network model and the impact of the model parameters on the geometry and topology of network formation are analyzed. We also present a numerical finite-element based discretization scheme and discuss sample cases of network formation simulations.

Novel indexes based on network structure to indicate financial market

Science.gov (United States)

Zhong, Tao; Peng, Qinke; Wang, Xiao; Zhang, Jing

2016-02-01

There have been various achievements to understand and to analyze the financial market by complex network model. However, current studies analyze the financial network model but seldom present quantified indexes to indicate or forecast the price action of market. In this paper, the stock market is modeled as a dynamic network, in which the vertices refer to listed companies and edges refer to their rank-based correlation based on price series. Characteristics of the network are analyzed and then novel indexes are introduced into market analysis, which are calculated from maximum and fully-connected subnets. The indexes are compared with existing ones and the results confirm that our indexes perform better to indicate the daily trend of market composite index in advance. Via investment simulation, the performance of our indexes is analyzed in detail. The results indicate that the dynamic complex network model could not only serve as a structural description of the financial market, but also work to predict the market and guide investment by indexes.

Using Modeling and Simulation to Analyze Application and Network Performance at the Radioactive Waste and Nuclear Material Disposition Facility

International Nuclear Information System (INIS)

LIFE, ROY A.; MAESTAS, JOSEPH H.; BATEMAN, DENNIS B.

2003-01-01

Telecommunication services customers at the Radioactive Waste and Nuclear Material Disposition Facility (RWNMDF) have endured regular service outages that seem to be associated with a custom Microsoft Access Database. In addition, the same customers have noticed periods when application response times are noticeably worse than at others. To the customers, the two events appear to be correlated. Although many network design activities can be accomplished using trial-and-error methods, there are as many, if not more occasions where computerized analysis is necessary to verify the benefits of implementing one design alternative versus another. This is particularly true when network design is performed with application flows and response times in mind. More times than not, it is unclear whether upgrading certain aspects of the network will provide sufficient benefit to justify the corresponding costs, and network modeling tools can be used to help staff make these decisions. This report summarizes our analysis of the situation at the RWNMDF, in which computerized analysis was used to accomplish four objectives: (1) identify the source of the problem; (2) identify areas where improvements make the most sense; (3) evaluate various scenarios ranging from upgrading the network infrastructure, installing an additional fiber trunk as a way to improve local network performance, and re-locating the RWNMDF database onto corporate servers; and (4) demonstrate a methodology for network design using actual application response times to predict, select, and implement the design alternatives that provide the best performance and cost benefits

Epidemic spreading on interconnected networks.

Science.gov (United States)

Saumell-Mendiola, Anna; Serrano, M Ángeles; Boguñá, Marián

2012-08-01

Many real networks are not isolated from each other but form networks of networks, often interrelated in nontrivial ways. Here, we analyze an epidemic spreading process taking place on top of two interconnected complex networks. We develop a heterogeneous mean-field approach that allows us to calculate the conditions for the emergence of an endemic state. Interestingly, a global endemic state may arise in the coupled system even though the epidemics is not able to propagate on each network separately and even when the number of coupling connections is small. Our analytic results are successfully confronted against large-scale numerical simulations.

On the impact of network dynamics on a discovery protocol for ad-hoc networks

NARCIS (Netherlands)

Liu, F.; Heijenk, Geert

A very promising approach to discovering services and context information in ad-hoc networks is based on the use of Attenuated Bloom filters. In this paper we analyze the impact of changes in the connectivity of an ad-hoc network on this approach. We evaluate the performance of the discovery

Human behavior understanding in networked sensing theory and applications of networks of sensors

CERN Document Server

Spagnolo, Paolo; Distante, Cosimo

2014-01-01

This unique text/reference provides a broad overview of both the technical challenges in sensor network development, and the real-world applications of distributed sensing. Important aspects of distributed computing in large-scale networked sensor systems are analyzed in the context of human behavior understanding, including such topics as systems design tools and techniques, in-network signals, and information processing. Additionally, the book examines a varied range of application scenarios, covering surveillance, indexing and retrieval, patient care, industrial safety, social and ambient

Network Analysis of Time-Lapse Microscopy Recordings

Directory of Open Access Journals (Sweden)

Erik eSmedler

2014-09-01

Full Text Available Multicellular organisms rely on intercellular communication to regulate important cellular processes critical to life. To further our understanding of those processes there is a need to scrutinize dynamical signaling events and their functions in both cells and organisms. Here, we report a method and provide MATLAB code that analyzes time-lapse microscopy recordings to identify and characterize network structures within large cell populations, such as interconnected neurons. The approach is demonstrated using intracellular calcium (Ca2+ recordings in neural progenitors and cardiac myocytes, but could be applied to a wide variety of biosensors employed in diverse cell types and organisms. In this method, network structures are analyzed by applying cross-correlation signal processing and graph theory to single-cell recordings. The goal of the analysis is to determine if the single cell activity constitutes a network of interconnected cells and to decipher the properties of this network. The method can be applied in many fields of biology in which biosensors are used to monitor signaling events in living cells. Analyzing intercellular communication in cell ensembles can reveal essential network structures that provide important biological insights.

A conceptual framework for analyzing sustainability strategies in industrial supply networks from an innovation perspective.

NARCIS (Netherlands)

van Bommel, H.W.M.; van Bommel, Harrie W.M.

2011-01-01

This article proposes a new conceptual framework concerning the implementation of sustainability in supply networks from an innovation perspective. Based upon a recent qualitative literature review in environmental, social/ethical and logistics/operations management journals, this article summarizes

Entropy Characterization of Random Network Models

Directory of Open Access Journals (Sweden)

Pedro J. Zufiria

2017-06-01

Full Text Available This paper elaborates on the Random Network Model (RNM as a mathematical framework for modelling and analyzing the generation of complex networks. Such framework allows the analysis of the relationship between several network characterizing features (link density, clustering coefficient, degree distribution, connectivity, etc. and entropy-based complexity measures, providing new insight on the generation and characterization of random networks. Some theoretical and computational results illustrate the utility of the proposed framework.

Brand marketing model on social networks

OpenAIRE

Jezukevičiūtė, Jolita; Davidavičienė, Vida

2014-01-01

Paper analyzes the brand and its marketing solutions on social networks. This analysis led to the creation of improved brand marketing model on social networks, which will contribute to the rapid and cheap organization brand recognition, increase competitive advantage and enhance consumer loyalty. Therefore, the brand and a variety of social networks are becoming a hot research area for brand marketing model on social networks. The world‘s most successful brand marketing models exploratory an...

Self-Interested Routing in Queueing Networks

OpenAIRE

Ali K. Parlaktürk; Sunil Kumar

2004-01-01

We study self-interested routing in stochastic networks, taking into account the discrete stochastic dynamics of such networks. We analyze a two-station multiclass queueing network in which the system manager chooses the scheduling rule and individual customers choose routes in a self-interested manner. We show that this network can be unstable in Nash equilibrium under some scheduling rules. We also design a nontrivial scheduling rule that negates the performance degradation resulting from s...

Extracting information from multiplex networks

Science.gov (United States)

Iacovacci, Jacopo; Bianconi, Ginestra

2016-06-01

Multiplex networks are generalized network structures that are able to describe networks in which the same set of nodes are connected by links that have different connotations. Multiplex networks are ubiquitous since they describe social, financial, engineering, and biological networks as well. Extending our ability to analyze complex networks to multiplex network structures increases greatly the level of information that is possible to extract from big data. For these reasons, characterizing the centrality of nodes in multiplex networks and finding new ways to solve challenging inference problems defined on multiplex networks are fundamental questions of network science. In this paper, we discuss the relevance of the Multiplex PageRank algorithm for measuring the centrality of nodes in multilayer networks and we characterize the utility of the recently introduced indicator function Θ ˜ S for describing their mesoscale organization and community structure. As working examples for studying these measures, we consider three multiplex network datasets coming for social science.

Review Essay: Does Qualitative Network Analysis Exist?

Directory of Open Access Journals (Sweden)

Rainer Diaz-Bone

2007-01-01

Full Text Available Social network analysis was formed and established in the 1970s as a way of analyzing systems of social relations. In this review the theoretical-methodological standpoint of social network analysis ("structural analysis" is introduced and the different forms of social network analysis are presented. Structural analysis argues that social actors and social relations are embedded in social networks, meaning that action and perception of actors as well as the performance of social relations are influenced by the network structure. Since the 1990s structural analysis has integrated concepts such as agency, discourse and symbolic orientation and in this way structural analysis has opened itself. Since then there has been increasing use of qualitative methods in network analysis. They are used to include the perspective of the analyzed actors, to explore networks, and to understand network dynamics. In the reviewed book, edited by Betina HOLLSTEIN and Florian STRAUS, the twenty predominantly empirically orientated contributions demonstrate the possibilities of combining quantitative and qualitative methods in network analyses in different research fields. In this review we examine how the contributions succeed in applying and developing the structural analysis perspective, and the self-positioning of "qualitative network analysis" is evaluated. URN: urn:nbn:de:0114-fqs0701287

Mining social networks and security informatics

CERN Document Server

Özyer, Tansel; Rokne, Jon; Khoury, Suheil

2013-01-01

Crime, terrorism and security are in the forefront of current societal concerns. This edited volume presents research based on social network techniques showing how data from crime and terror networks can be analyzed and how information can be extracted. The topics covered include crime data mining and visualization; organized crime detection; crime network visualization; computational criminology; aspects of terror network analyses and threat prediction including cyberterrorism and the related area of dark web; privacy issues in social networks; security informatics; graph algorithms for soci

Networks as integrated in research methodologies in PER

DEFF Research Database (Denmark)

Bruun, Jesper

2016-01-01

of using networks to create insightful maps of learning discussions. To conclude, I argue that conceptual blending is a powerful framework for constructing "mixed methods" methodologies that may integrate diverse theories and other methodologies with network methodologies.......In recent years a number of researchers within the PER community have started using network analysis as a new methodology to extend our understanding of teaching and learning physics by viewing these as complex systems. In this paper, I give examples of social, cognitive, and action mapping...... networks and how they can be analyzed. In so doing I show how a network can be methodologically described as a set of relations between a set of entities, and how a network can be characterized and analyzed as a mathematical object. Then, as an illustrative example, I discuss a relatively new example...

Local dependency in networks

Directory of Open Access Journals (Sweden)

Kudĕlka Miloš

2015-06-01

Full Text Available Many real world data and processes have a network structure and can usefully be represented as graphs. Network analysis focuses on the relations among the nodes exploring the properties of each network. We introduce a method for measuring the strength of the relationship between two nodes of a network and for their ranking. This method is applicable to all kinds of networks, including directed and weighted networks. The approach extracts dependency relations among the network’s nodes from the structure in local surroundings of individual nodes. For the tasks we deal with in this article, the key technical parameter is locality. Since only the surroundings of the examined nodes are used in computations, there is no need to analyze the entire network. This allows the application of our approach in the area of large-scale networks. We present several experiments using small networks as well as large-scale artificial and real world networks. The results of the experiments show high effectiveness due to the locality of our approach and also high quality node ranking comparable to PageRank.

Extending network approach to language dynamics and human cognition. Comment on "Approaching human language with complex networks" by Cong and Liu

Science.gov (United States)

Gong, Tao; Shuai, Lan; Wu, Yicheng

2014-12-01

By analyzing complex networks constructed from authentic language data, Cong and Liu [1] advance linguistics research into the big data era. The network approach has revealed many intrinsic generalities and crucial differences at both the macro and micro scales between human languages. The axiom behind this research is that language is a complex adaptive system [2]. Although many lexical, semantic, or syntactic features have been discovered by means of analyzing the static and dynamic linguistic networks of world languages, available network-based language studies have not explicitly addressed the evolutionary dynamics of language systems and the correlations between language and human cognition. This commentary aims to provide some insights on how to use the network approach to study these issues.

Scaling architecture-on-demand based optical networks

NARCIS (Netherlands)

Meyer, Hugo; Sancho, Jose Carlos; Mrdakovic, Milica; Peng, Shuping; Simeonidou, Dimitra; Miao, Wang; Calabretta, Nicola

2016-01-01

This paper analyzes methodologies that allow scaling properly Architecture-On-Demand (AoD) based optical networks. As Data Centers and HPC systems are growing in size and complexity, optical networks seem to be the way to scale the bandwidth of current network infrastructures. To scale the number of

Continuous Learning of a Multilayered Network Topology in a Video Camera Network

Directory of Open Access Journals (Sweden)

Zou Xiaotao

2009-01-01

Full Text Available Abstract A multilayered camera network architecture with nodes as entry/exit points, cameras, and clusters of cameras at different layers is proposed. Unlike existing methods that used discrete events or appearance information to infer the network topology at a single level, this paper integrates face recognition that provides robustness to appearance changes and better models the time-varying traffic patterns in the network. The statistical dependence between the nodes, indicating the connectivity and traffic patterns of the camera network, is represented by a weighted directed graph and transition times that may have multimodal distributions. The traffic patterns and the network topology may be changing in the dynamic environment. We propose a Monte Carlo Expectation-Maximization algorithm-based continuous learning mechanism to capture the latent dynamically changing characteristics of the network topology. In the experiments, a nine-camera network with twenty-five nodes (at the lowest level is analyzed both in simulation and in real-life experiments and compared with previous approaches.

Continuous Learning of a Multilayered Network Topology in a Video Camera Network

Directory of Open Access Journals (Sweden)

Xiaotao Zou

2009-01-01

Full Text Available A multilayered camera network architecture with nodes as entry/exit points, cameras, and clusters of cameras at different layers is proposed. Unlike existing methods that used discrete events or appearance information to infer the network topology at a single level, this paper integrates face recognition that provides robustness to appearance changes and better models the time-varying traffic patterns in the network. The statistical dependence between the nodes, indicating the connectivity and traffic patterns of the camera network, is represented by a weighted directed graph and transition times that may have multimodal distributions. The traffic patterns and the network topology may be changing in the dynamic environment. We propose a Monte Carlo Expectation-Maximization algorithm-based continuous learning mechanism to capture the latent dynamically changing characteristics of the network topology. In the experiments, a nine-camera network with twenty-five nodes (at the lowest level is analyzed both in simulation and in real-life experiments and compared with previous approaches.

Intrusion detection in wireless ad-hoc networks

CERN Document Server

Chaki, Nabendu

2014-01-01

Presenting cutting-edge research, Intrusion Detection in Wireless Ad-Hoc Networks explores the security aspects of the basic categories of wireless ad-hoc networks and related application areas. Focusing on intrusion detection systems (IDSs), it explains how to establish security solutions for the range of wireless networks, including mobile ad-hoc networks, hybrid wireless networks, and sensor networks.This edited volume reviews and analyzes state-of-the-art IDSs for various wireless ad-hoc networks. It includes case studies on honesty-based intrusion detection systems, cluster oriented-based

Artificial neural networks applied to forecasting time series.

Science.gov (United States)

Montaño Moreno, Juan J; Palmer Pol, Alfonso; Muñoz Gracia, Pilar

2011-04-01

This study offers a description and comparison of the main models of Artificial Neural Networks (ANN) which have proved to be useful in time series forecasting, and also a standard procedure for the practical application of ANN in this type of task. The Multilayer Perceptron (MLP), Radial Base Function (RBF), Generalized Regression Neural Network (GRNN), and Recurrent Neural Network (RNN) models are analyzed. With this aim in mind, we use a time series made up of 244 time points. A comparative study establishes that the error made by the four neural network models analyzed is less than 10%. In accordance with the interpretation criteria of this performance, it can be concluded that the neural network models show a close fit regarding their forecasting capacity. The model with the best performance is the RBF, followed by the RNN and MLP. The GRNN model is the one with the worst performance. Finally, we analyze the advantages and limitations of ANN, the possible solutions to these limitations, and provide an orientation towards future research.

Brand Marketing Model on Social Networks

Directory of Open Access Journals (Sweden)

Jolita Jezukevičiūtė

2014-04-01

Full Text Available The paper analyzes the brand and its marketing solutions onsocial networks. This analysis led to the creation of improvedbrand marketing model on social networks, which will contributeto the rapid and cheap organization brand recognition, increasecompetitive advantage and enhance consumer loyalty. Therefore,the brand and a variety of social networks are becoming a hotresearch area for brand marketing model on social networks.The world‘s most successful brand marketing models exploratoryanalysis of a single case study revealed a brand marketingsocial networking tools that affect consumers the most. Basedon information analysis and methodological studies, develop abrand marketing model on social networks.

Analysis of complex networks using aggressive abstraction.

Energy Technology Data Exchange (ETDEWEB)

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

2008-10-01

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

Self-Similar Traffic In Wireless Networks

OpenAIRE

Jerjomins, R.; Petersons, E.

2005-01-01

Many studies have shown that traffic in Ethernet and other wired networks is self-similar. This paper reveals that wireless network traffic is also self-similar and long-range dependant by analyzing big amount of data captured from the wireless router.

Telecommunication Value Network in Malaysia

OpenAIRE

Ong, Li Chien

2009-01-01

Business network is believed to offer a superior way of managing the challenges related to the uncertainty and complexity of the contemporary business environment in Malaysia telecommunication industry. This study strives to analyze the value business network in Malaysia telecommunication industry with emphasize on the market leader, Maxis Communication Bhd in its mobile content services. The business network represents the form of organization where the focal company focuses on certain key a...

Weighted Networks at the Polish Market

Science.gov (United States)

Chmiel, A. M.; Sienkiewicz, J.; Suchecki, K.; Hołyst, J. A.

During the last few years various models of networks [1,2] have become a powerful tool for analysis of complex systems in such distant fields as Internet [3], biology [4], social groups [5], ecology [6] and public transport [7]. Modeling behavior of economical agents is a challenging issue that has also been studied from a network point of view. The examples of such studies are models of financial networks [8], supply chains [9, 10], production networks [11], investment networks [12] or collective bank bankrupcies [13, 14]. Relations between different companies have been already analyzed using several methods: as networks of shareholders [15], networks of correlations between stock prices [16] or networks of board directors [17]. In several cases scaling laws for network characteristics have been observed.

Network Compression as a Quality Measure for Protein Interaction Networks

Science.gov (United States)

Royer, Loic; Reimann, Matthias; Stewart, A. Francis; Schroeder, Michael

2012-01-01

With the advent of large-scale protein interaction studies, there is much debate about data quality. Can different noise levels in the measurements be assessed by analyzing network structure? Because proteomic regulation is inherently co-operative, modular and redundant, it is inherently compressible when represented as a network. Here we propose that network compression can be used to compare false positive and false negative noise levels in protein interaction networks. We validate this hypothesis by first confirming the detrimental effect of false positives and false negatives. Second, we show that gold standard networks are more compressible. Third, we show that compressibility correlates with co-expression, co-localization, and shared function. Fourth, we also observe correlation with better protein tagging methods, physiological expression in contrast to over-expression of tagged proteins, and smart pooling approaches for yeast two-hybrid screens. Overall, this new measure is a proxy for both sensitivity and specificity and gives complementary information to standard measures such as average degree and clustering coefficients. PMID:22719828

Current redistribution in resistor networks: Fat-tail statistics in regular and small-world networks.

Science.gov (United States)

Lehmann, Jörg; Bernasconi, Jakob

2017-03-01

The redistribution of electrical currents in resistor networks after single-bond failures is analyzed in terms of current-redistribution factors that are shown to depend only on the topology of the network and on the values of the bond resistances. We investigate the properties of these current-redistribution factors for regular network topologies (e.g., d-dimensional hypercubic lattices) as well as for small-world networks. In particular, we find that the statistics of the current redistribution factors exhibits a fat-tail behavior, which reflects the long-range nature of the current redistribution as determined by Kirchhoff's circuit laws.

Liquidity and Counterparty Risks Tradeoff in Money Market Networks

NARCIS (Netherlands)

Leon Rincon, C.E.; Sarmiento, M.

2016-01-01

We examine how liquidity is exchanged in different types of Colombian money market networks (i.e. secured, unsecured, and central bank’s repo networks). Our examination first measures and analyzes the centralization of money market networks. Afterwards, based on a simple network optimization problem

Community structures and role detection in music networks

Science.gov (United States)

Teitelbaum, T.; Balenzuela, P.; Cano, P.; Buldú, Javier M.

2008-12-01

We analyze the existence of community structures in two different social networks using data obtained from similarity and collaborative features between musical artists. Our analysis reveals some characteristic organizational patterns and provides information about the driving forces behind the growth of the networks. In the similarity network, we find a strong correlation between clusters of artists and musical genres. On the other hand, the collaboration network shows two different kinds of communities: rather small structures related to music bands and geographic zones, and much bigger communities built upon collaborative clusters with a high number of participants related through the period the artists were active. Finally, we detect the leading artists inside their corresponding communities and analyze their roles in the network by looking at a few topological properties of the nodes.

Quantum network theory

International Nuclear Information System (INIS)

Yurke, B.; Denker, J.S.

1984-01-01

A general approach, within the framework of canonical quantization, is described for analyzing the quantum behavior of complicated electronic circuits. This approach is capable of dealing with electrical networks having nonlinear or dissipative elements. The techniques are used to analyze a degenerate parametric amplifier, a device capable of generating squeezed coherent state signals. A circuit capable of performing back-action-evading electrical measurements is also discussed. (author)

ARTIFICIAL NEURAL-NETWORK PREDICTIONS OF URINARY CALCULUS COMPOSITIONS ANALYZED WITH INFRARED-SPECTROSCOPY

NARCIS (Netherlands)

VOLMER, M; WOLTHERS, BG; METTING, HJ; DEHAAN, THY; COENEGRACHT, PMJ; VANDERSLIK, W

Infrared (IR) spectroscopy is used to analyze urinary calculus (renal stone) constituents. However, interpretation of IR spectra for quantifying urinary calculus constituents in mixtures is difficult, requiring expert knowledge by trained technicians. In our laboratory IR spectra of unknown calculi

Knowledge networking on Sociology: network analysis of blogs, YouTube videos and tweets about Sociology

Directory of Open Access Journals (Sweden)

Julián Cárdenas

2017-06-01

Full Text Available While mainstream scientific knowledge production have been widely studied in recent years with the development of scientometrics and bibliometrics, an emergent number of studies have focused on alternative sources of production and dissemination of knowledge such as blogs, YouTube videos and comments on Twitter. These online sources of knowledge become relevant in fields such as Sociology, where some academics seek to bring the sociological knowledge to the general population. To explore which knowledge on Sociology is produced and disseminated, and how is organized in these online sources, we analyze the knowledge networking of blogs, YouTube videos and tweets on Twitter using network analysis approach. Specifically, the present research analyzes the hyperlink network of the main blogs on Sociology, the networks of tags used to classify videos on Sociology hosted on YouTube, and the network of hashtags linked to #sociología on Twitter. The main results point out the existence of a cohesive and strongly connected community of blogs on Sociology, the very low presence of YouTube videos on Sociology in Spanish, and Sociology on Twitter is linked to others social sciences, classical scholars and social media

UMA/GAN network architecture analysis

Science.gov (United States)

Yang, Liang; Li, Wensheng; Deng, Chunjian; Lv, Yi

2009-07-01

This paper is to critically analyze the architecture of UMA which is one of Fix Mobile Convergence (FMC) solutions, and also included by the third generation partnership project(3GPP). In UMA/GAN network architecture, UMA Network Controller (UNC) is the key equipment which connects with cellular core network and mobile station (MS). UMA network could be easily integrated into the existing cellular networks without influencing mobile core network, and could provides high-quality mobile services with preferentially priced indoor voice and data usage. This helps to improve subscriber's experience. On the other hand, UMA/GAN architecture helps to integrate other radio technique into cellular network which includes WiFi, Bluetooth, and WiMax and so on. This offers the traditional mobile operators an opportunity to integrate WiMax technique into cellular network. In the end of this article, we also give an analysis of potential influence on the cellular core networks ,which is pulled by UMA network.

Coarse graining for synchronization in directed networks

Science.gov (United States)

Zeng, An; Lü, Linyuan

2011-05-01

Coarse-graining model is a promising way to analyze and visualize large-scale networks. The coarse-grained networks are required to preserve statistical properties as well as the dynamic behaviors of the initial networks. Some methods have been proposed and found effective in undirected networks, while the study on coarse-graining directed networks lacks of consideration. In this paper we proposed a path-based coarse-graining (PCG) method to coarse grain the directed networks. Performing the linear stability analysis of synchronization and numerical simulation of the Kuramoto model on four kinds of directed networks, including tree networks and variants of Barabási-Albert networks, Watts-Strogatz networks, and Erdös-Rényi networks, we find our method can effectively preserve the network synchronizability.

3-D diffusion program XYZ-MUGDI with data-analyzing program XYZFF

Energy Technology Data Exchange (ETDEWEB)

Siewers, H

1976-01-01

The XYZ-MUGDI program solves boudary value and eigenvalue problems for three-dimensional heterogeneous configurations in X, Y, Z-geometry for a maximum of four energy groups. The program XYZFF is a program for analyzing data; with it especially the average and maximum form factors for arbitrary coarse-meshed networks can be evaluated.

Modeling and Analyzing Intrusion Attempts to a Computer Network Operating in a Defense in Depth Posture

National Research Council Canada - National Science Library

Givens, Mark

2004-01-01

In order to ensure the confidentially, integrity, and availability of networked resources operating on the Global Information Grid, the Department of Defense has incorporated a "Defense-in-Depth" posture...

Towards Effective Intra-flow Network Coding in Software Defined Wireless Mesh Networks

Directory of Open Access Journals (Sweden)

Donghai Zhu

2016-01-01

Full Text Available Wireless Mesh Networks (WMNs have potential to provide convenient broadband wireless Internet access to mobile users.With the support of Software-Defined Networking (SDN paradigm that separates control plane and data plane, WMNs can be easily deployed and managed. In addition, by exploiting the broadcast nature of the wireless medium and the spatial diversity of multi-hop wireless networks, intra-flow network coding has shown a greater benefit in comparison with traditional routing paradigms in data transmission for WMNs. In this paper, we develop a novel OpenCoding protocol, which combines the SDN technique with intra-flow network coding for WMNs. Our developed protocol can simplify the deployment and management of the network and improve network performance. In OpenCoding, a controller that works on the control plane makes routing decisions for mesh routers and the hop-by-hop forwarding function is replaced by network coding functions in data plane. We analyze the overhead of OpenCoding. Through a simulation study, we show the effectiveness of the OpenCoding protocol in comparison with existing schemes. Our data shows that OpenCoding outperforms both traditional routing and intra-flow network coding schemes.

Integration of biological networks and gene expression data using Cytoscape

DEFF Research Database (Denmark)

Cline, M.S.; Smoot, M.; Cerami, E.

2007-01-01

of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules......Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context...... and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape....

Does where you stand depend on who you behave? Networking behavior as an alternative explanation for gender differences in network structure

NARCIS (Netherlands)

Gremmen, I.; Akkerman, A.; Benschop, Y.

2013-01-01

The purpose of this study is to gain insight into the relations between gender, networking behavior and network structure, in order to investigate the relevance of gender for organizational networks. Semi-structured interviews with 39 white, Dutch, women and men account managers were analyzed both

Preparing for a Career as a Network Engineer

Science.gov (United States)

Morris, Gerard; Fustos, Janos; Haga, Wayne

2012-01-01

A network engineer is an Information Technology (IT) professional who designs, implements, maintains, and troubleshoots computer networks. While the United States is still experiencing relatively high unemployment, demand for network engineers remains strong. To determine what skills employers are looking for, data was collected and analyzed from…

The modularity of pollination networks

DEFF Research Database (Denmark)

Olesen, Jens Mogens; Bascompte, J.; Dupont, Yoko

2007-01-01

In natural communities, species and their interactions are often organized as nonrandom networks, showing distinct and repeated complex patterns. A prevalent, but poorly explored pattern is ecological modularity, with weakly interlinked subsets of species (modules), which, however, internally...... consist of strongly connected species. The importance of modularity has been discussed for a long time, but no consensus on its prevalence in ecological networks has yet been reached. Progress is hampered by inadequate methods and a lack of large datasets. We analyzed 51 pollination networks including...... almost 10,000 species and 20,000 links and tested for modularity by using a recently developed simulated annealing algorithm. All networks with >150 plant and pollinator species were modular, whereas networks with

The use of network theory to model disparate ship design information

Science.gov (United States)

Rigterink, Douglas; Piks, Rebecca; Singer, David J.

2014-06-01

This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship's distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.

Privacy Breach Analysis in Social Networks

Science.gov (United States)

Nagle, Frank

This chapter addresses various aspects of analyzing privacy breaches in social networks. We first review literature that defines three types of privacy breaches in social networks: interactive, active, and passive. We then survey the various network anonymization schemes that have been constructed to address these privacy breaches. After exploring these breaches and anonymization schemes, we evaluate a measure for determining the level of anonymity inherent in a network graph based on its topological structure. Finally, we close by emphasizing the difficulty of anonymizing social network data while maintaining usability for research purposes and offering areas for future work.

The Effect of Social Network Diagrams on a Virtual Network of Practice: A Korean Case

Science.gov (United States)

Jo, Il-Hyun

2009-01-01

This study investigates the effect of the presentation of social network diagrams on virtual team members' interaction behavior via e-mail. E-mail transaction data from 22 software developers in a Korean IT company was analyzed and depicted as diagrams by social network analysis (SNA), and presented to the members as an intervention. Results…

Detection of network attacks based on adaptive resonance theory

Science.gov (United States)

Bukhanov, D. G.; Polyakov, V. M.

2018-05-01

The paper considers an approach to intrusion detection systems using a neural network of adaptive resonant theory. It suggests the structure of an intrusion detection system consisting of two types of program modules. The first module manages connections of user applications by preventing the undesirable ones. The second analyzes the incoming network traffic parameters to check potential network attacks. After attack detection, it notifies the required stations using a secure transmission channel. The paper describes the experiment on the detection and recognition of network attacks using the test selection. It also compares the obtained results with similar experiments carried out by other authors. It gives findings and conclusions on the sufficiency of the proposed approach. The obtained information confirms the sufficiency of applying the neural networks of adaptive resonant theory to analyze network traffic within the intrusion detection system.

ANALYZING SOCIAL NETWORKS FROM THE PERSPECTIVE OF MARKETING DECISIONS

Directory of Open Access Journals (Sweden)

Logica BANICA

2015-12-01

Full Text Available Nowadays, the Web became more than a space for product presentation, but also a capitalization market (e-commerce and an efficient way to know the customer preferences and to meet their requirements. Large companies have the financial potential to use various marketing strategies and, in particular, digital-marketing. Instead, small businesses are looking for lower cost or no cost methods (also called guerrilla marketing. A small company can compete with a large company by approaching a particular range of products that excel in quality, and also by inventiveness in the marketing strategy. During 2010-2015 the potential of Information Technology and Communications (IT&C sector was proved for the companies which aimed towards modernization of technologies and introduced new strategies in order to commercialize new products. An important challenge for companies was to be aware of the changes in customer behaviour, using social networks software. Finally, research centers have set up new IT&C services and improved marketing and communications following the crisis. More and more companies invest in analytic tools to monitor their marketing strategies and Big Data becomes extremely useful for this purpose, using information like customer demographics and spending habits, oscillation between simplicity, comfort and glamour. There are various tools that can transform in a very short time, massive amounts of data into real business value in a very short time, helping companies and retailers to understand, at any point in the product lifecycle, which trends are gaining and which are losing ground. These insights give them the possibility to reduce the risk of not selling their products by making adjustments to the design, production or promotional strategies, before putting the goods on the market. In this paper we aim to present the advantages of exploring customer requirements from social media for marketing strategy of an enterprise, by using SNA

Current-flow efficiency of networks

Science.gov (United States)

Liu, Kai; Yan, Xiaoyong

2018-02-01

Many real-world networks, from infrastructure networks to social and communication networks, can be formulated as flow networks. How to realistically measure the transport efficiency of these networks is of fundamental importance. The shortest-path-based efficiency measurement has limitations, as it assumes that flow travels only along those shortest paths. Here, we propose a new metric named current-flow efficiency, in which we calculate the average reciprocal effective resistance between all pairs of nodes in the network. This metric takes the multipath effect into consideration and is more suitable for measuring the efficiency of many real-world flow equilibrium networks. Moreover, this metric can handle a disconnected graph and can thus be used to identify critical nodes and edges from the efficiency-loss perspective. We further analyze how the topological structure affects the current-flow efficiency of networks based on some model and real-world networks. Our results enable a better understanding of flow networks and shed light on the design and improvement of such networks with higher transport efficiency.

Export policies for multi-domain WDM networks

DEFF Research Database (Denmark)

Manolova, Anna Vasileva; Ruepp, Sarah Renée

2010-01-01

We analyze the performance of six export policies for a multi-domain routing protocol in WDM networks. We show that providing many AS-disjoint paths for survivability and load-balancing does not necessarily guarantee the lowest connection blocking......We analyze the performance of six export policies for a multi-domain routing protocol in WDM networks. We show that providing many AS-disjoint paths for survivability and load-balancing does not necessarily guarantee the lowest connection blocking...

Flows in networks under fuzzy conditions

CERN Document Server

Bozhenyuk, Alexander Vitalievich; Kacprzyk, Janusz; Rozenberg, Igor Naymovich

2017-01-01

This book offers a comprehensive introduction to fuzzy methods for solving flow tasks in both transportation and networks. It analyzes the problems of minimum cost and maximum flow finding with fuzzy nonzero lower flow bounds, and describes solutions to minimum cost flow finding in a network with fuzzy arc capacities and transmission costs. After a concise introduction to flow theory and tasks, the book analyzes two important problems. The first is related to determining the maximum volume for cargo transportation in the presence of uncertain network parameters, such as environmental changes, measurement errors and repair work on the roads. These parameters are represented here as fuzzy triangular, trapezoidal numbers and intervals. The second problem concerns static and dynamic flow finding in networks under fuzzy conditions, and an effective method that takes into account the network’s transit parameters is presented here. All in all, the book provides readers with a practical reference guide to state-of-...

A random network based, node attraction facilitated network evolution method

Directory of Open Access Journals (Sweden)

WenJun Zhang

2016-03-01

Full Text Available In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999 of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor Lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor Lamda can reflect various effects of the node degree on connection mechanism. Even the changes of Lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.

A Directed Network of Greek and Roman Mythology

OpenAIRE

Choi, Yeon-Mu; Kim, Hyun-Joo

2005-01-01

We study the Greek and Roman mythology using the network theory. We construct a directed network by using a dictionary of Greek and Roman mythology in which the nodes represent the entries listed in the dictionary and we make directional links from an entry to other entries that appear in its explanatory part. We find that this network is clearly not a random network but a directed scale-free network. Also measuring the various quantities which characterize the mythology network, we analyze t...

A comparative study of artificial neural network and multivariate regression analysis to analyze optimum renal stone fragmentation by extracorporeal shock wave lithotripsy

Directory of Open Access Journals (Sweden)

Goyal Neeraj

2010-01-01

Full Text Available To compare the accuracy of artificial neural network (ANN analysis and multi-variate regression analysis (MVRA for renal stone fragmentation by extracorporeal shock wave lithotripsy (ESWL. A total of 276 patients with renal calculus were treated by ESWL during December 2001 to December 2006. Of them, the data of 196 patients were used for training the ANN. The predictability of trained ANN was tested on 80 subsequent patients. The input data include age of patient, stone size, stone burden, number of sittings and urinary pH. The output values (predicted values were number of shocks and shock power. Of these 80 patients, the input was analyzed and output was also calculated by MVRA. The output values (predicted values from both the methods were compared and the results were drawn. The predicted and observed values of shock power and number of shocks were compared using 1:1 slope line. The results were calculated as coefficient of correlation (COC (r2 . For prediction of power, the MVRA COC was 0.0195 and ANN COC was 0.8343. For prediction of number of shocks, the MVRA COC was 0.5726 and ANN COC was 0.9329. In conclusion, ANN gives better COC than MVRA, hence could be a better tool to analyze the optimum renal stone fragmentation by ESWL.

A comparative study of artificial neural network and multivariate regression analysis to analyze optimum renal stone fragmentation by extracorporeal shock wave lithotripsy

International Nuclear Information System (INIS)

Neeraj K Goyal, Abhay Kumar; Sameer Trivedi

2010-01-01

To compare the accuracy of artificial neural network (ANN) analysis and multivariate regression analysis (MVRA) for renal stone fragmentation by extracorporeal shock wave lithotripsy (ESWL). A total of 276 patients with renal calculus were treated by ESWL during December 2001 to December 2006. Of them, the data of 196 patients were used for training the ANN. The predictability of trained ANN was tested on 80 subsequent patients. The input data include age of patient, stone size, stone burden, number of sittings and urinary pH. The output values (predicted values) were number of shocks and shock power. Of these 80 patients, the input was analyzed and output was also calculated by MVRA. The output values (predicted values) from both the methods were compared and the results were drawn. The predicted and observed values of shock power and number of shocks were compared using 1:1 slope line. The results were calculated as coefficient of correlation (COC) (r2 ). For prediction of power, the MVRA COC was 0.0195 and ANN COC was 0.8343. For prediction of number of shocks, the MVRA COC was 0.5726 and ANN COC was 0.9329. In conclusion, ANN gives better COC than MVRA, hence could be a better tool to analyze the optimum renal stone fragmentation by ESWL (Author).

Design and microwave test of an ultrawideband input/output structure for sheet beam travelling wave tubes

International Nuclear Information System (INIS)

Shu, Guoxiang; Wang, Jianxun; Liu, Guo; Yang, Liya; Luo, Yong; Wang, Shafei

2015-01-01

Broadband operation is of great importance for the applications of travelling wave tubes such as high-data communication and wideband radar. An input/output (I/O) structure operating with broadband property plays a significant role to achieve these applications. In this paper, a Y-type branch waveguide (YTBW) coupler and its improvements are proposed and utilized to construct an extremely wideband I/O structure to ensure the broadband operation for sheet beam travelling wave tubes (SB-TWTs). Cascaded reflection resonators are utilized to improve the isolation characteristic and transmission efficiency. Furthermore, to minimize the reflectivity of the port connected with the RF circuit, wave-absorbing material (WAM) is loaded in the resonator. Simulation results for the YTBW loaded with WAM predict an excellent performance with a 50.2% relative bandwidth for port reflectivity under −15 dB, transmission up to −1.5 dB, and meanwhile isolation under −20 dB. In addition, the coupler has a relatively compact configuration and the beam tunnel can be widened, which is beneficial for the propagation of the electrons. A Q-band YTBW loaded with two reflection resonators is fabricated and microwave tested. Vector network analyzer (VNA) measured results have an excellent agreement with our simulation, which verify our theoretical analysis and simulation calculation

Investigation of Unequal Planar Wireless Electricity Device for Efficient Wireless Power Transfer

Directory of Open Access Journals (Sweden)

M. H. Mohd Salleh

2017-04-01

Full Text Available This article focuses on the design and investigation of a pair of unequally sized wireless electricity (Witricity devices that are equipped with integrated planar coil strips. The proposed pair of devices consists of two different square-shaped resonator sizes of 120 mm × 120 mm and 80 mm × 80 mm, acting as a transmitter and receiver, respectively. The devices are designed, simulated and optimized using the CST Microwave Studio software prior to being fabricated and verified using a vector network analyzer (VNA. The surface current results of the coupled devices indicate a good current density at 10 mm to 30 mm distance range. This good current density demonstrates that the coupled devices’ surface has more electric current per unit area, which leads to a good performance up to 30 mm range. Hence, the results also reveal good coupling efficiency between the coupled devices, which is approximately 54.5% at up to a 30 mm distance, with both devices axially aligned. In addition, a coupling efficiency of 50% is achieved when a maximum lateral misalignment (LM of 10 mm, and a varied angular misalignment (AM from 0° to 40° are implemented to the proposed device.

Design and microwave test of an ultrawideband input/output structure for sheet beam travelling wave tubes

Energy Technology Data Exchange (ETDEWEB)

Shu, Guoxiang; Wang, Jianxun; Liu, Guo; Yang, Liya; Luo, Yong [School of Physical Electronics, University of Electronic Science and Technology of China, Chengdu 610054 (China); Wang, Shafei [North Electronic Device Research Institution, P.O. Box 947, Beijing 100141 (China)

2015-06-15

Broadband operation is of great importance for the applications of travelling wave tubes such as high-data communication and wideband radar. An input/output (I/O) structure operating with broadband property plays a significant role to achieve these applications. In this paper, a Y-type branch waveguide (YTBW) coupler and its improvements are proposed and utilized to construct an extremely wideband I/O structure to ensure the broadband operation for sheet beam travelling wave tubes (SB-TWTs). Cascaded reflection resonators are utilized to improve the isolation characteristic and transmission efficiency. Furthermore, to minimize the reflectivity of the port connected with the RF circuit, wave-absorbing material (WAM) is loaded in the resonator. Simulation results for the YTBW loaded with WAM predict an excellent performance with a 50.2% relative bandwidth for port reflectivity under −15 dB, transmission up to −1.5 dB, and meanwhile isolation under −20 dB. In addition, the coupler has a relatively compact configuration and the beam tunnel can be widened, which is beneficial for the propagation of the electrons. A Q-band YTBW loaded with two reflection resonators is fabricated and microwave tested. Vector network analyzer (VNA) measured results have an excellent agreement with our simulation, which verify our theoretical analysis and simulation calculation.

The effect of BaM/PANI composition with epoxy paint matrix on single and double layers coating with spray coating method for radar absorbing materials applications

Science.gov (United States)

Widyastuti, Fajarin, Rindang; Pratiwi, Vania Mitha; Kholid, Rifki Rachman; Habib, Abdulloh

2018-04-01

In this study, RAM composite has been succesfully synthesized by mixing BaM as magnetic materials and PANI as conductive materials. BaM and PANI materials were prepared separately by solid state method and polymerization method, respectively. To investigated the presence of BaM phase and magnetic property of the as prepared BaM, XRD pert PAN analytical and VSM 250 Dexing Magnet were employed. Inductance Capacitance Resistance technique was carried out to measure electrical conductivity of the synthesized PANI materials. In order to further characterized the structural features of BaM and PANI, SEM-EDX FEI 850 and FTIR characterizations were conducted. RAM composite was prepared by mixing BaM and PANI powders with ultrasonic cleaner. Afterwards, VNA (Vector Network Analyzer) characterization was carried out to determine reflection loss value of RAM by applying mixed RAM composite and epoxy paint on aluminum plate using spray gun. Microscopic characterization was employed to investigated the distribution of RAM particles on the substrate. It was found that reflection loss value as low as -27.153 dB was achieved when applied 15 wt% BaM/PANi composite at 100.6 µm thickness. In addition, the absorption of electromagnetic waves value increase as the addition of RAM composite composition increases.

Statistical mechanics of the international trade network.

Science.gov (United States)

Fronczak, Agata; Fronczak, Piotr

2012-05-01

Analyzing real data on international trade covering the time interval 1950-2000, we show that in each year over the analyzed period the network is a typical representative of the ensemble of maximally random weighted networks, whose directed connections (bilateral trade volumes) are only characterized by the product of the trading countries' GDPs. It means that time evolution of this network may be considered as a continuous sequence of equilibrium states, i.e., a quasistatic process. This, in turn, allows one to apply the linear response theory to make (and also verify) simple predictions about the network. In particular, we show that bilateral trade fulfills a fluctuation-response theorem, which states that the average relative change in imports (exports) between two countries is a sum of the relative changes in their GDPs. Yearly changes in trade volumes prove that the theorem is valid.

Gossip algorithms in quantum networks

International Nuclear Information System (INIS)

Siomau, Michael

2017-01-01

Gossip algorithms is a common term to describe protocols for unreliable information dissemination in natural networks, which are not optimally designed for efficient communication between network entities. We consider application of gossip algorithms to quantum networks and show that any quantum network can be updated to optimal configuration with local operations and classical communication. This allows to speed-up – in the best case exponentially – the quantum information dissemination. Irrespective of the initial configuration of the quantum network, the update requiters at most polynomial number of local operations and classical communication. - Highlights: • We analyze the performance of gossip algorithms in quantum networks. • Local operations and classical communication (LOCC) can speed the performance up. • The speed-up is exponential in the best case; the number of LOCC is polynomial.

Gossip algorithms in quantum networks

Energy Technology Data Exchange (ETDEWEB)

Siomau, Michael, E-mail: siomau@nld.ds.mpg.de [Physics Department, Jazan University, P.O. Box 114, 45142 Jazan (Saudi Arabia); Network Dynamics, Max Planck Institute for Dynamics and Self-Organization (MPIDS), 37077 Göttingen (Germany)

2017-01-23

Gossip algorithms is a common term to describe protocols for unreliable information dissemination in natural networks, which are not optimally designed for efficient communication between network entities. We consider application of gossip algorithms to quantum networks and show that any quantum network can be updated to optimal configuration with local operations and classical communication. This allows to speed-up – in the best case exponentially – the quantum information dissemination. Irrespective of the initial configuration of the quantum network, the update requiters at most polynomial number of local operations and classical communication. - Highlights: • We analyze the performance of gossip algorithms in quantum networks. • Local operations and classical communication (LOCC) can speed the performance up. • The speed-up is exponential in the best case; the number of LOCC is polynomial.

Empirical Studies on the Network of Social Groups: The Case of Tencent QQ.

Science.gov (United States)

You, Zhi-Qiang; Han, Xiao-Pu; Lü, Linyuan; Yeung, Chi Ho

2015-01-01

Participation in social groups are important but the collective behaviors of human as a group are difficult to analyze due to the difficulties to quantify ordinary social relation, group membership, and to collect a comprehensive dataset. Such difficulties can be circumvented by analyzing online social networks. In this paper, we analyze a comprehensive dataset released from Tencent QQ, an instant messenger with the highest market share in China. Specifically, we analyze three derivative networks involving groups and their members-the hypergraph of groups, the network of groups and the user network-to reveal social interactions at microscopic and mesoscopic level. Our results uncover interesting behaviors on the growth of user groups, the interactions between groups, and their relationship with member age and gender. These findings lead to insights which are difficult to obtain in social networks based on personal contacts.

Neural Networks

International Nuclear Information System (INIS)

Smith, Patrick I.

2003-01-01

Physicists use large detectors to measure particles created in high-energy collisions at particle accelerators. These detectors typically produce signals indicating either where ionization occurs along the path of the particle, or where energy is deposited by the particle. The data produced by these signals is fed into pattern recognition programs to try to identify what particles were produced, and to measure the energy and direction of these particles. Ideally, there are many techniques used in this pattern recognition software. One technique, neural networks, is particularly suitable for identifying what type of particle caused by a set of energy deposits. Neural networks can derive meaning from complicated or imprecise data, extract patterns, and detect trends that are too complex to be noticed by either humans or other computer related processes. To assist in the advancement of this technology, Physicists use a tool kit to experiment with several neural network techniques. The goal of this research is interface a neural network tool kit into Java Analysis Studio (JAS3), an application that allows data to be analyzed from any experiment. As the final result, a physicist will have the ability to train, test, and implement a neural network with the desired output while using JAS3 to analyze the results or output. Before an implementation of a neural network can take place, a firm understanding of what a neural network is and how it works is beneficial. A neural network is an artificial representation of the human brain that tries to simulate the learning process [5]. It is also important to think of the word artificial in that definition as computer programs that use calculations during the learning process. In short, a neural network learns by representative examples. Perhaps the easiest way to describe the way neural networks learn is to explain how the human brain functions. The human brain contains billions of neural cells that are responsible for processing

Temporal networks

Science.gov (United States)

Holme, Petter; Saramäki, Jari

2012-10-01

A great variety of systems in nature, society and technology-from the web of sexual contacts to the Internet, from the nervous system to power grids-can be modeled as graphs of vertices coupled by edges. The network structure, describing how the graph is wired, helps us understand, predict and optimize the behavior of dynamical systems. In many cases, however, the edges are not continuously active. As an example, in networks of communication via e-mail, text messages, or phone calls, edges represent sequences of instantaneous or practically instantaneous contacts. In some cases, edges are active for non-negligible periods of time: e.g., the proximity patterns of inpatients at hospitals can be represented by a graph where an edge between two individuals is on throughout the time they are at the same ward. Like network topology, the temporal structure of edge activations can affect dynamics of systems interacting through the network, from disease contagion on the network of patients to information diffusion over an e-mail network. In this review, we present the emergent field of temporal networks, and discuss methods for analyzing topological and temporal structure and models for elucidating their relation to the behavior of dynamical systems. In the light of traditional network theory, one can see this framework as moving the information of when things happen from the dynamical system on the network, to the network itself. Since fundamental properties, such as the transitivity of edges, do not necessarily hold in temporal networks, many of these methods need to be quite different from those for static networks. The study of temporal networks is very interdisciplinary in nature. Reflecting this, even the object of study has many names-temporal graphs, evolving graphs, time-varying graphs, time-aggregated graphs, time-stamped graphs, dynamic networks, dynamic graphs, dynamical graphs, and so on. This review covers different fields where temporal graphs are considered

Low content Ag-coated poly(acrylonitrile) microspheres and graphene for enhanced microwave absorption performance epoxy composites

Science.gov (United States)

Zhang, Bin; Wang, Jun; Chen, Xiaocheng; Su, Xiaogang; Zou, Yi; Huo, Siqi; Chen, Wei; Wang, Junpeng

2018-04-01

Silver nanoparticles was uniformly anchored on the surface of hollow poly(acrylonitrile) microspheres with a facile chemical method using hydrazine hydrate as reductant. Integrating these conducting hollow spheres (PANS@Ag) with chemical reduced graphene oxide (RGO) dispersed in epoxy resin, a lightweight microwave absorber was successfully prepared with enhanced microwave absorption performance. The chemical constitution and surface morphology of as-synthesized RGO and PANS@Ag powders were characterized by XRD, XPS, FE-SEM and SAED, while the electromagnetic properties of these different proportion PANS@Ag-RGO/EP samples were analyzed through vector network analyzer (VNA). The minimum reflection loss (RL) could reach up to ‑28.1 dB at 8.8 GHz with a layer thickness of 2 mm, and the corresponding effective absorption bandwidth (RL values less than ‑10 dB) was from 7.9 GHz to 9.8 GHz. However, the dosage of PANS@Ag and RGO was merely 3 wt% and 1 wt%, respectively. As the content of PANS@Ag powders decreased to 1 wt%, the PANS@Ag-RGO/EP samples still retained effective microwave absorption performance and the optimal RL was ‑14.7 dB. The density of as-prepared absorbers was in the range of 0.49 ∼ 0.87 g cm‑3. The low content, low density and enhanced microwave absorption performance endow the hybrid composites with competitive application prospect in stealth technology field.

Malware Propagation and Prevention Model for Time-Varying Community Networks within Software Defined Networks

Directory of Open Access Journals (Sweden)

Lan Liu

2017-01-01

Full Text Available As the adoption of Software Defined Networks (SDNs grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the network as communities and links that are dense in subnets but sparse between subnets. Using numerical simulation and theoretical analysis, we find that the efficiency of network malware propagation in this model depends on the mobility rate q of the nodes between subnets. We also find that there exists a mobility rate threshold qc. The network malware will spread in the SDN when the mobility rate q>qc. The malware will survive when q>qc and perish when qnetwork malware and provide a theoretical basis to reduce and prevent network security incidents.

Research on Information Sharing Mechanism of Network Organization Based on Evolutionary Game

Science.gov (United States)

Wang, Lin; Liu, Gaozhi

2018-02-01

This article first elaborates the concept and effect of network organization, and the ability to share information is analyzed, secondly introduces the evolutionary game theory, network organization for information sharing all kinds of limitations, establishes the evolutionary game model, analyzes the dynamic evolution of network organization of information sharing, through reasoning and evolution. The network information sharing by the initial state and two sides of the game payoff matrix of excess profits and information is the information sharing of cost and risk sharing are the influence of network organization node information sharing decision.

Identifying Jets Using Artifical Neural Networks

Science.gov (United States)

Rosand, Benjamin; Caines, Helen; Checa, Sofia

2017-09-01

We investigate particle jet interactions with the Quark Gluon Plasma (QGP) using artificial neural networks modeled on those used in computer image recognition. We create jet images by binning jet particles into pixels and preprocessing every image. We analyzed the jets with a Multi-layered maxout network and a convolutional network. We demonstrate each network's effectiveness in differentiating simulated quenched jets from unquenched jets, and we investigate the method that the network uses to discriminate among different quenched jet simulations. Finally, we develop a greater understanding of the physics behind quenched jets by investigating what the network learnt as well as its effectiveness in differentiating samples. Yale College Freshman Summer Research Fellowship in the Sciences and Engineering.

Software ecosystems analyzing and managing business networks in the software industry

CERN Document Server

Jansen, S; Cusumano, MA

2013-01-01

This book describes the state-of-the-art of software ecosystems. It constitutes a fundamental step towards an empirically based, nuanced understanding of the implications for management, governance, and control of software ecosystems. This is the first book of its kind dedicated to this emerging field and offers guidelines on how to analyze software ecosystems; methods for managing and growing; methods on transitioning from a closed software organization to an open one; and instruments for dealing with open source, licensing issues, product management and app stores. It is unique in bringing t

Analyzing the disturbing effects of microwave probe on mm-wave antenna pattern measurements

NARCIS (Netherlands)

Reniers, A.C.F.; Dommele, van A.R.; Huang, M.D.; Herben, M.H.A.J.

2014-01-01

Realizing an antenna measurement environment with specific supporting structures and interconnection between the antenna under test and measurement equipment like a vector network analyzer in the mm-wave range is not as trivial as for the much lower frequencies. Commonly used interconnection methods

The use of network theory to model disparate ship design information

Directory of Open Access Journals (Sweden)

Douglas Rigterink

2014-06-01

Full Text Available This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship's distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.

The use of network theory to model disparate ship design information

Directory of Open Access Journals (Sweden)

Rigterink Douglas

2014-06-01

Full Text Available This paper introduces the use of network theory to model and analyze disparate ship design information. This work will focus on a ship’s distributed systems and their intra- and intersystem structures and interactions. The three system to be analyzed are: a passageway system, an electrical system, and a fire fighting system. These systems will be analyzed individually using common network metrics to glean information regarding their structures and attributes. The systems will also be subjected to community detection algorithms both separately and as a multiplex network to compare their similarities, differences, and interactions. Network theory will be shown to be useful in the early design stage due to its simplicity and ability to model any shipboard system.

Network performance analysis

CERN Document Server

Bonald, Thomas

2013-01-01

The book presents some key mathematical tools for the performance analysis of communication networks and computer systems.Communication networks and computer systems have become extremely complex. The statistical resource sharing induced by the random behavior of users and the underlying protocols and algorithms may affect Quality of Service.This book introduces the main results of queuing theory that are useful for analyzing the performance of these systems. These mathematical tools are key to the development of robust dimensioning rules and engineering methods. A number of examples i

Application of a neural network for reflectance spectrum classification

Science.gov (United States)

Yang, Gefei; Gartley, Michael

2017-05-01

Traditional reflectance spectrum classification algorithms are based on comparing spectrum across the electromagnetic spectrum anywhere from the ultra-violet to the thermal infrared regions. These methods analyze reflectance on a pixel by pixel basis. Inspired by high performance that Convolution Neural Networks (CNN) have demonstrated in image classification, we applied a neural network to analyze directional reflectance pattern images. By using the bidirectional reflectance distribution function (BRDF) data, we can reformulate the 4-dimensional into 2 dimensions, namely incident direction × reflected direction × channels. Meanwhile, RIT's micro-DIRSIG model is utilized to simulate additional training samples for improving the robustness of the neural networks training. Unlike traditional classification by using hand-designed feature extraction with a trainable classifier, neural networks create several layers to learn a feature hierarchy from pixels to classifier and all layers are trained jointly. Hence, the our approach of utilizing the angular features are different to traditional methods utilizing spatial features. Although training processing typically has a large computational cost, simple classifiers work well when subsequently using neural network generated features. Currently, most popular neural networks such as VGG, GoogLeNet and AlexNet are trained based on RGB spatial image data. Our approach aims to build a directional reflectance spectrum based neural network to help us to understand from another perspective. At the end of this paper, we compare the difference among several classifiers and analyze the trade-off among neural networks parameters.

Serial Network Flow Monitor

Science.gov (United States)

Robinson, Julie A.; Tate-Brown, Judy M.

2009-01-01

Using a commercial software CD and minimal up-mass, SNFM monitors the Payload local area network (LAN) to analyze and troubleshoot LAN data traffic. Validating LAN traffic models may allow for faster and more reliable computer networks to sustain systems and science on future space missions. Research Summary: This experiment studies the function of the computer network onboard the ISS. On-orbit packet statistics are captured and used to validate ground based medium rate data link models and enhance the way that the local area network (LAN) is monitored. This information will allow monitoring and improvement in the data transfer capabilities of on-orbit computer networks. The Serial Network Flow Monitor (SNFM) experiment attempts to characterize the network equivalent of traffic jams on board ISS. The SNFM team is able to specifically target historical problem areas including the SAMS (Space Acceleration Measurement System) communication issues, data transmissions from the ISS to the ground teams, and multiple users on the network at the same time. By looking at how various users interact with each other on the network, conflicts can be identified and work can begin on solutions. SNFM is comprised of a commercial off the shelf software package that monitors packet traffic through the payload Ethernet LANs (local area networks) on board ISS.

YANA – a software tool for analyzing flux modes, gene-expression and enzyme activities

Directory of Open Access Journals (Sweden)

Engels Bernd

2005-06-01

Full Text Available Abstract Background A number of algorithms for steady state analysis of metabolic networks have been developed over the years. Of these, Elementary Mode Analysis (EMA has proven especially useful. Despite its low user-friendliness, METATOOL as a reliable high-performance implementation of the algorithm has been the instrument of choice up to now. As reported here, the analysis of metabolic networks has been improved by an editor and analyzer of metabolic flux modes. Analysis routines for expression levels and the most central, well connected metabolites and their metabolic connections are of particular interest. Results YANA features a platform-independent, dedicated toolbox for metabolic networks with a graphical user interface to calculate (integrating METATOOL, edit (including support for the SBML format, visualize, centralize, and compare elementary flux modes. Further, YANA calculates expected flux distributions for a given Elementary Mode (EM activity pattern and vice versa. Moreover, a dissection algorithm, a centralization algorithm, and an average diameter routine can be used to simplify and analyze complex networks. Proteomics or gene expression data give a rough indication of some individual enzyme activities, whereas the complete flux distribution in the network is often not known. As such data are noisy, YANA features a fast evolutionary algorithm (EA for the prediction of EM activities with minimum error, including alerts for inconsistent experimental data. We offer the possibility to include further known constraints (e.g. growth constraints in the EA calculation process. The redox metabolism around glutathione reductase serves as an illustration example. All software and documentation are available for download at http://yana.bioapps.biozentrum.uni-wuerzburg.de. Conclusion A graphical toolbox and an editor for METATOOL as well as a series of additional routines for metabolic network analyses constitute a new user

Understanding the context of network traffic alerts

NARCIS (Netherlands)

Cappers, B.C.M.; van Wijk, J.J.; Best, D.M.; Staheli, D.; Prigent, N.; Engle, S.; Harrison, L.

2016-01-01

For the protection of critical infrastructures against complex virus attacks, automated network traffic analysis and deep packet inspection are unavoidable. However, even with the use of network intrusion detection systems, the number of alerts is still too large to analyze manually. In addition,

A Network of Networks Perspective on Global Trade.

Science.gov (United States)

Maluck, Julian; Donner, Reik V

2015-01-01

Mutually intertwined supply chains in contemporary economy result in a complex network of trade relationships with a highly non-trivial topology that varies with time. In order to understand the complex interrelationships among different countries and economic sectors, as well as their dynamics, a holistic view on the underlying structural properties of this network is necessary. This study employs multi-regional input-output data to decompose 186 national economies into 26 industry sectors and utilizes the approach of interdependent networks to analyze the substructure of the resulting international trade network for the years 1990-2011. The partition of the network into national economies is observed to be compatible with the notion of communities in the sense of complex network theory. By studying internal versus cross-subgraph contributions to established complex network metrics, new insights into the architecture of global trade are obtained, which allow to identify key elements of global economy. Specifically, financial services and business activities dominate domestic trade whereas electrical and machinery industries dominate foreign trade. In order to further specify each national sector's role individually, (cross-)clustering coefficients and cross-betweenness are obtained for different pairs of subgraphs. The corresponding analysis reveals that specific industrial sectors tend to favor distinct directionality patterns and that the cross-clustering coefficient for geographically close country pairs is remarkably high, indicating that spatial factors are still of paramount importance for the organization of trade patterns in modern economy. Regarding the evolution of the trade network's substructure, globalization is well-expressed by trends of several structural characteristics (e.g., link density and node strength) in the interacting network framework. Extreme events, such as the financial crisis 2008/2009, are manifested as anomalies superimposed to

Increasing Scalability of Researcher Network Extraction from the Web

Science.gov (United States)

Asada, Yohei; Matsuo, Yutaka; Ishizuka, Mitsuru

Social networks, which describe relations among people or organizations as a network, have recently attracted attention. With the help of a social network, we can analyze the structure of a community and thereby promote efficient communications within it. We investigate the problem of extracting a network of researchers from the Web, to assist efficient cooperation among researchers. Our method uses a search engine to get the cooccurences of names of two researchers and calculates the streangth of the relation between them. Then we label the relation by analyzing the Web pages in which these two names cooccur. Research on social network extraction using search engines as ours, is attracting attention in Japan as well as abroad. However, the former approaches issue too many queries to search engines to extract a large-scale network. In this paper, we propose a method to filter superfluous queries and facilitates the extraction of large-scale networks. By this method we are able to extract a network of around 3000-nodes. Our experimental results show that the proposed method reduces the number of queries significantly while preserving the quality of the network as compared to former methods.

Modeling online social networks based on preferential linking

International Nuclear Information System (INIS)

Hu Hai-Bo; Chen Jun; Guo Jin-Li

2012-01-01

We study the phenomena of preferential linking in a large-scale evolving online social network and find that the linear preference holds for preferential creation, preferential acceptance, and preferential attachment. Based on the linear preference, we propose an analyzable model, which illustrates the mechanism of network growth and reproduces the process of network evolution. Our simulations demonstrate that the degree distribution of the network produced by the model is in good agreement with that of the real network. This work provides a possible bridge between the micro-mechanisms of network growth and the macrostructures of online social networks

Relationship between Social Networks Adoption and Social Intelligence

Science.gov (United States)

Gunduz, Semseddin

2017-01-01

The purpose of this study was to set forth the relationship between the individuals' states to adopt social networks and social intelligence and analyze both concepts according to various variables. Research data were collected from 1145 social network users in the online media by using the Adoption of Social Network Scale and Social Intelligence…

Chrysler improved numerical differencing analyzer for third generation computers CINDA-3G

Science.gov (United States)

Gaski, J. D.; Lewis, D. R.; Thompson, L. R.

1972-01-01

New and versatile method has been developed to supplement or replace use of original CINDA thermal analyzer program in order to take advantage of improved systems software and machine speeds of third generation computers. CINDA-3G program options offer variety of methods for solution of thermal analog models presented in network format.

Estimating network effects in China's mobile telecommunications

Institute of Scientific and Technical Information of China (English)

无

2005-01-01

A model is proposed along with empirical investigation to prove the existence of network effects in China's mobile telecommunications market. Futhernore, network effects on China's mobile telecommunications are estimated with a dynamic model. The structural parameters are identified from regression coefficients and the results are analyzed and compared with another literature. Data and estimation issues are also discussed. Conclusions are drawn that network effects are significant in China's mobile telecommunications market, and that ignoring network effects leads to bad policy making.

Network models in economics and finance

CERN Document Server

Pardalos, Panos; Rassias, Themistocles

2014-01-01

Using network models to investigate the interconnectivity in modern economic systems allows researchers to better understand and explain some economic phenomena. This volume presents contributions by known experts and active researchers in economic and financial network modeling. Readers are provided with an understanding of the latest advances in network analysis as applied to economics, finance, corporate governance, and investments. Moreover, recent advances in market network analysis  that focus on influential techniques for market graph analysis are also examined. Young researchers will find this volume particularly useful in facilitating their introduction to this new and fascinating field. Professionals in economics, financial management, various technologies, and network analysis, will find the network models presented in this book beneficial in analyzing the interconnectivity in modern economic systems.

Correlated measurement error hampers association network inference

NARCIS (Netherlands)

Kaduk, M.; Hoefsloot, H.C.J.; Vis, D.J.; Reijmers, T.; Greef, J. van der; Smilde, A.K.; Hendriks, M.M.W.B.

2014-01-01

Modern chromatography-based metabolomics measurements generate large amounts of data in the form of abundances of metabolites. An increasingly popular way of representing and analyzing such data is by means of association networks. Ideally, such a network can be interpreted in terms of the

Towards a network ecology of software ecosystems

DEFF Research Database (Denmark)

Hansen, Klaus Marius; Manikas, Konstantinos

2013-01-01

of the "network ecology'' approach to the analysis of natural ecosystems. In doing so, we mine the Maven central Java repository and analyze two OSGi ecosystems: Apache Felix and Eclipse Equinox. In particular, we define the concept of an ecosystem ``neighborhood'', apply network ecology metrics...

Simulating activation propagation in social networks using the graph theory

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František Dařena

2010-01-01

Full Text Available The social-network formation and analysis is nowadays one of objects that are in a focus of intensive research. The objective of the paper is to suggest the perspective of representing social networks as graphs, with the application of the graph theory to problems connected with studying the network-like structures and to study spreading activation algorithm for reasons of analyzing these structures. The paper presents the process of modeling multidimensional networks by means of directed graphs with several characteristics. The paper also demonstrates using Spreading Activation algorithm as a good method for analyzing multidimensional network with the main focus on recommender systems. The experiments showed that the choice of parameters of the algorithm is crucial, that some kind of constraint should be included and that the algorithm is able to provide a stable environment for simulations with networks.

Seeded Bayesian Networks: Constructing genetic networks from microarray data

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Quackenbush John

2008-07-01

Full Text Available Abstract Background DNA microarrays and other genomics-inspired technologies provide large datasets that often include hidden patterns of correlation between genes reflecting the complex processes that underlie cellular metabolism and physiology. The challenge in analyzing large-scale expression data has been to extract biologically meaningful inferences regarding these processes – often represented as networks – in an environment where the datasets are often imperfect and biological noise can obscure the actual signal. Although many techniques have been developed in an attempt to address these issues, to date their ability to extract meaningful and predictive network relationships has been limited. Here we describe a method that draws on prior information about gene-gene interactions to infer biologically relevant pathways from microarray data. Our approach consists of using preliminary networks derived from the literature and/or protein-protein interaction data as seeds for a Bayesian network analysis of microarray results. Results Through a bootstrap analysis of gene expression data derived from a number of leukemia studies, we demonstrate that seeded Bayesian Networks have the ability to identify high-confidence gene-gene interactions which can then be validated by comparison to other sources of pathway data. Conclusion The use of network seeds greatly improves the ability of Bayesian Network analysis to learn gene interaction networks from gene expression data. We demonstrate that the use of seeds derived from the biomedical literature or high-throughput protein-protein interaction data, or the combination, provides improvement over a standard Bayesian Network analysis, allowing networks involving dynamic processes to be deduced from the static snapshots of biological systems that represent the most common source of microarray data. Software implementing these methods has been included in the widely used TM4 microarray analysis package.

An Approach to Data Analysis in 5G Networks

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Lorena Isabel Barona López

2017-02-01

Full Text Available 5G networks expect to provide significant advances in network management compared to traditional mobile infrastructures by leveraging intelligence capabilities such as data analysis, prediction, pattern recognition and artificial intelligence. The key idea behind these actions is to facilitate the decision-making process in order to solve or mitigate common network problems in a dynamic and proactive way. In this context, this paper presents the design of Self-Organized Network Management in Virtualized and Software Defined Networks (SELFNET Analyzer Module, which main objective is to identify suspicious or unexpected situations based on metrics provided by different network components and sensors. The SELFNET Analyzer Module provides a modular architecture driven by use cases where analytic functions can be easily extended. This paper also proposes the data specification to define the data inputs to be taking into account in diagnosis process. This data specification has been implemented with different use cases within SELFNET Project, proving its effectiveness.

6th International Conference on Network Analysis

CERN Document Server

Nikolaev, Alexey; Pardalos, Panos; Prokopyev, Oleg

2017-01-01

This valuable source for graduate students and researchers provides a comprehensive introduction to current theories and applications in optimization methods and network models. Contributions to this book are focused on new efficient algorithms and rigorous mathematical theories, which can be used to optimize and analyze mathematical graph structures with massive size and high density induced by natural or artificial complex networks. Applications to social networks, power transmission grids, telecommunication networks, stock market networks, and human brain networks are presented. Chapters in this book cover the following topics: Linear max min fairness Heuristic approaches for high-quality solutions Efficient approaches for complex multi-criteria optimization problems Comparison of heuristic algorithms New heuristic iterative local search Power in network structures Clustering nodes in random graphs Power transmission grid structure Network decomposition problems Homogeneity hypothesis testing Network analy...

Spatiotemporal network motif reveals the biological traits of developmental gene regulatory networks in Drosophila melanogaster

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Kim Man-Sun

2012-05-01

Full Text Available Abstract Background Network motifs provided a “conceptual tool” for understanding the functional principles of biological networks, but such motifs have primarily been used to consider static network structures. Static networks, however, cannot be used to reveal time- and region-specific traits of biological systems. To overcome this limitation, we proposed the concept of a “spatiotemporal network motif,” a spatiotemporal sequence of network motifs of sub-networks which are active only at specific time points and body parts. Results On the basis of this concept, we analyzed the developmental gene regulatory network of the Drosophila melanogaster embryo. We identified spatiotemporal network motifs and investigated their distribution pattern in time and space. As a result, we found how key developmental processes are temporally and spatially regulated by the gene network. In particular, we found that nested feedback loops appeared frequently throughout the entire developmental process. From mathematical simulations, we found that mutual inhibition in the nested feedback loops contributes to the formation of spatial expression patterns. Conclusions Taken together, the proposed concept and the simulations can be used to unravel the design principle of developmental gene regulatory networks.

The Unfolding MD Simulations of Cyclophilin: Analyzed by Surface Contact Networks and Their Associated Metrics

Science.gov (United States)

Roy, Sourav; Basu, Sankar; Dasgupta, Dipak; Bhattacharyya, Dhananjay; Banerjee, Rahul

2015-01-01

Currently, considerable interest exists with regard to the dissociation of close packed aminoacids within proteins, in the course of unfolding, which could result in either wet or dry moltenglobules. The progressive disjuncture of residues constituting the hydrophobic core ofcyclophilin from L. donovani (LdCyp) has been studied during the thermal unfolding of the molecule, by molecular dynamics simulations. LdCyp has been represented as a surface contactnetwork (SCN) based on the surface complementarity (Sm) of interacting residues within themolecular interior. The application of Sm to side chain packing within proteins make it a very sensitive indicator of subtle perturbations in packing, in the thermal unfolding of the protein. Network based metrics have been defined to track the sequential changes in the disintegration ofthe SCN spanning the hydrophobic core of LdCyp and these metrics prove to be highly sensitive compared to traditional metrics in indicating the increased conformational (and dynamical) flexibility in the network. These metrics have been applied to suggest criteria distinguishing DMG, WMG and transition state ensembles and to identify key residues involved in crucial conformational/topological events during the unfolding process. PMID:26545107

Requirements of the integration of renewable energy into network charge regulation. Proposals for the further development of the network charge system. Final report

International Nuclear Information System (INIS)

Friedrichsen, Nele; Klobasa, Marian; Marwitz, Simon; Hilpert, Johannes; Sailer, Frank

2016-01-01

In this project we analyzed options to advance the network tariff system to support the German energy transition. A power system with high shares of renewables, requires more flexibility of supply and demand than the traditional system based on centralized, fossil power plants. Further, the power networks need to be adjusted and expanded. The transformation should aim at system efficiency i.e. look at both generation and network development. Network tariffs allocate the network cost towards network users. They also should provide incentives, e.g. to reduce peak load in periods of network congestion. Inappropriate network tariffs can hinder the provision of flexibility and thereby become a barrier towards system integration of renewable. Against this background, this report presents a systematic review of the German network tariff system and a discussion of several options to adapt the network tarif system in order to support the energy transition. The following aspects are analyzed: An adjustment of the privileges for industrial users to increase potential network benefits and reduce barriers towards a more market oriented behaviour. The payments for avoided network charges to distributed generation, that do not reflect cost reality in distribution networks anymore. Uniform transmission network tariffs as an option for a more appropriate allocation of cost associated with the energy transition. Increased standing fees in low voltage networks as an option to increase the cost-contribution of users with self-generation to network financing. Generator tariffs, to allocate a share of network cost to generators and provide incentives for network oriented location choice and/or feed-in.

Implementability of two-qubit unitary operations over the butterfly network and the ladder network with free classical communication

Energy Technology Data Exchange (ETDEWEB)

Akibue, Seiseki [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo (Japan); Murao, Mio [Department of Physics, Graduate School of Science, The University of Tokyo, Tokyo, Japan and NanoQuine, The University of Tokyo, Tokyo (Japan)

2014-12-04

We investigate distributed implementation of two-qubit unitary operations over two primitive networks, the butterfly network and the ladder network, as a first step to apply network coding for quantum computation. By classifying two-qubit unitary operations in terms of the Kraus-Cirac number, the number of non-zero parameters describing the global part of two-qubit unitary operations, we analyze which class of two-qubit unitary operations is implementable over these networks with free classical communication. For the butterfly network, we show that two classes of two-qubit unitary operations, which contain all Clifford, controlled-unitary and matchgate operations, are implementable over the network. For the ladder network, we show that two-qubit unitary operations are implementable over the network if and only if their Kraus-Cirac number do not exceed the number of the bridges of the ladder.

Implementability of two-qubit unitary operations over the butterfly network and the ladder network with free classical communication

International Nuclear Information System (INIS)

Akibue, Seiseki; Murao, Mio

2014-01-01

We investigate distributed implementation of two-qubit unitary operations over two primitive networks, the butterfly network and the ladder network, as a first step to apply network coding for quantum computation. By classifying two-qubit unitary operations in terms of the Kraus-Cirac number, the number of non-zero parameters describing the global part of two-qubit unitary operations, we analyze which class of two-qubit unitary operations is implementable over these networks with free classical communication. For the butterfly network, we show that two classes of two-qubit unitary operations, which contain all Clifford, controlled-unitary and matchgate operations, are implementable over the network. For the ladder network, we show that two-qubit unitary operations are implementable over the network if and only if their Kraus-Cirac number do not exceed the number of the bridges of the ladder

Allocation of spectral and spatial modes in multidimensional metro-access optical networks

Science.gov (United States)

Gao, Wenbo; Cvijetic, Milorad

2018-04-01

Introduction of spatial division multiplexing (SDM) has added a new dimension in an effort to increase optical fiber channel capacity. At the same time, it can also be explored as an advanced optical networking tool. In this paper, we have investigated the resource allocation to end-users in multidimensional networking structure with plurality of spectral and spatial modes actively deployed in different networking segments. This presents a more comprehensive method as compared to the common practice where the segments of optical network are analyzed independently since the interaction between network hierarchies is included into consideration. We explored the possible transparency from the metro/core network to the optical access network, analyzed the potential bottlenecks from the network architecture perspective, and identified an optimized network structure. In our considerations, the viability of optical grooming through the entire hierarchical all-optical network is investigated by evaluating the effective utilization and spectral efficiency of the network architecture.

STRUCTURE AND COOPTATION IN ORGANIZATION NETWORK

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Valéria Riscarolli

2007-10-01

Full Text Available Business executive are rethinking business concept, based on horizontalization principles. As so, most organizational functions are outsourced, leading the enterprise to build business through a network of organizations. Here we study the case of Cia Hering’s network of organizations, a leader in knit apparel segment in Latin America (IEMI, 2004, looking at the network’s structure and levels of cooptation. A theoretical model was used using Quinn et al. (2001 “sun ray” network structure as basis to analyze the case study. Main results indicate higher degree of structural conformity, but incipient degree of coopetation in the network.

The 3-D diffusion program XYZ-MUGDI with data-analyzing program XYZFF

International Nuclear Information System (INIS)

Siewers, H.

1976-01-01

The XYZ-MUGDI program solves boudary value and eigenvalue problems for three-dimensional heterogeneous configurations in X, Y, Z-geometry for a maximum of four energy groups. The program XYZFF is a program for analyzing data; with it especially the average and maximum form factors for arbitrary coarse-meshed networks can be evaluated. (orig.) [de

Characterizing time series: when Granger causality triggers complex networks

Science.gov (United States)

Ge, Tian; Cui, Yindong; Lin, Wei; Kurths, Jürgen; Liu, Chong

2012-08-01

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIHMassachusetts Institute of Technology-Beth Israel Hospital. human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length.

Characterizing time series: when Granger causality triggers complex networks

International Nuclear Information System (INIS)

Ge Tian; Cui Yindong; Lin Wei; Liu Chong; Kurths, Jürgen

2012-01-01

In this paper, we propose a new approach to characterize time series with noise perturbations in both the time and frequency domains by combining Granger causality and complex networks. We construct directed and weighted complex networks from time series and use representative network measures to describe their physical and topological properties. Through analyzing the typical dynamical behaviors of some physical models and the MIT-BIH human electrocardiogram data sets, we show that the proposed approach is able to capture and characterize various dynamics and has much potential for analyzing real-world time series of rather short length. (paper)

Emission pathway modeling to analyze national ambition levels of decarbonization

International Nuclear Information System (INIS)

Kainuma, Mikiko; Waisman, Henri

2015-01-01

The Deep Decarbonization Pathways Project (DDPP) is a knowledge network comprising 15 Country Research Teams and several Partner Organizations which develop and share methods, assumptions, and findings related to deep decarbonization. It analyzes the technical decarbonization potential, exploring options for deep decarbonization, but also better taking into account existing infrastructure stocks. It shows the possibility to reduce total CO 2 -energy emissions by 45% by 2050, with bottom-up analyses by 15 Country Research Teams

NETWORK UNIVERSITIES: INTERNATIONAL EXPERIENCE AND TRENDS

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Г А Краснова

2016-12-01

Full Text Available The article is devoted to networking foreign universities, in particular, it considers the experience of cooperation of Vietnamese and Chinese universities with the leading universities of the world and the implementation of joint educational projects. The article deals with the basic characteristics of university networks that emerged in the last decade in developing countries. The authors analyzed the model, sources of financing, the organization of educational process, teaching of languages and the number of students in the university network, as well as the main mechanisms that allow open network structure of education in different countries of the world. The authors also address the main reasons for encouraging networking of foreign universities.

Study of co-authorship network of papers in the Journal of Research in Medical Sciences using social network analysis

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Firoozeh Zare-Farashbandi

2014-01-01

Full Text Available Background: Co-authorship is one of the most tangible forms of research collaboration. A co-authorship network is a social network in which the authors through participation in one or more publication through an indirect path have linked to each other. The present research using the social network analysis studied co-authorship network of 681 articles published in Journal of Research in Medical Sciences (JRMS during 2008-2012. Materials and Methods: The study was carried out with the scientometrics approach and using co-authorship network analysis of authors. The topology of the co-authorship network of 681 published articles in JRMS between 2008 and 2012 was analyzed using macro-level metrics indicators of network analysis such as density, clustering coefficient, components and mean distance. In addition, in order to evaluate the performance of each authors and countries in the network, the micro-level indicators such as degree centrality, closeness centrality and betweenness centrality as well as productivity index were used. The UCINET and NetDraw softwares were used to draw and analyze the co-authorship network of the papers. Results: The assessment of the authors productivity in this journal showed that the first ranks were belonged to only five authors, respectively. Furthermore, analysis of the co-authorship of the authors in the network demonstrated that in the betweenness centrality index, three authors of them had the good position in the network. They can be considered as the network leaders able to control the flow of information in the network compared with the other members based on the shortest paths. On the other hand, the key role of the network according to the productivity and centrality indexes was belonged to Iran, Malaysia and United States of America. Conclusion: Co-authorship network of JRMS has the characteristics of a small world network. In addition, the theory of 6° separation is valid in this network was also true.

A Network of Networks Perspective on Global Trade

Science.gov (United States)

Maluck, Julian; Donner, Reik V.

2015-01-01

Mutually intertwined supply chains in contemporary economy result in a complex network of trade relationships with a highly non-trivial topology that varies with time. In order to understand the complex interrelationships among different countries and economic sectors, as well as their dynamics, a holistic view on the underlying structural properties of this network is necessary. This study employs multi-regional input-output data to decompose 186 national economies into 26 industry sectors and utilizes the approach of interdependent networks to analyze the substructure of the resulting international trade network for the years 1990–2011. The partition of the network into national economies is observed to be compatible with the notion of communities in the sense of complex network theory. By studying internal versus cross-subgraph contributions to established complex network metrics, new insights into the architecture of global trade are obtained, which allow to identify key elements of global economy. Specifically, financial services and business activities dominate domestic trade whereas electrical and machinery industries dominate foreign trade. In order to further specify each national sector’s role individually, (cross-)clustering coefficients and cross-betweenness are obtained for different pairs of subgraphs. The corresponding analysis reveals that specific industrial sectors tend to favor distinct directionality patterns and that the cross-clustering coefficient for geographically close country pairs is remarkably high, indicating that spatial factors are still of paramount importance for the organization of trade patterns in modern economy. Regarding the evolution of the trade network’s substructure, globalization is well-expressed by trends of several structural characteristics (e.g., link density and node strength) in the interacting network framework. Extreme events, such as the financial crisis 2008/2009, are manifested as anomalies superimposed

The use of nodes attributes in social network analysis with an application to an international trade network

Science.gov (United States)

de Andrade, Ricardo Lopes; Rêgo, Leandro Chaves

2018-02-01

The social network analysis (SNA) studies the interactions among actors in a network formed through some relationship (friendship, cooperation, trade, among others). The SNA is constantly approached from a binary point of view, i.e., it is only observed if a link between two actors is present or not regardless of the strength of this link. It is known that different information can be obtained in weighted and unweighted networks and that the information extracted from weighted networks is more accurate and detailed. Another rarely discussed approach in the SNA is related to the individual attributes of the actors (nodes), because such analysis is usually focused on the topological structure of networks. Features of the nodes are not incorporated in the SNA what implies that there is some loss or misperception of information in those analyze. This paper aims at exploring more precisely the complexities of a social network, initially developing a method that inserts the individual attributes in the topological structure of the network and then analyzing the network in four different ways: unweighted, edge-weighted and two methods for using both edge-weights and nodes' attributes. The international trade network was chosen in the application of this approach, where the nodes represent the countries, the links represent the cash flow in the trade transactions and countries' GDP were chosen as nodes' attributes. As a result, it is possible to observe which countries are most connected in the world economy and with higher cash flows, to point out the countries that are central to the intermediation of the wealth flow and those that are most benefited from being included in this network. We also made a principal component analysis to study which metrics are more influential in describing the data variability, which turn out to be mostly the weighted metrics which include the nodes' attributes.

Analyzing Collaborative Governance Through Social Network Analysis: A Case Study of River Management Along the Waal River in The Netherlands.

Science.gov (United States)

Fliervoet, J M; Geerling, G W; Mostert, E; Smits, A J M

2016-02-01

Until recently, governmental organizations played a dominant and decisive role in natural resource management. However, an increasing number of studies indicate that this dominant role is developing towards a more facilitating role as equal partner to improve efficiency and create a leaner state. This approach is characterized by complex collaborative relationships between various actors and sectors on multiple levels. To understand this complexity in the field of environmental management, we conducted a social network analysis of floodplain management in the Dutch Rhine delta. We charted the current interorganizational relationships between 43 organizations involved in flood protection (blue network) and nature management (green network) and explored the consequences of abolishing the central actor in these networks. The discontinuation of this actor will decrease the connectedness of actors within the blue and green network and may therefore have a large impact on the exchange of ideas and decision-making processes. Furthermore, our research shows the dependence of non-governmental actors on the main governmental organizations. It seems that the Dutch governmental organizations still have a dominant and controlling role in floodplain management. This challenges the alleged shift from a dominant government towards collaborative governance and calls for detailed analysis of actual governance.

Complexities’ day-to-day dynamic evolution analysis and prediction for a Didi taxi trip network based on complex network theory

Science.gov (United States)

Zhang, Lin; Lu, Jian; Zhou, Jialin; Zhu, Jinqing; Li, Yunxuan; Wan, Qian

2018-03-01

Didi Dache is the most popular taxi order mobile app in China, which provides online taxi-hailing service. The obtained big database from this app could be used to analyze the complexities’ day-to-day dynamic evolution of Didi taxi trip network (DTTN) from the level of complex network dynamics. First, this paper proposes the data cleaning and modeling methods for expressing Nanjing’s DTTN as a complex network. Second, the three consecutive weeks’ data are cleaned to establish 21 DTTNs based on the proposed big data processing technology. Then, multiple topology measures that characterize the complexities’ day-to-day dynamic evolution of these networks are provided. Third, these measures of 21 DTTNs are calculated and subsequently explained with actual implications. They are used as a training set for modeling the BP neural network which is designed for predicting DTTN complexities evolution. Finally, the reliability of the designed BP neural network is verified by comparing with the actual data and the results obtained from ARIMA method simultaneously. Because network complexities are the basis for modeling cascading failures and conducting link prediction in complex system, this proposed research framework not only provides a novel perspective for analyzing DTTN from the level of system aggregated behavior, but can also be used to improve the DTTN management level.

Analyzing, Modelling, and Designing Software Ecosystems

DEFF Research Database (Denmark)

Manikas, Konstantinos

as the software development and distribution by a set of actors dependent on each other and the ecosystem. We commence on the hypothesis that the establishment of a software ecosystem on the telemedicine services of Denmark would address these issues and investigate how a software ecosystem can foster...... the development, implementation, and use of telemedicine services. We initially expand the theory of software ecosystems by contributing to the definition and understanding of software ecosystems, providing means of analyzing existing and designing new ecosystems, and defining and measuring the qualities...... of software ecosystems. We use these contributions to design a software ecosystem in the telemedicine services of Denmark with (i) a common platform that supports and promotes development from different actors, (ii) high software interaction, (iii) strong social network of actors, (iv) robust business...

Philosophy of social networking

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Markova T. V.

2018-04-01

Full Text Available the article is devoted to the study of social networks impact on an individual, which are an important part of a modern society. Through reflections the reasons of the popularity of the phenomenon of virtual communication in the 21st century are determined: what drives a person when he / she registers on the sites for communication, premises for his / her actions and consequences. The latter is viewed from both a social and a personal point of view. After analyzing the charts of social networks popularity, the authors come to the conclusion that there is an increase in the population of the virtual communication supporters. It allows to assert that the problem of the termination of live communication is relevant to this day. Dualism of social networks influence on the consciousness of an individual is stated: together with negative consequences positive aspects are considered. By analyzing social media researches, as well as by the means of a survey, the dominant reason for the world wide web entering is identified. After that, it is clearly shown what a typical site for communication is; as a result, the pros and cons of such time spending are specified. The conclusion states the predominance of the Internet dependence over the other types of dependencies, also forecasts are made for the future of both social networks and the people caught in their web.

Social Network Analysis as a Methodological Approach to Explore Health Systems: A Case Study Exploring Support among Senior Managers/Executives in a Hospital Network.

Science.gov (United States)

De Brún, Aoife; McAuliffe, Eilish

2018-03-13

Health systems research recognizes the complexity of healthcare, and the interacting and interdependent nature of components of a health system. To better understand such systems, innovative methods are required to depict and analyze their structures. This paper describes social network analysis as a methodology to depict, diagnose, and evaluate health systems and networks therein. Social network analysis is a set of techniques to map, measure, and analyze social relationships between people, teams, and organizations. Through use of a case study exploring support relationships among senior managers in a newly established hospital group, this paper illustrates some of the commonly used network- and node-level metrics in social network analysis, and demonstrates the value of these maps and metrics to understand systems. Network analysis offers a valuable approach to health systems and services researchers as it offers a means to depict activity relevant to network questions of interest, to identify opinion leaders, influencers, clusters in the network, and those individuals serving as bridgers across clusters. The strengths and limitations inherent in the method are discussed, and the applications of social network analysis in health services research are explored.

Social Network Analysis as a Methodological Approach to Explore Health Systems: A Case Study Exploring Support among Senior Managers/Executives in a Hospital Network

Directory of Open Access Journals (Sweden)

Aoife De Brún

2018-03-01

Full Text Available Health systems research recognizes the complexity of healthcare, and the interacting and interdependent nature of components of a health system. To better understand such systems, innovative methods are required to depict and analyze their structures. This paper describes social network analysis as a methodology to depict, diagnose, and evaluate health systems and networks therein. Social network analysis is a set of techniques to map, measure, and analyze social relationships between people, teams, and organizations. Through use of a case study exploring support relationships among senior managers in a newly established hospital group, this paper illustrates some of the commonly used network- and node-level metrics in social network analysis, and demonstrates the value of these maps and metrics to understand systems. Network analysis offers a valuable approach to health systems and services researchers as it offers a means to depict activity relevant to network questions of interest, to identify opinion leaders, influencers, clusters in the network, and those individuals serving as bridgers across clusters. The strengths and limitations inherent in the method are discussed, and the applications of social network analysis in health services research are explored.

An Efficient Hierarchy Algorithm for Community Detection in Complex Networks

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Lili Zhang

2014-01-01

Full Text Available Community structure is one of the most fundamental and important topology characteristics of complex networks. The research on community structure has wide applications and is very important for analyzing the topology structure, understanding the functions, finding the hidden properties, and forecasting the time-varying of the networks. This paper analyzes some related algorithms and proposes a new algorithm—CN agglomerative algorithm based on graph theory and the local connectedness of network to find communities in network. We show this algorithm is distributed and polynomial; meanwhile the simulations show it is accurate and fine-grained. Furthermore, we modify this algorithm to get one modified CN algorithm and apply it to dynamic complex networks, and the simulations also verify that the modified CN algorithm has high accuracy too.

Topology of the Erasmus student mobility network

Science.gov (United States)

Derzsi, A.; Derzsy, N.; Káptalan, E.; Néda, Z.

2011-07-01

The collaboration network generated by the Erasmus student mobilities in the year 2003 is analyzed and modeled. Nodes of this bipartite network are European universities and links are the Erasmus mobilities between these universities. This network is a complex directed and weighted graph. The non-directed and non-weighted projection of this network does not exhibit a scale-free nature, but proves to be a small-word type random network with a giant component. The connectivity data indicates an exponential degree distribution, a relatively high clustering coefficient and a small radius. It can be easily modeled by using a simple configuration model and arguing the exponential degree distribution. The weighted and directed version of the network can also be described by means of simple random network models.

Review of Biological Network Data and Its Applications

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Donghyeon Yu

2013-12-01

Full Text Available Studying biological networks, such as protein-protein interactions, is key to understanding complex biological activities. Various types of large-scale biological datasets have been collected and analyzed with high-throughput technologies, including DNA microarray, next-generation sequencing, and the two-hybrid screening system, for this purpose. In this review, we focus on network-based approaches that help in understanding biological systems and identifying biological functions. Accordingly, this paper covers two major topics in network biology: reconstruction of gene regulatory networks and network-based applications, including protein function prediction, disease gene prioritization, and network-based genome-wide association study.

Complex modular structure of large-scale brain networks

Science.gov (United States)

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

2009-06-01

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

Hyperbolicity measures democracy in real-world networks

Science.gov (United States)

Borassi, Michele; Chessa, Alessandro; Caldarelli, Guido

2015-09-01

In this work, we analyze the hyperbolicity of real-world networks, a geometric quantity that measures if a space is negatively curved. We provide two improvements in our understanding of this quantity: first of all, in our interpretation, a hyperbolic network is "aristocratic", since few elements "connect" the system, while a non-hyperbolic network has a more "democratic" structure with a larger number of crucial elements. The second contribution is the introduction of the average hyperbolicity of the neighbors of a given node. Through this definition, we outline an "influence area" for the vertices in the graph. We show that in real networks the influence area of the highest degree vertex is small in what we define "local" networks (i.e., social or peer-to-peer networks), and large in "global" networks (i.e., power grid, metabolic networks, or autonomous system networks).

EEGNET: An Open Source Tool for Analyzing and Visualizing M/EEG Connectome.

Science.gov (United States)

Hassan, Mahmoud; Shamas, Mohamad; Khalil, Mohamad; El Falou, Wassim; Wendling, Fabrice

2015-01-01

The brain is a large-scale complex network often referred to as the "connectome". Exploring the dynamic behavior of the connectome is a challenging issue as both excellent time and space resolution is required. In this context Magneto/Electroencephalography (M/EEG) are effective neuroimaging techniques allowing for analysis of the dynamics of functional brain networks at scalp level and/or at reconstructed sources. However, a tool that can cover all the processing steps of identifying brain networks from M/EEG data is still missing. In this paper, we report a novel software package, called EEGNET, running under MATLAB (Math works, inc), and allowing for analysis and visualization of functional brain networks from M/EEG recordings. EEGNET is developed to analyze networks either at the level of scalp electrodes or at the level of reconstructed cortical sources. It includes i) Basic steps in preprocessing M/EEG signals, ii) the solution of the inverse problem to localize / reconstruct the cortical sources, iii) the computation of functional connectivity among signals collected at surface electrodes or/and time courses of reconstructed sources and iv) the computation of the network measures based on graph theory analysis. EEGNET is the unique tool that combines the M/EEG functional connectivity analysis and the computation of network measures derived from the graph theory. The first version of EEGNET is easy to use, flexible and user friendly. EEGNET is an open source tool and can be freely downloaded from this webpage: https://sites.google.com/site/eegnetworks/.

Partner network communities – a resource of universities’ activities

Directory of Open Access Journals (Sweden)

Romm Mark V.

2016-01-01

Full Text Available The network activity is not only part and parcel of the modern university, but it also demonstrates the level of its success. There appeared an urgent need for understanding the nature of universities’ network interactions and finding the most effective models of their network cooperation. The article analyzes partnership network communities with higher educational establishments (universities’ participation, which are being actively created nowadays. The conditions for successful network activities of a university in scientific, academic and professional network communities are presented.

Research on NGN network control technology

Science.gov (United States)

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.

Triangulation positioning system network

Directory of Open Access Journals (Sweden)

Sfendourakis Marios

2017-01-01

Full Text Available This paper presents ongoing work on localization and positioning through triangulation procedure for a Fixed Sensors Network - FSN.The FSN has to work as a system.As the triangulation problem becomes high complicated in a case with large numbers of sensors and transmitters, an adequate grid topology is needed in order to tackle the detection complexity.For that reason a Network grid topology is presented and areas that are problematic and need further analysis are analyzed.The Network System in order to deal with problems of saturation and False Triangulations - FTRNs will have to find adequate methods in every sub-area of the Area Of Interest - AOI.Also, concepts like Sensor blindness and overall Network blindness, are presented. All these concepts affect the Network detection rate and its performance and ought to be considered in a way that the network overall performance won’t be degraded.Network performance should be monitored contentiously, with right algorithms and methods.It is also shown that as the number of TRNs and FTRNs is increased Detection Complexity - DC is increased.It is hoped that with further research all the characteristics of a triangulation system network for positioning will be gained and the system will be able to perform autonomously with a high detection rate.

Report on Asian Environment Information Network; 'Asia kankyo joho network' ni kansuru hokokusho

Energy Technology Data Exchange (ETDEWEB)

NONE

1996-03-01

The goal is the construction of Asian Environment Information Network (AEInet) in accordance with a contract signed between Indonesia's LIPI (Indonesian Institute of Science) and NEDO under NEDO's Research Cooperation Project Concerning the Development of Environment Measuring Laser Radar (LR). The network is so designed and constituted as to operate on a private line between Indonesia and Japan via IP (Internet protocol) and to enable the exchange on the Internet network of the data collected/analyzed by the Indonesian LR system and of articles of e-mail between scientists of the two countries. The AEInet will be utilized for the collection/analysis of LR-collected data; exchange of observed data and the result of processing; provision of support to environment information scientists in exchanging e-mail and information; and the search of databases for the implementation of the project. In this paper, the outline and functions of the system, network system design, WWW server construction, network operating status, joint researches with Indonesia, etc., are described. (NEDO)

Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach

Directory of Open Access Journals (Sweden)

Mike W.-L. Cheung

2016-05-01

Full Text Available Big data is a field that has traditionally been dominated by disciplines such as computer science and business, where mainly data-driven analyses have been performed. Psychology, a discipline in which a strong emphasis is placed on behavioral theories and empirical research, has the potential to contribute greatly to the big data movement. However, one challenge to psychologists – and probably the most crucial one – is that most researchers may not have the necessary programming and computational skills to analyze big data. In this study we argue that psychologists can also conduct big data research and that, rather than trying to acquire new programming and computational skills, they should focus on their strengths, such as performing psychometric analyses and testing theories using multivariate analyses to explain phenomena. We propose a split/analyze/meta-analyze approach that allows psychologists to easily analyze big data. Two real datasets are used to demonstrate the proposed procedures in R. A new research agenda related to the analysis of big data in psychology is outlined at the end of the study.

Analyzing Big Data in Psychology: A Split/Analyze/Meta-Analyze Approach.

Science.gov (United States)

Cheung, Mike W-L; Jak, Suzanne

2016-01-01

Big data is a field that has traditionally been dominated by disciplines such as computer science and business, where mainly data-driven analyses have been performed. Psychology, a discipline in which a strong emphasis is placed on behavioral theories and empirical research, has the potential to contribute greatly to the big data movement. However, one challenge to psychologists-and probably the most crucial one-is that most researchers may not have the necessary programming and computational skills to analyze big data. In this study we argue that psychologists can also conduct big data research and that, rather than trying to acquire new programming and computational skills, they should focus on their strengths, such as performing psychometric analyses and testing theories using multivariate analyses to explain phenomena. We propose a split/analyze/meta-analyze approach that allows psychologists to easily analyze big data. Two real datasets are used to demonstrate the proposed procedures in R. A new research agenda related to the analysis of big data in psychology is outlined at the end of the study.

Southeast Asia Report. Peoples Republic of Kampuchea: Biographic Information on Officials

National Research Council Canada - National Science Library

1987-01-01

... from the PRK's Phnom Penh Domestic Service radio broadcasts in Cambodian unless otherwise specified. Other than through comparisons with printed sources such as SPK, VNA, or KPL the spellings of the names published herein cannot be confirmed...

Case studies of attacks on communication networks

Energy Technology Data Exchange (ETDEWEB)

Kang, Sin Bok; Han, Eon Suk [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)

1996-06-15

Recently, as the computer hardware and communications are developed, the data exchange through inter-networking has been highlighted and the data is being recognized as a great asset. Most of the organizations, businesses and enterprises are open to the external world-computer communication networks, attention must be focused on the securities of the information infrastructure. A government organization has been developing 'Circuits Analyzers', and 'Hacker-Tracking Program' and is struggling to track down sneakers. In this report, we analyze the contents of the cases where the communication network has been invaded, from the past up until now in Korea. This report also contains the result of a study on E-mail security, for the protection of KAERI Integrated Management Information System under which utilizes the CALS concepts and web services. (Author)

Case studies of attacks on communication networks

International Nuclear Information System (INIS)

Kang, Sin Bok; Han, Eon Suk

1996-06-01

Recently, as the computer hardware and communications are developed, the data exchange through inter-networking has been highlighted and the data is being recognized as a great asset. Most of the organizations, businesses and enterprises are open to the external world-computer communication networks, attention must be focused on the securities of the information infrastructure. A government organization has been developing 'Circuits Analyzers', and 'Hacker-Tracking Program' and is struggling to track down sneakers. In this report, we analyze the contents of the cases where the communication network has been invaded, from the past up until now in Korea. This report also contains the result of a study on E-mail security, for the protection of KAERI Integrated Management Information System under which utilizes the CALS concepts and web services. (Author)

Cross-linked structure of network evolution

International Nuclear Information System (INIS)

Bassett, Danielle S.; Wymbs, Nicholas F.; Grafton, Scott T.; Porter, Mason A.; Mucha, Peter J.

2014-01-01

We study the temporal co-variation of network co-evolution via the cross-link structure of networks, for which we take advantage of the formalism of hypergraphs to map cross-link structures back to network nodes. We investigate two sets of temporal network data in detail. In a network of coupled nonlinear oscillators, hyperedges that consist of network edges with temporally co-varying weights uncover the driving co-evolution patterns of edge weight dynamics both within and between oscillator communities. In the human brain, networks that represent temporal changes in brain activity during learning exhibit early co-evolution that then settles down with practice. Subsequent decreases in hyperedge size are consistent with emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. Our results on real and synthetic networks give a poignant demonstration of the ability of cross-link structure to uncover unexpected co-evolution attributes in both real and synthetic dynamical systems. This, in turn, illustrates the utility of analyzing cross-links for investigating the structure of temporal networks

Cross-linked structure of network evolution

Energy Technology Data Exchange (ETDEWEB)

Bassett, Danielle S., E-mail: dsb@seas.upenn.edu [Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Department of Physics, University of California, Santa Barbara, California 93106 (United States); Sage Center for the Study of the Mind, University of California, Santa Barbara, California 93106 (United States); Wymbs, Nicholas F.; Grafton, Scott T. [Department of Psychology and UCSB Brain Imaging Center, University of California, Santa Barbara, California 93106 (United States); Porter, Mason A. [Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); CABDyN Complexity Centre, University of Oxford, Oxford, OX1 1HP (United Kingdom); Mucha, Peter J. [Carolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina, Chapel Hill, North Carolina 27599 (United States); Department of Applied Physical Sciences, University of North Carolina, Chapel Hill, North Carolina 27599 (United States)

2014-03-15

We study the temporal co-variation of network co-evolution via the cross-link structure of networks, for which we take advantage of the formalism of hypergraphs to map cross-link structures back to network nodes. We investigate two sets of temporal network data in detail. In a network of coupled nonlinear oscillators, hyperedges that consist of network edges with temporally co-varying weights uncover the driving co-evolution patterns of edge weight dynamics both within and between oscillator communities. In the human brain, networks that represent temporal changes in brain activity during learning exhibit early co-evolution that then settles down with practice. Subsequent decreases in hyperedge size are consistent with emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. Our results on real and synthetic networks give a poignant demonstration of the ability of cross-link structure to uncover unexpected co-evolution attributes in both real and synthetic dynamical systems. This, in turn, illustrates the utility of analyzing cross-links for investigating the structure of temporal networks.

Computer Networks and Globalization

Directory of Open Access Journals (Sweden)

J. Magliaro

2007-07-01

Full Text Available Communication and information computer networks connect the world in ways that make globalization more natural and inequity more subtle. As educators, we look at these phenomena holistically analyzing them from the realist’s view, thus exploring tensions, (in equity and (injustice, and from the idealist’s view, thus embracing connectivity, convergence and development of a collective consciousness. In an increasingly market- driven world we find examples of openness and human generosity that are based on networks, specifically the Internet. After addressing open movements in publishing, software industry and education, we describe the possibility of a dialectic equilibrium between globalization and indigenousness in view of ecologically designed future smart networks

Composing Music with Complex Networks

Science.gov (United States)

Liu, Xiaofan; Tse, Chi K.; Small, Michael

In this paper we study the network structure in music and attempt to compose music artificially. Networks are constructed with nodes and edges corresponding to musical notes and their co-occurrences. We analyze sample compositions from Bach, Mozart, Chopin, as well as other types of music including Chinese pop music. We observe remarkably similar properties in all networks constructed from the selected compositions. Power-law exponents of degree distributions, mean degrees, clustering coefficients, mean geodesic distances, etc. are reported. With the network constructed, music can be created by using a biased random walk algorithm, which begins with a randomly chosen note and selects the subsequent notes according to a simple set of rules that compares the weights of the edges, weights of the nodes, and/or the degrees of nodes. The newly created music from complex networks will be played in the presentation.

The queueing perspective of asynchronous network coding in two-way relay network

Science.gov (United States)

Liang, Yaping; Chang, Qing; Li, Xianxu

2018-04-01

Asynchronous network coding (NC) has potential to improve the wireless network performance compared with a routing or the synchronous network coding. Recent researches concentrate on the optimization between throughput/energy consuming and delay with a couple of independent input flow. However, the implementation of NC requires a thorough investigation of its impact on relevant queueing systems where few work focuses on. Moreover, few works study the probability density function (pdf) in network coding scenario. In this paper, the scenario with two independent Poisson input flows and one output flow is considered. The asynchronous NC-based strategy is that a new arrival evicts a head packet holding in its queue when waiting for another packet from the other flow to encode. The pdf for the output flow which contains both coded and uncoded packets is derived. Besides, the statistic characteristics of this strategy are analyzed. These results are verified by numerical simulations.

Location privacy protection in mobile networks

CERN Document Server

Liu, Xinxin

2013-01-01

This SpringerBrief analyzes the potential privacy threats in wireless and mobile network environments, and reviews some existing works. It proposes multiple privacy preserving techniques against several types of privacy threats that are targeting users in a mobile network environment. Depending on the network architecture, different approaches can be adopted. The first proposed approach considers a three-party system architecture where there is a trusted central authority that can be used to protect users? privacy. The second approach considers a totally distributed environment where users per

Tweacher: New proposal for Online Social Networks Impact in Secondary Education

Directory of Open Access Journals (Sweden)

Sebastián ROMERO

2013-05-01

Full Text Available This paper presents and analyzes the potential uses and motivations of online social networks in education, with special emphasis on secondary education. First, we show several previous researches supporting the use of social networking as an educational tool and discuss Edmodo, an educative online social network. The work carried out during two academic years with senior students of primary and secondary schools is also analyzed. After that we present Tweacher an educative social network application and evaluate its use in the classroom to prove its useful use between teachers and students. This research has allowed us to see the reality of social network use among young people and identify the challenges of its application to education environment.

Stochastic network interdiction optimization via capacitated network reliability modeling and probabilistic solution discovery

International Nuclear Information System (INIS)

Ramirez-Marquez, Jose Emmanuel; Rocco S, Claudio M.

2009-01-01

This paper introduces an evolutionary optimization approach that can be readily applied to solve stochastic network interdiction problems (SNIP). The network interdiction problem solved considers the minimization of the cost associated with an interdiction strategy such that the maximum flow that can be transmitted between a source node and a sink node for a fixed network design is greater than or equal to a given reliability requirement. Furthermore, the model assumes that the nominal capacity of each network link and the cost associated with their interdiction can change from link to link and that such interdiction has a probability of being successful. This version of the SNIP is for the first time modeled as a capacitated network reliability problem allowing for the implementation of computation and solution techniques previously unavailable. The solution process is based on an evolutionary algorithm that implements: (1) Monte-Carlo simulation, to generate potential network interdiction strategies, (2) capacitated network reliability techniques to analyze strategies' source-sink flow reliability and, (3) an evolutionary optimization technique to define, in probabilistic terms, how likely a link is to appear in the final interdiction strategy. Examples for different sizes of networks are used throughout the paper to illustrate the approach

Airline network structure in competitive market

Directory of Open Access Journals (Sweden)

Babić Danica D.

2014-01-01

Full Text Available Airline's network is the key element of its business strategy and selected network structure will not have influence only on the airline's costs but could gain some advantage in revenues, too. Network designing implies that an airline has to make decisions about markets that it will serve and how to serve those markets. Network choice raises the following questions for an airline: a what markets to serve, b how to serve selected markets, c what level of service to offer, d what are the benefits/cost of the that decisions and e what is the influence of the competition. We analyzed the existing airline business models and corresponding network structure. The paper highlights the relationship between the network structures and the airline business strategies. Using a simple model we examine the relationship between the network structure and service quality in deregulated market.

Signaling in large-scale neural networks

DEFF Research Database (Denmark)

Berg, Rune W; Hounsgaard, Jørn

2009-01-01

We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages of this m......We examine the recent finding that neurons in spinal motor circuits enter a high conductance state during functional network activity. The underlying concomitant increase in random inhibitory and excitatory synaptic activity leads to stochastic signal processing. The possible advantages...... of this metabolically costly organization are analyzed by comparing with synaptically less intense networks driven by the intrinsic response properties of the network neurons....

Study on the complex network characteristics of urban road system based on GIS

Science.gov (United States)

Gao, Zhonghua; Chen, Zhenjie; Liu, Yongxue; Huang, Kang

2007-06-01

Urban road system is the basic bone of urban transportation and one of the most important factors that influent and controls the urban configuration. In this paper, an approach of modeling, analyzing and optimizing urban road system is described based on complex network theory and GIS technology. The urban road system is studied on three focuses: building the urban road network, modeling the computational procedures based on urban road networks and analyzing the urban road system of Changzhou City as the study case. The conclusion is that the urban road network is a scale-free network with small-world characteristic, and there is still space for development of the whole network as a small-world network, also the key road crosses should be kept expedite.

Performance verification of network function virtualization in software defined optical transport networks

Science.gov (United States)

Zhao, Yongli; Hu, Liyazhou; Wang, Wei; Li, Yajie; Zhang, Jie

2017-01-01

With the continuous opening of resource acquisition and application, there are a large variety of network hardware appliances deployed as the communication infrastructure. To lunch a new network application always implies to replace the obsolete devices and needs the related space and power to accommodate it, which will increase the energy and capital investment. Network function virtualization1 (NFV) aims to address these problems by consolidating many network equipment onto industry standard elements such as servers, switches and storage. Many types of IT resources have been deployed to run Virtual Network Functions (vNFs), such as virtual switches and routers. Then how to deploy NFV in optical transport networks is a of great importance problem. This paper focuses on this problem, and gives an implementation architecture of NFV-enabled optical transport networks based on Software Defined Optical Networking (SDON) with the procedure of vNFs call and return. Especially, an implementation solution of NFV-enabled optical transport node is designed, and a parallel processing method for NFV-enabled OTN nodes is proposed. To verify the performance of NFV-enabled SDON, the protocol interaction procedures of control function virtualization and node function virtualization are demonstrated on SDON testbed. Finally, the benefits and challenges of the parallel processing method for NFV-enabled OTN nodes are simulated and analyzed.

An improved algorithm for searching all minimal cuts in modified networks

International Nuclear Information System (INIS)

Yeh, W.-C.

2008-01-01

A modified network is an updated network after inserting a branch string (a special path) between two nodes in the original network. Modifications are common for network expansion or reinforcement evaluation and planning. The problem of searching all minimal cuts (MCs) in a modified network is discussed and solved in this study. The existing best-known methods for solving this problem either needed extensive comparison and verification or failed to solve some special but important cases. Therefore, a more efficient, intuitive and generalized method for searching all MCs without an extensive research procedure is proposed. In this study, we first develop an intuitive algorithm based upon the reformation of all MCs in the original network to search for all MCs in a modified network. Next, the correctness of the proposed algorithm will be analyzed and proven. The computational complexity of the proposed algorithm is analyzed and compared with the existing best-known methods. Finally, two examples illustrate how all MCs are generated in a modified network using the information of all of the MCs in the corresponding original network

The Analysis of Duocentric Social Networks: A Primer.

Science.gov (United States)

Kennedy, David P; Jackson, Grace L; Green, Harold D; Bradbury, Thomas N; Karney, Benjamin R

2015-02-01

Marriages and other intimate partnerships are facilitated or constrained by the social networks within which they are embedded. To date, methods used to assess the social networks of couples have been limited to global ratings of social network characteristics or network data collected from each partner separately. In the current article, the authors offer new tools for expanding on the existing literature by describing methods of collecting and analyzing duocentric social networks, that is, the combined social networks of couples. They provide an overview of the key considerations for measuring duocentric networks, such as how and why to combine separate network interviews with partners into one shared duocentric network, the number of network members to assess, and the implications of different network operationalizations. They illustrate these considerations with analyses of social network data collected from 57 low-income married couples, presenting visualizations and quantitative measures of network composition and structure.

Rural Health Networks: How Network Analysis Can Inform Patient Care and Organizational Collaboration in a Rural Breast Cancer Screening Network.

Science.gov (United States)

Prusaczyk, Beth; Maki, Julia; Luke, Douglas A; Lobb, Rebecca

2018-04-15

Rural health networks have the potential to improve health care quality and access. Despite this, the use of network analysis to study rural health networks is limited. The purpose of this study was to use network analysis to understand how a network of rural breast cancer care providers deliver services and to demonstrate the value of this methodology in this research area. Leaders at 47 Federally Qualified Health Centers and Rural Health Clinics across 10 adjacent rural counties were asked where they refer patients for mammograms or breast biopsies. These clinics and the 22 referral providers that respondents named comprised the network. The network was analyzed graphically and statistically with exponential random graph modeling. Most (96%, n = 45) of the clinics and referral sites (95%, n = 21) are connected to each other. Two clinics of the same type were 62% less likely to refer patients to the same providers as 2 clinics of different types (OR = 0.38, 95% CI = 0.29-0.50). Clinics in the same county have approximately 8 times higher odds of referring patients to the same providers compared to clinics in different counties (OR = 7.80, CI = 4.57-13.31). This study found that geographic location of resources is an important factor in rural health care providers' referral decisions and demonstrated the usefulness of network analysis for understanding rural health networks. These results can be used to guide delivery of patient care and strengthen the network by building resources that take location into account. © 2018 National Rural Health Association.

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

Energy Technology Data Exchange (ETDEWEB)

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

2009-09-01

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

Global Electricity Trade Network: Structures and Implications

Science.gov (United States)

Ji, Ling; Jia, Xiaoping; Chiu, Anthony S. F.; Xu, Ming

2016-01-01

Nations increasingly trade electricity, and understanding the structure of the global power grid can help identify nations that are critical for its reliability. This study examines the global grid as a network with nations as nodes and international electricity trade as links. We analyze the structure of the global electricity trade network and find that the network consists of four sub-networks, and provide a detailed analysis of the largest network, Eurasia. Russia, China, Ukraine, and Azerbaijan have high betweenness measures in the Eurasian sub-network, indicating the degrees of centrality of the positions they hold. The analysis reveals that the Eurasian sub-network consists of seven communities based on the network structure. We find that the communities do not fully align with geographical proximity, and that the present international electricity trade in the Eurasian sub-network causes an approximately 11 million additional tons of CO2 emissions. PMID:27504825

Analyzing subsurface drain network performance in an agricultural monitoring site with a three-dimensional hydrological model

Science.gov (United States)

Nousiainen, Riikka; Warsta, Lassi; Turunen, Mika; Huitu, Hanna; Koivusalo, Harri; Pesonen, Liisa

2015-10-01

Effectiveness of a subsurface drainage system decreases with time, leading to a need to restore the drainage efficiency by installing new drain pipes in problem areas. The drainage performance of the resulting system varies spatially and complicates runoff and nutrient load generation within the fields. We presented a method to estimate the drainage performance of a heterogeneous subsurface drainage system by simulating the area with the three-dimensional hydrological FLUSH model. A GIS analysis was used to delineate the surface runoff contributing area in the field. We applied the method to reproduce the water balance and to investigate the effectiveness of a subsurface drainage network of a clayey field located in southern Finland. The subsurface drainage system was originally installed in the area in 1971 and the drainage efficiency was improved in 1995 and 2005 by installing new drains. FLUSH was calibrated against total runoff and drain discharge data from 2010 to 2011 and validated against total runoff in 2012. The model supported quantification of runoff fractions via the three installed drainage networks. Model realisations were produced to investigate the extent of the runoff contributing areas and the effect of the drainage parameters on subsurface drain discharge. The analysis showed that better model performance was achieved when the efficiency of the oldest drainage network (installed in 1971) was decreased. Our analysis method can reveal the drainage system performance but not the reason for the deterioration of the drainage performance. Tillage layer runoff from the field was originally computed by subtracting drain discharge from the total runoff. The drains installed in 1995 bypass the measurement system, which renders the tillage layer runoff calculation procedure invalid after 1995. Therefore, this article suggests use of a local correction coefficient based on the simulations for further research utilizing data from the study area.

Validation of network communicability metrics for the analysis of brain structural networks.

Directory of Open Access Journals (Sweden)

Jennifer Andreotti

Full Text Available Computational network analysis provides new methods to analyze the brain's structural organization based on diffusion imaging tractography data. Networks are characterized by global and local metrics that have recently given promising insights into diagnosis and the further understanding of psychiatric and neurologic disorders. Most of these metrics are based on the idea that information in a network flows along the shortest paths. In contrast to this notion, communicability is a broader measure of connectivity which assumes that information could flow along all possible paths between two nodes. In our work, the features of network metrics related to communicability were explored for the first time in the healthy structural brain network. In addition, the sensitivity of such metrics was analysed using simulated lesions to specific nodes and network connections. Results showed advantages of communicability over conventional metrics in detecting densely connected nodes as well as subsets of nodes vulnerable to lesions. In addition, communicability centrality was shown to be widely affected by the lesions and the changes were negatively correlated with the distance from lesion site. In summary, our analysis suggests that communicability metrics that may provide an insight into the integrative properties of the structural brain network and that these metrics may be useful for the analysis of brain networks in the presence of lesions. Nevertheless, the interpretation of communicability is not straightforward; hence these metrics should be used as a supplement to the more standard connectivity network metrics.

Thermodynamics of random reaction networks.

Science.gov (United States)

Fischer, Jakob; Kleidon, Axel; Dittrich, Peter

2015-01-01

Reaction networks are useful for analyzing reaction systems occurring in chemistry, systems biology, or Earth system science. Despite the importance of thermodynamic disequilibrium for many of those systems, the general thermodynamic properties of reaction networks are poorly understood. To circumvent the problem of sparse thermodynamic data, we generate artificial reaction networks and investigate their non-equilibrium steady state for various boundary fluxes. We generate linear and nonlinear networks using four different complex network models (Erdős-Rényi, Barabási-Albert, Watts-Strogatz, Pan-Sinha) and compare their topological properties with real reaction networks. For similar boundary conditions the steady state flow through the linear networks is about one order of magnitude higher than the flow through comparable nonlinear networks. In all networks, the flow decreases with the distance between the inflow and outflow boundary species, with Watts-Strogatz networks showing a significantly smaller slope compared to the three other network types. The distribution of entropy production of the individual reactions inside the network follows a power law in the intermediate region with an exponent of circa -1.5 for linear and -1.66 for nonlinear networks. An elevated entropy production rate is found in reactions associated with weakly connected species. This effect is stronger in nonlinear networks than in the linear ones. Increasing the flow through the nonlinear networks also increases the number of cycles and leads to a narrower distribution of chemical potentials. We conclude that the relation between distribution of dissipation, network topology and strength of disequilibrium is nontrivial and can be studied systematically by artificial reaction networks.

Modeling MAC layer for powerline communications networks

Science.gov (United States)

Hrasnica, Halid; Haidine, Abdelfatteh

2001-02-01

The usage of electrical power distribution networks for voice and data transmission, called Powerline Communications, becomes nowadays more and more attractive, particularly in the telecommunication access area. The most important reasons for that are the deregulation of the telecommunication market and a fact that the access networks are still property of former monopolistic companies. In this work, first we analyze a PLC network and system structure as well as a disturbance scenario in powerline networks. After that, we define a logical structure of the powerline MAC layer and propose the reservation MAC protocols for the usage in the PLC network which provides collision free data transmission. This makes possible better network utilization and realization of QoS guarantees which can make PLC networks competitive to other access technologies.

True Nature of Supply Network Communication Structure

Directory of Open Access Journals (Sweden)

Lokhman Hakim bin Osman

2016-04-01

Full Text Available Globalization of world economy has altered the definition of organizational structure. Global supply chain can no longer be viewed as an arm-length structure. It has become more complex. The complexity demands deeper research and understanding. This research analyzed a structure of supply network in an attempt to elucidate the true structure of the supply network. Using the quantitative Social Network Analysis methodology, findings of this study indicated that, the structure of the supply network differs depending on the types of network relations. An important implication of these findings would be a more focus resource management upon network relationship development that is based on firms’ positions in the different network structure. This research also contributes to the various strategies of effective and efficient supply chain management.

English and Chinese languages as weighted complex networks

Science.gov (United States)

Sheng, Long; Li, Chunguang

2009-06-01

In this paper, we analyze statistical properties of English and Chinese written human language within the framework of weighted complex networks. The two language networks are based on an English novel and a Chinese biography, respectively, and both of the networks are constructed in the same way. By comparing the intensity and density of connections between the two networks, we find that high weight connections in Chinese language networks prevail more than those in English language networks. Furthermore, some of the topological and weighted quantities are compared. The results display some differences in the structural organizations between the two language networks. These observations indicate that the two languages may have different linguistic mechanisms and different combinatorial natures.

Water Network Tool for Resilience (WNTR) User Manual

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The Water Network Tool for Resilience (WNTR) is a new Python package designed to simulate and analyze resilience of water distribution networks to a variety of disaster scenarios. WNTR can help water utilities to explore the capacity of their systems to handle disasters and gui...

A Network Reconfiguration Method Considering Data Uncertainties in Smart Distribution Networks

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Ke-yan Liu

2017-05-01

Full Text Available This work presents a method for distribution network reconfiguration with the simultaneous consideration of distributed generation (DG allocation. The uncertainties of load fluctuation before the network reconfiguration are also considered. Three optimal objectives, including minimal line loss cost, minimum Expected Energy Not Supplied, and minimum switch operation cost, are investigated. The multi-objective optimization problem is further transformed into a single-objective optimization problem by utilizing weighting factors. The proposed network reconfiguration method includes two periods. The first period is to create a feasible topology network by using binary particle swarm optimization (BPSO. Then the DG allocation problem is solved by utilizing sensitivity analysis and a Harmony Search algorithm (HSA. In the meanwhile, interval analysis is applied to deal with the uncertainties of load and devices parameters. Test cases are studied using the standard IEEE 33-bus and PG&E 69-bus systems. Different scenarios and comparisons are analyzed in the experiments. The results show the applicability of the proposed method. The performance analysis of the proposed method is also investigated. The computational results indicate that the proposed network reconfiguration algorithm is feasible.

Nuclear plant analyzer development at INEL

International Nuclear Information System (INIS)

Laats, E.T.; Russell, K.D.; Stewart, H.D.

1983-01-01

The Office of Nuclear Regulatory Research of the US Nuclear Regulatory Commission (NRC) has sponsored development of a software-hardware system called the Nuclear Plant Analyzer (NPA). This paper describes the status of the NPA project at the INEL after one year of development. When completed, the NPA will be an integrated network of analytical tools for performing reactor plant analyses. Development of the NPA in FY-1983 progressed along two parallel pathways; namely, conceptual planning and software development. Regarding NPA planning, and extensive effort was conducted to define the function requirements of the NPA, conceptual design, and hardware needs. Regarding software development conducted in FY-1983, all development was aimed toward demonstrating the basic concept and feasibility of the NPA. Nearly all software was developed and resides on the INEL twin Control Data Corporation 176 mainframe computers

Relationship between Entropy and Dimension of Financial Correlation-Based Network

Directory of Open Access Journals (Sweden)

Chun-xiao Nie

2018-03-01

Full Text Available We analyze the dimension of a financial correlation-based network and apply our analysis to characterize the complexity of the network. First, we generalize the volume-based dimension and find that it is well defined by the correlation-based network. Second, we establish the relationship between the Rényi index and the volume-based dimension. Third, we analyze the meaning of the dimensions sequence, which characterizes the level of departure from the comparison benchmark based on the randomized time series. Finally, we use real stock market data from three countries for empirical analysis. In some cases, our proposed analysis method can more accurately capture the structural differences of networks than the power law index commonly used in previous studies.

Entropy of dynamical social networks

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Zhao, Kun; Karsai, Marton; Bianconi, Ginestra

2012-02-01

Dynamical social networks are evolving rapidly and are highly adaptive. Characterizing the information encoded in social networks is essential to gain insight into the structure, evolution, adaptability and dynamics. Recently entropy measures have been used to quantify the information in email correspondence, static networks and mobility patterns. Nevertheless, we still lack methods to quantify the information encoded in time-varying dynamical social networks. In this talk we present a model to quantify the entropy of dynamical social networks and use this model to analyze the data of phone-call communication. We show evidence that the entropy of the phone-call interaction network changes according to circadian rhythms. Moreover we show that social networks are extremely adaptive and are modified by the use of technologies such as mobile phone communication. Indeed the statistics of duration of phone-call is described by a Weibull distribution and is significantly different from the distribution of duration of face-to-face interactions in a conference. Finally we investigate how much the entropy of dynamical social networks changes in realistic models of phone-call or face-to face interactions characterizing in this way different type human social behavior.

Energy and exergy analysis of low temperature district heating network

International Nuclear Information System (INIS)

Li, Hongwei; Svendsen, Svend

2012-01-01

Low temperature district heating with reduced network supply and return temperature provides better match of the low quality building heating demand and the low quality heating supply from waste heat or renewable energy. In this paper, a hypothetical low temperature district heating network is designed to supply heating for 30 low energy detached residential houses. The network operational supply/return temperature is set as 55 °C/25 °C, which is in line with a pilot project carried out in Denmark. Two types of in-house substations are analyzed to supply the consumer domestic hot water demand. The space heating demand is supplied through floor heating in the bathroom and low temperature radiators in the rest of rooms. The network thermal and hydraulic conditions are simulated under steady state. A district heating network design and simulation code is developed to incorporate the network optimization procedure and the network simultaneous factor. Through the simulation, the overall system energy and exergy efficiencies are calculated and the exergy losses for the major district heating system components are identified. Based on the results, suggestions are given to further reduce the system energy/exergy losses and increase the quality match between the consumer heating demand and the district heating supply. -- Highlights: ► Exergy and energy analysis for low and medium temperature district heating systems. ► Different district heating network dimensioning methods are analyzed. ► Major exergy losses are identified in the district heating network and the in-house substations. ► Advantages to apply low temperature district heating are highlighted through exergy analysis. ► The influence of thermal by-pass on system exergy/energy performance is analyzed.

Optimal topologies for maximizing network transmission capacity

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Chen, Zhenhao; Wu, Jiajing; Rong, Zhihai; Tse, Chi K.

2018-04-01

It has been widely demonstrated that the structure of a network is a major factor that affects its traffic dynamics. In this work, we try to identify the optimal topologies for maximizing the network transmission capacity, as well as to build a clear relationship between structural features of a network and the transmission performance in terms of traffic delivery. We propose an approach for designing optimal network topologies against traffic congestion by link rewiring and apply them on the Barabási-Albert scale-free, static scale-free and Internet Autonomous System-level networks. Furthermore, we analyze the optimized networks using complex network parameters that characterize the structure of networks, and our simulation results suggest that an optimal network for traffic transmission is more likely to have a core-periphery structure. However, assortative mixing and the rich-club phenomenon may have negative impacts on network performance. Based on the observations of the optimized networks, we propose an efficient method to improve the transmission capacity of large-scale networks.

Interorganizational Innovation in Systemic Networks

DEFF Research Database (Denmark)

Seemann, Janne; Dinesen, Birthe; Gustafsson, Jeppe

2013-01-01

patients with chronic obstructive pulmonary disease (COPD) to avoid readmission, perform self monitoring and to maintain rehabilitation in their homes. The aim of the paper is to identify, analyze and discuss innovation dynamics in the COPD network and on a preliminary basis to identify implications...... for managing innovations in systemic networks. The main argument of this paper is that innovation dynamics in systemic networks should be understood as a complex interplay of four logics: 1) Fragmented innovation, 2) Interface innovation, 3) Competing innovation, 4) Co-innovation. The findings indicate...... that linear n-stage models by reducing complexity and flux end up focusing only on the surface of the network and are thus unable to grasp important aspects of network dynamics. The paper suggests that there is a need for a more dynamic innovation model able to grasp the whole picture of dynamics in systemic...

The Graph Laplacian and the Dynamics of Complex Networks

Energy Technology Data Exchange (ETDEWEB)

Thulasidasan, Sunil [Los Alamos National Laboratory

2012-06-11

In this talk, we explore the structure of networks from a spectral graph-theoretic perspective by analyzing the properties of the Laplacian matrix associated with the graph induced by a network. We will see how the eigenvalues of the graph Laplacian relate to the underlying network structure and dynamics and provides insight into a phenomenon frequently observed in real world networks - the emergence of collective behavior from purely local interactions seen in the coordinated motion of animals and phase transitions in biological networks, to name a few.

Optimal transport on supply-demand networks.

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