WorldWideScience

Sample records for hierarchical networks consists

  1. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    of different types of hierarchical networks. This is supplemented by a review of ring network design problems and a presentation of a model allowing for modeling most hierarchical networks. We use methods based on linear programming to design the hierarchical networks. Thus, a brief introduction to the various....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...... linear programming based methods is included. The thesis is thus suitable as a foundation for study of design of hierarchical networks. The major contribution of the thesis consists of seven papers which are included in the appendix. The papers address hierarchical network design and/or ring network...

  2. Hierarchical Network Design

    DEFF Research Database (Denmark)

    Thomadsen, Tommy

    2005-01-01

    Communication networks are immensely important today, since both companies and individuals use numerous services that rely on them. This thesis considers the design of hierarchical (communication) networks. Hierarchical networks consist of layers of networks and are well-suited for coping...... the clusters. The design of hierarchical networks involves clustering of nodes, hub selection, and network design, i.e. selection of links and routing of ows. Hierarchical networks have been in use for decades, but integrated design of these networks has only been considered for very special types of networks....... The thesis investigates models for hierarchical network design and methods used to design such networks. In addition, ring network design is considered, since ring networks commonly appear in the design of hierarchical networks. The thesis introduces hierarchical networks, including a classification scheme...

  3. Detecting Hierarchical Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard;

    2012-01-01

    a generative Bayesian model that is able to infer whether hierarchies are present or not from a hypothesis space encompassing all types of hierarchical tree structures. For efficient inference we propose a collapsed Gibbs sampling procedure that jointly infers a partition and its hierarchical structure......Many real-world networks exhibit hierarchical organization. Previous models of hierarchies within relational data has focused on binary trees; however, for many networks it is unknown whether there is hierarchical structure, and if there is, a binary tree might not account well for it. We propose....... On synthetic and real data we demonstrate that our model can detect hierarchical structure leading to better link-prediction than competing models. Our model can be used to detect if a network exhibits hierarchical structure, thereby leading to a better comprehension and statistical account the network....

  4. 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...

  5. Network Consistent Data Association.

    Science.gov (United States)

    Chakraborty, Anirban; Das, Abir; Roy-Chowdhury, Amit K

    2016-09-01

    Existing data association techniques mostly focus on matching pairs of data-point sets and then repeating this process along space-time to achieve long term correspondences. However, in many problems such as person re-identification, a set of data-points may be observed at multiple spatio-temporal locations and/or by multiple agents in a network and simply combining the local pairwise association results between sets of data-points often leads to inconsistencies over the global space-time horizons. In this paper, we propose a Novel Network Consistent Data Association (NCDA) framework formulated as an optimization problem that not only maintains consistency in association results across the network, but also improves the pairwise data association accuracies. The proposed NCDA can be solved as a binary integer program leading to a globally optimal solution and is capable of handling the challenging data-association scenario where the number of data-points varies across different sets of instances in the network. We also present an online implementation of NCDA method that can dynamically associate new observations to already observed data-points in an iterative fashion, while maintaining network consistency. We have tested both the batch and the online NCDA in two application areas-person re-identification and spatio-temporal cell tracking and observed consistent and highly accurate data association results in all the cases.

  6. Onboard hierarchical network

    Science.gov (United States)

    Tunesi, Luca; Armbruster, Philippe

    2004-02-01

    The objective of this paper is to demonstrate a suitable hierarchical networking solution to improve capabilities and performances of space systems, with significant recurrent costs saving and more efficient design & manufacturing flows. Classically, a satellite can be split in two functional sub-systems: the platform and the payload complement. The platform is in charge of providing power, attitude & orbit control and up/down-link services, whereas the payload represents the scientific and/or operational instruments/transponders and embodies the objectives of the mission. One major possibility to improve the performance of payloads, by limiting the data return to pertinent information, is to process data on board thanks to a proper implementation of the payload data system. In this way, it is possible to share non-recurring development costs by exploiting a system that can be adopted by the majority of space missions. It is believed that the Modular and Scalable Payload Data System, under development by ESA, provides a suitable solution to fulfil a large range of future mission requirements. The backbone of the system is the standardised high data rate SpaceWire network http://www.ecss.nl/. As complement, a lower speed command and control bus connecting peripherals is required. For instance, at instrument level, there is a need for a "local" low complexity bus, which gives the possibility to command and control sensors and actuators. Moreover, most of the connections at sub-system level are related to discrete signals management or simple telemetry acquisitions, which can easily and efficiently be handled by a local bus. An on-board hierarchical network can therefore be defined by interconnecting high-speed links and local buses. Additionally, it is worth stressing another important aspect of the design process: Agencies and ESA in particular are frequently confronted with a big consortium of geographically spread companies located in different countries, each one

  7. Universal hierarchical behavior of citation networks

    CERN Document Server

    Mones, Enys; Vicsek, Tamás

    2014-01-01

    Many of the essential features of the evolution of scientific research are imprinted in the structure of citation networks. Connections in these networks imply information about the transfer of knowledge among papers, or in other words, edges describe the impact of papers on other publications. This inherent meaning of the edges infers that citation networks can exhibit hierarchical features, that is typical of networks based on decision-making. In this paper, we investigate the hierarchical structure of citation networks consisting of papers in the same field. We find that the majority of the networks follow a universal trend towards a highly hierarchical state, and i) the various fields display differences only concerning their phase in life (distance from the "birth" of a field) or ii) the characteristic time according to which they are approaching the stationary state. We also show by a simple argument that the alterations in the behavior are related to and can be understood by the degree of specializatio...

  8. Memory Stacking in Hierarchical Networks.

    Science.gov (United States)

    Westö, Johan; May, Patrick J C; Tiitinen, Hannu

    2016-02-01

    Robust representations of sounds with a complex spectrotemporal structure are thought to emerge in hierarchically organized auditory cortex, but the computational advantage of this hierarchy remains unknown. Here, we used computational models to study how such hierarchical structures affect temporal binding in neural networks. We equipped individual units in different types of feedforward networks with local memory mechanisms storing recent inputs and observed how this affected the ability of the networks to process stimuli context dependently. Our findings illustrate that these local memories stack up in hierarchical structures and hence allow network units to exhibit selectivity to spectral sequences longer than the time spans of the local memories. We also illustrate that short-term synaptic plasticity is a potential local memory mechanism within the auditory cortex, and we show that it can bring robustness to context dependence against variation in the temporal rate of stimuli, while introducing nonlinearities to response profiles that are not well captured by standard linear spectrotemporal receptive field models. The results therefore indicate that short-term synaptic plasticity might provide hierarchically structured auditory cortex with computational capabilities important for robust representations of spectrotemporal patterns.

  9. Hierarchical Neural Network Structures for Phoneme Recognition

    CERN Document Server

    Vasquez, Daniel; Minker, Wolfgang

    2013-01-01

    In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are evaluated on the phoneme recognition task where a  Hybrid Hidden Markov Model/Artificial Neural Network paradigm is used. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron. Additionally, the output of the first level serves as a second level input. The computational speed of the phoneme recognizer can be substantially increased by removing redundant information still contained at the first level output. Several techniques based on temporal and phonetic criteria have been investigated to remove this redundant information. The computational time could be reduced by 57% whilst keeping the system accuracy comparable to the baseline hierarchical approach.

  10. Hierarchical mutual information for the comparison of hierarchical community structures in complex networks

    CERN Document Server

    Perotti, Juan Ignacio; Caldarelli, Guido

    2015-01-01

    The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the {\\it hierarchical mutual information}, which is a generalization of the traditional mutual information, and allows to compare hierarchical partitions and hierarchical community structures. The {\\it normalized} version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here, the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies, and on the hierarchical ...

  11. Hierarchical networks of scientific journals

    CERN Document Server

    Palla, Gergely; Mones, Enys; Pollner, Péter; Vicsek, Tamás

    2015-01-01

    Scientific journals are the repositories of the gradually accumulating knowledge of mankind about the world surrounding us. Just as our knowledge is organised into classes ranging from major disciplines, subjects and fields to increasingly specific topics, journals can also be categorised into groups using various metrics. In addition to the set of topics characteristic for a journal, they can also be ranked regarding their relevance from the point of overall influence. One widespread measure is impact factor, but in the present paper we intend to reconstruct a much more detailed description by studying the hierarchical relations between the journals based on citation data. We use a measure related to the notion of m-reaching centrality and find a network which shows the level of influence of a journal from the point of the direction and efficiency with which information spreads through the network. We can also obtain an alternative network using a suitably modified nested hierarchy extraction method applied ...

  12. Hierarchical Network Design Using Simulated Annealing

    DEFF Research Database (Denmark)

    Thomadsen, Tommy; Clausen, Jens

    2002-01-01

    The hierarchical network problem is the problem of finding the least cost network, with nodes divided into groups, edges connecting nodes in each groups and groups ordered in a hierarchy. The idea of hierarchical networks comes from telecommunication networks where hierarchies exist. Hierarchical...... networks are described and a mathematical model is proposed for a two level version of the hierarchical network problem. The problem is to determine which edges should connect nodes, and how demand is routed in the network. The problem is solved heuristically using simulated annealing which as a sub......-algorithm uses a construction algorithm to determine edges and route the demand. Performance for different versions of the algorithm are reported in terms of runtime and quality of the solutions. The algorithm is able to find solutions of reasonable quality in approximately 1 hour for networks with 100 nodes....

  13. Hierarchical modularity in human brain functional networks

    CERN Document Server

    Meunier, D; Fornito, A; Ersche, K D; Bullmore, E T; 10.3389/neuro.11.037.2009

    2010-01-01

    The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at ...

  14. Consistence of Network Filtering Rules

    Institute of Scientific and Technical Information of China (English)

    SHE Kun; WU Yuancheng; HUANG Juncai; ZHOU Mingtian

    2004-01-01

    The inconsistence of firewall/VPN(Virtual Private Network) rule makes a huge maintainable cost.With development of Multinational Company,SOHO office,E-government the number of firewalls/VPN will increase rapidly.Rule table in stand-alone or network will be increased in geometric series accordingly.Checking the consistence of rule table manually is inadequate.A formal approach can define semantic consistence,make a theoretic foundation of intelligent management about rule tables.In this paper,a kind of formalization of host rules and network ones for auto rule-validation based on SET theory were proporsed and a rule validation scheme was defined.The analysis results show the superior performance of the methods and demonstrate its potential for the intelligent management based on rule tables.

  15. Modular, Hierarchical Learning By Artificial Neural Networks

    Science.gov (United States)

    Baldi, Pierre F.; Toomarian, Nikzad

    1996-01-01

    Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.

  16. Genetic Algorithm for Hierarchical Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Sajid Hussain

    2007-09-01

    Full Text Available Large scale wireless sensor networks (WSNs can be used for various pervasive and ubiquitous applications such as security, health-care, industry automation, agriculture, environment and habitat monitoring. As hierarchical clusters can reduce the energy consumption requirements for WSNs, we investigate intelligent techniques for cluster formation and management. A genetic algorithm (GA is used to create energy efficient clusters for data dissemination in wireless sensor networks. The simulation results show that the proposed intelligent hierarchical clustering technique can extend the network lifetime for different network deployment environments.

  17. Hierarchical social networks and information flow

    Science.gov (United States)

    López, Luis; F. F. Mendes, Jose; Sanjuán, Miguel A. F.

    2002-12-01

    Using a simple model for the information flow on social networks, we show that the traditional hierarchical topologies frequently used by companies and organizations, are poorly designed in terms of efficiency. Moreover, we prove that this type of structures are the result of the individual aim of monopolizing as much information as possible within the network. As the information is an appropriate measurement of centrality, we conclude that this kind of topology is so attractive for leaders, because the global influence each actor has within the network is completely determined by the hierarchical level occupied.

  18. Strategic games on a hierarchical network model

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Among complex network models, the hierarchical network model is the one most close to such real networks as world trade web, metabolic network, WWW, actor network, and so on. It has not only the property of power-law degree distribution, but growth based on growth and preferential attachment, showing the scale-free degree distribution property. In this paper, we study the evolution of cooperation on a hierarchical network model, adopting the prisoner's dilemma (PD) game and snowdrift game (SG) as metaphors of the interplay between connected nodes. BA model provides a unifying framework for the emergence of cooperation. But interestingly, we found that on hierarchical model, there is no sign of cooperation for PD game, while the frequency of cooperation decreases as the common benefit decreases for SG. By comparing the scaling clustering coefficient properties of the hierarchical network model with that of BA model, we found that the former amplifies the effect of hubs. Considering different performances of PD game and SG on complex network, we also found that common benefit leads to cooperation in the evolution. Thus our study may shed light on the emergence of cooperation in both natural and social environments.

  19. Ultrafast Hierarchical OTDM/WDM Network

    Directory of Open Access Journals (Sweden)

    Hideyuki Sotobayashi

    2003-12-01

    Full Text Available Ultrafast hierarchical OTDM/WDM network is proposed for the future core-network. We review its enabling technologies: C- and L-wavelength-band generation, OTDM-WDM mutual multiplexing format conversions, and ultrafast OTDM wavelengthband conversions.

  20. Noise enhances information transfer in hierarchical networks.

    Science.gov (United States)

    Czaplicka, Agnieszka; Holyst, Janusz A; Sloot, Peter M A

    2013-01-01

    We study the influence of noise on information transmission in the form of packages shipped between nodes of hierarchical networks. Numerical simulations are performed for artificial tree networks, scale-free Ravasz-Barabási networks as well for a real network formed by email addresses of former Enron employees. Two types of noise are considered. One is related to packet dynamics and is responsible for a random part of packets paths. The second one originates from random changes in initial network topology. We find that the information transfer can be enhanced by the noise. The system possesses optimal performance when both kinds of noise are tuned to specific values, this corresponds to the Stochastic Resonance phenomenon. There is a non-trivial synergy present for both noisy components. We found also that hierarchical networks built of nodes of various degrees are more efficient in information transfer than trees with a fixed branching factor.

  1. Biased trapping issue on weighted hierarchical networks

    Indian Academy of Sciences (India)

    Meifeng Dai; Jie Liu; Feng Zhu

    2014-10-01

    In this paper, we present trapping issues of weight-dependent walks on weighted hierarchical networks which are based on the classic scale-free hierarchical networks. Assuming that edge’s weight is used as local information by a random walker, we introduce a biased walk. The biased walk is that a walker, at each step, chooses one of its neighbours with a probability proportional to the weight of the edge. We focus on a particular case with the immobile trap positioned at the hub node which has the largest degree in the weighted hierarchical networks. Using a method based on generating functions, we determine explicitly the mean first-passage time (MFPT) for the trapping issue. Let parameter (0 < < 1) be the weight factor. We show that the efficiency of the trapping process depends on the parameter a; the smaller the value of a, the more efficient is the trapping process.

  2. Non-homogeneous fractal hierarchical weighted networks.

    Science.gov (United States)

    Dong, Yujuan; Dai, Meifeng; Ye, Dandan

    2015-01-01

    A model of fractal hierarchical structures that share the property of non-homogeneous weighted networks is introduced. These networks can be completely and analytically characterized in terms of the involved parameters, i.e., the size of the original graph Nk and the non-homogeneous weight scaling factors r1, r2, · · · rM. We also study the average weighted shortest path (AWSP), the average degree and the average node strength, taking place on the non-homogeneous hierarchical weighted networks. Moreover the AWSP is scrupulously calculated. We show that the AWSP depends on the number of copies and the sum of all non-homogeneous weight scaling factors in the infinite network order limit.

  3. Hierarchical community structure in complex (social) networks

    CERN Document Server

    Massaro, Emanuele

    2014-01-01

    The investigation of community structure in networks is a task of great importance in many disciplines, namely physics, sociology, biology and computer science where systems are often represented as graphs. One of the challenges is to find local communities from a local viewpoint in a graph without global information in order to reproduce the subjective hierarchical vision for each vertex. In this paper we present the improvement of an information dynamics algorithm in which the label propagation of nodes is based on the Markovian flow of information in the network under cognitive-inspired constraints \\cite{Massaro2012}. In this framework we have introduced two more complex heuristics that allow the algorithm to detect the multi-resolution hierarchical community structure of networks from a source vertex or communities adopting fixed values of model's parameters. Experimental results show that the proposed methods are efficient and well-behaved in both real-world and synthetic networks.

  4. The Hourglass Effect in Hierarchical Dependency Networks

    CERN Document Server

    Sabrin, Kaeser M

    2016-01-01

    Many hierarchically modular systems are structured in a way that resembles a bow-tie or hourglass. This "hourglass effect" means that the system generates many outputs from many inputs through a relatively small number of intermediate modules that are critical for the operation of the entire system (the waist of the hourglass). We investigate the hourglass effect in general (not necessarily layered) hierarchical dependency networks. Our analysis focuses on the number of source-to-target dependency paths that traverse each vertex, and it identifies the core of a dependency network as the smallest set of vertices that collectively cover almost all dependency paths. We then examine if a given network exhibits the hourglass property or not, comparing its core size with a "flat" (i.e., non-hierarchical) network that preserves the source dependencies of each target in the original network. As a possible explanation for the hourglass effect, we propose the Reuse Preference (RP) model that captures the bias of new mo...

  5. Hierarchical Ring Network Design Using Branch-and-Price

    DEFF Research Database (Denmark)

    Thomadsen, Tommy; Stidsen, Thomas K.

    2005-01-01

    We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed l...... for jointly solving the clustering problem, the metro ring design problem and the routing problem. Computational results are given for networks with up to 36 nodes.......We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed...... link establishment costs and the link capacity costs into account. Hierarchical ring network design problems combines the following optimization problems: Clustering, hub selection, metro ring design, federal ring design and routing problems. In this paper a branch-and-price algorithm is presented...

  6. Synchronization patterns: from network motifs to hierarchical networks

    Science.gov (United States)

    Krishnagopal, Sanjukta; Lehnert, Judith; Poel, Winnie; Zakharova, Anna; Schöll, Eckehard

    2017-03-01

    We investigate complex synchronization patterns such as cluster synchronization and partial amplitude death in networks of coupled Stuart-Landau oscillators with fractal connectivities. The study of fractal or self-similar topology is motivated by the network of neurons in the brain. This fractal property is well represented in hierarchical networks, for which we present three different models. In addition, we introduce an analytical eigensolution method and provide a comprehensive picture of the interplay of network topology and the corresponding network dynamics, thus allowing us to predict the dynamics of arbitrarily large hierarchical networks simply by analysing small network motifs. We also show that oscillation death can be induced in these networks, even if the coupling is symmetric, contrary to previous understanding of oscillation death. Our results show that there is a direct correlation between topology and dynamics: hierarchical networks exhibit the corresponding hierarchical dynamics. This helps bridge the gap between mesoscale motifs and macroscopic networks. This article is part of the themed issue 'Horizons of cybernetical physics'.

  7. Hierarchicality of trade flow networks reveals complexity of products.

    Science.gov (United States)

    Shi, Peiteng; Zhang, Jiang; Yang, Bo; Luo, Jingfei

    2014-01-01

    With globalization, countries are more connected than before by trading flows, which amounts to at least 36 trillion dollars today. Interestingly, around 30-60 percents of exports consist of intermediate products in global. Therefore, the trade flow network of particular product with high added values can be regarded as value chains. The problem is weather we can discriminate between these products from their unique flow network structure? This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent η can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, it is pointed out that the flow networks of products with higher added values and complexity like machinary, transport equipment etc. have larger exponents, meaning that their trade flow networks are more hierarchical. As a result, without the extra data like global input-output table, we can identify the product categories with higher complexity, and the relative importance of a country in the global value chain by the trading network solely.

  8. Hierarchicality of trade flow networks reveals complexity of products.

    Directory of Open Access Journals (Sweden)

    Peiteng Shi

    Full Text Available With globalization, countries are more connected than before by trading flows, which amounts to at least 36 trillion dollars today. Interestingly, around 30-60 percents of exports consist of intermediate products in global. Therefore, the trade flow network of particular product with high added values can be regarded as value chains. The problem is weather we can discriminate between these products from their unique flow network structure? This paper applies the flow analysis method developed in ecology to 638 trading flow networks of different products. We claim that the allometric scaling exponent η can be used to characterize the degree of hierarchicality of a flow network, i.e., whether the trading products flow on long hierarchical chains. Then, it is pointed out that the flow networks of products with higher added values and complexity like machinary, transport equipment etc. have larger exponents, meaning that their trade flow networks are more hierarchical. As a result, without the extra data like global input-output table, we can identify the product categories with higher complexity, and the relative importance of a country in the global value chain by the trading network solely.

  9. First-passage phenomena in hierarchical networks

    CERN Document Server

    Tavani, Flavia

    2016-01-01

    In this paper we study Markov processes and related first passage problems on a class of weighted, modular graphs which generalize the Dyson hierarchical model. In these networks, the coupling strength between two nodes depends on their distance and is modulated by a parameter $\\sigma$. We find that, in the thermodynamic limit, ergodicity is lost and the "distant" nodes can not be reached. Moreover, for finite-sized systems, there exists a threshold value for $\\sigma$ such that, when $\\sigma$ is relatively large, the inhomogeneity of the coupling pattern prevails and "distant" nodes are hardly reached. The same analysis is carried on also for generic hierarchical graphs, where interactions are meant to involve $p$-plets ($p>2$) of nodes, finding that ergodicity is still broken in the thermodynamic limit, but no threshold value for $\\sigma$ is evidenced, ultimately due to a slow growth of the network diameter with the size.

  10. Design of Hierarchical Ring Networks Using Branch-and-Price

    DEFF Research Database (Denmark)

    Thomadsen, Tommy; Stidsen, Thomas K.

    2004-01-01

    We consider the problem of designing hierarchical two layer ring networks. The top layer consists of a federal-ring which establishes connection between a number of node disjoint metro-rings in a bottom layer. The objective is to minimize the costs of links in the network, taking both the fixed...... link establishment costs and the link capacity costs into account. The hierarchical two layer ring network design problem is solved in two stages: First the bottom layer, i.e. the metro-rings are designed, implicitly taking into account the capacity cost of the federal-ring. Then the federal......-ring is designed connecting the metro-rings, minimizing fixed link establishment costs of the federal-ring. A branch-and-price algorithm is presented for the design of the bottom layer and it is suggested that existing methods are used for the design of the federal-ring. Computational results are given...

  11. Learning Contextual Dependence With Convolutional Hierarchical Recurrent Neural Networks

    Science.gov (United States)

    Zuo, Zhen; Shuai, Bing; Wang, Gang; Liu, Xiao; Wang, Xingxing; Wang, Bing; Chen, Yushi

    2016-07-01

    Existing deep convolutional neural networks (CNNs) have shown their great success on image classification. CNNs mainly consist of convolutional and pooling layers, both of which are performed on local image areas without considering the dependencies among different image regions. However, such dependencies are very important for generating explicit image representation. In contrast, recurrent neural networks (RNNs) are well known for their ability of encoding contextual information among sequential data, and they only require a limited number of network parameters. General RNNs can hardly be directly applied on non-sequential data. Thus, we proposed the hierarchical RNNs (HRNNs). In HRNNs, each RNN layer focuses on modeling spatial dependencies among image regions from the same scale but different locations. While the cross RNN scale connections target on modeling scale dependencies among regions from the same location but different scales. Specifically, we propose two recurrent neural network models: 1) hierarchical simple recurrent network (HSRN), which is fast and has low computational cost; and 2) hierarchical long-short term memory recurrent network (HLSTM), which performs better than HSRN with the price of more computational cost. In this manuscript, we integrate CNNs with HRNNs, and develop end-to-end convolutional hierarchical recurrent neural networks (C-HRNNs). C-HRNNs not only make use of the representation power of CNNs, but also efficiently encodes spatial and scale dependencies among different image regions. On four of the most challenging object/scene image classification benchmarks, our C-HRNNs achieve state-of-the-art results on Places 205, SUN 397, MIT indoor, and competitive results on ILSVRC 2012.

  12. HIDEN: Hierarchical decomposition of regulatory networks

    Directory of Open Access Journals (Sweden)

    Gülsoy Günhan

    2012-09-01

    Full Text Available Abstract Background Transcription factors regulate numerous cellular processes by controlling the rate of production of each gene. The regulatory relations are modeled using transcriptional regulatory networks. Recent studies have shown that such networks have an underlying hierarchical organization. We consider the problem of discovering the underlying hierarchy in transcriptional regulatory networks. Results We first transform this problem to a mixed integer programming problem. We then use existing tools to solve the resulting problem. For larger networks this strategy does not work due to rapid increase in running time and space usage. We use divide and conquer strategy for such networks. We use our method to analyze the transcriptional regulatory networks of E. coli, H. sapiens and S. cerevisiae. Conclusions Our experiments demonstrate that: (i Our method gives statistically better results than three existing state of the art methods; (ii Our method is robust against errors in the data and (iii Our method’s performance is not affected by the different topologies in the data.

  13. The hierarchical brain network for face recognition.

    Science.gov (United States)

    Zhen, Zonglei; Fang, Huizhen; Liu, Jia

    2013-01-01

    Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

  14. Antiferromagnetic Ising Model in Hierarchical Networks

    Science.gov (United States)

    Cheng, Xiang; Boettcher, Stefan

    2015-03-01

    The Ising antiferromagnet is a convenient model of glassy dynamics. It can introduce geometric frustrations and may give rise to a spin glass phase and glassy relaxation at low temperatures [ 1 ] . We apply the antiferromagnetic Ising model to 3 hierarchical networks which share features of both small world networks and regular lattices. Their recursive and fixed structures make them suitable for exact renormalization group analysis as well as numerical simulations. We first explore the dynamical behaviors using simulated annealing and discover an extremely slow relaxation at low temperatures. Then we employ the Wang-Landau algorithm to investigate the energy landscape and the corresponding equilibrium behaviors for different system sizes. Besides the Monte Carlo methods, renormalization group [ 2 ] is used to study the equilibrium properties in the thermodynamic limit and to compare with the results from simulated annealing and Wang-Landau sampling. Supported through NSF Grant DMR-1207431.

  15. Consistency Analysis of Network Traffic Repositories

    NARCIS (Netherlands)

    Lastdrager, Elmer; Pras, Aiko

    2009-01-01

    Traffic repositories with TCP/IP header information are very important for network analysis. Researchers often assume that such repositories reliably represent all traffic that has been flowing over the network; little thoughts are made regarding the consistency of these repositories. Still, for var

  16. Consistency of Network Traffic Repositories: An Overview

    NARCIS (Netherlands)

    Lastdrager, E.; Pras, A.

    2009-01-01

    Traffc repositories with TCP/IP header information are very important for network analysis. Researchers often assume that such repositories reliably represent all traffc that has been flowing over the network; little thoughts are made regarding the consistency of these repositories. Still, for vario

  17. Hierarchical Communication Network Architectures for Offshore Wind Power Farms

    Directory of Open Access Journals (Sweden)

    Mohamed A. Ahmed

    2014-05-01

    Full Text Available Nowadays, large-scale wind power farms (WPFs bring new challenges for both electric systems and communication networks. Communication networks are an essential part of WPFs because they provide real-time control and monitoring of wind turbines from a remote location (local control center. However, different wind turbine applications have different requirements in terms of data volume, latency, bandwidth, QoS, etc. This paper proposes a hierarchical communication network architecture that consist of a turbine area network (TAN, farm area network (FAN, and control area network (CAN for offshore WPFs. The two types of offshore WPFs studied are small-scale WPFs close to the grid and medium-scale WPFs far from the grid. The wind turbines are modelled based on the logical nodes (LN concepts of the IEC 61400-25 standard. To keep pace with current developments in wind turbine technology, the network design takes into account the extension of the LNs for both the wind turbine foundation and meteorological measurements. The proposed hierarchical communication network is based on Switched Ethernet. Servers at the control center are used to store and process the data received from the WPF. The network architecture is modelled and evaluated via OPNET. We investigated the end-to-end (ETE delay for different WPF applications. The results are validated by comparing the amount of generated sensing data with that of received traffic at servers. The network performance is evaluated, analyzed and discussed in view of end-to-end (ETE delay for different link bandwidths.

  18. Field experiment on a robust hierarchical metropolitan quantum cryptography network

    Institute of Scientific and Technical Information of China (English)

    XU FangXing; CHEN Wei; WANG Shuang; YIN ZhenQiang; ZHANG Yang; LIU Yun; ZHOU Zheng; ZHAO YiBo; LI HongWei; LIU Dong; HAN ZhengFu; GUO GuangCan

    2009-01-01

    these bureaus.The whole implementation including the hierarchical quantum cryptographic communication network links and the corresponding application software shows a big step toward the practical user-oriented network with a high security level.

  19. Consistently weighted measures for complex network topologies

    CERN Document Server

    Heitzig, Jobst; Zou, Yong; Marwan, Norbert; Kurths, Jürgen

    2011-01-01

    When network and graph theory are used in the study of complex systems, a typically finite set of nodes of the network under consideration is frequently either explicitly or implicitly considered representative of a much larger finite or infinite set of objects of interest. The selection procedure, e.g., formation of a subset or some kind of discretization or aggregation, typically results in individual nodes of the studied network representing quite differently sized parts of the domain of interest. This heterogeneity may induce substantial bias and artifacts in derived network statistics. To avoid this bias, we propose an axiomatic scheme based on the idea of {\\em node splitting invariance} to derive consistently weighted variants of various commonly used statistical network measures. The practical relevance and applicability of our approach is demonstrated for a number of example networks from different fields of research, and is shown to be of fundamental importance in particular in the study of climate n...

  20. A Hierarchical Sensor Network Based on Voronoi Diagram

    Institute of Scientific and Technical Information of China (English)

    SHANG Rui-qiang; ZHAO Jian-li; SUN Qiu-xia; WANG Guang-xing

    2006-01-01

    A hierarchical sensor network is proposed which places the sensing and routing capacity at different layer nodes.It thus simplifies the hardware design and reduces cost. Adopting Voronoi diagram in the partition of backbone network,a mathematical model of data aggregation based on hierarchical architecture is given. Simulation shows that the number of transmission data packages is sharply cut down in the network, thus reducing the needs in the bandwidth and energy resources and is thus well adapted to sensor networks.

  1. Automatic Construction of Hierarchical Road Networks

    Science.gov (United States)

    Yang, Weiping

    2016-06-01

    This paper describes an automated method of constructing a hierarchical road network given a single dataset, without the presence of thematic attributes. The method is based on a pattern graph which maintains nodes and paths as junctions and through-traffic roads. The hierarchy is formed incrementally in a top-down fashion for highways, ramps, and major roads directly connected to ramps; and bottom-up for the rest of major and minor roads. Through reasoning and analysis, ramps are identified as unique characteristics for recognizing and assembling high speed roads. The method makes distinctions on the types of ramps by articulating their connection patterns with highways. Major and minor roads will be identified by both quantitative and qualitative analysis of spatial properties and by discovering neighbourhood patterns revealed in the data. The result of the method would enrich data description and support comprehensive queries on sorted exit or entry points on highways and their related roads. The enrichment on road network data is important to a high successful rate of feature matching for road networks and to geospatial data integration.

  2. Hierarchical Network Models for Education Research: Hierarchical Latent Space Models

    Science.gov (United States)

    Sweet, Tracy M.; Thomas, Andrew C.; Junker, Brian W.

    2013-01-01

    Intervention studies in school systems are sometimes aimed not at changing curriculum or classroom technique, but rather at changing the way that teachers, teaching coaches, and administrators in schools work with one another--in short, changing the professional social networks of educators. Current methods of social network analysis are…

  3. Big Data Processing in Complex Hierarchical Network Systems

    CERN Document Server

    Polishchuk, Olexandr; Tyutyunnyk, Maria; Yadzhak, Mykhailo

    2016-01-01

    This article covers the problem of processing of Big Data that describe process of complex networks and network systems operation. It also introduces the notion of hierarchical network systems combination into associations and conglomerates alongside with complex networks combination into multiplexes. The analysis is provided for methods of global network structures study depending on the purpose of the research. Also the main types of information flows in complex hierarchical network systems being the basic components of associations and conglomerates are covered. Approaches are proposed for creation of efficient computing environments, distributed computations organization and information processing methods parallelization at different levels of system hierarchy.

  4. Retrieval capabilities of hierarchical networks: from Dyson to Hopfield.

    Science.gov (United States)

    Agliari, Elena; Barra, Adriano; Galluzzi, Andrea; Guerra, Francesco; Tantari, Daniele; Tavani, Flavia

    2015-01-16

    We consider statistical-mechanics models for spin systems built on hierarchical structures, which provide a simple example of non-mean-field framework. We show that the coupling decay with spin distance can give rise to peculiar features and phase diagrams much richer than their mean-field counterpart. In particular, we consider the Dyson model, mimicking ferromagnetism in lattices, and we prove the existence of a number of metastabilities, beyond the ordered state, which become stable in the thermodynamic limit. Such a feature is retained when the hierarchical structure is coupled with the Hebb rule for learning, hence mimicking the modular architecture of neurons, and gives rise to an associative network able to perform single pattern retrieval as well as multiple-pattern retrieval, depending crucially on the external stimuli and on the rate of interaction decay with distance; however, those emergent multitasking features reduce the network capacity with respect to the mean-field counterpart. The analysis is accomplished through statistical mechanics, Markov chain theory, signal-to-noise ratio technique, and numerical simulations in full consistency. Our results shed light on the biological complexity shown by real networks, and suggest future directions for understanding more realistic models.

  5. Reliable Point to Multipoint Hierarchical Routing in Scatternet Sensor Network

    Directory of Open Access Journals (Sweden)

    R.Dhaya

    2011-01-01

    Full Text Available In the recent development of communication, Bluetooth Scatternet wireless is a technology developed for wideband local accesses. Bluetooth technology is very popular because of its low cost and easy deployment which is based on IEEE 802.11standards. On the other hand Wireless Sensor Network (WSN consists of large number of sensor nodes distributed to monitor an environment and each node in a WSN consists of a small CPU, a sensing device and battery. Mostly, the sensor networks are distributed in an inconvenient location and it is difficult to recharge often. So routing in WSN is an important issue to consume energy and as well as to increase the life of the network, since a routing protocol finds the path between sources and sink. Moreover it is a challenging task to schedule the data between nodes in a scatternet in a congestive environment. Here this paper presents a new scheduling method for point to multi- point routing in Scatternet sensor network and the new dynamic routing method designed is cluster-based with hierarchical routing. The efficiency of this method is also compared in terms of energy consumption and the results show that the proposed routing is an energy efficient one which simultaneously increases the lifetime of the network.

  6. Category theoretic analysis of hierarchical protein materials and social networks.

    Directory of Open Access Journals (Sweden)

    David I Spivak

    Full Text Available Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine.

  7. Object recognition with hierarchical discriminant saliency networks

    Directory of Open Access Journals (Sweden)

    Sunhyoung eHan

    2014-09-01

    Full Text Available The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognitionmodel, the hierarchical discriminant saliency network (HDSN, whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. The HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a neuralnetwork implementation, all layers are convolutional and implement acombination of filtering, rectification, and pooling. The rectificationis performed with a parametric extension of the now popular rectified linearunits (ReLUs, whose parameters can be tuned for the detection of targetobject classes. This enables a number of functional enhancementsover neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation ofsaliency responses by the discriminant power of the underlying features,and the ability to detect both feature presence and absence.In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity totarget object classes and invariance. The resulting performance demonstrates benefits for all the functional enhancements of the HDSN.

  8. Object recognition with hierarchical discriminant saliency networks.

    Science.gov (United States)

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  9. A HIERARCHICAL INTRUSION DETECTION ARCHITECTURE FOR WIRELESS SENSOR NETWORKS

    Directory of Open Access Journals (Sweden)

    Hossein Jadidoleslamy

    2011-10-01

    Full Text Available Networks protection against different types of attacks is one of most important posed issue into the network andinformation security application domains. This problem on Wireless Sensor Networks (WSNs, in attention to theirspecial properties, has more importance. Now, there are some of proposed architectures and guide lines to protectWireless Sensor Networks (WSNs against different types of intrusions; but any one of them do not has acomprehensive view to this problem and they are usually designed and implemented in single-purpose; but, theproposed design in this paper tries to has been a comprehensive view to this issue by presenting a complete andcomprehensive Intrusion Detection Architecture (IDA. The main contribution of this architecture is its hierarchicalstructure; i.e., it is designed and applicable, in one or two levels, consistent to the application domain and itsrequired security level. Focus of this paper is on the clustering WSNs, designing and deploying Cluster-basedIntrusion Detection System (CIDS on cluster-heads and Wireless Sensor Network wide level Intrusion DetectionSystem (WSNIDS on the central server. Suppositions of the WSN and Intrusion Detection Architecture (IDA are:static and heterogeneous network, hierarchical and clustering structure, clusters' overlapping and using hierarchicalrouting protocol such as LEACH, but along with minor changes. Finally, the proposed idea has been verified bydesigning a questionnaire, representing it to some (about 50 people experts and then, analyzing and evaluating itsacquired results.

  10. Brain rhythms reveal a hierarchical network organization.

    Directory of Open Access Journals (Sweden)

    G Karl Steinke

    2011-10-01

    Full Text Available Recordings of ongoing neural activity with EEG and MEG exhibit oscillations of specific frequencies over a non-oscillatory background. The oscillations appear in the power spectrum as a collection of frequency bands that are evenly spaced on a logarithmic scale, thereby preventing mutual entrainment and cross-talk. Over the last few years, experimental, computational and theoretical studies have made substantial progress on our understanding of the biophysical mechanisms underlying the generation of network oscillations and their interactions, with emphasis on the role of neuronal synchronization. In this paper we ask a very different question. Rather than investigating how brain rhythms emerge, or whether they are necessary for neural function, we focus on what they tell us about functional brain connectivity. We hypothesized that if we were able to construct abstract networks, or "virtual brains", whose dynamics were similar to EEG/MEG recordings, those networks would share structural features among themselves, and also with real brains. Applying mathematical techniques for inverse problems, we have reverse-engineered network architectures that generate characteristic dynamics of actual brains, including spindles and sharp waves, which appear in the power spectrum as frequency bands superimposed on a non-oscillatory background dominated by low frequencies. We show that all reconstructed networks display similar topological features (e.g. structural motifs and dynamics. We have also reverse-engineered putative diseased brains (epileptic and schizophrenic, in which the oscillatory activity is altered in different ways, as reported in clinical studies. These reconstructed networks show consistent alterations of functional connectivity and dynamics. In particular, we show that the complexity of the network, quantified as proposed by Tononi, Sporns and Edelman, is a good indicator of brain fitness, since virtual brains modeling diseased states

  11. Road network safety evaluation using Bayesian hierarchical joint model.

    Science.gov (United States)

    Wang, Jie; Huang, Helai

    2016-05-01

    Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well.

  12. Road Network Selection Based on Road Hierarchical Structure Control

    Directory of Open Access Journals (Sweden)

    HE Haiwei

    2015-04-01

    Full Text Available A new road network selection method based on hierarchical structure is studied. Firstly, road network is built as strokes which are then classified into hierarchical collections according to the criteria of betweenness centrality value (BC value. Secondly, the hierarchical structure of the strokes is enhanced using structural characteristic identification technique. Thirdly, the importance calculation model was established according to the relationships among the hierarchical structure of the strokes. Finally, the importance values of strokes are got supported with the model's hierarchical calculation, and with which the road network is selected. Tests are done to verify the advantage of this method by comparing it with other common stroke-oriented methods using three kinds of typical road network data. Comparision of the results show that this method had few need to semantic data, and could eliminate the negative influence of edge strokes caused by the criteria of BC value well. So, it is better to maintain the global hierarchical structure of road network, and suitable to meet with the selection of various kinds of road network at the same time.

  13. Neural Mechanisms of Hierarchical Planning in a Virtual Subway Network.

    Science.gov (United States)

    Balaguer, Jan; Spiers, Hugo; Hassabis, Demis; Summerfield, Christopher

    2016-05-18

    Planning allows actions to be structured in pursuit of a future goal. However, in natural environments, planning over multiple possible future states incurs prohibitive computational costs. To represent plans efficiently, states can be clustered hierarchically into "contexts". For example, representing a journey through a subway network as a succession of individual states (stations) is more costly than encoding a sequence of contexts (lines) and context switches (line changes). Here, using functional brain imaging, we asked humans to perform a planning task in a virtual subway network. Behavioral analyses revealed that humans executed a hierarchically organized plan. Brain activity in the dorsomedial prefrontal cortex and premotor cortex scaled with the cost of hierarchical plan representation and unique neural signals in these regions signaled contexts and context switches. These results suggest that humans represent hierarchical plans using a network of caudal prefrontal structures. VIDEO ABSTRACT.

  14. Coevolution of Information Processing and Topology in Hierarchical Adaptive Random Boolean Networks

    CERN Document Server

    Gorski, Piotr J; Holyst, Janusz A

    2015-01-01

    Random Boolean networks (RBNs) are frequently employed for modelling complex systems driven by information processing, e.g. for gene regulatory networks (GRNs). Here we propose a hierarchical adaptive RBN (HARBN) as a system consisting of distinct adaptive RBNs - subnetworks - connected by a set of permanent interlinks. Information measures and internal subnetworks topology of HARBN coevolve and reach steady-states that are specific for a given network structure. We investigate mean node information, mean edge information as well as a mean node degree as functions of model parameters and demonstrate HARBN's ability to describe complex hierarchical systems.

  15. Field Experiment on a Robust Hierarchical Metropolitan Quantum Cryptography Network

    CERN Document Server

    Xu, Fangxing; Wang, Shuang; Yin, Zhenqiang; Zhang, Yang; Liu, Yun; Zhou, Zheng; Zhao, Yibo; Li, Hongwei; Liu, Dong; Han, Zhengfu; Guo, Guangcan

    2009-01-01

    A hierarchical metropolitan quantum cryptography network upon the inner-city commercial telecom fiber cables is reported in this paper. The seven-user network contains a four-node backbone net with one node acting as the subnet gateway, a two-user subnet and a single-fiber access link, which is realized by the Faraday-Michelson Interferometer set-ups. The techniques of the quantum router, optical switch and trusted relay are assembled here to guarantee the feasibility and expandability of the quantum cryptography network. Five nodes of the network are located in the government departments and the secure keys generated by the quantum key distribution network are utilized to encrypt the instant video, sound, text messages and confidential files transmitting between these bureaus. The whole implementation including the hierarchical quantum cryptographic communication network links and corresponding application software shows a big step toward the practical user-oriented network with high security level.

  16. Complex Evaluation of Hierarchically-Network Systems

    CERN Document Server

    Polishchuk, Dmytro; Yadzhak, Mykhailo

    2016-01-01

    Methods of complex evaluation based on local, forecasting, aggregated, and interactive evaluation of the state, function quality, and interaction of complex system's objects on the all hierarchical levels is proposed. Examples of analysis of the structural elements of railway transport system are used for illustration of efficiency of proposed approach.

  17. Modelling hierarchical and modular complex networks: division and independence

    Science.gov (United States)

    Kim, D.-H.; Rodgers, G. J.; Kahng, B.; Kim, D.

    2005-06-01

    We introduce a growing network model which generates both modular and hierarchical structure in a self-organized way. To this end, we modify the Barabási-Albert model into the one evolving under the principles of division and independence as well as growth and preferential attachment (PA). A newly added vertex chooses one of the modules composed of existing vertices, and attaches edges to vertices belonging to that module following the PA rule. When the module size reaches a proper size, the module is divided into two, and a new module is created. The karate club network studied by Zachary is a simple version of the current model. We find that the model can reproduce both modular and hierarchical properties, characterized by the hierarchical clustering function of a vertex with degree k, C(k), being in good agreement with empirical measurements for real-world networks.

  18. Hierarchical Overlapping Clustering of Network Data Using Cut Metrics

    CERN Document Server

    Gama, Fernando; Ribeiro, Alejandro

    2016-01-01

    A novel method to obtain hierarchical and overlapping clusters from network data -i.e., a set of nodes endowed with pairwise dissimilarities- is presented. The introduced method is hierarchical in the sense that it outputs a nested collection of groupings of the node set depending on the resolution or degree of similarity desired, and it is overlapping since it allows nodes to belong to more than one group. Our construction is rooted on the facts that a hierarchical (non-overlapping) clustering of a network can be equivalently represented by a finite ultrametric space and that a convex combination of ultrametrics results in a cut metric. By applying a hierarchical (non-overlapping) clustering method to multiple dithered versions of a given network and then convexly combining the resulting ultrametrics, we obtain a cut metric associated to the network of interest. We then show how to extract a hierarchical overlapping clustering structure from the aforementioned cut metric. Furthermore, the so-called overlappi...

  19. Detect overlapping and hierarchical community structure in networks

    CERN Document Server

    Shen, Huawei; Cai, Kai; Hu, Mao-Bin

    2008-01-01

    Clustering and community structure is crucial for many network systems and the related dynamic processes. It has been shown that communities are usually overlapping and hierarchical. However, previous methods investigate these two properties of community structure separately. This paper propose an algorithm (EAGLE) to detect both the overlapping and hierarchical properties of complex community structure together. This algorithm deals with the set of maximal cliques and adopts an agglomerative framework. The quality function of modularity is extended to evaluate the goodness of a cover. The examples of application to real world networks give excellent results.

  20. Hierarchical Routing over Dynamic Wireless Networks

    CERN Document Server

    Tschopp, Dominique; Grossglauser, Matthias

    2009-01-01

    Wireless network topologies change over time and maintaining routes requires frequent updates. Updates are costly in terms of consuming throughput available for data transmission, which is precious in wireless networks. In this paper, we ask whether there exist low-overhead schemes that produce low-stretch routes. This is studied by using the underlying geometric properties of the connectivity graph in wireless networks.

  1. Tiresias: Online Anomaly Detection for Hierarchical Operational Network Data

    CERN Document Server

    Hong, Chi-Yao; Duffield, Nick; Wang, Jia

    2012-01-01

    Operational network data, management data such as customer care call logs and equipment system logs, is a very important source of information for network operators to detect problems in their networks. Unfortunately, there is lack of efficient tools to automatically track and detect anomalous events on operational data, causing ISP operators to rely on manual inspection of this data. While anomaly detection has been widely studied in the context of network data, operational data presents several new challenges, including the volatility and sparseness of data, and the need to perform fast detection (complicating application of schemes that require offline processing or large/stable data sets to converge). To address these challenges, we propose Tiresias, an automated approach to locating anomalous events on hierarchical operational data. Tiresias leverages the hierarchical structure of operational data to identify high-impact aggregates (e.g., locations in the network, failure modes) likely to be associated w...

  2. Category theoretic analysis of hierarchical protein materials and social networks

    CERN Document Server

    Spivak, David I; Buehler, Markus J

    2011-01-01

    Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we review an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other ologs. We consider a simple example of an alpha-helical and an amyloid-like protein filament subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog f...

  3. Hierarchical document categorization using associative networks

    NARCIS (Netherlands)

    Bloom, Niels; Theune, Mariet; de Jong, Franciska M.G.; Klement, E.P.; Borutzky, W.; Fahringer, T.; Hamza, M.H.; Uskov, V.

    Associative networks are a connectionist language model with the ability to handle dynamic data. We used two associative networks to categorize random sets of related Wikipedia articles with only their raw text as input. We then compared the resulting categorization to a gold standard: the manual

  4. Changes of hierarchical network in local and world stock market

    Science.gov (United States)

    Patwary, Enayet Ullah; Lee, Jong Youl; Nobi, Ashadun; Kim, Doo Hwan; Lee, Jae Woo

    2017-10-01

    We consider the cross-correlation coefficients of the daily returns in the local and global stock markets. We generate the minimal spanning tree (MST) using the correlation matrix. We observe that the MSTs change their structure from chain-like networks to star-like networks during periods of market uncertainty. We quantify the measure of the hierarchical network utilizing the value of the hierarchy measured by the hierarchical path. The hierarchy and betweenness centrality characterize the state of the market regarding the impact of crises. During crises, the non-financial company is established as the central node of the MST. However, before the crisis and during stable periods, the financial company is occupying the central node of the MST in the Korean and the U.S. stock markets. The changes in the network structure and the central node are good indicators of an upcoming crisis.

  5. Information Sharing During Crisis Management in Hierarchical vs. Network Teams

    NARCIS (Netherlands)

    Schraagen, J.M.C.; Veld, M.H.I.T.; Koning, L. de

    2010-01-01

    This study examines the differences between hierarchical and network teams in emergency management. A controlled experimental environment was created in which we could study teams that differed in decision rights, availability of information, information sharing, and task division. Thirty-two teams

  6. Self-organized Criticality in Hierarchical Brain Network

    Institute of Scientific and Technical Information of China (English)

    YANG Qiu-Ying; ZHANG Ying-Yue; CHEN Tian-Lun

    2008-01-01

    It is shown that the cortical brain network of the macaque displays a hierarchically clustered organization and the neuron network shows small-world properties. Now the two factors will be considered in our model and the dynamical behavior of the model will be studied. We study the characters of the model and find that the distribution of avalanche size of the model follows power-law behavior.

  7. An Extended Hierarchical Trusted Model for Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    DU Ruiying; XU Mingdi; ZHANG Huanguo

    2006-01-01

    Cryptography and authentication are traditional approach for providing network security. However, they are not sufficient for solving the problems which malicious nodes compromise whole wireless sensor network leading to invalid data transmission and wasting resource by using vicious behaviors. This paper puts forward an extended hierarchical trusted architecture for wireless sensor network, and establishes trusted congregations by three-tier framework. The method combines statistics, economics with encrypt mechanism for developing two trusted models which evaluate cluster head nodes and common sensor nodes respectively. The models form logical trusted-link from command node to common sensor nodes and guarantees the network can run in secure and reliable circumstance.

  8. Strongly Resilient Non-Interactive Key Predistribution For Hierarchical Networks

    CERN Document Server

    Chen, Hao

    2010-01-01

    Key establishment is the basic necessary tool in the network security, by which pairs in the network can establish shared keys for protecting their pairwise communications. There have been some key agreement or predistribution schemes with the property that the key can be established without the interaction (\\cite{Blom84,BSHKY92,S97}). Recently the hierarchical cryptography and the key management for hierarchical networks have been active topics(see \\cite{BBG05,GHKRRW08,GS02,HNZI02,HL02,Matt04}. ). Key agreement schemes for hierarchical networks were presented in \\cite{Matt04,GHKRRW08} which is based on the Blom key predistribution scheme(Blom KPS, [1]) and pairing. In this paper we introduce generalized Blom-Blundo et al key predistribution schemes. These generalized Blom-Blundo et al key predistribution schemes have the same security functionality as the Blom-Blundo et al KPS. However different and random these KPSs can be used for various parts of the networks for enhancing the resilience. We also presentk...

  9. Hierarchical Compressed Sensing for Cluster Based Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Vishal Krishna Singh

    2016-02-01

    Full Text Available Data transmission consumes significant amount of energy in large scale wireless sensor networks (WSNs. In such an environment, reducing the in-network communication and distributing the load evenly over the network can reduce the overall energy consumption and maximize the network lifetime significantly. In this work, the aforementioned problem of network lifetime and uneven energy consumption in large scale wireless sensor networks is addressed. This work proposes a hierarchical compressed sensing (HCS scheme to reduce the in-network communication during the data gathering process. Co-related sensor readings are collected via a hierarchical clustering scheme. A compressed sensing (CS based data processing scheme is devised to transmit the data from the source to the sink. The proposed HCS is able to identify the optimal position for the application of CS to achieve reduced and similar number of transmissions on all the nodes in the network. An activity map is generated to validate the reduced and uniformly distributed communication load of the WSN. Based on the number of transmissions per data gathering round, the bit-hop metric model is used to analyse the overall energy consumption. Simulation results validate the efficiency of the proposed method over the existing CS based approaches.

  10. Time Synchronization in Hierarchical TESLA Wireless Sensor Networks

    Energy Technology Data Exchange (ETDEWEB)

    Jason L. Wright; Milos Manic

    2009-08-01

    Time synchronization and event time correlation are important in wireless sensor networks. In particular, time is used to create a sequence events or time line to answer questions of cause and effect. Time is also used as a basis for determining the freshness of received packets and the validity of cryptographic certificates. This paper presents secure method of time synchronization and event time correlation for TESLA-based hierarchical wireless sensor networks. The method demonstrates that events in a TESLA network can be accurately timestamped by adding only a few pieces of data to the existing protocol.

  11. SOFM Neural Network Based Hierarchical Topology Control for Wireless Sensor Networks

    OpenAIRE

    2014-01-01

    Well-designed network topology provides vital support for routing, data fusion, and target tracking in wireless sensor networks (WSNs). Self-organization feature map (SOFM) neural network is a major branch of artificial neural networks, which has self-organizing and self-learning features. In this paper, we propose a cluster-based topology control algorithm for WSNs, named SOFMHTC, which uses SOFM neural network to form a hierarchical network structure, completes cluster head selection by the...

  12. Extending stability through hierarchical clusters in Echo State Networks

    Directory of Open Access Journals (Sweden)

    Sarah Jarvis

    2010-07-01

    Full Text Available Echo State Networks (ESN are reservoir networks that satisfy well-established criteria for stability when constructed as feedforward networks. Recent evidence suggests that stability criteria are altered in the presence of reservoir substructures, such as clusters. Understanding how the reservoir architecture affects stability is thus important for the appropriate design of any ESN. To quantitatively determine the influence of the most relevant network parameters, we analysed the impact of reservoir substructures on stability in hierarchically clustered ESNs (HESN, as they allow a smooth transition from highly structured to increasingly homogeneous reservoirs. Previous studies used the largest eigenvalue of the reservoir connectivity matrix (spectral radius as a predictor for stable network dynamics. Here, we evaluate the impact of clusters, hierarchy and intercluster connectivity on the predictive power of the spectral radius for stability. Both hierarchy and low relative cluster sizes extend the range of spectral radius values, leading to stable networks, while increasing intercluster connectivity decreased maximal spectral radius.

  13. Effective Hierarchical Routing Algorithm for Large-scale Wireless Mobile Networks

    Directory of Open Access Journals (Sweden)

    Guofeng Yan

    2014-02-01

    Full Text Available The growing interest in wireless mobile network techniques has resulted in many routing protocol proposals. The unpredictable motion and the unreliable behavior of mobile nodes is one of the key issues in wireless mobile network. Virtual mobile node (VMN consists of robust virtual nodes that are both predictable and reliable. Based on VMN, in this paper, we present a hierarchical routing algorithm, i.e., EHRA-WAVE, for large-scale wireless mobile networks. By using mobile WAVE technology, a routing path can be found rapidly between VMNs without accurate topology information. We introduce the routing algorithm and the implementation issues of the proposed EHRA-WAVE routing algorithm. Finally, we evaluate the performance of EHRA-WAVE through experiments, and compare the performance on VMN failure and message delivery ratio using hierarchical and non-hierarchical routing methods. However, due to the large amounts WAVE flooding, EHRAWAVE results in too large load which would impede the application of the EHRA-WAVE algorithm. Therefore, the further routing protocol focuses on minimizing the number of WAVE using hierarchical structures in large-scale wireless mobile networks

  14. Hierarchical Resource Allocation in Femtocell Networks using Graph Algorithms

    CERN Document Server

    Sadr, Sanam

    2012-01-01

    This paper presents a hierarchical approach to resource allocation in open-access femtocell networks. The major challenge in femtocell networks is interference management which in our system, based on the Long Term Evolution (LTE) standard, translates to which user should be allocated which physical resource block (or fraction thereof) from which femtocell access point (FAP). The globally optimal solution requires integer programming and is mathematically intractable. We propose a hierarchical three-stage solution: first, the load of each FAP is estimated considering the number of users connected to the FAP, their average channel gain and required data rates. Second, based on each FAP's load, the physical resource blocks (PRBs) are allocated to FAPs in a manner that minimizes the interference by coloring the modified interference graph. Finally, the resource allocation is performed at each FAP considering users' instantaneous channel gain. The two major advantages of this suboptimal approach are the significa...

  15. Dynamic and Quantitative Method of Analyzing Service Consistency Evolution Based on Extended Hierarchical Finite State Automata

    Directory of Open Access Journals (Sweden)

    Linjun Fan

    2014-01-01

    Full Text Available This paper is concerned with the dynamic evolution analysis and quantitative measurement of primary factors that cause service inconsistency in service-oriented distributed simulation applications (SODSA. Traditional methods are mostly qualitative and empirical, and they do not consider the dynamic disturbances among factors in service’s evolution behaviors such as producing, publishing, calling, and maintenance. Moreover, SODSA are rapidly evolving in terms of large-scale, reusable, compositional, pervasive, and flexible features, which presents difficulties in the usage of traditional analysis methods. To resolve these problems, a novel dynamic evolution model extended hierarchical service-finite state automata (EHS-FSA is constructed based on finite state automata (FSA, which formally depict overall changing processes of service consistency states. And also the service consistency evolution algorithms (SCEAs based on EHS-FSA are developed to quantitatively assess these impact factors. Experimental results show that the bad reusability (17.93% on average is the biggest influential factor, the noncomposition of atomic services (13.12% is the second biggest one, and the service version’s confusion (1.2% is the smallest one. Compared with previous qualitative analysis, SCEAs present good effectiveness and feasibility. This research can guide the engineers of service consistency technologies toward obtaining a higher level of consistency in SODSA.

  16. Replanning Using Hierarchical Task Network and Operator-Based Planning

    Science.gov (United States)

    Wang, X.; Chien, S.

    1997-01-01

    In order to scale-up to real-world problems, planning systems must be able to replan in order to deal with changes in problem context. In this paper we describe hierarchical task network and operatorbased re-planning techniques which allow adaptation of a previous plan to account for problems associated with executing plans in real-world domains with uncertainty, concurrency, changing objectives.

  17. Multi-mode clustering model for hierarchical wireless sensor networks

    Science.gov (United States)

    Hu, Xiangdong; Li, Yongfu; Xu, Huifen

    2017-03-01

    The topology management, i.e., clusters maintenance, of wireless sensor networks (WSNs) is still a challenge due to its numerous nodes, diverse application scenarios and limited resources as well as complex dynamics. To address this issue, a multi-mode clustering model (M2 CM) is proposed to maintain the clusters for hierarchical WSNs in this study. In particular, unlike the traditional time-trigger model based on the whole-network and periodic style, the M2 CM is proposed based on the local and event-trigger operations. In addition, an adaptive local maintenance algorithm is designed for the broken clusters in the WSNs using the spatial-temporal demand changes accordingly. Numerical experiments are performed using the NS2 network simulation platform. Results validate the effectiveness of the proposed model with respect to the network maintenance costs, node energy consumption and transmitted data as well as the network lifetime.

  18. Hierarchical network architectures of carbon fiber paper supported cobalt oxide nanonet for high-capacity pseudocapacitors.

    Science.gov (United States)

    Yang, Lei; Cheng, Shuang; Ding, Yong; Zhu, Xingbao; Wang, Zhong Lin; Liu, Meilin

    2012-01-11

    We present a high-capacity pseudocapacitor based on a hierarchical network architecture consisting of Co(3)O(4) nanowire network (nanonet) coated on a carbon fiber paper. With this tailored architecture, the electrode shows ideal capacitive behavior (rectangular shape of cyclic voltammograms) and large specific capacitance (1124 F/g) at high charge/discharge rate (25.34 A/g), still retaining ~94% of the capacitance at a much lower rate of 0.25 A/g. The much-improved capacity, rate capability, and cycling stability may be attributed to the unique hierarchical network structures, which improves electron/ion transport, enhances the kinetics of redox reactions, and facilitates facile stress relaxation during cycling.

  19. Routing and wavelength assignment in hierarchical WDM networks

    Institute of Scientific and Technical Information of China (English)

    Yiyi LU; Ruxiang JIN; Chen HE

    2008-01-01

    A new routing and wavelength assignment method applied in hierarchical wavelength division multiplexing(WDM)networks is proposed.The algorithm is called offiine band priority algorithm(offiine BPA).The offline BPA targets to maximize the number of waveband paths under the condition of minimum number of wavelengths,and solve the routing and wavelength assignment(RWA)problem with waveband grooming to reduce cost.Based on the circle construction algorithm,waveband priority function is introduced to calculate the RWA problem.Simulation results demonstrate that the proposed algorithm achieves significant cost reduction in WDM network construction.

  20. Hierarchical control based on Hopfield network for nonseparable optimization problems

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The nonseparable optimization control problem is considered, where the overall objective function is not of an additive form with respect to subsystems. Since there exists the problem that computation is very slow when using iterative algorithms in multiobjective optimization, Hopfield optimization hierarchical network based on IPM is presented to overcome such slow computation difficulty. Asymptotic stability of this Hopfield network is proved and its equilibrium point is the optimal point of the original problem. The simulation shows that the net is effective to deal with the optimization control problem for large-scale nonseparable steady state systems.

  1. Hierarchical organization of brain functional network during visual task

    CERN Document Server

    Zhuo, Zhao; Fu, Zhong-Qian; Zhang, Jie

    2011-01-01

    In this paper, the brain functional networks derived from high-resolution synchronous EEG time series during visual task are generated by calculating the phase synchronization among the time series. The hierarchical modular organizations of these networks are systematically investigated by the fast Girvan-Newman algorithm. At the same time, the spatially adjacent electrodes (corresponding to EEG channels) are clustered into functional groups based on anatomical parcellation of brain cortex, and this clustering information are compared to that of the functional network. The results show that the modular architectures of brain functional network are in coincidence with that from the anatomical structures over different levels of hierarchy, which suggests that population of neurons performing the same function excite and inhibit in identical rhythms. The structure-function relationship further reveals that the correlations among EEG time series in the same functional group are much stronger than those in differe...

  2. An Isolation Intrusion Detection System for Hierarchical Wireless Sensor Networks

    OpenAIRE

    Rung-Ching Chen; Chia-Fen Hsieh; Yung-Fa Huang

    2010-01-01

    A wireless sensor network (WSN) is a wireless network consisting of spatially distributed autonomous devices using sensors to cooperatively monitor environmental conditions, such as battlefield data and personal health information, and some environment limited resources. To avoid malicious damage is important while information is transmitted in wireless network. Thus, Wireless Intrusion Detection Systems are crucial to safe operation in wireless sensor networks. Wireless networks are subject ...

  3. Complex networks with scale-free nature and hierarchical modularity

    Science.gov (United States)

    Shekatkar, Snehal M.; Ambika, G.

    2015-09-01

    Generative mechanisms which lead to empirically observed structure of networked systems from diverse fields like biology, technology and social sciences form a very important part of study of complex networks. The structure of many networked systems like biological cell, human society and World Wide Web markedly deviate from that of completely random networks indicating the presence of underlying processes. Often the main process involved in their evolution is the addition of links between existing nodes having a common neighbor. In this context we introduce an important property of the nodes, which we call mediating capacity, that is generic to many networks. This capacity decreases rapidly with increase in degree, making hubs weak mediators of the process. We show that this property of nodes provides an explanation for the simultaneous occurrence of the observed scale-free structure and hierarchical modularity in many networked systems. This also explains the high clustering and small-path length seen in real networks as well as non-zero degree-correlations. Our study also provides insight into the local process which ultimately leads to emergence of preferential attachment and hence is also important in understanding robustness and control of real networks as well as processes happening on real networks.

  4. Doubly Optimal Secure Multicasting: Hierarchical Hybrid Communication Network : Disaster Relief

    CERN Document Server

    Garimella, Rama Murthy; Singhal, Deepti

    2011-01-01

    Recently, the world has witnessed the increasing occurrence of disasters, some of natural origin and others caused by man. The intensity of the phenomenon that cause such disasters, the frequency in which they occur, the number of people affected and the material damage caused by them have been growing substantially. Disasters are defined as natural, technological, and human-initiated events that disrupt the normal functioning of the economy and society on a large scale. Areas where disasters have occurred bring many dangers to rescue teams and the communication network infrastructure is usually destroyed. To manage these hazards, different wireless technologies can be launched in the area of disaster. This paper discusses the innovative wireless technologies for Disaster Management. Specifically, issues related to the design of Hierarchical Hybrid Communication Network (arising in the communication network for disaster relief) are discussed.

  5. Hierarchical modular granular neural networks with fuzzy aggregation

    CERN Document Server

    Sanchez, Daniela

    2016-01-01

    In this book, a new method for hybrid intelligent systems is proposed. The proposed method is based on a granular computing approach applied in two levels. The techniques used and combined in the proposed method are modular neural networks (MNNs) with a Granular Computing (GrC) approach, thus resulting in a new concept of MNNs; modular granular neural networks (MGNNs). In addition fuzzy logic (FL) and hierarchical genetic algorithms (HGAs) are techniques used in this research work to improve results. These techniques are chosen because in other works have demonstrated to be a good option, and in the case of MNNs and HGAs, these techniques allow to improve the results obtained than with their conventional versions; respectively artificial neural networks and genetic algorithms.

  6. Frontoparietal Connectivity and Hierarchical Structure of the Brain’s Functional Network during Sleep

    Directory of Open Access Journals (Sweden)

    Victor I Spoormaker

    2012-05-01

    Full Text Available Frontal and parietal regions are associated with some of the most complex cognitive functions, and several frontoparietal resting-state networks can be observed in wakefulness. We used functional magnetic resonance imaging (fMRI data acquired in polysomnographically validated wakefulness, light sleep and slow-wave sleep to examine the hierarchical structure of a low-frequency functional brain network, and to examine whether frontoparietal connectivity would disintegrate in sleep. Whole-brain analyses with hierarchical cluster analysis on predefined atlases were performed, as well as regression of inferior parietal lobules seeds against all voxels in the brain, and an evaluation of the integrity of voxel time-courses in subcortical regions-of-interest. We observed that frontoparietal functional connectivity disintegrated in sleep stage 1 and was absent in deeper sleep stages. Slow-wave sleep was characterized by strong hierarchical clustering of local submodules. Frontoparietal connectivity between inferior parietal lobules and superior medial and right frontal gyrus was lower in sleep stages than in wakefulness. Moreover, thalamus voxels showed maintained integrity in sleep stage 1, making intrathalamic desynchronization an unlikely source of reduced thalamocortical connectivity in this sleep stage. Our data suggest a transition from a globally integrated functional brain network in wakefulness to a disintegrated network consisting of local submodules in slow-wave sleep, in which frontoparietal inter-modular nodes may play a crucial role, possibly in combination with the thalamus.

  7. Genomic analysis of the hierarchical structure of regulatory networks

    Science.gov (United States)

    Yu, Haiyuan; Gerstein, Mark

    2006-01-01

    A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

  8. [A medical image semantic modeling based on hierarchical Bayesian networks].

    Science.gov (United States)

    Lin, Chunyi; Ma, Lihong; Yin, Junxun; Chen, Jianyu

    2009-04-01

    A semantic modeling approach for medical image semantic retrieval based on hierarchical Bayesian networks was proposed, in allusion to characters of medical images. It used GMM (Gaussian mixture models) to map low-level image features into object semantics with probabilities, then it captured high-level semantics through fusing these object semantics using a Bayesian network, so that it built a multi-layer medical image semantic model, aiming to enable automatic image annotation and semantic retrieval by using various keywords at different semantic levels. As for the validity of this method, we have built a multi-level semantic model from a small set of astrocytoma MRI (magnetic resonance imaging) samples, in order to extract semantics of astrocytoma in malignant degree. Experiment results show that this is a superior approach.

  9. Spatially Resolved Monitoring of Drying of Hierarchical Porous Organic Networks.

    Science.gov (United States)

    Velasco, Manuel Isaac; Silletta, Emilia V; Gomez, Cesar G; Strumia, Miriam C; Stapf, Siegfried; Monti, Gustavo Alberto; Mattea, Carlos; Acosta, Rodolfo H

    2016-03-01

    Evaporation kinetics of water confined in hierarchal polymeric porous media is studied by low field nuclear magnetic resonance (NMR). Systems synthesized with various degrees of cross-linker density render networks with similar pore sizes but different response when soaked with water. Polymeric networks with low percentage of cross-linker can undergo swelling, which affects the porosity as well as the drying kinetics. The drying process is monitored macroscopically by single-sided NMR, with spatial resolution of 100 μm, while microscopic information is obtained by measurements of spin-spin relaxation times (T2). Transition from a funicular to a pendular regime, where hydraulic connectivity is lost and the capillary flow cannot compensate for the surface evaporation, can be observed from inspection of the water content in different sample layers. Relaxation measurements indicate that even when the larger pore structures are depleted of water, capillary flow occurs through smaller voids.

  10. Architecture of the parallel hierarchical network for fast image recognition

    Science.gov (United States)

    Timchenko, Leonid; Wójcik, Waldemar; Kokriatskaia, Natalia; Kutaev, Yuriy; Ivasyuk, Igor; Kotyra, Andrzej; Smailova, Saule

    2016-09-01

    Multistage integration of visual information in the brain allows humans to respond quickly to most significant stimuli while maintaining their ability to recognize small details in the image. Implementation of this principle in technical systems can lead to more efficient processing procedures. The multistage approach to image processing includes main types of cortical multistage convergence. The input images are mapped into a flexible hierarchy that reflects complexity of image data. Procedures of the temporal image decomposition and hierarchy formation are described in mathematical expressions. The multistage system highlights spatial regularities, which are passed through a number of transformational levels to generate a coded representation of the image that encapsulates a structure on different hierarchical levels in the image. At each processing stage a single output result is computed to allow a quick response of the system. The result is presented as an activity pattern, which can be compared with previously computed patterns on the basis of the closest match. With regard to the forecasting method, its idea lies in the following. In the results synchronization block, network-processed data arrive to the database where a sample of most correlated data is drawn using service parameters of the parallel-hierarchical network.

  11. GSMNet: A Hierarchical Graph Model for Moving Objects in Networks

    Directory of Open Access Journals (Sweden)

    Hengcai Zhang

    2017-03-01

    Full Text Available Existing data models for moving objects in networks are often limited by flexibly controlling the granularity of representing networks and the cost of location updates and do not encompass semantic information, such as traffic states, traffic restrictions and social relationships. In this paper, we aim to fill the gap of traditional network-constrained models and propose a hierarchical graph model called the Geo-Social-Moving model for moving objects in Networks (GSMNet that adopts four graph structures, RouteGraph, SegmentGraph, ObjectGraph and MoveGraph, to represent the underlying networks, trajectories and semantic information in an integrated manner. The bulk of user-defined data types and corresponding operators is proposed to handle moving objects and answer a new class of queries supporting three kinds of conditions: spatial, temporal and semantic information. Then, we develop a prototype system with the native graph database system Neo4Jto implement the proposed GSMNet model. In the experiment, we conduct the performance evaluation using simulated trajectories generated from the BerlinMOD (Berlin Moving Objects Database benchmark and compare with the mature MOD system Secondo. The results of 17 benchmark queries demonstrate that our proposed GSMNet model has strong potential to reduce time-consuming table join operations an d shows remarkable advantages with regard to representing semantic information and controlling the cost of location updates.

  12. Impact of informal networks on opinion dynamics in hierarchically formal organization

    Science.gov (United States)

    Song, Xiao; Shi, Wen; Ma, Yaofei; Yang, Chen

    2015-10-01

    Traditional opinion dynamics model focused mainly on the conditions under which a group of agents would reach a consensus. Conclusion has been gained that continuous opinion dynamics are subject to the constraint that convergent opinion adjustment only proceeds when opinion difference is below a given tolerance. This conclusion is useful but neglected the fact that an organization often consists of overlapped networks including formally hierarchical network and small-world/scale-free informal networks. To study the impact of different types of informal networks on converging speed or the number of opinion clusters, four typical types of informal networks (small-world, scale-free, tree and fully connected) are modeled and proposed as complements to formal communications. Experiments to compare formal network and hybrid networks are then carried out. It is observed that opinion dynamics with supplemented communications of informal networks can benefit convergence speed and reduce opinion clusters. More importantly, it is revealed that three key factors of informal networks affect their impact on formal network. These factors of informal network in descending orders are: agents' tolerances, scale and number of links.

  13. A hierarchical network modeling method for railway tunnels safety assessment

    Science.gov (United States)

    Zhou, Jin; Xu, Weixiang; Guo, Xin; Liu, Xumin

    2017-02-01

    Using network theory to model risk-related knowledge on accidents is regarded as potential very helpful in risk management. A large amount of defects detection data for railway tunnels is collected in autumn every year in China. It is extremely important to discover the regularities knowledge in database. In this paper, based on network theories and by using data mining techniques, a new method is proposed for mining risk-related regularities to support risk management in railway tunnel projects. A hierarchical network (HN) model which takes into account the tunnel structures, tunnel defects, potential failures and accidents is established. An improved Apriori algorithm is designed to rapidly and effectively mine correlations between tunnel structures and tunnel defects. Then an algorithm is presented in order to mine the risk-related regularities table (RRT) from the frequent patterns. At last, a safety assessment method is proposed by consideration of actual defects and possible risks of defects gained from the RRT. This method cannot only generate the quantitative risk results but also reveal the key defects and critical risks of defects. This paper is further development on accident causation network modeling methods which can provide guidance for specific maintenance measure.

  14. A method for identifying hierarchical sub-networks / modules and weighting network links based on their similarity in sub-network / module affiliation

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2016-06-01

    Full Text Available Some networks, including biological networks, consist of hierarchical sub-networks / modules. Based on my previous study, in present study a method for both identifying hierarchical sub-networks / modules and weighting network links is proposed. It is based on the cluster analysis in which between-node similarity in sets of adjacency nodes is used. Two matrices, linkWeightMat and linkClusterIDs, are achieved by using the algorithm. Two links with both the same weight in linkWeightMat and the same cluster ID in linkClusterIDs belong to the same sub-network / module. Two links with the same weight in linkWeightMat but different cluster IDs in linkClusterIDs belong to two sub-networks / modules at the same hirarchical level. However, a link with an unique cluster ID in linkClusterIDs does not belong to any sub-networks / modules. A sub-network / module of the greater weight is the more connected sub-network / modules. Matlab codes of the algorithm are presented.

  15. Hierarchical Interference Mitigation for Massive MIMO Cellular Networks

    Science.gov (United States)

    Liu, An; Lau, Vincent

    2014-09-01

    We propose a hierarchical interference mitigation scheme for massive MIMO cellular networks. The MIMO precoder at each base station (BS) is partitioned into an inner precoder and an outer precoder. The inner precoder controls the intra-cell interference and is adaptive to local channel state information (CSI) at each BS (CSIT). The outer precoder controls the inter-cell interference and is adaptive to channel statistics. Such hierarchical precoding structure reduces the number of pilot symbols required for CSI estimation in massive MIMO downlink and is robust to the backhaul latency. We study joint optimization of the outer precoders, the user selection, and the power allocation to maximize a general concave utility which has no closed-form expression. We first apply random matrix theory to obtain an approximated problem with closed-form objective. We show that the solution of the approximated problem is asymptotically optimal with respect to the original problem as the number of antennas per BS grows large. Then using the hidden convexity of the problem, we propose an iterative algorithm to find the optimal solution for the approximated problem. We also obtain a low complexity algorithm with provable convergence. Simulations show that the proposed design has significant gain over various state-of-the-art baselines.

  16. Distributed Plume Source Localization Using Hierarchical Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    KUANG Xing-hong; LIU Yu-qing; WU Yan-xiang; SHAO Hui-he

    2009-01-01

    A hierarchical wireless sensor networks (WSN) was proposed to estimate the plume source location. Such WSN can be of tremendous help to emergency personnel trying to protect people from terrorist attacks or responding to an accident. The entire surveillant field is divided into several small sub-regions. In each sub-region, the localization algorithm based on the improved particle filter (IPF) was performed to estimate the location. Some improved methods such as weighted centroid, residual resampling were introduced to the IPF algorithm to increase the localization performance. This distributed estimation method elirninates many drawbacks inherent with the traditional centralized optimization method. Simulation results show that localization algorithm is efficient far estimating the plume source location.

  17. Hierarchical self-organization of cytoskeletal active networks

    CERN Document Server

    Gordon, Daniel; Keasar, Chen; Farago, Oded

    2012-01-01

    The structural reorganization of the actin cytoskeleton is facilitated through the action of motor proteins that crosslink the actin filaments and transport them relative to each other. Here, we present a combined experimental-computational study that probes the dynamic evolution of mixtures of actin filaments and clusters of myosin motors. While on small spatial and temporal scales the system behaves in a very noisy manner, on larger scales it evolves into several well distinct patterns such as bundles, asters, and networks. These patterns are characterized by junctions with high connectivity, whose formation is possible due to the organization of the motors in "oligoclusters" (intermediate-size aggregates). The simulations reveal that the self-organization process proceeds through a series of hierarchical steps, starting from local microscopic moves and ranging up to the macroscopic large scales where the steady-state structures are formed. Our results shed light into the mechanisms involved in processes li...

  18. Learning Probabilistic Hierarchical Task Networks to Capture User Preferences

    CERN Document Server

    Li, Nan; Kambhampati, Subbarao; Yoon, Sungwook

    2010-01-01

    We propose automatically learning probabilistic Hierarchical Task Networks (pHTNs) in order to capture a user's preferences on plans, by observing only the user's behavior. HTNs are a common choice of representation for a variety of purposes in planning, including work on learning in planning. Our contributions are (a) learning structure and (b) representing preferences. In contrast, prior work employing HTNs considers learning method preconditions (instead of structure) and representing domain physics or search control knowledge (rather than preferences). Initially we will assume that the observed distribution of plans is an accurate representation of user preference, and then generalize to the situation where feasibility constraints frequently prevent the execution of preferred plans. In order to learn a distribution on plans we adapt an Expectation-Maximization (EM) technique from the discipline of (probabilistic) grammar induction, taking the perspective of task reductions as productions in a context-free...

  19. Integration of relational and hierarchical network information for protein function prediction

    Directory of Open Access Journals (Sweden)

    Jiang Xiaoyu

    2008-08-01

    Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

  20. Consistent deniable lying : privacy in mobile social networks

    OpenAIRE

    Belle, Sebastian Kay; Waldvogel, Marcel

    2008-01-01

    Social networking is moving to mobile phones. This not only means continuous access, but also allows to link virtual and physical neighbourhood in novel ways. To make such systems useful, personal data such as lists of friends and interests need to be shared with more and frequently unknown people, posing a risk to your privacy. In this paper, we present our approach to social networking, Consistent Deniable Lying (CDL). Using easy-to-understand mechanisms and tuned to this environment, i...

  1. Novel nanocomposite hydrogels consisting of layered double hydroxide with ultrahigh tensibility and hierarchical porous structure at low inorganic content.

    Science.gov (United States)

    Hu, Ziqiao; Chen, Guangming

    2014-09-10

    A novel type of polymer nanocomposite (NC) hydrogel with extraordinary mechanical properties at low inorganic content is prepared and investigated. The NC hydrogels consist of isethionate-loaded layered double hydroxide/polyacrylamide (LDH-Ise/PAM) - with LDH-Ise being used because of its swelling properties - and no conventional organic crosslinker. The NC hydrogels exhibit an unusual hierarchical porous structure at the micro- and nanometer scales, and their elongation at break can exceed 4000%.

  2. Coevolution of information processing and topology in hierarchical adaptive random Boolean networks

    Science.gov (United States)

    Górski, Piotr J.; Czaplicka, Agnieszka; Hołyst, Janusz A.

    2016-02-01

    Random Boolean Networks (RBNs) are frequently used for modeling complex systems driven by information processing, e.g. for gene regulatory networks (GRNs). Here we propose a hierarchical adaptive random Boolean Network (HARBN) as a system consisting of distinct adaptive RBNs (ARBNs) - subnetworks - connected by a set of permanent interlinks. We investigate mean node information, mean edge information as well as mean node degree. Information measures and internal subnetworks topology of HARBN coevolve and reach steady-states that are specific for a given network structure. The main natural feature of ARBNs, i.e. their adaptability, is preserved in HARBNs and they evolve towards critical configurations which is documented by power law distributions of network attractor lengths. The mean information processed by a single node or a single link increases with the number of interlinks added to the system. The mean length of network attractors and the mean steady-state connectivity possess minima for certain specific values of the quotient between the density of interlinks and the density of all links in networks. It means that the modular network displays extremal values of its observables when subnetworks are connected with a density a few times lower than a mean density of all links.

  3. Registration Cost Performance Analysis of a Hierarchical Mobile Internet Protocol Network

    Institute of Scientific and Technical Information of China (English)

    XU Kai; JI Hong; YUE Guang-xin

    2004-01-01

    On the basis of introducing principles for hierarchical mobile Internet protocol networks, the registration cost performance in this network model is analyzed in detail. Furthermore, the functional relationship is also established in the paper among registration cost, hierarchical level number and the maximum handover time for gateway foreign agent regional registration. At last, the registration cost of the hierarchical mobile Internet protocol network is compared with that of the traditional mobile Internet protocol. Theoretic analysis and computer simulation results show that the hierarchical level number and the maximum handover times can both affect the registration cost importantly, when suitable values of which are chosen, the hierarchical network can significantly improve the registration performance compared with the traditional mobile IP.

  4. Hierarchical Real-time Network Traffic Classification Based on ECOC

    Directory of Open Access Journals (Sweden)

    Yaou Zhao

    2013-09-01

    Full Text Available Classification of network traffic is basic and essential for manynetwork researches and managements. With the rapid development ofpeer-to-peer (P2P application using dynamic port disguisingtechniques and encryption to avoid detection, port-based and simplepayload-based network traffic classification methods were diminished.An alternative method based on statistics and machine learning hadattracted researchers' attention in recent years. However, most ofthe proposed algorithms were off-line and usually used a single classifier.In this paper a new hierarchical real-time model was proposed which comprised of a three tuple (source ip, destination ip and destination portlook up table(TT-LUT part and layered milestone part. TT-LUT was used to quickly classify short flows whichneed not to pass the layered milestone part, and milestones in layered milestone partcould classify the other flows in real-time with the real-time feature selection and statistics.Every milestone was a ECOC(Error-Correcting Output Codes based model which was usedto improve classification performance. Experiments showed that the proposedmodel can improve the efficiency of real-time to 80%, and themulti-class classification accuracy encouragingly to 91.4% on the datasets which had been captured from the backbone router in our campus through a week.

  5. Sensor Networks Hierarchical Optimization Model for Security Monitoring in High-Speed Railway Transport Hub

    Directory of Open Access Journals (Sweden)

    Zhengyu Xie

    2015-01-01

    Full Text Available We consider the sensor networks hierarchical optimization problem in high-speed railway transport hub (HRTH. The sensor networks are optimized from three hierarchies which are key area sensors optimization, passenger line sensors optimization, and whole area sensors optimization. Case study on a specific HRTH in China showed that the hierarchical optimization method is effective to optimize the sensor networks for security monitoring in HRTH.

  6. Spectral characterization of hierarchical network modularity and limits of modularity detection.

    Directory of Open Access Journals (Sweden)

    Somwrita Sarkar

    Full Text Available Many real world networks are reported to have hierarchically modular organization. However, there exists no algorithm-independent metric to characterize hierarchical modularity in a complex system. The main results of the paper are a set of methods to address this problem. First, classical results from random matrix theory are used to derive the spectrum of a typical stochastic block model hierarchical modular network form. Second, it is shown that hierarchical modularity can be fingerprinted using the spectrum of its largest eigenvalues and gaps between clusters of closely spaced eigenvalues that are well separated from the bulk distribution of eigenvalues around the origin. Third, some well-known results on fingerprinting non-hierarchical modularity in networks automatically follow as special cases, threreby unifying these previously fragmented results. Finally, using these spectral results, it is found that the limits of detection of modularity can be empirically established by studying the mean values of the largest eigenvalues and the limits of the bulk distribution of eigenvalues for an ensemble of networks. It is shown that even when modularity and hierarchical modularity are present in a weak form in the network, they are impossible to detect, because some of the leading eigenvalues fall within the bulk distribution. This provides a threshold for the detection of modularity. Eigenvalue distributions of some technological, social, and biological networks are studied, and the implications of detecting hierarchical modularity in real world networks are discussed.

  7. Hierarchical Structure, Disassortativity and Information Measures of the US Flight Network

    Institute of Scientific and Technical Information of China (English)

    WANG Ru; CAI Xu

    2005-01-01

    @@ We investigate the mixing structure of directed and evolutionary US flight network. It is shown that such a network is a hierarchical network, with average assortativity coefficient -0.37. Application of the informationbased method that can give the same result provides a way to explore the structure of complex networks.

  8. Pattern formation in oscillatory complex networks consisting of excitable nodes

    Science.gov (United States)

    Liao, Xuhong; Xia, Qinzhi; Qian, Yu; Zhang, Lisheng; Hu, Gang; Mi, Yuanyuan

    2011-05-01

    Oscillatory dynamics of complex networks has recently attracted great attention. In this paper we study pattern formation in oscillatory complex networks consisting of excitable nodes. We find that there exist a few center nodes and small skeletons for most oscillations. Complicated and seemingly random oscillatory patterns can be viewed as well-organized target waves propagating from center nodes along the shortest paths, and the shortest loops passing through both the center nodes and their driver nodes play the role of oscillation sources. Analyzing simple skeletons we are able to understand and predict various essential properties of the oscillations and effectively modulate the oscillations. These methods and results will give insights into pattern formation in complex networks and provide suggestive ideas for studying and controlling oscillations in neural networks.

  9. Resolution of Singularities Introduced by Hierarchical Structure in Deep Neural Networks.

    Science.gov (United States)

    Nitta, Tohru

    2016-06-30

    We present a theoretical analysis of singular points of artificial deep neural networks, resulting in providing deep neural network models having no critical points introduced by a hierarchical structure. It is considered that such deep neural network models have good nature for gradient-based optimization. First, we show that there exist a large number of critical points introduced by a hierarchical structure in deep neural networks as straight lines, depending on the number of hidden layers and the number of hidden neurons. Second, we derive a sufficient condition for deep neural networks having no critical points introduced by a hierarchical structure, which can be applied to general deep neural networks. It is also shown that the existence of critical points introduced by a hierarchical structure is determined by the rank and the regularity of weight matrices for a specific class of deep neural networks. Finally, two kinds of implementation methods of the sufficient conditions to have no critical points are provided. One is a learning algorithm that can avoid critical points introduced by the hierarchical structure during learning (called avoidant learning algorithm). The other is a neural network that does not have some critical points introduced by the hierarchical structure as an inherent property (called avoidant neural network).

  10. Hierarchical expansion of the kinetic energy operator in curvilinear coordinates for the vibrational self-consistent field method.

    Science.gov (United States)

    Strobusch, D; Scheurer, Ch

    2011-09-28

    A new hierarchical expansion of the kinetic energy operator in curvilinear coordinates is presented and modified vibrational self-consistent field (VSCF) equations are derived including all kinematic effects within the mean field approximation. The new concept for the kinetic energy operator is based on many-body expansions for all G matrix elements and its determinant. As a test application VSCF computations were performed on the H(2)O(2) molecule using an analytic potential (PCPSDE) and different hierarchical approximations for the kinetic energy operator. The results indicate that coordinate-dependent reduced masses account for the largest part of the kinetic energy. Neither kinematic couplings nor derivatives of the G matrix nor its determinant had significant effects on the VSCF energies. Only the zero-point value of the pseudopotential yields an offset to absolute energies which, however, is irrelevant for spectroscopic problems.

  11. A Tool for Fast Development of Modular and Hierarchic Neural Network-based Systems

    Directory of Open Access Journals (Sweden)

    Francisco Reinaldo

    2006-08-01

    Full Text Available This paper presents PyramidNet tool as a fast and easy way to develop Modular and Hierarchic Neural Network-based Systems. This tool facilitates the fast emergence of autonomous behaviors in agents because it uses a hierarchic and modular control methodology of heterogeneous learning modules: the pyramid. Using the graphical resources of PyramidNet the user is able to specify a behavior system even having little understanding of artificial neural networks. Experimental tests have shown that a very significant speedup is attained in the development of modular and hierarchic neural network-based systems by using this tool.

  12. SO2 Emissions in China - Their Network and Hierarchical Structures

    Science.gov (United States)

    Yan, Shaomin; Wu, Guang

    2017-04-01

    SO2 emissions lead to various harmful effects on environment and human health. The SO2 emission in China has significant contribution to the global SO2 emission, so it is necessary to employ various methods to study SO2 emissions in China with great details in order to lay the foundation for policymaking to improve environmental conditions in China. Network analysis is used to analyze the SO2 emissions from power generation, industrial, residential and transportation sectors in China for 2008 and 2010, which are recently available from 1744 ground surface monitoring stations. The results show that the SO2 emissions from power generation sector were highly individualized as small-sized clusters, the SO2 emissions from industrial sector underwent an integration process with a large cluster contained 1674 places covering all industrial areas in China, the SO2 emissions from residential sector was not impacted by time, and the SO2 emissions from transportation sector underwent significant integration. Hierarchical structure is obtained by further combining SO2 emissions from all four sectors and is potentially useful to find out similar patterns of SO2 emissions, which can provide information on understanding the mechanisms of SO2 pollution and on designing different environmental measure to combat SO2 emissions.

  13. Hierarchical Artificial Bee Colony Algorithm for RFID Network Planning Optimization

    Directory of Open Access Journals (Sweden)

    Lianbo Ma

    2014-01-01

    Full Text Available This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization, called HABC, to tackle the radio frequency identification network planning (RNP problem. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operators is applied to enhance the global search ability between species. Experiments are conducted on a set of 10 benchmark optimization problems. The results demonstrate that the proposed HABC obtains remarkable performance on most chosen benchmark functions when compared to several successful swarm intelligence and evolutionary algorithms. Then HABC is used for solving the real-world RNP problem on two instances with different scales. Simulation results show that the proposed algorithm is superior for solving RNP, in terms of optimization accuracy and computation robustness.

  14. Consistent Steering System using SCTP for Bluetooth Scatternet Sensor Network

    Science.gov (United States)

    Dhaya, R.; Sadasivam, V.; Kanthavel, R.

    2012-12-01

    Wireless communication is the best way to convey information from source to destination with flexibility and mobility and Bluetooth is the wireless technology suitable for short distance. On the other hand a wireless sensor network (WSN) consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants. Using Bluetooth piconet wireless technique in sensor nodes creates limitation in network depth and placement. The introduction of Scatternet solves the network restrictions with lack of reliability in data transmission. When the depth of the network increases, it results in more difficulties in routing. No authors so far focused on the reliability factors of Scatternet sensor network's routing. This paper illustrates the proposed system architecture and routing mechanism to increase the reliability. The another objective is to use reliable transport protocol that uses the multi-homing concept and supports multiple streams to prevent head-of-line blocking. The results show that the Scatternet sensor network has lower packet loss even in the congestive environment than the existing system suitable for all surveillance applications.

  15. PATH PRIORITIZATION AND OPERATIONAL CONSISTENCY FOR DYNAMIC TRAFFIC ASSIGNMENT: AN ANALYTIC HIERARCHICAL APPROACH

    Directory of Open Access Journals (Sweden)

    Srinivas Bulusu

    2016-06-01

    Full Text Available An operational consistency model for real-time dynamic traffic assignment (DTA applications seeks to correct the time-dependent path assignment within a rolling horizon scheme. This study extends an existing consistency framework to develop a hierarchy for the time-dependent path set based upon their relative importance to ensuring consistency. Using the analytic hierarchy process, the eigenvalue associated with a path is identified as the parameter which enables the rank ordering of paths. The ability to identify a subset of dominant paths relative to enhancing consistency enhances the computational viability of the consistency framework for real-time implementation and has significant practical implications. Additionally, it provides insights on the complex dynamics that are inherent to the operational consistency problem.

  16. Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems

    CERN Document Server

    Rosvall, M

    2010-01-01

    To comprehend the hierarchical organization of large integrated systems, we introduce the hierarchical map equation that reveals multilevel structures in networks. In this information-theoretic approach, we exploit the duality between compression and pattern detection; by compressing a description of a random walker as a proxy for real flow on a network, we find regularities in the network that induce this system-wide flow. Finding the shortest multilevel description of the random walker therefore gives us the best hierarchical clustering of the network, the optimal number of levels and modular partition at each level, with respect to the dynamics on the network. With a novel search algorithm, we extract and illustrate the rich multilevel organization of several large social and biological networks. For example, from the global air traffic network we uncover countries and continents, and from the pattern of scientific communication we reveal more than 100 scientific fields organized in four major disciplines:...

  17. Multiple dynamical time-scales in networks with hierarchically nested modular organization

    Indian Academy of Sciences (India)

    Sitabhra Sinha; Swarup Poria

    2011-11-01

    Many natural and engineered complex networks have intricate mesoscopic organization, e.g., the clustering of the constituent nodes into several communities or modules. Often, such modularity is manifested at several different hierarchical levels, where the clusters defined at one level appear as elementary entities at the next higher level. Using a simple model of a hierarchical modular network, we show that such a topological structure gives rise to characteristic time-scale separation between dynamics occurring at different levels of the hierarchy. This generalizes our earlier result for simple modular networks, where fast intramodular and slow intermodular processes were clearly distinguished. Investigating the process of synchronization of oscillators in a hierarchical modular network, we show the existence of as many distinct time-scales as there are hierarchical levels in the system. This suggests a possible functional role of such mesoscopic organization principle in natural systems, viz., in the dynamical separation of events occurring at different spatial scales.

  18. Loss Performance Modeling for Hierarchical Heterogeneous Wireless Networks With Speed-Sensitive Call Admission Control

    DEFF Research Database (Denmark)

    Huang, Qian; Huang, Yue-Cai; Ko, King-Tim;

    2011-01-01

    dimensioning and planning. This paper investigates the computationally efficient loss performance modeling for multiservice in hierarchical heterogeneous wireless networks. A speed-sensitive call admission control (CAC) scheme is considered in our model to assign overflowed calls to appropriate tiers...

  19. Consistently Trained Artificial Neural Network for Automatic Ship Berthing Control

    Directory of Open Access Journals (Sweden)

    Y.A. Ahmed

    2015-09-01

    Full Text Available In this paper, consistently trained Artificial Neural Network controller for automatic ship berthing is discussed. Minimum time course changing manoeuvre is utilised to ensure such consistency and a new concept named ‘virtual window’ is introduced. Such consistent teaching data are then used to train two separate multi-layered feed forward neural networks for command rudder and propeller revolution output. After proper training, several known and unknown conditions are tested to judge the effectiveness of the proposed controller using Monte Carlo simulations. After getting acceptable percentages of success, the trained networks are implemented for the free running experiment system to judge the network’s real time response for Esso Osaka 3-m model ship. The network’s behaviour during such experiments is also investigated for possible effect of initial conditions as well as wind disturbances. Moreover, since the final goal point of the proposed controller is set at some distance from the actual pier to ensure safety, therefore a study on automatic tug assistance is also discussed for the final alignment of the ship with actual pier.

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

    Science.gov (United States)

    Kawano, Keita; Kinoshita, Kazuhiko; Yamai, Nariyoshi

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

  1. IPTV traffic management using topology-based hierarchical scheduling in Carrier Ethernet transport networks

    DEFF Research Database (Denmark)

    Yu, Hao; Yan, Ying; Berger, Michael Stubert

    2009-01-01

    of Service (QoS) provisioning abilities, which guarantee end-to-end performances of voice, video and data traffic delivered over networks. This paper introduces a topology-based hierarchical scheduler scheme, which controls the incoming traffic at the edge of the network based on the network topology...

  2. Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images

    Science.gov (United States)

    Alshehhi, Rasha; Marpu, Prashanth Reddy

    2017-04-01

    Extraction of road networks in urban areas from remotely sensed imagery plays an important role in many urban applications (e.g. road navigation, geometric correction of urban remote sensing images, updating geographic information systems, etc.). It is normally difficult to accurately differentiate road from its background due to the complex geometry of the buildings and the acquisition geometry of the sensor. In this paper, we present a new method for extracting roads from high-resolution imagery based on hierarchical graph-based image segmentation. The proposed method consists of: 1. Extracting features (e.g., using Gabor and morphological filtering) to enhance the contrast between road and non-road pixels, 2. Graph-based segmentation consisting of (i) Constructing a graph representation of the image based on initial segmentation and (ii) Hierarchical merging and splitting of image segments based on color and shape features, and 3. Post-processing to remove irregularities in the extracted road segments. Experiments are conducted on three challenging datasets of high-resolution images to demonstrate the proposed method and compare with other similar approaches. The results demonstrate the validity and superior performance of the proposed method for road extraction in urban areas.

  3. Hierarchically structured monolithic silicalite-1 consisting of crystallized nanoparticles and its performance in the Beckmann rearrangement of cyclohexanone oxime.

    Science.gov (United States)

    Li, Wen-Cui; Lu, An-Hui; Palkovits, Regina; Schmidt, Wolfgang; Spliethoff, Bernd; Schüth, Ferdi

    2005-09-14

    In this study, we present a synthetic pathway for the fabrication of self-supporting zeolite monoliths consisting of crystallized nanoparticles. A resorcinol-formaldehyde-based organic aerogel is used as a template, and silicalite-1 is used as the zeolite example. The silicalite-1 monoliths obtained consist of individual well-defined zeolite nanocrystals with sizes of 30-40 nm. The monoliths exhibit a high mechanical stability and have hierarchical porosity, with micropores within the zeolite particles, a mesopore system formed by the packing of the nanoparticles, and a macropore system on the monolith level. Such monolithic zeolites show high selectivity typically above 80% to epsilon-caprolactam combined with a high rate of reaction of 0.46 g(caprolactame)/(g(catalyst).h) in the Beckmann rearrangement of cyclohexanone oxime.

  4. Stable functional networks exhibit consistent timing in the human brain.

    Science.gov (United States)

    Chapeton, Julio I; Inati, Sara K; Zaghloul, Kareem A

    2017-03-01

    Despite many advances in the study of large-scale human functional networks, the question of timing, stability, and direction of communication between cortical regions has not been fully addressed. At the cellular level, neuronal communication occurs through axons and dendrites, and the time required for such communication is well defined and preserved. At larger spatial scales, however, the relationship between timing, direction, and communication between brain regions is less clear. Here, we use a measure of effective connectivity to identify connections between brain regions that exhibit communication with consistent timing. We hypothesized that if two brain regions are communicating, then knowledge of the activity in one region should allow an external observer to better predict activity in the other region, and that such communication involves a consistent time delay. We examine this question using intracranial electroencephalography captured from nine human participants with medically refractory epilepsy. We use a coupling measure based on time-lagged mutual information to identify effective connections between brain regions that exhibit a statistically significant increase in average mutual information at a consistent time delay. These identified connections result in sparse, directed functional networks that are stable over minutes, hours, and days. Notably, the time delays associated with these connections are also highly preserved over multiple time scales. We characterize the anatomic locations of these connections, and find that the propagation of activity exhibits a preferred posterior to anterior temporal lobe direction, consistent across participants. Moreover, networks constructed from connections that reliably exhibit consistent timing between anatomic regions demonstrate features of a small-world architecture, with many reliable connections between anatomically neighbouring regions and few long range connections. Together, our results demonstrate

  5. Hierarchical Route Optimization By Using Memetic Algorithm In A Mobile Networks

    Directory of Open Access Journals (Sweden)

    K .K. Gautam

    2011-02-01

    Full Text Available The networks Mobility (NEMO Protocol is a way of managing the mobility of an entire network, and mobile internet protocol is the basic solution for networks Mobility. A hierarchical route optimization system for mobile network is proposed to solve management of hierarchical route optimization problems. In present paper we study hierarchical Route Optimization scheme using memetic algorithm(HROSMA The concept of optimization- finding the extreme of a function that maps candidate ‘solution’ to scalar values of ‘quality’ – is an extremely general and useful idea. For solving this problem, we use a few salient adaptations, and we also extend HROSMA perform routing between the mobile networks.

  6. Coordinated Workload Scheduling in Hierarchical Sensor Networks for Data Fusion Applications

    Institute of Scientific and Technical Information of China (English)

    Xiao-Lin Li; Jian-Nong Cao

    2008-01-01

    To minimize the execution time of a sensing task over a multi-hop hierarchical sensor network, we present acoordinated scheduling method following the divisible load scheduling paradigm. The proposed scheduling strategy builds on eliminating transmission collisions and idle gaps between two successive data transmissions. We consider a sensor network consisting of several clusters. In a cluster, after related raw data measured by source nodes are collected at the fusion node,in-network data aggregation is further considered. The scheduling strategies consist of two phases: intra-cluster scheduling and inter-cluster scheduling. Intra-cluster scheduling deals with assigning different fractions of a sensing workload among source nodes in each cluster; inter-cluster scheduling involves the distribution of fused data among all fusion nodes. Closed-form solutions to the problem of task scheduling are derived. Finally, numerical examples are presented to demonstrate the impacts of different system parameters such as the number of sensor nodes, measurement, communication, and processing speed, on the finish time and energy consumption.

  7. Multilevel compression of random walks on networks reveals hierarchical organization in large integrated systems.

    Directory of Open Access Journals (Sweden)

    Martin Rosvall

    Full Text Available To comprehend the hierarchical organization of large integrated systems, we introduce the hierarchical map equation, which reveals multilevel structures in networks. In this information-theoretic approach, we exploit the duality between compression and pattern detection; by compressing a description of a random walker as a proxy for real flow on a network, we find regularities in the network that induce this system-wide flow. Finding the shortest multilevel description of the random walker therefore gives us the best hierarchical clustering of the network--the optimal number of levels and modular partition at each level--with respect to the dynamics on the network. With a novel search algorithm, we extract and illustrate the rich multilevel organization of several large social and biological networks. For example, from the global air traffic network we uncover countries and continents, and from the pattern of scientific communication we reveal more than 100 scientific fields organized in four major disciplines: life sciences, physical sciences, ecology and earth sciences, and social sciences. In general, we find shallow hierarchical structures in globally interconnected systems, such as neural networks, and rich multilevel organizations in systems with highly separated regions, such as road networks.

  8. Identifying time-delayed gene regulatory networks via an evolvable hierarchical recurrent neural network.

    Science.gov (United States)

    Kordmahalleh, Mina Moradi; Sefidmazgi, Mohammad Gorji; Harrison, Scott H; Homaifar, Abdollah

    2017-01-01

    The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design. Interactions in gene regulatory networks (GRNs) include effects of transcription factors, repressors, small metabolites, and microRNA species. In addition, the effects of regulatory interactions are not always simultaneous, but can occur after a finite time delay, or as a combined outcome of simultaneous and time delayed interactions. Powerful biotechnologies have been rapidly and successfully measuring levels of genetic expression to illuminate different states of biological systems. This has led to an ensuing challenge to improve the identification of specific regulatory mechanisms through regulatory network reconstructions. Solutions to this challenge will ultimately help to spur forward efforts based on the usage of regulatory network reconstructions in systems biology applications. We have developed a hierarchical recurrent neural network (HRNN) that identifies time-delayed gene interactions using time-course data. A customized genetic algorithm (GA) was used to optimize hierarchical connectivity of regulatory genes and a target gene. The proposed design provides a non-fully connected network with the flexibility of using recurrent connections inside the network. These features and the non-linearity of the HRNN facilitate the process of identifying temporal patterns of a GRN. Our HRNN method was implemented with the Python language. It was first evaluated on simulated data representing linear and nonlinear time-delayed gene-gene interaction models across a range of network sizes and variances of noise. We then further demonstrated the capability of our method in reconstructing GRNs of the Saccharomyces cerevisiae synthetic network for in vivo benchmarking of reverse-engineering and modeling approaches (IRMA). We compared the performance of our method to TD-ARACNE, HCC-CLINDE, TSNI and ebdbNet across different network

  9. Fluctuation relations between hierarchical kinetically equivalent networks with Arrhenius-type transitions and their roles in systems and structural biology

    Science.gov (United States)

    Deng, De-Ming; Lu, Yi-Ta; Chang, Cheng-Hung

    2017-06-01

    The legality of using simple kinetic schemes to determine the stochastic properties of a complex system depends on whether the fluctuations generated from hierarchical equivalent schemes are consistent with one another. To analyze this consistency, we perform lumping processes on the stochastic differential equations and the generalized fluctuation-dissipation theorem and apply them to networks with the frequently encountered Arrhenius-type transition rates. The explicit Langevin force derived from those networks enables us to calculate the state fluctuations caused by the intrinsic and extrinsic noises on the free energy surface and deduce their relations between kinetically equivalent networks. In addition to its applicability to wide classes of network related systems, such as those in structural and systems biology, the result sheds light on the fluctuation relations for general physical variables in Keizer's canonical theory.

  10. Sustained Activity in Hierarchical Modular Neural Networks: Self-Organized Criticality and Oscillations

    Science.gov (United States)

    Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong

    2010-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  11. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations

    Directory of Open Access Journals (Sweden)

    Sheng-Jun Wang

    2011-06-01

    Full Text Available Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. They are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality. We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. It was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We find that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and self-organized criticality, which are not present in the respective random networks. The underlying mechanism is that each dense module cannot sustain activity on its own, but displays self-organized criticality in the presence of weak perturbations. The hierarchical modular networks provide the coupling among subsystems with self-organized criticality. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivityof critical state and predictability and timing of oscillations for efficient

  12. Sustained activity in hierarchical modular neural networks: self-organized criticality and oscillations.

    Science.gov (United States)

    Wang, Sheng-Jun; Hilgetag, Claus C; Zhou, Changsong

    2011-01-01

    Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information

  13. Context-specific metabolic networks are consistent with experiments.

    Directory of Open Access Journals (Sweden)

    Scott A Becker

    2008-05-01

    Full Text Available Reconstructions of cellular metabolism are publicly available for a variety of different microorganisms and some mammalian genomes. To date, these reconstructions are "genome-scale" and strive to include all reactions implied by the genome annotation, as well as those with direct experimental evidence. Clearly, many of the reactions in a genome-scale reconstruction will not be active under particular conditions or in a particular cell type. Methods to tailor these comprehensive genome-scale reconstructions into context-specific networks will aid predictive in silico modeling for a particular situation. We present a method called Gene Inactivity Moderated by Metabolism and Expression (GIMME to achieve this goal. The GIMME algorithm uses quantitative gene expression data and one or more presupposed metabolic objectives to produce the context-specific reconstruction that is most consistent with the available data. Furthermore, the algorithm provides a quantitative inconsistency score indicating how consistent a set of gene expression data is with a particular metabolic objective. We show that this algorithm produces results consistent with biological experiments and intuition for adaptive evolution of bacteria, rational design of metabolic engineering strains, and human skeletal muscle cells. This work represents progress towards producing constraint-based models of metabolism that are specific to the conditions where the expression profiling data is available.

  14. Prolonging the Lifetime of Wireless Sensor Networks Interconnected to Fixed Network Using Hierarchical Energy Tree Based Routing Algorithm

    Directory of Open Access Journals (Sweden)

    M. Kalpana

    2014-01-01

    Full Text Available This research work proposes a mathematical model for the lifetime of wireless sensor networks (WSN. It also proposes an energy efficient routing algorithm for WSN called hierarchical energy tree based routing algorithm (HETRA based on hierarchical energy tree constructed using the available energy in each node. The energy efficiency is further augmented by reducing the packet drops using exponential congestion control algorithm (TCP/EXP. The algorithms are evaluated in WSNs interconnected to fixed network with seven distribution patterns, simulated in ns2 and compared with the existing algorithms based on the parameters such as number of data packets, throughput, network lifetime, and data packets average network lifetime product. Evaluation and simulation results show that the combination of HETRA and TCP/EXP maximizes longer network lifetime in all the patterns. The lifetime of the network with HETRA algorithm has increased approximately 3.2 times that of the network implemented with AODV.

  15. Dynamic Hierarchical Sleep Scheduling for Wireless Ad-Hoc Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chih-Yu Wen

    2009-05-01

    Full Text Available This paper presents two scheduling management schemes for wireless sensor networks, which manage the sensors by utilizing the hierarchical network structure and allocate network resources efficiently. A local criterion is used to simultaneously establish the sensing coverage and connectivity such that dynamic cluster-based sleep scheduling can be achieved. The proposed schemes are simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithms provide efficient network power control and can achieve high scalability in wireless sensor networks.

  16. Exact and Approximate Inference in Associative Hierarchical Networks using Graph Cuts

    CERN Document Server

    Russell, Chris; Kohli, Pushmeet; Torr, Philip H S

    2012-01-01

    Markov Networks are widely used through out computer vision and machine learning. An important subclass are the Associative Markov Networks which are used in a wide variety of applications. For these networks a good approximate minimum cost solution can be found efficiently using graph cut based move making algorithms such as alpha- expansion. Recently a related model has been proposed, the associative hierarchical net- work, which provides a natural generalisation of the Associative Markov Network for higher order cliques (i.e. clique size greater than two). This method provides a good model for object class segmentation problem in com- puter vision. Within this paper we briefly describe the associative hierarchical network and provide a computationally efficient method for ap- proximate inference based on graph cuts. Our method performs well for networks con- taining hundreds of thousand of variables, and higher order potentials are defined over cliques containing tens of thousands of vari- ables. Due to th...

  17. The Griffiths Phase on Hierarchical Modular Networks with Small-world Edges

    CERN Document Server

    Li, Shanshan

    2016-01-01

    The Griffiths phase has been proposed to induce a stretched critical regime that facilitates self organizing of brain networks for optimal function. This phase stems from the intrinsic structural heterogeneity of brain networks, such as the hierarchical modular structure. In this work, we extend this concept to modified hierarchical networks with small-world connections based on Hanoi networks [1]. Through extensive simulations, we identify the essential role played by the exponential distribution of the inter-moduli connectivity probability across hierarchies on the emergence of the Griffiths phase in this network. Additionally, the spectral analysis on the adjacency matrix of the relevant networks [2] shows that a localized principle eigenvector is not necessarily the fingerprint of the Griffiths phase.

  18. NEW METHOD TO ESTIMATE SCALING OF POWER-LAW DEGREE DISTRIBUTION AND HIERARCHICAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    YANG Bo; DUAN Wen-qi; CHEN Zhong

    2006-01-01

    A new method and corresponding numerical procedure are introduced to estimate scaling exponents of power-law degree distribution and hierarchical clustering func tion for complex networks. This method can overcome the biased and inaccurate faults of graphical linear fitting methods commonly used in current network research. Furthermore, it is verified to have higher goodness-of-fit than graphical methods by comparing the KS (Kolmogorov-Smirnov) test statistics for 10 CNN (Connecting Nearest-Neighbor)networks.

  19. Modular networks with hierarchical organization: The dynamical implications of complex structure

    Indian Academy of Sciences (India)

    Raj Kumar Pan; Sitabhra Sinha

    2008-08-01

    Several networks occurring in real life have modular structures that are arranged in a hierarchical fashion. In this paper, we have proposed a model for such networks, using a stochastic generation method. Using this model we show that, the scaling relation between the clustering and degree of the nodes is not a necessary property of hierarchical modular networks, as had previously been suggested on the basis of a deterministically constructed model. We also look at dynamics on such networks, in particular, the stability of equilibria of network dynamics and of synchronized activity in the network. For both of these, we find that, increasing modularity or the number of hierarchical levels tends to increase the probability of instability. As both hierarchy and modularity are seen in natural systems, which necessarily have to be robust against environmental fluctuations, we conclude that additional constraints are necessary for the emergence of hierarchical structure, similar to the occurrence of modularity through multi-constraint optimization as shown by us previously.

  20. Application of growing hierarchical SOM for visualisation of network forensics traffic data.

    Science.gov (United States)

    Palomo, E J; North, J; Elizondo, D; Luque, R M; Watson, T

    2012-08-01

    Digital investigation methods are becoming more and more important due to the proliferation of digital crimes and crimes involving digital evidence. Network forensics is a research area that gathers evidence by collecting and analysing network traffic data logs. This analysis can be a difficult process, especially because of the high variability of these attacks and large amount of data. Therefore, software tools that can help with these digital investigations are in great demand. In this paper, a novel approach to analysing and visualising network traffic data based on growing hierarchical self-organising maps (GHSOM) is presented. The self-organising map (SOM) has been shown to be successful for the analysis of highly-dimensional input data in data mining applications as well as for data visualisation in a more intuitive and understandable manner. However, the SOM has some problems related to its static topology and its inability to represent hierarchical relationships in the input data. The GHSOM tries to overcome these limitations by generating a hierarchical architecture that is automatically determined according to the input data and reflects the inherent hierarchical relationships among them. Moreover, the proposed GHSOM has been modified to correctly treat the qualitative features that are present in the traffic data in addition to the quantitative features. Experimental results show that this approach can be very useful for a better understanding of network traffic data, making it easier to search for evidence of attacks or anomalous behaviour in a network environment. Copyright © 2012 Elsevier Ltd. All rights reserved.

  1. A Hierarchical Approach to Persistent Scatterer Network Construction and Deformation Time Series Estimation

    Directory of Open Access Journals (Sweden)

    Rui Zhang

    2014-12-01

    Full Text Available This paper presents a hierarchical approach to network construction and time series estimation in persistent scatterer interferometry (PSI for deformation analysis using the time series of high-resolution satellite SAR images. To balance between computational efficiency and solution accuracy, a dividing and conquering algorithm (i.e., two levels of PS networking and solution is proposed for extracting deformation rates of a study area. The algorithm has been tested using 40 high-resolution TerraSAR-X images collected between 2009 and 2010 over Tianjin in China for subsidence analysis, and validated by using the ground-based leveling measurements. The experimental results indicate that the hierarchical approach can remarkably reduce computing time and memory requirements, and the subsidence measurements derived from the hierarchical solution are in good agreement with the leveling data.

  2. Detecting Hidden Hierarchy of Non Hierarchical Terrorist Networks

    DEFF Research Database (Denmark)

    Memon, Nasrullah

    to analyze terrorist networks and prioritize their targets. Applying recently introduced mathematical methods for constructing the hidden hierarchy of "nonhierarchical" terrorist networks; we present case studies of the terrorist attacks occurred / planned in the past, in order to identify hidden hierarchy...

  3. A Hierarchical Multiobjective Routing Model for MPLS Networks with Two Service Classes

    Science.gov (United States)

    Craveirinha, José; Girão-Silva, Rita; Clímaco, João; Martins, Lúcia

    This work presents a model for multiobjective routing in MPLS networks formulated within a hierarchical network-wide optimization framework, with two classes of services, namely QoS and Best Effort (BE) services. The routing model uses alternative routing and hierarchical optimization with two optimization levels, including fairness objectives. Another feature of the model is the use of an approximate stochastic representation of the traffic flows in the network, based on the concept of effective bandwidth. The theoretical foundations of a heuristic strategy for finding “good” compromise solutions to the very complex bi-level routing optimization problem, based on a conjecture concerning the definition of marginal implied costs for QoS flows and BE flows, will be described. The main features of a first version of this heuristic based on a bi-objective shortest path model and some preliminary results for a benchmark network will also be revealed.

  4. An Advanced Survey on Secure Energy-Efficient Hierarchical Routing Protocols in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Abdoulaye Diop

    2013-01-01

    Full Text Available Wireless Sensor Networks (WSNs are often deployed in hostile environments, which make such networks highly vulnerable and increase the risk of attacks against this type of network. WSN comprise of large number of sensor nodes with different hardware abilities and functions. Due to the limited memory resources and energy constraints, complex security algorithms cannot be used in sensor networks. Therefore, it is necessary to balance between the security level and the associated energy consumption overhead to mitigate the security risks. Hierarchical routing protocol is more energy-efficient than other routing protocols in WSNs. Many secure cluster-based routing protocols have been proposed in the literature to overcome these constraints. In this paper, we discuss Secure Energy-Efficient Hierarchical Routing Protocols in WSNs and compare them in terms of security, performance and efficiency. Security issues for WSNs and their solutions are also discussed.

  5. Bottom-up GGM algorithm for constructing multiple layered hierarchical gene regulatory networks

    Science.gov (United States)

    Multilayered hierarchical gene regulatory networks (ML-hGRNs) are very important for understanding genetics regulation of biological pathways. However, there are currently no computational algorithms available for directly building ML-hGRNs that regulate biological pathways. A bottom-up graphic Gaus...

  6. A Novel Hierarchical Semi-centralized Telemedicine Network Architecture Proposition for Bangladesh

    DEFF Research Database (Denmark)

    Choudhury, Samiul; Peterson, Carrie Beth; Kyriazakos, Sofoklis

    2011-01-01

    where there are extreme paucities of efficient healthcare professionals and equipments, specifically in the rural areas. In this paper a novel, hierarchical and semi-centralized telemedicine network architecture has been proposed holisti-cally focusing on the rural underdeveloped areas of Bangladesh...... of Bangladesh. Finally, some features and services associated with the model have also been proposed which are pragmatic and easily implementable....

  7. The exact Laplacian spectrum for the Dyson hierarchical network

    CERN Document Server

    Agliari, Elena

    2016-01-01

    We consider the Dyson hierarchical graph $\\mathcal{G}$, that is a weighted fully-connected graph, where the pattern of weights is ruled by the parameter $\\sigma \\in (1/2, 1]$. Exploiting the deterministic recursivity through which $\\mathcal{G}$ is built, we are able to derive explicitly the whole set of the eigenvalues and the eigenvectors for its Laplacian matrix. Given that the Laplacian operator is intrinsically implied in the analysis of dynamic processes (e.g., random walks) occurring on the graph, as well as in the investigation of the dynamical properties of connected structures themselves (e.g., vibrational structures and the relaxation modes), this result allows addressing analytically a large class of problems. In particular, as examples of applications, we study the random walk and the continuous-time quantum walk embedded in $\\mathcal{G}$, and the relaxation times of a polymer whose structure is described by $\\mathcal{G}$.

  8. The exact Laplacian spectrum for the Dyson hierarchical network

    Science.gov (United States)

    Agliari, Elena; Tavani, Flavia

    2017-01-01

    We consider the Dyson hierarchical graph , that is a weighted fully-connected graph, where the pattern of weights is ruled by the parameter σ ∈ (1/2, 1]. Exploiting the deterministic recursivity through which is built, we are able to derive explicitly the whole set of the eigenvalues and the eigenvectors for its Laplacian matrix. Given that the Laplacian operator is intrinsically implied in the analysis of dynamic processes (e.g., random walks) occurring on the graph, as well as in the investigation of the dynamical properties of connected structures themselves (e.g., vibrational structures and relaxation modes), this result allows addressing analytically a large class of problems. In particular, as examples of applications, we study the random walk and the continuous-time quantum walk embedded in , the relaxation times of a polymer whose structure is described by , and the community structure of in terms of modularity measures.

  9. Cluster based hierarchical resource searching model in P2P network

    Institute of Scientific and Technical Information of China (English)

    Yang Ruijuan; Liu Jian; Tian Jingwen

    2007-01-01

    For the problem of large network load generated by the Gnutella resource-searching model in Peer to Peer (P2P) network, a improved model to decrease the network expense is proposed, which establishes a duster in P2P network,auto-organizes logical layers, and applies a hybrid mechanism of directional searching and flooding. The performance analysis and simulation results show that the proposed hierarchical searching model has availably reduced the generated message load and that its searching-response time performance is as fairly good as that of the Gnutella model.

  10. Avalanche transmission and critical behaviour in load-bearing hierarchical networks

    Indian Academy of Sciences (India)

    Ajay Deep Kachhvah; Neelima Gupte

    2011-11-01

    The strength and stability properties of hierarchical load-bearing networks and their strengthened variants have been discussed in a recent work. Here, we study the avalanche time distributions on these load-bearing networks. The avalanche time distributions of the V-lattice, a unique realization of the networks, show power-law behaviour when tested with certain fractions of its trunk weights. All other avalanche distributions show Gaussian peaked behaviour. Thus the V-lattice is the critical case of the network. We discuss the implications of this result.

  11. Internal representation of hierarchical sequences involves the default network

    Directory of Open Access Journals (Sweden)

    Rogers Baxter P

    2010-04-01

    Full Text Available Abstract Background The default network is a set of brain regions that exhibit a reduction in BOLD response during attention-demanding cognitive tasks, and distinctive patterns of functional connectivity that typically include anti-correlations with a fronto-parietal network involved in attention, working memory, and executive control. The function of the default network regions has been attributed to introspection, self-awareness, and theory of mind judgments, and some of its regions are involved in episodic memory processes. Results Using the method of psycho-physiological interactions, we studied the functional connectivity of several regions in a fronto-parietal network involved in a paired image discrimination task involving transitive inference. Some image pairs were derived from an implicit underlying sequence A>B>C>D>E, and some were independent (F>G, H>J, etc. Functional connectivity between the fronto-parietal regions and the default network regions depended on the presence of the underlying sequence relating the images. When subjects viewed learned and novel pairs from the sequence, connectivity between these two networks was higher than when subjects viewed learned and novel pairs from the independent sets. Conclusions These results suggest that default network regions were involved in maintaining the internal model that subserved discrimination of image pairs derived from the implicit sequence, and contributed to introspective access of an internal sequence model built during training. The default network may not be a unified entity with a specific function, but rather may interact with other functional networks in task-dependent ways.

  12. Multilevel hierarchical kernel spectral clustering for real-life large scale complex networks.

    Directory of Open Access Journals (Sweden)

    Raghvendra Mall

    Full Text Available Kernel spectral clustering corresponds to a weighted kernel principal component analysis problem in a constrained optimization framework. The primal formulation leads to an eigen-decomposition of a centered Laplacian matrix at the dual level. The dual formulation allows to build a model on a representative subgraph of the large scale network in the training phase and the model parameters are estimated in the validation stage. The KSC model has a powerful out-of-sample extension property which allows cluster affiliation for the unseen nodes of the big data network. In this paper we exploit the structure of the projections in the eigenspace during the validation stage to automatically determine a set of increasing distance thresholds. We use these distance thresholds in the test phase to obtain multiple levels of hierarchy for the large scale network. The hierarchical structure in the network is determined in a bottom-up fashion. We empirically showcase that real-world networks have multilevel hierarchical organization which cannot be detected efficiently by several state-of-the-art large scale hierarchical community detection techniques like the Louvain, OSLOM and Infomap methods. We show that a major advantage of our proposed approach is the ability to locate good quality clusters at both the finer and coarser levels of hierarchy using internal cluster quality metrics on 7 real-life networks.

  13. Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

    Science.gov (United States)

    Chang, Yuchao; Tang, Hongying; Cheng, Yongbo; Zhao, Qin; Yuan, Baoqing Li andXiaobing

    2017-07-19

    Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

  14. Hierarchical Synchrony of Phase Oscillators in Modular Networks

    CERN Document Server

    Skardal, Per Sebastian

    2011-01-01

    We study synchronization of sinusoidally coupled phase oscillators on networks with modular structure and a large number of oscillators in each community. Of particular interest is the hierarchy of local and global synchrony, i.e., synchrony within and between communities, respectively. Using the recent ansatz of Ott and Antonsen, we find that the degree of local synchrony can be determined from a set of coupled low-dimensional equations. If the number of communities in the network is large, a low-dimensional description of global synchrony can be also found. Using these results, we study bifurcations between different types of synchrony. We find that, depending on the relative strength of local and global coupling, the transition to synchrony in the network can be mediated by local or global effects.

  15. Identifying overlapping and hierarchical thematic structures in networks of scholarly papers: a comparison of three approaches.

    Science.gov (United States)

    Havemann, Frank; Gläser, Jochen; Heinz, Michael; Struck, Alexander

    2012-01-01

    The aim of this paper is to introduce and assess three algorithms for the identification of overlapping thematic structures in networks of papers. We implemented three recently proposed approaches to the identification of overlapping and hierarchical substructures in graphs and applied the corresponding algorithms to a network of 492 information-science papers coupled via their cited sources. The thematic substructures obtained and overlaps produced by the three hierarchical cluster algorithms were compared to a content-based categorisation, which we based on the interpretation of titles, abstracts, and keywords. We defined sets of papers dealing with three topics located on different levels of aggregation: h-index, webometrics, and bibliometrics. We identified these topics with branches in the dendrograms produced by the three cluster algorithms and compared the overlapping topics they detected with one another and with the three predefined paper sets. We discuss the advantages and drawbacks of applying the three approaches to paper networks in research fields.

  16. Identifying overlapping and hierarchical thematic structures in networks of scholarly papers: a comparison of three approaches.

    Directory of Open Access Journals (Sweden)

    Frank Havemann

    Full Text Available The aim of this paper is to introduce and assess three algorithms for the identification of overlapping thematic structures in networks of papers. We implemented three recently proposed approaches to the identification of overlapping and hierarchical substructures in graphs and applied the corresponding algorithms to a network of 492 information-science papers coupled via their cited sources. The thematic substructures obtained and overlaps produced by the three hierarchical cluster algorithms were compared to a content-based categorisation, which we based on the interpretation of titles, abstracts, and keywords. We defined sets of papers dealing with three topics located on different levels of aggregation: h-index, webometrics, and bibliometrics. We identified these topics with branches in the dendrograms produced by the three cluster algorithms and compared the overlapping topics they detected with one another and with the three predefined paper sets. We discuss the advantages and drawbacks of applying the three approaches to paper networks in research fields.

  17. A CDMA Based Scalable Hierarchical Architecture for Network-On-Chip

    Directory of Open Access Journals (Sweden)

    Mohamed A. Abd El Ghany

    2012-09-01

    Full Text Available A Scalable hierarchical architecture based Code-Division Multiple Access (CDMA is proposed for high performance Network-on-Chip (NoC. This hierarchical architecture provides the integration of a large number of IPs in a single on-chip system. The network encoding and decoding schemes for CDMA transmission are provided. The proposed CDMA NoC architecture is compared to the conventional architecture in terms of latency, area and power dissipation. The overall area required to implement the proposed CDMA NoC design is reduced by 24.2%. The design decreases the latency of the network by 40%. The total power consumption required to achieve the proposed design is also decreased by 25%.

  18. Scaling of the Average Receiving Time on a Family of Weighted Hierarchical Networks

    Science.gov (United States)

    Sun, Yu; Dai, Meifeng; Sun, Yanqiu; Shao, Shuxiang

    2016-08-01

    In this paper, based on the un-weight hierarchical networks, a family of weighted hierarchical networks are introduced, the weight factor is denoted by r. The weighted hierarchical networks depend on the number of nodes in complete bipartite graph, denoted by n1, n2 and n = n1 + n2. Assume that the walker, at each step, starting from its current node, moves to any of its neighbors with probability proportional to the weight of edge linking them. We deduce the analytical expression of the average receiving time (ART). The obtained remarkable results display two conditions. In the large network, when nr > n1n2, the ART grows as a power-law function of the network size |V (Gk)| with the exponent, represented by θ =logn( nr n1n2 ), 0 < θ < 1. This means that the smaller the value of θ, the more efficient the process of receiving information. When nr ≤ n1n2, the ART grows with increasing order |V (Gk)| as logn|V (Gk)| or (logn|V (Gk)|)2.

  19. Rubber elasticity for percolation network consisting of Gaussian chains

    Energy Technology Data Exchange (ETDEWEB)

    Nishi, Kengo, E-mail: kengo.nishi@phys.uni-goettingen.de, E-mail: sakai@tetrapod.t.u-tokyo.ac.jp, E-mail: sibayama@issp.u-tokyo.ac.jp; Noguchi, Hiroshi; Shibayama, Mitsuhiro, E-mail: kengo.nishi@phys.uni-goettingen.de, E-mail: sakai@tetrapod.t.u-tokyo.ac.jp, E-mail: sibayama@issp.u-tokyo.ac.jp [Institute for Solid State Physics, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8581 (Japan); Sakai, Takamasa, E-mail: kengo.nishi@phys.uni-goettingen.de, E-mail: sakai@tetrapod.t.u-tokyo.ac.jp, E-mail: sibayama@issp.u-tokyo.ac.jp [Department of Bioengineering, School of Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656 (Japan)

    2015-11-14

    A theory describing the elastic modulus for percolation networks of Gaussian chains on general lattices such as square and cubic lattices is proposed and its validity is examined with simulation and mechanical experiments on well-defined polymer networks. The theory was developed by generalizing the effective medium approximation (EMA) for Hookian spring network to Gaussian chain networks. From EMA theory, we found that the ratio of the elastic modulus at p, G to that at p = 1, G{sub 0}, must be equal to G/G{sub 0} = (p − 2/f)/(1 − 2/f) if the position of sites can be determined so as to meet the force balance, where p is the degree of cross-linking reaction. However, the EMA prediction cannot be applicable near its percolation threshold because EMA is a mean field theory. Thus, we combine real-space renormalization and EMA and propose a theory called real-space renormalized EMA, i.e., REMA. The elastic modulus predicted by REMA is in excellent agreement with the results of simulations and experiments of near-ideal diamond lattice gels.

  20. Rubber elasticity for percolation network consisting of Gaussian chains.

    Science.gov (United States)

    Nishi, Kengo; Noguchi, Hiroshi; Sakai, Takamasa; Shibayama, Mitsuhiro

    2015-11-14

    A theory describing the elastic modulus for percolation networks of Gaussian chains on general lattices such as square and cubic lattices is proposed and its validity is examined with simulation and mechanical experiments on well-defined polymer networks. The theory was developed by generalizing the effective medium approximation (EMA) for Hookian spring network to Gaussian chain networks. From EMA theory, we found that the ratio of the elastic modulus at p, G to that at p = 1, G0, must be equal to G/G0 = (p - 2/f)/(1 - 2/f) if the position of sites can be determined so as to meet the force balance, where p is the degree of cross-linking reaction. However, the EMA prediction cannot be applicable near its percolation threshold because EMA is a mean field theory. Thus, we combine real-space renormalization and EMA and propose a theory called real-space renormalized EMA, i.e., REMA. The elastic modulus predicted by REMA is in excellent agreement with the results of simulations and experiments of near-ideal diamond lattice gels.

  1. Rubber Elasticity for percolation network consisting of Gaussian Chains

    Science.gov (United States)

    Nishi, Kengo; Shibayama, Mitsuhiro; Sakai, Takamasa

    A theory describing the elastic modulus for percolation networks of Gaussian chains on general lattices such as square and cubic lattices is proposed and its validity is examined with simulation and mechanical experiments on well-defined polymer networks. The theory was developed by generalizing the effective medium approximation for Hookian spring network (EMA) to Gaussian chain networks. From EMA theory, we found that the ratio of the elastic modulus at p, G to that at p = 1 ,G0, must be equal to G /G0 = (p - 2 / f) / (1 - 2 / f) if the position of sites can be determined so as to meet the force balance, where p is the degree of cross-linking reaction. However, the EMA prediction cannot be applicable near its percolation threshold because EMA is a mean field theory. Thus, we combine real-space renormalization and EMA, and propose a theory called real-space renormalized EMA, i.e., REMA. The elastic modulus predicted by REMA is in excellent agreement with the results of simulations and experiments of near-ideal diamond lattice gels.

  2. Synchronization in heterogeneous FitzHugh-Nagumo networks with hierarchical architecture

    Science.gov (United States)

    Plotnikov, S. A.; Lehnert, J.; Fradkov, A. L.; Schöll, E.

    2016-07-01

    We study synchronization in heterogeneous FitzHugh-Nagumo networks. It is well known that heterogeneities in the nodes hinder synchronization when becoming too large. Here we develop a controller to counteract the impact of these heterogeneities. We first analyze the stability of the equilibrium point in a ring network of heterogeneous nodes. We then derive a sufficient condition for synchronization in the absence of control. Based on these results we derive the controller providing synchronization for parameter values where synchronization without control is absent. We demonstrate our results in networks with different topologies. Particular attention is given to hierarchical (fractal) topologies, which are relevant for the architecture of the brain.

  3. Hierarchical micro-mobility management in high-speed multihop access networks

    Institute of Scientific and Technical Information of China (English)

    TANG Bi-hua; MA Xiao-lei; LIU Yuan-an; GAO Jin-chun

    2006-01-01

    This article integrates the hierarchical micro-mobility management and the high-speed multihop access networks (HMAN), to accomplish the smooth handover between different access routers. The proposed soft handover scheme in the high-speed HMAN can solve the micro-mobility management problem in the access network. This article also proposes the hybrid access router (AR) advertisement scheme and AR selection algorithm, which uses the time delay and stable route to the AR as the gateway selection parameters. By simulation, the proposed micro-mobility management scheme can achieve high packet delivery fraction and improve the lifetime of network.

  4. Topology of the correlation networks among major currencies using hierarchical structure methods

    Science.gov (United States)

    Keskin, Mustafa; Deviren, Bayram; Kocakaplan, Yusuf

    2011-02-01

    We studied the topology of correlation networks among 34 major currencies using the concept of a minimal spanning tree and hierarchical tree for the full years of 2007-2008 when major economic turbulence occurred. We used the USD (US Dollar) and the TL (Turkish Lira) as numeraires in which the USD was the major currency and the TL was the minor currency. We derived a hierarchical organization and constructed minimal spanning trees (MSTs) and hierarchical trees (HTs) for the full years of 2007, 2008 and for the 2007-2008 period. We performed a technique to associate a value of reliability to the links of MSTs and HTs by using bootstrap replicas of data. We also used the average linkage cluster analysis for obtaining the hierarchical trees in the case of the TL as the numeraire. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial data. We illustrated how the minimal spanning trees and their related hierarchical trees developed over a period of time. From these trees we identified different clusters of currencies according to their proximity and economic ties. The clustered structure of the currencies and the key currency in each cluster were obtained and we found that the clusters matched nicely with the geographical regions of corresponding countries in the world such as Asia or Europe. As expected the key currencies were generally those showing major economic activity.

  5. Mapping the hierarchical layout of the structural network of the macaque prefrontal cortex.

    Science.gov (United States)

    Goulas, Alexandros; Uylings, Harry B M; Stiers, Peter

    2014-05-01

    A consensus on the prefrontal cortex (PFC) holds that it is pivotal for flexible behavior and the integration of the cognitive, affective, and motivational domains. Certain models have been put forth and a dominant model postulates a hierarchical anterior-posterior gradient. The structural connectivity principles of this model dictate that increasingly anterior PFC regions exhibit more efferent connections toward posterior ones than vice versa. Such hierarchical asymmetry principles are thought to pertain to the macaque PFC. Additionally, the laminar patterns of the connectivity of PFC regions can be used for defining hierarchies. In the current study, we formally tested the asymmetry-based hierarchical principles of the anterior-posterior model by employing an exhaustive dataset on macaque PFC connectivity and tools from network science. On the one hand, the asymmetry-based principles and predictions of the hierarchical anterior-posterior model were not confirmed. The wiring of the macaque PFC does not fully correspond to the principles of the model, and its asymmetry-based hierarchical layout does not follow a strict anterior-posterior gradient. On the other hand, our results suggest that the laminar-based hierarchy seems a more tenable working hypothesis for models advocating an anterior-posterior gradient. Our results can inform models of the human PFC.

  6. Sleeping of a Complex Brain Networks with Hierarchical Organization

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ying-Yue; YANG Qiu-Ying; CHEN Tian-Lun

    2009-01-01

    The dynamical behavior in the cortical brain network of macaque is studied by modeling each cortical area with a subnetwork of interacting excitable neurons. We characterize the system by studying how to perform the transition, which is now topology-dependent, from the active state to that with no activity. This could be a naive model for the wakening and sleeping of a brain-like system, i.e., a multi-component system with two different dynamical behavior.

  7. Hierarchical brain networks active in approach and avoidance goal pursuit

    Directory of Open Access Journals (Sweden)

    Jeffrey Martin Spielberg

    2013-06-01

    Full Text Available Effective approach/avoidance goal pursuit is critical for attaining long-term health and well-being. Research on the neural correlates of key goal pursuit processes (e.g., motivation has long been of interest, with lateralization in prefrontal cortex being a particularly fruitful target of investigation. However, this literature has often been limited by a lack of spatial specificity and has not delineated the precise aspects of approach/avoidance motivation involved. Additionally, the relationships among brain regions (i.e., network connectivity vital to goal pursuit remain largely unexplored. Specificity in location, process, and network relationship is vital for moving beyond gross characterizations of function and identifying the precise cortical mechanisms involved in motivation. The present paper integrates research using more spatially specific methodologies (e.g., functional magnetic resonance imaging with the rich psychological literature on approach/avoidance to propose an integrative network model that takes advantage of the strengths of each of these literatures.

  8. HIERARCHICAL DESIGN BASED INTRUSION DETECTION SYSTEM FOR WIRELESS AD HOC SENSOR NETWORK

    Directory of Open Access Journals (Sweden)

    Mohammad Saiful Islam Mamun

    2010-07-01

    Full Text Available In recent years, wireless ad hoc sensor network becomes popular both in civil and military jobs.However, security is one of the significant challenges for sensor network because of their deploymentin open and unprotected environment. As cryptographic mechanism is not enough to protect sensornetwork from external attacks, intrusion detection system needs to be introduced. Though intrusionprevention mechanism is one of the major and efficient methods against attacks, but there might besome attacks for which prevention method is not known. Besides preventing the system from someknown attacks, intrusion detection system gather necessary information related to attack technique andhelp in the development of intrusion prevention system. In addition to reviewing the present attacksavailable in wireless sensor network this paper examines the current efforts to intrusion detectionsystem against wireless sensor network. In this paper we propose a hierarchical architectural designbased intrusion detection system that fits the current demands and restrictions of wireless ad hocsensor network. In this proposed intrusion detection system architecture we followed clusteringmechanism to build a four level hierarchical network which enhances network scalability to largegeographical area and use both anomaly and misuse detection techniques for intrusion detection. Weintroduce policy based detection mechanism as well as intrusion response together with GSM cellconcept for intrusion detection architecture.

  9. Predicting Hierarchical Structure in Small World Social Networks

    DEFF Research Database (Denmark)

    Hussain, Dil Muhammad Akbar

    2009-01-01

    Typisk analytisk foranstaltninger i grafteori gerne grad centralitet, betweenness og nærhed centralities er meget almindelige og har lang tradition for deres vellykkede brug. Men modellering af skjult, terrorister eller kriminelle netværk gennem sociale grafer ikke rigtig give den hierarkiske str...... udnyttet til at forudsige den kommandostruktur af nettet. Nøgleord: Social Networks Analyse, Bayes Teorem, entropi, hierarkisk struktur.......Typisk analytisk foranstaltninger i grafteori gerne grad centralitet, betweenness og nærhed centralities er meget almindelige og har lang tradition for deres vellykkede brug. Men modellering af skjult, terrorister eller kriminelle netværk gennem sociale grafer ikke rigtig give den hierarkiske...

  10. Natural forest conservation hierarchical program with neural network

    Institute of Scientific and Technical Information of China (English)

    LUO Chuanwen; LI Jihong

    2006-01-01

    In this paper,the implementing steps of a natural forest protection program grading (NFPPG) with neural network (NN) were summarized and the concepts of program illustration,patch sign unification and regression,and inclining factor were set forth.Employing Arc/Info GIS,the tree species diversity and rarity,disturbance degree,protection of channel system,and classification management in the Maoershan National Forest Park were described,and used as the input factors of NN.The relationships between NFPPG and above factors were also analyzed.By artificially determining training samples,the NFPPG of Moershan National Forest Park was created.Tested with all patches in the park,the generalization of NFPPG was satisfied.NFPPG took both the classification management and the protection of forest community types into account,as well as the ecological environment.The excitation function of NFPPG was not seriously saturated,indicating the leading effect of the inclining factor on the network optimization.

  11. NHRPA: a novel hierarchical routing protocol algorithm for wireless sensor networks

    Institute of Scientific and Technical Information of China (English)

    CHENG Hong-bing; YANG Geng; HU Su-jun

    2008-01-01

    Considering severe resources constraints and security threat of wireless sensor networks (WSN), the article proposed a novel hierarchical routing protocol algorithm. The proposed routing protocol algorithm can adopt suitable routing technology for the nodes according to the distance of nodes to the base station, density of nodes distribution, and residual energy of nodes. Comparing the proposed routing protocol algorithm with simple direction diffusion routing technology, cluster-based routing mechanisms, and simple hierarchical routing protocol algorithm through comprehensive analysis and simulation in terms of the energy usage, packet latency, and security in the presence of node compromise attacks, the results show that the proposed routing protocol algorithm is more efficient for wireless sensor networks.

  12. Identifying Overlapping and Hierarchical Thematic Structures in Networks of Scholarly Papers: A Comparison of Three Approaches

    CERN Document Server

    Havemann, Frank; Heinz, Michael; Struck, Alexander

    2011-01-01

    We implemented three recently proposed approaches to the identification of overlapping and hierarchical substructures in graphs and applied the corresponding algorithms to a network of 492 information-science papers coupled via their cited sources. The thematic substructures obtained and overlaps produced by the three hierarchical cluster algorithms were compared to a content-based categorisation, which we based on the interpretation of titles and keywords. We defined sets of papers dealing with three topics located on different levels of aggregation: h-index, webometrics, and bibliometrics. We identified these topics with branches in the dendrograms produced by the three cluster algorithms and compared the overlapping topics they detected with one another and with the three pre-defined paper sets. We discuss the advantages and drawbacks of applying the three approaches to paper networks in research fields.

  13. Systemic risk and hierarchical transitions of financial networks

    Science.gov (United States)

    Nobi, Ashadun; Lee, Jae Woo

    2017-06-01

    In this paper, the change in topological hierarchy, which is measured by the minimum spanning tree constructed from the cross-correlations between the stock indices from the S & P 500 for 1998-2012 in a one year moving time window, was used to analyze a financial crisis. The hierarchy increased in all minor crises in the observation time window except for the sharp crisis of 2007-2008 when the global financial crisis occurred. The sudden increase in hierarchy just before the global financial crisis can be used for the early detection of an upcoming crisis. Clearly, the higher the hierarchy, the higher the threats to financial stability. The scaling relations were developed to observe the changes in hierarchy with the network topology. These scaling relations can also identify and quantify the financial crisis periods, and appear to contain the predictive power of an upcoming crisis.

  14. Communication Theories and Protocols for Smart Grid Hierarchical Network

    Directory of Open Access Journals (Sweden)

    CHHAYA Lipi

    2017-05-01

    Full Text Available Smart grid technology is a revolutionary approach for improvisation in existing power grid. Integration of electrical and communication infrastructure is inevitable for the deployment of Smart grid network. Smart grid infrastructure is characterized by full duplex communication, automatic metering infrastructure, renewable energy integration, distribution automation and complete monitoring and control of entire power grid. Different levels of smart grid deployment require diverse set of communication protocols. Application of information theory and optimization of various communication technologies is essential for layered architecture of smart grid technology. This paper is anticipated to serve as a comprehensive survey and analysis of communication theories and wireless communication protocols for optimization and design of energy efficient smart grid communication infrastructure.

  15. Sensor Network Data Fault Detection using Hierarchical Bayesian Space-Time Modeling

    OpenAIRE

    Ni, Kevin; Pottie, G J

    2009-01-01

    We present a new application of hierarchical Bayesian space-time (HBST) modeling: data fault detection in sensor networks primarily used in environmental monitoring situations. To show the effectiveness of HBST modeling, we develop a rudimentary tagging system to mark data that does not fit with given models. Using this, we compare HBST modeling against first order linear autoregressive (AR) modeling, which is a commonly used alternative due to its simplicity. We show that while HBST is mo...

  16. An energy efficient cooperative hierarchical MIMO clustering scheme for wireless sensor networks.

    Science.gov (United States)

    Nasim, Mehwish; Qaisar, Saad; Lee, Sungyoung

    2012-01-01

    In this work, we present an energy efficient hierarchical cooperative clustering scheme for wireless sensor networks. Communication cost is a crucial factor in depleting the energy of sensor nodes. In the proposed scheme, nodes cooperate to form clusters at each level of network hierarchy ensuring maximal coverage and minimal energy expenditure with relatively uniform distribution of load within the network. Performance is enhanced by cooperative multiple-input multiple-output (MIMO) communication ensuring energy efficiency for WSN deployments over large geographical areas. We test our scheme using TOSSIM and compare the proposed scheme with cooperative multiple-input multiple-output (CMIMO) clustering scheme and traditional multihop Single-Input-Single-Output (SISO) routing approach. Performance is evaluated on the basis of number of clusters, number of hops, energy consumption and network lifetime. Experimental results show significant energy conservation and increase in network lifetime as compared to existing schemes.

  17. A hierarchical P2P overlay network for interest-based media contents lookup

    Science.gov (United States)

    Lee, HyunRyong; Kim, JongWon

    2006-10-01

    We propose a P2P (peer-to-peer) overlay architecture, called IGN (interest grouping network), for contents lookup in the DHC (digital home community), which aims to provide a formalized home-network-extended construction of current P2P file sharing community. The IGN utilizes the Chord and de Bruijn graph for its hierarchical overlay network construction. By combining two schemes and by inheriting its features, the IGN efficiently supports contents lookup. More specifically, by introducing metadata-based lookup keyword, the IGN offers detailed contents lookup that can reflect the user interests. Moreover, the IGN tries to reflect home network environments of DHC by utilizing HG (home gateway) of each home network as a participating node of the IGN. Through experimental and analysis results, we show that the IGN is more efficient than Chord, a well-known DHT (distributed hash table)-based lookup protocol.

  18. A new Hierarchical Group Key Management based on Clustering Scheme for Mobile Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Ayman EL-SAYED

    2014-05-01

    Full Text Available The migration from wired network to wireless network has been a global trend in the past few decades because they provide anytime-anywhere networking services. The wireless networks are rapidly deployed in the future, secure wireless environment will be mandatory. As well, The mobility and scalability brought by wireless network made it possible in many applications. Among all the contemporary wireless networks,Mobile Ad hoc Networks (MANET is one of the most important and unique applications. MANET is a collection of autonomous nodes or terminals which communicate with each other by forming a multihop radio network and maintaining connectivity in a decentralized manner. Due to the nature of unreliable wireless medium data transfer is a major problem in MANET and it lacks security and reliability of data. The most suitable solution to provide the expected level of security to these services is the provision of a key management protocol. A Key management is vital part of security. This issue is even bigger in wireless network compared to wired network. The distribution of keys in an authenticated manner is a difficult task in MANET. When a member leaves or joins the group, it needs to generate a new key to maintain forward and backward secrecy. In this paper, we propose a new group key management schemes namely a Hierarchical, Simple, Efficient and Scalable Group Key (HSESGK based on clustering management scheme for MANETs and different other schemes are classified. Group members deduce the group key in a distributed manner.

  19. Hierarchically Coordinated Power Management for Target Tracking in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Feng Juan

    2013-10-01

    Full Text Available Energy efficiency is very important for wireless sensor networks (WSNs since sensor nodes have a limited energy supply from a battery. So far, a lot research has focused on this issue, while less emphasis has been placed on the adaptive sleep time for each node with a consideration for the application constraints. In this paper, we propose a hierarchically coordinated power management (HCPM approach, which both addresses the energy conservation problem and reduces the packet forwarding delay for target tracking WSNs based on a virtual‐grid‐based network structure. We extend the network lifetime by adopting an adaptive sleep scheduling scheme that combines the local power management (PM and the adaptive coordinate PM strategies to schedule the activities of the sensor nodes at the surveillance stage. Furthermore, we propose a hierarchical structure for the tracking stage. Experimental results show that the proposed approach has a greater capability of extending the network lifetime while maintaining a short transmission delay when compared with the protocol which does not consider the application constraints in target tracking sensor networks.

  20. Hierarchical differentiation of myeloid progenitors is encoded in the transcription factor network.

    Science.gov (United States)

    Krumsiek, Jan; Marr, Carsten; Schroeder, Timm; Theis, Fabian J

    2011-01-01

    Hematopoiesis is an ideal model system for stem cell biology with advanced experimental access. A systems view on the interactions of core transcription factors is important for understanding differentiation mechanisms and dynamics. In this manuscript, we construct a Boolean network to model myeloid differentiation, specifically from common myeloid progenitors to megakaryocytes, erythrocytes, granulocytes and monocytes. By interpreting the hematopoietic literature and translating experimental evidence into Boolean rules, we implement binary dynamics on the resulting 11-factor regulatory network. Our network contains interesting functional modules and a concatenation of mutual antagonistic pairs. The state space of our model is a hierarchical, acyclic graph, typifying the principles of myeloid differentiation. We observe excellent agreement between the steady states of our model and microarray expression profiles of two different studies. Moreover, perturbations of the network topology correctly reproduce reported knockout phenotypes in silico. We predict previously uncharacterized regulatory interactions and alterations of the differentiation process, and line out reprogramming strategies.

  1. Spectral dimensions of hierarchical scale-free networks with weighted shortcuts

    Science.gov (United States)

    Hwang, S.; Yun, C.-K.; Lee, D.-S.; Kahng, B.; Kim, D.

    2010-11-01

    Spectral dimensions have been widely used to understand transport properties on regular and fractal lattices. However, they have received little attention with regard to complex networks such as scale-free and small-world networks. Here, we study the spectral dimension and the return-to-origin probability of random walks on hierarchical scale-free networks, which can be either fractal or nonfractal depending on the weight of the shortcuts. Applying the renormalization-group (RG) approach to a Gaussian model, we obtain the exact spectral dimension. While the spectral dimension varies between 1 and 2 for the fractal case, it remains at 2, independent of the variation in the network structure, for the nonfractal case. The crossover behavior between the two cases is studied by carrying out the RG flow analysis. The analytical results are confirmed by simulation results and their implications for the architecture of complex systems are discussed.

  2. Hierarchical Location Service with Prediction in Mobile Ad-Hoc Networks

    CERN Document Server

    Amar, Ebtisam; Renault, Éric; 10.5121/ijcnc.2010.2204

    2010-01-01

    Position-based routing protocols take advantage of location information to perform a stateless and efficient routing. To enable position-based routing, a node must be able to discover the location of the messages' destination node. This task is typically accomplished by a location service. Recently, several location service protocols have been developed for ad hoc networks. In this paper we propose a novel location service called PHLS: Predictive Hierarchical Location Service. In PHLS, the entire network is partitioned into a hierarchy of smaller and smaller regions. For each node, one node in each-level region of the hierarchy is chosen as its local location server. When the network initializes or when a node attaches the network, nodes contact their local location server with their current location information (ie. position and velocity). Then, they only need to update their location server when they move away from their current region. Finally, nodes query their location servers and get the exact or predic...

  3. TWO-LEVEL HIERARCHICAL COORDINATION QUEUING METHOD FOR TELECOMMUNICATION NETWORK NODES

    Directory of Open Access Journals (Sweden)

    M. V. Semenyaka

    2014-07-01

    Full Text Available The paper presents hierarchical coordination queuing method. Within the proposed method a queuing problem has been reduced to optimization problem solving that was presented as two-level hierarchical structure. The required distribution of flows and bandwidth allocation was calculated at the first level independently for each macro-queue; at the second level solutions obtained on lower level for each queue were coordinated in order to prevent probable network link overload. The method of goal coordination has been determined for multilevel structure managing, which makes it possible to define the order for consideration of queue cooperation restrictions and calculation tasks distribution between levels of hierarchy. Decisions coordination was performed by the method of Lagrange multipliers. The study of method convergence has been carried out by analytical modeling.

  4. Secure Session Mobility using Hierarchical Authentication Key Management in Next Generation Networks

    Directory of Open Access Journals (Sweden)

    Muhammad Zubair

    2014-05-01

    Full Text Available In this paper we propose a novel authentication mechanism for session mobility in Next Generation Networks named as Hierarchical Authentication Key Management (HAKM. The design objectives of HAKM are twofold: i to minimize the authentication latency in NGNs; ii to provide protection against an assortment of attacks such as denial-of-service attacks, man-in-the-middle attacks, guessing attacks, and capturing node attacks. In order to achieve these objectives, we combine Session Initiation Protocol (SIP with Hierarchical Mobile IPv6 (HMIPv6 to perform local authentication for session mobility. The concept of group keys and pairwise keys with one way hash function is employed to make HAKM vigorous against the aforesaid attacks. The performance analysis and numerical results demonstrate that HAKM outperforms the existing approaches in terms of latency and protection against the abovementioned attacks

  5. A Hybrid P2P Overlay Network for Non-strictly Hierarchically Categorized Content

    Science.gov (United States)

    Wan, Yi; Asaka, Takuya; Takahashi, Tatsuro

    In P2P content distribution systems, there are many cases in which the content can be classified into hierarchically organized categories. In this paper, we propose a hybrid overlay network design suitable for such content called Pastry/NSHCC (Pastry for Non-Strictly Hierarchically Categorized Content). The semantic information of classification hierarchies of the content can be utilized regardless of whether they are in a strict tree structure or not. By doing so, the search scope can be restrained to any granularity, and the number of query messages also decreases while maintaining keyword searching availability. Through simulation, we showed that the proposed method provides better performance and lower overhead than unstructured overlays exploiting the same semantic information.

  6. A Hierarchical Energy Efficient Reliable Transport Protocol for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Prabhudutta Mohanty

    2014-12-01

    Full Text Available The two important requirements for many Wireless Senor Networks (WSNs are prolonged network lifetime and end-to-end reliability. The sensor nodes consume more energy during data transmission than the data sensing. In WSN, the redundant data increase the energy consumption, latency and reduce reliability during data transmission. Therefore, it is important to support energy efficient reliable data transport in WSNs. In this paper, we present a Hierarchical Energy Efficient Reliable Transport Protocol (HEERTP for the data transmission within the WSN. This protocol maximises the network lifetime by controlling the redundant data transmission with the co-ordination of Base Station (BS. The proposed protocol also achieves end-to-end reliability using a hop-by-hop acknowledgement scheme. We evaluate the performance of the proposed protocol through simulation. The simulation results reveal that our proposed protocol achieves better performance in terms of energy efficiency, latency and reliability than the existing protocols.

  7. A Hierarchical Approach to Real-time Activity Recognition in Body Sensor Networks

    DEFF Research Database (Denmark)

    Wang, Liang; Gu, Tao; Tao, Xianping

    2012-01-01

    algorithm to detect gestures at the sensor node level, and then propose a pattern based real-time algorithm to recognize complex, high-level activities at the portable device level. We evaluate our algorithms over a real-world dataset. The results show that the proposed system not only achieves good......Real-time activity recognition in body sensor networks is an important and challenging task. In this paper, we propose a real-time, hierarchical model to recognize both simple gestures and complex activities using a wireless body sensor network. In this model, we rst use a fast and lightweight...... performance (an average utility of 0.81, an average accuracy of 82.87%, and an average real-time delay of 5.7 seconds), but also signicantly reduces the network communication cost by 60.2%....

  8. Toughening mystery of natural rubber deciphered by double network incorporating hierarchical structures.

    Science.gov (United States)

    Zhou, Weiming; Li, Xiangyang; Lu, Jie; Huang, Ningdong; Chen, Liang; Qi, Zeming; Li, Liangbin; Liang, Haiyi

    2014-12-16

    As an indispensible material for modern society, natural rubber possesses peerless mechanical properties such as strength and toughness over its artificial analogues, which remains a mystery. Intensive experimental and theoretical investigations have revealed the self-enhancement of natural rubber due to strain-induced crystallization. However a rigorous model on the self-enhancement, elucidating natural rubber's extraordinary mechanical properties, is obscured by deficient understanding of the local hierarchical structure under strain. With spatially resolved synchrotron radiation micro-beam scanning X-ray diffraction we discover weak oscillation in distributions of strain-induced crystallinity around crack tip for stretched natural rubber film, demonstrating a soft-hard double network structure. The fracture energy enhancement factor obtained by utilizing the double network model indicates an enhancement of toughness by 3 orders. It's proposed that upon stretching spontaneously developed double network structures integrating hierarchy at multi length-scale in natural rubber play an essential role in its remarkable mechanical performance.

  9. Decentralized Cooperative TOA/AOA Target Tracking for Hierarchical Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chih-Yu Wen

    2012-11-01

    Full Text Available This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processingis conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are applied to adaptively select a sub-cluster for thelocalization task. The proposed energy-efficient tracking algorithm allows each sub-clustermember to locally estimate the target position with a Bayesian filtering framework and a neural networking model, and further performs estimation fusion in the leader node with the covariance intersection algorithm. This paper evaluates the merits and trade-offs of the protocol design towards developing more efficient and practical algorithms for objectposition estimation. 

  10. Decentralized cooperative TOA/AOA target tracking for hierarchical wireless sensor networks.

    Science.gov (United States)

    Chen, Ying-Chih; Wen, Chih-Yu

    2012-11-08

    This paper proposes a distributed method for cooperative target tracking in hierarchical wireless sensor networks. The concept of leader-based information processing is conducted to achieve object positioning, considering a cluster-based network topology. Random timers and local information are applied to adaptively select a sub-cluster for the localization task. The proposed energy-efficient tracking algorithm allows each sub-cluster member to locally estimate the target position with a Bayesian filtering framework and a neural networking model, and further performs estimation fusion in the leader node with the covariance intersection algorithm. This paper evaluates the merits and trade-offs of the protocol design towards developing more efficient and practical algorithms for object position estimation.

  11. Structure function relationship in complex brain networks expressed by hierarchical synchronization

    Science.gov (United States)

    Zhou, Changsong; Zemanová, Lucia; Zamora-López, Gorka; Hilgetag, Claus C.; Kurths, Jürgen

    2007-06-01

    The brain is one of the most complex systems in nature, with a structured complex connectivity. Recently, large-scale corticocortical connectivities, both structural and functional, have received a great deal of research attention, especially using the approach of complex network analysis. Understanding the relationship between structural and functional connectivity is of crucial importance in neuroscience. Here we try to illuminate this relationship by studying synchronization dynamics in a realistic anatomical network of cat cortical connectivity. We model the nodes (cortical areas) by a neural mass model (population model) or by a subnetwork of interacting excitable neurons (multilevel model). We show that if the dynamics is characterized by well-defined oscillations (neural mass model and subnetworks with strong couplings), the synchronization patterns are mainly determined by the node intensity (total input strengths of a node) and the detailed network topology is rather irrelevant. On the other hand, the multilevel model with weak couplings displays more irregular, biologically plausible dynamics, and the synchronization patterns reveal a hierarchical cluster organization in the network structure. The relationship between structural and functional connectivity at different levels of synchronization is explored. Thus, the study of synchronization in a multilevel complex network model of cortex can provide insights into the relationship between network topology and functional organization of complex brain networks.

  12. Hierarchical neural network model of the visual system determining figure/ground relation

    Science.gov (United States)

    Kikuchi, Masayuki

    2017-07-01

    One of the most important functions of the visual perception in the brain is figure/ground interpretation from input images. Figural region in 2D image corresponding to object in 3D space are distinguished from background region extended behind the object. Previously the author proposed a neural network model of figure/ground separation constructed on the standpoint that local geometric features such as curvatures and outer angles at corners are extracted and propagated along input contour in a single layer network (Kikuchi & Akashi, 2001). However, such a processing principle has the defect that signal propagation requires manyiterations despite the fact that actual visual system determines figure/ground relation within the short period (Zhou et al., 2000). In order to attain speed-up for determining figure/ground, this study incorporates hierarchical architecture into the previous model. This study confirmed the effect of the hierarchization as for the computation time by simulation. As the number of layers increased, the required computation time reduced. However, such speed-up effect was saturatedas the layers increased to some extent. This study attempted to explain this saturation effect by the notion of average distance between vertices in the area of complex network, and succeeded to mimic the saturation effect by computer simulation.

  13. A blind hierarchical coherent search for gravitational-wave signals from coalescing compact binaries in a network of interferometric detectors

    Energy Technology Data Exchange (ETDEWEB)

    Bose, Sukanta; Dayanga, Thilina; Ghosh, Shaon; Talukder, Dipongkar, E-mail: sukanta@wsu.edu, E-mail: wdayanga@wsu.edu, E-mail: shaonghosh@mail.wsu.edu, E-mail: talukder_d@wsu.edu [Department of Physics and Astronomy, Washington State University, 1245 Webster, Pullman, WA 99164-2814 (United States)

    2011-07-07

    We describe a hierarchical data analysis pipeline for coherently searching for gravitational-wave signals from non-spinning compact binary coalescences (CBCs) in the data of multiple earth-based detectors. This search assumes no prior information on the sky position of the source or the time of occurrence of its transient signals and, hence, is termed 'blind'. The pipeline computes the coherent network search statistic that is optimal in stationary, Gaussian noise. More importantly, it allows for the computation of a suite of alternative multi-detector coherent search statistics and signal-based discriminators that can improve the performance of CBC searches in real data, which can be both non-stationary and non-Gaussian. Also, unlike the coincident multi-detector search statistics that have been employed so far, the coherent statistics are different in the sense that they check for the consistency of the signal amplitudes and phases in the different detectors with their different orientations and with the signal arrival times in them. Since the computation of coherent statistics entails searching in the sky, it is more expensive than that of the coincident statistics that do not require it. To reduce computational costs, the first stage of the hierarchical pipeline constructs coincidences of triggers from the multiple interferometers, by requiring their proximity in time and component masses. The second stage follows up on these coincident triggers by computing the coherent statistics. Here, we compare the performances of this hierarchical pipeline with and without the second (or coherent) stage in Gaussian noise. Although introducing hierarchy can be expected to cause some degradation in the detection efficiency compared to that of a single-stage coherent pipeline, nevertheless it improves the computational speed of the search considerably. The two main results of this work are as follows: (1) the performance of the hierarchical coherent pipeline on

  14. Hierarchical self-assembly of a striped gyroid formed by threaded chiral mesoscale networks

    DEFF Research Database (Denmark)

    Kirkensgaard, Jacob Judas Kain; Evans, Myfanwy; de Campo, Lilliana;

    2014-01-01

    the gyroid film are densely packed and contain either graphitic hcb nets (chicken wire) or srs nets, forming convoluted intergrowths of multiple nets. Furthermore, each net is ideally a single chiral enantiomer, induced by the gyroid architecture. However, the numerical simulations result in defect......Numerical simulations reveal a family of hierarchical and chiral multicontinuous network structures self-assembled from a melt blend of Y-shaped ABC and ABD three-miktoarm star terpolymers, constrained to have equal-sized A/B and C/D chains, respectively. The C and D majority domains within...

  15. A hierarchical virtual backbone construction protocol for mobile ad hoc networks

    Directory of Open Access Journals (Sweden)

    Bharti Sharma

    2016-07-01

    Full Text Available We propose a hierarchical backbone construction protocol for mobile ad hoc networks. Our protocol is based on the idea of using an efficient extrema finding method to create clusters comprising the nodes that are within certain prespecified wireless hop distance. Afterward, we apply our ‘diameter’ algorithm among clusters to identify the dominating nodes that are, finally, connected via multi-hop virtual links to construct the backbone. We present the analytic as well as simulation study of our algorithm and also a method for the dynamic maintenance of constructed backbone. In the end, we illustrate the use of the virtual backbone with the help of an interesting application.

  16. On Hierarchical Extensions of Large-Scale 4-regular Grid Network Structures

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Patel, A.; Knudsen, Thomas Phillip

    It is studied how the introduction of ordered hierarchies in 4-regular grid network structures decreses distances remarkably, while at the same time allowing for simple topological routing schemes. Both meshes and tori are considered; in both cases non-hierarchical structures have power law......, and it is shown that while they allow for more flexibility in design and construction of structures supporting topological routing, their performances are comparable to the performance of the perfect square mesh. Finally suggestions for further research within the field are given....

  17. On Hierarchical Extensions of Large-Scale 4-regular Grid Network Structures

    DEFF Research Database (Denmark)

    Pedersen, Jens Myrup; Patel, A.; Knudsen, Thomas Phillip

    2004-01-01

    It is studied how the introduction of ordered hierarchies in 4-regular grid network structures decreases distances remarkably, while at the same time allowing for simple topological routing schemes. Both meshes and tori are considered; in both cases non-hierarchical structures have power law......, and it is shown that while they allow for more flexibility in design and construction of structures supporting topological routing, their performances are comparable to the performance of the perfect square mesh. Finally suggestions for further research within the field are given....

  18. Hierarchical Self-healing Key Distribution for Heterogeneous Wireless Sensor Networks

    Science.gov (United States)

    Yang, Yanjiang; Zhou, Jianying; Deng, Robert H.; Bao, Feng

    Self-healing group key distribution aims to achieve robust key distribution over lossy channels in wireless sensor networks (WSNs). However, all existing self-healing group key distribution schemes in the literature consider homogenous WSNs which are known to be unscalable. Heterogeneous WSNs have better scalability and performance than homogenous ones. We are thus motivated to study hierarchial self-healing group key distribution, tailored to the heterogeneous WSN architecture. In particular, we revisit and adapt Dutta et al.’s model to the setting of hierarchical self-healing group key distribution, and propose a concrete scheme that achieves computational security and high efficiency.

  19. Hierarchical organization of functional connectivity in the mouse brain: a complex network approach

    Science.gov (United States)

    Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano

    2016-08-01

    This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.

  20. Evaluating the Performance of Fast Handover for Hierarchical MIPv6 in Cellular Networks

    Directory of Open Access Journals (Sweden)

    Li Jun Zhang

    2008-06-01

    Full Text Available Next-Generation Wireless Networks (NGWNs present an all-IP-based architecture integrating existing cellular networks with Wireless Local Area Networks (WLANs, Wireless Metropolitan Area Networks (WMANs, ad hoc networks, Bluetooth, etc. This makes mobility management an important issue for users roaming among these networks/systems. On one hand, intelligent schemes need to be devised to empower mobile users to benefit from the IP-based technology. On the other hand, new solutions are required to take into account global roaming among various radio access technologies and support of real-time multimedia services. This paper presents a comprehensive performance analysis of Fast handover for Hierarchical Mobile IPv6 (F-HMIPv6 using the fluid-flow and randomwalk mobility models. Location update cost, packet delivery cost and total cost functions are formulated based on the proposed analytical models. We investigate the impact of several wireless system factors such as user velocity, user density, mobility domain size, session-to-mobility ratio on these costs, and present some numerical results.

  1. Mobile Agent Based Hierarchical Intrusion Detection System in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Surraya Khanum

    2012-01-01

    Full Text Available Security mechanism is a fundamental requirement of wireless networks in general and Wireless Sensor Networks (WSN in particular. Therefore, it is necessary that this security concern must be articulate right from the beginning of the network design and deployment. WSN needs strong security mechanism as it is usually deployed in a critical, hostile and sensitive environment where human labour is usually not involved. However, due to inbuilt resource and computing restriction, security in WSN needs a special consideration. Traditional security techniques such as encryption, VPN, authentication and firewalls cannot be directly applied to WSN as it provides defence only against external threats. The existing literature shows that there seems an inverse relationship between strong security mechanism and efficient network resource utilization. In this research article, we have proposed a Mobile Agent Based Hierarchical Intrusion Detection System (MABHIDS for WSN. The Proposed scheme performs two levels of intrusion detection by utilizing minimum possible network resources. Our proposed idea enhance network lifetime by reducing the work load on Cluster Head (CH and it also provide enhanced level of security in WSN.

  2. Hierarchical Supervisor and Agent Routing Algorithm in LEO/MEO Double-layered Optical Satellite Network

    Science.gov (United States)

    Li, Yongjun; Zhao, Shanghong

    2016-09-01

    A novel routing algorithm (Hierarchical Supervisor and Agent Routing Algorithm, HSARA) for LEO/MEO (low earth orbit/medium earth orbit) double-layered optical satellite network is brought forward. The so-called supervisor (MEO satellite) is designed for failure recovery and network management. LEO satellites are grouped according to the virtual managed field of MEO which is different from coverage area of MEO satellite in RF satellite network. In each LEO group, one LEO satellite which has maximal persistent link with its supervisor is called the agent. A LEO group is updated when this optical inter-orbit links between agent LEO satellite and the corresponding MEO satellite supervisor cuts off. In this way, computations of topology changes and LEO group updating can be decreased. Expense of routing is integration of delay and wavelength utilization. HSARA algorithm simulations are implemented and the results are as follows: average network delay of HSARA can reduce 21 ms and 31.2 ms compared with traditional multilayered satellite routing and single-layer LEO satellite respectively; LEO/MEO double-layered optical satellite network can cover polar region which cannot be covered by single-layered LEO satellite and throughput is 1% more than that of single-layered LEO satellite averagely. Therefore, exact global coverage can be achieved with this double-layered optical satellite network.

  3. Hierarchical alteration of brain structural and functional networks in female migraine sufferers.

    Directory of Open Access Journals (Sweden)

    Jixin Liu

    Full Text Available BACKGROUND: Little is known about the changes of brain structural and functional connectivity networks underlying the pathophysiology in migraine. We aimed to investigate how the cortical network reorganization is altered by frequent cortical overstimulation associated with migraine. METHODOLOGY/PRINCIPAL FINDINGS: Gray matter volumes and resting-state functional magnetic resonance imaging signal correlations were employed to construct structural and functional networks between brain regions in 43 female patients with migraine (PM and 43 gender-matched healthy controls (HC by using graph theory-based approaches. Compared with the HC group, the patients showed abnormal global topology in both structural and functional networks, characterized by higher mean clustering coefficients without significant change in the shortest absolute path length, which indicated that the PM lost optimal topological organization in their cortical networks. Brain hubs related to pain-processing revealed abnormal nodal centrality in both structural and functional networks, including the precentral gyrus, orbital part of the inferior frontal gyrus, parahippocampal gyrus, anterior cingulate gyrus, thalamus, temporal pole of the middle temporal gyrus and the inferior parietal gyrus. Negative correlations were found between migraine duration and regions with abnormal centrality. Furthermore, the dysfunctional connections in patients' cortical networks formed into a connected component and three dysregulated modules were identified involving pain-related information processing and motion-processing visual networks. CONCLUSIONS: Our results may reflect brain alteration dynamics resulting from migraine and suggest that long-term and high-frequency headache attacks may cause both structural and functional connectivity network reorganization. The disrupted information exchange between brain areas in migraine may be reshaped into a hierarchical modular structure progressively.

  4. Analysis of Hierarchical Diff-EDF Schedulability over Heterogeneous Real-Time Packet Networks

    Directory of Open Access Journals (Sweden)

    M. Saleh

    2007-01-01

    Full Text Available Packet networks are currently enabling the integration of traffic with a wide range of characteristics that extend from video traffic with stringent QoS requirements to the best-effort traffic requiring no guarantees. QoS guarantees can be provided in conventional packet networks by the use of proper packet scheduling algorithms. As a computer revolution, many scheduling algorithms have been proposed to provide different schemes of QoS guarantees with Earliest Deadline First (EDF as the most popular one. With EDF scheduling, all flows receive the same miss rate regardless of their traffic characteristics and deadlines. This makes the standard EDF algorithm unsuitable for situations in which the different flows have different miss rate requirements since in order to meet all miss rate requirements it is necessary to limit admissions so as to satisfy the flow with the most stringent miss rate requirements. In this paper, we propose a new priority assignment scheduling algorithm, Hierarchal Diff-EDF (Differentiate Earliest Deadline First, which can meet the real-time needs of these applications while continuing to provide best effort service to non-real time traffic. The Hierarchal Diff-EDF features a feedback control mechanism that detects overload conditions and modifies packet priority assignments accordingly. To examine our proposed scheduler model, we introduced our attempt to provide an exact analytical solution. The attempt showed that the solution was apparently very complicated due to the high interdependence between the system queues' service. Hence, the use of simulation techniques seems inevitable. The simulation results showed that the Hierarchical Diff-EDF achieved the minimum packet average delay when compared with both EDF and Diff-EDF schedulers.

  5. Hierarchical structures of correlations networks among Turkey’s exports and imports by currencies

    Science.gov (United States)

    Kocakaplan, Yusuf; Deviren, Bayram; Keskin, Mustafa

    2012-12-01

    We have examined the hierarchical structures of correlations networks among Turkey’s exports and imports by currencies for the 1996-2010 periods, using the concept of a minimal spanning tree (MST) and hierarchical tree (HT) which depend on the concept of ultrametricity. These trees are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in financial markets. We derived a hierarchical organization and build the MSTs and HTs during the 1996-2001 and 2002-2010 periods. The reason for studying two different sub-periods, namely 1996-2001 and 2002-2010, is that the Euro (EUR) came into use in 2001, and some countries have made their exports and imports with Turkey via the EUR since 2002, and in order to test various time-windows and observe temporal evolution. We have carried out bootstrap analysis to associate a value of the statistical reliability to the links of the MSTs and HTs. We have also used the average linkage cluster analysis (ALCA) to observe the cluster structure more clearly. Moreover, we have obtained the bidimensional minimal spanning tree (BMST) due to economic trade being a bidimensional problem. From the structural topologies of these trees, we have identified different clusters of currencies according to their proximity and economic ties. Our results show that some currencies are more important within the network, due to a tighter connection with other currencies. We have also found that the obtained currencies play a key role for Turkey’s exports and imports and have important implications for the design of portfolio and investment strategies.

  6. Gel-based composite polymer electrolytes with novel hierarchical mesoporous silica network for lithium batteries

    Energy Technology Data Exchange (ETDEWEB)

    Wang Xiaoliang; Cai Qiang [Department of Materials Science and Engineering, and State Key Laboratory of New Ceramics and Fine Processing, Tsinghua University, Beijing 100084 (China); Fan Lizhen [School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing 100083 (China); Hua Tao; Lin Yuanhua [Department of Materials Science and Engineering, and State Key Laboratory of New Ceramics and Fine Processing, Tsinghua University, Beijing 100084 (China); Nan Cewen [Department of Materials Science and Engineering, and State Key Laboratory of New Ceramics and Fine Processing, Tsinghua University, Beijing 100084 (China)], E-mail: cwnan@tsinghua.edu.cn

    2008-11-15

    In the present work, novel gel-based composite polymer electrolytes for lithium batteries were prepared by introducing a hierarchical mesoporous silica network to the poly(vinylidene fluoride-hexafluoropropylene) (PVDF-HFP)-based gel electrolytes. As compared with the PVDF-HFP-based gel electrolytes with/without conventional nano-sized silica fillers, the novel electrolytes have shown more homogeneous microstructure, higher ionic conductivity and better mechanical stability, which could be caused by the strong silica network and the effective interactions among the polymer, the liquid electrolytes and the silica. Moreover, the cell with this kind of electrolytes could achieve a discharge capacity as much as 150 mAh g{sup -1} at room temperature (LiCoO{sub 2} as the cathode active material), with high Coulomb efficiency.

  7. Gel-based composite polymer electrolytes with novel hierarchical mesoporous silica network for lithium batteries

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xiao-Liang; Cai, Qiang; Hua, Tao; Lin, Yuan-Hua; Nan, Ce-Wen [Department of Materials Science and Engineering, and State Key Laboratory of New Ceramics and Fine Processing, Tsinghua University, Beijing 100084 (China); Fan, Li-Zhen [School of Materials Science and Engineering, University of Science and Technology Beijing, Beijing 100083 (China)

    2008-11-15

    In the present work, novel gel-based composite polymer electrolytes for lithium batteries were prepared by introducing a hierarchical mesoporous silica network to the poly(vinylidene fluoride-hexafluoropropylene) (PVDF-HFP)-based gel electrolytes. As compared with the PVDF-HFP-based gel electrolytes with/without conventional nano-sized silica fillers, the novel electrolytes have shown more homogeneous microstructure, higher ionic conductivity and better mechanical stability, which could be caused by the strong silica network and the effective interactions among the polymer, the liquid electrolytes and the silica. Moreover, the cell with this kind of electrolytes could achieve a discharge capacity as much as 150 mAh g{sup -1} at room temperature (LiCoO{sub 2} as the cathode active material), with high Coulomb efficiency. (author)

  8. A New Enhanced Fast Handover Algorithm in Hierarchical Mobile IPv6 Network

    Institute of Scientific and Technical Information of China (English)

    XU Kai; JI Hong; YUE Guang-xin

    2004-01-01

    Hierarchical Mobile IPv6 (HMIPv6) can reduce the delay and the amount of signaling during handover compared with the basic mobile IPv6. However, the protocol still cannot meet the requirement for traffic that is delay sensitive, such as voice, especially in macro mobility handover. Duplicate address detection and the transmission time for the handover operation could cause high handover delay. This paper proposes a new mechanism to improve the fast handover algorithms efficiency in HMIPv6 network. And we present and analyze the performance testing for our proposal by comparing it with the traditional HMIPv6 fast handover algorithm. The results of simulation show that our scheme can reduce the handover delay much more than the traditional fast handover method for HMIPv6 network.

  9. A special hierarchical fuzzy neural-networks based reinforcement learning for multi-variables system

    Institute of Scientific and Technical Information of China (English)

    ZHANG Wen-zhi; LU Tian-sheng

    2005-01-01

    Proposes a reinforcement learning scheme based on a special Hierarchical Fuzzy Neural-Networks (HFNN) for solving complicated learning tasks in a continuous multi-variables environment. The output of the previous layer in the HFNN is no longer used as if-part of the next layer, but used only in then-part. Thus it can deal with the difficulty when the output of the previous layer is meaningless or its meaning is uncertain. The proposed HFNN has a minimal number of fuzzy rules and can successfully solve the problem of rules combination explosion and decrease the quantity of computation and memory requirement. In the learning process, two HFNN with the same structure perform fuzzy action composition and evaluation function approximation simultaneously where the parameters of neural-networks are tuned and updated on line by using gradient descent algorithm. The reinforcement learning method is proved to be correct and feasible by simulation of a double inverted pendulum system.

  10. Hierarchical Neural Networks Method for Fault Diagnosis of Large-Scale Analog Circuits

    Institute of Scientific and Technical Information of China (English)

    TAN Yanghong; HE Yigang; FANG Gefeng

    2007-01-01

    A novel hierarchical neural networks (HNNs) method for fault diagnosis of large-scale circuits is proposed. The presented techniques using neural networks(NNs) approaches require a large amount of computation for simulating various faulty component possibilities. For large scale circuits, the number of possible faults, and hence the simulations, grow rapidly and become tedious and sometimes even impractical. Some NNs are distributed to the torn sub-blocks according to the proposed torn principles of large scale circuits. And the NNs are trained in batches by different patterns in the light of the presented rules of various patterns when the DC, AC and transient responses of the circuit are available. The method is characterized by decreasing the over-lapped feasible domains of responses of circuits with tolerance and leads to better performance and higher correct classification. The methodology is illustrated by means of diagnosis examples.

  11. Robustness Results for Hierarchical Diff-EDF Scheduling upon Heterogeneous Real-Time Packet Networks

    Directory of Open Access Journals (Sweden)

    Moutaz Saleh

    2007-01-01

    Full Text Available Packet networks are currently enabling the integration of traffic with a wide range of characteristics that extend from video traffic with stringent QoS requirements to the best-effort traffic requiring no guarantees. QoS guarantees can be provided in conventional packet networks by the use of proper packet scheduling algorithms. As a computer revolution, many scheduling algorithms have been proposed to provide different schemes of QoS guarantees with Earliest Deadline First (EDF as the most popular one. With EDF scheduling, all flows receive the same miss rate regardless of their traffic characteristics and deadlines. This makes the standard EDF algorithm unsuitable for situations in which the different flows have different miss rate requirements since in order to meet all miss rate requirements it is necessary to limit admissions so as to satisfy the flow with the most stringent miss rate requirements. In this study, we propose a new priority assignment scheduling algorithm, Hierarchal Diff-EDF (Differentiate Earliest Deadline First, which can meet the real-time needs of these applications while continuing to provide best effort service to non-real time traffic. The Hierarchal Diff-EDF features a feedback control mechanism that detects overload conditions and modifies packet priority assignments accordingly.

  12. SMR-Based Adaptive Mobility Management Scheme in Hierarchical SIP Networks

    Directory of Open Access Journals (Sweden)

    KwangHee Choi

    2014-10-01

    Full Text Available In hierarchical SIP networks, paging is performed to reduce location update signaling cost for mobility management. However, the cost efficiency largely depends on each mobile node’s session-to-mobility-ratio (SMR, which is defined as a ratio of the session arrival rate to the movement rate. In this paper, we propose the adaptive mobility management scheme that can determine the policy regarding to each mobile node’s SMR. Each mobile node determines whether the paging is applied or not after comparing its SMR with the threshold. In other words, the paging is applied to a mobile node when a mobile node’s SMR is less than the threshold. Therefore, the proposed scheme provides a way to minimize signaling costs according to each mobile node’s SMR. We find out the optimal threshold through performance analysis, and show that the proposed scheme can reduce signaling cost than the existing SIP and paging schemes in hierarchical SIP networks.

  13. Hierarchical modularity in ERα transcriptional network is associated with distinct functions and implicates clinical outcomes.

    Science.gov (United States)

    Tang, Binhua; Hsu, Hang-Kai; Hsu, Pei-Yin; Bonneville, Russell; Chen, Su-Shing; Huang, Tim H-M; Jin, Victor X

    2012-01-01

    Recent genome-wide profiling reveals highly complex regulation networks among ERα and its targets. We integrated estrogen (E2)-stimulated time-series ERα ChIP-seq and gene expression data to identify the ERα-centered transcription factor (TF) hubs and their target genes, and inferred the time-variant hierarchical network structures using a Bayesian multivariate modeling approach. With its recurrent motif patterns, we determined three embedded regulatory modules from the ERα core transcriptional network. The GO analyses revealed the distinct biological function associated with each of three embedded modules. The survival analysis showed the genes in each module were able to render a significant survival correlation in breast cancer patient cohorts. In summary, our Bayesian statistical modeling and modularity analysis not only reveals the dynamic properties of the ERα-centered regulatory network and associated distinct biological functions, but also provides a reliable and effective genomic analytical approach for the analysis of dynamic regulatory network for any given TF.

  14. A Comprehensive Survey on Hierarchical-Based Routing Protocols for Mobile Wireless Sensor Networks: Review, Taxonomy, and Future Directions

    Directory of Open Access Journals (Sweden)

    Nabil Sabor

    2017-01-01

    Full Text Available Introducing mobility to Wireless Sensor Networks (WSNs puts new challenges particularly in designing of routing protocols. Mobility can be applied to the sensor nodes and/or the sink node in the network. Many routing protocols have been developed to support the mobility of WSNs. These protocols are divided depending on the routing structure into hierarchical-based, flat-based, and location-based routing protocols. However, the hierarchical-based routing protocols outperform the other routing types in saving energy, scalability, and extending lifetime of Mobile WSNs (MWSNs. Selecting an appropriate hierarchical routing protocol for specific applications is an important and difficult task. Therefore, this paper focuses on reviewing some of the recently hierarchical-based routing protocols that are developed in the last five years for MWSNs. This survey divides the hierarchical-based routing protocols into two broad groups, namely, classical-based and optimized-based routing protocols. Also, we present a detailed classification of the reviewed protocols according to the routing approach, control manner, mobile element, mobility pattern, network architecture, clustering attributes, protocol operation, path establishment, communication paradigm, energy model, protocol objectives, and applications. Moreover, a comparison between the reviewed protocols is investigated in this survey depending on delay, network size, energy-efficiency, and scalability while mentioning the advantages and drawbacks of each protocol. Finally, we summarize and conclude the paper with future directions.

  15. Top-down feedback in an HMAX-like cortical model of object perception based on hierarchical Bayesian networks and belief propagation.

    Directory of Open Access Journals (Sweden)

    Salvador Dura-Bernal

    Full Text Available Hierarchical generative models, such as Bayesian networks, and belief propagation have been shown to provide a theoretical framework that can account for perceptual processes, including feedforward recognition and feedback modulation. The framework explains both psychophysical and physiological experimental data and maps well onto the hierarchical distributed cortical anatomy. However, the complexity required to model cortical processes makes inference, even using approximate methods, very computationally expensive. Thus, existing object perception models based on this approach are typically limited to tree-structured networks with no loops, use small toy examples or fail to account for certain perceptual aspects such as invariance to transformations or feedback reconstruction. In this study we develop a Bayesian network with an architecture similar to that of HMAX, a biologically-inspired hierarchical model of object recognition, and use loopy belief propagation to approximate the model operations (selectivity and invariance. Crucially, the resulting Bayesian network extends the functionality of HMAX by including top-down recursive feedback. Thus, the proposed model not only achieves successful feedforward recognition invariant to noise, occlusions, and changes in position and size, but is also able to reproduce modulatory effects such as illusory contour completion and attention. Our novel and rigorous methodology covers key aspects such as learning using a layerwise greedy algorithm, combining feedback information from multiple parents and reducing the number of operations required. Overall, this work extends an established model of object recognition to include high-level feedback modulation, based on state-of-the-art probabilistic approaches. The methodology employed, consistent with evidence from the visual cortex, can be potentially generalized to build models of hierarchical perceptual organization that include top-down and bottom

  16. Scalable Hierarchical Network Management System for Displaying Network Information in Three Dimensions

    Science.gov (United States)

    George, Jude (Inventor); Schlecht, Leslie (Inventor); McCabe, James D. (Inventor); LeKashman, John Jr. (Inventor)

    1998-01-01

    A network management system has SNMP agents distributed at one or more sites, an input output module at each site, and a server module located at a selected site for communicating with input output modules, each of which is configured for both SNMP and HNMP communications. The server module is configured exclusively for HNMP communications, and it communicates with each input output module according to the HNMP. Non-iconified, informationally complete views are provided of network elements to aid in network management.

  17. AN OPTIMUM VEHICULAR PATH ALGORITHM FOR TRAFFIC NETWORK BASED ON HIERARCHICAL SPATIAL REASONING

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Human beings' intellection is the characteristic of a distinct hierarchy and can be taken to construct a heuristic in the shortest path algorithms.It is detailed in this paper how to utilize the hierarchical reasoning on the basis of greedy and directional strategy to establish a spatial heuristic,so as to improve running efficiency and suitability of shortest path algorithm for traffic network.The authors divide urban traffic network into three hierarchies and set forward a new node hierarchy division rule to avoid the unreliable solution of shortest path.It is argued that the shortest path,no matter distance shortest or time shortest,is usually not the favorite of drivers in practice.Some factors difficult to expect or quantify influence the drivers' choice greatly.It makes the drivers prefer choosing a less shortest,but more reliable or flexible path to travel on.The presented optimum path algorithm,in addition to the improvement of the running efficiency of shortest path algorithms up to several times,reduces the emergence of those factors,conforms to the intellection characteristic of human beings,and is more easily accepted by drivers.Moreover,it does not require the completeness of networks in the lowest hierarchy and the applicability and fault tolerance of the algorithm have improved.The experiment result shows the advantages of the presented algorithm.The authors argued that the algorithm has great potential application for navigation systems of large-scale traffic networks.

  18. Clustering-based classification of road traffic accidents using hierarchical clustering and artificial neural networks.

    Science.gov (United States)

    Taamneh, Madhar; Taamneh, Salah; Alkheder, Sharaf

    2017-09-01

    Artificial neural networks (ANNs) have been widely used in predicting the severity of road traffic crashes. All available information about previously occurred accidents is typically used for building a single prediction model (i.e., classifier). Too little attention has been paid to the differences between these accidents, leading, in most cases, to build less accurate predictors. Hierarchical clustering is a well-known clustering method that seeks to group data by creating a hierarchy of clusters. Using hierarchical clustering and ANNs, a clustering-based classification approach for predicting the injury severity of road traffic accidents was proposed. About 6000 road accidents occurred over a six-year period from 2008 to 2013 in Abu Dhabi were used throughout this study. In order to reduce the amount of variation in data, hierarchical clustering was applied on the data set to organize it into six different forms, each with different number of clusters (i.e., clusters from 1 to 6). Two ANN models were subsequently built for each cluster of accidents in each generated form. The first model was built and validated using all accidents (training set), whereas only 66% of the accidents were used to build the second model, and the remaining 34% were used to test it (percentage split). Finally, the weighted average accuracy was computed for each type of models in each from of data. The results show that when testing the models using the training set, clustering prior to classification achieves (11%-16%) more accuracy than without using clustering, while the percentage split achieves (2%-5%) more accuracy. The results also suggest that partitioning the accidents into six clusters achieves the best accuracy if both types of models are taken into account.

  19. Synchronization in node of complex networks consist of complex chaotic system

    Directory of Open Access Journals (Sweden)

    Qiang Wei

    2014-07-01

    Full Text Available A new synchronization method is investigated for node of complex networks consists of complex chaotic system. When complex networks realize synchronization, different component of complex state variable synchronize up to different scaling complex function by a designed complex feedback controller. This paper change synchronization scaling function from real field to complex field for synchronization in node of complex networks with complex chaotic system. Synchronization in constant delay and time-varying coupling delay complex networks are investigated, respectively. Numerical simulations are provided to show the effectiveness of the proposed method.

  20. Hierarchical transport networks optimizing dynamic response of permeable energy-storage materials.

    Science.gov (United States)

    Nilson, Robert H; Griffiths, Stewart K

    2009-07-01

    Channel widths and spacing in latticelike hierarchical transport networks are optimized to achieve maximum extraction of gas or electrical charge from nanoporous energy-storage materials during charge and discharge cycles of specified duration. To address a range of physics, the effective transport diffusivity is taken to vary as a power, m , of channel width. Optimal channel widths and spacing in all levels of the hierarchy are found to increase in a power-law manner with normalized system size, facilitating the derivation of closed-form approximations for the optimal dimensions. Characteristic response times and ratios of channel width to spacing are both shown to vary by the factor 2/m between successive levels of any optimal hierarchy. This leads to fractal-like self-similar geometry, but only for m=2 . For this case of quadratic dependence of diffusivity on channel width, the introduction of transport channels permits increases in system size on the order of 10;{4} , 10;{8} , and 10;{10} , without any reduction in extraction efficiency, for hierarchies having 1, 2 and, 8 levels, respectively. However, we also find that for a given system size there is an optimum number of hierarchical levels that maximizes extraction efficiency.

  1. Emergence of hierarchical structure mirroring linguistic composition in a recurrent neural network.

    Science.gov (United States)

    Hinoshita, Wataru; Arie, Hiroaki; Tani, Jun; Okuno, Hiroshi G; Ogata, Tetsuya

    2011-05-01

    We show that a Multiple Timescale Recurrent Neural Network (MTRNN) can acquire the capabilities to recognize, generate, and correct sentences by self-organizing in a way that mirrors the hierarchical structure of sentences: characters grouped into words, and words into sentences. The model can control which sentence to generate depending on its initial states (generation phase) and the initial states can be calculated from the target sentence (recognition phase). In an experiment, we trained our model over a set of unannotated sentences from an artificial language, represented as sequences of characters. Once trained, the model could recognize and generate grammatical sentences, even if they were not learned. Moreover, we found that our model could correct a few substitution errors in a sentence, and the correction performance was improved by adding the errors to the training sentences in each training iteration with a certain probability. An analysis of the neural activations in our model revealed that the MTRNN had self-organized, reflecting the hierarchical linguistic structure by taking advantage of the differences in timescale among its neurons: in particular, neurons that change the fastest represented "characters", those that change more slowly, "words", and those that change the slowest, "sentences".

  2. Semiautomatic transfer function initialization for abdominal visualization using self-generating hierarchical radial basis function networks.

    Science.gov (United States)

    Selver, M Alper; Güzeliş, Cüneyt

    2009-01-01

    As being a tool that assigns optical parameters used in interactive visualization, Transfer Functions (TF) have important effects on the quality of volume rendered medical images. Unfortunately, finding accurate TFs is a tedious and time consuming task because of the trade off between using extensive search spaces and fulfilling the physician's expectations with interactive data exploration tools and interfaces. By addressing this problem, we introduce a semi-automatic method for initial generation of TFs. The proposed method uses a Self Generating Hierarchical Radial Basis Function Network to determine the lobes of a Volume Histogram Stack (VHS) which is introduced as a new domain by aligning the histograms of slices of a image series. The new self generating hierarchical design strategy allows the recognition of suppressed lobes corresponding to suppressed tissues and representation of the overlapping regions which are parts of the lobes but can not be represented by the Gaussian bases in VHS. Moreover, approximation with a minimum set of basis functions provides the possibility of selecting and adjusting suitable units to optimize the TF. Applications on different CT and MR data sets show enhanced rendering quality and reduced optimization time in abdominal studies.

  3. Hierarchical leak detection and localization method in natural gas pipeline monitoring sensor networks.

    Science.gov (United States)

    Wan, Jiangwen; Yu, Yang; Wu, Yinfeng; Feng, Renjian; Yu, Ning

    2012-01-01

    In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point's position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.

  4. The comparison of tree-sibling time consistent phylogenetic networks is graph isomorphism-complete.

    Science.gov (United States)

    Cardona, Gabriel; Llabrés, Mercè; Rosselló, Francesc; Valiente, Gabriel

    2014-01-01

    Several polynomial time computable metrics on the class of semibinary tree-sibling time consistent phylogenetic networks are available in the literature; in particular, the problem of deciding if two networks of this kind are isomorphic is in P. In this paper, we show that if we remove the semibinarity condition, then the problem becomes much harder. More precisely, we prove that the isomorphism problem for generic tree-sibling time consistent phylogenetic networks is polynomially equivalent to the graph isomorphism problem. Since the latter is believed not to belong to P, the chances are that it is impossible to define a metric on the class of all tree-sibling time consistent phylogenetic networks that can be computed in polynomial time.

  5. Soft sensor of chemical processes with large numbers of input parameters using auto-associative hierarchical neural network

    Institute of Scientific and Technical Information of China (English)

    Yanlin He; Yuan Xu; Zhiqiang Geng; Qunxiong Zhu

    2015-01-01

    To explore the problems of monitoring chemical processes with large numbers of input parameters, a method based on Auto-associative Hierarchical Neural Network (AHNN) is proposed. AHNN focuses on dealing with datasets in high-dimension. AHNNs consist of two parts:groups of subnets based on well trained Auto-associative Neural Networks (AANNs) and a main net. The subnets play an important role on the performance of AHNN. A simple but effective method of designing the subnets is developed in this paper. In this method, the subnets are designed according to the classification of the data attributes. For getting the classification, an effective method called Extension Data Attributes Classification (EDAC) is adopted. Soft sensor using AHNN based on EDAC (EDAC-AHNN) is introduced. As a case study, the production data of Purified Terephthalic Acid (PTA) solvent system are selected to examine the proposed model. The results of the EDAC-AHNN model are compared with the experimental data extracted from the literature, which shows the efficiency of the proposed model.

  6. Bayesian methods for estimating the reliability in complex hierarchical networks (interim report).

    Energy Technology Data Exchange (ETDEWEB)

    Marzouk, Youssef M.; Zurn, Rena M.; Boggs, Paul T.; Diegert, Kathleen V. (Sandia National Laboratories, Albuquerque, NM); Red-Horse, John Robert (Sandia National Laboratories, Albuquerque, NM); Pebay, Philippe Pierre

    2007-05-01

    Current work on the Integrated Stockpile Evaluation (ISE) project is evidence of Sandia's commitment to maintaining the integrity of the nuclear weapons stockpile. In this report, we undertake a key element in that process: development of an analytical framework for determining the reliability of the stockpile in a realistic environment of time-variance, inherent uncertainty, and sparse available information. This framework is probabilistic in nature and is founded on a novel combination of classical and computational Bayesian analysis, Bayesian networks, and polynomial chaos expansions. We note that, while the focus of the effort is stockpile-related, it is applicable to any reasonably-structured hierarchical system, including systems with feedback.

  7. Virtual and Dynamic Hierarchical Architecture: an overlay network topology for discovering grid services with high performance

    Institute of Scientific and Technical Information of China (English)

    黄理灿; 吴朝晖; 潘云鹤

    2004-01-01

    This paper presents an overlay network topology called Virtual and Dynamic Hierarchical Architecture (VDHA) for discovering Grid services with high performance. Service discovery based on VDHA has scalable, autonomous, efficient, reliable and quick responsive. We propose two service discovery algorithms. Full Search Query and Discovery Protocol (FSQDP) discovers the nodes that match the request message from all N nodes, which has time complexity O(logN), space complexity O(nvg) (nvg being node numbers of each virtual group), and message-cost O(N), and Domain-Specific Query and Discovery Protocol (DSQDP) searches nodes in only specific domains with time complexity O(nvg), space complexity O(nvg), and message-cost O(nvg). In this paper, we also describe VDHA, its formal definition, and Grid Group Management Protocol.

  8. AH-MAC: Adaptive Hierarchical MAC Protocol for Low-Rate Wireless Sensor Network Applications

    Directory of Open Access Journals (Sweden)

    Adnan Ismail Al-Sulaifanie

    2017-01-01

    Full Text Available This paper proposes an adaptive hierarchical MAC protocol (AH-MAC with cross-layer optimization for low-rate and large-scale wireless sensor networks. The main goal of the proposed protocol is to combine the strengths of LEACH and IEEE 802.15.4 while offsetting their weaknesses. The predetermined cluster heads are supported with an energy harvesting circuit, while the normal nodes are battery-operated. To prolong the network’s operational lifetime, the proposed protocol transfers most of the network’s activities to the cluster heads while minimizing the node’s activity. Some of the main features of this protocol include energy efficiency, self-configurability, scalability, and self-healing. The simulation results showed great improvement of the AH-MAC over LEACH protocol in terms of energy consumption and throughput. AH-MAC consumes eight times less energy while improving throughput via acknowledgment support.

  9. Electropolymerized Star-Shaped Benzotrithiophenes Yield π-Conjugated Hierarchical Networks with High Areal Capacitance

    KAUST Repository

    Ringk, Andreas

    2016-03-30

    High-surface-area π-conjugated polymeric networks have the potential to lend outstanding capacitance to supercapacitors because of the pronounced faradaic processes that take place across the dense intimate interface between active material and electrolytes. In this report, we describe how benzo[1,2-b:3,4-b’:5,6-b’’]trithiophene (BTT) and tris-EDOT-benzo[1,2-b:3,4-b’:5,6-b’’]trithiophene (TEBTT) can serve as 2D (trivalent) building blocks in the development of electropolymerized hierarchical π-conjugated frameworks with particularly high areal capacitance. In comparing electropolymerized networks of BTT, TEBTT, and their copolymers with EDOT, we show that P(TEBTT/EDOT)-based frameworks can achieve higher areal capacitance (e.g., as high as 443.8 mF cm-2 at 1 mA cm-2) than those achieved by their respective homopolymers (PTEBTT and PEDOT) in the same experimental conditions of electrodeposition (PTEBTT: 271.1 mF cm-2 (at 1 mA cm-2) and PEDOT: 12.1 mF cm-2 (at 1 mA cm-2)). For example, P(TEBTT/EDOT)-based frameworks synthesized in a 1:1 monomer-to-comonomer ratio show a ca. 35x capacitance improvement over PEDOT. The high areal capacitance measured for P(TEBTT/EDOT) copolymers can be explained by the open, highly porous hierarchical morphologies formed during the electropolymerization step. With >70% capacitance retention over 1,000 cycles (up to 89% achieved), both PTEBTT- and P(TEBTT/EDOT)-based frameworks are resilient to repeated electrochemical cycling and can be considered promising systems for high life cycle capacitive electrode applications.

  10. A Dynamic Key Management Scheme Based on Secret Sharing for Hierarchical Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Enjian Bai

    2013-01-01

    Full Text Available Since wireless sensor networks (WSN for short are often deployed in hostile environments in many applications, security becomes one of the critical issues in WSN. Moreover, due to the limitation of the sensor nodes, traditional key management schemes are not suitable for it. Thereby,a feasible and efficient key management scheme is an important guarantee for WSN to communicate securely. For the moment, many protocols have been proposed and each has its own advantages. However, these protocols cannot provide sufficient security in many cases, such as node capture attack, which makes WSN more vulnerable than traditional wireless networks. Key protection and revocation issues must be considered with special attention in WSN. To address these two issues, we propose a dynamically clustering key management scheme based on secret sharing for WSN. The scheme combined the hierarchical structure of wireless sensor networks with dynamic key management scheme. The analysis results show that the scheme has strong security and resistance of captured attack, as well as low communicational overhead, and it well meets the requirement of scalability.

  11. Hierarchical network model for the analysis of human spatio-temporal information processing

    Science.gov (United States)

    Schill, Kerstin; Baier, Volker; Roehrbein, Florian; Brauer, Wilfried

    2001-06-01

    The perception of spatio-temporal pattern is a fundamental part of visual cognition. In order to understand more about the principles behind these biological processes, we are analyzing and modeling the presentation of spatio-temporal structures on different levels of abstraction. For the low- level processing of motion information we have argued for the existence of a spatio-temporal memory in early vision. The basic properties of this structure are reflected in a neural network model which is currently developed. Here we discuss major architectural features of this network which is base don Kohonens SOMs. In order to enable the representation, processing and prediction of spatio-temporal pattern on different levels of granularity and abstraction the SOMs are organized in a hierarchical manner. The model has the advantage of a 'self-teaching' learning algorithm and stored temporal information try local feedback in each computational layer. The constraints for the neural modeling and data set for training the neural network are obtained by psychophysical experiments where human subjects' abilities for dealing with spatio-temporal information is investigated.

  12. Hierarchical surface code for network quantum computing with modules of arbitrary size

    Science.gov (United States)

    Li, Ying; Benjamin, Simon C.

    2016-10-01

    The network paradigm for quantum computing involves interconnecting many modules to form a scalable machine. Typically it is assumed that the links between modules are prone to noise while operations within modules have a significantly higher fidelity. To optimize fault tolerance in such architectures we introduce a hierarchical generalization of the surface code: a small "patch" of the code exists within each module and constitutes a single effective qubit of the logic-level surface code. Errors primarily occur in a two-dimensional subspace, i.e., patch perimeters extruded over time, and the resulting noise threshold for intermodule links can exceed ˜10 % even in the absence of purification. Increasing the number of qubits within each module decreases the number of qubits necessary for encoding a logical qubit. But this advantage is relatively modest, and broadly speaking, a "fine-grained" network of small modules containing only about eight qubits is competitive in total qubit count versus a "course" network with modules containing many hundreds of qubits.

  13. A hierarchical nanostructure consisting of amorphous MnO 2, Mn 3O 4 nanocrystallites, and single-crystalline MnOOH nanowires for supercapacitors

    Science.gov (United States)

    Hu, Chi-Chang; Hung, Ching-Yun; Chang, Kuo-Hsin; Yang, Yi-Lin

    In this communication, a porous hierarchical nanostructure consisting of amorphous MnO 2 (a-MnO 2), Mn 3O 4 nanocrystals, and single-crystalline MnOOH nanowires is designed for the supercapacitor application, which is prepared by a simple two-step electrochemical deposition process. Because of the gradual co-transformation of Mn 3O 4 nanocrystals and a-MnO 2 nanorods into an amorphous manganese oxide, the cycle stability of a-MnO 2 is obviously enhanced by adding Mn 3O 4. This unique ternary oxide nanocomposite with 100-cycle CV activation exhibits excellent capacitive performances, i.e., excellent reversibility, high specific capacitances (470 F g -1 in CaCl 2), high power property, and outstanding cycle stability. The highly porous microstructures of this composite before and after the 10,000-cycle CV test are examined by means of scanning electron microscopy (SEM) and transmission electron microscopy (TEM).

  14. APPLICATION OF NEURAL NETWORK WITH MULTI-HIERARCHIC STRUCTURE TO EVALUATE SUSTAINABLE DEVELOPMENT OF THE COAL MINES

    Institute of Scientific and Technical Information of China (English)

    李新春; 陶学禹

    2000-01-01

    The neural network with multi-hierarchic structure is provided in this paper to evaluate sustainable development of the coal mines based on analyzing its effect factors. The whole evaluating system is composed of 5 neural networks.The feasibility of this method has been proved by case study. This study will provide a scientfic and theoretic foundation for evaluating the sustainable development of coal mines.

  15. Method of Parallel-Hierarchical Network Self-Training and its Application for Pattern Classification and Recognition

    Directory of Open Access Journals (Sweden)

    TIMCHENKO, L.

    2012-11-01

    Full Text Available Propositions necessary for development of parallel-hierarchical (PH network training methods are discussed in this article. Unlike already known structures of the artificial neural network, where non-normalized (absolute similarity criteria are used for comparison, the suggested structure uses a normalized criterion. Based on the analysis of training rules, a conclusion is made that application of two training methods with a teacher is optimal for PH network training: error correction-based training and memory-based training. Mathematical models of training and a combined method of PH network training for recognition of static and dynamic patterns are developed.

  16. Using Bayesian Networks for Candidate Generation in Consistency-based Diagnosis

    Science.gov (United States)

    Narasimhan, Sriram; Mengshoel, Ole

    2008-01-01

    Consistency-based diagnosis relies heavily on the assumption that discrepancies between model predictions and sensor observations can be detected accurately. When sources of uncertainty like sensor noise and model abstraction exist robust schemes have to be designed to make a binary decision on whether predictions are consistent with observations. This risks the occurrence of false alarms and missed alarms when an erroneous decision is made. Moreover when multiple sensors (with differing sensing properties) are available the degree of match between predictions and observations can be used to guide the search for fault candidates. In this paper we propose a novel approach to handle this problem using Bayesian networks. In the consistency- based diagnosis formulation, automatically generated Bayesian networks are used to encode a probabilistic measure of fit between predictions and observations. A Bayesian network inference algorithm is used to compute most probable fault candidates.

  17. Hierarchical structure and modules in the Escherichia coli transcriptional regulatory network revealed by a new top-down approach

    Directory of Open Access Journals (Sweden)

    Buer Jan

    2004-12-01

    Full Text Available Abstract Background Cellular functions are coordinately carried out by groups of genes forming functional modules. Identifying such modules in the transcriptional regulatory network (TRN of organisms is important for understanding the structure and function of these fundamental cellular networks and essential for the emerging modular biology. So far, the global connectivity structure of TRN has not been well studied and consequently not applied for the identification of functional modules. Moreover, network motifs such as feed forward loop are recently proposed to be basic building blocks of TRN. However, their relationship to functional modules is not clear. Results In this work we proposed a top-down approach to identify modules in the TRN of E. coli. By studying the global connectivity structure of the regulatory network, we first revealed a five-layer hierarchical structure in which all the regulatory relationships are downward. Based on this regulatory hierarchy, we developed a new method to decompose the regulatory network into functional modules and to identify global regulators governing multiple modules. As a result, 10 global regulators and 39 modules were identified and shown to have well defined functions. We then investigated the distribution and composition of the two basic network motifs (feed forward loop and bi-fan motif in the hierarchical structure of TRN. We found that most of these network motifs include global regulators, indicating that these motifs are not basic building blocks of modules since modules should not contain global regulators. Conclusion The transcriptional regulatory network of E. coli possesses a multi-layer hierarchical modular structure without feedback regulation at transcription level. This hierarchical structure builds the basis for a new and simple decomposition method which is suitable for the identification of functional modules and global regulators in the transcriptional regulatory network of E

  18. Connectome-scale group-wise consistent resting-state network analysis in autism spectrum disorder

    Directory of Open Access Journals (Sweden)

    Yu Zhao

    2016-01-01

    Full Text Available Understanding the organizational architecture of human brain function and its alteration patterns in diseased brains such as Autism Spectrum Disorder (ASD patients are of great interests. In-vivo functional magnetic resonance imaging (fMRI offers a unique window to investigate the mechanism of brain function and to identify functional network components of the human brain. Previously, we have shown that multiple concurrent functional networks can be derived from fMRI signals using whole-brain sparse representation. Yet it is still an open question to derive group-wise consistent networks featured in ASD patients and controls. Here we proposed an effective volumetric network descriptor, named connectivity map, to compactly describe spatial patterns of brain network maps and implemented a fast framework in Apache Spark environment that can effectively identify group-wise consistent networks in big fMRI dataset. Our experiment results identified 144 group-wisely common intrinsic connectivity networks (ICNs shared between ASD patients and healthy control subjects, where some ICNs are substantially different between the two groups. Moreover, further analysis on the functional connectivity and spatial overlap between these 144 common ICNs reveals connectomics signatures characterizing ASD patients and controls. In particular, the computing time of our Spark-enabled functional connectomics framework is significantly reduced from 240 hours (C++ code, single core to 20 hours, exhibiting a great potential to handle fMRI big data in the future.

  19. An Efficient Admission Control Algorithm for Load Balancing In Hierarchical Mobile IPv6 Networks

    CERN Document Server

    Harini, Prof P

    2009-01-01

    In hierarchical Mobile IPv6 networks, Mobility Anchor Point (MAP) may become a single point of bottleneck as it handles more and more mobile nodes (MNs). A number of schemes have been proposed to achieve load balancing among different MAPs. However, signaling reduction is still imperfect because these schemes also avoid the effect of the number of CNs. Also only the balancing of MN is performed, but not the balancing of the actual traffic load, since CN of each MN may be different. This paper proposes an efficient admission control algorithm along with a replacement mechanism for HMIPv6 networks. The admission control algorithm is based on the number of serving CNs and achieves actual load balancing among MAPs. Moreover, a replacement mechanism is introduced to decrease the new MN blocking probability and the handoff MN dropping probability. By simulation results, we show that, the handoff delay and packet loss are reduced in our scheme, when compared with the standard HMIPv6 based handoff.

  20. A Hybrid System of Hierarchical Planning of Behaviour Selection Networks for Mobile Robot Control

    Directory of Open Access Journals (Sweden)

    Young-Seol Lee

    2014-04-01

    Full Text Available An office delivery robot receives a large amount of sensory data and there is uncertainty in its action outcomes. The robot should not only accomplish its goals using environmental information, but also consider various exceptions simultaneously. In this paper, we propose a hybrid system using hierarchical planning of modular behaviour selection networks to generate autonomous behaviour in the office delivery robot. Behaviour selection networks, one of the well-known behaviour-based methods suitable for goal-oriented tasks, are made up of several smaller behaviour modules. Planning is attached to the construct and adjust sequences of the modules by considering the sub-goals, the priority in each task and the user feedback. This helps the robot to quickly react in dynamic situations as well as achieve global goals efficiently. The proposed system is verified with both the Webot simulator and a Khepera II robot that runs in a real office environment carrying out delivery tasks. Experimental results have shown that a robot can achieve goals and generate module sequences successfully even in unpredictable situations. Additionally, the proposed planning method reduced the elapsed time during tasks by 17.5% since it adjusts the behaviour module sequences more effectively.

  1. Hierarchical Agglomerative Clustering Schemes for Energy-Efficiency in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Taleb Tariq

    2017-06-01

    Full Text Available Extending the lifetime of wireless sensor networks (WSNs while delivering the expected level of service remains a hot research topic. Clustering has been identified in the literature as one of the primary means to save communication energy. In this paper, we argue that hierarchical agglomerative clustering (HAC provides a suitable foundation for designing highly energy efficient communication protocols for WSNs. To this end, we study a new mechanism for selecting cluster heads (CHs based both on the physical location of the sensors and their residual energy. Furthermore, we study different patterns of communications between the CHs and the base station depending on the possible transmission ranges and the ability of the sensors to act as traffic relays. Simulation results show that our proposed clustering and communication schemes outperform well-knows existing approaches by comfortable margins. In particular, networks lifetime is increased by more than 60% compared to LEACH and HEED, and by more than 30% compared to K-means clustering.

  2. Using Complex Networks to Quantify Consistency in the Use of Words

    CERN Document Server

    Amancio, Diego R; Costa, Luciano da F; 10.1088/1742-5468/2012/01/P01004

    2013-01-01

    In this paper we quantify the consistency of word usage in written texts represented by complex networks, where words were taken as nodes, by measuring the degree of preservation of the node neighborhood.} Words were considered highly consistent if the authors used them with the same neighborhood. When ranked according to the consistency of use, the words obeyed a log-normal distribution, in contrast to the Zipf's law that applies to the frequency of use. Consistency correlated positively with the familiarity and frequency of use, and negatively with ambiguity and age of acquisition. An inspection of some highly consistent words confirmed that they are used in very limited semantic contexts. A comparison of consistency indices for 8 authors indicated that these indices may be employed for author recognition. Indeed, as expected authors of novels could be distinguished from those who wrote scientific texts. Our analysis demonstrated the suitability of the consistency indices, which can now be applied in other ...

  3. A Social Potential Fields Approach for Self-Deployment and Self-Healing in Hierarchical Mobile Wireless Sensor Networks

    Science.gov (United States)

    González-Parada, Eva; Cano-García, Jose; Aguilera, Francisco; Sandoval, Francisco; Urdiales, Cristina

    2017-01-01

    Autonomous mobile nodes in mobile wireless sensor networks (MWSN) allow self-deployment and self-healing. In both cases, the goals are: (i) to achieve adequate coverage; and (ii) to extend network life. In dynamic environments, nodes may use reactive algorithms so that each node locally decides when and where to move. This paper presents a behavior-based deployment and self-healing algorithm based on the social potential fields algorithm. In the proposed algorithm, nodes are attached to low cost robots to autonomously navigate in the coverage area. The proposed algorithm has been tested in environments with and without obstacles. Our study also analyzes the differences between non-hierarchical and hierarchical routing configurations in terms of network life and coverage. PMID:28075364

  4. CytoASP: a Cytoscape app for qualitative consistency reasoning, prediction and repair in biological networks.

    Science.gov (United States)

    Kittas, Aristotelis; Barozet, Amélie; Sereshti, Jekaterina; Grabe, Niels; Tsoka, Sophia

    2015-07-11

    Qualitative reasoning frameworks, such as the Sign Consistency Model (SCM), enable modelling regulatory networks to check whether observed behaviour can be explained or if unobserved behaviour can be predicted. The BioASP software collection offers ideal tools for such analyses. Additionally, the Cytoscape platform can offer extensive functionality and visualisation capabilities. However, specialist programming knowledge is required to use BioASP and no methods exist to integrate both of these software platforms effectively. We report the implementation of CytoASP, an app that allows the use of BioASP for influence graph consistency checking, prediction and repair operations through Cytoscape. While offering inherent benefits over traditional approaches using BioASP, it provides additional advantages such as customised visualisation of predictions and repairs, as well as the ability to analyse multiple networks in parallel, exploiting multi-core architecture. We demonstrate its usage in a case study of a yeast genetic network, and highlight its capabilities in reasoning over regulatory networks. We have presented a user-friendly Cytoscape app for the analysis of regulatory networks using BioASP. It allows easy integration of qualitative modelling, combining the functionality of BioASP with the visualisation and processing capability in Cytoscape, and thereby greatly simplifying qualitative network modelling, promoting its use in relevant projects.

  5. Hierarchical mechanisms of spatially contagious seed dispersal in complex seed-disperser networks.

    Science.gov (United States)

    Fedriani, José M; Wiegand, Thorsten

    2014-02-01

    Intra- and interspecific spatially contagious seed dispersal has far-reaching implications for plant recruitment, distribution, and community assemblage. However, logistical and analytical limitations have curtailed our understanding concerning the mechanisms and resulting spatial patterns of contagious seed dispersal in most systems and, especially, in complex seed-disperser networks. We investigated mechanisms of seed aggregation using techniques of spatial point pattern analysis and extensive data sets on mutispecific endozoochorous seed rain generated by five frugivorous mammals in three Mediterranean shrublands over two seasons. Our novel analytical approach revealed three hierarchical and complementary mechanisms of seed aggregation acting at different levels (fecal samples, seeds, pairs of seed species) and spatial scales. First, the three local guilds of frugivores tended to deliver their feces highly aggregated at small and intermediate spatial scales, and the overall pattern of fecal delivery could be described well by a nested double-cluster Thomas process. Second, once the strong observed fecal aggregation was accounted for, the distribution of mammal feces containing seeds was clustered within the pattern of all feces (i.e., with and without seeds), and the density of fecal samples containing seeds was higher than expected around other feces containing seeds in two out of the three studied seed-disperser networks. Finally, at a finer level, mark correlation analyses revealed that for some plant species pairs, the number of dispersed seeds was positively associated either at small or large spatial scales. Despite the relatively invariant patterning of nested double-clustering, some attributes of endozoochorous seed rain (e.g., intensity, scales of aggregation) were variable among study sites due to changes in the ecological context in which seeds and their dispersers interact. Our investigation disentangles for the first time the hierarchy of synergic

  6. Oscillatory Dynamics and Oscillation Death in Complex Networks Consisting of Both Excitatory and Inhibitory Nodes

    Institute of Scientific and Technical Information of China (English)

    张立升; 廖旭红; 弭元元; 谷伟风; 胡岗

    2012-01-01

    Zn neural networks, both excitatory and inhibitory cells play important roles in determining the functions of systems. Various dynamical networks have been proposed as artificial neural networks to study the properties of biological systems where the influences of excitatory nodes have been extensively investigated while those of inhibitory nodes have been studied much less. In this paper, we consider a model of oscillatory networks of excitable Boolean maps consisting of both excitatory and inhibitory nodes, focusing on the roles of inhibitory nodes. We find that inhibitory nodes in sparse networks (smM1 average connection degree) play decisive roles in weakening oscillations, and oscillation death occurs after continual weakening of oscillation for sufficiently high inhibitory node density. In the sharp contrast, increasing inhibitory nodes in dense networks may result in the increase of oscillation amplitude and sudden oscillation death at much lower inhibitory node density and the nearly highest excitation activities. Mechanism under these peculiar behaviors of dense networks is explained by the competition of the duplex effects of inhibitory nodes.

  7. Hierarchical hybrid control network design based on LON and master-slave RS-422/485 protocol

    Institute of Scientific and Technical Information of China (English)

    彭可; 陈际达; 陈岚

    2002-01-01

    Aiming at the weaknesses of LON bus, combining the coexistence of fieldbus and DCS (Distribu-ted Control Systems) in control networks, the authors introduce a hierarchical hybrid control network design based on LON and master-slave RS-422/485 protocol. This design adopts LON as the trunk, master-slave RS-422/485 control networks are connected to LON as special subnets by dedicated gateways. It is an implementation method for isomerous control network integration. Data management is ranked according to real-time requirements for different network data. The core components, such as control network nodes, router and gateway, are detailed in the paper. The design utilizes both communication advantage of LonWorks technology and the more powerful control ability of universal MCUs or PLCs, thus it greatly increases system response speed and performance-cost ratio.

  8. Carbon nanotube-based polymer nanocomposites: Fractal network to hierarchical morphology

    Science.gov (United States)

    Chatterjee, Tirtha

    The dispersion of anisotropic nanoparticles such as single-walled carbon nanotubes in polymeric matrices promises the ability to develop advanced materials with controlled and tailored combinations of properties. However, dispersion of such nanotubes in a polymer matrix is an extremely challenging task due to strong attractive interactions between the nanotubes. The successful dispersion of single-walled carbon nanotubes in poly(ethylene oxide) using an anionic surfactant (lithium dodecyl sulfate) as compatibilizer is reported here. The geometrical percolation threshold (pc, in vol %) of nanotubes, as revealed by melt-state rheological measurements, is found to be at ˜ 0.09 vol % loading, which corresponds to an effective tube anisotropy of ˜ 650. The system shows an even earlier development of the electrical percolation at 0.03 vol % SWNT loading as obtained by electrical conductivity measurements. In their quiescent state, the nanotubes show hierarchical fractal network (mass fractal dimension ˜ 2.3 +/- 0.2) made of aggregated flocs. Inside the floc, individual or small bundles of nanotubes overlap each other to form a dense mesh. The interfloc interactions provides the stress bearing capacity for these nano composites and are responsible for the unique modulus scaling of these systems (˜(p-pc)delta, 3.0 ≤ delta ≤ 4.5). The interaction is inversely related to the particle dispersion state, which influences the absolute values of the viscoelastic parameters. As a direct consequence of the self-similar fractal network, the linear flow properties display 'time-temperature-composition' superposition. This superposability can be extended for non-linear deformations when the non-linear properties are scaled by the local strain experienced by the elements of the network. More interestingly, under steady shear, these nanocomposites show network-independent behavior. The absolute stress value is a function of the nanotube loading, but the characteristic time

  9. SO2 Emissions in China – Their Network and Hierarchical Structures

    Science.gov (United States)

    Yan, Shaomin; Wu, Guang

    2017-01-01

    SO2 emissions lead to various harmful effects on environment and human health. The SO2 emission in China has significant contribution to the global SO2 emission, so it is necessary to employ various methods to study SO2 emissions in China with great details in order to lay the foundation for policymaking to improve environmental conditions in China. Network analysis is used to analyze the SO2 emissions from power generation, industrial, residential and transportation sectors in China for 2008 and 2010, which are recently available from 1744 ground surface monitoring stations. The results show that the SO2 emissions from power generation sector were highly individualized as small-sized clusters, the SO2 emissions from industrial sector underwent an integration process with a large cluster contained 1674 places covering all industrial areas in China, the SO2 emissions from residential sector was not impacted by time, and the SO2 emissions from transportation sector underwent significant integration. Hierarchical structure is obtained by further combining SO2 emissions from all four sectors and is potentially useful to find out similar patterns of SO2 emissions, which can provide information on understanding the mechanisms of SO2 pollution and on designing different environmental measure to combat SO2 emissions. PMID:28387301

  10. A Hierarchical of Security Situation Element Acquisition Mechanism in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Li Fangwei

    2015-08-01

    Full Text Available In wireless sensor network, the processing ability of the sensor nodes is poor. And the security situational element acquisition is also a serious problem. Thus, this paper proposes a hierarchical framework of security situational elements acquisition mechanism. In this framework, support vector machine hyper sphere multi class algorithm is introduced as basic classifier. The method of attribute reduction uses non negative matrix factorization algorithm. The fuzzy classification algorithm used to initialize non negative matrix factorization, in order to avoid the local optimal which is caused by non negative matrix factorization random initialization. In the sink node classification rules and attribute reduction rules are formed by learning. The classification analyses respectively focus on the cluster head and sink node, which can reduce the requirement of the sensor node properties. Attribute reduction before the data transmission, which reduces communication consumption data transmission, improves the performance of classifiers. By simulation analysis, the scheme has preferably accuracy in the situation elements acquisiton, and smaller communication overhead in the process of information transmission.

  11. Interference mitigation for broadcast in hierarchical cell structure networks: Transmission strategy and area spectral efficiency

    KAUST Repository

    Yang, Yuli

    2014-10-01

    In this paper, a hierarchical cell structure (HCS) is considered, where an access point (AP) broadcasts to local nodes (LNs) over orthogonal frequency subbands within a local cell located in a macrocell. Since the local cell shares the spectrum licensed to the macrocell, a given LN is interfered with by the macrocell user (MU)\\'s transmissions over the same subband. To improve the performance of the AP\\'s broadcast service, a novel transmission strategy is proposed to mitigate the interference from the MU to the LN while achieving diversity gain. For the purpose of performance evaluation, the ergodic capacity of the proposed scheme is quantified, and the corresponding closed-form expression is obtained. By comparing with the traditional transmission scheme, which suffers from MU\\'s interference, illustrative numerical results substantiate that the proposed scheme achieves better performance than the traditional scheme as the MU-LN mean channel power gain is larger than half of the AP-LN mean channel power gain. Subsequently, we develop an optimized network design by maximizing the area spectral efficiency (ASE) of the AP\\'s broadcast in the local cell.

  12. A comparative performance evaluation of intrusion detection techniques for hierarchical wireless sensor networks

    Directory of Open Access Journals (Sweden)

    H.H. Soliman

    2012-11-01

    Full Text Available An explosive growth in the field of wireless sensor networks (WSNs has been achieved in the past few years. Due to its important wide range of applications especially military applications, environments monitoring, health care application, home automation, etc., they are exposed to security threats. Intrusion detection system (IDS is one of the major and efficient defensive methods against attacks in WSN. Therefore, developing IDS for WSN have attracted much attention recently and thus, there are many publications proposing new IDS techniques or enhancement to the existing ones. This paper evaluates and compares the most prominent anomaly-based IDS systems for hierarchical WSNs and identifying their strengths and weaknesses. For each IDS, the architecture and the related functionality are briefly introduced, discussed, and compared, focusing on both the operational strengths and weakness. In addition, a comparison of the studied IDSs is carried out using a set of critical evaluation metrics that are divided into two groups; the first one related to performance and the second related to security. Finally based on the carried evaluation and comparison, a set of design principles are concluded, which have to be addressed and satisfied in future research of designing and implementing IDS for WSNs.

  13. A Secure Hierarchical Identify Authentication Scheme Combining Trust Mechanism in Mobile IPv6 Networks

    Directory of Open Access Journals (Sweden)

    Zhi Zhang

    2009-07-01

    Full Text Available During the last few years, it has become more and more conpeling in mobile applications, mobile IPv6 technology is convenient, but also produces a series of security compromise. Identify authentication is an important part of the network security. In this paper, we proposed a secure identify authentication scheme combining reputation mechanism, which considers inters domain trust relationship between mobile node home domain and the access domain in the pre-handoff procedure and realizes effective mutual authentication between mobile node(MN and the access domain. A dynamic reputation maintenance mechanism for inter domain relationship is also designed. Based SMC signature, a hierarchical signature and verification scheme is designed in one round mutual authentication. Theoretical analysis and numerical results show that proposed scheme is more effective in reducing total authentication and handoff delay and the signaling overhead than relative schemes. Security analysis shows, basing on the security of SMC-IBS, the proposed scheme is sufficient for private key privacy, signature unforgeability. Moreover, our scheme first provide public key revocation and key escrow problem in mobile IPv6 networks’ access authentication.

  14. Learning invariant object recognition from temporal correlation in a hierarchical network.

    Science.gov (United States)

    Lessmann, Markus; Würtz, Rolf P

    2014-06-01

    Invariant object recognition, which means the recognition of object categories independent of conditions like viewing angle, scale and illumination, is a task of great interest that humans can fulfill much better than artificial systems. During the last years several basic principles were derived from neurophysiological observations and careful consideration: (1) Developing invariance to possible transformations of the object by learning temporal sequences of visual features that occur during the respective alterations. (2) Learning in a hierarchical structure, so basic level (visual) knowledge can be reused for different kinds of objects. (3) Using feedback to compare predicted input with the current one for choosing an interpretation in the case of ambiguous signals. In this paper we propose a network which implements all of these concepts in a computationally efficient manner which gives very good results on standard object datasets. By dynamically switching off weakly active neurons and pruning weights computation is sped up and thus handling of large databases with several thousands of images and a number of categories in a similar order becomes possible. The involved parameters allow flexible adaptation to the information content of training data and allow tuning to different databases relatively easily. Precondition for successful learning is that training images are presented in an order assuring that images of the same object under similar viewing conditions follow each other. Through an implementation with sparse data structures the system has moderate memory demands and still yields very good recognition rates.

  15. CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks

    Science.gov (United States)

    Franke, R.

    2016-11-01

    In many networks discovered in biology, medicine, neuroscience and other disciplines special properties like a certain degree distribution and hierarchical cluster structure (also called communities) can be observed as general organizing principles. Detecting the cluster structure of an unknown network promises to identify functional subdivisions, hierarchy and interactions on a mesoscale. It is not trivial choosing an appropriate detection algorithm because there are multiple network, cluster and algorithmic properties to be considered. Edges can be weighted and/or directed, clusters overlap or build a hierarchy in several ways. Algorithms differ not only in runtime, memory requirements but also in allowed network and cluster properties. They are based on a specific definition of what a cluster is, too. On the one hand, a comprehensive network creation model is needed to build a large variety of benchmark networks with different reasonable structures to compare algorithms. On the other hand, if a cluster structure is already known, it is desirable to separate effects of this structure from other network properties. This can be done with null model networks that mimic an observed cluster structure to improve statistics on other network features. A third important application is the general study of properties in networks with different cluster structures, possibly evolving over time. Currently there are good benchmark and creation models available. But what is left is a precise sandbox model to build hierarchical, overlapping and directed clusters for undirected or directed, binary or weighted complex random networks on basis of a sophisticated blueprint. This gap shall be closed by the model CHIMERA (Cluster Hierarchy Interconnection Model for Evaluation, Research and Analysis) which will be introduced and described here for the first time.

  16. 3D Graphene-Foam-Reduced-Graphene-Oxide Hybrid Nested Hierarchical Networks for High-Performance Li-S Batteries.

    Science.gov (United States)

    Hu, Guangjian; Xu, Chuan; Sun, Zhenhua; Wang, Shaogang; Cheng, Hui-Ming; Li, Feng; Ren, Wencai

    2016-02-24

    A 3D graphene-foam-reduced-graphene-oxide hybrid nested hierarchical network is synthesized to achieve high sulfur loading and content simultaneously, which solves the "double low" issues of Li-S batteries. The obtained Li-S cathodes show a high areal capacity two times larger than that of commercial lithium-ion batteries, and a good cycling performance comparable to those at low sulfur loading.

  17. RedeR: R/Bioconductor package for representing modular structures, nested networks and multiple levels of hierarchical associations.

    Science.gov (United States)

    Castro, Mauro A A; Wang, Xin; Fletcher, Michael N C; Meyer, Kerstin B; Markowetz, Florian

    2012-04-24

    Visualization and analysis of molecular networks are both central to systems biology. However, there still exists a large technological gap between them, especially when assessing multiple network levels or hierarchies. Here we present RedeR, an R/Bioconductor package combined with a Java core engine for representing modular networks. The functionality of RedeR is demonstrated in two different scenarios: hierarchical and modular organization in gene co-expression networks and nested structures in time-course gene expression subnetworks. Our results demonstrate RedeR as a new framework to deal with the multiple network levels that are inherent to complex biological systems. RedeR is available from http://bioconductor.org/packages/release/bioc/html/RedeR.html.

  18. A Simplified Self-Consistent Probabilities Framework to Characterize Percolation Phenomena on Interdependent Networks : An Overview

    CERN Document Server

    Feng, Ling; Hu, Yanqing

    2015-01-01

    Interdependent networks are ubiquitous in our society, ranging from infrastructure to economics, and the study of their cascading behaviors using percolation theory has attracted much attention in the recent years. To analyze the percolation phenomena of these systems, different mathematical frameworks have been proposed including generating functions, eigenvalues among some others. These different frameworks approach the phase transition behaviors from different angles, and have been very successful in shaping the different quantities of interest including critical threshold, size of the giant component, order of phase transition and the dynamics of cascading. These methods also vary in their mathematical complexity in dealing with interdependent networks that have additional complexity in terms of the correlation among different layers of networks or links. In this work, we review a particular approach of simple self-consistent probability equations, and illustrate that it can greatly simplify the mathemati...

  19. Combined multi-nozzle deposition and freeze casting process to superimpose two porous networks for hierarchical three-dimensional microenvironment.

    Science.gov (United States)

    Snyder, Jessica E; Hunger, Philipp M; Wang, Chengyang; Hamid, Qudus; Wegst, Ulrike G K; Sun, Wei

    2014-03-01

    An engineered three-dimensional scaffold with hierarchical porosity and multiple niche microenvironments is produced using a combined multi-nozzle deposition-freeze casting technique. In this paper we present a process to fabricate a scaffold with improved interconnectivity and hierarchical porosity. The scaffold is produced using a two-stage manufacturing process which superimposes a printed porous alginate (Alg) network and a directionally frozen ceramic-polymer matrix. The combination of two processes, multi-nozzle deposition and freeze casting, provides engineering control of the microenvironment of the scaffolds over several length scales; including the addition of lateral porosity and the ratio of polymer to ceramic microstructures. The printed polymer scaffold is submerged in a ceramic-polymer slurry and subsequently, both structures are directionally frozen (freeze cast), superimposing and patterning both microenvironments into a single hierarchical architecture. An optional additional sintering step removes the organic material and densifies the ceramic phase to produce a well-defined network of open pores and a homogenous cell wall material composition. The techniques presented in this contribution address processing challenges, such as structure definition, reproducibility and fine adjustments of unique length scales, which one typically encounters when fabricating topological channels between longitudinal and transverse porous networks.

  20. Using complex networks to quantify consistency in the use of words

    Science.gov (United States)

    Amancio, D. R.; Oliveira, O. N., Jr.; Costa, L. da F.

    2012-01-01

    In this paper we have quantified the consistency of word usage in written texts represented by complex networks, where words were taken as nodes, by measuring the degree of preservation of the node neighborhood. Words were considered highly consistent if the authors used them with the same neighborhood. When ranked according to the consistency of use, the words obeyed a log-normal distribution, in contrast to Zipf's law that applies to the frequency of use. Consistency correlated positively with the familiarity and frequency of use, and negatively with ambiguity and age of acquisition. An inspection of some highly consistent words confirmed that they are used in very limited semantic contexts. A comparison of consistency indices for eight authors indicated that these indices may be employed for author recognition. Indeed, as expected, authors of novels could be distinguished from those who wrote scientific texts. Our analysis demonstrated the suitability of the consistency indices, which can now be applied in other tasks, such as emotion recognition.

  1. Recursive random forest algorithm for constructing multilayered hierarchical gene regulatory networks that govern biological pathways

    Science.gov (United States)

    Zhang, Kui; Busov, Victor; Wei, Hairong

    2017-01-01

    Background Present knowledge indicates a multilayered hierarchical gene regulatory network (ML-hGRN) often operates above a biological pathway. Although the ML-hGRN is very important for understanding how a pathway is regulated, there is almost no computational algorithm for directly constructing ML-hGRNs. Results A backward elimination random forest (BWERF) algorithm was developed for constructing the ML-hGRN operating above a biological pathway. For each pathway gene, the BWERF used a random forest model to calculate the importance values of all transcription factors (TFs) to this pathway gene recursively with a portion (e.g. 1/10) of least important TFs being excluded in each round of modeling, during which, the importance values of all TFs to the pathway gene were updated and ranked until only one TF was remained in the list. The above procedure, termed BWERF. After that, the importance values of a TF to all pathway genes were aggregated and fitted to a Gaussian mixture model to determine the TF retention for the regulatory layer immediately above the pathway layer. The acquired TFs at the secondary layer were then set to be the new bottom layer to infer the next upper layer, and this process was repeated until a ML-hGRN with the expected layers was obtained. Conclusions BWERF improved the accuracy for constructing ML-hGRNs because it used backward elimination to exclude the noise genes, and aggregated the individual importance values for determining the TFs retention. We validated the BWERF by using it for constructing ML-hGRNs operating above mouse pluripotency maintenance pathway and Arabidopsis lignocellulosic pathway. Compared to GENIE3, BWERF showed an improvement in recognizing authentic TFs regulating a pathway. Compared to the bottom-up Gaussian graphical model algorithm we developed for constructing ML-hGRNs, the BWERF can construct ML-hGRNs with significantly reduced edges that enable biologists to choose the implicit edges for experimental

  2. Flexible Data Dissemination Strategy For Effective Cache Consistency In Mobile Wireless Communication Networks

    Directory of Open Access Journals (Sweden)

    Kahkashan Tabassum

    2012-06-01

    Full Text Available In mobile wireless communication network, caching data items at the mobile clients is important to reduce the data access delay. However, efficient cache invalidation strategies are used to ensure the consistency between the data in the cache of mobile clients and at the database server. Servers use invalidation reports (IRs to inform the mobile clients about data item updates. This paper proposes and implements a multicast based strategy to maintain cache consistency in mobile environment using AVI as the cache invalidationscheme. The proposed algorithm is outlined as follows – To resolve a query, the mobile client searches its cache to check if its data is valid. If yes, then query is answered, otherwise the client queries the DTA (Dynamic Transmitting Agent for latest updates and the query is answered. If DTA doesn’t have the latest updates, it gets it from the server. So, the main idea here is that DTA will be multicasting updates to the clients and hence the clients need not uplink to the server individually, thus preserving the network bandwidth. The scenario of simulation is developed in Java. The results demonstrate that the traffic generated in the proposed multicast model is simplified and it also retains cache consistency when compared to the existing methods that used broadcast strategy.

  3. An Improved Particle Swarm Optimization Based on Deluge Approach for Enhanced Hierarchical Cache Optimization in IPTV Networks

    Directory of Open Access Journals (Sweden)

    M. Somu

    2014-05-01

    Full Text Available In recent years, IP network has been considered as a new delivery network for TV services. A majority of the telecommunication industries have used IP network to offer on-demand services and linear TV services as it can offer a two-way and high-speed communication. In order to effectively and economically utilize the IP network, caching is the technique which is usually preferred. In IPTV system, a managed network is utilized to bring out TV services, the requests of Video on Demand (VOD objects are usually combined in a limited period intensively and user preferences are fluctuated dynamically. Furthermore, the VOD content updates often under the control of IPTV providers. In order to minimize this traffic and overall network cost, a segment of the video content is stored in caches closer to subscribers, for example, Digital Subscriber Line Access Multiplexer (DSLAM, a Central Office (CO and Intermediate Office (IO. The major problem focused in this approach is to determine the optimal cache memory that should be assigned in order to attain maximum cost effectiveness. This approach uses an effective Grate Deluge algorithm based Particle Swarm Optimization (GDPSO approach for attaining the optimal cache memory size which in turn minimizes the overall network cost. The analysis shows that hierarchical distributed caching can save significant network cost through the utilization of the GDPSO algorithm.

  4. On Energy Efficient Hierarchical Cross-Layer Design: Joint Power Control and Routing for Ad Hoc Networks

    CERN Document Server

    Comaniciu, Cristina

    2007-01-01

    In this paper, a hierarchical cross-layer design approach is proposed to increase energy efficiency in ad hoc networks through joint adaptation of nodes' transmitting powers and route selection. The design maintains the advantages of the classic OSI model, while accounting for the cross-coupling between layers, through information sharing. The proposed joint power control and routing algorithm is shown to increase significantly the overall energy efficiency of the network, at the expense of a moderate increase in complexity. Performance enhancement of the joint design using multiuser detection is also investigated, and it is shown that the use of multiuser detection can increase the capacity of the ad hoc network significantly for a given level of energy consumption.

  5. Synchronization of chaotic systems and identification of nonlinear systems by using recurrent hierarchical type-2 fuzzy neural networks.

    Science.gov (United States)

    Mohammadzadeh, Ardashir; Ghaemi, Sehraneh

    2015-09-01

    This paper proposes a novel approach for training of proposed recurrent hierarchical interval type-2 fuzzy neural networks (RHT2FNN) based on the square-root cubature Kalman filters (SCKF). The SCKF algorithm is used to adjust the premise part of the type-2 FNN and the weights of defuzzification and the feedback weights. The recurrence property in the proposed network is the output feeding of each membership function to itself. The proposed RHT2FNN is employed in the sliding mode control scheme for the synchronization of chaotic systems. Unknown functions in the sliding mode control approach are estimated by RHT2FNN. Another application of the proposed RHT2FNN is the identification of dynamic nonlinear systems. The effectiveness of the proposed network and its learning algorithm is verified by several simulation examples. Furthermore, the universal approximation of RHT2FNNs is also shown.

  6. On Energy-Efficient Hierarchical Cross-Layer Design: Joint Power Control and Routing for Ad Hoc Networks

    Directory of Open Access Journals (Sweden)

    Poor HVincent

    2007-01-01

    Full Text Available A hierarchical cross-layer design approach is proposed to increase energy efficiency in ad hoc networks through joint adaptation of nodes' transmitting powers and route selection. The design maintains the advantages of the classic OSI model, while accounting for the cross-coupling between layers, through information sharing. The proposed joint power control and routing algorithm is shown to increase significantly the overall energy efficiency of the network, at the expense of a moderate increase in complexity. Performance enhancement of the joint design using multiuser detection is also investigated, and it is shown that the use of multiuser detection can increase the capacity of the ad hoc network significantly for a given level of energy consumption.

  7. Facile solid-state synthesis of Ni@C nanosheet-assembled hierarchical network for high-performance lithium storage

    Science.gov (United States)

    Gu, Jinghe; Li, Qiyun; Zeng, Pan; Meng, Yulin; Zhang, Xiukui; Wu, Ping; Zhou, Yiming

    2017-08-01

    Micro/nano-architectured transition-metal@C hybrids possess unique structural and compositional features toward lithium storage, and are thus expected to manifest ideal anodic performances in advanced lithium-ion batteries (LIBs). Herein, we propose a facile and scalable solid-state coordination and subsequent pyrolysis route for the formation of a novel type of micro/nano-architectured transition-metal@C hybrid (i.e., Ni@C nanosheet-assembled hierarchical network, Ni@C network). Moreover, this coordination-pyrolysis route has also been applied for the construction of bare carbon network using zinc salts instead of nickel salts as precursors. When applied as potential anodic materials in LIBs, the Ni@C network exhibits Ni-content-dependent electrochemical performances, and the partially-etched Ni@C network manifests markedly enhanced Li-storage performances in terms of specific capacities, cycle life, and rate capability than the pristine Ni@C network and carbon network. The proposed solid-state coordination and pyrolysis strategy would open up new opportunities for constructing micro/nano-architectured transition-metal@C hybrids as advanced anode materials for LIBs.

  8. Bistability of mixed states in a neural network storing hierarchical patterns

    Science.gov (United States)

    Toya, Kaname; Fukushima, Kunihiko; Kabashima, Yoshiyuki; Okada, Masato

    2000-04-01

    We discuss the properties of equilibrium states in an autoassociative memory model storing hierarchically correlated patterns (hereafter, hierarchical patterns). We will show that symmetric mixed states (hereafter, mixed states) are bistable on the associative memory model storing the hierarchical patterns in a region of the ferromagnetic phase. This means that the first-order transition occurs in this ferromagnetic phase. We treat these contents with a statistical mechanical method (SCSNA) and by computer simulation. Finally, we discuss a physiological implication of this model. Sugase et al (1999 Nature 400 869) analysed the time-course of the information carried by the firing of face-responsive neurons in the inferior temporal cortex. We also discuss the relation between the theoretical results and the physiological experiments of Sugase et al .

  9. Self-consistent core-pedestal transport simulations with neural network accelerated models

    Science.gov (United States)

    Meneghini, O.; Smith, S. P.; Snyder, P. B.; Staebler, G. M.; Candy, J.; Belli, E.; Lao, L.; Kostuk, M.; Luce, T.; Luda, T.; Park, J. M.; Poli, F.

    2017-08-01

    Fusion whole device modeling simulations require comprehensive models that are simultaneously physically accurate, fast, robust, and predictive. In this paper we describe the development of two neural-network (NN) based models as a means to perform a snon-linear multivariate regression of theory-based models for the core turbulent transport fluxes, and the pedestal structure. Specifically, we find that a NN-based approach can be used to consistently reproduce the results of the TGLF and EPED1 theory-based models over a broad range of plasma regimes, and with a computational speedup of several orders of magnitudes. These models are then integrated into a predictive workflow that allows prediction with self-consistent core-pedestal coupling of the kinetic profiles within the last closed flux surface of the plasma. The NN paradigm is capable of breaking the speed-accuracy trade-off that is expected of traditional numerical physics models, and can provide the missing link towards self-consistent coupled core-pedestal whole device modeling simulations that are physically accurate and yet take only seconds to run.

  10. H-P2PSIP: Interconnection of P2PSIP domains for Global Multimedia Services based on a Hierarchical DHT Overlay Network

    OpenAIRE

    Martínez-Yelmo, Isaías; Bikfalvi, Alex; Cuevas, Rubén; Guerrero, Carmen; García-Reinoso, Jaime

    2009-01-01

    The IETF P2PSIP WG is currently standardising a protocol for distributed mul- timedia services combining the media session functionality of SIP and the decentralised distribution and localisation of resources in peer-to-peer networks. The current P2PSIP scenarios only consider the infrastructure for the connectivity inside a single domain. This paper proposes an extension of the current work to a hierarchical multi-domain scenario: a two level hierarchical peer-to-peer overlay architecture...

  11. Path-finding through flexible hierarchical road networks: An experiential approach using taxi trajectory data

    Science.gov (United States)

    Li, Qingquan; Zeng, Zhe; Zhang, Tong; Li, Jonathan; Wu, Zhongheng

    2011-02-01

    Optimal paths computed by conventional path-planning algorithms are usually not "optimal" since realistic traffic information and local road network characteristics are not considered. We present a new experiential approach that computes optimal paths based on the experience of taxi drivers by mining a huge number of floating car trajectories. The approach consists of three steps. First, routes are recovered from original taxi trajectories. Second, an experiential road hierarchy is constructed using travel frequency and speed information for road segments. Third, experiential optimal paths are planned based on the experiential road hierarchy. Compared with conventional path-planning methods, the proposed method provides better experiential optimal path identification. Experiments demonstrate that the travel time is less for these experiential paths than for paths planned by conventional methods. Results obtained for a case study in the city of Wuhan, China, demonstrate that experiential optimal paths can be flexibly obtained in different time intervals, particularly during peak hours.

  12. Consistent empirical physical formula construction for recoil energy distribution in HPGe detectors using artificial neural networks

    CERN Document Server

    Akkoyun, Serkan

    2012-01-01

    The gamma-ray tracking technique is one of the highly efficient detection method in experimental nuclear structure physics. On the basis of this method, two gamma-ray tracking arrays, AGATA in Europe and GRETA in the USA, are currently being developed. The interactions of neutrons in these detectors lead to an unwanted background in the gamma-ray spectra. Thus, the interaction points of neutrons in these detectors have to be determined in the gamma-ray tracking process in order to improve photo-peak efficiencies and peak-to-total ratios of the gamma-ray peaks. Therefore, the recoil energy distributions of germanium nuclei due to inelastic scatterings of 1-5 MeV neutrons were obtained both experimentally and using artificial neural networks. Also, for highly nonlinear detector response for recoiling germanium nuclei, we have constructed consistent empirical physical formulas (EPFs) by appropriate layered feed-forward neural networks (LFNNs). These LFNN-EPFs can be used to derive further physical functions whic...

  13. Hierarchical spatial segregation of two Mediterranean vole species: the role of patch-network structure and matrix composition.

    Science.gov (United States)

    Pita, Ricardo; Lambin, Xavier; Mira, António; Beja, Pedro

    2016-09-01

    According to ecological theory, the coexistence of competitors in patchy environments may be facilitated by hierarchical spatial segregation along axes of environmental variation, but empirical evidence is limited. Cabrera and water voles show a metapopulation-like structure in Mediterranean farmland, where they are known to segregate along space, habitat, and time axes within habitat patches. Here, we assess whether segregation also occurs among and within landscapes, and how this is influenced by patch-network and matrix composition. We surveyed 75 landscapes, each covering 78 ha, where we mapped all habitat patches potentially suitable for Cabrera and water voles, and the area effectively occupied by each species (extent of occupancy). The relatively large water vole tended to be the sole occupant of landscapes with high habitat amount but relatively low patch density (i.e., with a few large patches), and with a predominantly agricultural matrix, whereas landscapes with high patch density (i.e., many small patches) and low agricultural cover, tended to be occupied exclusively by the small Cabrera vole. The two species tended to co-occur in landscapes with intermediate patch-network and matrix characteristics, though their extents of occurrence were negatively correlated after controlling for environmental effects. In combination with our previous studies on the Cabrera-water vole system, these findings illustrated empirically the occurrence of hierarchical spatial segregation, ranging from within-patches to among-landscapes. Overall, our study suggests that recognizing the hierarchical nature of spatial segregation patterns and their major environmental drivers should enhance our understanding of species coexistence in patchy environments.

  14. Perturbation Detection Through Modeling of Gene Expression on a Latent Biological Pathway Network: A Bayesian hierarchical approach.

    Science.gov (United States)

    Pham, Lisa M; Carvalho, Luis; Schaus, Scott; Kolaczyk, Eric D

    Cellular response to a perturbation is the result of a dynamic system of biological variables linked in a complex network. A major challenge in drug and disease studies is identifying the key factors of a biological network that are essential in determining the cell's fate. Here our goal is the identification of perturbed pathways from high-throughput gene expression data. We develop a three-level hierarchical model, where (i) the first level captures the relationship between gene expression and biological pathways using confirmatory factor analysis, (ii) the second level models the behavior within an underlying network of pathways induced by an unknown perturbation using a conditional autoregressive model, and (iii) the third level is a spike-and-slab prior on the perturbations. We then identify perturbations through posterior-based variable selection. We illustrate our approach using gene transcription drug perturbation profiles from the DREAM7 drug sensitivity predication challenge data set. Our proposed method identified regulatory pathways that are known to play a causative role and that were not readily resolved using gene set enrichment analysis or exploratory factor models. Simulation results are presented assessing the performance of this model relative to a network-free variant and its robustness to inaccuracies in biological databases.

  15. A Resting-State Brain Functional Network Study in MDD Based on Minimum Spanning Tree Analysis and the Hierarchical Clustering

    Directory of Open Access Journals (Sweden)

    Xiaowei Li

    2017-01-01

    Full Text Available A large number of studies demonstrated that major depressive disorder (MDD is characterized by the alterations in brain functional connections which is also identifiable during the brain’s “resting-state.” But, in the present study, the approach of constructing functional connectivity is often biased by the choice of the threshold. Besides, more attention was paid to the number and length of links in brain networks, and the clustering partitioning of nodes was unclear. Therefore, minimum spanning tree (MST analysis and the hierarchical clustering were first used for the depression disease in this study. Resting-state electroencephalogram (EEG sources were assessed from 15 healthy and 23 major depressive subjects. Then the coherence, MST, and the hierarchical clustering were obtained. In the theta band, coherence analysis showed that the EEG coherence of the MDD patients was significantly higher than that of the healthy controls especially in the left temporal region. The MST results indicated the higher leaf fraction in the depressed group. Compared with the normal group, the major depressive patients lost clustering in frontal regions. Our findings suggested that there was a stronger brain interaction in the MDD group and a left-right functional imbalance in the frontal regions for MDD controls.

  16. Energy Efficient Backoff Hierarchical Clustering Algorithms for Multi-Hop Wireless Sensor Networks

    Institute of Scientific and Technical Information of China (English)

    Jun Wang; Yong-Tao Cao; Jun-Yuan Xie; Shi-Fu Chen

    2011-01-01

    Compared with flat routing protocols, clustering is a fundamental performance improvement technique in wireless sensor networks, which can increase network scalability and lifetime. In this paper, we integrate the multi-hop technique with a backoff-based clustering algorithm to organize sensors. By using an adaptive backoff strategy, the algorithm not only realizes load balance among sensor node, but also achieves fairly uniform cluster head distribution across the network. Simulation results also demonstrate our algorithm is more energy-efficient than classical ones. Our algorithm is also easily extended to generate a hierarchy of cluster heads to obtain better network management and energy-efficiency.

  17. Risk Assessment for Mobile Systems Through a Multilayered Hierarchical Bayesian Network.

    Science.gov (United States)

    Li, Shancang; Tryfonas, Theo; Russell, Gordon; Andriotis, Panagiotis

    2016-08-01

    Mobile systems are facing a number of application vulnerabilities that can be combined together and utilized to penetrate systems with devastating impact. When assessing the overall security of a mobile system, it is important to assess the security risks posed by each mobile applications (apps), thus gaining a stronger understanding of any vulnerabilities present. This paper aims at developing a three-layer framework that assesses the potential risks which apps introduce within the Android mobile systems. A Bayesian risk graphical model is proposed to evaluate risk propagation in a layered risk architecture. By integrating static analysis, dynamic analysis, and behavior analysis in a hierarchical framework, the risks and their propagation through each layer are well modeled by the Bayesian risk graph, which can quantitatively analyze risks faced to both apps and mobile systems. The proposed hierarchical Bayesian risk graph model offers a novel way to investigate the security risks in mobile environment and enables users and administrators to evaluate the potential risks. This strategy allows to strengthen both app security as well as the security of the entire system.

  18. Inference of hierarchical regulatory network of estrogen-dependent breast cancer through ChIP-based data

    Directory of Open Access Journals (Sweden)

    Parvin Jeffrey

    2010-12-01

    Full Text Available Abstract Background Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks. Results In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2 were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM. A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes. We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes and targeted TFs (25% of common TFs. The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells. Conclusions Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to

  19. Inference of hierarchical regulatory network of estrogen-dependent breast cancer through ChIP-based data

    Science.gov (United States)

    2010-01-01

    Background Global profiling of in vivo protein-DNA interactions using ChIP-based technologies has evolved rapidly in recent years. Although many genome-wide studies have identified thousands of ERα binding sites and have revealed the associated transcription factor (TF) partners, such as AP1, FOXA1 and CEBP, little is known about ERα associated hierarchical transcriptional regulatory networks. Results In this study, we applied computational approaches to analyze three public available ChIP-based datasets: ChIP-seq, ChIP-PET and ChIP-chip, and to investigate the hierarchical regulatory network for ERα and ERα partner TFs regulation in estrogen-dependent breast cancer MCF7 cells. 16 common TFs and two common new TF partners (RORA and PITX2) were found among ChIP-seq, ChIP-chip and ChIP-PET datasets. The regulatory networks were constructed by scanning the ChIP-peak region with TF specific position weight matrix (PWM). A permutation test was performed to test the reliability of each connection of the network. We then used DREM software to perform gene ontology function analysis on the common genes. We found that FOS, PITX2, RORA and FOXA1 were involved in the up-regulated genes. We also conducted the ERα and Pol-II ChIP-seq experiments in tamoxifen resistance MCF7 cells (denoted as MCF7-T in this study) and compared the difference between MCF7 and MCF7-T cells. The result showed very little overlap between these two cells in terms of targeted genes (21.2% of common genes) and targeted TFs (25% of common TFs). The significant dissimilarity may indicate totally different transcriptional regulatory mechanisms between these two cancer cells. Conclusions Our study uncovers new estrogen-mediated regulatory networks by mining three ChIP-based data in MCF7 cells and ChIP-seq data in MCF7-T cells. We compared the different ChIP-based technologies as well as different breast cancer cells. Our computational analytical approach may guide biologists to further study the

  20. Cross-linked carbon network with hierarchical porous structure for high performance solid-state electrochemical capacitor

    Science.gov (United States)

    Cheng, Yongliang; Huang, Liang; Xiao, Xu; Yao, Bin; Hu, Zhimi; Li, Tianqi; Liu, Kang; Zhou, Jun

    2016-09-01

    The development of portable electronics strongly requires flexible, lightweight, and inexpensive energy-storage devices with high power density, long cycling stability, and high reliability. In this work, we prepare a flexible solid-state electrochemical capacitor using cross-linked hierarchical porous carbon network as electrode material via electrospinning and carbonization process. This device can reversibly deliver a maximum energy density of 10.18 W h/kg with excellent cycling stability which achieves 95% capacitance retention after 20000 charge/discharge cycles. Moreover, it also demonstrates outstanding mechanical flexibility and excellent capacitance retention even when the device is repeatedly bended 10000 cycles under 90°. All of these results suggest its promising perspective in flexible energy storage device.

  1. Virtual and Dynamic Hierarchical Architecture:an overlay network topology for discovering grid services with high performance

    Institute of Scientific and Technical Information of China (English)

    黄理灿; 吴朝晖; 潘云鹤

    2004-01-01

    This paper presents an overlay network topology called Virtual and Dynamic Hierarchical Architecture (VDHA) for discovering Grid services with high performance. Service discovery based on VDHA has scalable, autonomous, efficient, reliable and quick responsive. We propose two service discovery algorithms. Full Search Query and Discovery Protocol (FSQDP) discovers the nodes that match the request message from all N nodes, which has time complexity O(logN), space complexity O(nvg) (nvg being node numbers of each virtual group), and message-cost O(N), and Domain-Specific Query and Discovery Protocol (DSQDP) searches nodes in only specific domains with time complexity O(nvg), space complexity O(nvg), and message-cost O(nvg). In this paper, we also describe VDHA, its formal definition, and Grid Group Management Protocol.

  2. Criticality governed by the stable renormalization fixed point of the Ising model in the hierarchical small-world network.

    Science.gov (United States)

    Nogawa, Tomoaki; Hasegawa, Takehisa; Nemoto, Koji

    2012-09-01

    We study the Ising model in a hierarchical small-world network by renormalization group analysis and find a phase transition between an ordered phase and a critical phase, which is driven by the coupling strength of the shortcut edges. Unlike ordinary phase transitions, which are related to unstable renormalization fixed points (FPs), the singularity in the ordered phase of the present model is governed by the FP that coincides with the stable FP of the ordered phase. The weak stability of the FP yields peculiar criticalities, including logarithmic behavior. On the other hand, the critical phase is related to a nontrivial FP, which depends on the coupling strength and is continuously connected to the ordered FP at the transition point. We show that this continuity indicates the existence of a finite correlation-length-like quantity inside the critical phase, which diverges upon approaching the transition point.

  3. Hierarchical Group Based Mutual Authentication and Key Agreement for Machine Type Communication in LTE and Future 5G Networks

    Directory of Open Access Journals (Sweden)

    Probidita Roychoudhury

    2017-01-01

    Full Text Available In view of the exponential growth in the volume of wireless data communication among heterogeneous devices ranging from smart phones to tiny sensors across a wide range of applications, 3GPP LTE-A has standardized Machine Type Communication (MTC which allows communication between entities without any human intervention. The future 5G cellular networks also envisage massive deployment of MTC Devices (MTCDs which will increase the total number of connected devices hundredfold. This poses a huge challenge to the traditional cellular system processes, especially the traditional Mutual Authentication and Key Agreement (AKA mechanism currently used in LTE systems, as the signaling load caused by the increasingly large number of devices may have an adverse effect on the regular Human to Human (H2H traffic. A solution in the literature has been the use of group based architecture which, while addressing the authentication traffic, has their share of issues. This paper introduces Hierarchical Group based Mutual Authentication and Key Agreement (HGMAKA protocol to address those issues and also enables the small cell heterogeneous architecture in line with 5G networks to support MTC services. The aggregate Message Authentication Code based approach has been shown to be lightweight and significantly efficient in terms of resource usage compared to the existing protocols, while being robust to authentication message failures, and scalable to heterogeneous network architectures.

  4. RAHIM: Robust Adaptive Approach Based on Hierarchical Monitoring Providing Trust Aggregation for Wireless Sensor Networks

    NARCIS (Netherlands)

    Labraoui, Nabila; Gueroui, Mourad; Aliouat, Makhlouf; Petit, Jonathan

    2011-01-01

    In-network data aggregation has a great impact on the energy consumption in large-scale wireless sensor networks. However, the resource constraints and vulnerable deployment environments challenge the application of this technique in terms of security and efficiency. A compromised node may forge

  5. RAHIM: Robust Adaptive Approach Based on Hierarchical Monitoring Providing Trust Aggregation for Wireless Sensor Networks

    NARCIS (Netherlands)

    Labraoui, Nabila; Gueroui, Mourad; Aliouat, Makhlouf; Petit, Jonathan

    2011-01-01

    In-network data aggregation has a great impact on the energy consumption in large-scale wireless sensor networks. However, the resource constraints and vulnerable deployment environments challenge the application of this technique in terms of security and efficiency. A compromised node may forge arb

  6. Self-organized Critical Model Based on Complex Brain Networks with Hierarchical Organization

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ying-Yue; ZHANG Gui-Qing; YANG Qiu-Ying; CHEN Tian-Lun

    2008-01-01

    The dynamical behavior in the cortical brain network of macaque is studied by modelling each cortical area with a subnetwork of interacting excitable neurons.We find that the avalanche of our model on different levels exhibits power-law.Furthermore the power-law exponent of the distribution and the average avalanche Size are affected by the topology of the network.

  7. On the use of topological features and hierarchical characterization for disambiguating names in collaborative networks

    CERN Document Server

    Amancio, Diego R; Costa, Luciano da F; 10.1209/0295-5075/99/48002

    2013-01-01

    Many features of complex systems can now be unveiled by applying statistical physics methods to treat them as social networks. The power of the analysis may be limited, however, by the presence of ambiguity in names, e.g., caused by homonymy in collaborative networks. In this paper we show that the ability to distinguish between homonymous authors is enhanced when longer-distance connections are considered, rather than looking at only the immediate neighbors of a node in the collaborative network. Optimized results were obtained upon using the 3rd hierarchy in connections. Furthermore, reasonable distinction among authors could also be achieved upon using pattern recognition strategies for the data generated from the topology of the collaborative network. These results were obtained with a network from papers in the arXiv repository, into which homonymy was deliberately introduced to test the methods with a controlled, reliable dataset. In all cases, several methods of supervised and unsupervised machine lear...

  8. A data management proposal to connect in a hierarchical way nodes of the Spanish Long Term Ecological Research (LTER) network

    Science.gov (United States)

    Fuentes, Daniel; Pérez-Luque, Antonio J.; Bonet García, Francisco J.; Moreno-LLorca, Ricardo A.; Sánchez-Cano, Francisco M.; Suárez-Muñoz, María

    2017-04-01

    The Long Term Ecological Research (LTER) network aims to provide the scientific community, policy makers, and society with the knowledge and predictive understanding necessary to conserve, protect, and manage the ecosystems. LTER is organized into networks ranging from the global to national scale. In the top of network, the International Long Term Ecological Research (ILTER) Network coordinates among ecological researchers and LTER research networks at local, regional and global scales. In Spain, the Spanish Long Term Ecological Research (LTER-Spain) network was built to foster the collaboration and coordination between longest-lived ecological researchers and networks on a local scale. Currently composed by nine nodes, this network facilitates the data exchange, documentation and preservation encouraging the development of cross-disciplinary works. However, most nodes have no specific information systems, tools or qualified personnel to manage their data for continued conservation and there are no harmonized methodologies for long-term monitoring protocols. Hence, the main challenge is to place the nodes in its correct position in the network, providing the best tools that allow them to manage their data autonomously and make it easier for them to access information and knowledge in the network. This work proposes a connected structure composed by four LTER nodes located in southern Spain. The structure is built considering hierarchical approach: nodes that create information which is documented using metadata standards (such as Ecological Metadata Language, EML); and others nodes that gather metadata and information. We also take into account the capacity of each node to manage their own data and the premise that the data and metadata must be maintained where it is generated. The current state of the nodes is a follows: two of them have their own information management system (Sierra Nevada-Granada and Doñana Long-Term Socio-ecological Research Platform) and

  9. Brain networks for confidence weighting and hierarchical inference during probabilistic learning.

    Science.gov (United States)

    Meyniel, Florent; Dehaene, Stanislas

    2017-05-09

    Learning is difficult when the world fluctuates randomly and ceaselessly. Classical learning algorithms, such as the delta rule with constant learning rate, are not optimal. Mathematically, the optimal learning rule requires weighting prior knowledge and incoming evidence according to their respective reliabilities. This "confidence weighting" implies the maintenance of an accurate estimate of the reliability of what has been learned. Here, using fMRI and an ideal-observer analysis, we demonstrate that the brain's learning algorithm relies on confidence weighting. While in the fMRI scanner, human adults attempted to learn the transition probabilities underlying an auditory or visual sequence, and reported their confidence in those estimates. They knew that these transition probabilities could change simultaneously at unpredicted moments, and therefore that the learning problem was inherently hierarchical. Subjective confidence reports tightly followed the predictions derived from the ideal observer. In particular, subjects managed to attach distinct levels of confidence to each learned transition probability, as required by Bayes-optimal inference. Distinct brain areas tracked the likelihood of new observations given current predictions, and the confidence in those predictions. Both signals were combined in the right inferior frontal gyrus, where they operated in agreement with the confidence-weighting model. This brain region also presented signatures of a hierarchical process that disentangles distinct sources of uncertainty. Together, our results provide evidence that the sense of confidence is an essential ingredient of probabilistic learning in the human brain, and that the right inferior frontal gyrus hosts a confidence-based statistical learning algorithm for auditory and visual sequences.

  10. Two-user opportunistic scheduling using hierarchical modulations in wireless networks with heterogenous average link gains

    KAUST Repository

    Hossain, Md Jahangir

    2010-03-01

    Our contribution, in this paper, is two-fold. First, we analyze the performance of a hierarchical modulation-assisted two-best user opportunistic scheduling (TBS) scheme, which was proposed by the authors, in a fading environment where different users have different average link gains. Specifically, we present a new expression for the spectral efficiency (SE) of the users and using this expression, we compare the degrees of fairness (DOF) of the TBS scheme with that of classical single user opportunistic scheduling schemes, namely, absolute carrier-to-noise ratio (CNR) based single-best user scheduling (SBS) and normalized CNR based proportional fair scheduling (PFS) schemes. The second contribution is that we propose a new hybrid two-user opportunistic scheduling (HTS) scheme based on our earlier proposed TBS scheme. This HTS scheme selects the first user based on the largest absolute CNR value among all the users while the second user is selected based on the ratios of the absolute CNRs to the corresponding average CNRs of the remaining users. The total transmission rate i.e., the constellation size is selected according to the absolute CNR of the first best user. The total transmission rate is then allocated among these selected users by joint consideration of their absolute CNRs and allocated number of information bit(s) are transmitted to them using hierarchical modulations. Numerical results are presented for a fading environment where different users experience independent but non-identical (i.n.d.) channel fading. These selected numerical results show that the proposed HTS scheme can considerably increase the system\\'s fairness without any degradation of the link spectral efficiency (LSE) i.e., the multiuser diversity gain compared to the classical SBS scheme. These results also show that the proposed HTS scheme has a lower fairness in comparison to the PFS scheme which suffers from a considerable degradation in LSE. © 2010 IEEE.

  11. A Distance Metric for Tree-Sibling Time Consistent Phylogenetic Networks

    CERN Document Server

    Cardona, Gabriel; Rossello, Francesc; Valiente, Gabriel

    2008-01-01

    The presence of reticulate evolutionary events in phylogenies turn phylogenetic trees into phylogenetic networks. These events imply in particular that there may exist multiple evolutionary paths from a non-extant species to an extant one, and this multiplicity makes the comparison of phylogenetic networks much more difficult than the comparison of phylogenetic trees. In fact, all attempts to define a sound distance measure on the class of all phylogenetic networks have failed so far. Thus, the only practical solutions have been either the use of rough estimates of similarity (based on comparison of the trees embedded in the networks), or narrowing the class of phylogenetic networks to a certain class where such a distance is known and can be efficiently computed. The first approach has the problem that one may identify two networks as equivalent, when they are not; the second one has the drawback that there may not exist algorithms to reconstruct such networks from biological sequences. We present in this pa...

  12. Hierarchical winner-take-all particle swarm optimization social network for neural model fitting.

    Science.gov (United States)

    Coventry, Brandon S; Parthasarathy, Aravindakshan; Sommer, Alexandra L; Bartlett, Edward L

    2017-02-01

    Particle swarm optimization (PSO) has gained widespread use as a general mathematical programming paradigm and seen use in a wide variety of optimization and machine learning problems. In this work, we introduce a new variant on the PSO social network and apply this method to the inverse problem of input parameter selection from recorded auditory neuron tuning curves. The topology of a PSO social network is a major contributor to optimization success. Here we propose a new social network which draws influence from winner-take-all coding found in visual cortical neurons. We show that the winner-take-all network performs exceptionally well on optimization problems with greater than 5 dimensions and runs at a lower iteration count as compared to other PSO topologies. Finally we show that this variant of PSO is able to recreate auditory frequency tuning curves and modulation transfer functions, making it a potentially useful tool for computational neuroscience models.

  13. Hierarchical block structures and high-resolution model selection in large networks

    CERN Document Server

    Peixoto, Tiago P

    2013-01-01

    Discovering the large-scale topological features in empirical networks is a crucial tool in understanding how complex systems function. However most existing methods used to obtain the modular structure of networks suffer from serious problems, such as the resolution limit on the size of communities, where smaller but well-defined clusters are not detectable when the network becomes large. This phenomenon occurs for the very popular approach of modularity optimization, but also for more principled ones based on statistical inference and model selection. Here we construct a nested generative model which, through a complete description of the entire network hierarchy at multiple scales, is capable of avoiding this limitation, and enables the detection of modular structure at levels far beyond those possible by current approaches. Even with this increased resolution, the method is based on the principle of parsimony, and is capable of separating signal from noise, and thus will not lead to the identification of ...

  14. Multipath Routing for Self-Organizing Hierarchical Mobile Ad-Hoc Networks – A Review

    OpenAIRE

    Udayachandran Ramasamy; Sankaranarayanan, K.

    2010-01-01

    Security has become a primary concern for providing protected communication between mobile nodes in a hostile environment. The characteristics of Ad-hoc networks (dynamic topology, infrastructure less, variable capacity links, etc) are origin of many issues. Limited bandwidth, energy constraints, high cost security are the encountered problems. This type of networks pose particular challenges in terms of Quality of Service (QoS) and performance. In this paper, the issues of multipath routing ...

  15. Inter-Cluster Routing Authentication for Ad Hoc Networks by a Hierarchical Key Scheme

    Institute of Scientific and Technical Information of China (English)

    Yueh-Min Huang; Hua-Yi Lin; Tzone-I Wang

    2006-01-01

    Dissimilar to traditional networks, the features of mobile wireless devices that can actively form a network without any infrastructure mean that mobile ad hoc networks frequently display partition due to node mobility or link failures. These indicate that an ad hoc network is difficult to provide on-line access to a trusted authority server. Therefore,applying traditional Public Key Infrastructure (PKI) security framework to mobile ad hoc networks will cause insecurities.This study proposes a scalable and elastic key management scheme integrated into Cluster Based Secure Routing Protocol (CBSRP) to enhance security and non-repudiation of routing authentication, and introduces an ID-Based internal routing authentication scheme to enhance the routing performance in an internal cluster. Additionally, a method of performing routing authentication between internal and external clusters, as well as inter-cluster routing authentication, is developed.The proposed cluster-based key management scheme distributes trust to an aggregation of cluster heads using a threshold scheme faculty, provides Certificate Authority (CA) with a fault tolerance mechanism to prevent a single point of compromise or failure, and saves CA large repositories from maintaining member certificates, making ad hoc networks robust to malicious behaviors and suitable for numerous mobile devices.

  16. Hierarchical networks of redox-active reduced crumpled graphene oxide and functionalized few-walled carbon nanotubes for rapid electrochemical energy storage

    Science.gov (United States)

    Lee, Byeongyong; Lee, Chongmin; Liu, Tianyuan; Eom, Kwangsup; Chen, Zhongming; Noda, Suguru; Fuller, Thomas F.; Jang, Hee Dong; Lee, Seung Woo

    2016-06-01

    Crumpled graphene is known to have a strong aggregation-resistive property due to its unique 3D morphology, providing a promising solution to prevent the restacking issue of graphene based electrode materials. Here, we demonstrate the utilization of redox-active oxygen functional groups on the partially reduced crumpled graphene oxide (r-CGO) for electrochemical energy storage applications. To effectively utilize the surface redox reactions of the functional groups, hierarchical networks of electrodes including r-CGO and functionalized few-walled carbon nanotubes (f-FWNTs) are assembled via a vacuum-filtration process, resulting in a 3D porous structure. These composite electrodes are employed as positive electrodes in Li-cells, delivering high gravimetric capacities of up to ~170 mA h g-1 with significantly enhanced rate-capability compared to the electrodes consisting of conventional 2D reduced graphene oxide and f-FWNTs. These results highlight the importance of microstructure design coupled with oxygen chemistry control, to maximize the surface redox reactions on functionalized graphene based electrodes.Crumpled graphene is known to have a strong aggregation-resistive property due to its unique 3D morphology, providing a promising solution to prevent the restacking issue of graphene based electrode materials. Here, we demonstrate the utilization of redox-active oxygen functional groups on the partially reduced crumpled graphene oxide (r-CGO) for electrochemical energy storage applications. To effectively utilize the surface redox reactions of the functional groups, hierarchical networks of electrodes including r-CGO and functionalized few-walled carbon nanotubes (f-FWNTs) are assembled via a vacuum-filtration process, resulting in a 3D porous structure. These composite electrodes are employed as positive electrodes in Li-cells, delivering high gravimetric capacities of up to ~170 mA h g-1 with significantly enhanced rate-capability compared to the electrodes

  17. Efficient hierarchical analysis of the stability of a network through dimensional reduction of its influence topology

    CERN Document Server

    Kinkhabwala, Ali

    2013-01-01

    The connection between network topology and stability remains unclear. General approaches that clarify this relationship and allow for more efficient stability analysis would be desirable. In this manuscript, I examine the mathematical notion of influence topology, which is fundamentally based on the network reaction stoichiometries and the first derivatives of the reactions with respect to each species at the steady state solution(s). The influence topology is naturally represented as a signed directed bipartite graph with arrows or blunt arrows connecting a species node to a reaction node (positive/negative derivative) or a reaction node to a species node (positive/negative stoichiometry). The set of all such graphs is denumerable. A significant reduction in dimensionality is possible through stoichiometric scaling, cycle compaction, and temporal scaling. All cycles in a network can be read directly from the graph of its influence topology, enabling efficient and intuitive computation of the principal minor...

  18. Investigation on overlapping interference on VLC networks consisting of multiple LEDs

    Directory of Open Access Journals (Sweden)

    Nan Chi

    2015-09-01

    Full Text Available Visible light communication (VLC has become an alternative candidate in next-generation indoor wireless local area network. However, it is a great challenge for a receiver to obtain the signals from multiple LED sources that transmit different information. In this paper, we explore the BER degradation due to the overlapping of multiple LED sources in the visible light communication network. We experimentally demonstrate a Multiple Input Signal Output (MISO VLC system utilizing space–time block coding (STBC to overcome the signal interference due to multiple inputs. A throughput of 1.6 Gbit/s is successfully achieved, which reveals great improvement in the robustness and compatibility of LED based network system.

  19. Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity

    Directory of Open Access Journals (Sweden)

    Benjamin eDummer

    2014-09-01

    Full Text Available A major source of random variability in cortical networks is the quasi-random arrival of presynaptic action potentials from many other cells. In network studies as well as in the study of the response properties of single cells embedded in a network, synaptic background input is often approximated by Poissonian spike trains. However, the output statistics of the cells is in most cases far from being Poisson. This is inconsistent with the assumption of similar spike-train statistics for pre- and postsynaptic cells in a recurrent network. Here we tackle this problem for the popular class of integrate-and-fire neurons and study a self-consistent statistics of input and output spectra of neural spike trains. Instead of actually using a large network, we use an iterative scheme, in which we simulate a single neuron over several generations. In each of these generations, the neuron is stimulated with surrogate stochastic input that has a similar statistics as the output of the previous generation. For the surrogate input, we employ two distinct approximations: (i a superposition of renewal spike trains with the same interspike interval density as observed in the previous generation and (ii a Gaussian current with a power spectrum proportional to that observed in the previous generation. For input parameters that correspond to balanced input in the network, both the renewal and the Gaussian iteration procedure converge quickly and yield comparable results for the self-consistent spike-train power spectrum. We compare our results to large-scale simulations of a random sparsely connected network of leaky integrate-and-fire neurons (Brunel, J. Comp. Neurosci. 2000 and show that in the asynchronous regime close to a state of balanced synaptic input from the network, our iterative schemes provide excellent approximations to the autocorrelation of spike trains in the recurrent network.

  20. Self-consistent determination of the spike-train power spectrum in a neural network with sparse connectivity.

    Science.gov (United States)

    Dummer, Benjamin; Wieland, Stefan; Lindner, Benjamin

    2014-01-01

    A major source of random variability in cortical networks is the quasi-random arrival of presynaptic action potentials from many other cells. In network studies as well as in the study of the response properties of single cells embedded in a network, synaptic background input is often approximated by Poissonian spike trains. However, the output statistics of the cells is in most cases far from being Poisson. This is inconsistent with the assumption of similar spike-train statistics for pre- and postsynaptic cells in a recurrent network. Here we tackle this problem for the popular class of integrate-and-fire neurons and study a self-consistent statistics of input and output spectra of neural spike trains. Instead of actually using a large network, we use an iterative scheme, in which we simulate a single neuron over several generations. In each of these generations, the neuron is stimulated with surrogate stochastic input that has a similar statistics as the output of the previous generation. For the surrogate input, we employ two distinct approximations: (i) a superposition of renewal spike trains with the same interspike interval density as observed in the previous generation and (ii) a Gaussian current with a power spectrum proportional to that observed in the previous generation. For input parameters that correspond to balanced input in the network, both the renewal and the Gaussian iteration procedure converge quickly and yield comparable results for the self-consistent spike-train power spectrum. We compare our results to large-scale simulations of a random sparsely connected network of leaky integrate-and-fire neurons (Brunel, 2000) and show that in the asynchronous regime close to a state of balanced synaptic input from the network, our iterative schemes provide an excellent approximations to the autocorrelation of spike trains in the recurrent network.

  1. Bayesian hierarchical models for network meta-analysis incorporating nonignorable missingness.

    Science.gov (United States)

    Zhang, Jing; Chu, Haitao; Hong, Hwanhee; Virnig, Beth A; Carlin, Bradley P

    2015-07-28

    Network meta-analysis expands the scope of a conventional pairwise meta-analysis to simultaneously compare multiple treatments, synthesizing both direct and indirect information and thus strengthening inference. Since most of trials only compare two treatments, a typical data set in a network meta-analysis managed as a trial-by-treatment matrix is extremely sparse, like an incomplete block structure with significant missing data. Zhang et al. proposed an arm-based method accounting for correlations among different treatments within the same trial and assuming that absent arms are missing at random. However, in randomized controlled trials, nonignorable missingness or missingness not at random may occur due to deliberate choices of treatments at the design stage. In addition, those undertaking a network meta-analysis may selectively choose treatments to include in the analysis, which may also lead to missingness not at random. In this paper, we extend our previous work to incorporate missingness not at random using selection models. The proposed method is then applied to two network meta-analyses and evaluated through extensive simulation studies. We also provide comprehensive comparisons of a commonly used contrast-based method and the arm-based method via simulations in a technical appendix under missing completely at random and missing at random.

  2. AtPID: the overall hierarchical functional protein interaction network interface and analytic platform for Arabidopsis.

    Science.gov (United States)

    Li, Peng; Zang, Weidong; Li, Yuhua; Xu, Feng; Wang, Jigang; Shi, Tieliu

    2011-01-01

    Protein interactions are involved in important cellular functions and biological processes that are the fundamentals of all life activities. With improvements in experimental techniques and progress in research, the overall protein interaction network frameworks of several model organisms have been created through data collection and integration. However, most of the networks processed only show simple relationships without boundary, weight or direction, which do not truly reflect the biological reality. In vivo, different types of protein interactions, such as the assembly of protein complexes or phosphorylation, often have their specific functions and qualifications. Ignorance of these features will bring much bias to the network analysis and application. Therefore, we annotate the Arabidopsis proteins in the AtPID database with further information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways. The latest updated AtPID database is available at http://www.megabionet.org/atpid/.

  3. Viscoelasticity of networks consisting of crosslinked or entangled macromolecules. I. normal modes and mechanical spectra

    NARCIS (Netherlands)

    Chompff, A.J.; Duiser, J.A.

    1966-01-01

    A molecular theory is developed to describe quantitatively the mechanical behavior of entanglement networks of linear, randomly coiling molecules. The theory is based on the model of Rouse for a single molecule and is a generalization of the theory of Duiser and Staverman for chemically crosslinked

  4. Hebbian learning of hand-centred representations in a hierarchical neural network model of the primate visual system.

    Science.gov (United States)

    Born, Jannis; Galeazzi, Juan M; Stringer, Simon M

    2017-01-01

    A subset of neurons in the posterior parietal and premotor areas of the primate brain respond to the locations of visual targets in a hand-centred frame of reference. Such hand-centred visual representations are thought to play an important role in visually-guided reaching to target locations in space. In this paper we show how a biologically plausible, Hebbian learning mechanism may account for the development of localized hand-centred representations in a hierarchical neural network model of the primate visual system, VisNet. The hand-centered neurons developed in the model use an invariance learning mechanism known as continuous transformation (CT) learning. In contrast to previous theoretical proposals for the development of hand-centered visual representations, CT learning does not need a memory trace of recent neuronal activity to be incorporated in the synaptic learning rule. Instead, CT learning relies solely on a Hebbian learning rule, which is able to exploit the spatial overlap that naturally occurs between successive images of a hand-object configuration as it is shifted across different retinal locations due to saccades. Our simulations show how individual neurons in the network model can learn to respond selectively to target objects in particular locations with respect to the hand, irrespective of where the hand-object configuration occurs on the retina. The response properties of these hand-centred neurons further generalise to localised receptive fields in the hand-centred space when tested on novel hand-object configurations that have not been explored during training. Indeed, even when the network is trained with target objects presented across a near continuum of locations around the hand during training, the model continues to develop hand-centred neurons with localised receptive fields in hand-centred space. With the help of principal component analysis, we provide the first theoretical framework that explains the behavior of Hebbian learning

  5. Hierarchal Variable Switching Sets of Interacting Multiple Model for Tracking Maneuvering Targets in Sensor Network

    Directory of Open Access Journals (Sweden)

    Seham Moawoud Ay Ebrahim

    2013-01-01

    Full Text Available Tracking maneuvering targets introduce two major directions to improve the Multiple Model (MM approach: Develop a better MM algorithm and design a better model set. The Interacting Multiple Model (IMM estimator is a suboptimal hybrid filter that has been shown to be one of the most cost-effective hybrid state estimation schemes. The main feature of this algorithm is the ability to estimate the state of a dynamic system with several behavior modes which can "switch" from one to another. In particular, the use of too many models is performance-wise as bad as that of too few models. In this paper we show that the use of too many models is performance-wise as bad as that of too few models. To overcome this we divide the models into a small number of sets, tuning these sets during operation at the right operating set. We proposed Hierarchal Switching sets of IMM (HSIMM. The state space of the nonlinear variable is divided into sets each set has its own IMM. The connection between them is the switching algorithm which manages the activation and termination of sets. Also the re-initialization process overcomes the error accumulation due to the targets changes from one model to another. This switching can introduce a number of different models while no restriction on their number. The activation of sets depends on the threshold value of set likely hood. As the likely hood of the set is higher than threshold it is active otherwise it is minimized. The result is the weighted sum of the output of active sets. The computational time is minimum than introduced by IMM and VIMM. HSIMM introduces less error as the noise increase and there is no need for re adjustment to the Covariance as the noise increase so it is more robust against noise and introduces minimum computational time.

  6. Optimizing data access for wind farm control over hierarchical communication networks

    DEFF Research Database (Denmark)

    Madsen, Jacob Theilgaard; Findrik, Mislav; Madsen, Tatiana Kozlova

    2016-01-01

    and communication networks on the controller performance. We start by investigating the effects of a communication network that introduces delays in the information access for the central controller. The control performance as measured by accumulated fatigue is shown to be significantly impacted by communication....... This information quality metric is called mismatch probability, mmPr, and is used to express quantitatively the information accuracy in a given scenario. Lastly measurements of different communication technologies have been performed in order to carry out the analysis in a practically relevant scenario......In this paper we investigate a centralized wind farm controller which runs periodically. The controller attempts to reduce the damage a wind turbine sustains during operation by estimating fatigue based on the wind turbine state. The investigation focuses on the impact of information access...

  7. A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America.

    Directory of Open Access Journals (Sweden)

    Ling Xue

    Full Text Available Rift Valley fever is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease vectors and hosts will be vital for developing mitigation strategies. Presented here is a general network-based mathematical model of Rift Valley fever. Given a lack of empirical data on disease vector species and their vector competence, this discrete time epidemic model uses stochastic parameters following several PERT distributions to model the dynamic interactions between hosts and likely North American mosquito vectors in dispersed geographic areas. Spatial effects and climate factors are also addressed in the model. The model is applied to a large directed asymmetric network of 3,621 nodes based on actual farms to examine a hypothetical introduction to some counties of Texas, an important ranching area in the United States of America. The nodes of the networks represent livestock farms, livestock markets, and feedlots, and the links represent cattle movements and mosquito diffusion between different nodes. Cattle and mosquito (Aedes and Culex populations are treated with different contact networks to assess virus propagation. Rift Valley fever virus spread is assessed under various initial infection conditions (infected mosquito eggs, adults or cattle. A surprising trend is fewer initial infectious organisms result in a longer delay before a larger and more prolonged outbreak. The delay is likely caused by a lack of herd immunity while the infection expands geographically before becoming an epidemic involving many dispersed farms and animals almost simultaneously. Cattle movement between farms is a large driver of virus expansion, thus quarantines can be efficient mitigation strategy to prevent further geographic spread.

  8. A hierarchical network approach for modeling Rift Valley fever epidemics with applications in North America.

    Science.gov (United States)

    Xue, Ling; Cohnstaedt, Lee W; Scott, H Morgan; Scoglio, Caterina

    2013-01-01

    Rift Valley fever is a vector-borne zoonotic disease which causes high morbidity and mortality in livestock. In the event Rift Valley fever virus is introduced to the United States or other non-endemic areas, understanding the potential patterns of spread and the areas at risk based on disease vectors and hosts will be vital for developing mitigation strategies. Presented here is a general network-based mathematical model of Rift Valley fever. Given a lack of empirical data on disease vector species and their vector competence, this discrete time epidemic model uses stochastic parameters following several PERT distributions to model the dynamic interactions between hosts and likely North American mosquito vectors in dispersed geographic areas. Spatial effects and climate factors are also addressed in the model. The model is applied to a large directed asymmetric network of 3,621 nodes based on actual farms to examine a hypothetical introduction to some counties of Texas, an important ranching area in the United States of America. The nodes of the networks represent livestock farms, livestock markets, and feedlots, and the links represent cattle movements and mosquito diffusion between different nodes. Cattle and mosquito (Aedes and Culex) populations are treated with different contact networks to assess virus propagation. Rift Valley fever virus spread is assessed under various initial infection conditions (infected mosquito eggs, adults or cattle). A surprising trend is fewer initial infectious organisms result in a longer delay before a larger and more prolonged outbreak. The delay is likely caused by a lack of herd immunity while the infection expands geographically before becoming an epidemic involving many dispersed farms and animals almost simultaneously. Cattle movement between farms is a large driver of virus expansion, thus quarantines can be efficient mitigation strategy to prevent further geographic spread.

  9. Non-Linear Behaviour Of Gelatin Networks Reveals A Hierarchical Structure

    KAUST Repository

    Yang, Zhi

    2015-12-14

    We investigate the strain hardening behaviour of various gelatin networks - namely physically-crosslinked gelatin gel, chemically-crosslinked gelatin gels, and a hybrid gels made of a combination of the former two - under large shear deformations using the pre-stress, strain ramp, and large amplitude oscillation shear protocols. Further, the internal structures of physically-crosslinked gelatin gel and chemically-crosslinked gelatin gels were characterized by small angle neutron scattering (SANS) to enable their internal structures to be correlated with their nonlinear rheology. The Kratky plots of SANS data demonstrate the presence of small cross-linked aggregates within the chemically-crosslinked network, whereas in the physically-crosslinked gels a relatively homogeneous structure is observed. Through model fitting to the scattering data, we were able to obtain structural parameters, such as correlation length (ξ), cross-sectional polymer chain radius (Rc), and the fractal dimension (df) of the gel networks. The fractal dimension df obtained from the SANS data of the physically-crosslinked and chemically crosslinked gels is 1.31 and 1.53, respectively. These values are in excellent agreement with the ones obtained from a generalized non-linear elastic theory we used to fit our stress-strain curves. The chemical crosslinking that generates coils and aggregates hinders the free stretching of the triple helices bundles in the physically-crosslinked gels.

  10. Admission Control for Multiservices Traffic in Hierarchical Mobile IPv6 Networks by Using Fuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Jung-Shyr Wu

    2012-01-01

    Full Text Available CAC (Call Admission Control plays a significant role in providing QoS (Quality of Service in mobile wireless networks. In addition to much research that focuses on modified Mobile IP to get better efficient handover performance, CAC should be introduced to Mobile IP-based network to guarantee the QoS for users. In this paper, we propose a CAC scheme which incorporates multiple traffic types and adjusts the admission threshold dynamically using fuzzy control logic to achieve better usage of resources. The method can provide QoS in Mobile IPv6 networks with few modifications on MAP (Mobility Anchor Point functionality and slight change in BU (Binding Update message formats. According to the simulation results, the proposed scheme presents good performance of voice and video traffic at the expenses of poor performance on data traffic. It is evident that these CAC schemes can reduce the probability of the handoff dropping and the cell overload and limit the probability of the new call blocking.

  11. Energy Efficient Zone Division Multihop Hierarchical Clustering Algorithm for Load Balancing in Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Ashim Kumar Ghosh

    2011-12-01

    Full Text Available Wireless sensor nodes are use most embedded computing application. Multihop cluster hierarchy has been presented for large wireless sensor networks (WSNs that can provide scalable routing, data aggregation, and querying. The energy consumption rate for sensors in a WSN varies greatly based on the protocols the sensors use for communications. In this paper we present a cluster based routing algorithm. One of our main goals is to design the energy efficient routing protocol. Here we try to solve the usual problems of WSNs. We know the efficiency of WSNs depend upon the distance between node to base station and the amount of data to be transferred and the performance of clustering is greatly influenced by the selection of cluster-heads, which are in charge of creating clusters and controlling member nodes. This algorithm makes the best use of node with low number of cluster head know as super node. Here we divided the full region in four equal zones and the centre area of the region is used to select for super node. Each zone is considered separately and the zone may be or not divided further that’s depending upon the density of nodes in that zone and capability of the super node. This algorithm forms multilayer communication. The no of layer depends on the network current load and statistics. Our algorithm is easily extended to generate a hierarchy of cluster heads to obtain better network management and energy efficiency.

  12. Self-consisting modeling of entangled network strands and dangling ends

    DEFF Research Database (Denmark)

    Jensen, Mette Krog; Schieber, Jay D.; Khaliullin, Renat N.;

    2009-01-01

    of dangling ends and soluble structures. Energy dissipation is increased by adding a fraction of dangling ends, wDE, to the ensemble. We find that when wDE=0.6, G0 is about 75% lower than GN0, this suggests that the fraction of network strands, wNS=1-wDE, largely influences the plateau value at low...... frequencies. Soluble strands can also be added to the theory which is expected to increase energy dissipation further....

  13. Enhanced Deployment Strategy for Role-based Hierarchical Application Agents in Wireless Sensor Networks with Established Clusterheads

    Science.gov (United States)

    Gendreau, Audrey

    Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research, a model used to deploy intrusion detection capability on a Local Area Network (LAN), in the literature, was extended to develop a role-based hierarchical agent deployment algorithm for a WSN. The resulting model took into consideration the monitoring capability, risk, deployment distribution cost, and monitoring cost associated with each node. Changing the original LAN methodology approach to model a cluster-based sensor network depended on the ability to duplicate a specific parameter that represented the monitoring capability. Furthermore, other parameters derived from a LAN can elevate costs and risk of deployment, as well as jeopardize the success of an application on a WSN. A key component of the approach presented in this research was to reduce the costs when established clusterheads in the network were found to be capable of hosting additional detection agents. In addition, another cost savings component of the study addressed the reduction of vulnerabilities associated with deployment of agents to high volume nodes. The effectiveness of the presented method was validated by comparing it against a type of a power-based scheme that used each node's remaining energy as the deployment value. While available energy is directly related to the model used in the presented method, the study deliberately sought out nodes that were identified with having superior monitoring capability, cost less to create and sustain, and are at low-risk of an attack. This work investigated improving the efficiency of an intrusion detection system (IDS) by using the proposed model to deploy monitoring agents after a temperature sensing

  14. Hierarchically designed agarose and poly(ethylene glycol) interpenetrating network hydrogels for cartilage tissue engineering.

    Science.gov (United States)

    DeKosky, Brandon J; Dormer, Nathan H; Ingavle, Ganesh C; Roatch, Christopher H; Lomakin, Joseph; Detamore, Michael S; Gehrke, Stevin H

    2010-12-01

    A new method for encapsulating cells in interpenetrating network (IPN) hydrogels of superior mechanical integrity was developed. In this study, two biocompatible materials-agarose and poly(ethylene glycol) (PEG) diacrylate-were combined to create a new IPN hydrogel with greatly enhanced mechanical performance. Unconfined compression of hydrogel samples revealed that the IPN displayed a fourfold increase in shear modulus relative to a pure PEG-diacrylate network (39.9 vs. 9.9 kPa) and a 4.9-fold increase relative to a pure agarose network (8.2 kPa). PEG and IPN compressive failure strains were found to be 71% ± 17% and 74% ± 17%, respectively, while pure agarose gels failed around 15% strain. Similar mechanical property improvements were seen when IPNs-encapsulated chondrocytes, and LIVE/DEAD cell viability assays demonstrated that cells survived the IPN encapsulation process. The majority of IPN-encapsulated chondrocytes remained viable 1 week postencapsulation, and chondrocytes exhibited glycosaminoglycan synthesis comparable to that of agarose-encapsulated chondrocytes at 3 weeks postencapsulation. The introduction of a new method for encapsulating cells in a hydrogel with enhanced mechanical performance is a promising step toward cartilage defect repair. This method can be applied to fabricate a broad variety of cell-based IPNs by varying monomers and polymers in type and concentration and by adding functional groups such as degradable sequences or cell adhesion groups. Further, this technology may be applicable in other cell-based applications where mechanical integrity of cell-containing hydrogels is of great importance.

  15. A Hierarchical Network of Provably Optimal Learning Control Systems: Extensions of the Associative Control Process (ACP) Network

    Science.gov (United States)

    1993-01-01

    either behavior or learning, The modified ACP network does not have a negative reinforcement center yet is able to reproduce the simulation results of...Assuming N = 0 at all times, there is only one reinforcement center that is active, the positive reinforcement ccnter (PC). The negative ... reinforcement center (NC) is never active, and the weights associated with NC never change. The state is sensed through the sensors, and the actions are

  16. Cellulose nanofiber-templated three-dimension TiO2 hierarchical nanowire network for photoelectrochemical photoanode

    Science.gov (United States)

    Li, Zhaodong; Yao, Chunhua; Wang, Fei; Cai, Zhiyong; Wang, Xudong

    2014-12-01

    Three dimensional (3D) nanostructures with extremely large porosity possess a great promise for the development of high-performance energy harvesting and storage devices. In this paper, we developed a high-density 3D TiO2 fiber-nanorod (NR) heterostructure for efficient photoelectrochemical (PEC) water splitting. The hierarchical structure was synthesized on a ZnO-coated cellulose nanofiber (CNF) template using atomic layer deposition (ALD)-based thin film and NR growth procedures. The tubular structure evolution was in good agreement with the recently discovered vapor-phase Kirkendall effect in high-temperature ALD processes. The NR morphology was formed via the surface-reaction-limited pulsed chemical vapor deposition (SPCVD) mechanism. Under Xenon lamp illumination without and with an AM 1.5G filter or a UV cut off filter, the PEC efficiencies of a 3D TiO2 fiber-NR heterostructure were found to be 22-249% higher than those of the TiO2-ZnO bilayer tubular nanofibers and TiO2 nanotube networks that were synthesized as reference samples. Such a 3D TiO2 fiber-NR heterostructure offers a new route for a cellulose-based nanomanufacturing technique, which can be used for large-area, low-cost, and green fabrication of nanomaterials as well as their utilizations for efficient solar energy harvesting and conversion.

  17. A CAD System for Identification and Classification of Breast Cancer Tumors in DCE-MR Images Based on Hierarchical Convolutional Neural Networks

    Directory of Open Access Journals (Sweden)

    Reza Rastiboroujeni

    2015-06-01

    Full Text Available In this paper, we propose a computer aided diagnosis (CAD system based on hierarchical convolutional neural networks (HCNNs to discriminate between malignant and benign tumors in breast DCE-MRIs. A HCNN is a hierarchical neural network that operates on two-dimensional images. A HCNN integrates feature extraction and classification processes into one single and fully adaptive structure. It can extract two-dimensional key features automatically, and it is relatively tolerant to geometric and local distortions in input images. We evaluate CNN implementation learning and testing processes based on gradient descent (GD and resilient back-propagation (RPROP approaches. We show that, proposed HCNN with RPROP learning approach provide an effective and robust neural structure to design a CAD base system for breast MRI, and has potential as a mechanism for the evaluation of different types of abnormalities in medical images.

  18. Hierarchical tree-structured control network for the Antares laser facility

    Energy Technology Data Exchange (ETDEWEB)

    McGirt, F.

    1979-01-01

    The design and implementation of a distributed, computer-based control system for the Antares 100-kJ gas laser fusion facility is presented. Control system requirements and their operational interrelationships that consider both integrated system control and individual subsystem control are described. Several configurations of minicomputers are established to provide direct control of sets of microcomputers and to provide points of operator-laser interaction. Over 100 microcomputers are located very close to the laser device control points or sources of data and perform the real-time functions of the control system, such as data and control signal multiplexing, stepping motor control, and vacuum and gas system control. These microcomputers are designed to be supported as an integral part of the control network and to be software compatible with the larger minicomputers.

  19. Circumpolar Arctic vegetation: a hierarchic review and roadmap toward an internationally consistent approach to survey, archive and classify tundra plot data

    Science.gov (United States)

    Walker, D. A.; Daniëls, F. J. A.; Alsos, I.; Bhatt, U. S.; Breen, A. L.; Buchhorn, M.; Bültmann, H.; Druckenmiller, L. A.; Edwards, M. E.; Ehrich, D.; Epstein, H. E.; Gould, W. A.; Ims, R. A.; Meltofte, H.; Raynolds, M. K.; Sibik, J.; Talbot, S. S.; Webber, P. J.

    2016-05-01

    Satellite-derived remote-sensing products are providing a modern circumpolar perspective of Arctic vegetation and its changes, but this new view is dependent on a long heritage of ground-based observations in the Arctic. Several products of the Conservation of Arctic Flora and Fauna are key to our current understanding. We review aspects of the PanArctic Flora, the Circumpolar Arctic Vegetation Map, the Arctic Biodiversity Assessment, and the Arctic Vegetation Archive (AVA) as they relate to efforts to describe and map the vegetation, plant biomass, and biodiversity of the Arctic at circumpolar, regional, landscape and plot scales. Cornerstones for all these tools are ground-based plant-species and plant-community surveys. The AVA is in progress and will store plot-based vegetation observations in a public-accessible database for vegetation classification, modeling, diversity studies, and other applications. We present the current status of the Alaska Arctic Vegetation Archive (AVA-AK), as a regional example for the panarctic archive, and with a roadmap for a coordinated international approach to survey, archive and classify Arctic vegetation. We note the need for more consistent standards of plot-based observations, and make several recommendations to improve the linkage between plot-based observations biodiversity studies and satellite-based observations of Arctic vegetation.

  20. Stress Averaging for a Beam Network for Use in a Hierarchical Multiscale Framework

    Science.gov (United States)

    2015-03-01

    and can also have a linear taper along their length. Only circular beams of constant cross section are used in this study. The method presented...will be applicable to arbitrary beam cross sections, but additional work will be needed to determine the accuracy of the method for tapered beams...The definitions of the projected shear strains must be consistent with the virtual work expression for beam elements, Eq. 7. The displacements

  1. An exact arithmetic toolbox for a consistent and reproducible structural analysis of metabolic network models.

    Science.gov (United States)

    Chindelevitch, Leonid; Trigg, Jason; Regev, Aviv; Berger, Bonnie

    2014-10-07

    Constraint-based models are currently the only methodology that allows the study of metabolism at the whole-genome scale. Flux balance analysis is commonly used to analyse constraint-based models. Curiously, the results of this analysis vary with the software being run, a situation that we show can be remedied by using exact rather than floating-point arithmetic. Here we introduce MONGOOSE, a toolbox for analysing the structure of constraint-based metabolic models in exact arithmetic. We apply MONGOOSE to the analysis of 98 existing metabolic network models and find that the biomass reaction is surprisingly blocked (unable to sustain non-zero flux) in nearly half of them. We propose a principled approach for unblocking these reactions and extend it to the problems of identifying essential and synthetic lethal reactions and minimal media. Our structural insights enable a systematic study of constraint-based metabolic models, yielding a deeper understanding of their possibilities and limitations.

  2. Hierarchical Wireless Multimedia Sensor Networks for Collaborative Hybrid Semi-Supervised Classifier Learning

    Directory of Open Access Journals (Sweden)

    Liang Ding

    2007-11-01

    Full Text Available Wireless multimedia sensor networks (WMSN have recently emerged as one ofthe most important technologies, driven by the powerful multimedia signal acquisition andprocessing abilities. Target classification is an important research issue addressed in WMSN,which has strict requirement in robustness, quickness and accuracy. This paper proposes acollaborative semi-supervised classifier learning algorithm to achieve durative onlinelearning for support vector machine (SVM based robust target classification. The proposedalgorithm incrementally carries out the semi-supervised classifier learning process inhierarchical WMSN, with the collaboration of multiple sensor nodes in a hybrid computingparadigm. For decreasing the energy consumption and improving the performance, somemetrics are introduced to evaluate the effectiveness of the samples in specific sensor nodes,and a sensor node selection strategy is also proposed to reduce the impact of inevitablemissing detection and false detection. With the ant optimization routing, the learningprocess is implemented with the selected sensor nodes, which can decrease the energyconsumption. Experimental results demonstrate that the collaborative hybrid semi-supervised classifier learning algorithm can effectively implement target classification inhierarchical WMSN. It has outstanding performance in terms of energy efficiency and timecost, which verifies the effectiveness of the sensor nodes selection and ant optimizationrouting.

  3. An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

    Directory of Open Access Journals (Sweden)

    Dezhi Zhang

    2014-01-01

    Full Text Available This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users’ demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators’ service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

  4. An optimal hierarchical decision model for a regional logistics network with environmental impact consideration.

    Science.gov (United States)

    Zhang, Dezhi; Li, Shuangyan; Qin, Jin

    2014-01-01

    This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level.

  5. An Optimal Hierarchical Decision Model for a Regional Logistics Network with Environmental Impact Consideration

    Science.gov (United States)

    Zhang, Dezhi; Li, Shuangyan

    2014-01-01

    This paper proposes a new model of simultaneous optimization of three-level logistics decisions, for logistics authorities, logistics operators, and logistics users, for regional logistics network with environmental impact consideration. The proposed model addresses the interaction among the three logistics players in a complete competitive logistics service market with CO2 emission charges. We also explicitly incorporate the impacts of the scale economics of the logistics park and the logistics users' demand elasticity into the model. The logistics authorities aim to maximize the total social welfare of the system, considering the demand of green logistics development by two different methods: optimal location of logistics nodes and charging a CO2 emission tax. Logistics operators are assumed to compete with logistics service fare and frequency, while logistics users minimize their own perceived logistics disutility given logistics operators' service fare and frequency. A heuristic algorithm based on the multinomial logit model is presented for the three-level decision model, and a numerical example is given to illustrate the above optimal model and its algorithm. The proposed model provides a useful tool for modeling competitive logistics services and evaluating logistics policies at the strategic level. PMID:24977209

  6. Large information plus noise random matrix models and consistent subspace estimation in large sensor networks

    CERN Document Server

    Hachem, Walid; Mestre, Xavier; Najim, Jamal; Vallet, Pascal

    2011-01-01

    In array processing, a common problem is to estimate the angles of arrival of $K$ deterministic sources impinging on an array of $M$ antennas, from $N$ observations of the source signal, corrupted by gaussian noise. The problem reduces to estimate a quadratic form (called "localization function") of a certain projection matrix related to the source signal empirical covariance matrix. Recently, a new subspace estimation method (called "G-MUSIC") has been proposed, in the context where the number of available samples $N$ is of the same order of magnitude than the number of sensors $M$. In this context, the traditional subspace methods tend to fail because the empirical covariance matrix of the observations is a poor estimate of the source signal covariance matrix. The G-MUSIC method is based on a new consistent estimator of the localization function in the regime where $M$ and $N$ tend to $+\\infty$ at the same rate. However, the consistency of the angles estimator was not adressed. The purpose of this paper is ...

  7. Auditing Complex Concepts of SNOMED using a Refined Hierarchical Abstraction Network

    Science.gov (United States)

    Wang, Yue; Halper, Michael; Wei, Duo; Gu, Huanying; Perl, Yehoshua; Xu, Junchuan; Elhanan, Gai; Chen, Yan; Spackman, Kent A.; Case, James T.; Hripcsak, George

    2012-01-01

    Auditors of a large terminology, such as SNOMED CT, face a daunting challenge. To aid them in their efforts, it is essential to devise techniques that can automatically identify concepts warranting special attention. “Complex” concepts, which by their very nature are more difficult to model, fall neatly into this category. A special kind of grouping, called a partial-area, is utilized in the characterization of complex concepts. In particular, the complex concepts that are the focus of this work are those appearing in intersections of multiple partial-areas and are thus referred to as overlapping concepts. In a companion paper, an automatic methodology for identifying and partitioning the entire collection of overlapping concepts into disjoint, singly-rooted groups, that are more manageable to work with and comprehend, has been presented. The partitioning methodology formed the foundation for the development of an abstraction network for the overlapping concepts called a disjoint partial-area taxonomy. This new disjoint partial-area taxonomy offers a collection of semantically uniform partial-areas and is exploited herein as the basis for a novel auditing methodology. The review of the overlapping concepts is done in a top-down order within semantically uniform groups. These groups are themselves reviewed in a top-down order, which proceeds from the less complex to the more complex overlapping concepts. The results of applying the methodology to SNOMED’s Specimen hierarchy are presented. Hypotheses regarding error ratios for overlapping concepts and between different kinds of overlapping concepts are formulated. Two phases of auditing the Specimen hierarchy for two releases of SNOMED are reported on. With the use of the double bootstrap and Fisher’s exact test (two-tailed), the auditing of concepts and especially roots of overlapping partial-areas is shown to yield a statistically significant higher proportion of errors. PMID:21907827

  8. APHiD: Hierarchical Task Placement to Enable a Tapered Fat Tree Topology for Lower Power and Cost in HPC Networks

    Energy Technology Data Exchange (ETDEWEB)

    Michelogiannakis, George; Ibrahim, Khaled Z.; Shalf, John; Wilke, Jeremiah J.; Knight, Samuel; Kenny, Joseph P.

    2017-05-14

    The power and procurement cost of bandwidth in system-wide networks has forced a steady drop in the byte/flop ratio. This trend of computation becoming faster relative to the network is expected to hold. In this paper, we explore how cost-oriented task placement enables reducing the cost of system-wide networks by enabling high performance even on tapered topologies where more bandwidth is provisioned at lower levels. We describe APHiD, an efficient hierarchical placement algorithm that uses new techniques to improve the quality of heuristic solutions and reduces the demand on high-level, expensive bandwidth in hierarchical topologies. We apply APHiD to a tapered fat-tree, demonstrating that APHiD maintains application scalability even for severely tapered network configurations. Using simulation, we show that for tapered networks APHiD improves performance by more than 50% over random placement and even 15% in some cases over costlier, state-of-the-art placement algorithms.

  9. Discussion on the Hierarchical Cell Structure of LTE under the Network Simulation%从网络仿真看LTE网络分层结构部署

    Institute of Scientific and Technical Information of China (English)

    刘彦婷; 南作用

    2015-01-01

    “网络分层”并不是一个新的概念或组网模式,其在2008年WCDMA网络建设之初即被明确提出,但至今仍未贯彻至网络规划建设中。从LTE网络规划中遇到的问题入手,基于某运营商多地网络现状,分析问题产生的根源,并加以详细的理论分析,重新提出网络分层理念及未来网络规划建设的布局及趋势建议。并通过网络仿真分析其对LTE网络性能的影响,提出若干问题的解决方法。为后期LTE网络规划与建设提供参考。%Hierarchical cel structure is not a new concept or mode,it has been put forward in the beginning of WCDMA network con-struction in 2008,but has not been carried out in network planning and construction. Beginning with the problems on LTE net-work planning,based on the current network conditions of some operator,it analyzes the origin of the problems and explores them theoretical y,presents the hierarchical cel structure again and the layout of future network planning and the trend sug-gestion. It analyzes the impact on LTE network performance through network simulation,presents the resolutions on some problems,to provide reference for LTE network planning and construction in later stage.

  10. 水声通信网层次路由算法%Research on hierarchical routing algorithm for underwater acoustic communication networks

    Institute of Scientific and Technical Information of China (English)

    卞金洪; 徐新洲; 魏昕; 赵力

    2013-01-01

    针对水声通信网中由于节点能耗不均衡而影响网络生命周期的问题,基于无线传感网络的层次路由算法,提出了一种适用于水下环境的水声通信网层次路由算法.该算法采用分轮的思想,使用改进的复杂网络社团结构检测谱方法的相关算法.通过网络初始化等措施构建水声通信网的图结构,并利用Laplacian阵与聚类算法得到簇结构,进而实现网络中数据的正常传输.仿真实验表明,在水声通信网的特殊条件下,该算法相对于传统的LEACH协议能取得较好的效果,在网络稳定传输数据的情况下,网络各轮的存活节点数均优于LEACH.%In order to overcome the existing problem facing underwater acoustic communication networks, the researchers propose to examine a novel hierarchical routing algorithm for underwater acoustic communication networks. This study will be conducted in accordance to the hierarchical routing algorithms in wireless sensor network. While focusing on the problems of the network life cycle affected by the unbalanced node' s energy consumption. The improved detection spectral algorithm of complex network is introduced based on the ideal of sub-wheel. First, the graph structure of acoustic communication networks is constructed by means of network initialization. Next, the Laplacian matrix and cluster algorithm will be used to generate the cluster structure thus realizing normal data transmission successfully. The simulation results shows, under the special condition of underwater acoustic communication networks, the hierarchical routing algorithm can achieve better results compared to the traditional LEACH protocol. The number of surviving nodes for each round in our algorithm exceeds that in LEACH, and in the condition of stable network data transmission.

  11. Credit networks and systemic risk of Chinese local financing platforms: Too central or too big to fail?. -based on different credit correlations using hierarchical methods

    Science.gov (United States)

    He, Fang; Chen, Xi

    2016-11-01

    The accelerating accumulation and risk concentration of Chinese local financing platforms debts have attracted wide attention throughout the world. Due to the network of financial exposures among institutions, the failure of several platforms or regions of systemic importance will probably trigger systemic risk and destabilize the financial system. However, the complex network of credit relationships in Chinese local financing platforms at the state level remains unknown. To fill this gap, we presented the first complex networks and hierarchical cluster analysis of the credit market of Chinese local financing platforms using the ;bottom up; method from firm-level data. Based on balance-sheet channel, we analyzed the topology and taxonomy by applying the analysis paradigm of subdominant ultra-metric space to an empirical data in 2013. It is remarked that we chose to extract the network of co-financed financing platforms in order to evaluate the effect of risk contagion from platforms to bank system. We used the new credit similarity measure by combining the factor of connectivity and size, to extract minimal spanning trees (MSTs) and hierarchical trees (HTs). We found that: (1) the degree distributions of credit correlation backbone structure of Chinese local financing platforms are fat tailed, and the structure is unstable with respect to targeted failures; (2) the backbone is highly hierarchical, and largely explained by the geographic region; (3) the credit correlation backbone structure based on connectivity and size is significantly heterogeneous; (4) key platforms and regions of systemic importance, and contagion path of systemic risk are obtained, which are contributed to preventing systemic risk and regional risk of Chinese local financing platforms and preserving financial stability under the framework of macro prudential supervision. Our approach of credit similarity measure provides a means of recognizing ;systemically important; institutions and regions

  12. A Self-Consistent Scheme for Optical Response of large Hybrid Networks of Semiconductor Quantum Dots and Plasmonic Metal Nanoparticles

    Science.gov (United States)

    Barbiellini, Bernardo; Hayati, L.; Lane, C.; Bansil, A.; Mosallaei, H.

    We discuss a self-consistent scheme for treating the optical response of large, hybrid networks of semiconducting quantum dots (SQDs) and plasmonic metallic nanoparticles (MNPs). Our method is efficient and scalable and becomes exact in the limiting case of weakly interacting SQDs. The self-consistent equations obtained for the steady state are analogous to the Heisenberg equations of motion for the density matrix of a SQD placed in an effective electric field computed within the discrete dipole approximation (DDA). Illustrative applications of the theory to square and honeycomb SQD, MNP and hybrid SDQ/MNP lattices as well as SQD-MNP dimers are presented. Our results demonstrate that hybrid SQD-MNP lattices can provide flexible platforms for light manipulation with tunable resonant characteristics.

  13. Self-consistent scheme for optical response of large hybrid networks of semiconductor quantum dots and plasmonic metal nanoparticles

    Science.gov (United States)

    Hayati, L.; Lane, C.; Barbiellini, B.; Bansil, A.; Mosallaei, H.

    2016-06-01

    We discuss a self-consistent scheme for treating the optical response of large, hybrid networks of semiconducting quantum dots (SQDs) and plasmonic metallic nanoparticles (MNPs). Our method is efficient and scalable and becomes exact in the limiting case of weakly interacting SQDs. The self-consistent equations obtained for the steady state are analogous to the von Neumann equations of motion for the density matrix of a SQD placed in an effective electric field computed within the discrete dipole approximation. Illustrative applications of the theory to square and honeycomb SQD, MNP, and hybrid SDQ-MNP lattices as well as SQD-MNP dimers are presented. Our results demonstrate that hybrid SQD-MNP lattices can provide flexible platforms for light manipulation with tunable resonant characteristics.

  14. MX Hierarchical Networking System.

    Science.gov (United States)

    1982-02-01

    Information needed to analyze the deployment masterplan . This is the facili- ties level of detail. The third level (level 3) reflects the quantities of...Summary) 100 Level 1 SUBTOTAL 1 100 Level 2 (Deployment Masterplan ) DAA 350 OBTS 200 OPBASE 600 DDA/DTN 1,200 AUX OPBASE 550 LIFE SUPPORT 300...CEMXPA Program Summary -- 1 -- 100 Deployment Masterplan -- 2 -- 260 360 CEMXCO Deployment !asterplan 0 3 -- 900 900 AFRCE Deployment Masterplan 1 0

  15. Hierarchical organization of fluxes in Escherichia coli metabolic network: using flux coupling analysis for understanding the physiological properties of metabolic genes.

    Science.gov (United States)

    Hosseini, Zhaleh; Marashi, Sayed-Amir

    2015-05-01

    Flux coupling analysis is a method for investigating the connections between reactions of metabolic networks. Here, we construct the hierarchical flux coupling graph for the reactions of the Escherichia coli metabolic network model to determine the level of each reaction in the graph. This graph is constructed based on flux coupling analysis of metabolic network: if zero flux through reaction a results in zero flux through reaction b (and not vice versa), then reaction a is located at the top of reaction b in the flux coupling graph. We show that in general, more important, older and essential reactions are located at the top of the graph. Strikingly, genes corresponding to these reactions are found to be the genes which are most regulated.

  16. Cooperative mechanism of self-regulation in hierarchical living systems

    CERN Document Server

    Lubashevsky, I A

    1998-01-01

    We study the problem of how a ``living'' system complex in structure can respond perfectly to local changes in the environment. Such a system is assumed to consist of a distributed ``living'' medium and a hierarchical ``supplying'' network that provides this medium with ``nutritious'' products. Because of the hierarchical organization each element of the supplying network has to behave in a self-consistent way for the system can adapt to changes in the environment. We propose a cooperative mechanism of self-regulation by which the system as a whole can react perfectly. This mechanism is based on an individual response of each element to the corresponding small piece of the information on the state of the ``living'' medium. The conservation of flux through the supplying network gives rise to a certain processing of information and the self-consistent behavior of the elements, leading to the perfect self-regulation. The corresponding equations governing the ``living'' medium state are obtained.

  17. QoS Algorithms in Hierarchical IPv4 Network%层次型IPv4网络QoS算法

    Institute of Scientific and Technical Information of China (English)

    蒋建峰

    2014-01-01

    Hierarchical IPv4 networks put forward higher requirements for the quality of service. This paper analyzes the advantages, disadvantages and the application environment of the traditional QoS architecture based on business according to the second layer and the third layer of the OSI reference model. Then a QoS algorithm integrated differentiated service model with integrated service model is designed to enhance the QoS of a hierarchical network. The simulation results prove that the model can improve the network’s QoS in many aspects such as packet loss rate, transmission delay, delay jitter and network throughput.%网络服务质量 QoS 在层次型网络中要求更高.从 OSI 参考模型的第二层与第三层出发,分析了传统的QoS体系结构和三种QoS模型的工作原理、优缺点以及网络应用环境.设计了将IntServ与DiffServ模型相结合的互补算法来保证层次型网络的服务质量.仿真结果表明,此模型能够从传输延迟、丢包率、延时抖动和网络吞吐量等多个方面提升网络的QoS.

  18. 输电网络的分层分区电压无功调节方法%An Algorithm for Hierarchical and Partitioned Regulation of Voltage and Reactive Power in Transmission Network

    Institute of Scientific and Technical Information of China (English)

    颜伟; 高强; 余娟; 杜跃明

    2011-01-01

    According to the principles of hierarchical and partitioned balance and local compensation of reactive power as well as the principle of contrary regulation of voltage, a method for voltage and reactive power regulation in transmission network is proposed. Firstly, the concepts such as partition in the same hierarchy and its load factor, reactive power regulation ability and unbalancedness degree of reactive power are defined and used to determine ideal targets of reactive power balance and contrary regulation of voltage and to evaluate reactive power balance level. On this basis, a hierarchical and partitioned regulation strategy of voltage and reactive power is put forward, and the regulation strategy consists of three stages: global voltage and reactive power regulation, hierarchical and partitioned regulation of voltage and reactive power and local regulation of voltage and ractive power of teminal substaions. The features of power flow in every single stage are analyzed and the regulation rules of voltage and reactive power in each stage are drafted for the aims of making the voltage of whole network conforming to the guide as well as implementing hierarchical and partitioned reactive power balance as possible. The availability of the proposed algurithm is verified by the results of calculation example.%基于无功的分层分区平衡与就地补偿原则、中枢点电压的逆调压原则,提出了输电网络电压无功调节方法.首先定义了同层区及其负载率、无功调节能力和无功不平衡度等概念,以此来确定无功平衡与逆调压的理想目标,评估电网的无功平衡水平.在此基础上提出了分层分区的电压无功调节策略,该策略包括3个阶段:1)全局电压无功调节;2)无功的分层分区平衡调节;3)终端变电站的局部电压与无功调节.分析了每个阶段的潮流特征,制定了各阶段的电压无功调节规则,尽可能实现全网的电压合格和分层分区的无功平衡.

  19. Consistency and complementarity of different coastal ocean observations: A neural network-based analysis for the German Bight

    Science.gov (United States)

    Wahle, K.; Stanev, E. V.

    2011-05-01

    HF radar measurements in the German Bight and their consistency with other available observations were analyzed. First, an empirical orthogonal function (EOF) analysis of the radial component of the surface current measured by one radar was performed. Afterwards, Neural Networks (NNs) were trained to now- and forecast the first five EOFs from tide gauge measurements. The inverse problem, i.e., to forecast a sea level from these EOFs was also solved using NNs. For both problems, the influence of wind measurements on the nowcast/forecast accuracy was quantified. The forecast improves if HF radar data are used in combination with wind data. Analysis of the upscaling potential of HF radar measurements demonstrated that information from one radar station in the German Bight is representative of an area larger than the observational domain and could contribute to correcting information from biased observations or numerical models.

  20. Global synchronization in complex networks consisted of systems with the property of x-leading asymptotic stability

    Science.gov (United States)

    Wen, Sun; Chen, Shihua; Wang, Changping

    2008-04-01

    Recently a large set of dynamical systems have been intensively investigated as models of complex networks in which there exist a class of very common systems with the property of x-leading asymptotic stability [R. Zhang, M. Hu, Z. Xu, Phys. Lett. A 368 (2007) 276]. In this Letter, we introduced a new complex network model consisted of this systems, then considered its global synchronization. Based on Lasalle invariance principle, global synchronization criteria is derived. We also do not assume coupling matrix is symmetric and irreducible, so our model is more general than that of [R. Zhang, M. Hu, Z. Xu, Phys. Lett. A 368 (2007) 276]. What is more, our assumption f∈Quad(θ,P,α) is weaker than the assumption f∈Quad(D,P,α) in [W. Lu, T. Chen, Physica D 213 (2006) 214], but it improves synchronization results greatly. Numerical simulations of Lorenz systems as the nodes are given to show the effectiveness of the proposed global asymptotic synchronization criteria.

  1. Global synchronization in complex networks consisted of systems with the property of x{sub k}-leading asymptotic stability

    Energy Technology Data Exchange (ETDEWEB)

    Wen Sun [College of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China)], E-mail: sunwen_2201@163.com; Chen Shihua [College of Mathematics and Statistics, Wuhan University, Wuhan 430072 (China); Wang Changping [Department of Mathematics and Statistics, Dalhousie University, Halifax NS, B3H 3J5 (Canada)

    2008-04-21

    Recently a large set of dynamical systems have been intensively investigated as models of complex networks in which there exist a class of very common systems with the property of x{sub k}-leading asymptotic stability [R. Zhang, M. Hu, Z. Xu, Phys. Lett. A 368 (2007) 276]. In this Letter, we introduced a new complex network model consisted of this systems, then considered its global synchronization. Based on Lasalle invariance principle, global synchronization criteria is derived. We also do not assume coupling matrix is symmetric and irreducible, so our model is more general than that of [R. Zhang, M. Hu, Z. Xu, Phys. Lett. A 368 (2007) 276]. What is more, our assumption f element of Quad*({theta},P,{alpha}) is weaker than the assumption f element of Quad(D,P,{alpha}) in [W. Lu, T. Chen, Physica D 213 (2006) 214], but it improves synchronization results greatly. Numerical simulations of Lorenz systems as the nodes are given to show the effectiveness of the proposed global asymptotic synchronization criteria.

  2. 3D Networked Tin Oxide/Graphene Aerogel with a Hierarchically Porous Architecture for High-Rate Performance Sodium-Ion Batteries.

    Science.gov (United States)

    Xie, Xiuqiang; Chen, Shuangqiang; Sun, Bing; Wang, Chengyin; Wang, Guoxiu

    2015-09-07

    Low-cost and sustainable sodium-ion batteries are regarded as a promising technology for large-scale energy storage and conversion. The development of high-rate anode materials is highly desirable for sodium-ion batteries. The optimization of mass transport and electron transfer is crucial in the discovery of electrode materials with good high-rate performances. Herein, we report the synthesis of 3 D interconnected SnO2 /graphene aerogels with a hierarchically porous structure as anode materials for sodium-ion batteries. The unique 3 D architecture was prepared by a facile in situ process, during which cross-linked 3 D conductive graphene networks with macro-/meso-sized hierarchical pores were formed and SnO2 nanoparticles were dispersed uniformly on the graphene surface simultaneously. Such a 3 D functional architecture not only facilitates the electrode-electrolyte interaction but also provides an efficient electron pathway within the graphene networks. When applied as anode materials in sodium-ion batteries, the as-prepared SnO2 /graphene aerogel exhibited high reversible capacity, improved cycling performance compared to SnO2 , and promising high-rate capability.

  3. Structural changes in the minimal spanning tree and the hierarchical network in the Korean stock market around the global financial crisis

    Science.gov (United States)

    Nobi, Ashadun; Maeng, Seong Eun; Ha, Gyeong Gyun; Lee, Jae Woo

    2015-04-01

    This paper considers stock prices in the Korean stock market during the 2008 global financial crisis by focusing on three time periods: before, during, and after the crisis. Complex networks are extracted from cross-correlation coefficients between the normalized logarithmic return of the stock price time series of firms. The minimal spanning trees (MSTs) and the hierarchical network (HN) are generated from cross-correlation coefficients. Before and after the crisis, securities firms are located at the center of the MST. During the crisis, however, the center of the MST changes to a firm in heavy industry and construction. During the crisis, the MST shrinks in comparison to that before and that after the crisis. This topological change in the MST during the crisis reflects a distinct effect of the global financial crisis. The cophenetic correlation coefficient increases during the crisis, indicating an increase in the hierarchical structure during in this period. When crisis hits the market, firms behave synchronously, and their correlations are higher than those during a normal period.

  4. Consistency of long-term elemental carbon trends from thermal and optical measurements in the IMPROVE network

    Directory of Open Access Journals (Sweden)

    L.-W. A. Chen

    2012-05-01

    Full Text Available Decreasing trends of elemental carbon (EC have been reported at US Interagency Monitoring of Protected Visual Environments (IMPROVE network since 1990, consistent with the phase-in of cleaner engines, residential biomass burning technologies, and prescribed burning methods. The EC trends from the past decade are cautioned due to an upgrade of IMPROVE carbon analyzers and the thermal/optical analysis protocol since 2005. Filter reflectance (τR values measured as part of the carbon analysis were retrieved from archived data and compared with EC for 65 sites with more complete records from 2000 to 2009. The EC-τR relationships show only minor changes of EC quantified by the original and upgraded instruments for most of the IMPROVE samples. EC and τR show universal decreasing trends across the US. The EC and τR trends are correlated well, with national average downward trends of 4.5% and 4.1% (of the 2000–2004 baseline medians per year, respectively. The consistency between independent EC and τR trends adds to the weight-of-evidence that EC reductions are real rather than an artifact of the measurement process.

  5. Phase-Controlled Iron Oxide Nanobox Deposited on Hierarchically Structured Graphene Networks for Lithium Ion Storage and Photocatalysis

    Science.gov (United States)

    Yun, Sol; Lee, Young-Chul; Park, Ho Seok

    2016-01-01

    The phase control, hierarchical architecturing and hybridization of iron oxide is important for achieving multifunctional capability for many practical applications. Herein, hierarchically structured reduced graphene oxide (hrGO)/α-Fe2O3 and γ-Fe3O4 nanobox hybrids (hrGO/α-Fe and hrGO/γ-Fe NBhs) are synthesized via a one-pot, hydrothermal process and their functionality controlled by the crystalline phases is adapted for energy storage and photocatalysis. The three-dimensionally (3D) macroporous structure of hrGO/α-Fe NBhs is constructed, while α-Fe2O3 nanoboxes (NBs) in a proximate contact with the hrGO surface are simultaneously grown during a hydrothermal treatment. The discrete α-Fe2O3 NBs are uniformly distributed on the surface of the hrGO/α-Fe and confined in the 3D architecture, thereby inhibiting the restacking of rGO. After the subsequent phase transition into γ-Fe3O4, the hierarchical structure and the uniform distribution of NBs are preserved. Despite lower initial capacity, the hrGO/α-Fe NBhs show better rate and cyclic performances than those of commercial rGO/α-Fe due to the uniform distribution of discrete α-Fe2O3 NBs and electronic conductivity, macroporosity, and buffering effect of the hrGO for lithium ion battery anodes. Moreover, the catalytic activity and kinetics of hrGO/γ-Fe NBhs are enhanced for photo-Fenton reaction because of the uniform distribution of discrete γ-Fe3O4 NBs on the 3D hierarchical architecture.

  6. Hierarchical Policy Model for Managing Heterogeneous Security Systems

    Science.gov (United States)

    Lee, Dong-Young; Kim, Minsoo

    2007-12-01

    The integrated security management becomes increasingly complex as security manager must take heterogeneous security systems, different networking technologies, and distributed applications into consideration. The task of managing these security systems and applications depends on various systems and vender specific issues. In this paper, we present a hierarchical policy model which are derived from the conceptual policy, and specify means to enforce this behavior. The hierarchical policy model consist of five levels which are conceptual policy level, goal-oriented policy level, target policy level, process policy level and low-level policy.

  7. Hierarchical photocatalysts.

    Science.gov (United States)

    Li, Xin; Yu, Jiaguo; Jaroniec, Mietek

    2016-05-01

    As a green and sustainable technology, semiconductor-based heterogeneous photocatalysis has received much attention in the last few decades because it has potential to solve both energy and environmental problems. To achieve efficient photocatalysts, various hierarchical semiconductors have been designed and fabricated at the micro/nanometer scale in recent years. This review presents a critical appraisal of fabrication methods, growth mechanisms and applications of advanced hierarchical photocatalysts. Especially, the different synthesis strategies such as two-step templating, in situ template-sacrificial dissolution, self-templating method, in situ template-free assembly, chemically induced self-transformation and post-synthesis treatment are highlighted. Finally, some important applications including photocatalytic degradation of pollutants, photocatalytic H2 production and photocatalytic CO2 reduction are reviewed. A thorough assessment of the progress made in photocatalysis may open new opportunities in designing highly effective hierarchical photocatalysts for advanced applications ranging from thermal catalysis, separation and purification processes to solar cells.

  8. Hierarchical structures consisting of SiO2 nanorods and p-GaN microdomes for efficiently harvesting solar energy for InGaN quantum well photovoltaic cells.

    Science.gov (United States)

    Ho, Cheng-Han; Lien, Der-Hsien; Chang, Hung-Chih; Lin, Chin-An; Kang, Chen-Fang; Hsing, Meng-Kai; Lai, Kun-Yu; He, Jr-Hau

    2012-12-07

    We experimentally and theoretically demonstrated the hierarchical structure of SiO(2) nanorod arrays/p-GaN microdomes as a light harvesting scheme for InGaN-based multiple quantum well solar cells. The combination of nano- and micro-structures leads to increased internal multiple reflection and provides an intermediate refractive index between air and GaN. Cells with the hierarchical structure exhibit improved short-circuit current densities and fill factors, rendering a 1.47 fold efficiency enhancement as compared to planar cells.

  9. A decaying factor accounts for contained activity in neuronal networks with no need of hierarchical or modular organization

    CERN Document Server

    Amancio, Diego R; Costa, Luciano da F

    2012-01-01

    The mechanisms responsible for contention of activity in systems represented by networks are crucial in various phenomena, as in diseases such as epilepsy that affects the neuronal networks, and for information dissemination in social networks. The first models to account for contained activity included triggering and inhibition processes, but they cannot be applied to social networks where inhibition is clearly absent. A recent model showed that contained activity can be achieved with no need of inhibition processes provided that the network is subdivided in modules (communities). In this paper, we introduce a new concept inspired in the Hebbian theory through which activity contention is reached by incorporating a dynamics based on a decaying activity in a random walk mechanism preferential to the node activity. Upon selecting the decay coefficient within a proper range, we observed sustained activity in all the networks tested, viz. random, Barabasi-Albert and geographical networks. The generality of this ...

  10. Neutrosophic Hierarchical Clustering Algoritms

    Directory of Open Access Journals (Sweden)

    Rıdvan Şahin

    2014-03-01

    Full Text Available Interval neutrosophic set (INS is a generalization of interval valued intuitionistic fuzzy set (IVIFS, whose the membership and non-membership values of elements consist of fuzzy range, while single valued neutrosophic set (SVNS is regarded as extension of intuitionistic fuzzy set (IFS. In this paper, we extend the hierarchical clustering techniques proposed for IFSs and IVIFSs to SVNSs and INSs respectively. Based on the traditional hierarchical clustering procedure, the single valued neutrosophic aggregation operator, and the basic distance measures between SVNSs, we define a single valued neutrosophic hierarchical clustering algorithm for clustering SVNSs. Then we extend the algorithm to classify an interval neutrosophic data. Finally, we present some numerical examples in order to show the effectiveness and availability of the developed clustering algorithms.

  11. Feynman Clocks, Causal Networks, and The Origin of Hierarchical "Arrows of Time" in Complex Systems; 1, "Conjectures"

    CERN Document Server

    Hitchcock, S M

    2000-01-01

    A theory of time as 'information' is outlined using new tools such as Feynman Clocks (FCs), Collective Excitation Networks (CENs), Sequential Excitation Networks (SENs), and Plateaus of Complexity (POCs). Applications of this approach range from the Big Bang to the emergence of 'consciousness'. Keywords: the 'problem of time', the 'direction' and 'dimension' of time, causal networks, entangled states, decoherence, excitons, kaons, time reversal, time travel, photosynthesis, the double slit experiment, quantum computers, unification of the fundamental interactions of matter, neural networks, quantum gravity, CMB radiation, quintessence, the anthropic principle, and quantum cosmology.

  12. Constructing storyboards based on hierarchical clustering analysis

    Science.gov (United States)

    Hasebe, Satoshi; Sami, Mustafa M.; Muramatsu, Shogo; Kikuchi, Hisakazu

    2005-07-01

    There are growing needs for quick preview of video contents for the purpose of improving accessibility of video archives as well as reducing network traffics. In this paper, a storyboard that contains a user-specified number of keyframes is produced from a given video sequence. It is based on hierarchical cluster analysis of feature vectors that are derived from wavelet coefficients of video frames. Consistent use of extracted feature vectors is the key to avoid a repetition of computationally-intensive parsing of the same video sequence. Experimental results suggest that a significant reduction in computational time is gained by this strategy.

  13. A Hierarchical Collaborative Optimization Method for Transmission Network Restoration%输电网架恢复的分层协同优化方法

    Institute of Scientific and Technical Information of China (English)

    曹曦; 王洪涛; 刘玉田

    2015-01-01

    实际大规模输电网架恢复时间与空间跨度大,涉及操作众多,需要各级调度共同参与,因此提出一种网架恢复的分层协同优化方法.引入"受电点"的概念,将输电网架拆分,构建基于受电点指标约定的恢复协作机制,继而建立网架恢复的分层协同优化模型.该模型将主网架重构完成度与各地区新增发电量作为优化目标,采用分层次独立优化与受电点指标值整体寻优相结合的方法,可有效降低问题求解规模,并能够兼顾求解全局性与各层级的恢复偏好.通过受电点指标约定,明确任务分工与各地区的操作边界,能够实现有功、无功的协调控制与分层分区独立并行恢复,可显著提高恢复效率.山东电网实际算例验证了所提方法的有效性和实用性.%Network restoration after a widespread blackout involves complicated multi-process operations with a large spatial and temporal span, which needs the cooperation of multi-level dispatching centers. So a hierarchical collaborative optimization method for network restoration was proposed. The concept of feed point (FP) was introduced and the network restoration was divided into two layers. An FP based restoration cooperation mechanism was built. And then the collaborative optimization model was established. The objectives of this model are defined as network reconfiguration degree and total power production. The method combined hierarchical optimization with overall searching of the FP index value which makes the solving scale of the whole problem reduced dramatically. Global optimization and preference of each region can be obtained at the same time. The cooperation mechanism makes the task assignment clear. The coordination control of active/reactive power and multi-process parallel restoration operations can be achieved. The cases of Shandong power grid verify the effectiveness and practicability of this method.

  14. Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

    Science.gov (United States)

    2016-04-05

    applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...represents that important data are compromised. The second condition represents that the mobile group is unable to function correctly and is compromised as a...include mobile computing, wireless systems, dependable and secure computing, multimedia, sensor networks, data and service management, trust management

  15. Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

    Directory of Open Access Journals (Sweden)

    Yongcheng Li

    Full Text Available Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

  16. Application of hierarchical dissociated neural network in closed-loop hybrid system integrating biological and mechanical intelligence.

    Science.gov (United States)

    Li, Yongcheng; Sun, Rong; Zhang, Bin; Wang, Yuechao; Li, Hongyi

    2015-01-01

    Neural networks are considered the origin of intelligence in organisms. In this paper, a new design of an intelligent system merging biological intelligence with artificial intelligence was created. It was based on a neural controller bidirectionally connected to an actual mobile robot to implement a novel vehicle. Two types of experimental preparations were utilized as the neural controller including 'random' and '4Q' (cultured neurons artificially divided into four interconnected parts) neural network. Compared to the random cultures, the '4Q' cultures presented absolutely different activities, and the robot controlled by the '4Q' network presented better capabilities in search tasks. Our results showed that neural cultures could be successfully employed to control an artificial agent; the robot performed better and better with the stimulus because of the short-term plasticity. A new framework is provided to investigate the bidirectional biological-artificial interface and develop new strategies for a future intelligent system using these simplified model systems.

  17. Assessing the effect of quantitative and qualitative predictors on gastric cancer individuals survival using hierarchical artificial neural network models.

    Science.gov (United States)

    Amiri, Zohreh; Mohammad, Kazem; Mahmoudi, Mahmood; Parsaeian, Mahbubeh; Zeraati, Hojjat

    2013-01-01

    There are numerous unanswered questions in the application of artificial neural network models for analysis of survival data. In most studies, independent variables have been studied as qualitative dichotomous variables, and results of using discrete and continuous quantitative, ordinal, or multinomial categorical predictive variables in these models are not well understood in comparison to conventional models. This study was designed and conducted to examine the application of these models in order to determine the survival of gastric cancer patients, in comparison to the Cox proportional hazards model. We studied the postoperative survival of 330 gastric cancer patients who suffered surgery at a surgical unit of the Iran Cancer Institute over a five-year period. Covariates of age, gender, history of substance abuse, cancer site, type of pathology, presence of metastasis, stage, and number of complementary treatments were entered in the models, and survival probabilities were calculated at 6, 12, 18, 24, 36, 48, and 60 months using the Cox proportional hazards and neural network models. We estimated coefficients of the Cox model and the weights in the neural network (with 3, 5, and 7 nodes in the hidden layer) in the training group, and used them to derive predictions in the study group. Predictions with these two methods were compared with those of the Kaplan-Meier product limit estimator as the gold standard. Comparisons were performed with the Friedman and Kruskal-Wallis tests. Survival probabilities at different times were determined using the Cox proportional hazards and a neural network with three nodes in the hidden layer; the ratios of standard errors with these two methods to the Kaplan-Meier method were 1.1593 and 1.0071, respectively, revealed a significant difference between Cox and Kaplan-Meier (P neural network, and the neural network and the standard (Kaplan-Meier), as well as better accuracy for the neural network (with 3 nodes in the hidden layer

  18. Hierarchical manifold learning.

    Science.gov (United States)

    Bhatia, Kanwal K; Rao, Anil; Price, Anthony N; Wolz, Robin; Hajnal, Jo; Rueckert, Daniel

    2012-01-01

    We present a novel method of hierarchical manifold learning which aims to automatically discover regional variations within images. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate its utility in two very different settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease,

  19. Regularization of non-homogeneous dynamic Bayesian networks with global information-coupling based on hierarchical Bayesian models

    NARCIS (Netherlands)

    Grzegorczyk, Marco; Husmeier, Dirk

    2013-01-01

    To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying assumption is that the parameters associated with time series segments delimited by multiple changepoints are a priori inde

  20. Enhanced Deployment Strategy for Role-Based Hierarchical Application Agents in Wireless Sensor Networks with Established Clusterheads

    Science.gov (United States)

    Gendreau, Audrey

    2014-01-01

    Efficient self-organizing virtual clusterheads that supervise data collection based on their wireless connectivity, risk, and overhead costs, are an important element of Wireless Sensor Networks (WSNs). This function is especially critical during deployment when system resources are allocated to a subsequent application. In the presented research,…

  1. Hierarchical state space partitioning with a network self-organising map for the recognition of ST-T segment changes.

    Science.gov (United States)

    Bezerianos, A; Vladutu, L; Papadimitriou, S

    2000-07-01

    The problem of maximising the performance of ST-T segment automatic recognition for ischaemia detection is a difficult pattern classification problem. The paper proposes the network self-organising map (NetSOM) model as an enhancement to the Kohonen self-organised map (SOM) model. This model is capable of effectively decomposing complex large-scale pattern classification problems into a number of partitions, each of which is more manageable with a local classification device. The NetSOM attempts to generalize the regularization and ordering potential of the basic SOM from the space of vectors to the space of approximating functions. It becomes a device for the ordering of local experts (i.e. independent neural networks) over its lattice of neurons and for their selection and co-ordination. Each local expert is an independent neural network that is trained and activated under the control of the NetSOM. This method is evaluated with examples from the European ST-T database. The first results obtained after the application of NetSOM to ST-T segment change recognition show a significant improvement in the performance compared with that obtained with monolithic approaches, i.e. with single network types. The basic SOM model has attained an average ischaemic beat sensitivity of 73.6% and an average ischaemic beat predictivity of 68.3%. The work reports and discusses the improvements that have been obtained from the implementation of a NetSOM classification system with both multilayer perceptrons and radial basis function (RBF) networks as local experts for the ST-T segment change problem. Specifically, the NetSOM with multilayer perceptrons (radial basis functions) as local experts has improved the results over the basic SOM to an average ischaemic beat sensitivity of 75.9% (77.7%) and an average ischaemic beat predictivity of 72.5% (74.1%).

  2. MODELACIÓN DE LA ESTRUCTURA JERÁRQUICA DE MACROINVERTEBRADOS BENTÓNICOS A TRAVÉS DE REDES NEURONALES ARTIFICIALES Modeling of the Hierarchical Structure of Freshwater Macroinvertebrates Using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    CLAUDIA RICO

    ordination or clustering. Currently, analytical tools of bio-inspired computation belonging to the area of artificial intelligence are available to achieve ecological models with desirable characteristics, such as; flexibility, accuracy, robustness and reliability. In this context, this study employed two computational methods useful in ecoinformatics referring to artificial neural networks (RNAR for the modeling of the hierarchical structure of a benthic macroinvertebrate community in self-organization and prediction terms. The first ANN modeling method consisted of a Kohonen self-organization map (SOM, a non-supervised learning tool that classify the species of macroinvertebrates; this SOM in the input layer of gets the abundance of each ‘taxa’ from the data matrix, while in the output layer was visualized the computational results. Thus, in the output layer the species are organized in fifteen units and four hierarchical clusters. The second ANN method applied consisted of a multilayer feed-forward perceptron net with back-propagation algorithm to predict the three major insect orders; this means, Ephemeroptera, Coleoptera and Trichoptera (ECT richness and abundance using a set of nine physical-chemical variables. This ANN architecture included a neuron for each environmental variable, a hidden layer with seven neurons and a neuron in the output layer for ECT prediction. The results suggest that both types of ANN used, SOM and perceptron, were correspondingly related to the hierarchical patterns and with the richness and abundance patterns’ predictions, and gave the data analysis and understanding of the dynamic of the macroinvertebrates community, in a correct way.

  3. Achieving Consistent Near-Optimal Pattern Recognition Accuracy Using Particle Swarm Optimization to Pre-Train Artificial Neural Networks

    Science.gov (United States)

    Nikelshpur, Dmitry O.

    2014-01-01

    Similar to mammalian brains, Artificial Neural Networks (ANN) are universal approximators, capable of yielding near-optimal solutions to a wide assortment of problems. ANNs are used in many fields including medicine, internet security, engineering, retail, robotics, warfare, intelligence control, and finance. "ANNs have a tendency to get…

  4. Achieving Consistent Near-Optimal Pattern Recognition Accuracy Using Particle Swarm Optimization to Pre-Train Artificial Neural Networks

    Science.gov (United States)

    Nikelshpur, Dmitry O.

    2014-01-01

    Similar to mammalian brains, Artificial Neural Networks (ANN) are universal approximators, capable of yielding near-optimal solutions to a wide assortment of problems. ANNs are used in many fields including medicine, internet security, engineering, retail, robotics, warfare, intelligence control, and finance. "ANNs have a tendency to get…

  5. Mathematical Identification of a Neuronal Network Consisting of GABA and DA in Striatal Slices of the Rat Brain

    Directory of Open Access Journals (Sweden)

    L. Ramrath

    2009-01-01

    Full Text Available High frequency stimulation (HFS has been used to treat various neurological and psychiatric diseases. Although further disorders are under investigation to extend the clinical application of HFS, the complex effect of HFS within a neuronal network is still unknown. Thus, it would be desirable to find a theoretical model that allows an estimation of the expected effect of applied HFS. Based on the neurochemical analysis of effects of the γ-aminobutyric acid (GABAA receptor antagonist bicuculline, the D2-like receptor antagonist sulpiride and the D1-like receptor antagonist SCH-23390 on HFS evoked GABA and dopamine (DA release from striatal slices of the rat brain, a mathematical network model is proposed including the neurotransmitters GABA, DA and glutamate (GLU. The model reflects inhibitory and excitatory interactions of the neurotransmitters outflow in the presence of HFS. Under the assumption of linear interactions and static measurements, the model is expressed analytically. Numerical identification of inhibition and excitation is performed on a basis of real outflow levels of GABA and DA in the rat striatum. Results validate the nature of the proposed model. Therefore, this leads to an analytical model of the interactions within distinct neural network components of the rat striatum.

  6. Functional annotation of hierarchical modularity.

    Directory of Open Access Journals (Sweden)

    Kanchana Padmanabhan

    Full Text Available In biological networks of molecular interactions in a cell, network motifs that are biologically relevant are also functionally coherent, or form functional modules. These functionally coherent modules combine in a hierarchical manner into larger, less cohesive subsystems, thus revealing one of the essential design principles of system-level cellular organization and function-hierarchical modularity. Arguably, hierarchical modularity has not been explicitly taken into consideration by most, if not all, functional annotation systems. As a result, the existing methods would often fail to assign a statistically significant functional coherence score to biologically relevant molecular machines. We developed a methodology for hierarchical functional annotation. Given the hierarchical taxonomy of functional concepts (e.g., Gene Ontology and the association of individual genes or proteins with these concepts (e.g., GO terms, our method will assign a Hierarchical Modularity Score (HMS to each node in the hierarchy of functional modules; the HMS score and its p-value measure functional coherence of each module in the hierarchy. While existing methods annotate each module with a set of "enriched" functional terms in a bag of genes, our complementary method provides the hierarchical functional annotation of the modules and their hierarchically organized components. A hierarchical organization of functional modules often comes as a bi-product of cluster analysis of gene expression data or protein interaction data. Otherwise, our method will automatically build such a hierarchy by directly incorporating the functional taxonomy information into the hierarchy search process and by allowing multi-functional genes to be part of more than one component in the hierarchy. In addition, its underlying HMS scoring metric ensures that functional specificity of the terms across different levels of the hierarchical taxonomy is properly treated. We have evaluated our

  7. Hierarchical architecture of active knits

    Science.gov (United States)

    Abel, Julianna; Luntz, Jonathan; Brei, Diann

    2013-12-01

    Nature eloquently utilizes hierarchical structures to form the world around us. Applying the hierarchical architecture paradigm to smart materials can provide a basis for a new genre of actuators which produce complex actuation motions. One promising example of cellular architecture—active knits—provides complex three-dimensional distributed actuation motions with expanded operational performance through a hierarchically organized structure. The hierarchical structure arranges a single fiber of active material, such as shape memory alloys (SMAs), into a cellular network of interlacing adjacent loops according to a knitting grid. This paper defines a four-level hierarchical classification of knit structures: the basic knit loop, knit patterns, grid patterns, and restructured grids. Each level of the hierarchy provides increased architectural complexity, resulting in expanded kinematic actuation motions of active knits. The range of kinematic actuation motions are displayed through experimental examples of different SMA active knits. The results from this paper illustrate and classify the ways in which each level of the hierarchical knit architecture leverages the performance of the base smart material to generate unique actuation motions, providing necessary insight to best exploit this new actuation paradigm.

  8. Energy Efficient Hierarchical Collaboration Coverage Model in Wireless Sensor Network%WSN中能量有效的分层协作覆盖模型

    Institute of Scientific and Technical Information of China (English)

    杨勇; 夏士雄; 周勇

    2012-01-01

    针对传统网络覆盖模型仅以区域覆盖率作为评价标准,而未考察不同覆盖模型下节点能量有效性问题,在协作覆盖模型的基础上,提出了能量有效的分层协作覆盖模型EEHCCM(energy efficient hierarchical collaboration coverage model),并应用蚁群优化算法进行求解.该模型通过对目标区域进行分层,并优化各个层内的节点数目来实现节点能量的能耗均衡.提出了基于分层协作覆盖模型的启发式因子和全覆盖条件下节点数量的上下限的计算方法.通过Matlab仿真实验,其结果表明,应用EEHCCM模型实现目标区域节点的部署,在同等覆盖能力下,网络的生存时间可以得到较大的提升,与传统的覆盖算法相比,更适用于实际的节点部署.%Since the node's energy dissipation model is not taken in to account in the traditional coverage models, based on the collaboration coverage model, the energy efficient hierarchical collaboration coverage model is proposed, which can evenly balance the energy dissipation among different layers in the target monitor area. This paper solves two specific problems in the ant colony solution. They are a formula of heuristic factor calculating for the model and the upper and lower bounds of node numbers. Simulations in Matlab show that the proposed model is more suitable for practical deployment which can evidently prolong the network lifetime.

  9. Communication Network Community Detection Algorithm Orienting Hierarchical Structure Analysis%面向层次结构分析的通信网络社区检测算法

    Institute of Scientific and Technical Information of China (English)

    陈鸿昶; 李印海; 刘力雄

    2011-01-01

    In order to detect communication community and analyze its hierarchical structure of a communication network, this paper presents a community detection algorithm based on reachable communication distance ordering. By building multi-resolution embedded tree of communication density, it can display the hierarchical structure and key members of a community. Via pruning the embedded tree, computation complexity can be reduced in the process of community detection and hierarchical structure analysis. Experimental results on artificially synthesized network data and real network data approve that the algorithm is effective.%针对通信网络社区发现及其层次结构分析问题,提出一种基于可达通信距离排序的通信社区检测算法,通过建立通信密度的多分辨率嵌套树,展示社区的层次关系和核心成员,并对嵌套树进行修剪,从而在实现社区发现与层次结构分析的同时降低计算复杂度.对人工合成网络和真实网络数据进行测试,结果表明该算法有效.

  10. Evaluation of hierarchical structured representations for QSPR studies of small molecules and polymers by recursive neural networks.

    Science.gov (United States)

    Bertinetto, Carlo; Duce, Celia; Micheli, Alessio; Solaro, Roberto; Starita, Antonina; Tiné, Maria Rosaria

    2009-04-01

    This paper reports some recent results from the empirical evaluation of different types of structured molecular representations used in QSPR analysis through a recursive neural network (RNN) model, which allows for their direct use without the need for measuring or computing molecular descriptors. This RNN methodology has been applied to the prediction of the properties of small molecules and polymers. In particular, three different descriptions of cyclic moieties, namely group, template and cyclebreak have been proposed. The effectiveness of the proposed method in dealing with different representations of chemical structures, either specifically designed or of more general use, has been demonstrated by its application to data sets encompassing various types of cyclic structures. For each class of experiments a test set with data that were not used for the development of the model was used for validation, and the comparisons have been based on the test results. The reported results highlight the flexibility of the RNN in directly treating different classes of structured input data without using input descriptors.

  11. Genome-Wide Mapping of Collier In Vivo Binding Sites Highlights Its Hierarchical Position in Different Transcription Regulatory Networks.

    Directory of Open Access Journals (Sweden)

    Mathilde de Taffin

    Full Text Available Collier, the single Drosophila COE (Collier/EBF/Olf-1 transcription factor, is required in several developmental processes, including head patterning and specification of muscle and neuron identity during embryogenesis. To identify direct Collier (Col targets in different cell types, we used ChIP-seq to map Col binding sites throughout the genome, at mid-embryogenesis. In vivo Col binding peaks were associated to 415 potential direct target genes. Gene Ontology analysis revealed a strong enrichment in proteins with DNA binding and/or transcription-regulatory properties. Characterization of a selection of candidates, using transgenic CRM-reporter assays, identified direct Col targets in dorso-lateral somatic muscles and specific neuron types in the central nervous system. These data brought new evidence that Col direct control of the expression of the transcription regulators apterous and eyes-absent (eya is critical to specifying neuronal identities. They also showed that cross-regulation between col and eya in muscle progenitor cells is required for specification of muscle identity, revealing a new parallel between the myogenic regulatory networks operating in Drosophila and vertebrates. Col regulation of eya, both in specific muscle and neuronal lineages, may illustrate one mechanism behind the evolutionary diversification of Col biological roles.

  12. Routing Algorithm of Hierarchical Wireless Sensor Network%一种基于分层无线传感器网络的路由算法

    Institute of Scientific and Technical Information of China (English)

    邹瑜; 彭舰; 黎红友

    2012-01-01

    在多跳无线传感器网络中,靠近sink的节点由于需要转发来自外部的数据,其能量消耗速度快于离sink较远的节点,从而导致“能量空洞”的出现.采用分层的网络结构能够有效延迟能量空洞的出现.在分析现有路由算法 的基础上,结合分层的思想,对现有算法的路由算法进行了改进,提出了分层网络中各层环内最佳簇头和成簇概率的计算方法.在路由发现阶段引入了簇头路由指标,用于控制路由簇头接纳的路由数量,从而平衡了环内各个路由簇头的能量消耗.仿真实验结果表明,新的路由算法在网络生存时间、能耗均匀程度方面均优于现有算法.%Cluster-heads closer to the sink are burdened with heavy relay traffic and incline to die early, because the clustesr-heads transmit their data to sink via multi-hop communication. And this phenomenon is known as "energy hole". It wasproved that the architecture of hierarchical network can effectively delay the energy hole problem. Based on the method of the main routing algorithms, the existing routing algorithms was improved in computing the number of optimal cluster-head and the probability of each node being cluster-head, in every annular network. Considering the thought of hierarchy,cluster-head routing quota (CRQ) algorithm was proposed,which can be used to control the accepting numbers of each router,in phrase of routing detecting. Thus,it meets the demand of evenly consuming the ener-gy of each cluster-head located in the same ring. Simulation results demonstrate that the new algorithm is better than existing routing algorithm in the network lifetime and energy consumption.

  13. Hierarchical radial basis function networks and local polynomial un-warping for X-ray image intensifier distortion correction: a comparison with global techniques.

    Science.gov (United States)

    Cerveri, P; Forlani, C; Pedotti, A; Ferrigno, G

    2003-03-01

    Global polynomial (GP) methods have been widely used to correct geometric image distortion of small-size (up to 30 cm) X-ray image intensifiers (XRIIs). This work confirms that this kind of approach is suitable for 40 cm XRIIs (now increasingly used). Nonetheless, two local methods, namely 3rd-order local un-warping polynomials (LUPs) and hierarchical radial basis function (HRBF) networks are proposed as alternative solutions. Extensive experimental tests were carried out to compare these methods with classical low-order local polynomial and GP techniques, in terms of residual error (RMSE) measured at points not used for parameter estimation. Simulations showed that the LUP and HRBF methods had accuracies comparable with that attained using GP methods. In detail, the LUP method (0.353 microm) performed worse than HRBF (0.348 microm) only for small grid spacing (15 x 15 control points); the accuracy of both HRBF (0.157 microm) and LUP (0.160 microm) methods was little affected by local distortions (30 x 30 control points); weak local distortions made the GP method poorer (0.320 microm). Tests on real data showed that LUP and HRBF had accuracies comparable with that of GP for both 30 cm (GP: 0.238 microm; LUP: 0.240 microm; HRBF: 0.238 microm) and 40 cm (GP: 0.164 microm; LUP: 0.164 microm; HRBF: 0.164 microm) XRIIs. The LUP-based distortion correction was implemented in real time for image correction in digital tomography applications.

  14. Hierarchical Affinity Propagation

    CERN Document Server

    Givoni, Inmar; Frey, Brendan J

    2012-01-01

    Affinity propagation is an exemplar-based clustering algorithm that finds a set of data-points that best exemplify the data, and associates each datapoint with one exemplar. We extend affinity propagation in a principled way to solve the hierarchical clustering problem, which arises in a variety of domains including biology, sensor networks and decision making in operational research. We derive an inference algorithm that operates by propagating information up and down the hierarchy, and is efficient despite the high-order potentials required for the graphical model formulation. We demonstrate that our method outperforms greedy techniques that cluster one layer at a time. We show that on an artificial dataset designed to mimic the HIV-strain mutation dynamics, our method outperforms related methods. For real HIV sequences, where the ground truth is not available, we show our method achieves better results, in terms of the underlying objective function, and show the results correspond meaningfully to geographi...

  15. Hierarchical organisation of Britain through percolation theory

    CERN Document Server

    Arcaute, Elsa; Hatna, Erez; Murcio, Roberto; Vargas-Ruiz, Camilo; Masucci, Paolo; Wang, Jiaqiu; Batty, Michael

    2015-01-01

    Urban systems present hierarchical structures at many different scales. These are observed as administrative regional delimitations, which are the outcome of geographical, political and historical constraints. Using percolation theory on the street intersections and on the road network of Britain, we obtain hierarchies at different scales that are independent of administrative arrangements. Natural boundaries, such as islands and National Parks, consistently emerge at the largest/regional scales. Cities are devised through recursive percolations on each of the emerging clusters, but the system does not undergo a phase transition at the distance threshold at which cities can be defined. This specific distance is obtained by computing the fractal dimension of the clusters extracted at each distance threshold. We observe that the fractal dimension presents a maximum over all the different distance thresholds. The clusters obtained at this maximum are in very good correspondence to the morphological definition of...

  16. Interface Consistency

    DEFF Research Database (Denmark)

    Staunstrup, Jørgen

    1998-01-01

    This paper proposes that Interface Consistency is an important issue for the development of modular designs. Byproviding a precise specification of component interfaces it becomes possible to check that separately developedcomponents use a common interface in a coherent matter thus avoiding a very...... significant source of design errors. Awide range of interface specifications are possible, the simplest form is a syntactical check of parameter types.However, today it is possible to do more sophisticated forms involving semantic checks....

  17. Solid consistency

    Science.gov (United States)

    Bordin, Lorenzo; Creminelli, Paolo; Mirbabayi, Mehrdad; Noreña, Jorge

    2017-03-01

    We argue that isotropic scalar fluctuations in solid inflation are adiabatic in the super-horizon limit. During the solid phase this adiabatic mode has peculiar features: constant energy-density slices and comoving slices do not coincide, and their curvatures, parameterized respectively by ζ and Script R, both evolve in time. The existence of this adiabatic mode implies that Maldacena's squeezed limit consistency relation holds after angular average over the long mode. The correlation functions of a long-wavelength spherical scalar mode with several short scalar or tensor modes is fixed by the scaling behavior of the correlators of short modes, independently of the solid inflation action or dynamics of reheating.

  18. Hierarchical Heteroclinics in Dynamical Model of Cognitive Processes: Chunking

    Science.gov (United States)

    Afraimovich, Valentin S.; Young, Todd R.; Rabinovich, Mikhail I.

    Combining the results of brain imaging and nonlinear dynamics provides a new hierarchical vision of brain network functionality that is helpful in understanding the relationship of the network to different mental tasks. Using these ideas it is possible to build adequate models for the description and prediction of different cognitive activities in which the number of variables is usually small enough for analysis. The dynamical images of different mental processes depend on their temporal organization and, as a rule, cannot be just simple attractors since cognition is characterized by transient dynamics. The mathematical image for a robust transient is a stable heteroclinic channel consisting of a chain of saddles connected by unstable separatrices. We focus here on hierarchical chunking dynamics that can represent several cognitive activities. Chunking is the dynamical phenomenon that means dividing a long information chain into shorter items. Chunking is known to be important in many processes of perception, learning, memory and cognition. We prove that in the phase space of the model that describes chunking there exists a new mathematical object — heteroclinic sequence of heteroclinic cycles — using the technique of slow-fast approximations. This new object serves as a skeleton of motions reflecting sequential features of hierarchical chunking dynamics and is an adequate image of the chunking processing.

  19. Hierarchical Multiagent Reinforcement Learning

    Science.gov (United States)

    2004-01-25

    In this paper, we investigate the use of hierarchical reinforcement learning (HRL) to speed up the acquisition of cooperative multiagent tasks. We...introduce a hierarchical multiagent reinforcement learning (RL) framework and propose a hierarchical multiagent RL algorithm called Cooperative HRL. In

  20. The Revelation about the Information Network Planning and Construction by the Road Classification System and Hierarchical Planning Management Mode%道路分级体系和分层规划管理模式对信息管网规划及建设的启示

    Institute of Scientific and Technical Information of China (English)

    殷洁琰

    2013-01-01

    This paper condects a deep investigation about the road classification system and hierarchical planning management mode of China. It uses the characteristic of road classification system and hierarchical planning management mode for reference to analyzing the planning of information network. Based on the similarity between information network and road network, suggestions on the classification system and hierarchical planning management mode for information network are put forword.%  从信息网络与道路网络内涵的相关性、结构的相似性、建设的关联性出发,分析借鉴目前成熟的道路分级体系和分层规划管理模式,提出对信息管网在合理的等级体系和分层管理模式下进行统一规划建设的建议。

  1. Hierarchical nanostructures with unique Y-shaped interconnection networks in manganese substituted cobalt oxides: the enhancement effect on electrochemical sensing performance.

    Science.gov (United States)

    Lan, Wen-Jie; Kuo, Cheng-Chi; Chen, Chun-Hu

    2013-04-14

    A general redox procedure was successfully developed for the controlled synthesis of substituted cobalt oxides with hierarchical flower-like nanostructures comprising unique Y-shaped interconnections. The substitution and nanostructures synergistically enhance the material's electrochemical activities for highly efficient sensing of H2O2.

  2. A neural signature of hierarchical reinforcement learning.

    Science.gov (United States)

    Ribas-Fernandes, José J F; Solway, Alec; Diuk, Carlos; McGuire, Joseph T; Barto, Andrew G; Niv, Yael; Botvinick, Matthew M

    2011-07-28

    Human behavior displays hierarchical structure: simple actions cohere into subtask sequences, which work together to accomplish overall task goals. Although the neural substrates of such hierarchy have been the target of increasing research, they remain poorly understood. We propose that the computations supporting hierarchical behavior may relate to those in hierarchical reinforcement learning (HRL), a machine-learning framework that extends reinforcement-learning mechanisms into hierarchical domains. To test this, we leveraged a distinctive prediction arising from HRL. In ordinary reinforcement learning, reward prediction errors are computed when there is an unanticipated change in the prospects for accomplishing overall task goals. HRL entails that prediction errors should also occur in relation to task subgoals. In three neuroimaging studies we observed neural responses consistent with such subgoal-related reward prediction errors, within structures previously implicated in reinforcement learning. The results reported support the relevance of HRL to the neural processes underlying hierarchical behavior.

  3. The Hierarchical Nature of the Spin Alignment of Dark Matter Haloes in Filaments

    CERN Document Server

    Aragon-Calvo, Miguel A

    2013-01-01

    Dark matter haloes in cosmological filaments and walls have their spin vector aligned (in average) with their host structure. While haloes in walls are aligned with the plane of the wall independently of their mass, haloes in filaments present a mass dependent two-regime orientation. Here we show that the transition mass determining the change in the alignment regime (from parallel to perpendicular) depends on the hierarchical level in which the halo is located, reflecting the hierarchical nature of the Cosmic Web. By explicitly exposing this hierarchy we are able to identify the contributions of different components of the filament network to the spin alignment signal. We discuss a unifying picture to describe the alignment of haloes in filaments and walls consistent with previous results and our findings based on a two-phase angular momentum acquisition, first via tidal torquening and later via anisotropic mass accretion. The hierarchical identification and characterization of cosmic structures was done wit...

  4. An expanding universe of circadian networks in higher plants

    OpenAIRE

    Pruneda-Paz, Jose L.; Kay, Steve A.

    2010-01-01

    Extensive circadian clock networks regulate almost every biological process in plants. Clock-controlled physiological responses are coupled with daily oscillations in environmental conditions resulting in enhanced fitness and growth vigor. Identification of core clock components and their associated molecular interactions has established the basic network architecture of plant clocks, which consists of multiple interlocked feedback loops. A hierarchical structure of transcriptional feedback o...

  5. Analysis hierarchical model for discrete event systems

    Science.gov (United States)

    Ciortea, E. M.

    2015-11-01

    The This paper presents the hierarchical model based on discrete event network for robotic systems. Based on the hierarchical approach, Petri network is analysed as a network of the highest conceptual level and the lowest level of local control. For modelling and control of complex robotic systems using extended Petri nets. Such a system is structured, controlled and analysed in this paper by using Visual Object Net ++ package that is relatively simple and easy to use, and the results are shown as representations easy to interpret. The hierarchical structure of the robotic system is implemented on computers analysed using specialized programs. Implementation of hierarchical model discrete event systems, as a real-time operating system on a computer network connected via a serial bus is possible, where each computer is dedicated to local and Petri model of a subsystem global robotic system. Since Petri models are simplified to apply general computers, analysis, modelling, complex manufacturing systems control can be achieved using Petri nets. Discrete event systems is a pragmatic tool for modelling industrial systems. For system modelling using Petri nets because we have our system where discrete event. To highlight the auxiliary time Petri model using transport stream divided into hierarchical levels and sections are analysed successively. Proposed robotic system simulation using timed Petri, offers the opportunity to view the robotic time. Application of goods or robotic and transmission times obtained by measuring spot is obtained graphics showing the average time for transport activity, using the parameters sets of finished products. individually.

  6. 目标网络分层描述与自修复机制研究∗%Analysis of Hierarchical Models of Target Network and Self Repairing Mechanisms

    Institute of Scientific and Technical Information of China (English)

    张明星; 杨垚; 程光权; 刘忠

    2016-01-01

    针对目标网络分层建模与自修复机制问题展开研究。首先建立了分层次的作战目标网络模型,在此基础上提出六种维度的指标以评价作战目标网络在攻击前后能力的变化情况;其次,从预警网络层、火力网络层、指控网络层分析探索作战目标体系在遭受攻击后的最优自修复策略;最后,通过模拟攻击实验仿真分析上述自修复机制的可行性。实验结果表明该目标网络的自修复机制相比传统方法,能够更好地发挥剩余节点的作战效能。%This paper researches the hierarchical models of the target operation network and the self repairing mechanisms. First, it builds the hierarchical models of the target operation network and proposes six measures to quantify the different a⁃bilities variations of target operation network before and after attacks. Then, it analyzes the best strategies for different types of nodes after attacks from the perspectives of intelligence level, force network level, command and control level. Last, it an⁃alyzes the feasibility of the self repairing mechanism through the simulation experiment. Theoretical analysis and simulation results confirms that our methods is better than the traditional ones on which it can better utilize the left nodes� effects.

  7. Hierarchical structure of biological systems

    Science.gov (United States)

    Alcocer-Cuarón, Carlos; Rivera, Ana L; Castaño, Victor M

    2014-01-01

    A general theory of biological systems, based on few fundamental propositions, allows a generalization of both Wierner and Berthalanffy approaches to theoretical biology. Here, a biological system is defined as a set of self-organized, differentiated elements that interact pair-wise through various networks and media, isolated from other sets by boundaries. Their relation to other systems can be described as a closed loop in a steady-state, which leads to a hierarchical structure and functioning of the biological system. Our thermodynamical approach of hierarchical character can be applied to biological systems of varying sizes through some general principles, based on the exchange of energy information and/or mass from and within the systems. PMID:24145961

  8. Quantum transport through hierarchical structures.

    Science.gov (United States)

    Boettcher, S; Varghese, C; Novotny, M A

    2011-04-01

    The transport of quantum electrons through hierarchical lattices is of interest because such lattices have some properties of both regular lattices and random systems. We calculate the electron transmission as a function of energy in the tight-binding approximation for two related Hanoi networks. HN3 is a Hanoi network with every site having three bonds. HN5 has additional bonds added to HN3 to make the average number of bonds per site equal to five. We present a renormalization group approach to solve the matrix equation involved in this quantum transport calculation. We observe band gaps in HN3, while no such band gaps are observed in linear networks or in HN5. We provide a detailed scaling analysis near the edges of these band gaps.

  9. 水声传感器网络簇头分层通信模式路由算法%Routing Protocol of Hierarchical Cluster-Communication Model in the Underwater Acoustic Sensor Network

    Institute of Scientific and Technical Information of China (English)

    马绅惟; 刘广钟

    2014-01-01

    Routing protocol plays a very important role in underwater acoustic sensor networks. Based on the traditional TEEN protocol, a new routing protocol named HCM-TEEN(Hierarchical Cluster-communication Model on TEEN) has been put forward. The improved algorithm sets a new threshold function on the basis of the process of cluster candidate and the cluster elimination, and then introduces a Hierarchical Cluster-communication model in the period of data transmission to optimize the routing process. The experiment by the Matlab proved that HCM-TEEN performed better than the traditional algorithm on the network lifetime and the network average residual energy.%路由协议在水声传感器网络研究领域中扮演着非常重要的角色。基于传统的TEEN协议路由算法,提出了水声传感器网络中簇头分层通信模式的路由算法(HCM-TEEN)。新算法从簇头候选与淘汰过程入手,设置新的阈值函数。在簇头确定完成后,在数据传输阶段引入簇头分层通信模式,从距离和能量的角度上优化路由选择。通过Matlab仿真实验显示, HCM-TEEN算法与传统的算法相比在网络生命周期和节点平均剩余能量上都更具优越性。

  10. 一种适合于分级Ad Hoc网络的实时风险评估安全策略%A Real-Time Risk Evaluation Security Strategy in Hierarchical Ad Hoc Networks

    Institute of Scientific and Technical Information of China (English)

    于尧; 郭磊; 王兴伟; 李平平

    2011-01-01

    为提高分级Ad Hoc网络面临入侵行为时的路由性能,提出一种基于风险评估的入侵响应决策模型.该模型通过自组织神经元映射手段将攻击行为聚类,实时量化攻击节点的风险程度,以评估当前攻击对网络的威胁程度,并结合节点状态等辅助信息预测攻击持续程度和规模,对攻击节点采取相应的决策响应措施.仿真结果表明,该方法能够实时量化网络面临的威胁,及时、有效地遏制或减轻路由攻击对网络的危害.%an this paper,an intrusion response decision-making model based on the risk evaluation is proposed to improve the routing performance in hierarchical Ad Hoc networks. In this model, the attack behaviors were in clustering analyzing according to self-organizing map,and the risk degree was calculated in real time and quantity,in order to evaluate the threaten extent of the current attack. Combined with the related information such as the node statue, we could forecast the sustainable extent and scale of the attack,and thereby adopt the relevant decision-making to the attack node. Simulation results show that,the model proposed in this paper can real-time quantize the intimidation that hierarchical Ad Hoc networks meet, and alleviate and even contain the network harm caused by the routing attacks.

  11. Topology-based hierarchical scheduling using deficit round robin

    DEFF Research Database (Denmark)

    Yu, Hao; Yan, Ying; Berger, Michael Stubert

    2009-01-01

    This paper proposes a topology-based hierarchical scheduling scheme using Deficit Round Robin (DRR). The main idea of the topology-based hierarchical scheduling is to map the topology of the connected network into the logical structure of the scheduler, and combine several token schedulers...

  12. Ultrasensitive non-enzymatic glucose sensor based on three-dimensional network of ZnO-CuO hierarchical nanocomposites by electrospinning

    OpenAIRE

    2014-01-01

    Three-dimensional (3D) porous ZnO–CuO hierarchical nanocomposites (HNCs) nonenzymatic glucose electrodes with different thicknesses were fabricated by coelectrospinning and compared with 3D mixed ZnO/CuO nanowires (NWs) and pure CuO NWs electrodes. The structural characterization revealed that the ZnO–CuO HNCs were composed of the ZnO and CuO mixed NWs trunk (~200 nm), whose outer surface was attached with small CuO nanoparticles (NPs). Moreover, a good synergetic effect between CuO and ZnO w...

  13. Ultrasensitive non-enzymatic glucose sensor based on three-dimensional network of ZnO-CuO hierarchical nanocomposites by electrospinning

    Science.gov (United States)

    Zhou, Chunyang; Xu, Lin; Song, Jian; Xing, Ruiqing; Xu, Sai; Liu, Dali; Song, Hongwei

    2014-12-01

    Three-dimensional (3D) porous ZnO-CuO hierarchical nanocomposites (HNCs) nonenzymatic glucose electrodes with different thicknesses were fabricated by coelectrospinning and compared with 3D mixed ZnO/CuO nanowires (NWs) and pure CuO NWs electrodes. The structural characterization revealed that the ZnO-CuO HNCs were composed of the ZnO and CuO mixed NWs trunk (~200 nm), whose outer surface was attached with small CuO nanoparticles (NPs). Moreover, a good synergetic effect between CuO and ZnO was confirmed. The nonenzymatic biosensing properties of as prepared 3D porous electrodes based on fluorine doped tin oxide (FTO) were studied and the results indicated that the sensing properties of 3D porous ZnO-CuO HNCs electrodes were significantly improved and depended strongly on the thickness of the HNCs. At an applied potential of + 0.7 V, the optimum ZnO-CuO HNCs electrode presented a high sensitivity of 3066.4 μAmM-1cm-2, the linear range up to 1.6 mM, and low practical detection limit of 0.21 μM. It also showed outstanding long term stability, good reproducibility, excellent selectivity and accurate measurement in real serum sample. The formation of special hierarchical heterojunction and the well-constructed 3D structure were the main reasons for the enhanced nonenzymatic biosensing behavior.

  14. Investigation on Reliability and Scalability of an FBG-Based Hierarchical AOFSN

    Directory of Open Access Journals (Sweden)

    Li-Mei Peng

    2010-03-01

    Full Text Available The reliability and scalability of large-scale based optical fiber sensor networks (AOFSN are considered in this paper. The AOFSN network consists of three-level hierarchical sensor network architectures. The first two levels consist of active interrogation and remote nodes (RNs and the third level, called the sensor subnet (SSN, consists of passive Fiber Bragg Gratings (FBGs and a few switches. The switch architectures in the RN and various SSNs to improve the reliability and scalability of AOFSN are studied. Two SSNs with a regular topology are proposed to support simple routing and scalability in AOFSN: square-based sensor cells (SSC and pentagon-based sensor cells (PSC. The reliability and scalability are evaluated in terms of the available sensing coverage in the case of one or multiple link failures.

  15. Neural network consistent empirical physical formula construction for density functional theory based nonlinear vibrational absorbance and intensity of 6-choloronicotinic acid molecule.

    Science.gov (United States)

    Yildiz, Nihat; Karabacak, Mehmet; Kurt, Mustafa; Akkoyun, Serkan

    2012-05-01

    Being directly related to the electric charge distributions in a molecule, the vibrational spectra intensities are both experimentally and theoretically important physical quantities. However, these intensities are inherently highly nonlinear and of complex pattern. Therefore, in particular for unknown detailed spatial molecular structures, it is difficult to make ab initio intensity calculations to compare with new experimental data. In this respect, we very recently initiated entirely novel layered feedforward neural network (LFNN) approach to construct empirical physical formulas (EPFs) for density functional theory (DFT) vibrational spectra of some molecules. In this paper, as a new and far improved contribution to our novel molecular vibrational spectra LFNN-EPF approach, we constructed LFFN-EPFs for absorbances and intensities of 6-choloronicotinic acid (6-CNA) molecule. The 6-CNA data, borrowed from our previous study, was entirely different and much larger than the vibrational intensity data of our formerly used LFNN-EPF molecules. In line with our another previous work which theoretically proved the LFNN relevance to EPFs, although the 6-CNA DFT absorbance and intensity were inherently highly nonlinear and sharply fluctuating in character, still the optimally constructed train set LFFN-EPFs very successfully fitted the absorbances and intensities. Moreover, test set (i.e. yet-to-be measured experimental data) LFNN-EPFs consistently and successfully predicted the absorbance and intensity data. This simply means that the physical law embedded in the 6-CNA vibrational data was successfully extracted by the LFNN-EPFs. In conclusion, these vibrational LFNN-EPFs are of explicit form. Therefore, by various suitable operations of mathematical analysis, they can be used to estimate the electronic charge distributions of the unknown molecule of the significant complexity. Additionally, these estimations can be combined with those of theoretical DFT atomic polar

  16. A note on hierarchical hubbing for a generalization of the VPN problem

    NARCIS (Netherlands)

    Olver, N.K.

    2014-01-01

    Robust network design refers to a class of optimization problems that occur when designing networks to efficiently handle variable demands. The notion of "hierarchical hubbing" was introduced (in the narrow context of a specific robust network design question), by Olver and Shepherd [2010]. Hierarch

  17. 基于RFID和ZigBee网络的通用分级考勤管理系统%Universal and Hierarchical Attendance Management System Based on RFID and ZigBee Network

    Institute of Scientific and Technical Information of China (English)

    张琼英; 王能河; 张伟刚; 瞿少成

    2016-01-01

    【目的】针对考勤管理移动性差、数据难以共享、过于依赖网络和后台计算机等缺陷,设计一种基于射频识别技术(RFID)和ZigBee网络的通用分级管理考勤系统。【方法】基于 MFRC500与 STC89C52设计被动非接触式RFID考勤读卡子系统;采用CC2530设计ZigBee无线传感网络;基于 Linux/QT完成 ARM主控平台开发。【结果】系统实现多 RFID读卡子系统的自组网、子节点与主控平台的分级管理。【结论】测试表明,该系统部署灵活,能适应复杂的楼宇环境,且性价比较高,具有一定推广价值。%[Objective]A design of universal and hierarchical attendance system,which uses RFID and ZigBee network,is proposed to fix the shortcomings of attendance management.[Methods]Based on MFRC500 and STC89C52,a passive contactless RFID reader subsystem is designed. Multi-RFID reader subsystems can be attached by ZigBee wireless sensor network using CC2530.A master platform based on Linux/QT is developed.[Results]This system can achieve hierarchical attendance management for child node and host platform,respectively.Also a web background data management system is provided for data mining in future.[Conclusion]Experi-ments show that the system can be easily implemented and works stable in complex environ-ment.

  18. 一种基于分层结构的Ad Hoc网络分簇路由协议研究%Research based on the hierarchical structure of the Ad Hoc network clustering routing protocol

    Institute of Scientific and Technical Information of China (English)

    冯永亮

    2015-01-01

    The traditional Ad Hoc network clustering routing protocol has low packet delivery ratio problem, this paper proposes a clustering routing protocol based on hierarchical structure. The advanced network layer using AODV routing protocol based backup, and the lower network layer adopts a smaller delay DSDV protocol. The simulation results show that the improved routing protocol improves the packet delivery rate, Shortening the end to end delay.%传统Ad Hoc网络分簇路由协议存在分组投递率低的问题,论文提出一种基于分层结构的分簇路由协议.高级网络层采用基于备份路由的AODV协议,而低级网络层则采用时延较小的DSDV协议.仿真结果显示,改进后的路由协议提高了分组投递率,缩短了端到端时延.

  19. Hierarchical Prisoner's Dilemma in Hierarchical Public-Goods Game

    CERN Document Server

    Fujimoto, Yuma; Kaneko, Kunihiko

    2016-01-01

    The dilemma in cooperation is one of the major concerns in game theory. In a public-goods game, each individual pays a cost for cooperation, or to prevent defection, and receives a reward from the collected cost in a group. Thus, defection is beneficial for each individual, while cooperation is beneficial for the group. Now, groups (say, countries) consisting of individual players also play games. To study such a multi-level game, we introduce a hierarchical public-goods (HPG) game in which two groups compete for finite resources by utilizing costs collected from individuals in each group. Analyzing this HPG game, we found a hierarchical prisoner's dilemma, in which groups choose the defection policy (say, armaments) as a Nash strategy to optimize each group's benefit, while cooperation optimizes the total benefit. On the other hand, for each individual within a group, refusing to pay the cost (say, tax) is a Nash strategy, which turns to be a cooperation policy for the group, thus leading to a hierarchical d...

  20. Feynman Clocks, Casual Networks, and the Origin of Hierarchical "Arrows of Time" in Complex Systems from the Big Bang to the Brain

    CERN Document Server

    Hitchcock, S M

    2000-01-01

    A theory of 'time' as a form of 'information' is proposed. New tools such as Feynman Clocks, Collective Excitation Networks, Sequential Excitation Networks, Plateaus of Complexity, Causal Networks, and Quantum Computation methods are used to unify previously separate 'arrows of time'. The 'direction' and 'dimension' of 'time' are found to be secondary information structures created by the 'processing' of the information carried by signals connecting 'clocks' together in networks. The 'problem of time' may be solved by identification of a fundamental 'irreversible' Quantum Arrow of Time and 'reversible' Classical Arrows of Time. These 'arrows' can used to map information flow through complex causal networks from the Big Bang to the Brain. Keywords; unification of the fundamental interactions of matter, consciousness, entangled states, time reversal, time travel, and FTL or superluminal signals

  1. Network Source Active Enhancement Algorithm Based on PSO Hierarchical Evolutionary%基于PSO递阶进化的网络资源活跃度增强算法

    Institute of Scientific and Technical Information of China (English)

    侯贵法; 常国权

    2015-01-01

    为了提高云计算环境下网络资源访问和调度能力,需要增强网络资源的活跃度,传统方法采用源信息系统最小方差粒子群优化算法实现资源活跃度增强调度,直接交互式多源信息的缺陷,导致信息访问的滞后和时延.提出一种基于粒子群(PSO)递阶进化的多出口网络资源活跃度增强算法,构建多出口网络资源调度和网络系统结构,粒子群进化按照属性的数据波动进行递阶分层,得到一个资源数据聚类的高密度区域,使得每一个初始种群中的个体都应有一个解,在多波束搜索PSO空间中实现粒子群PSO递阶进化,提高网络资源访问的活跃度.仿真实验表明,采用该算法,能避免粒子群在进行网络资源搜索调度过程中陷入局部最优,有效提高控制搜索精度,运行时间较短,能有效增强多出口网络资源的活跃度,进而提高了资源搜索成功率.%In order to improve the cloud computing cyber source access and scheduling capability of environment, the need to strengthen the cyber source activity, the traditional method is using the source information system minimum variance of particle swarm optimization algorithm for resource scheduling activity enhancement, defect directly interactive multiple source information, resulting in information access delay and delay. Proposed one kind based on Particle Swarm (PSO) ex-port more network resources hierarchical evolutionary liveness enhancement algorithm, constructing multi export network resource scheduling and network system structure, particle swarm optimization for hierarchical data according to the fluctu-ation property, get a resource data clustering of the high-density region, so that each individual in the initial population there should be a solution, in a multi beam search implementation of particle swarm PSO hierarchical evolutionary PSO space, improve the network resource access activity. Simulation results show that using this

  2. Visualization of Social Networks

    NARCIS (Netherlands)

    Boertjes, E.M.; Kotterink, B.; Jager, E.J.

    2011-01-01

    Current visualizations of social networks are mostly some form of node-link diagram. Depending on the type of social network, this can be some treevisualization with a strict hierarchical structure or a more generic network visualization.

  3. Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

    Energy Technology Data Exchange (ETDEWEB)

    Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

    2016-10-25

    An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

  4. Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

    Energy Technology Data Exchange (ETDEWEB)

    Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

    2015-07-28

    An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

  5. Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

    Science.gov (United States)

    Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

    2016-10-25

    An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

  6. A Wireless Sensor Network Multicast Model Based on Hierarchical Windmill Structure%一种风车形状层次结构的WSN组播模型

    Institute of Scientific and Technical Information of China (English)

    许建真; 李韩芬; 李方菊

    2012-01-01

    A region-oriented and energy-efficient WSN multicast model based on hierarchical windmill structure (HWSM) is put forward here. Firstly, it sets up hierarchical ring-type multicast model and elects one leader from each ring group. Then, all those leaders elected from each ring group compose the upper level ring. Leader adopts the traversal method to deliver data to all the other nodes of the ring group by means of flooding routing method. Simulation results prove that, this model can reduce the energy consumption and improve the data transmission efficiency as well as lengthening the survival time of WSN.%提出一种面向特定区域的高效节能的风车形状层次结构WSN组播模型(HWSM),该模型首先构建层次化风车环状结构,在每个环中选举出一个首节点,构成风车“轴心”,同时选举出来的各个首节点构成上一级风车环状结构.环内节点采用组播方式进行数据分发,由首节点通过辐射路由一次遍历其它所有节点,完成数据传输.仿真实验证明,该模型可降低环内节点的能量消耗,提高数据传输效率,延长网络生存时间.

  7. Treatment Protocols as Hierarchical Structures

    Science.gov (United States)

    Ben-Bassat, Moshe; Carlson, Richard W.; Puri, Vinod K.; Weil, Max Harry

    1978-01-01

    We view a treatment protocol as a hierarchical structure of therapeutic modules. The lowest level of this structure consists of individual therapeutic actions. Combinations of individual actions define higher level modules, which we call routines. Routines are designed to manage limited clinical problems, such as the routine for fluid loading to correct hypovolemia. Combinations of routines and additional actions, together with comments, questions, or precautions organized in a branching logic, in turn, define the treatment protocol for a given disorder. Adoption of this modular approach may facilitate the formulation of treatment protocols, since the physician is not required to prepare complex flowcharts. This hierarchical approach also allows protocols to be updated and modified in a flexible manner. By use of such a standard format, individual components may be fitted together to create protocols for multiple disorders. The technique is suited for computer implementation. We believe that this hierarchical approach may facilitate standarization of patient care as well as aid in clinical teaching. A protocol for acute pancreatitis is used to illustrate this technique.

  8. A real-time in-memory discovery service leveraging hierarchical packaging information in a unique identifier network to retrieve track and trace information

    CERN Document Server

    Müller, Jürgen

    2014-01-01

    This book examines how to efficiently retrieve track and trace information for an item that took a certain path through a complex network of manufacturers, wholesalers, retailers and consumers. It includes valuable tips on in-memory data management.

  9. Correlated spin networks in frustrated systems

    Science.gov (United States)

    Stone, Thomas E.; McKay, Susan R.

    2010-08-01

    We introduce a network model for frustrated spin systems based on highly correlated spin fluctuations, to quantify and visualize their ordering. This model shows that networks of strongly correlated but non-contiguous spins exist at low temperatures on a triangular Ising lattice with competing nearest-neighbor interactions. This finding is consistent with chaotic renormalization-group trajectories previously reported for frustrated hierarchical lattices.

  10. 3D hierarchical MnO2 nanorod/welded Ag-nanowire-network composites for high-performance supercapacitor electrodes.

    Science.gov (United States)

    Qiao, Zhensong; Yang, Xiaopeng; Yang, Shuhua; Zhang, Liqiang; Cao, Bingqiang

    2016-06-28

    3D MnO2 nanorod/welded Ag-nanowire-network supercapacitor electrodes were prepared. Welding treatment of the Ag nanowire-network leads to low resistance and long lifetime. Galvanostatic charge/discharge (GCD) induces an ever-lasting morphology changing from flower-like to honeycomb-like for MnO2, which manifests as increasing specific capacitance to 663.4 F g(-1) after 7000 GCD cycles.

  11. Micromechanics of hierarchical materials

    DEFF Research Database (Denmark)

    Mishnaevsky, Leon, Jr.

    2012-01-01

    A short overview of micromechanical models of hierarchical materials (hybrid composites, biomaterials, fractal materials, etc.) is given. Several examples of the modeling of strength and damage in hierarchical materials are summarized, among them, 3D FE model of hybrid composites...... with nanoengineered matrix, fiber bundle model of UD composites with hierarchically clustered fibers and 3D multilevel model of wood considered as a gradient, cellular material with layered composite cell walls. The main areas of research in micromechanics of hierarchical materials are identified, among them......, the investigations of the effects of load redistribution between reinforcing elements at different scale levels, of the possibilities to control different material properties and to ensure synergy of strengthening effects at different scale levels and using the nanoreinforcement effects. The main future directions...

  12. Hierarchical auxetic mechanical metamaterials.

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I; Azzopardi, Keith M; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N

    2015-02-11

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  13. Introduction into Hierarchical Matrices

    KAUST Repository

    Litvinenko, Alexander

    2013-12-05

    Hierarchical matrices allow us to reduce computational storage and cost from cubic to almost linear. This technique can be applied for solving PDEs, integral equations, matrix equations and approximation of large covariance and precision matrices.

  14. Hierarchical Auxetic Mechanical Metamaterials

    Science.gov (United States)

    Gatt, Ruben; Mizzi, Luke; Azzopardi, Joseph I.; Azzopardi, Keith M.; Attard, Daphne; Casha, Aaron; Briffa, Joseph; Grima, Joseph N.

    2015-02-01

    Auxetic mechanical metamaterials are engineered systems that exhibit the unusual macroscopic property of a negative Poisson's ratio due to sub-unit structure rather than chemical composition. Although their unique behaviour makes them superior to conventional materials in many practical applications, they are limited in availability. Here, we propose a new class of hierarchical auxetics based on the rotating rigid units mechanism. These systems retain the enhanced properties from having a negative Poisson's ratio with the added benefits of being a hierarchical system. Using simulations on typical hierarchical multi-level rotating squares, we show that, through design, one can control the extent of auxeticity, degree of aperture and size of the different pores in the system. This makes the system more versatile than similar non-hierarchical ones, making them promising candidates for industrial and biomedical applications, such as stents and skin grafts.

  15. Applied Bayesian Hierarchical Methods

    CERN Document Server

    Congdon, Peter D

    2010-01-01

    Bayesian methods facilitate the analysis of complex models and data structures. Emphasizing data applications, alternative modeling specifications, and computer implementation, this book provides a practical overview of methods for Bayesian analysis of hierarchical models.

  16. Programming with Hierarchical Maps

    DEFF Research Database (Denmark)

    Ørbæk, Peter

    This report desribes the hierarchical maps used as a central data structure in the Corundum framework. We describe its most prominent features, ague for its usefulness and briefly describe some of the software prototypes implemented using the technology....

  17. Catalysis with hierarchical zeolites

    DEFF Research Database (Denmark)

    Holm, Martin Spangsberg; Taarning, Esben; Egeblad, Kresten

    2011-01-01

    Hierarchical (or mesoporous) zeolites have attracted significant attention during the first decade of the 21st century, and so far this interest continues to increase. There have already been several reviews giving detailed accounts of the developments emphasizing different aspects of this research...... topic. Until now, the main reason for developing hierarchical zeolites has been to achieve heterogeneous catalysts with improved performance but this particular facet has not yet been reviewed in detail. Thus, the present paper summaries and categorizes the catalytic studies utilizing hierarchical...... zeolites that have been reported hitherto. Prototypical examples from some of the different categories of catalytic reactions that have been studied using hierarchical zeolite catalysts are highlighted. This clearly illustrates the different ways that improved performance can be achieved with this family...

  18. Hierarchical Control for Smart Grids

    DEFF Research Database (Denmark)

    Trangbæk, K; Bendtsen, Jan Dimon; Stoustrup, Jakob

    2011-01-01

    This paper deals with hierarchical model predictive control (MPC) of smart grid systems. The design consists of a high level MPC controller, a second level of so-called aggregators, which reduces the computational and communication-related load on the high-level control, and a lower level...... of autonomous consumers. The control system is tasked with balancing electric power production and consumption within the smart grid, and makes active use of the flexibility of a large number of power producing and/or power consuming units. The objective is to accommodate the load variation on the grid, arising...

  19. P-Adic Analog of Navier–Stokes Equations: Dynamics of Fluid’s Flow in Percolation Networks (from Discrete Dynamics with Hierarchic Interactions to Continuous Universal Scaling Model

    Directory of Open Access Journals (Sweden)

    Klaudia Oleschko

    2017-04-01

    Full Text Available Recently p-adic (and, more generally, ultrametric spaces representing tree-like networks of percolation, and as a special case of capillary patterns in porous media, started to be used to model the propagation of fluids (e.g., oil, water, oil-in-water, and water-in-oil emulsion. The aim of this note is to derive p-adic dynamics described by fractional differential operators (Vladimirov operators starting with discrete dynamics based on hierarchically-structured interactions between the fluids’ volumes concentrated at different levels of the percolation tree and coming to the multiscale universal topology of the percolating nets. Similar systems of discrete hierarchic equations were widely applied to modeling of turbulence. However, in the present work this similarity is only formal since, in our model, the trees are real physical patterns with a tree-like topology of capillaries (or fractures in random porous media (not cascade trees, as in the case of turbulence, which we will be discussed elsewhere for the spinner flowmeter commonly used in the petroleum industry. By going to the “continuous limit” (with respect to the p-adic topology we represent the dynamics on the tree-like configuration space as an evolutionary nonlinear p-adic fractional (pseudo- differential equation, the tree-like analog of the Navier–Stokes equation. We hope that our work helps to come closer to a nonlinear equation solution, taking into account the scaling, hierarchies, and formal derivations, imprinted from the similar properties of the real physical world. Once this coupling is resolved, the more problematic question of information scaling in industrial applications will be achieved.

  20. Theinfluence of a hierarchical porous carbon network on the coherent dynamics of a nanoconfined room temperature ionic liquid: A neutron spin echo and atomistic simulation investigation

    Energy Technology Data Exchange (ETDEWEB)

    Banuelos, Jose Leo [ORNL; Feng, Guang [ORNL; Fulvio, Pasquale F [ORNL; Li, Song [Vanderbilt University, Nashville; Rother, Gernot [ORNL; Arend, Nikolas [ORNL; Faraone, Antonio [National Institute of Standards and Technology (NIST); Dai, Sheng [ORNL; Cummings, Peter T [ORNL; Wesolowski, David J [ORNL

    2014-01-01

    The molecular-scale dynamic properties of the room temperature ionic liquid (RTIL) 1-butyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, or [C4mim+ ][Tf2N ], confined in hierarchical microporous mesoporous carbon, were investigated using neutron spin echo (NSE) and molecular dynamics (MD) simulations. Both NSE and MD reveal pronounced slowing of the overall collective dynamics, including the presence of an immobilized fraction of RTIL at the pore wall, on the time scales of these approaches. A fraction of the dynamics, corresponding to RTIL inside 0.75 nm micropores located along the mesopore surfaces, are faster than those of RTIL in direct contact with the walls of 5.8 nm and 7.8 nm cylindrical mesopores. This behavior is ascribed to the near-surface confined-ion density fluctuations resulting from the ion ion and ion wall interactions between the micropores and mesopores as well as their confinement geometries. Strong micropore RTIL interactions result in less-coordinated RTIL within the micropores than in the bulk fluid. Increasing temperature from 296 K to 353 K reduces the immobilized RTIL fraction and results in nearly an order of magnitude increase in the RTIL dynamics. The observed interfacial phenomena underscore the importance of tailoring the surface properties of porous carbons to achieve desirable electrolyte dynamic behavior, since this impacts the performance in applications such as electrical energy storage devices.

  1. Flat Cellular (UMTS) Networks

    NARCIS (Netherlands)

    Bosch, H.G.P.; Samuel, L.G.; Mullender, S.J.; Polakos, P.; Rittenhouse, G.

    2007-01-01

    Traditionally, cellular systems have been built in a hierarchical manner: many specialized cellular access network elements that collectively form a hierarchical cellular system. When 2G and later 3G systems were designed there was a good reason to make system hierarchical: from a cost-perspective i

  2. Hierarchical bismuth phosphate microspheres with high photocatalytic performance

    Energy Technology Data Exchange (ETDEWEB)

    Pei, Lizhai; Wei, Tian; Lin, Nan; Yu, Haiyun [Anhui University of Technology, Ma' anshan (China). Key Laboratory of Materials Science and Processing of Anhui Province

    2016-05-15

    Hierarchical bismuth phosphate microspheres have been prepared by a simple hydrothermal process with polyvinyl pyrrolidone. Scanning electron microscopy observations show that the hierarchical bismuth phosphate microspheres consist of nanosheets with a thickness of about 30 nm. The diameter of the microspheres is about 1 - 3 μm. X-ray diffraction analysis shows that the microspheres are comprised of triclinic Bi{sub 23}P{sub 4}O{sub 44.5} phase. The formation of the hierarchical microspheres depends on polyvinyl pyrrolidone concentration, hydrothermal temperature and reaction time. Gentian violet acts as the pollutant model for investigating the photocatalytic activity of the hierarchical bismuth phosphate microspheres under ultraviolet-visible light irradiation. Irradiation time, dosage of the hierarchical microspheres and initial gentian violet concentration on the photocatalytic efficiency are also discussed. The hierarchical bismuth phosphate microspheres show good photocatalytic performance for gentian violet removal in aqueous solution.

  3. A P2P NETWORK-BASED HIERARCHICAL OVERLAY MULTICAST MODEL%一种基于P2P网络的层次化覆盖多播模型

    Institute of Scientific and Technical Information of China (English)

    陈良彬; 李强

    2011-01-01

    P2P网络的应用日益广泛,但是针对网络中各个终端主机网络接口带宽各异的实际情况,目前的覆盖多播模型没有综合考虑节点的延迟和实际可用带宽的限制.针对上述问题,提出了一种基于P2P网络的层次化覆盖多播模型(HOMM),该模型综合考虑了延迟和带宽两种因素,采用优先度作为构建ALM树的标准,在簇内构建局部ALM树,同时节点的加入、失效等操作的影响只局限于较小的局部范围内,使整个P2P网络的数据转发负载更为均衡.仿真实验表明该模型具有高效性、健壮性,能够很好地适应终端主机网络接口带宽各异的大规模组播环境.%P2P network is widely used. In dealing with the fact that different end hosts in real network have different network interface bandwidth, present overlay multicast models haven't taken bandwidth and latency into consideration very well. In this paper, a hierarchical overlay multicast model based on P2P network(HOMM) is proposed; it takes both the latency and available bandwidth of peers into consideration, introducing the concept of priority as the standard to build ALM tree, and it adopts the idea of building local ALM tree in the cluster.At the same time influence of these operations such as peer arrivals and departures is limited in small local range, which makes whole data forwarding load of P2P network more balance. The result of simulation demonstrates that this model is efficient and robust, it can well adapt to the large scale multicast environment with various network interface bandwidth of end host.

  4. Self-consistent modeling of entangled network strands and linear dangling structures in a single-strand mean-field slip-link model

    DEFF Research Database (Denmark)

    Jensen, Mette Krog; Khaliullin, Renat; Schieber, Jay D.

    2012-01-01

    Linear viscoelastic (LVE) measurements as well as non-linear elongation measurements have been performed on stoichiometrically imbalanced polymeric networks to gain insight into the structural influence on the rheological response (Jensen et al., Rheol Acta 49(1):1–13, 2010). In particular, we se...

  5. Parallel hierarchical radiosity rendering

    Energy Technology Data Exchange (ETDEWEB)

    Carter, M.

    1993-07-01

    In this dissertation, the step-by-step development of a scalable parallel hierarchical radiosity renderer is documented. First, a new look is taken at the traditional radiosity equation, and a new form is presented in which the matrix of linear system coefficients is transformed into a symmetric matrix, thereby simplifying the problem and enabling a new solution technique to be applied. Next, the state-of-the-art hierarchical radiosity methods are examined for their suitability to parallel implementation, and scalability. Significant enhancements are also discovered which both improve their theoretical foundations and improve the images they generate. The resultant hierarchical radiosity algorithm is then examined for sources of parallelism, and for an architectural mapping. Several architectural mappings are discussed. A few key algorithmic changes are suggested during the process of making the algorithm parallel. Next, the performance, efficiency, and scalability of the algorithm are analyzed. The dissertation closes with a discussion of several ideas which have the potential to further enhance the hierarchical radiosity method, or provide an entirely new forum for the application of hierarchical methods.

  6. HIERARCHICAL OPTIMIZATION MODEL ON GEONETWORK

    Directory of Open Access Journals (Sweden)

    Z. Zha

    2012-07-01

    Full Text Available In existing construction experience of Spatial Data Infrastructure (SDI, GeoNetwork, as the geographical information integrated solution, is an effective way of building SDI. During GeoNetwork serving as an internet application, several shortcomings are exposed. The first one is that the time consuming of data loading has been considerately increasing with the growth of metadata count. Consequently, the efficiency of query and search service becomes lower. Another problem is that stability and robustness are both ruined since huge amount of metadata. The final flaw is that the requirements of multi-user concurrent accessing based on massive data are not effectively satisfied on the internet. A novel approach, Hierarchical Optimization Model (HOM, is presented to solve the incapability of GeoNetwork working with massive data in this paper. HOM optimizes the GeoNetwork from these aspects: internal procedure, external deployment strategies, etc. This model builds an efficient index for accessing huge metadata and supporting concurrent processes. In this way, the services based on GeoNetwork can maintain stable while running massive metadata. As an experiment, we deployed more than 30 GeoNetwork nodes, and harvest nearly 1.1 million metadata. From the contrast between the HOM-improved software and the original one, the model makes indexing and retrieval processes more quickly and keeps the speed stable on metadata amount increasing. It also shows stable on multi-user concurrent accessing to system services, the experiment achieved good results and proved that our optimization model is efficient and reliable.

  7. A general strategy to determine the congruence between a hierarchical and a non-hierarchical classification

    Directory of Open Access Journals (Sweden)

    Marín Ignacio

    2007-11-01

    Full Text Available Abstract Background Classification procedures are widely used in phylogenetic inference, the analysis of expression profiles, the study of biological networks, etc. Many algorithms have been proposed to establish the similarity between two different classifications of the same elements. However, methods to determine significant coincidences between hierarchical and non-hierarchical partitions are still poorly developed, in spite of the fact that the search for such coincidences is implicit in many analyses of massive data. Results We describe a novel strategy to compare a hierarchical and a dichotomic non-hierarchical classification of elements, in order to find clusters in a hierarchical tree in which elements of a given "flat" partition are overrepresented. The key improvement of our strategy respect to previous methods is using permutation analyses of ranked clusters to determine whether regions of the dendrograms present a significant enrichment. We show that this method is more sensitive than previously developed strategies and how it can be applied to several real cases, including microarray and interactome data. Particularly, we use it to compare a hierarchical representation of the yeast mitochondrial interactome and a catalogue of known mitochondrial protein complexes, demonstrating a high level of congruence between those two classifications. We also discuss extensions of this method to other cases which are conceptually related. Conclusion Our method is highly sensitive and outperforms previously described strategies. A PERL script that implements it is available at http://www.uv.es/~genomica/treetracker.

  8. Hierarchical Representation Learning for Kinship Verification.

    Science.gov (United States)

    Kohli, Naman; Vatsa, Mayank; Singh, Richa; Noore, Afzel; Majumdar, Angshul

    2017-01-01

    Kinship verification has a number of applications such as organizing large collections of images and recognizing resemblances among humans. In this paper, first, a human study is conducted to understand the capabilities of human mind and to identify the discriminatory areas of a face that facilitate kinship-cues. The visual stimuli presented to the participants determine their ability to recognize kin relationship using the whole face as well as specific facial regions. The effect of participant gender and age and kin-relation pair of the stimulus is analyzed using quantitative measures such as accuracy, discriminability index d' , and perceptual information entropy. Utilizing the information obtained from the human study, a hierarchical kinship verification via representation learning (KVRL) framework is utilized to learn the representation of different face regions in an unsupervised manner. We propose a novel approach for feature representation termed as filtered contractive deep belief networks (fcDBN). The proposed feature representation encodes relational information present in images using filters and contractive regularization penalty. A compact representation of facial images of kin is extracted as an output from the learned model and a multi-layer neural network is utilized to verify the kin accurately. A new WVU kinship database is created, which consists of multiple images per subject to facilitate kinship verification. The results show that the proposed deep learning framework (KVRL-fcDBN) yields the state-of-the-art kinship verification accuracy on the WVU kinship database and on four existing benchmark data sets. Furthermore, kinship information is used as a soft biometric modality to boost the performance of face verification via product of likelihood ratio and support vector machine based approaches. Using the proposed KVRL-fcDBN framework, an improvement of over 20% is observed in the performance of face verification.

  9. A Method for Improving the Consistency of Judging Matrix Using Neural Network%一种利用神经网络改善判断矩阵一致性的方法

    Institute of Scientific and Technical Information of China (English)

    孙首群; 于建华; 杨凡; 满微微

    2011-01-01

    With respect to the problem of improving the consistency of judgement matrix in analytic hierarchy Process, a method is proposed to improve the consistency of judgement matrix by using neural network.Based on the BP neural network model, this paper transforms the problem of adjusting the consistency of judgement matrix into the problem of multi-input and multi-output solution of BP neural network.The judgement matrix return a-gain for the expert further is adjusted after the BP neural network algorithm is adjusted to conform to Saaty scale.Numerical examples indicate that this method is effective in practice.%针对层次分析法中判断矩阵致性改进问题,提出了一种利用神经网络改善判断矩阵一致性的方法.本文在建立了BP神经网络模型的基础上,把判断矩阵一致性调整问题转化为BP神经网络的多输入多输出求解问题.经BP神经网络算法调整过的判断矩阵再返回给专家进一步调整使其符合萨迪标度.计算实例表明,此种方法是可行的.

  10. 三角网约束下的层次匹配方法%Hierarchical Matching Method with Triangle Network Constraint

    Institute of Scientific and Technical Information of China (English)

    郑顺义; 马电; 王晓南

    2014-01-01

    Focusing on dense matching in photogrammetry ,an image matching method by combing the triangle network constraint with pyramid strategy has been proposed in this paper .Firstly ,feature points are extracted in each layer ,and then image matching is done under the constraint of a Delaunay triangle network ,which has been constructed by the matching result of a higher layer .The pyramid strategy itself shows a coarse‐to‐fine process and meanwhile Delaunay triangle network can pass a powerful match control from the higher layer to the lower layer .Experiments shows that the proposed method can get a reliable ,high‐accuracy and dense match result and the generated point cloud can describe the topography well .%针对数字摄影测量中密集匹配问题,提出一种三角网约束与金字塔策略相结合的影像匹配方法。该方法在每层金字塔影像中提取特征点,利用金字塔上层影像的匹配结果构建Delaunay三角网,约束和指导金字塔下层影像的匹配;金字塔策略本身体现由粗到精的匹配过程,而Delaunay三角网能有效地将上层匹配结果作为约束传递到下层影像。实验结果证明,文中方法生成的密集匹配点云密度大、误匹配少、精度高,能有效地反映地貌特征。

  11. A hyperaccumulation pathway to three-dimensional hierarchical porous nanocomposites for highly robust high-power electrodes

    Science.gov (United States)

    Zhu, Jian; Shan, Yu; Wang, Tao; Sun, Hongtao; Zhao, Zipeng; Mei, Lin; Fan, Zheng; Xu, Zhi; Shakir, Imran; Huang, Yu; Lu, Bingan; Duan, Xiangfeng

    2016-11-01

    Natural plants consist of a hierarchical architecture featuring an intricate network of highly interconnected struts and channels that not only ensure extraordinary structural stability, but also allow efficient transport of nutrients and electrolytes throughout the entire plants. Here we show that a hyperaccumulation effect can allow efficient enrichment of selected metal ions (for example, Sn2+, Mn2+) in the halophytic plants, which can then be converted into three-dimensional carbon/metal oxide (3DC/MOx) nanocomposites with both the composition and structure hierarchy. The nanocomposites retain the 3D hierarchical porous network structure, with ultrafine MOx nanoparticles uniformly distributed in multi-layers of carbon derived from the cell wall, cytomembrane and tonoplast. It can simultaneously ensure efficient electron and ion transport and help withstand the mechanical stress during the repeated electrochemical cycles, enabling the active material to combine high specific capacities typical of batteries and the cycling stability of supercapacitors.

  12. Classification using Hierarchical Naive Bayes models

    DEFF Research Database (Denmark)

    Langseth, Helge; Dyhre Nielsen, Thomas

    2006-01-01

    Classification problems have a long history in the machine learning literature. One of the simplest, and yet most consistently well-performing set of classifiers is the Naïve Bayes models. However, an inherent problem with these classifiers is the assumption that all attributes used to describe...... an instance are conditionally independent given the class of that instance. When this assumption is violated (which is often the case in practice) it can reduce classification accuracy due to “information double-counting” and interaction omission. In this paper we focus on a relatively new set of models......, termed Hierarchical Naïve Bayes models. Hierarchical Naïve Bayes models extend the modeling flexibility of Naïve Bayes models by introducing latent variables to relax some of the independence statements in these models. We propose a simple algorithm for learning Hierarchical Naïve Bayes models...

  13. Self-assembled biomimetic superhydrophobic hierarchical arrays.

    Science.gov (United States)

    Yang, Hongta; Dou, Xuan; Fang, Yin; Jiang, Peng

    2013-09-01

    Here, we report a simple and inexpensive bottom-up technology for fabricating superhydrophobic coatings with hierarchical micro-/nano-structures, which are inspired by the binary periodic structure found on the superhydrophobic compound eyes of some insects (e.g., mosquitoes and moths). Binary colloidal arrays consisting of exemplary large (4 and 30 μm) and small (300 nm) silica spheres are first assembled by a scalable Langmuir-Blodgett (LB) technology in a layer-by-layer manner. After surface modification with fluorosilanes, the self-assembled hierarchical particle arrays become superhydrophobic with an apparent water contact angle (CA) larger than 150°. The throughput of the resulting superhydrophobic coatings with hierarchical structures can be significantly improved by templating the binary periodic structures of the LB-assembled colloidal arrays into UV-curable fluoropolymers by a soft lithography approach. Superhydrophobic perfluoroether acrylate hierarchical arrays with large CAs and small CA hysteresis can be faithfully replicated onto various substrates. Both experiments and theoretical calculations based on the Cassie's dewetting model demonstrate the importance of the hierarchical structure in achieving the final superhydrophobic surface states. Copyright © 2013 Elsevier Inc. All rights reserved.

  14. Clustering of resting state networks.

    Directory of Open Access Journals (Sweden)

    Megan H Lee

    Full Text Available BACKGROUND: The goal of the study was to demonstrate a hierarchical structure of resting state activity in the healthy brain using a data-driven clustering algorithm. METHODOLOGY/PRINCIPAL FINDINGS: The fuzzy-c-means clustering algorithm was applied to resting state fMRI data in cortical and subcortical gray matter from two groups acquired separately, one of 17 healthy individuals and the second of 21 healthy individuals. Different numbers of clusters and different starting conditions were used. A cluster dispersion measure determined the optimal numbers of clusters. An inner product metric provided a measure of similarity between different clusters. The two cluster result found the task-negative and task-positive systems. The cluster dispersion measure was minimized with seven and eleven clusters. Each of the clusters in the seven and eleven cluster result was associated with either the task-negative or task-positive system. Applying the algorithm to find seven clusters recovered previously described resting state networks, including the default mode network, frontoparietal control network, ventral and dorsal attention networks, somatomotor, visual, and language networks. The language and ventral attention networks had significant subcortical involvement. This parcellation was consistently found in a large majority of algorithm runs under different conditions and was robust to different methods of initialization. CONCLUSIONS/SIGNIFICANCE: The clustering of resting state activity using different optimal numbers of clusters identified resting state networks comparable to previously obtained results. This work reinforces the observation that resting state networks are hierarchically organized.

  15. Hierarchical Porous Structures

    Energy Technology Data Exchange (ETDEWEB)

    Grote, Christopher John [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-06-07

    Materials Design is often at the forefront of technological innovation. While there has always been a push to generate increasingly low density materials, such as aero or hydrogels, more recently the idea of bicontinuous structures has gone more into play. This review will cover some of the methods and applications for generating both porous, and hierarchically porous structures.

  16. Finding Hierarchical and Overlapping Dense Subgraphs using Nucleus Decompositions

    Energy Technology Data Exchange (ETDEWEB)

    Seshadhri, Comandur [The Ohio State Univ., Columbus, OH (United States); Pinar, Ali [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Sariyuce, Ahmet Erdem [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Catalyurek, Umit [The Ohio State Univ., Columbus, OH (United States)

    2014-11-01

    Finding dense substructures in a graph is a fundamental graph mining operation, with applications in bioinformatics, social networks, and visualization to name a few. Yet most standard formulations of this problem (like clique, quasiclique, k-densest subgraph) are NP-hard. Furthermore, the goal is rarely to nd the \\true optimum", but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine a hierarchical structure among them. Current dense subgraph nding algorithms usually optimize some objective, and only nd a few such subgraphs without providing any hierarchy. It is also not clear how to account for overlaps in dense substructures. We de ne the nucleus decomposition of a graph, which represents the graph as a forest of nuclei. Each nucleus is a subgraph where smaller cliques are present in many larger cliques. The forest of nuclei is a hierarchy by containment, where the edge density increases as we proceed towards leaf nuclei. Sibling nuclei can have limited intersections, which allows for discovery of overlapping dense subgraphs. With the right parameters, the nuclear decomposition generalizes the classic notions of k-cores and k-trusses. We give provable e cient algorithms for nuclear decompositions, and empirically evaluate their behavior in a variety of real graphs. The tree of nuclei consistently gives a global, hierarchical snapshot of dense substructures, and outputs dense subgraphs of higher quality than other state-of-theart solutions. Our algorithm can process graphs with tens of millions of edges in less than an hour.

  17. Evaluation of hierarchical temporal memory for a real world application

    OpenAIRE

    Melis, Wim J.C.; Chizuwa, Shuhei; Kameyama, Michitaka

    2010-01-01

    A large number of real world applications, such as user support systems, can still not be performed easily by conventional algorithms in comparison with the human brain. Such intelligence is often implemented, by using probability based systems. This paper focuses on comparing the implementation of a cellular phone intention estimation example on a Bayesian Network and Hierarchical Temporal Memory. It is found that Hierarchical Temporal Memory is a system that requires little effort for desig...

  18. Zinc oxide's hierarchical nanostructure and its photocatalytic properties

    DEFF Research Database (Denmark)

    Kanjwal, Muzafar Ahmed; Sheikh, Faheem A.; Barakat, Nasser A. M.

    2012-01-01

    In this study, a new hierarchical nanostructure that consists of zinc oxide (ZnO) was produced by the electrospinning process followed by a hydrothermal technique. First, electrospinning of a colloidal solution that consisted of zinc nanoparticles, zinc acetate dihydrate and poly(vinyl alcohol) w...... technique was used. Methylene blue dihydrate was used to check the photocatalytic ability of the produced nanostructures. The results indicated that the hierarchical nanostructure had a better performance than the other form....

  19. A Hierarchical Evaluation Approach for Network Security Based on Threat Spread Model%基于威胁传播模型的层次化网络安全评估方法

    Institute of Scientific and Technical Information of China (English)

    陈锋; 刘德辉; 张怡; 苏金树

    2011-01-01

    Network system is generally faced with invasion of the external and internal threat agents.Moreover, threat agents have the capability of spreading threats via the interrelation among vulnerabilities and components in the network, bringing about potential threats.Designing a reasonable model to identify, analyze and quantitatively measure the consequences resulting from potential threats is one of the main challenges that the research of network security evaluation faces.For this issue, a hierarchical evaluation approach based on the threat spread model for the network security is proposed.Firstly the threat spread model is put forward to identify the threat agents,analyze the spread paths of threats, and predict potential threats.The threat spread model includes target network model, threat agent model, threat spread graphs and threat spread algorithm.On this basis, the security measure model is presented to compute the danger indexes of services, hosts and network system respectively.The security measure model is composed of spread graphs, metrics,metric computing functions and index computing functions.Based on the novel approach, the prototype system is implemented and applied by an enterprise local network system.The result demonstrates the correctness of the threat spread model and the advantage of the approach compared with traditional methods.%网络系统不仅面临外部和内部威胁主体的入侵,同时威胁主体会利用脆弱点间、网络组件间的相互作用关系进行威胁传播,产生严重的潜在威胁.设计合理的模型对潜在威胁进行识别、分析,并量化测度其对网络安全的影响,是当前网络安全评估所面临的主要挑战之一.针对该问题,提出了一种基于威胁传播模型的层次化网络安全评估方法.首先提出了威胁传播模型识别目标网络系统的威胁主体,分析其传播路径,预测其对网络系统的潜在破坏;在此基础上提出了层次化网络安全测度

  20. Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?

    Science.gov (United States)

    Czégel, Dániel; Palla, Gergely

    2015-01-01

    Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology. PMID:26657012

  1. Random walk hierarchy measure: What is more hierarchical, a chain, a tree or a star?

    Science.gov (United States)

    Czégel, Dániel; Palla, Gergely

    2015-12-10

    Signs of hierarchy are prevalent in a wide range of systems in nature and society. One of the key problems is quantifying the importance of hierarchical organisation in the structure of the network representing the interactions or connections between the fundamental units of the studied system. Although a number of notable methods are already available, their vast majority is treating all directed acyclic graphs as already maximally hierarchical. Here we propose a hierarchy measure based on random walks on the network. The novelty of our approach is that directed trees corresponding to multi level pyramidal structures obtain higher hierarchy scores compared to directed chains and directed stars. Furthermore, in the thermodynamic limit the hierarchy measure of regular trees is converging to a well defined limit depending only on the branching number. When applied to real networks, our method is computationally very effective, as the result can be evaluated with arbitrary precision by subsequent multiplications of the transition matrix describing the random walk process. In addition, the tests on real world networks provided very intuitive results, e.g., the trophic levels obtained from our approach on a food web were highly consistent with former results from ecology.

  2. 层次化电力信息网络威胁态势评估方法%Hierarchical Cyber-Threat Situation Evaluation Method for Electric Power Information Network

    Institute of Scientific and Technical Information of China (English)

    王宇飞; 徐志博; 王婧

    2013-01-01

    为了实时描述电力信息网络的宏观安全状况,提出了一种层次化的网络威胁态势评估方法并予以系统实现.该方法通过灰色聚类分析将各种网络威胁按危害程度划分为强、中、弱3类,并以这3类作为层次分析法中准则层的设计依据,再利用层次分析法构造层次化的评估指标体系并确定各种网络威胁的权重.将各种网络威胁的权重与其实时发生次数加权求和得到网络威胁态势值,其数值大小反映了电力信息网络实时安全状况.最后的实验和系统运行情况表明,该方法可有效地展示电力信息网络安全状况,有助于提高其安全防护水平.%To describe the macro safety situation of electric power information network in real-time,an hierarchical threat situation evaluation method is proposed and implemented.This method adopt the gray clustering analysis to categorize the damage degree as strong,medium,weak in total 3 types,hased on which the principle layer of the analytic hierarchy process is designed.According to the evaluation index system of the structure layer of analytic hierarchy process,the weight of the cyber-threat is confirmed.And the cyber-threat situation value can be obtained by the weighted summation of each cyber-threat weight and its real-time occurrence frequency,which reports the real-time safety situation of the electric power network.The final experiment and system operation shows that,this method may effectively describe the safety situation of electric power network and be helpful for the development of safety and protection level.

  3. Three Layer Hierarchical Model for Chord

    Directory of Open Access Journals (Sweden)

    Waqas A. Imtiaz

    2012-12-01

    Full Text Available Increasing popularity of decentralized Peer-to-Peer (P2P architecture emphasizes on the need to come across an overlay structure that can provide efficient content discovery mechanism, accommodate high churn rate and adapt to failures in the presence of heterogeneity among the peers. Traditional p2p systems incorporate distributed client-server communication, which finds the peer efficiently that store a desires data item, with minimum delay and reduced overhead. However traditional models are not able to solve the problems relating scalability and high churn rates. Hierarchical model were introduced to provide better fault isolation, effective bandwidth utilization, a superior adaptation to the underlying physical network and a reduction of the lookup path length as additional advantages. It is more efficient and easier to manage than traditional p2p networks. This paper discusses a further step in p2p hierarchy via 3-layers hierarchical model with distributed database architecture in different layer, each of which is connected through its root. The peers are divided into three categories according to their physical stability and strength. They are Ultra Super-peer, Super-peer and Ordinary Peer and we assign these peers to first, second and third level of hierarchy respectively. Peers in a group in lower layer have their own local database which hold as associated super-peer in middle layer and access the database among the peers through user queries. In our 3-layer hierarchical model for DHT algorithms, we used an advanced Chord algorithm with optimized finger table which can remove the redundant entry in the finger table in upper layer that influences the system to reduce the lookup latency. Our research work finally resulted that our model really provides faster search since the network lookup latency is decreased by reducing the number of hops. The peers in such network then can contribute with improve functionality and can perform well in

  4. Galaxy formation through hierarchical clustering

    Science.gov (United States)

    White, Simon D. M.; Frenk, Carlos S.

    1991-01-01

    Analytic methods for studying the formation of galaxies by gas condensation within massive dark halos are presented. The present scheme applies to cosmogonies where structure grows through hierarchical clustering of a mixture of gas and dissipationless dark matter. The simplest models consistent with the current understanding of N-body work on dissipationless clustering, and that of numerical and analytic work on gas evolution and cooling are adopted. Standard models for the evolution of the stellar population are also employed, and new models for the way star formation heats and enriches the surrounding gas are constructed. Detailed results are presented for a cold dark matter universe with Omega = 1 and H(0) = 50 km/s/Mpc, but the present methods are applicable to other models. The present luminosity functions contain significantly more faint galaxies than are observed.

  5. Collaborative Hierarchical Sparse Modeling

    CERN Document Server

    Sprechmann, Pablo; Sapiro, Guillermo; Eldar, Yonina C

    2010-01-01

    Sparse modeling is a powerful framework for data analysis and processing. Traditionally, encoding in this framework is done by solving an l_1-regularized linear regression problem, usually called Lasso. In this work we first combine the sparsity-inducing property of the Lasso model, at the individual feature level, with the block-sparsity property of the group Lasso model, where sparse groups of features are jointly encoded, obtaining a sparsity pattern hierarchically structured. This results in the hierarchical Lasso, which shows important practical modeling advantages. We then extend this approach to the collaborative case, where a set of simultaneously coded signals share the same sparsity pattern at the higher (group) level but not necessarily at the lower one. Signals then share the same active groups, or classes, but not necessarily the same active set. This is very well suited for applications such as source separation. An efficient optimization procedure, which guarantees convergence to the global opt...

  6. Green remanufacturing hierarchical network management model and Application%绿色再制造管理层次网络分析模型及应用

    Institute of Scientific and Technical Information of China (English)

    谭显波

    2013-01-01

    The human understanding of the importance and necessity of environmental protection is more and more deep,China put forward the “sustainable development strategy”,one of its aims is to realize the harmony of human and natural environment.Put forward the concept of green remanufacturing,also in order to realize the resource from the behavior of the economy,to protect environment.This article mainly from the influence and control of these two factors to explore the management problems of the green remanufacturing. And analysis of green remanufacturing management level network analysis model based on the application,the implementation process management strategy.%  人类对于环境保护的重要性和必要性的认识越来越深刻,我国提出的“可持续发展战略”,其目的之一也是为了实现人类与自然环境的和谐。而绿色再制造这个概念的提出,也是为了从行为上真正的实现资源的节约,从而保护环境。本文主要从影响与控制这两个因素来探讨绿色再制造的管理问题。并分析绿色再制造管理基于层次网络分析模型的应用,管理战略的实施过程。

  7. Hierarchically Structured Electrospun Fibers

    Directory of Open Access Journals (Sweden)

    Nicole E. Zander

    2013-01-01

    Full Text Available Traditional electrospun nanofibers have a myriad of applications ranging from scaffolds for tissue engineering to components of biosensors and energy harvesting devices. The generally smooth one-dimensional structure of the fibers has stood as a limitation to several interesting novel applications. Control of fiber diameter, porosity and collector geometry will be briefly discussed, as will more traditional methods for controlling fiber morphology and fiber mat architecture. The remainder of the review will focus on new techniques to prepare hierarchically structured fibers. Fibers with hierarchical primary structures—including helical, buckled, and beads-on-a-string fibers, as well as fibers with secondary structures, such as nanopores, nanopillars, nanorods, and internally structured fibers and their applications—will be discussed. These new materials with helical/buckled morphology are expected to possess unique optical and mechanical properties with possible applications for negative refractive index materials, highly stretchable/high-tensile-strength materials, and components in microelectromechanical devices. Core-shell type fibers enable a much wider variety of materials to be electrospun and are expected to be widely applied in the sensing, drug delivery/controlled release fields, and in the encapsulation of live cells for biological applications. Materials with a hierarchical secondary structure are expected to provide new superhydrophobic and self-cleaning materials.

  8. HDS: Hierarchical Data System

    Science.gov (United States)

    Pearce, Dave; Walter, Anton; Lupton, W. F.; Warren-Smith, Rodney F.; Lawden, Mike; McIlwrath, Brian; Peden, J. C. M.; Jenness, Tim; Draper, Peter W.

    2015-02-01

    The Hierarchical Data System (HDS) is a file-based hierarchical data system designed for the storage of a wide variety of information. It is particularly suited to the storage of large multi-dimensional arrays (with their ancillary data) where efficient access is needed. It is a key component of the Starlink software collection (ascl:1110.012) and is used by the Starlink N-Dimensional Data Format (NDF) library (ascl:1411.023). HDS organizes data into hierarchies, broadly similar to the directory structure of a hierarchical filing system, but contained within a single HDS container file. The structures stored in these files are self-describing and flexible; HDS supports modification and extension of structures previously created, as well as functions such as deletion, copying, and renaming. All information stored in HDS files is portable between the machines on which HDS is implemented. Thus, there are no format conversion problems when moving between machines. HDS can write files in a private binary format (version 4), or be layered on top of HDF5 (version 5).

  9. Hierarchical video summarization

    Science.gov (United States)

    Ratakonda, Krishna; Sezan, M. Ibrahim; Crinon, Regis J.

    1998-12-01

    We address the problem of key-frame summarization of vide in the absence of any a priori information about its content. This is a common problem that is encountered in home videos. We propose a hierarchical key-frame summarization algorithm where a coarse-to-fine key-frame summary is generated. A hierarchical key-frame summary facilitates multi-level browsing where the user can quickly discover the content of the video by accessing its coarsest but most compact summary and then view a desired segment of the video with increasingly more detail. At the finest level, the summary is generated on the basis of color features of video frames, using an extension of a recently proposed key-frame extraction algorithm. The finest level key-frames are recursively clustered using a novel pairwise K-means clustering approach with temporal consecutiveness constraint. We also address summarization of MPEG-2 compressed video without fully decoding the bitstream. We also propose efficient mechanisms that facilitate decoding the video when the hierarchical summary is utilized in browsing and playback of video segments starting at selected key-frames.

  10. 基于多源融合的网络安全态势层次感知%Hierarchical Awareness of Network Security Situation Based on Multi-source Fusion

    Institute of Scientific and Technical Information of China (English)

    张淑雯; 刘效武; 孙雪岩

    2016-01-01

    网络安全态势感知是近年来的一种新型安全技术,因其可以解决传统安全技术难以解决的数据源单一、虚警率高等问题,提升对全局安全状况的动态理解能力而备受关注。针对现有的研究,提出一种基于多源融合的网络安全态势层次感知模型,利用蚁群D-S证据组合规则处理多源融合问题,从而减少态势参数赋予主观性强的问题。同时,利用神经网络搜索安全事件的关键特征,降低数据维数,避免维数爆炸,提高实时性。最后采用层次化感知算法,将离散报警映射为动态威胁趋势,提升对网络安全的定量分析能力。仿真结果表明,提出的算法能够提高检测率,降低误警率,可以动态监控网络安全威胁的演化状态。%In recent year,network security situation awareness is an emerging security technology and garners widespread attentions be-cause it can solve the issues that the traditional security technology difficult to deal with,such as a single data source and the high false a-larm rate,and enhance the dynamic understanding abilities for the overall security situation. For the current research,a network security situation awareness model is proposed based on multi-source fusion which utilizes ant colony D-S evidence combination rule to deal with the multi-source data fusion problem with aim of reducing the subjective dependence of situation parameters. Meanwhile,the neural net-work is applied for searching key characteristics of security events to reduce data dimension,avoid dimension explosion and improve the real-time performance. It also discusses a hierarchical awareness algorithm and can map the discrete alarms to the dynamic threats tenden-cy in order to improve the capacity of quantitative analysis for network security. The simulation shows that the proposed model and algo-rithm can improve the detection rate and decrease false alarm rate,and dynamically monitor the

  11. An Hierarchical Approach to Big Data

    CERN Document Server

    Allen, M G; Boch, T; Durand, D; Oberto, A; Merin, B; Stoehr, F; Genova, F; Pineau, F-X; Salgado, J

    2016-01-01

    The increasing volumes of astronomical data require practical methods for data exploration, access and visualisation. The Hierarchical Progressive Survey (HiPS) is a HEALPix based scheme that enables a multi-resolution approach to astronomy data from the individual pixels up to the whole sky. We highlight the decisions and approaches that have been taken to make this scheme a practical solution for managing large volumes of heterogeneous data. Early implementors of this system have formed a network of HiPS nodes, with some 250 diverse data sets currently available, with multiple mirror implementations for important data sets. This hierarchical approach can be adapted to expose Big Data in different ways. We describe how the ease of implementation, and local customisation of the Aladin Lite embeddable HiPS visualiser have been keys for promoting collaboration on HiPS.

  12. 土地系统多级综合观测研究网络建设框架%Strategic Framework of China Land System Hierarchical Comprehensive Observation and Research Network

    Institute of Scientific and Technical Information of China (English)

    张衍毓; 郭旭东; 陈美景

    2016-01-01

    The purpose of this study is to define the functions, organizational framework and cooperative innovation mechanism of China Land System Observation and Research Network(CLSORN) based on land system science theories, and to put forward general ideas of land system observation technologies system, data management system, land system observation and research bases construction and network distribution, and to construct the framework for land system comprehensive observation theory, technology, platform and mechanism innovations as well as to build the strategic framework for CLSORN. The methods include literature research, expert interview and fieldwork. The results show that: 1) Land system is a spatiotemporal system of human-land relationship, which is composed of human and natural factors. The core of the land system research is the dynamic changes of land system factors, interaction mechanism among factors and the coupling and control mechanism between human and land. Land system is hierarchical, dynamic and comprehensive, and implementing continuous observation is an effective way to enhance the land system scientific cognition. 2)The functions of CLSORN are land system data observation, scientific research, policy innovation, scientific research resource sharing, staff training, education, and popularization of land science. The contents of CLSORN construction focus on: building hierarchal, synergetic organization framework to link land science and technology innovation among national-regional-county-town/village levels; innovating mechanisms of joint construction, staff exchange, synergic research, sustainable investment, data sharing, and joint investigation to formulate CLSORN operation management policies; against key scientific and research fields, developing indicators and technologies system and web-based data system for land system integrated observation; and optimizing distribution of scientific observation and research bases to form the hierarchal

  13. Synthesis and Characterization of ZnTe Hierarchical Nanostructures

    Directory of Open Access Journals (Sweden)

    Baohua Zhang

    2012-01-01

    Full Text Available Single-crystalline ZnTe hierarchical nanostructures have been successfully synthesized by a simple thermal evaporation technology. The as-prepared products were characterized with X-ray diffraction (XRD, scanning electron microcopy (SEM, transmission electron microscope (TEM, and photoluminescence spectrum (PL. These results showed that the ZnTe hierarchical nanostructures consisted of nanowires and nanolumps. The room temperature PL spectrum exhibited a pure green luminescence centered at 545nm. The growth mechanism of hierarchical nanostructure was also discussed.

  14. Fractal Analysis Based on Hierarchical Scaling in Complex Systems

    CERN Document Server

    Chen, Yanguang

    2016-01-01

    A fractal is in essence a hierarchy with cascade structure, which can be described with a set of exponential functions. From these exponential functions, a set of power laws indicative of scaling can be derived. Hierarchy structure and spatial network proved to be associated with one another. This paper is devoted to exploring the theory of fractal analysis of complex systems by means of hierarchical scaling. Two research methods are utilized to make this study, including logic analysis method and empirical analysis method. The main results are as follows. First, a fractal system such as Cantor set is described from the hierarchical angle of view; based on hierarchical structure, three approaches are proposed to estimate fractal dimension. Second, the hierarchical scaling can be generalized to describe multifractals, fractal complementary sets, and self-similar curve such as logarithmic spiral. Third, complex systems such as urban system are demonstrated to be a self-similar hierarchy. The human settlements i...

  15. Context updates are hierarchical

    Directory of Open Access Journals (Sweden)

    Anton Karl Ingason

    2016-10-01

    Full Text Available This squib studies the order in which elements are added to the shared context of interlocutors in a conversation. It focuses on context updates within one hierarchical structure and argues that structurally higher elements are entered into the context before lower elements, even if the structurally higher elements are pronounced after the lower elements. The crucial data are drawn from a comparison of relative clauses in two head-initial languages, English and Icelandic, and two head-final languages, Korean and Japanese. The findings have consequences for any theory of a dynamic semantics.

  16. Optimization of Hierarchical System for Data Acquisition

    Directory of Open Access Journals (Sweden)

    V. Novotny

    2011-04-01

    Full Text Available Television broadcasting over IP networks (IPTV is one of a number of network applications that are except of media distribution also interested in data acquisition from group of information resources of variable size. IP-TV uses Real-time Transport Protocol (RTP protocol for media streaming and RTP Control Protocol (RTCP protocol for session quality feedback. Other applications, for example sensor networks, have data acquisition as the main task. Current solutions have mostly problem with scalability - how to collect and process information from large amount of end nodes quickly and effectively? The article deals with optimization of hierarchical system of data acquisition. Problem is mathematically described, delay minima are searched and results are proved by simulations.

  17. Preparation and li storage properties of hierarchical porous carbon fibers derived from alginic acid.

    Science.gov (United States)

    Wu, Xing-Long; Chen, Li-Li; Xin, Sen; Yin, Ya-Xia; Guo, Yu-Guo; Kong, Qing-Shan; Xia, Yan-Zhi

    2010-06-21

    One-dimensional (1D) hierarchical porous carbon fibers (HPCFs) have been prepared by controlled carbonization of alginic acid fibers and investigated with scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, nitrogen adsorption-desorption isotherms, and electrochemical tests toward lithium storage. The as-obtained HPCFs consist of a 3D network of nanosized carbon particles with diameters less than 10 nm and exhibit a hierarchical porous architecture composed of both micropores and mesopores. Electrochemical measurements show that HPCFs exhibit excellent rate capability and capacity retention compared with commercial graphite when employed as anode materials for lithium-ion batteries. At the discharge/charge rate of 45 C, the reversible capacity of HPCFs is still as high as 80 mA h g(-1) even after 1500 cycles, which is about five times larger than that of commercial graphite anode. The much improved electrochemical performances could be attributed to the nanosized building blocks, the hierarchical porous structure, and the 1D morphology of HPCFs.

  18. Hierarchical organisation in perception of orientation.

    Science.gov (United States)

    Spinelli, D; Antonucci, G; Daini, R; Martelli, M L; Zoccolotti, P

    1999-01-01

    According to Rock [1990, in The Legacy of Solomon Asch (Hillsdale, NJ: Lawrence Erlbaum Associates)], hierarchical organisation of perception describes cases in which the orientation of an object is affected by the immediately surrounding elements in the visual field. Various experiments were performed to study the hierarchical organisation of orientation perception. In most of them the rod-and-frame-illusion (RFI: change of the apparent vertical measured on a central rod surrounded by a tilted frame) was measured in the presence/absence of a second inner frame. The first three experiments showed that, when the inner frame is vertical, the direction and size of the illusion are consistent with expectancies based on the hierarchical organisation hypothesis. An analysis of published and unpublished data collected on a large number of subjects showed that orientational hierarchical effects are independent from the absolute size of the RFI. In experiments 4 to 7 we examined the perceptual conditions of the inner stimulus (enclosure, orientation, and presence of luminance borders) critical for obtaining a hierarchical organisation effect. Although an inner vertical square was effective in reducing the illusion (experiment 3), an inner circle enclosing the rod was ineffective (experiment 4). This indicates that definite orientation is necessary to modulate the illusion. However, orientational information provided by a vertical or horizontal rectangle presented near the rod, but not enclosing it, did not modulate the RFI (experiment 5). This suggests that the presence of a figure with oriented contours enclosing the rod is critical. In experiments 6 and 7 we studied whether the presence of luminance borders is important or whether the inner upright square might be effective also if made of subjective contours. When the subjective contour figure was salient and the observers perceived it clearly, its effectiveness in modulating the RFI was comparable to that observed with

  19. Three Ways to Link Merge with Hierarchical Concept-Combination

    Directory of Open Access Journals (Sweden)

    Chris Thornton

    2016-11-01

    Full Text Available In the Minimalist Program, language competence is seen to stem from a fundamental ability to construct hierarchical structure, an operation dubbed ‘Merge’. This raises the problem of how to view hierarchical concept-combination. This is a conceptual operation which also builds hierarchical structure. We can conceive of a garden that consists of a lawn and a flower-bed, for example, or a salad consisting of lettuce, fennel and rocket, or a crew consisting of a pilot and engineer. In such cases, concepts are put together in a way that makes one the accommodating element with respect to the others taken in combination. The accommodating element becomes the root of a hierarchical unit. Since this unit is itself a concept, the operation is inherently recursive. Does this mean the mind has two independent systems of hierarchical construction? Or is some form of integration more likely? Following a detailed examination of the operations involved, this paper shows there are three main ways in which Merge might be linked to hierarchical concept-combination. Also examined are the architectural implications that arise in each case.

  20. Multi-level Control Framework for Enhanced Flexibility of Active Distribution Network

    DEFF Research Database (Denmark)

    Nainar, Karthikeyan; Pokhrel, Basanta Raj; Pillai, Jayakrishnan Radhakrishna

    2017-01-01

    the selected control objectives and provides enhanced flexibility. The control architecture is supported by generation/load forecasting and distribution state estimation techniques to improve the controllability of the network. The multi-level control architecture consists of three levels of hierarchical...

  1. Interoperable Communications for Hierarchical Heterogeneous Wireless Networks

    Science.gov (United States)

    2016-04-01

    signatures of various wireless devices (cellular, WiFi , bluetooth, etc.) are captured using USRP2 and GNUradio platform, and the traces are available on a...action. The algorithm acquires the channel occupancy matrix from the SU channel sensing results and the actual channel occupancy determined by the PUs...true channel status Ma- trix, A (Dc). In the algorithm the values of the estimated matrix and the true channel status matrix are compared to determine

  2. Hierarchical porous microspheres of the Co3O4@graphene with enhanced electrocatalytic performance for electrochemical biosensors.

    Science.gov (United States)

    Yang, MinHo; Jeong, Jae-Min; Lee, Kyoung G; Kim, Do Hyun; Lee, Seok Jae; Choi, Bong Gill

    2017-03-15

    The integration of organic and inorganic building blocks into hierarchical porous architectures makes potentially desirable electrocatalytic materials in many electrochemical applications due to their combination of attractive qualities of dissimilar components and well-constructed charge transfer pathways. Herein, we demonstrate the preparation of the hierarchical porous Co3O4@graphene (Co3O4@G) microspheres by one-step hydrothermal method to achieve high electrocatalytic performance for enzyme-free biosensor applications. The obtained Co3O4@G microspheres are consisted of the interconnected networks of Co3O4 and graphene sheets, and thus provide large accessible active sites through porous structure, while graphene sheets offer continuous electron pathways for efficient electrocatalytic reaction of Co3O4. These structural merits with synergy effect of Co3O4 and graphene lead to a high performance of enzyme-free detection for glucose: high sensitivity, good selectivity, and remarkable stability.

  3. Classifying hospitals as mortality outliers: logistic versus hierarchical logistic models.

    Science.gov (United States)

    Alexandrescu, Roxana; Bottle, Alex; Jarman, Brian; Aylin, Paul

    2014-05-01

    The use of hierarchical logistic regression for provider profiling has been recommended due to the clustering of patients within hospitals, but has some associated difficulties. We assess changes in hospital outlier status based on standard logistic versus hierarchical logistic modelling of mortality. The study population consisted of all patients admitted to acute, non-specialist hospitals in England between 2007 and 2011 with a primary diagnosis of acute myocardial infarction, acute cerebrovascular disease or fracture of neck of femur or a primary procedure of coronary artery bypass graft or repair of abdominal aortic aneurysm. We compared standardised mortality ratios (SMRs) from non-hierarchical models with SMRs from hierarchical models, without and with shrinkage estimates of the predicted probabilities (Model 1 and Model 2). The SMRs from standard logistic and hierarchical models were highly statistically significantly correlated (r > 0.91, p = 0.01). More outliers were recorded in the standard logistic regression than hierarchical modelling only when using shrinkage estimates (Model 2): 21 hospitals (out of a cumulative number of 565 pairs of hospitals under study) changed from a low outlier and 8 hospitals changed from a high outlier based on the logistic regression to a not-an-outlier based on shrinkage estimates. Both standard logistic and hierarchical modelling have identified nearly the same hospitals as mortality outliers. The choice of methodological approach should, however, also consider whether the modelling aim is judgment or improvement, as shrinkage may be more appropriate for the former than the latter.

  4. Hierarchical security situational element acquisition mechanism in wireless sensor networks%无线传感器网络中层次化安全态势要素获取机制

    Institute of Scientific and Technical Information of China (English)

    李方伟; 汪岩; 朱江; 张海波

    2016-01-01

    In wireless sensor network ,the processing ability of the sensor nodes is poor .And the security situational element acquisition is also a serious problem .Thus ,a hierarchical framework of security situational elements acquisition mechanism was proposed .In this framework ,support vector machine hyper sphere multi classification algorithm was introduced as basic classi‐fier .The non‐negative matrix factorization algorithm was used as the method of attribute reduction .The fuzzy classification algo‐rithm was used to initialize non‐negative matrix factorization ,to avoid the local optimal caused by random initialization of non‐negative matrix factorization .In the sink node ,classification rules and attribute reduction rules were formed by learning .The classification analyses respectively focused on the cluster head and sink node ,which reduced the requirement of the sensor node properties .Attribute reduction was carried out before the data transmission ,reducing communication consumption of data trans‐mission and improving the performance of classifiers .Simulation results show ,the scheme has preferable accuracy on the situa‐tional elements acquisition ,and smaller communication overhead in the process of information transmission .%针对无线传感器网络中感知节点处理能力较差,获取网络安全态势要素困难的问题,提出一种层次化架构态势要素获取机制。在该架构中,采用支持向量机超球体多分类算法作为基分类器,非负矩阵分解算法作为属性约简的方法,采用模糊分类算法初始化该算法,解决随机初始化导致局部最优的缺陷。在汇聚节点完成对分类规则和属性约简规则的学习,分别在簇头和汇聚节点做分类分析,降低对感知节点性能要求。数据传输前进行属性约简,减小数据传输时的通信开销,提高分类器分类性能。仿真结果表明,该方案有较好的态势要素获取准确度和

  5. An Image Local Feature Representation Method Using Hierarchical Vision Network Model%利用多层视觉网络模型进行图像局部特征表征的方法

    Institute of Scientific and Technical Information of China (English)

    郎波; 黄静; 危辉

    2015-01-01

    为了寻求代价更小、效率更高、适应性更强的图像局部特征表征方法,提出一种基于视觉机制的多层网络计算模型。首先对初级视皮层中的简单细胞和复杂细胞等神经元进行建模;然后对腹侧视通路上的V4区神经元和下颞叶皮层区神经元的响应模式进行研究,并利用该计算模型对输入图像进行局部特征的表征。实验结果表明,与传统的图像特征描述方法相比,该模型所提取的图像局部特征具有足够的区分度;此外,利用生物视觉模型提取出的图像局部特征在具有复杂背景的场景中显示出了更加优秀的泛化能力。%For representing local image features, minor price, more efficient and more flexible, a hierarchical network model based on human vision physiological mechanism was put forward. Firstly, simple cell and com-plex cell in primary visual cortex are modeled, then studied the response pattern of V4 area and inferior temporal cortex on ventral side channel and representing the local features of input image utilized the computational model. The experiment results show that local image features extracted by computational model have sufficient dis-crimination; furthermore, the local image features extracted using biological visual model demonstrated much more excellent generalization ability in natural scene with complicated background.

  6. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.

    Science.gov (United States)

    Kim, Junghoe; Calhoun, Vince D; Shim, Eunsoo; Lee, Jong-Hwan

    2016-01-01

    Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was

  7. Hierarchical partial order ranking.

    Science.gov (United States)

    Carlsen, Lars

    2008-09-01

    Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritization of polluted sites is given.

  8. Trees and Hierarchical Structures

    CERN Document Server

    Haeseler, Arndt

    1990-01-01

    The "raison d'etre" of hierarchical dustering theory stems from one basic phe­ nomenon: This is the notorious non-transitivity of similarity relations. In spite of the fact that very often two objects may be quite similar to a third without being that similar to each other, one still wants to dassify objects according to their similarity. This should be achieved by grouping them into a hierarchy of non-overlapping dusters such that any two objects in ~ne duster appear to be more related to each other than they are to objects outside this duster. In everyday life, as well as in essentially every field of scientific investigation, there is an urge to reduce complexity by recognizing and establishing reasonable das­ sification schemes. Unfortunately, this is counterbalanced by the experience of seemingly unavoidable deadlocks caused by the existence of sequences of objects, each comparatively similar to the next, but the last rather different from the first.

  9. Optimisation by hierarchical search

    Science.gov (United States)

    Zintchenko, Ilia; Hastings, Matthew; Troyer, Matthias

    2015-03-01

    Finding optimal values for a set of variables relative to a cost function gives rise to some of the hardest problems in physics, computer science and applied mathematics. Although often very simple in their formulation, these problems have a complex cost function landscape which prevents currently known algorithms from efficiently finding the global optimum. Countless techniques have been proposed to partially circumvent this problem, but an efficient method is yet to be found. We present a heuristic, general purpose approach to potentially improve the performance of conventional algorithms or special purpose hardware devices by optimising groups of variables in a hierarchical way. We apply this approach to problems in combinatorial optimisation, machine learning and other fields.

  10. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L.; Bod, Rens; Christiansen, Morten H.

    2012-01-01

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science. PMID:22977157

  11. How hierarchical is language use?

    Science.gov (United States)

    Frank, Stefan L; Bod, Rens; Christiansen, Morten H

    2012-11-22

    It is generally assumed that hierarchical phrase structure plays a central role in human language. However, considerations of simplicity and evolutionary continuity suggest that hierarchical structure should not be invoked too hastily. Indeed, recent neurophysiological, behavioural and computational studies show that sequential sentence structure has considerable explanatory power and that hierarchical processing is often not involved. In this paper, we review evidence from the recent literature supporting the hypothesis that sequential structure may be fundamental to the comprehension, production and acquisition of human language. Moreover, we provide a preliminary sketch outlining a non-hierarchical model of language use and discuss its implications and testable predictions. If linguistic phenomena can be explained by sequential rather than hierarchical structure, this will have considerable impact in a wide range of fields, such as linguistics, ethology, cognitive neuroscience, psychology and computer science.

  12. Hierarchical self-organization of non-cooperating individuals

    CERN Document Server

    Nepusz, Tamás

    2013-01-01

    Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introduce an approach which is capable of reproducing the emergence of a multi-levelled network structure based on the plausible assumption that the individuals (representing the nodes of the network) can make the right estimate about the state of their changing environment to a varying degree. Our model accounts for a fundamental feature of knowledge-based organizations: the less capable individuals tend to follow those who are better at solving the problems they all face. We find that relatively simple rules lead to hierarchic...

  13. Associative Hierarchical Random Fields.

    Science.gov (United States)

    Ladický, L'ubor; Russell, Chris; Kohli, Pushmeet; Torr, Philip H S

    2014-06-01

    This paper makes two contributions: the first is the proposal of a new model-The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation. Most methods for semantic segmentation are formulated as a labeling problem for variables that might correspond to either pixels or segments such as super-pixels. It is well known that the generation of super pixel segmentations is not unique. This has motivated many researchers to use multiple super pixel segmentations for problems such as semantic segmentation or single view reconstruction. These super-pixels have not yet been combined in a principled manner, this is a difficult problem, as they may overlap, or be nested in such a way that the segmentations form a segmentation tree. Our new hierarchical random field model allows information from all of the multiple segmentations to contribute to a global energy. MAP inference in this model can be performed efficiently using powerful graph cut based move making algorithms. Our framework generalizes much of the previous work based on pixels or segments, and the resulting labelings can be viewed both as a detailed segmentation at the pixel level, or at the other extreme, as a segment selector that pieces together a solution like a jigsaw, selecting the best segments from different segmentations as pieces. We evaluate its performance on some of the most challenging data sets for object class segmentation, and show that this ability to perform inference using multiple overlapping segmentations leads to state-of-the-art results.

  14. Chip Multithreaded Consistency Model

    Institute of Scientific and Technical Information of China (English)

    Zu-Song Li; Dan-Dan Huan; Wei-Wu Hu; Zhi-Min Tang

    2008-01-01

    Multithreaded technique is the developing trend of high performance processor. Memory consistency model is essential to the correctness, performance and complexity of multithreaded processor. The chip multithreaded consistency model adapting to multithreaded processor is proposed in this paper. The restriction imposed on memory event ordering by chip multithreaded consistency is presented and formalized. With the idea of critical cycle built by Wei-Wu Hu, we prove that the proposed chip multithreaded consistency model satisfies the criterion of correct execution of sequential consistency model. Chip multithreaded consistency model provides a way of achieving high performance compared with sequential consistency model and ensures the compatibility of software that the execution result in multithreaded processor is the same as the execution result in uniprocessor. The implementation strategy of chip multithreaded consistency model in Godson-2 SMT processor is also proposed. Godson-2 SMT processor supports chip multithreaded consistency model correctly by exception scheme based on the sequential memory access queue of each thread.

  15. Hierarchical Model Predictive Control for Plug-and-Play Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2012-01-01

    This chapter deals with hierarchical model predictive control (MPC) of distributed systems. A three level hierarchical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonom......This chapter deals with hierarchical model predictive control (MPC) of distributed systems. A three level hierarchical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level...

  16. Hierarchical Neural Regression Models for Customer Churn Prediction

    Directory of Open Access Journals (Sweden)

    Golshan Mohammadi

    2013-01-01

    Full Text Available As customers are the main assets of each industry, customer churn prediction is becoming a major task for companies to remain in competition with competitors. In the literature, the better applicability and efficiency of hierarchical data mining techniques has been reported. This paper considers three hierarchical models by combining four different data mining techniques for churn prediction, which are backpropagation artificial neural networks (ANN, self-organizing maps (SOM, alpha-cut fuzzy c-means (α-FCM, and Cox proportional hazards regression model. The hierarchical models are ANN + ANN + Cox, SOM + ANN + Cox, and α-FCM + ANN + Cox. In particular, the first component of the models aims to cluster data in two churner and nonchurner groups and also filter out unrepresentative data or outliers. Then, the clustered data as the outputs are used to assign customers to churner and nonchurner groups by the second technique. Finally, the correctly classified data are used to create Cox proportional hazards model. To evaluate the performance of the hierarchical models, an Iranian mobile dataset is considered. The experimental results show that the hierarchical models outperform the single Cox regression baseline model in terms of prediction accuracy, Types I and II errors, RMSE, and MAD metrics. In addition, the α-FCM + ANN + Cox model significantly performs better than the two other hierarchical models.

  17. Hierarchical self-organization of non-cooperating individuals

    OpenAIRE

    Tamás Nepusz; Tamás Vicsek

    2013-01-01

    Hierarchy is one of the most conspicuous features of numerous natural, technological and social systems. The underlying structures are typically complex and their most relevant organizational principle is the ordering of the ties among the units they are made of according to a network displaying hierarchical features. In spite of the abundant presence of hierarchy no quantitative theoretical interpretation of the origins of a multi-level, knowledge-based social network exists. Here we introdu...

  18. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    CERN Document Server

    Jelonek, M

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of modeling hierarchical linear equations and estimation based on MPlus software. I present my own model to illustrate the impact of different factors on school acceptation level.

  19. 基于全网统筹的联络线分层优化调度%Optimization of Tie-line Hierarchical Schedule Based on Network-wide Coordination

    Institute of Scientific and Technical Information of China (English)

    许丹; 李晓磊; 丁强; 崔晖; 韩彬

    2014-01-01

    The traditional tie-line schedule is entirely based on the electricity transaction,hence it is loosely coupled with power grid operation all along and relatively independent from the generation scheduling.These cause difficulties in adj usting tie-line schedule and lack of capacity in global allocation of resources.In face of these problems,a hierarchical tie-line schedule model based on network-wide coordination is proposed by resorting to the existing tie-line planning.The upper model gets the ideal tie-line schedule through the economical dispatch constrained by the whole network security.The lower model uses the ideal tie-line schedule as the optimization obj ective,and takes electricity transactions as constraints to achieve the tie-line schedule. This model has achieved automatic preparation and flexible adj ustment of tie-line scheduling,while providing an available manner that combines the schedule with the grid operating state.The proposed algorithm is applied to the tie-line schedule of Central China power grid,while the comparison between the proposed method and the traditional method showing the correctness and effectiveness of the proposed algorithm.%传统联络线计划完全基于电力交易,与电网运行长期处于松耦合状态且与机组计划相对独立,存在联络线计划调整困难,资源全局配置能力不足等问题。针对上述问题,文中以现有联络线计划编制方式为基础,提出了基于全网统筹的联络线分层优化模型。上层模型通过全网安全约束经济调度求取理想联络线计划。下层模型以理想联络线计划为优化目标,以交易合同实际执行为相关约束求解联络线计划。该模型实现了联络线计划自动编制与灵活调整,提供了一种将联络线计划与电网运行状态相结合的可用方式。将所提模型运用于华中电网联络线计划编制,并对优化结果与传统计划进行对比分析,验证了所提方法的正确性与有效性。

  20. Hierarchical Power Flow Control Strategy and Algorithm for Multi-terminal Interconnected AC/DC Distribution Network%多端互联交直流配电网的潮流分层控制策略及算法

    Institute of Scientific and Technical Information of China (English)

    彭克; 咸日常; 张新慧; 陈羽; 陆海

    2016-01-01

    随着直流配电系统的提出与发展,传统配电网的网架结构与运行方式正在逐渐改变,未来会形成交直流混联的配电网新型供电模式,交直流之间的电气量耦合给潮流的有序控制以及混联求解都带来了新的挑战。为此,提出了多端互联的交直流配电网分层潮流控制策略,实现交直流电压的有序控制。第一层控制由交直流互联的换流器实现,采用下垂控制均摊直流配电网内的负荷,并根据下垂曲线对直流母线电压进行控制。第二层控制由具有调压功能的分布式电源实现,维持就地电压平衡。第三层控制由电压调节器实现,进行区域电压调整。针对交直流配电网的特点,提出了高斯—牛顿交直流混合潮流算法,提高了算法的收敛性能。最后,在改进的 IEEE 123节点系统上进行了测试,验证了所述控制策略及算法的有效性与正确性。%With the development of DC distribution system , the network structure and operation mode of traditional distribution system have greatly changed . The AC/DC hybrid distribution network will be dominant in the future and poses a new challenge to power flow control and the AC/DC hybrid algorithm . For this reason , a hierarchical power flow control strategy is proposed to carry out orderly voltage control . At the first layer , DC load sharing is realized by the bidirectional converter with droop control , and DC bus voltage is controlled according to the droop control curve , at the second layer , local voltage balance is regulated by the distributed generator , while at the third , regional voltage is controlled by the voltage regulator . Secondly , the Gauss‐Newton hybrid algorithm is proposed according to the characteristics of the AC/DC hybrid distribution system to improve the convergence performance of the algorithm . Finally , the test results on a modified IEEE 123‐bus system show the validity and

  1. Cognitive Memory Network

    CERN Document Server

    James, Alex Pappachen; 10.1049/el.2010.0279

    2012-01-01

    A resistive memory network that has no crossover wiring is proposed to overcome the hardware limitations to size and functional complexity that is associated with conventional analogue neural networks. The proposed memory network is based on simple network cells that are arranged in a hierarchical modular architecture. Cognitive functionality of this network is demonstrated by an example of character recognition. The network is trained by an evolutionary process to completely recognise characters deformed by random noise, rotation, scaling and shifting

  2. On the geostatistical characterization of hierarchical media

    Science.gov (United States)

    Neuman, Shlomo P.; Riva, Monica; Guadagnini, Alberto

    2008-02-01

    The subsurface consists of porous and fractured materials exhibiting a hierarchical geologic structure, which gives rise to systematic and random spatial and directional variations in hydraulic and transport properties on a multiplicity of scales. Traditional geostatistical moment analysis allows one to infer the spatial covariance structure of such hierarchical, multiscale geologic materials on the basis of numerous measurements on a given support scale across a domain or "window" of a given length scale. The resultant sample variogram often appears to fit a stationary variogram model with constant variance (sill) and integral (spatial correlation) scale. In fact, some authors, who recognize that hierarchical sedimentary architecture and associated log hydraulic conductivity fields tend to be nonstationary, nevertheless associate them with stationary "exponential-like" transition probabilities and variograms, respectively, the latter being a consequence of the former. We propose that (1) the apparent ability of stationary spatial statistics to characterize the covariance structure of nonstationary hierarchical media is an artifact stemming from the finite size of the windows within which geologic and hydrologic variables are ubiquitously sampled, and (2) the artifact is eliminated upon characterizing the covariance structure of such media with the aid of truncated power variograms, which represent stationary random fields obtained upon sampling a nonstationary fractal over finite windows. To support our opinion, we note that truncated power variograms arise formally when a hierarchical medium is sampled jointly across all geologic categories and scales within a window; cite direct evidence that geostatistical parameters (variance and integral scale) inferred on the basis of traditional variograms vary systematically with support and window scales; demonstrate the ability of truncated power models to capture these variations in terms of a few scaling parameters

  3. 一种新型无线网络自适应分层覆盖系统研究%Research on an adaptive hierarchical coverage scheme of wireless networks

    Institute of Scientific and Technical Information of China (English)

    赵兆

    2011-01-01

    First, a utility function was proposed to evaluate the performance of hierarchical cellular system. Both the blocking probability and handover times were considered in the function. Second, an adaptive hierarchical cellular system was proposed which allows the mobile equipments in macrocells to communicate with any base station in the system. Simulation results indicate that the adaptive hierarchical cellular system performances better than hierarchical cellular system in blocking probability, handover times and utility function.%首先提出一种衡量分层覆盖系统性能的效用函数,该效用函数综合考虑了阻塞率和切换次数;然后,提出了一种自适应分层覆盖系统,该系统允许接入宏蜂窝的移动台可以与任何基站通信.仿真结果表明:在阻塞率、切换次数、效用函数等方面自适应分层覆盖系统优于传统分层覆盖系统.

  4. Modeling hierarchical structures - Hierarchical Linear Modeling using MPlus

    OpenAIRE

    Jelonek, Magdalena

    2006-01-01

    The aim of this paper is to present the technique (and its linkage with physics) of overcoming problems connected to modeling social structures, which are typically hierarchical. Hierarchical Linear Models provide a conceptual and statistical mechanism for drawing conclusions regarding the influence of phenomena at different levels of analysis. In the social sciences it is used to analyze many problems such as educational, organizational or market dilemma. This paper introduces the logic of m...

  5. Urban pattern: Layout design by hierarchical domain splitting

    KAUST Repository

    Yang, Yongliang

    2013-11-01

    We present a framework for generating street networks and parcel layouts. Our goal is the generation of high-quality layouts that can be used for urban planning and virtual environments. We propose a solution based on hierarchical domain splitting using two splitting types: streamline-based splitting, which splits a region along one or multiple streamlines of a cross field, and template-based splitting, which warps pre-designed templates to a region and uses the interior geometry of the template as the splitting lines. We combine these two splitting approaches into a hierarchical framework, providing automatic and interactive tools to explore the design space.

  6. Hierarchical fringe tracking

    CERN Document Server

    Petrov, Romain G; Boskri, Abdelkarim; Folcher, Jean-Pierre; Lagarde, Stephane; Bresson, Yves; Benkhaldoum, Zouhair; Lazrek, Mohamed; Rakshit, Suvendu

    2014-01-01

    The limiting magnitude is a key issue for optical interferometry. Pairwise fringe trackers based on the integrated optics concepts used for example in GRAVITY seem limited to about K=10.5 with the 8m Unit Telescopes of the VLTI, and there is a general "common sense" statement that the efficiency of fringe tracking, and hence the sensitivity of optical interferometry, must decrease as the number of apertures increases, at least in the near infrared where we are still limited by detector readout noise. Here we present a Hierarchical Fringe Tracking (HFT) concept with sensitivity at least equal to this of a two apertures fringe trackers. HFT is based of the combination of the apertures in pairs, then in pairs of pairs then in pairs of groups. The key HFT module is a device that behaves like a spatial filter for two telescopes (2TSF) and transmits all or most of the flux of a cophased pair in a single mode beam. We give an example of such an achromatic 2TSF, based on very broadband dispersed fringes analyzed by g...

  7. Hierarchical Reverberation Mapping

    CERN Document Server

    Brewer, Brendon J

    2013-01-01

    Reverberation mapping (RM) is an important technique in studies of active galactic nuclei (AGN). The key idea of RM is to measure the time lag $\\tau$ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of $\\tau$ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass $M_{\\rm BH}$. A major difficulty with RM campaigns is the large amount of data needed to measure $\\tau$. Recently, Fine et al (2012) introduced a new approach to RM where the BLR light curve is sparsely sampled, but this is counteracted by observing a large sample of AGN, rather than a single system. The results are combined to infer properties of the sample of AGN. In this letter we implement this method using a hierarchical Bayesian model and contrast this with the results from the previous stacked cross-correlation technique. We find that our inferences are more precise and allow fo...

  8. Dynamics and thermodynamics in hierarchically organized systems applications in physics, biology and economics

    CERN Document Server

    Auger, P

    2013-01-01

    One of the most fundamental and efficient ways of conceptualizing complex systems is to organize them hierarchically. A hierarchically organized system is represented by a network of interconnected subsystems, each of which has its own network of subsystems, and so on, until some elementary subsystems are reached that are not further decomposed. This original and important book proposes a general mathematical theory of a hierarchical system and shows how it can be applied to very different topics such as physics (Hamiltonian systems), biology (coupling the molecular and the cellular levels), e

  9. Consistent model driven architecture

    Science.gov (United States)

    Niepostyn, Stanisław J.

    2015-09-01

    The goal of the MDA is to produce software systems from abstract models in a way where human interaction is restricted to a minimum. These abstract models are based on the UML language. However, the semantics of UML models is defined in a natural language. Subsequently the verification of consistency of these diagrams is needed in order to identify errors in requirements at the early stage of the development process. The verification of consistency is difficult due to a semi-formal nature of UML diagrams. We propose automatic verification of consistency of the series of UML diagrams originating from abstract models implemented with our consistency rules. This Consistent Model Driven Architecture approach enables us to generate automatically complete workflow applications from consistent and complete models developed from abstract models (e.g. Business Context Diagram). Therefore, our method can be used to check practicability (feasibility) of software architecture models.

  10. Decentralized Consistent Updates in SDN

    KAUST Repository

    Nguyen, Thanh Dang

    2017-04-10

    We present ez-Segway, a decentralized mechanism to consistently and quickly update the network state while preventing forwarding anomalies (loops and blackholes) and avoiding link congestion. In our design, the centralized SDN controller only pre-computes information needed by the switches during the update execution. This information is distributed to the switches, which use partial knowledge and direct message passing to efficiently realize the update. This separation of concerns has the key benefit of improving update performance as the communication and computation bottlenecks at the controller are removed. Our evaluations via network emulations and large-scale simulations demonstrate the efficiency of ez-Segway, which compared to a centralized approach, improves network update times by up to 45% and 57% at the median and the 99th percentile, respectively. A deployment of a system prototype in a real OpenFlow switch and an implementation in P4 demonstrate the feasibility and low overhead of implementing simple network update functionality within switches.

  11. A new global river network database for macroscale hydrologic modeling

    Science.gov (United States)

    Wu, Huan; Kimball, John S.; Li, Hongyi; Huang, Maoyi; Leung, L. Ruby; Adler, Robert F.

    2012-09-01

    Coarse-resolution (upscaled) river networks are critical inputs for runoff routing in macroscale hydrologic models. Recently, Wu et al. (2011) developed a hierarchical dominant river tracing (DRT) algorithm for automated extraction and spatial upscaling of river networks using fine-scale hydrography inputs. We applied the DRT algorithms using combined HydroSHEDS and HYDRO1k global fine-scale hydrography inputs and produced a new series of upscaled global river network data at multiple (1/16° to 2°) spatial resolutions. The new upscaled results are internally consistent and congruent with the baseline fine-scale inputs and should facilitate improved regional to global scale hydrologic simulations.

  12. Hierarchical materials: Background and perspectives

    DEFF Research Database (Denmark)

    2016-01-01

    Hierarchical design draws inspiration from analysis of biological materials and has opened new possibilities for enhancing performance and enabling new functionalities and extraordinary properties. With the development of nanotechnology, the necessary technological requirements for the manufactur...

  13. Hierarchical clustering for graph visualization

    CERN Document Server

    Clémençon, Stéphan; Rossi, Fabrice; Tran, Viet Chi

    2012-01-01

    This paper describes a graph visualization methodology based on hierarchical maximal modularity clustering, with interactive and significant coarsening and refining possibilities. An application of this method to HIV epidemic analysis in Cuba is outlined.

  14. Direct hierarchical assembly of nanoparticles

    Science.gov (United States)

    Xu, Ting; Zhao, Yue; Thorkelsson, Kari

    2014-07-22

    The present invention provides hierarchical assemblies of a block copolymer, a bifunctional linking compound and a nanoparticle. The block copolymers form one micro-domain and the nanoparticles another micro-domain.

  15. Hierarchical processing in the prefrontal cortex in a variety of cognitive domains

    Directory of Open Access Journals (Sweden)

    Hyeon-Ae eJeon

    2014-11-01

    Full Text Available This review scrutinizes several findings on human hierarchical processing within the prefrontal cortex (PFC in diverse cognitive domains. Converging evidence from previous studies has shown that the PFC, specifically Brodmann area (BA 44, may function as the essential region for hierarchical processing across the domains. In language fMRI studies, BA 44 was significantly activated for the hierarchical processing of center-embedded sentences and this pattern of activations was also observed in artificial grammar. The same pattern was observed in the visuo-spatial domain where BA44 was actively involved in the processing of hierarchy for the visual symbol. Musical syntax, which is the rule-based arrangement of musical sets, has also been construed as hierarchical processing as in the language domain such that the activation in BA44 was observed in a chord sequence paradigm. P600 ERP was also engendered during the processing of musical hierarchy. Along with a longstanding idea that a human’s number faculty is developed as a by-product of language faculty, BA44 was closely involved in hierarchical processing in mental arithmetic. This review extended its discussion of hierarchical processing to hierarchical behavior, that is, human action which has been referred to as being hierarchically composed. Several lesion and TMS studies supported the involvement of BA44 for hierarchical processing in the action domain. Lastly, the hierarchical organization of cognitive controls was discussed within the PFC, forming a cascade of top-down hierarchical processes operating along a posterior-to-anterior axis of the lateral PFC including BA44 within the network. It is proposed that PFC is actively involved in different forms of hierarchical processing and specifically BA44 may play an integral role in the process. Taking levels of proficiency and subcortical areas into consideration may provide further insight into the functional role of BA44 for hierarchical

  16. Hierarchical Dragonfly Wing: Microstructure-Biomechanical Behavior Relations

    Institute of Scientific and Technical Information of China (English)

    Yinglong Chen; Xishu Wang; Huaihui Ren; Hang Yin; Su Jia

    2012-01-01

    The dragonfly wing,which consists of veins and membrane,is of biological hierarchical material.We observed the cross-sections of longitudinal veins and membrane using Environmental Scanning Electron Microscopy (ESEM).Based on the experiments and previous studies,we described the longitudinal vein and the membrane in terms of two hierarchical levels of organization of composite materials at the micro- and nano-scales.The longitudinal vein of dragonfly wing has a complex sandwich structure with two chitinous shells and a protein layer,and it is considered as the first hierarchical level of the vein.Moreover,the chitinous shells are concentric multilayered structures.Clusters of nano-fibrils grow along the circumferential orientation embedded into the protein layer.It is considered as the second level of the hierarchy.Similarly,the upper and lower epidermises of membrane constitute the first hierarchical level of organization in micro scale.Similar to the vein shell,the membrane epidermises were found to be a paralleled multilayered structure,defined as the second hierarchical level of the membrane.Combining with the mechanical behavior analysis of the dragonfly wing,we concluded that the growth orientation of the hierarchical structure of the longitudinal vein and membrane is relevant to its biomechanical behavior.

  17. No consistent bimetric gravity?

    CERN Document Server

    Deser, S; Waldron, A

    2013-01-01

    We discuss the prospects for a consistent, nonlinear, partially massless (PM), gauge symmetry of bimetric gravity (BMG). Just as for single metric massive gravity, ultimate consistency of both BMG and the putative PM BMG theory relies crucially on this gauge symmetry. We argue, however, that it does not exist.

  18. Networks in financial markets based on the mutual information rate.

    Science.gov (United States)

    Fiedor, Paweł

    2014-05-01

    In the last few years there have been many efforts in econophysics studying how network theory can facilitate understanding of complex financial markets. These efforts consist mainly of the study of correlation-based hierarchical networks. This is somewhat surprising as the underlying assumptions of research looking at financial markets are that they are complex systems and thus behave in a nonlinear manner, which is confirmed by numerous studies, making the use of correlations which are inherently dealing with linear dependencies only baffling. In this paper we introduce a way to incorporate nonlinear dynamics and dependencies into hierarchical networks to study financial markets using mutual information and its dynamical extension: the mutual information rate. We show that this approach leads to different results than the correlation-based approach used in most studies, on the basis of 91 companies listed on the New York Stock Exchange 100 between 2003 and 2013, using minimal spanning trees and planar maximally filtered graphs.

  19. Dynamic load balancing based on restricted multicast tree in triplet-based hierarchical interconnection network%基三分层互连网络中基于受限多播树的动态负载平衡

    Institute of Scientific and Technical Information of China (English)

    刘滨; 石峰; 高玉金; 计卫星; 宋红

    2008-01-01

    To solve the load balancing problem in a triplet-based hierarchical interconnection network(THIN)system,a dynamic load balancing(DLB)algorithm-THINDLBA,which adopts multicast tree(MT)technology to improve the efficiency of interchanging load information,is presented.To support the algorithm,a complete set of DLB messages and a schema of maintaining DLB information in each processing node are designed.The load migration request messages from the heavily loaded node(HLN)are spread along an MT whose root is the HLN.And the lightly loaded nodes(LLNs) covered by the MT are the candidate destinations of load migration; the load information interchanged between the LLNs and the HLN can be transmitted along the MT.So the HLN can migrate excess loads out as many as possible during a one time execution of the THINDLBA,and its load state can be improved as quickly as possible.To avoid wrongly transmitted or redundant DLB messages due to MT overlapping,the MT construction is restricted in the design of the THINDLBA.Through experiments,the effectiveness of four DLB algorithms are compared,and the results show that the THINDLBA can effectively decrease the time costs of THIN systems in dealing with large scale compute-intensive tasks more than others.%为了解决基三分层互连网络(THIN)系统中的负载平衡问题,提出一种采用多播树技术提高节点间交换负载信息效率的动态负载平衡(DLB)算法--THINDLBA.设计了一套完整的DLB消息和各节点处的信息维护机制以辅助算法实现.重载节点的负载迁移请求消息沿着一棵以该节点为根的多播树传播,被该树覆盖的轻载节点均成为负载迁移的候选目标节点,可以沿着该树和重载节点交互负载信息,从而使重载节点能够在算法的一次执行中外迁最多的过载进程,尽快改善自身负载状态.算法设计中约束了多播树的构造过程,以避免因树间覆盖造成的消息误传或冗余.通过实验对比了4

  20. Electronic Properties in a Hierarchical Multilayer Structure

    Institute of Scientific and Technical Information of China (English)

    ZHU Chen-Ping; XIONG Shi-Jie

    2001-01-01

    We investigate electronic properties of a hierarchical multilayer structure consisting of stacking of barriers and wells. The structure is formed in a sequence of generations, each of which is constructed with the same pattern but with the previous generation as the basic building blocks. We calculate the transmission spectrum which shows the multifractal behavior for systems with large generation index. From the analysis of the average resistivity and the multifractal structure of the wavefunctions, we show that there exist different types of states exhibiting extended, localized and intermediate characteristics. The degree of localization is sensitive to the variation of the structural parameters.Suggestion of the possible experimental realization is discussed.