A Hierarchical Dispatch Structure for Distribution Network Pricing

OpenAIRE

Yuan, Zhao; Hesamzadeh, Mohammad Reza

2015-01-01

This paper presents a hierarchical dispatch structure for efficient distribution network pricing. The dispatch coordination problem in the context of hierarchical network operators are addressed. We formulate decentralized generation dispatch into a bilevel optimization problem in which main network operator and the connected distribution network operator optimize their costs in two levels. By using Karush-Kuhn-Tucker conditions and Fortuny-Amat McCarl linearization, the bilevel optimization ...

Stability of glassy hierarchical networks

Science.gov (United States)

Zamani, M.; Camargo-Forero, L.; Vicsek, T.

2018-02-01

The structure of interactions in most animal and human societies can be best represented by complex hierarchical networks. In order to maintain close-to-optimal function both stability and adaptability are necessary. Here we investigate the stability of hierarchical networks that emerge from the simulations of an organization type with an efficiency function reminiscent of the Hamiltonian of spin glasses. Using this quantitative approach we find a number of expected (from everyday observations) and highly non-trivial results for the obtained locally optimal networks, including, for example: (i) stability increases with growing efficiency and level of hierarchy; (ii) the same perturbation results in a larger change for more efficient states; (iii) networks with a lower level of hierarchy become more efficient after perturbation; (iv) due to the huge number of possible optimal states only a small fraction of them exhibit resilience and, finally, (v) ‘attacks’ targeting the nodes selectively (regarding their position in the hierarchy) can result in paradoxical outcomes.

Modular networks with hierarchical organization

Indian Academy of Sciences (India)

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 ...

Loops in hierarchical channel networks

Science.gov (United States)

Katifori, Eleni; Magnasco, Marcelo

2012-02-01

Nature provides us with many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture. Although a number of methods have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated and natural graphs extracted from digitized images of dicotyledonous leaves and animal vasculature. We calculate various metrics on the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information from the metric topology (connectivity and edge weight) and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.

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. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

Science.gov (United States)

Nitta, Tohru

2017-10-01

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).

Hierarchical spatial organization of geographical networks

International Nuclear Information System (INIS)

Travencolo, Bruno A N; Costa, Luciano da F

2008-01-01

In this work, we propose a hierarchical extension of the polygonality index as the means to characterize geographical planar networks. By considering successive neighborhoods around each node, it is possible to obtain more complete information about the spatial order of the network at progressive spatial scales. The potential of the methodology is illustrated with respect to synthetic and real geographical networks

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.

Multiple simultaneous fault diagnosis via hierarchical and single artificial neural networks

International Nuclear Information System (INIS)

Eslamloueyan, R.; Shahrokhi, M.; Bozorgmehri, R.

2003-01-01

Process fault diagnosis involves interpreting the current status of the plant given sensor reading and process knowledge. There has been considerable work done in this area with a variety of approaches being proposed for process fault diagnosis. Neural networks have been used to solve process fault diagnosis problems in chemical process, as they are well suited for recognizing multi-dimensional nonlinear patterns. In this work, the use of Hierarchical Artificial Neural Networks in diagnosing the multi-faults of a chemical process are discussed and compared with that of Single Artificial Neural Networks. The lower efficiency of Hierarchical Artificial Neural Networks , in comparison to Single Artificial Neural Networks, in process fault diagnosis is elaborated and analyzed. Also, the concept of a multi-level selection switch is presented and developed to improve the performance of hierarchical artificial neural networks. Simulation results indicate that application of multi-level selection switch increase the performance of the hierarchical artificial neural networks considerably

Energy Efficient Hierarchical Clustering Approaches in Wireless Sensor Networks: A Survey

Directory of Open Access Journals (Sweden)

Bilal Jan

2017-01-01

Full Text Available Wireless sensor networks (WSN are one of the significant technologies due to their diverse applications such as health care monitoring, smart phones, military, disaster management, and other surveillance systems. Sensor nodes are usually deployed in large number that work independently in unattended harsh environments. Due to constraint resources, typically the scarce battery power, these wireless nodes are grouped into clusters for energy efficient communication. In clustering hierarchical schemes have achieved great interest for minimizing energy consumption. Hierarchical schemes are generally categorized as cluster-based and grid-based approaches. In cluster-based approaches, nodes are grouped into clusters, where a resourceful sensor node is nominated as a cluster head (CH while in grid-based approach the network is divided into confined virtual grids usually performed by the base station. This paper highlights and discusses the design challenges for cluster-based schemes, the important cluster formation parameters, and classification of hierarchical clustering protocols. Moreover, existing cluster-based and grid-based techniques are evaluated by considering certain parameters to help users in selecting appropriate technique. Furthermore, a detailed summary of these protocols is presented with their advantages, disadvantages, and applicability in particular cases.

Towards Business Process Management in networked ecosystems

NARCIS (Netherlands)

Johan Versendaal; dr. Martijn Zoet; Jeroen Grondelle

2014-01-01

Managing and supporting the collaboration between different actors is key in any organizational context, whether of a hierarchical or a networked nature. In the networked context of ecosystems of service providers and other stakeholders, BPM is faced with different challenges than in a conventional

Detecting the overlapping and hierarchical community structure in complex networks

International Nuclear Information System (INIS)

Lancichinetti, Andrea; Fortunato, Santo; Kertesz, Janos

2009-01-01

Many networks in nature, society and technology are characterized by a mesoscopic level of organization, with groups of nodes forming tightly connected units, called communities or modules, that are only weakly linked to each other. Uncovering this community structure is one of the most important problems in the field of complex networks. Networks often show a hierarchical organization, with communities embedded within other communities; moreover, nodes can be shared between different communities. Here, we present the first algorithm that finds both overlapping communities and the hierarchical structure. The method is based on the local optimization of a fitness function. Community structure is revealed by peaks in the fitness histogram. The resolution can be tuned by a parameter enabling different hierarchical levels of organization to be investigated. Tests on real and artificial networks give excellent results.

Traffic Management for Next Generation Transport Networks

DEFF Research Database (Denmark)

Yu, Hao

required by the next generation transport network to provide Quality-of-Service (QoS) guaranteed video services. Augmenting network capacity and upgrading network nodes indicate long deployment period, replacement of equipment and thus significant cost to the network service providers. This challenge may...... slacken the steps of some network operators towards providing IPTV services. In this dissertation, the topology-based hierarchical scheduling scheme is proposed to tackle the problem addressed. The scheme simplifies the deployment process by placing an intelligent switch with centralized traffic...... management functions at the edge of the network, scheduling traffic on behalf of the other nodes. The topology-based hierarchical scheduling scheme is able to provide outstanding flow isolation due to its centralized scheduling ability, which is essential for providing IPTV services. In order to reduce...

Hierarchical organization of brain functional networks during visual tasks.

Science.gov (United States)

Zhuo, Zhao; Cai, Shi-Min; Fu, Zhong-Qian; Zhang, Jie

2011-09-01

The functional network of the brain is known to demonstrate modular structure over different hierarchical scales. In this paper, we systematically investigated the hierarchical modular organizations of the brain functional networks that are derived from the extent of phase synchronization among high-resolution EEG time series during a visual task. In particular, we compare the modular structure of the functional network from EEG channels with that of the anatomical parcellation of the brain cortex. Our results show that the modular architectures of brain functional networks correspond well to those from the anatomical structures over different levels of hierarchy. Most importantly, we find that the consistency between the modular structures of the functional network and the anatomical network becomes more pronounced in terms of vision, sensory, vision-temporal, motor cortices during the visual task, which implies that the strong modularity in these areas forms the functional basis for the visual task. The structure-function relationship further reveals that the phase synchronization of EEG time series in the same anatomical group is much stronger than that of EEG time series from different anatomical groups during the task and that the hierarchical organization of functional brain network may be a consequence of functional segmentation of the brain cortex.

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.

Hierarchical Network Design Using Simulated Annealing

DEFF Research Database (Denmark)

Thomadsen, Tommy; Clausen, Jens

2002-01-01

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....

A local adaptive algorithm for emerging scale-free hierarchical networks

International Nuclear Information System (INIS)

Gomez Portillo, I J; Gleiser, P M

2010-01-01

In this work we study a growing network model with chaotic dynamical units that evolves using a local adaptive rewiring algorithm. Using numerical simulations we show that the model allows for the emergence of hierarchical networks. First, we show that the networks that emerge with the algorithm present a wide degree distribution that can be fitted by a power law function, and thus are scale-free networks. Using the LaNet-vi visualization tool we present a graphical representation that reveals a central core formed only by hubs, and also show the presence of a preferential attachment mechanism. In order to present a quantitative analysis of the hierarchical structure we analyze the clustering coefficient. In particular, we show that as the network grows the clustering becomes independent of system size, and also presents a power law decay as a function of the degree. Finally, we compare our results with a similar version of the model that has continuous non-linear phase oscillators as dynamical units. The results show that local interactions play a fundamental role in the emergence of hierarchical networks.

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.

Chimera states in networks of logistic maps with hierarchical connectivities

Science.gov (United States)

zur Bonsen, Alexander; Omelchenko, Iryna; Zakharova, Anna; Schöll, Eckehard

2018-04-01

Chimera states are complex spatiotemporal patterns consisting of coexisting domains of coherence and incoherence. We study networks of nonlocally coupled logistic maps and analyze systematically how the dilution of the network links influences the appearance of chimera patterns. The network connectivities are constructed using an iterative Cantor algorithm to generate fractal (hierarchical) connectivities. Increasing the hierarchical level of iteration, we compare the resulting spatiotemporal patterns. We demonstrate that a high clustering coefficient and symmetry of the base pattern promotes chimera states, and asymmetric connectivities result in complex nested chimera patterns.

A new hierarchical method to find community structure in networks

Science.gov (United States)

Saoud, Bilal; Moussaoui, Abdelouahab

2018-04-01

Community structure is very important to understand a network which represents a context. Many community detection methods have been proposed like hierarchical methods. In our study, we propose a new hierarchical method for community detection in networks based on genetic algorithm. In this method we use genetic algorithm to split a network into two networks which maximize the modularity. Each new network represents a cluster (community). Then we repeat the splitting process until we get one node at each cluster. We use the modularity function to measure the strength of the community structure found by our method, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our method are highly effective at discovering community structure in both computer-generated and real-world network data.

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

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

Hierarchical regular small-world networks

International Nuclear Information System (INIS)

Boettcher, Stefan; Goncalves, Bruno; Guclu, Hasan

2008-01-01

Two new networks are introduced that resemble small-world properties. These networks are recursively constructed but retain a fixed, regular degree. They possess a unique one-dimensional lattice backbone overlaid by a hierarchical sequence of long-distance links, mixing real-space and small-world features. Both networks, one 3-regular and the other 4-regular, lead to distinct behaviors, as revealed by renormalization group studies. The 3-regular network is planar, has a diameter growing as √N with system size N, and leads to super-diffusion with an exact, anomalous exponent d w = 1.306..., but possesses only a trivial fixed point T c = 0 for the Ising ferromagnet. In turn, the 4-regular network is non-planar, has a diameter growing as ∼2 √(log 2 N 2 ) , exhibits 'ballistic' diffusion (d w = 1), and a non-trivial ferromagnetic transition, T c > 0. It suggests that the 3-regular network is still quite 'geometric', while the 4-regular network qualifies as a true small world with mean-field properties. As an engineering application we discuss synchronization of processors on these networks. (fast track communication)

A Multi-layer, Hierarchical Information Management System for the Smart Grid

Energy Technology Data Exchange (ETDEWEB)

Lu, Ning; Du, Pengwei; Paulson, Patrick R.; Greitzer, Frank L.; Guo, Xinxin; Hadley, Mark D.

2011-10-10

This paper presents the modeling approach, methodologies, and initial results of setting up a multi-layer, hierarchical information management system (IMS) for the smart grid. The IMS allows its users to analyze the data collected by multiple control and communication networks to characterize the states of the smart grid. Abnormal, corrupted, or erroneous measurement data and outliers are detected and analyzed to identify whether they are caused by random equipment failures, unintentional human errors, or deliberate tempering attempts. Data collected from different information networks are crosschecked for data integrity based on redundancy, dependency, correlation, or cross-correlations, which reveal the interdependency between data sets. A hierarchically structured reasoning mechanism is used to rank possible causes of an event to aid the system operators to proactively respond or provide mitigation recommendations to remove or neutralize the threats. The model provides satisfactory performance on identifying the cause of an event and significantly reduces the need of processing myriads of data collected.

Modular networks with hierarchical organization: The dynamical ...

Indian Academy of Sciences (India)

Most of the complex systems seen in real life also have associated dynamics [10], and the ... another example, this time a hierarchical structure, viz., the Cayley tree with b ..... natural constraints operating on networks in real life, such as the ...

Diagnostic Classifiers: Revealing how Neural Networks Process Hierarchical Structure

NARCIS (Netherlands)

Veldhoen, S.; Hupkes, D.; Zuidema, W.

2016-01-01

We investigate how neural networks can be used for hierarchical, compositional semantics. To this end, we define the simple but nontrivial artificial task of processing nested arithmetic expressions and study whether different types of neural networks can learn to add and subtract. We find that

Multiple dynamical time-scales in networks with hierarchically

Indian Academy of Sciences (India)

Modular networks; hierarchical organization; synchronization. ... we show that such a topological structure gives rise to characteristic time-scale separation ... This suggests a possible functional role of such mesoscopic organization principle in ...

Epidemics and dimensionality in hierarchical networks

Science.gov (United States)

Zheng, Da-Fang; Hui, P. M.; Trimper, Steffen; Zheng, Bo

2005-07-01

Epidemiological processes are studied within a recently proposed hierarchical network model using the susceptible-infected-refractory dynamics of an epidemic. Within the network model, a population may be characterized by H independent hierarchies or dimensions, each of which consists of groupings of individuals into layers of subgroups. Detailed numerical simulations reveal that for H>1, global spreading results regardless of the degree of homophily of the individuals forming a social circle. For H=1, a transition from global to local spread occurs as the population becomes decomposed into increasingly homophilous groups. Multiple dimensions in classifying individuals (nodes) thus make a society (computer network) highly susceptible to large-scale outbreaks of infectious diseases (viruses).

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.

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

Mobility management techniques for the next-generation wireless networks

Science.gov (United States)

Sun, Junzhao; Howie, Douglas P.; Sauvola, Jaakko J.

2001-10-01

The tremendous demands from social market are pushing the booming development of mobile communications faster than ever before, leading to plenty of new advanced techniques emerging. With the converging of mobile and wireless communications with Internet services, the boundary between mobile personal telecommunications and wireless computer networks is disappearing. Wireless networks of the next generation need the support of all the advances on new architectures, standards, and protocols. Mobility management is an important issue in the area of mobile communications, which can be best solved at the network layer. One of the key features of the next generation wireless networks is all-IP infrastructure. This paper discusses the mobility management schemes for the next generation mobile networks through extending IP's functions with mobility support. A global hierarchical framework model for the mobility management of wireless networks is presented, in which the mobility management is divided into two complementary tasks: macro mobility and micro mobility. As the macro mobility solution, a basic principle of Mobile IP is introduced, together with the optimal schemes and the advances in IPv6. The disadvantages of the Mobile IP on solving the micro mobility problem are analyzed, on the basis of which three main proposals are discussed as the micro mobility solutions for mobile communications, including Hierarchical Mobile IP (HMIP), Cellular IP, and Handoff-Aware Wireless Access Internet Infrastructure (HAWAII). A unified model is also described in which the different micro mobility solutions can coexist simultaneously in mobile networks.

Discursive Hierarchical Patterning in Law and Management Cases

Science.gov (United States)

Lung, Jane

2008-01-01

This paper investigates the differences in the discursive patterning of cases in Law and Management. It examines a corpus of 271 Law and Management cases and discusses the kind of information that these two disciplines call for and how discourses are constructed in discursive hierarchical patterns. A discursive hierarchical pattern is a model…

Extension of mixture-of-experts networks for binary classification of hierarchical data.

Science.gov (United States)

Ng, Shu-Kay; McLachlan, Geoffrey J

2007-09-01

For many applied problems in the context of medically relevant artificial intelligence, the data collected exhibit a hierarchical or clustered structure. Ignoring the interdependence between hierarchical data can result in misleading classification. In this paper, we extend the mechanism for mixture-of-experts (ME) networks for binary classification of hierarchical data. Another extension is to quantify cluster-specific information on data hierarchy by random effects via the generalized linear mixed-effects model (GLMM). The extension of ME networks is implemented by allowing for correlation in the hierarchical data in both the gating and expert networks via the GLMM. The proposed model is illustrated using a real thyroid disease data set. In our study, we consider 7652 thyroid diagnosis records from 1984 to early 1987 with complete information on 20 attribute values. We obtain 10 independent random splits of the data into a training set and a test set in the proportions 85% and 15%. The test sets are used to assess the generalization performance of the proposed model, based on the percentage of misclassifications. For comparison, the results obtained from the ME network with independence assumption are also included. With the thyroid disease data, the misclassification rate on test sets for the extended ME network is 8.9%, compared to 13.9% for the ME network. In addition, based on model selection methods described in Section 2, a network with two experts is selected. These two expert networks can be considered as modeling two groups of patients with high and low incidence rates. Significant variation among the predicted cluster-specific random effects is detected in the patient group with low incidence rate. It is shown that the extended ME network outperforms the ME network for binary classification of hierarchical data. With the thyroid disease data, useful information on the relative log odds of patients with diagnosed conditions at different periods can be

TiO2 nanowire-templated hierarchical nanowire network as water-repelling coating

Science.gov (United States)

Hang, Tian; Chen, Hui-Jiuan; Xiao, Shuai; Yang, Chengduan; Chen, Meiwan; Tao, Jun; Shieh, Han-ping; Yang, Bo-ru; Liu, Chuan; Xie, Xi

2017-12-01

Extraordinary water-repelling properties of superhydrophobic surfaces make them novel candidates for a great variety of potential applications. A general approach to achieve superhydrophobicity requires low-energy coating on the surface and roughness on nano- and micrometre scale. However, typical construction of superhydrophobic surfaces with micro-nano structure through top-down fabrication is restricted by sophisticated fabrication techniques and limited choices of substrate materials. Micro-nanoscale topographies templated by conventional microparticles through surface coating may produce large variations in roughness and uncontrollable defects, resulting in poorly controlled surface morphology and wettability. In this work, micro-nanoscale hierarchical nanowire network was fabricated to construct self-cleaning coating using one-dimensional TiO2 nanowires as microscale templates. Hierarchical structure with homogeneous morphology was achieved by branching ZnO nanowires on the TiO2 nanowire backbones through hydrothermal reaction. The hierarchical nanowire network displayed homogeneous micro/nano-topography, in contrast to hierarchical structure templated by traditional microparticles. This hierarchical nanowire network film exhibited high repellency to both water and cell culture medium after functionalization with fluorinated organic molecules. The hierarchical structure templated by TiO2 nanowire coating significantly increased the surface superhydrophobicity compared to vertical ZnO nanowires with nanotopography alone. Our results demonstrated a promising strategy of using nanowires as microscale templates for the rational design of hierarchical coatings with desired superhydrophobicity that can also be applied to various substrate materials.

Hierarchical modular structure enhances the robustness of self-organized criticality in neural networks

International Nuclear Information System (INIS)

Wang Shengjun; Zhou Changsong

2012-01-01

One of the most prominent architecture properties of neural networks in the brain is the hierarchical modular structure. How does the structure property constrain or improve brain function? It is thought that operating near criticality can be beneficial for brain function. Here, we find that networks with modular structure can extend the parameter region of coupling strength over which critical states are reached compared to non-modular networks. Moreover, we find that one aspect of network function—dynamical range—is highest for the same parameter region. Thus, hierarchical modularity enhances robustness of criticality as well as function. However, too much modularity constrains function by preventing the neural networks from reaching critical states, because the modular structure limits the spreading of avalanches. Our results suggest that the brain may take advantage of the hierarchical modular structure to attain criticality and enhanced function. (paper)

Metastable states in the hierarchical Dyson model drive parallel processing in the hierarchical Hopfield network

International Nuclear Information System (INIS)

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

2015-01-01

In this paper, we introduce and investigate the statistical mechanics of hierarchical neural networks. First, we approach these systems à la Mattis, by thinking of the Dyson model as a single-pattern hierarchical neural network. We also discuss the stability of different retrievable states as predicted by the related self-consistencies obtained both from a mean-field bound and from a bound that bypasses the mean-field limitation. The latter is worked out by properly reabsorbing the magnetization fluctuations related to higher levels of the hierarchy into effective fields for the lower levels. Remarkably, mixing Amit's ansatz technique for selecting candidate-retrievable states with the interpolation procedure for solving for the free energy of these states, we prove that, due to gauge symmetry, the Dyson model accomplishes both serial and parallel processing. We extend this scenario to multiple stored patterns by implementing the Hebb prescription for learning within the couplings. This results in Hopfield-like networks constrained on a hierarchical topology, for which, by restricting to the low-storage regime where the number of patterns grows at its most logarithmical with the amount of neurons, we prove the existence of the thermodynamic limit for the free energy, and we give an explicit expression of its mean-field bound and of its related improved bound. We studied the resulting self-consistencies for the Mattis magnetizations, which act as order parameters, are studied and the stability of solutions is analyzed to get a picture of the overall retrieval capabilities of the system according to both mean-field and non-mean-field scenarios. Our main finding is that embedding the Hebbian rule on a hierarchical topology allows the network to accomplish both serial and parallel processing. By tuning the level of fast noise affecting it or triggering the decay of the interactions with the distance among neurons, the system may switch from sequential retrieval to

On the design of a hierarchical SS7 network: A graph theoretical approach

Science.gov (United States)

Krauss, Lutz; Rufa, Gerhard

1994-04-01

This contribution is concerned with the design of Signaling System No. 7 networks based on graph theoretical methods. A hierarchical network topology is derived by combining the advantage of the hierarchical network structure with the realization of node disjoint routes between nodes of the network. By using specific features of this topology, we develop an algorithm to construct circle-free routing data and to assure bidirectionality also in case of failure situations. The methods described are based on the requirements that the network topology, as well as the routing data, may be easily changed.

Translating Management Practices in Hierarchical Organizations

DEFF Research Database (Denmark)

Wæraas, Arild; Nielsen, Jeppe Agger

structures affect translators’ approaches taken towards management ideas. This paper reports the findings from a longitudinal case study of the translation of Leadership Pipeline in a Danish fire department and how the translators’ approach changed over time from a modifying to a reproducing mode. The study......This study examines how translators in a hierarchical context approach the translation of management practices. Although current translation theory and research emphasize the importance of contextual factors in translation processes, little research has investigated how strongly hierarchical...... finds that translation does not necessarily imply transformation of the management idea, pointing instead to aspects of exact imitation and copying of an ”original” idea. It also highlights how translation is likely to involve multiple and successive translation modes and, furthermore, that strongly...

Topology-based hierarchical scheduling using deficit round robin

DEFF Research Database (Denmark)

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

2009-01-01

according to the topology. The mapping process could be completed through the network management plane or by manual configuration. Based on the knowledge of the network, the scheduler can manage the traffic on behalf of other less advanced nodes, avoid potential traffic congestion, and provide flow...... protection and isolation. Comparisons between hierarchical scheduling, flow-based scheduling, and class-based scheduling schemes have been carried out under a symmetric tree topology. Results have shown that the hierarchical scheduling scheme provides better flow protection and isolation from attack...

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.

Hierarchical feedback modules and reaction hubs in cell signaling networks.

Science.gov (United States)

Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

Hierarchical feedback modules and reaction hubs in cell signaling networks.

Directory of Open Access Journals (Sweden)

Jianfeng Xu

Full Text Available Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks.

Hierarchical Feedback Modules and Reaction Hubs in Cell Signaling Networks

Science.gov (United States)

Xu, Jianfeng; Lan, Yueheng

2015-01-01

Despite much effort, identification of modular structures and study of their organizing and functional roles remain a formidable challenge in molecular systems biology, which, however, is essential in reaching a systematic understanding of large-scale cell regulation networks and hence gaining capacity of exerting effective interference to cell activity. Combining graph theoretic methods with available dynamics information, we successfully retrieved multiple feedback modules of three important signaling networks. These feedbacks are structurally arranged in a hierarchical way and dynamically produce layered temporal profiles of output signals. We found that global and local feedbacks act in very different ways and on distinct features of the information flow conveyed by signal transduction but work highly coordinately to implement specific biological functions. The redundancy embodied with multiple signal-relaying channels and feedback controls bestow great robustness and the reaction hubs seated at junctions of different paths announce their paramount importance through exquisite parameter management. The current investigation reveals intriguing general features of the organization of cell signaling networks and their relevance to biological function, which may find interesting applications in analysis, design and control of bio-networks. PMID:25951347

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.

Hierarchically porous MgCo2O4 nanochain networks: template-free synthesis and catalytic application

Science.gov (United States)

Guan, Xiangfeng; Yu, Yunlong; Li, Xiaoyan; Chen, Dagui; Luo, Peihui; Zhang, Yu; Guo, Shanxin

2018-01-01

In this work, hierarchically porous MgCo2O4 nanochain networks were successfully synthesized by a novel template-free method realized via a facile solvothermal synthesis followed by a heat treatment. The morphologies of MgCo2O4 precursor could be adjusted from nanosheets to nanobelts and finally to interwoven nanowires, depending on the volume ratio of diethylene glycol to deionized water in the solution. After calcination, the interwoven precursor nanowires were transformed to hierarchical MgCo2O4 nanochain networks with marco-/meso-porosity, which are composed of 10-20 nm nanoparticles connected one by one. Moreover, the relative formation mechanism of the MgCo2O4 nanochain networks was discussed. More importantly, when evaluated as catalytic additive for AP thermal decomposition, the MgCo2O4 nanochain networks show excellent accelerating effect. It is benefited from the unique hierarchically porous network structure and multicomponent effect, which effectively accelerates ammonia oxidation and {{{{ClO}}}4}- species dissociation. This approach opens the way to design other hierarchically porous multicomponent metal oxides.

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.

Efficient Utilization of Hierarchical iJTAG Networks for Interrupts Management

NARCIS (Netherlands)

Ibrahim, Ahmed Mohammed Youssef; Kerkhoff, Hans G.

2016-01-01

Modern systems-on-chips rely on embedded instruments for testing and debugging, the same instruments could be used for managing the lifetime dependability of the chips. The IEEE 1687 (iJTAG) standard introduces an access network to the instruments based on reconfigurable scan paths. During lifetime,

A distributed location management strategy for next generation IP-based wireless networks

Institute of Scientific and Technical Information of China (English)

SONG Mei; FENG Rui-jun; HUANG Jian-wen; SONG Jun-de

2006-01-01

Location management is the most important function in mobility management technology. The hierarchical structure of the proposed hierarchical network-layer mobility management (HNMM) can reduce the signaling cost. The selforganizing topology scheme can enhance the robustness and quality of the mobility management. The information of location of the mobile node is stored in the distributed database,which makes the storage of the location information more reliable and robust, and more flexible strategies can be used.The numeric results show that HNMM can provide better performance than the general structure of mobile IPv6, when the mobile nodes move frequently and when there is high traffic throughput.

Visual question answering using hierarchical dynamic memory networks

Science.gov (United States)

Shang, Jiayu; Li, Shiren; Duan, Zhikui; Huang, Junwei

2018-04-01

Visual Question Answering (VQA) is one of the most popular research fields in machine learning which aims to let the computer learn to answer natural language questions with images. In this paper, we propose a new method called hierarchical dynamic memory networks (HDMN), which takes both question attention and visual attention into consideration impressed by Co-Attention method, which is the best (or among the best) algorithm for now. Additionally, we use bi-directional LSTMs, which have a better capability to remain more information from the question and image, to replace the old unit so that we can capture information from both past and future sentences to be used. Then we rebuild the hierarchical architecture for not only question attention but also visual attention. What's more, we accelerate the algorithm via a new technic called Batch Normalization which helps the network converge more quickly than other algorithms. The experimental result shows that our model improves the state of the art on the large COCO-QA dataset, compared with other methods.

Energy-efficient hierarchical processing in the network of wireless intelligent sensors (WISE)

Science.gov (United States)

Raskovic, Dejan

Sensor network nodes have benefited from technological advances in the field of wireless communication, processing, and power sources. However, the processing power of microcontrollers is often not sufficient to perform sophisticated processing, while the power requirements of digital signal processing boards or handheld computers are usually too demanding for prolonged system use. We are matching the intrinsic hierarchical nature of many digital signal-processing applications with the natural hierarchy in distributed wireless networks, and building the hierarchical system of wireless intelligent sensors. Our goal is to build a system that will exploit the hierarchical organization to optimize the power consumption and extend battery life for the given time and memory constraints, while providing real-time processing of sensor signals. In addition, we are designing our system to be able to adapt to the current state of the environment, by dynamically changing the algorithm through procedure replacement. This dissertation presents the analysis of hierarchical environment and methods for energy profiling used to evaluate different system design strategies, and to optimize time-effective and energy-efficient processing.

Eigenspaces of networks reveal the overlapping and hierarchical community structure more precisely

International Nuclear Information System (INIS)

Ma, Xiaoke; Gao, Lin; Yong, Xuerong

2010-01-01

Identifying community structure is fundamental for revealing the structure–functionality relationship in complex networks, and spectral algorithms have been shown to be powerful for this purpose. In a traditional spectral algorithm, each vertex of a network is embedded into a spectral space by making use of the eigenvectors of the adjacency matrix or Laplacian matrix of the graph. In this paper, a novel spectral approach for revealing the overlapping and hierarchical community structure of complex networks is proposed by not only using the eigenvalues and eigenvectors but also the properties of eigenspaces of the networks involved. This gives us a better characterization of community. We first show that the communicability between a pair of vertices can be rewritten in term of eigenspaces of a network. An agglomerative clustering algorithm is then presented to discover the hierarchical communities using the communicability matrix. Finally, these overlapping vertices are discovered with the corresponding eigenspaces, based on the fact that the vertices more densely connected amongst one another are more likely to be linked through short cycles. Compared with the traditional spectral algorithms, our algorithm can identify both the overlapping and hierarchical community without increasing the time complexity O(n 3 ), where n is the size of the network. Furthermore, our algorithm can also distinguish the overlapping vertices from bridges. The method is tested by applying it to some computer-generated and real-world networks. The experimental results indicate that our algorithm can reveal community structure more precisely than the traditional spectral approaches

Convergent evidence for hierarchical prediction networks from human electrocorticography and magnetoencephalography.

Science.gov (United States)

Phillips, Holly N; Blenkmann, Alejandro; Hughes, Laura E; Kochen, Silvia; Bekinschtein, Tristan A; Cam-Can; Rowe, James B

2016-09-01

We propose that sensory inputs are processed in terms of optimised predictions and prediction error signals within hierarchical neurocognitive models. The combination of non-invasive brain imaging and generative network models has provided support for hierarchical frontotemporal interactions in oddball tasks, including recent identification of a temporal expectancy signal acting on prefrontal cortex. However, these studies are limited by the need to invert magnetoencephalographic or electroencephalographic sensor signals to localise activity from cortical 'nodes' in the network, or to infer neural responses from indirect measures such as the fMRI BOLD signal. To overcome this limitation, we examined frontotemporal interactions estimated from direct cortical recordings from two human participants with cortical electrode grids (electrocorticography - ECoG). Their frontotemporal network dynamics were compared to those identified by magnetoencephalography (MEG) in forty healthy adults. All participants performed the same auditory oddball task with standard tones interspersed with five deviant tone types. We normalised post-operative electrode locations to standardised anatomic space, to compare across modalities, and inverted the MEG to cortical sources using the estimated lead field from subject-specific head models. A mismatch negativity signal in frontal and temporal cortex was identified in all subjects. Generative models of the electrocorticographic and magnetoencephalographic data were separately compared using the free-energy estimate of the model evidence. Model comparison confirmed the same critical features of hierarchical frontotemporal networks in each patient as in the group-wise MEG analysis. These features included bilateral, feedforward and feedback frontotemporal modulated connectivity, in addition to an asymmetric expectancy driving input on left frontal cortex. The invasive ECoG provides an important step in construct validation of the use of neural

Hierarchical modeling of molecular energies using a deep neural network

Science.gov (United States)

Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

2018-06-01

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

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

DEFF Research Database (Denmark)

Ding, Tao; Li, Cheng; Huang, Can

2018-01-01

–slave structure and improves traditional centralized modeling methods by alleviating the big data problem in a control center. Specifically, the transmission-distribution-network coordination issue of the hierarchical modeling method is investigated. First, a curve-fitting approach is developed to provide a cost......In order to solve the reactive power optimization with joint transmission and distribution networks, a hierarchical modeling method is proposed in this paper. It allows the reactive power optimization of transmission and distribution networks to be performed separately, leading to a master...... optimality. Numerical results on two test systems verify the effectiveness of the proposed hierarchical modeling and curve-fitting methods....

Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

Science.gov (United States)

Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

Optimal Hierarchical Modular Topologies for Producing Limited Sustained Activation of Neural Networks

OpenAIRE

Kaiser, Marcus; Hilgetag, Claus C.

2010-01-01

An essential requirement for the representation of functional patterns in complex neural networks, such as the mammalian cerebral cortex, is the existence of stable regimes of network activation, typically arising from a limited parameter range. In this range of limited sustained activity (LSA), the activity of neural populations in the network persists between the extremes of either quickly dying out or activating the whole network. Hierarchical modular networks were previously found to show...

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.

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.

A bioscaffolding strategy for hierarchical zeolites with a nanotube-trimodal network.

Science.gov (United States)

Li, Guannan; Huang, Haibo; Yu, Bowen; Wang, Yun; Tao, Jiawei; Wei, Yingxu; Li, Shougui; Liu, Zhongmin; Xu, Yan; Xu, Ruren

2016-02-01

Hierarchical zeolite monoliths with multimodal porosity are of paramount importance as they open up new horizons for advanced applications. So far, hierarchical zeolites based on nanotube scaffolds have never been reported. Inspired by the organization of biominerals, we have developed a novel precursor scaffolding-solid phase crystallization strategy for hierarchical zeolites with a unique nanotube scaffolding architecture and nanotube-trimodal network, where biomolecular self-assembly (BSA) provides a scaffolding blueprint. By vapor-treating Sil-1 seeded precursor scaffolds, zeolite MFI nanotube scaffolds are self-generated, during which evolution phenomena such as segmented voids and solid bridges are observed, in agreement with the Kirkendall effect in a solid-phase crystallization system. The nanotube walls are made of intergrown single crystals rendering good mechanical stability. The inner diameter of the nanotube is tunable between 30 and 90 nm by varying the thickness of the precursor layers. Macropores enclosed by cross-linked nanotubes can be modulated by the choice of BSA. Narrow mesopores are formed by intergrown nanocrystals. Hierarchical ZSM-5 monoliths with nanotube (90 nm), micropore (0.55 nm), mesopore (2 nm) and macropore (700 nm) exhibit superior catalytic performance in the methanol-to-hydrocarbon (MTH) conversion compared to conventional ZSM-5. BSA remains intact after crystallization, allowing a higher level of organization and functionalization of the zeolite nanotube scaffolds. The current work may afford a versatile strategy for hierarchical zeolite monoliths with nanotube scaffolding architectures and a nanotube-multimodal network leading to self-supporting and active zeolite catalysts, and for applications beyond.

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

Visualization and Hierarchical Analysis of Flow in Discrete Fracture Network Models

Science.gov (United States)

Aldrich, G. A.; Gable, C. W.; Painter, S. L.; Makedonska, N.; Hamann, B.; Woodring, J.

2013-12-01

Flow and transport in low permeability fractured rock is primary in interconnected fracture networks. Prediction and characterization of flow and transport in fractured rock has important implications in underground repositories for hazardous materials (eg. nuclear and chemical waste), contaminant migration and remediation, groundwater resource management, and hydrocarbon extraction. We have developed methods to explicitly model flow in discrete fracture networks and track flow paths using passive particle tracking algorithms. Visualization and analysis of particle trajectory through the fracture network is important to understanding fracture connectivity, flow patterns, potential contaminant pathways and fast paths through the network. However, occlusion due to the large number of highly tessellated and intersecting fracture polygons preclude the effective use of traditional visualization methods. We would also like quantitative analysis methods to characterize the trajectory of a large number of particle paths. We have solved these problems by defining a hierarchal flow network representing the topology of particle flow through the fracture network. This approach allows us to analyses the flow and the dynamics of the system as a whole. We are able to easily query the flow network, and use paint-and-link style framework to filter the fracture geometry and particle traces based on the flow analytics. This allows us to greatly reduce occlusion while emphasizing salient features such as the principal transport pathways. Examples are shown that demonstrate the methodology and highlight how use of this new method allows quantitative analysis and characterization of flow and transport in a number of representative fracture networks.

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.

Hierarchical analysis of dependency in metabolic networks.

Science.gov (United States)

Gagneur, Julien; Jackson, David B; Casari, Georg

2003-05-22

Elucidation of metabolic networks for an increasing number of organisms reveals that even small networks can contain thousands of reactions and chemical species. The intimate connectivity between components complicates their decomposition into biologically meaningful sub-networks. Moreover, traditional higher-order representations of metabolic networks as metabolic pathways, suffers from the lack of rigorous definition, yielding pathways of disparate content and size. We introduce a hierarchical representation that emphasizes the gross organization of metabolic networks in largely independent pathways and sub-systems at several levels of independence. The approach highlights the coupling of different pathways and the shared compounds responsible for those couplings. By assessing our results on Escherichia coli (E.coli metabolic reactions, Genetic Circuits Research Group, University of California, San Diego, http://gcrg.ucsd.edu/organisms/ecoli.html, 'model v 1.01. reactions') against accepted biochemical annotations, we provide the first systematic synopsis of an organism's metabolism. Comparison with operons of E.coli shows that low-level clusters are reflected in genome organization and gene regulation. Source code, data sets and supplementary information are available at http://www.mas.ecp.fr/labo/equipe/gagneur/hierarchy/hierarchy.html

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

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 al...

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

Exploring hierarchical and overlapping modular structure in the yeast protein interaction network

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Zhao Yi

2010-12-01

Full Text Available Abstract Background Developing effective strategies to reveal modular structures in protein interaction networks is crucial for better understanding of molecular mechanisms of underlying biological processes. In this paper, we propose a new density-based algorithm (ADHOC for clustering vertices of a protein interaction network using a novel subgraph density measurement. Results By statistically evaluating several independent criteria, we found that ADHOC could significantly improve the outcome as compared with five previously reported density-dependent methods. We further applied ADHOC to investigate the hierarchical and overlapping modular structure in the yeast PPI network. Our method could effectively detect both protein modules and the overlaps between them, and thus greatly promote the precise prediction of protein functions. Moreover, by further assaying the intermodule layer of the yeast PPI network, we classified hubs into two types, module hubs and inter-module hubs. Each type presents distinct characteristics both in network topology and biological functions, which could conduce to the better understanding of relationship between network architecture and biological implications. Conclusions Our proposed algorithm based on the novel subgraph density measurement makes it possible to more precisely detect hierarchical and overlapping modular structures in protein interaction networks. In addition, our method also shows a strong robustness against the noise in network, which is quite critical for analyzing such a high noise network.

Accurate detection of hierarchical communities in complex networks based on nonlinear dynamical evolution

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Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng

2018-04-01

One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community

The hierarchical brain network for face recognition.

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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.

Network management paradigm in education as a component of information society

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O. O. Kolesnic

2014-05-01

Full Text Available Network organization has always existed, but that today information technologies create the material basis for the penetration of this type of structure in all areas. This allows to interpret the formation of a network management paradigm as one of the innovative processes of information society . The effects on the development of the virtual environment in the form of a network society leads to the fact that traditional forms of management education change it its own characteristics and there are conditions for the effective use of new forms of governance, it is connected with the network nature of education as a space object management. In practice, the process of modernization of the existing network of educational institutions and organizations that generally means use of information technology and the significant decline in the share of traditional hierarchical forms of control by increasing the share of collective polyarchical forms. Today, the introduction of a network management paradigm of education is performed primarily as a stochastic process of entering educational institutions in the space of network society. The main methodological shortcomings of network management in education is the lack of understanding of its specificity in the context of providing social impact of educational activities. Promising area of implementation of network management in education is the use of targeted management practices that focus on the development of very specific forms of network co­operation in education.

Category theoretic analysis of hierarchical protein materials and social networks.

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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.

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

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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

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 depen...

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

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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

A Framework for Joint Optical-Wireless Resource Management in Multi-RAT, Heterogeneous Mobile Networks

DEFF Research Database (Denmark)

Zakrzewska, Anna; Popovska Avramova, Andrijana; Christiansen, Henrik Lehrmann

2013-01-01

Mobile networks are constantly evolving: new Radio Access Technologies (RATs) are being introduced, and backhaul architectures like Cloud-RAN (C-RAN) and distributed base stations are being proposed. Furthermore, small cells are being deployed to enhance network capacity. The end-users wish...... to be always connected to a high-quality service (high bit rates, low latency), thus causing a very complex network control task from an operator’s point of view. We thus propose a framework allowing joint overall network resource management. This scheme covers different types of network heterogeneity (multi......-RAT, multi-layer, multi-architecture) by introducing a novel, hierarchical approach to network resource management. Self-Organizing Networks (SON) and cognitive network behaviors are covered as well as more traditional mobile network features. The framework is applicable to all phases of network operation...

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

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Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical inverse covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fmri, meg and eeg data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in meg beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

Growth and containment of a hierarchical criminal network

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Marshak, Charles Z.; Rombach, M. Puck; Bertozzi, Andrea L.; D'Orsogna, Maria R.

2016-02-01

We model the hierarchical evolution of an organized criminal network via antagonistic recruitment and pursuit processes. Within the recruitment phase, a criminal kingpin enlists new members into the network, who in turn seek out other affiliates. New recruits are linked to established criminals according to a probability distribution that depends on the current network structure. At the same time, law enforcement agents attempt to dismantle the growing organization using pursuit strategies that initiate on the lower level nodes and that unfold as self-avoiding random walks. The global details of the organization are unknown to law enforcement, who must explore the hierarchy node by node. We halt the pursuit when certain local criteria of the network are uncovered, encoding if and when an arrest is made; the criminal network is assumed to be eradicated if the kingpin is arrested. We first analyze recruitment and study the large scale properties of the growing network; later we add pursuit and use numerical simulations to study the eradication probability in the case of three pursuit strategies, the time to first eradication, and related costs. Within the context of this model, we find that eradication becomes increasingly costly as the network increases in size and that the optimal way of arresting the kingpin is to intervene at the early stages of network formation. We discuss our results in the context of dark network disruption and their implications on possible law enforcement strategies.

Priority-Based Hierarchical Operational Management for Multiagent-Based Microgrids

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Takumi Kato

2014-03-01

Full Text Available Electricity consumption in the world is constantly increasing, making our lives become more and more dependent on electricity. There are several new paradigms proposed in the field of power grids. In Japan, especially after the Great East Japan Earthquake in March 2011, the new power grid paradigms are expected to be more resilient to survive several difficulties during disasters. In this paper, we focus on microgrids and propose priority-based hierarchical operational management for multiagent-based microgrids. The proposed management is a new multiagent-based load shedding scheme and multiagent-based hierarchical architecture to realize such resilient microgrids. We developed a prototype system and performed an evaluation of the proposed management using the developed system. The result of the evaluation shows the effectiveness of our proposal in power shortage situations, such as disasters.

Hierarchical ordering with partial pairwise hierarchical relationships on the macaque brain data sets.

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Woosang Lim

Full Text Available Hierarchical organizations of information processing in the brain networks have been known to exist and widely studied. To find proper hierarchical structures in the macaque brain, the traditional methods need the entire pairwise hierarchical relationships between cortical areas. In this paper, we present a new method that discovers hierarchical structures of macaque brain networks by using partial information of pairwise hierarchical relationships. Our method uses a graph-based manifold learning to exploit inherent relationship, and computes pseudo distances of hierarchical levels for every pair of cortical areas. Then, we compute hierarchy levels of all cortical areas by minimizing the sum of squared hierarchical distance errors with the hierarchical information of few cortical areas. We evaluate our method on the macaque brain data sets whose true hierarchical levels are known as the FV91 model. The experimental results show that hierarchy levels computed by our method are similar to the FV91 model, and its errors are much smaller than the errors of hierarchical clustering approaches.

Complex networks with scale-free nature and hierarchical modularity

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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.

Hierarchical-control-based output synchronization of coexisting attractor networks

International Nuclear Information System (INIS)

Yun-Zhong, Song; Yi-Fa, Tang

2010-01-01

This paper introduces the concept of hierarchical-control-based output synchronization of coexisting attractor networks. Within the new framework, each dynamic node is made passive at first utilizing intra-control around its own arena. Then each dynamic node is viewed as one agent, and on account of that, the solution of output synchronization of coexisting attractor networks is transformed into a multi-agent consensus problem, which is made possible by virtue of local interaction between individual neighbours; this distributed working way of coordination is coined as inter-control, which is only specified by the topological structure of the network. Provided that the network is connected and balanced, the output synchronization would come true naturally via synergy between intra and inter-control actions, where the Tightness is proved theoretically via convex composite Lyapunov functions. For completeness, several illustrative examples are presented to further elucidate the novelty and efficacy of the proposed scheme. (general)

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

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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.

LSTM-Based Hierarchical Denoising Network for Android Malware Detection

OpenAIRE

Yan, Jinpei; Qi, Yong; Rao, Qifan

2018-01-01

Mobile security is an important issue on Android platform. Most malware detection methods based on machine learning models heavily rely on expert knowledge for manual feature engineering, which are still difficult to fully describe malwares. In this paper, we present LSTM-based hierarchical denoise network (HDN), a novel static Android malware detection method which uses LSTM to directly learn from the raw opcode sequences extracted from decompiled Android files. However, most opcode sequence...

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

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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...

Classifying dysmorphic syndromes by using artificial neural network based hierarchical decision tree.

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Özdemir, Merve Erkınay; Telatar, Ziya; Eroğul, Osman; Tunca, Yusuf

2018-05-01

Dysmorphic syndromes have different facial malformations. These malformations are significant to an early diagnosis of dysmorphic syndromes and contain distinctive information for face recognition. In this study we define the certain features of each syndrome by considering facial malformations and classify Fragile X, Hurler, Prader Willi, Down, Wolf Hirschhorn syndromes and healthy groups automatically. The reference points are marked on the face images and ratios between the points' distances are taken into consideration as features. We suggest a neural network based hierarchical decision tree structure in order to classify the syndrome types. We also implement k-nearest neighbor (k-NN) and artificial neural network (ANN) classifiers to compare classification accuracy with our hierarchical decision tree. The classification accuracy is 50, 73 and 86.7% with k-NN, ANN and hierarchical decision tree methods, respectively. Then, the same images are shown to a clinical expert who achieve a recognition rate of 46.7%. We develop an efficient system to recognize different syndrome types automatically in a simple, non-invasive imaging data, which is independent from the patient's age, sex and race at high accuracy. The promising results indicate that our method can be used for pre-diagnosis of the dysmorphic syndromes by clinical experts.

Correlation between hierarchical structure of crystal networks and macroscopic performance of mesoscopic soft materials and engineering principles.

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Lin, Naibo; Liu, Xiang Yang

2015-11-07

This review examines how the concepts and ideas of crystallization can be extended further and applied to the field of mesoscopic soft materials. It concerns the structural characteristics vs. the macroscopic performance, and the formation mechanism of crystal networks. Although this subject can be discussed in a broad sense across the area of mesoscopic soft materials, our main focus is on supramolecular materials, spider and silkworm silks, and biominerals. First, the occurrence of a hierarchical structure, i.e. crystal network and domain network structures, will facilitate the formation kinetics of mesoscopic phases and boost up the macroscopic performance of materials in some cases (i.e. spider silk fibres). Second, the structure and performance of materials can be correlated in some way by the four factors: topology, correlation length, symmetry/ordering, and strength of association of crystal networks. Moreover, four different kinetic paths of crystal network formation are identified, namely, one-step process of assembly, two-step process of assembly, mixed mode of assembly and foreign molecule mediated assembly. Based on the basic mechanisms of crystal nucleation and growth, the formation of crystal networks, such as crystallographic mismatch (or noncrystallographic) branching (tip branching and fibre side branching) and fibre/polymeric side merging, are reviewed. This facilitates the rational design and construction of crystal networks in supramolecular materials. In this context, the (re-)construction of a hierarchical crystal network structure can be implemented by thermal, precipitate, chemical, and sonication stimuli. As another important class of soft materials, the unusual mechanical performance of spider and silkworm silk fibres are reviewed in comparison with the regenerated silk protein derivatives. It follows that the considerably larger breaking stress and unusual breaking strain of spider silk fibres vs. silkworm silk fibres can be interpreted

A hierarchical clustering scheme approach to assessment of IP-network traffic using detrended fluctuation analysis

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Takuma, Takehisa; Masugi, Masao

2009-03-01

This paper presents an approach to the assessment of IP-network traffic in terms of the time variation of self-similarity. To get a comprehensive view in analyzing the degree of long-range dependence (LRD) of IP-network traffic, we use a hierarchical clustering scheme, which provides a way to classify high-dimensional data with a tree-like structure. Also, in the LRD-based analysis, we employ detrended fluctuation analysis (DFA), which is applicable to the analysis of long-range power-law correlations or LRD in non-stationary time-series signals. Based on sequential measurements of IP-network traffic at two locations, this paper derives corresponding values for the LRD-related parameter α that reflects the degree of LRD of measured data. In performing the hierarchical clustering scheme, we use three parameters: the α value, average throughput, and the proportion of network traffic that exceeds 80% of network bandwidth for each measured data set. We visually confirm that the traffic data can be classified in accordance with the network traffic properties, resulting in that the combined depiction of the LRD and other factors can give us an effective assessment of network conditions at different times.

An Efficient, Hierarchical Viewpoint Planning Strategy for Terrestrial Laser Scanner Networks

Science.gov (United States)

Jia, F.; Lichti, D. D.

2018-05-01

Terrestrial laser scanner (TLS) techniques have been widely adopted in a variety of applications. However, unlike in geodesy or photogrammetry, insufficient attention has been paid to the optimal TLS network design. It is valuable to develop a complete design system that can automatically provide an optimal plan, especially for high-accuracy, large-volume scanning networks. To achieve this goal, one should look at the "optimality" of the solution as well as the computational complexity in reaching it. In this paper, a hierarchical TLS viewpoint planning strategy is developed to solve the optimal scanner placement problems. If one targeted object to be scanned is simplified as discretized wall segments, any possible viewpoint can be evaluated by a score table representing its visible segments under certain scanning geometry constraints. Thus, the design goal is to find a minimum number of viewpoints that achieves complete coverage of all wall segments. The efficiency is improved by densifying viewpoints hierarchically, instead of a "brute force" search within the entire workspace. The experiment environments in this paper were simulated from two buildings located on University of Calgary campus. Compared with the "brute force" strategy in terms of the quality of the solutions and the runtime, it is shown that the proposed strategy can provide a scanning network with a compatible quality but with more than a 70 % time saving.

Hierarchical ZnO microspheres built by sheet-like network: Large-scale synthesis and structurally enhanced catalytic performances

International Nuclear Information System (INIS)

Zhu Guoxing; Liu Yuanjun; Ji Zhenyuan; Bai Song; Shen Xiaoping; Xu Zheng

2012-01-01

Highlights: ► Hierarchical ZnO microspheres were prepared through a facile precursor procedure in the absence of self-assembled templates, organic additives, or matrices. ► The building blocks of microspheres, sheet-like ZnO networks, are porous mesocrystal terminated with (0 1 −1 0) crystal planes. ► The hierarchical ZnO microsphere catalyst exhibits structure-induced enhancement of catalytic performance and a strong durability. - Abstract: Large-scale novel hierarchical ZnO microspheres were fabricated by a facile precursor procedure in the absence of self-assembled templates, organic additives, or matrices. A field emission scanning electron microscopy (FESEM) image reveals that the ZnO microspheres with diameter of 5–18 μm are built by sheet-like ZnO networks with average thickness of 40 nm and length of several microns. High resolution transmission electron microscopy (HRTEM) image indicates that the building blocks, sheet-like ZnO networks, are porous mesocrystal terminated with {0 1 −1 0} crystal planes. A potential application of the ZnO microspheres as a catalyst in the synthesis of 5-substituted 1H-tetrazoles was investigated. It was found that the hierarchical ZnO microsphere catalyst exhibits structure-induced enhancement of catalytic performance and a strong durability.

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

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

2017-01-09

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.

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

. This approach avoids unnecessary and frequent handoff between cells and reduces signaling overheads. An approximation model with guaranteed accuracy and low computational complexity is presented for the loss performance of multiservice traffic. The accuracy of numerical results is validated by comparing......A hierarchical overlay structure is an alternative solution that integrates existing and future heterogeneous wireless networks to provide subscribers with better mobile broadband services. Traffic loss performance in such integrated heterogeneous networks is necessary for an operator's network...

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

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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.

IMPLEMENTASI MANAJEMEN BANDWIDTH DENGAN DISIPLIN ANTRIAN HIERARCHICAL TOKEN BUCKET (HTB PADA SISTEM OPERASI LINUX

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Muhammad Nugraha

2017-01-01

Full Text Available Important Problem on Internet networking is exhausted resource and bandwidth by some user while other user did not get service properly. To overcome that problem we need to implement traffic control and bandwidth management system in router. In this research author want to implement Hierarchical Token Bucket algorithm as queue discipline (qdisc to get bandwidth management accurately in order the user can get bandwidth properly. The result of this research is form the management bandwidth cheaply and efficiently by using Hierarchical Token Bucket qdisc on Linux operating system were able to manage the user as we want.

Implementasi Manajemen Bandwidth Dengan Disiplin Antrian Hierarchical Token Bucket (HTB Pada Sistem Operasi Linux

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Muhammad Nugraha

2016-09-01

Full Text Available Important Problem on Internet networking is exhausted resource and bandwidth by some user while other user did not get service properly. To overcome that problem we need to implement traffic control and bandwidth management system in router. In this research author want to implement Hierarchical Token Bucket algorithm as queue discipline (qdisc to get bandwidth management accurately in order the user can get bandwidth properly. The result of this research is form the management bandwidth cheaply and efficiently by using Hierarchical Token Bucket qdisc on Linux operating system were able to manage the user as we want.

Forecasting building energy consumption with hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system

Energy Technology Data Exchange (ETDEWEB)

Li, Kangji [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China); School of Electricity Information Engineering, Jiangsu University, Zhenjiang 212013 (China); Su, Hongye [Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027 (China)

2010-11-15

There are several ways to forecast building energy consumption, varying from simple regression to models based on physical principles. In this paper, a new method, namely, the hybrid genetic algorithm-hierarchical adaptive network-based fuzzy inference system (GA-HANFIS) model is developed. In this model, hierarchical structure decreases the rule base dimension. Both clustering and rule base parameters are optimized by GAs and neural networks (NNs). The model is applied to predict a hotel's daily air conditioning consumption for a period over 3 months. The results obtained by the proposed model are presented and compared with regular method of NNs, which indicates that GA-HANFIS model possesses better performance than NNs in terms of their forecasting accuracy. (author)

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

Directory of Open Access Journals (Sweden)

Eva González-Parada

2017-01-01

Full Text Available 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.

Epidemic spreading in a hierarchical social network.

Science.gov (United States)

Grabowski, A; Kosiński, R A

2004-09-01

A model of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The structure of interpersonal connections is based on a scale-free network. Spatial localization of individuals belonging to different social groups, and the mobility of a contemporary community, as well as the effectiveness of different interpersonal interactions, are taken into account. Typical relations characterizing the spreading process, like a range of epidemic and epidemic curves, are discussed. The influence of preventive vaccinations on the spreading process is investigated. The critical value of preventively vaccinated individuals that is sufficient for the suppression of an epidemic is calculated. Our results are compared with solutions of the master equation for the spreading process and good agreement of the character of this process is found.

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.

Mobility management in the future mobile network

NARCIS (Netherlands)

Karimzadeh Motallebi Azar, Morteza

2018-01-01

The current mobile network architectures are heavily hierarchical, which implies that all traffic must be traversed through a centralized core entity. This makes the network prone to several limitations, e.g., suboptimal communication paths, low scalability, signaling overhead, and single point of

An Energy Efficient Cooperative Hierarchical MIMO Clustering Scheme for Wireless Sensor Networks

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Sungyoung Lee

2011-12-01

Full Text Available 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.

Hierarchical classification with a competitive evolutionary neural tree.

Science.gov (United States)

Adams, R G.; Butchart, K; Davey, N

1999-04-01

A new, dynamic, tree structured network, the Competitive Evolutionary Neural Tree (CENT) is introduced. The network is able to provide a hierarchical classification of unlabelled data sets. The main advantage that the CENT offers over other hierarchical competitive networks is its ability to self determine the number, and structure, of the competitive nodes in the network, without the need for externally set parameters. The network produces stable classificatory structures by halting its growth using locally calculated heuristics. The results of network simulations are presented over a range of data sets, including Anderson's IRIS data set. The CENT network demonstrates its ability to produce a representative hierarchical structure to classify a broad range of data sets.

A Hierarchical Transactive Energy Management System for Energy Sharing in Residential Microgrids

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Most Nahida Akter

2017-12-01

Full Text Available This paper presents an analytical framework to develop a hierarchical energy management system (EMS for energy sharing among neighbouring households in residential microgrids. The houses in residential microgrids are categorized into three different types, traditional, proactive and enthusiastic, based on the inclusion of solar photovoltaic (PV systems and battery energy storage systems (BESSs. Each of these three houses has an individual EMS, which is defined as the primary EMS. Two other EMSs (secondary and tertiary are also considered in the proposed hierarchical energy management framework for the purpose of effective energy sharing. The intelligences of each EMS are presented in this paper for the purpose of energy sharing in a residential microgrid along with the priorities. The effectiveness of the proposed hierarchical framework is evaluated on a residential microgrid in Australia. The analytical results clearly reflect that the proposed scheme effectively and efficiently shares the energy among neighbouring houses in a residential microgrid.

INFOGRAPHIC MODELING OF THE HIERARCHICAL STRUCTURE OF THE MANAGEMENT SYSTEM EXPOSED TO AN INNOVATIVE CONFLICT

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Chulkov Vitaliy Olegovich

2012-12-01

Full Text Available This article deals with the infographic modeling of hierarchical management systems exposed to innovative conflicts. The authors analyze the facts that serve as conflict drivers in the construction management environment. The reasons for innovative conflicts include changes in hierarchical structures of management systems, adjustment of workers to new management conditions, changes in the ideology, etc. Conflicts under consideration may involve contradictions between requests placed by customers and the legislation, any risks that may originate from the above contradiction, conflicts arising from any failure to comply with any accepted standards of conduct, etc. One of the main objectives of the theory of hierarchical structures is to develop a model capable of projecting potential innovative conflicts. Models described in the paper reflect dynamic changes in patterns of external impacts within the conflict area. The simplest model element is a monad, or an indivisible set of characteristics of participants at the pre-set level. Interaction between two monads forms a diad. Modeling of situations that involve a different number of monads, diads, resources and impacts can improve methods used to control and manage hierarchical structures in the construction industry. However, in the absence of any mathematical models employed to simulate conflict-related events, processes and situations, any research into, projection and management of interpersonal and group-to-group conflicts are to be performed in the legal environment

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.

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

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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.

Structure-function relationship in complex brain networks expressed by hierarchical synchronization

International Nuclear Information System (INIS)

Zhou Changsong; Zemanova, Lucia; Zamora-Lopez, Gorka; Hilgetag, Claus C; Kurths, Juergen

2007-01-01

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

Structure-function relationship in complex brain networks expressed by hierarchical synchronization

Energy Technology Data Exchange (ETDEWEB)

Zhou Changsong [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zemanova, Lucia [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Zamora-Lopez, Gorka [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany); Hilgetag, Claus C [Jacobs University Bremen, Campus Ring 6, Rm 116, D-28759 Bremen (Germany); Kurths, Juergen [Institute of Physics, University of Potsdam, PF 601553, 14415 Potsdam (Germany)

2007-06-15

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.

Enhancement of the Monet/Atonet Washington DC Network

National Research Council Canada - National Science Library

Jackel, Janet

2003-01-01

... Internet research networks. The report also describes research in the use of hierarchical multiplexing approaches for more efficient use of multi-wavelength networks and enhancements to the MONET Network Control & Management System...

A Hardware-Supported Algorithm for Self-Managed and Choreographed Task Execution in Sensor Networks

Directory of Open Access Journals (Sweden)

Borja Bordel

2018-03-01

Full Text Available Nowadays, sensor networks are composed of a great number of tiny resource-constraint nodes, whose management is increasingly more complex. In fact, although collaborative or choreographic task execution schemes are which fit in the most perfect way with the nature of sensor networks, they are rarely implemented because of the high resource consumption of these algorithms (especially if networks include many resource-constrained devices. On the contrary, hierarchical networks are usually designed, in whose cusp it is included a heavy orchestrator with a remarkable processing power, being able to implement any necessary management solution. However, although this orchestration approach solves most practical management problems of sensor networks, a great amount of the operation time is wasted while nodes request the orchestrator to address a conflict and they obtain the required instructions to operate. Therefore, in this paper it is proposed a new mechanism for self-managed and choreographed task execution in sensor networks. The proposed solution considers only a lightweight gateway instead of traditional heavy orchestrators and a hardware-supported algorithm, which consume a negligible amount of resources in sensor nodes. The gateway avoids the congestion of the entire sensor network and the hardware-supported algorithm enables a choreographed task execution scheme, so no particular node is overloaded. The performance of the proposed solution is evaluated through numerical and electronic ModelSim-based simulations.

Economic–environmental hierarchical frequency management of a droop-controlled islanded microgrid

International Nuclear Information System (INIS)

Rezaei, Navid; Kalantar, Mohsen

2014-01-01

Highlights: • Modeling the steady-state frequency of the droop-controlled microgrids. • Precise formulation the hierarchical control levels of islanded microgrids. • Economic–environmental frequency management using mixed-integer linear programming. • Proposing a novel objective function based on the microgrid daily frequency profile. • Scheduling primary and secondary control reserves using a stochastic optimization. - Abstract: This paper presents a novel energy management system (EMS) for a microgrid to enhance the power system security in a cost-effective manner. Small size of the islanded microgrids, high levels of intermittency and energy fluctuations, lower inertia potential of inverter-interfaced distributed energy resources (DERs) makes the frequency a vital factor in the microgrid energy management system that should be managed subject to the economic–environmental policies of the microgrid EMS. The proposed model is based on precise energy and reserve scheduling of the DERs in a droop-controlled islanded microgrid to manage the possible microgrid frequency excursions. The expected value of the microgrid frequency excursions stem from system power deviations is employed as a new objective function in this study, which is aimed to be minimized using a two stage stochastic mixed-integer linear programming method. In order to model the hierarchical control structure of the islanded microgrid, the frequency dependent behavior of the droop-controlled inverter-interfaced DERs is formulated thoroughly. The proposed model is applied to a typical microgrid test system. The primary and secondary frequency control reserves are appropriately scheduled over a 24 h period. A methodology based on the Monte-Carlo simulation strategy is adapted to generate some random scenarios corresponding to renewable generation variations, load consumption deviations and contingencies of line/unit outages. The generated scenarios are reduced and applied to the

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

2016-08-18

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.

A Multidimensional and Multimembership Clustering Method for Social Networks and Its Application in Customer Relationship Management

Directory of Open Access Journals (Sweden)

Peixin Zhao

2013-01-01

Full Text Available Community detection in social networks plays an important role in cluster analysis. Many traditional techniques for one-dimensional problems have been proven inadequate for high-dimensional or mixed type datasets due to the data sparseness and attribute redundancy. In this paper we propose a graph-based clustering method for multidimensional datasets. This novel method has two distinguished features: nonbinary hierarchical tree and the multi-membership clusters. The nonbinary hierarchical tree clearly highlights meaningful clusters, while the multimembership feature may provide more useful service strategies. Experimental results on the customer relationship management confirm the effectiveness of the new method.

LSTM-Based Hierarchical Denoising Network for Android Malware Detection

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Jinpei Yan

2018-01-01

Full Text Available Mobile security is an important issue on Android platform. Most malware detection methods based on machine learning models heavily rely on expert knowledge for manual feature engineering, which are still difficult to fully describe malwares. In this paper, we present LSTM-based hierarchical denoise network (HDN, a novel static Android malware detection method which uses LSTM to directly learn from the raw opcode sequences extracted from decompiled Android files. However, most opcode sequences are too long for LSTM to train due to the gradient vanishing problem. Hence, HDN uses a hierarchical structure, whose first-level LSTM parallelly computes on opcode subsequences (we called them method blocks to learn the dense representations; then the second-level LSTM can learn and detect malware through method block sequences. Considering that malicious behavior only appears in partial sequence segments, HDN uses method block denoise module (MBDM for data denoising by adaptive gradient scaling strategy based on loss cache. We evaluate and compare HDN with the latest mainstream researches on three datasets. The results show that HDN outperforms these Android malware detection methods,and it is able to capture longer sequence features and has better detection efficiency than N-gram-based malware detection which is similar to our method.

Preventing Distribution Grid Congestion by Integrating Indirect Control in a Hierarchical Electric Vehicles Management System

DEFF Research Database (Denmark)

Hu, Junjie; Si, Chengyong; Lind, Morten

2016-01-01

In this paper, a hierarchical management system is proposed to integrate electric vehicles (EVs) into a distribution grid. Three types of actors are included in the system: Distribution system operators (DSOs), Fleet operators (FOs) and EV owners. In contrast to a typical hierarchical control sys...

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.

A Hierarchical Energy Efficient Reliable Transport Protocol for Wireless Sensor Networks

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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.

Enhanced fuzzy-connective-based hierarchical aggregation network using particle swarm optimization

Science.gov (United States)

Wang, Fang-Fang; Su, Chao-Ton

2014-11-01

The fuzzy-connective-based aggregation network is similar to the human decision-making process. It is capable of aggregating and propagating degrees of satisfaction of a set of criteria in a hierarchical manner. Its interpreting ability and transparency make it especially desirable. To enhance its effectiveness and further applicability, a learning approach is successfully developed based on particle swarm optimization to determine the weights and parameters of the connectives in the network. By experimenting on eight datasets with different characteristics and conducting further statistical tests, it has been found to outperform the gradient- and genetic algorithm-based learning approaches proposed in the literature; furthermore, it is capable of generating more accurate estimates. The present approach retains the original benefits of fuzzy-connective-based aggregation networks and is widely applicable. The characteristics of the learning approaches are also discussed and summarized, providing better understanding of the similarities and differences among these three approaches.

GSMNet: A Hierarchical Graph Model for Moving Objects in Networks

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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.

Complex networks as an emerging property of hierarchical preferential attachment

Science.gov (United States)

Hébert-Dufresne, Laurent; Laurence, Edward; Allard, Antoine; Young, Jean-Gabriel; Dubé, Louis J.

2015-12-01

Real complex systems are not rigidly structured; no clear rules or blueprints exist for their construction. Yet, amidst their apparent randomness, complex structural properties universally emerge. We propose that an important class of complex systems can be modeled as an organization of many embedded levels (potentially infinite in number), all of them following the same universal growth principle known as preferential attachment. We give examples of such hierarchy in real systems, for instance, in the pyramid of production entities of the film industry. More importantly, we show how real complex networks can be interpreted as a projection of our model, from which their scale independence, their clustering, their hierarchy, their fractality, and their navigability naturally emerge. Our results suggest that complex networks, viewed as growing systems, can be quite simple, and that the apparent complexity of their structure is largely a reflection of their unobserved hierarchical nature.

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

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...... components also forming labyrinthine domains whose geometry and topology changes systematically as a function of composition. These smaller labyrinths are well described by a family of patterns that tile the hyperbolic plane by regular degree-three trees mapped onto the gyroid. The labyrinths within......-ridden achiral patterns, containing domains of either hand, due to the achiral terpolymeric starting molecules. These mesostructures are among the most topologically complex morphologies identified to date and represent an example of hierarchical ordering within a hyperbolic pattern, a unique mode of soft...

Mitigating Herding in Hierarchical Crowdsourcing Networks.

Science.gov (United States)

Yu, Han; Miao, Chunyan; Leung, Cyril; Chen, Yiqiang; Fauvel, Simon; Lesser, Victor R; Yang, Qiang

2016-12-05

Hierarchical crowdsourcing networks (HCNs) provide a useful mechanism for social mobilization. However, spontaneous evolution of the complex resource allocation dynamics can lead to undesirable herding behaviours in which a small group of reputable workers are overloaded while leaving other workers idle. Existing herding control mechanisms designed for typical crowdsourcing systems are not effective in HCNs. In order to bridge this gap, we investigate the herding dynamics in HCNs and propose a Lyapunov optimization based decision support approach - the Reputation-aware Task Sub-delegation approach with dynamic worker effort Pricing (RTS-P) - with objective functions aiming to achieve superlinear time-averaged collective productivity in an HCN. By considering the workers' current reputation, workload, eagerness to work, and trust relationships, RTS-P provides a systematic approach to mitigate herding by helping workers make joint decisions on task sub-delegation, task acceptance, and effort pricing in a distributed manner. It is an individual-level decision support approach which results in the emergence of productive and robust collective patterns in HCNs. High resolution simulations demonstrate that RTS-P mitigates herding more effectively than state-of-the-art approaches.

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

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.

Expert hierarchical selection of oil and gas distribution systems

International Nuclear Information System (INIS)

Frankel, E.G.

1991-01-01

Selection and design of oil and gas distribution systems involves a large number of decision makers and interest groups, as well as many alternative technical, financial, network, operating, management and regulatory options. Their objectives and measures of performance are different. Decision models can be effectively represented by hierarchical structures. A simple deterministic analytic hierarchy process is presented with application to oil and gas distribution systems

Autonomous distributed self-organization for mobile wireless sensor networks.

Science.gov (United States)

Wen, Chih-Yu; Tang, Hung-Kai

2009-01-01

This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

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.

Improving network management with Software Defined Networking

International Nuclear Information System (INIS)

Dzhunev, Pavel

2013-01-01

Software-defined networking (SDN) is developed as an alternative to closed networks in centers for data processing by providing a means to separate the control layer data layer switches, and routers. SDN introduces new possibilities for network management and configuration methods. In this article, we identify problems with the current state-of-the-art network configuration and management mechanisms and introduce mechanisms to improve various aspects of network management

Filling the gap between disaster preparedness and response networks of urban emergency management: Following the 2013 Seoul Floods.

Science.gov (United States)

Song, Minsun; Jung, Kyujin

2015-01-01

To examine the gap between disaster preparedness and response networks following the 2013 Seoul Floods in which the rapid transmission of disaster information and resources was impeded by severe changes of interorganizational collaboration networks. This research uses the 2013 Seoul Emergency Management Survey data that were collected before and after the floods, and total 94 organizations involving in coping with the floods were analyzed in bootstrap independent-sample t-test and social network analysis through UCINET 6 and STATA 12. The findings show that despite the primary network form that is more hierarchical, horizontal collaboration has been relatively invigorated in actual response. Also, interorganizational collaboration networks for response operations seem to be more flexible grounded on improvisation to coping with unexpected victims and damages. Local organizations under urban emergency management are recommended to tightly build a strong commitment for joint response operations through full-size exercises at the metropolitan level before a catastrophic event. Also, interorganizational emergency management networks need to be restructured by reflecting the actual response networks to reduce collaboration risk during a disaster. This research presents a critical insight into inverse thinking of the view designing urban emergency management networks and provides original evidences for filling the gap between previously coordinated networks for disaster preparedness and practical response operations after a disaster.

N-Doped carbon spheres with hierarchical micropore-nanosheet networks for high performance supercapacitors.

Science.gov (United States)

Wang, Shoupei; Zhang, Jianan; Shang, Pei; Li, Yuanyuan; Chen, Zhimin; Xu, Qun

2014-10-18

N-doped carbon spheres with hierarchical micropore-nanosheet networks (HPSCSs) were facilely fabricated by a one-step carbonization and activation process of N containing polymer spheres by KOH. With the synergy effect of the multiple structures, HPSCSs exhibit a very high specific capacitance of 407.9 F g(-1) at 1 mV s(-1) (1.2 times higher than that of porous carbon spheres) and a robust cycling stability for supercapacitors.

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

OpenAIRE

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

2011-01-01

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 initia...

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.

Autonomous Distributed Self-Organization for Mobile Wireless Sensor Networks

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Chih-Yu Wen

2009-11-01

Full Text Available This paper presents an adaptive combined-metrics-based clustering scheme for mobile wireless sensor networks, which manages the mobile sensors by utilizing the hierarchical network structure and allocates network resources efficiently. A local criteria is used to help mobile sensors form a new cluster or join a current cluster. The messages transmitted during hierarchical clustering are applied to choose distributed gateways such that communication for adjacent clusters and distributed topology control can be achieved. In order to balance the load among clusters and govern the topology change, a cluster reformation scheme using localized criterions is implemented. The proposed scheme is simulated and analyzed to abstract the network behaviors in a number of settings. The experimental results show that the proposed algorithm provides efficient network topology management and achieves high scalability in mobile sensor networks.

The use of hierarchical clustering for the design of optimized monitoring networks

Science.gov (United States)

Soares, Joana; Makar, Paul Andrew; Aklilu, Yayne; Akingunola, Ayodeji

2018-05-01

Associativity analysis is a powerful tool to deal with large-scale datasets by clustering the data on the basis of (dis)similarity and can be used to assess the efficacy and design of air quality monitoring networks. We describe here our use of Kolmogorov-Zurbenko filtering and hierarchical clustering of NO2 and SO2 passive and continuous monitoring data to analyse and optimize air quality networks for these species in the province of Alberta, Canada. The methodology applied in this study assesses dissimilarity between monitoring station time series based on two metrics: 1 - R, R being the Pearson correlation coefficient, and the Euclidean distance; we find that both should be used in evaluating monitoring site similarity. We have combined the analytic power of hierarchical clustering with the spatial information provided by deterministic air quality model results, using the gridded time series of model output as potential station locations, as a proxy for assessing monitoring network design and for network optimization. We demonstrate that clustering results depend on the air contaminant analysed, reflecting the difference in the respective emission sources of SO2 and NO2 in the region under study. Our work shows that much of the signal identifying the sources of NO2 and SO2 emissions resides in shorter timescales (hourly to daily) due to short-term variation of concentrations and that longer-term averages in data collection may lose the information needed to identify local sources. However, the methodology identifies stations mainly influenced by seasonality, if larger timescales (weekly to monthly) are considered. We have performed the first dissimilarity analysis based on gridded air quality model output and have shown that the methodology is capable of generating maps of subregions within which a single station will represent the entire subregion, to a given level of dissimilarity. We have also shown that our approach is capable of identifying different

Security management based on trust determination in cognitive radio networks

Science.gov (United States)

Li, Jianwu; Feng, Zebing; Wei, Zhiqing; Feng, Zhiyong; Zhang, Ping

2014-12-01

Security has played a major role in cognitive radio networks. Numerous researches have mainly focused on attacking detection based on source localization and detection probability. However, few of them took the penalty of attackers into consideration and neglected how to implement effective punitive measures against attackers. To address this issue, this article proposes a novel penalty mechanism based on cognitive trust value. The main feature of this mechanism has been realized by six functions: authentication, interactive, configuration, trust value collection, storage and update, and punishment. Data fusion center (FC) and cluster heads (CHs) have been put forward as a hierarchical architecture to manage trust value of cognitive users. Misbehaving users would be punished by FC by declining their trust value; thus, guaranteeing network security via distinguishing attack users is of great necessity. Simulation results verify the rationality and effectiveness of our proposed mechanism.

Leading processes of patient care and treatment in hierarchical healthcare organizations in Sweden--process managers' experiences.

Science.gov (United States)

Nilsson, Kerstin; Sandoff, Mette

2015-01-01

The purpose of this study is to gain better understanding of the roles and functions of process managers by describing Swedish process managers' experiences of leading processes involving patient care and treatment when working in a hierarchical health-care organization. This study is based on an explorative design. The data were gathered from interviews with 12 process managers at three Swedish hospitals. These data underwent qualitative and interpretative analysis with a modified editing style. The process managers' experiences of leading processes in a hierarchical health-care organization are described under three themes: having or not having a mandate, exposure to conflict situations and leading process development. The results indicate a need for clarity regarding process manager's responsibility and work content, which need to be communicated to all managers and staff involved in the patient care and treatment process, irrespective of department. There also needs to be an emphasis on realistic expectations and orientation of the goals that are an intrinsic part of the task of being a process manager. Generalizations from the results of the qualitative interview studies are limited, but a deeper understanding of the phenomenon was reached, which, in turn, can be transferred to similar settings. This study contributes qualitative descriptions of leading care and treatment processes in a functional, hierarchical health-care organization from process managers' experiences, a subject that has not been investigated earlier.

Functional annotation of hierarchical modularity.

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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

Attachment and social networks.

Science.gov (United States)

Gillath, Omri; C Karantzas, Gery; Lee, Juwon

2018-02-21

The current review covers two lines of research linking attachment and social networks. One focuses on attachment networks (the people who fulfill one's attachment needs), examining composition and age-related differences pertaining to these networks. The other line integrates attachment with social network analysis to investigate how individual differences in adult attachment are associated with the management and characteristics (e.g., density, multiplexity, and centrality) of people's social networks. We show that most people's attachment networks are small and hierarchical, with one figure being the primary attachment figure (often a mother or romantic partner, depending on age). Furthermore, attachment style predicts network characteristics and management, such that insecurity is associated with less closeness, multiplexity, centrality, and poorer management (less maintenance, more dissolution). Copyright © 2018 Elsevier Ltd. All rights reserved.

SDN‐Based Hierarchical Agglomerative Clustering Algorithm for Interference Mitigation in Ultra‐Dense Small Cell Networks

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Guang Yang

2018-04-01

Full Text Available Ultra‐dense small cell networks (UD‐SCNs have been identified as a promising scheme for next‐generation wireless networks capable of meeting the ever‐increasing demand for higher transmission rates and better quality of service. However, UD‐SCNs will inevitably suffer from severe interference among the small cell base stations, which will lower their spectral efficiency. In this paper, we propose a software‐defined networking (SDN‐based hierarchical agglomerative clustering (SDN‐HAC framework, which leverages SDN to centrally control all sub‐channels in the network, and decides on cluster merging using a similarity criterion based on a suitability function. We evaluate the proposed algorithm through simulation. The obtained results show that the proposed algorithm performs well and improves system payoff by 18.19% and 436.34% when compared with the traditional network architecture algorithms and non‐cooperative scenarios, respectively.

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.

Networked inventory management systems: materializing supply chain management

NARCIS (Netherlands)

Verwijmeren, M.A.A.P.; Vlist, van der P.; Donselaar, van K.H.

1996-01-01

Aims to explain the driving forces for networked inventory management. Discusses major developments with respect to customer requirements, networked organizations and networked inventory management. Presents high level specifications of networked inventory management information systems (NIMISs).

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

A Persistent Structured Hierarchical Overlay Network to Counter Intentional Churn Attack

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Ramanpreet Kaur

2016-01-01

Full Text Available The increased use of structured overlay network for a variety of applications has attracted a lot of attention from both research community and attackers. However, the structural constraints, open nature (anybody can join and anybody may leave, and unreliability of its participant nodes significantly affect the performance of these applications and make it vulnerable to a variety of attacks such as eclipse, Sybil, and churn. One attack to compromise the service availability in overlay network is intentional churn (join/leave attack, where a large number of malicious users will join and leave the overlay network so frequently that the entire structure collapses and becomes unavailable. The focus of this paper is to provide a new robust, efficient, and scalable hierarchical overlay architecture that will counter these attacks by providing a structure that can accommodate the fleeting behaviour of nodes without causing much structural inconsistencies. The performance evaluation showed that the proposed architecture has more failure resilience and self-organization as compared to chord based architecture. Experimental results have demonstrated that the effect of failures on an overlay is proportional to the size of failure.

A Hierarchical Poisson Log-Normal Model for Network Inference from RNA Sequencing Data

Science.gov (United States)

Gallopin, Mélina; Rau, Andrea; Jaffrézic, Florence

2013-01-01

Gene network inference from transcriptomic data is an important methodological challenge and a key aspect of systems biology. Although several methods have been proposed to infer networks from microarray data, there is a need for inference methods able to model RNA-seq data, which are count-based and highly variable. In this work we propose a hierarchical Poisson log-normal model with a Lasso penalty to infer gene networks from RNA-seq data; this model has the advantage of directly modelling discrete data and accounting for inter-sample variance larger than the sample mean. Using real microRNA-seq data from breast cancer tumors and simulations, we compare this method to a regularized Gaussian graphical model on log-transformed data, and a Poisson log-linear graphical model with a Lasso penalty on power-transformed data. For data simulated with large inter-sample dispersion, the proposed model performs better than the other methods in terms of sensitivity, specificity and area under the ROC curve. These results show the necessity of methods specifically designed for gene network inference from RNA-seq data. PMID:24147011

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.

Diagnostics for generalized linear hierarchical models in network meta-analysis.

Science.gov (United States)

Zhao, Hong; Hodges, James S; Carlin, Bradley P

2017-09-01

Network meta-analysis (NMA) combines direct and indirect evidence comparing more than 2 treatments. Inconsistency arises when these 2 information sources differ. Previous work focuses on inconsistency detection, but little has been done on how to proceed after identifying inconsistency. The key issue is whether inconsistency changes an NMA's substantive conclusions. In this paper, we examine such discrepancies from a diagnostic point of view. Our methods seek to detect influential and outlying observations in NMA at a trial-by-arm level. These observations may have a large effect on the parameter estimates in NMA, or they may deviate markedly from other observations. We develop formal diagnostics for a Bayesian hierarchical model to check the effect of deleting any observation. Diagnostics are specified for generalized linear hierarchical NMA models and investigated for both published and simulated datasets. Results from our example dataset using either contrast- or arm-based models and from the simulated datasets indicate that the sources of inconsistency in NMA tend not to be influential, though results from the example dataset suggest that they are likely to be outliers. This mimics a familiar result from linear model theory, in which outliers with low leverage are not influential. Future extensions include incorporating baseline covariates and individual-level patient data. Copyright © 2017 John Wiley & Sons, Ltd.

Hierarchical Data Distribution Scheme for Peer-to-Peer Networks

Science.gov (United States)

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

2010-11-01

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

Hierarchical Recurrent Neural Hashing for Image Retrieval With Hierarchical Convolutional Features.

Science.gov (United States)

Lu, Xiaoqiang; Chen, Yaxiong; Li, Xuelong

Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep learning architectures can learn more effective image representation features. However, these methods only use semantic features to generate hash codes by shallow projection but ignore texture details. In this paper, we proposed a novel hashing method, namely hierarchical recurrent neural hashing (HRNH), to exploit hierarchical recurrent neural network to generate effective hash codes. There are three contributions of this paper. First, a deep hashing method is proposed to extensively exploit both spatial details and semantic information, in which, we leverage hierarchical convolutional features to construct image pyramid representation. Second, our proposed deep network can exploit directly convolutional feature maps as input to preserve the spatial structure of convolutional feature maps. Finally, we propose a new loss function that considers the quantization error of binarizing the continuous embeddings into the discrete binary codes, and simultaneously maintains the semantic similarity and balanceable property of hash codes. Experimental results on four widely used data sets demonstrate that the proposed HRNH can achieve superior performance over other state-of-the-art hashing methods.Hashing has been an important and effective technology in image retrieval due to its computational efficiency and fast search speed. The traditional hashing methods usually learn hash functions to obtain binary codes by exploiting hand-crafted features, which cannot optimally represent the information of the sample. Recently, deep learning methods can achieve better performance, since deep

Optimal Parameter for the Training of Multilayer Perceptron Neural Networks by Using Hierarchical Genetic Algorithm

International Nuclear Information System (INIS)

Orozco-Monteagudo, Maykel; Taboada-Crispi, Alberto; Gutierrez-Hernandez, Liliana

2008-01-01

This paper deals with the controversial topic of the selection of the parameters of a genetic algorithm, in this case hierarchical, used for training of multilayer perceptron neural networks for the binary classification. The parameters to select are the crossover and mutation probabilities of the control and parametric genes and the permanency percent. The results can be considered as a guide for using this kind of algorithm.

Impact of hierarchical modular structure on ranking of individual nodes in directed networks

Energy Technology Data Exchange (ETDEWEB)

Masuda, Naoki [Graduate School of Information Science and Technology, University of Tokyo, 7-3-1 Hongo, Bunkyo, Tokyo 113-8656 (Japan); Kawamura, Yoji [Institute for Research on Earth Evolution, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showa-machi, Kanazawa-ku, Yokohama, Kanagawa 236-0001 (Japan); Kori, Hiroshi [PRESTO, Japan Science and Technology Agency, 4-1-8 Honcho, Kawaguchi, Saitama 332-0012 (Japan)], E-mail: masuda@mist.i.u-tokyo.ac.jp

2009-11-15

Many systems, ranging from biological and engineering systems to social systems, can be modeled as directed networks, with links representing directed interaction between two nodes. To assess the importance of a node in a directed network, various centrality measures based on different criteria have been proposed. However, calculating the centrality of a node is often difficult because of the overwhelming size of the network or because the information held about the network is incomplete. Thus, developing an approximation method for estimating centrality measures is needed. In this study, we focus on modular networks; many real-world networks are composed of modules, where connection is dense within a module and sparse across different modules. We show that ranking-type centrality measures, including the PageRank, can be efficiently estimated once the modular structure of a network is extracted. We develop an analytical method to evaluate the centrality of nodes by combining the local property (i.e. indegree and outdegree of nodes) and the global property (i.e. centrality of modules). The proposed method is corroborated by real data. Our results provide a linkage between the ranking-type centrality values of modules and those of individual nodes. They also reveal the hierarchical structure of networks in the sense of subordination (not nestedness) laid out by connectivity among modules of different relative importance. The present study raises a novel motive for identifying modules in networks.

Impact of hierarchical modular structure on ranking of individual nodes in directed networks

International Nuclear Information System (INIS)

Masuda, Naoki; Kawamura, Yoji; Kori, Hiroshi

2009-01-01

Many systems, ranging from biological and engineering systems to social systems, can be modeled as directed networks, with links representing directed interaction between two nodes. To assess the importance of a node in a directed network, various centrality measures based on different criteria have been proposed. However, calculating the centrality of a node is often difficult because of the overwhelming size of the network or because the information held about the network is incomplete. Thus, developing an approximation method for estimating centrality measures is needed. In this study, we focus on modular networks; many real-world networks are composed of modules, where connection is dense within a module and sparse across different modules. We show that ranking-type centrality measures, including the PageRank, can be efficiently estimated once the modular structure of a network is extracted. We develop an analytical method to evaluate the centrality of nodes by combining the local property (i.e. indegree and outdegree of nodes) and the global property (i.e. centrality of modules). The proposed method is corroborated by real data. Our results provide a linkage between the ranking-type centrality values of modules and those of individual nodes. They also reveal the hierarchical structure of networks in the sense of subordination (not nestedness) laid out by connectivity among modules of different relative importance. The present study raises a novel motive for identifying modules in networks.

Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks

Energy Technology Data Exchange (ETDEWEB)

Gearhart, Jared Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kurtz, Nolan Scot [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2014-09-01

The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance are investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.

Study on the correlation between the hierarchical urban system and high-speed railway network planning in China

Directory of Open Access Journals (Sweden)

Hong Sun

2016-09-01

Full Text Available This study examines the interrelatedness between the hierarchical structure of China׳s urban system and high-speed railway (HSR network planning at the national level. As a multi-layered system, the Chinese HSR can be categorized into three sub-networks, namely, the national HSR trunk network, the national HSR extensional network, and the intercity HSR network. By examining the direct HSR network connection, HSR nodal connection, and HSR operational frequency of 287 prefecture-level cities, this study demonstrates that the hierarchies of China׳s administrative, demographic, and economic urban systems strongly influence HSR network planning. The national HSR trunk network prioritizes the connection of top-level central cities, whereas the extensional network prioritizes cities at the lower level of the urban system. Moreover, the national HSR system forms the backbone of the HSR network structure based on a national scale, whereas the intercity HSR system satisfies the travel needs within urban agglomerations based on the regional level.

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

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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.

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

Directory of Open Access Journals (Sweden)

Cristina Comaniciu

2007-03-01

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.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Science.gov (United States)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

Directory of Open Access Journals (Sweden)

Aichun Zhu

2018-03-01

Full Text Available This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN. Firstly, a Relative Mixture Deformable Model (RMDM is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Managing Networks

DEFF Research Database (Denmark)

Jørgensen, Heidi; Vintergaard, Christian

Logically it seems that companies pursuing different business strategies wouldalso manage their relationships with other firms accordingly. Nevertheless, due tothe lack of research in the field of network strategies, this link still remainsinadequately examined. Based on the well-known framework...... isprovided, that the relation between a company's strategy, structure and processesin fact have a considerable influence on its pattern of network behaviour. Threecase studies from the Danish biotech industry exemplify and illustrate how acompany's strategy is directly correlated with how it manages its...... of networkbehaviour, knowing how to manage this relation becomes essential, especiallyduring the development of new strategies....

Hierarchical level oF managers’ abilities: A Moderator between Quality Management Practices and Company Financial Performance

Directory of Open Access Journals (Sweden)

Wakhid Slamet Ciptono

2007-09-01

Full Text Available This study investigates the moderating impacts of hierarchical level of managers’ abilities on the form and strength of all structural relationships between quality management practices and company financial performance. This study describes the structural relationships among the research constructs —six critical factors of quality management practices (quality improvement program, supervisory leadership, supplier involvement, management commitment, training to improve products/services, cross-functional relationships; the contextual factors of oil and gas companies—world-class performance in operations (world-class company practices, operational excellence practices, company non-financial performance; and company financial performance. It uses a sample of 1,332 managers in 140 strategic business units (SBUs within 49 oil and gas companies operating in Indonesia. The empirical results indicate that the goodness-of-fit of the unconstrained model is much better than that of the constrained model, and this is an indicator that hierarchical level of managers’ abilities moderates all structural relationships among the research constructs. Hence, the hierarchical level of managers’ abilities acts as a moderating variable of the whole model (i.e., among critical factors of quality management practices, world-class company practices, operational excellence practices, company non-financial performance, and company financial performance. It means that the major contribution of the hierarchical level of managers’ abilities is how to make changes in the organizational system. Top level managers’ abilities are deemed the most capable of making significant changes because of their broad sources of power and influence. Conversely, lower level managers’ abilities find it more difficult making significant changes in the system because of bureaucratic control processes that limit their actions —powerlessness or a chronic lack of autonomy

Managing ANSA Objects with OSI Network Management Tools

OpenAIRE

Polizzi, Marc; Genilloud, Guy

1995-01-01

OSI Network Management provides a general framework for the management of OSI systems, and by extension of any distributed system. However, as this model is not well-adapted for the management of software components, distributed programming environments (e.g. DCE, CORBA, ANSAware) essentially ignore the OSI Network Management model. We assume nevertheless that OSI Network managers will want to have some control of a distributed infrastructure and application. We examine how access to some of ...

The SIS Model of Epidemic Spreading in a Hierarchical Social Network

International Nuclear Information System (INIS)

Grabowski, A.; Kosinski, R.A.

2005-01-01

The phenomenon of epidemic spreading in a population with a hierarchical structure of interpersonal interactions is described and investigated numerically. The SIS model with temporal immunity to a disease and a time of incubation is used. In our model spatial localization of individuals belonging to different social groups, effectiveness of different interpersonal interactions and the mobility of a contemporary community are taken into account. The structure of interpersonal connections is based on a scale-free network. The influence of the structure of the social network on typical relations characterizing the spreading process, like a range of epidemic and epidemic curves, is discussed. The probability that endemic state occurs is also calculated. Surprisingly it occurs, that less contagious diseases has greater chance to survive. The influence of preventive vaccinations on the spreading process is investigated and critical range of vaccinations that is sufficient for the suppression of an epidemic is calculated. Our results of numerical calculations are compared with the solutions of the master equation for the spreading process, and good agreement is found. (author)

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. PMID:22368464

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.

Hierarchical Leak Detection and Localization Method in Natural Gas Pipeline Monitoring Sensor Networks

Directory of Open Access Journals (Sweden)

Ning Yu

2011-12-01

Full Text Available 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.

Challenges of growth in a network company

OpenAIRE

Axani, Darrell Kirk

2006-01-01

Mark Engineering is a large network company facing challenges between growth and its small company feel. Small networks are rewarding for both individuals and companies. With growth, networks become cumbersome and costly to operate. Like effective teams, networks must remain small to be efficient. Growth tends to drive management to more traditional hierarchical structures, but such a move would undermine the value of a network organization. Strategy and market forces influence organizational...

Hierarchical Data Replication and Service Monitoring Methods in a Scientific Data Grid

Directory of Open Access Journals (Sweden)

Weizhong Lu

2009-04-01

Full Text Available In a grid and distributed computing environment, data replication is an effective way to improve data accessibility and data accessing efficiency. It is also significant in developing a real-time service monitoring system for a Chinese Scientific Data Grid to guarantee the system stability and data availability. Hierarchical data replication and service monitoring methods are proposed in this paper. The hierarchical data replication method divides the network into different domains and replicates data in local domains. The nodes in a local domain are classified into hierarchies to improve data accessibility according to bandwidth and storage memory space. An extensible agent-based prototype of a hierarchical service monitoring system is presented. The status information of services in the Chinese Scientific Data Grid is collected from the grid nodes based on agent technology and then is transformed into real-time operational pictures for management needs. This paper presents frameworks of the hierarchical data replication and service monitoring methods and gives detailed resolutions. Simulation analyses have demonstrated improved data accessing efficiency and verified the effectiveness of the methods at the same time.

Network management in motion. Part 1. Network management in perspective. Transition or paradox?

International Nuclear Information System (INIS)

Van Beuge, M.

2010-01-01

In a series of articles various legal aspects of network management are discussed from a European and a Dutch perspective. In this first part a general introduction is given on network management and related topics, such as developing local networks to international networks, the integration to unbundling the energy market in Europe, the development of centralized to decentralized, and from conventional to sustainable. [nl

An Architectural Modelfor Intelligent Network Management

Institute of Scientific and Technical Information of China (English)

罗军舟; 顾冠群; 费翔

2000-01-01

Traditional network management approach involves the management of each vendor's equipment and network segment in isolation through its own proprietary element management system. It is necessary to set up a new network management architecture that calls for operation consolidation across vendor and technology boundaries. In this paper, an architectural model for Intelligent Network Management (INM) is presented. The INM system includes a manager system, which controls all subsystems and coordinates different management tasks; an expert system, which is responsible for handling particularly difficult problems, and intelligent agents, which bring the management closer to applications and user requirements by spreading intelligent agents through network segments or domain. In the expert system model proposed, especially an intelligent fault management system is given.The architectural model is to build the INM system to meet the need of managing modern network systems.

Managing IT infrastructure standardisation in the networked manufacturing firm

NARCIS (Netherlands)

Akkermans, H.A.; Horst, van der H.

2002-01-01

This paper discusses managerial aspects of information technology (IT) infrastructure standardisation in networked manufacturing firms. It shows that in these firms, where local initiative is very important and strict central hierarchical control is lacking, standardisation of IT infrastructure is

Cable networks, services, and management

CERN Document Server

2015-01-01

Cable Networks, Services, and Management is the first book to cover cable networks, services, and their management, in-depth, for network operators, engineers, researchers, and students. Thirteen experts in various fields have contributed their knowledge of network architectures and services, Operations, Administration, Maintenance, Provisioning, Troubleshooting (OAMPT) for residential and business services, cloud, Software Defined Networks (SDN), as well as virtualization concepts and their applications as part of the future directions of cable networks. The book begins by introducing architecture and services for Data Over Cable Service Interface Specification (DOCSIS) 3.0/ 3.1, Converged Cable Access Platform (CCAP), Content Distribution Networks (CDN, IP TV, and Packet Cable and Wi-Fi for Residential Services. Topics that are discussed in proceeding chapters include: operational systems and management architectures, service orders, provisioning, fault manageme t, performance management, billing systems a...

Hierarchical architecture of active knits

International Nuclear Information System (INIS)

Abel, Julianna; Luntz, Jonathan; Brei, Diann

2013-01-01

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. (paper)

Hierarchical level oF managers’ abilities: A Moderator between Quality Management Practices and Company Financial Performance

OpenAIRE

Ciptono, Wakhid Slamet

2007-01-01

This study investigates the moderating impacts of hierarchical level of managers’ abilities on the form and strength of all structural relationships between quality management practices and company financial performance. This study describes the structural relationships among the research constructs —six critical factors of quality management practices (quality improvement program, supervisory leadership, supplier involvement, management commitment, training to improve products/services, cros...

Hierarchical Broadcasting in the Future Mobile Internet

NARCIS (Netherlands)

Hesselman, C.E.W.; Eertink, E.H.; Fernandez, Milagros; Crnkovic, Ivica; Fohler, Gerhard; Griwodz, Carsten; Plagemann, Thomas; Gruenbacher, Paul

2002-01-01

We describe an architecture for the hierarchical distribution of multimedia broadcasts in the future mobile Internet. The architecture supports network as well as application-layer mobility solutions, and uses stream control functions that are influenced by available network resources, user-defined

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.

Security-Enhanced Autonomous Network Management

Science.gov (United States)

Zeng, Hui

2015-01-01

Ensuring reliable communication in next-generation space networks requires a novel network management system to support greater levels of autonomy and greater awareness of the environment and assets. Intelligent Automation, Inc., has developed a security-enhanced autonomous network management (SEANM) approach for space networks through cross-layer negotiation and network monitoring, analysis, and adaptation. The underlying technology is bundle-based delay/disruption-tolerant networking (DTN). The SEANM scheme allows a system to adaptively reconfigure its network elements based on awareness of network conditions, policies, and mission requirements. Although SEANM is generically applicable to any radio network, for validation purposes it has been prototyped and evaluated on two specific networks: a commercial off-the-shelf hardware test-bed using Institute of Electrical Engineers (IEEE) 802.11 Wi-Fi devices and a military hardware test-bed using AN/PRC-154 Rifleman Radio platforms. Testing has demonstrated that SEANM provides autonomous network management resulting in reliable communications in delay/disruptive-prone environments.

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.

Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks

Energy Technology Data Exchange (ETDEWEB)

Deng, De-Ming; Chang, Cheng-Hung [Institute of Physics, National Chiao Tung University, Hsinchu 300, Taiwan (China)

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

Stochastic lumping analysis for linear kinetics and its application to the fluctuation relations between hierarchical kinetic networks.

Science.gov (United States)

Deng, De-Ming; Chang, Cheng-Hung

2015-05-14

Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.

Cellular Decomposition Based Hybrid-Hierarchical Control Systems with Applications to Flight Management Systems

Science.gov (United States)

Caines, P. E.

1999-01-01

The work in this research project has been focused on the construction of a hierarchical hybrid control theory which is applicable to flight management systems. The motivation and underlying philosophical position for this work has been that the scale, inherent complexity and the large number of agents (aircraft) involved in an air traffic system imply that a hierarchical modelling and control methodology is required for its management and real time control. In the current work the complex discrete or continuous state space of a system with a small number of agents is aggregated in such a way that discrete (finite state machine or supervisory automaton) controlled dynamics are abstracted from the system's behaviour. High level control may then be either directly applied at this abstracted level, or, if this is in itself of significant complexity, further layers of abstractions may be created to produce a system with an acceptable degree of complexity at each level. By the nature of this construction, high level commands are necessarily realizable at lower levels in the system.

Energy Management Systems and tertiary regulation in hierarchical control architectures for islanded micro-grids

DEFF Research Database (Denmark)

Sanseverino, Eleonora Riva; Di Silvestre, Maria Luisa; Quang, Ninh Nguyen

2015-01-01

In this paper, the structure of the highest level of a hierarchical control architecture for micro-grids is proposed. Such structure includes two sub-levels: the Energy Management System, EMS, and the tertiary regulation. The first devoted to energy resources allocation in each time slot based...

Dynamic clustering scheme based on the coordination of management and control in multi-layer and multi-region intelligent optical network

Science.gov (United States)

Niu, Xiaoliang; Yuan, Fen; Huang, Shanguo; Guo, Bingli; Gu, Wanyi

2011-12-01

A Dynamic clustering scheme based on coordination of management and control is proposed to reduce network congestion rate and improve the blocking performance of hierarchical routing in Multi-layer and Multi-region intelligent optical network. Its implement relies on mobile agent (MA) technology, which has the advantages of efficiency, flexibility, functional and scalability. The paper's major contribution is to adjust dynamically domain when the performance of working network isn't in ideal status. And the incorporation of centralized NMS and distributed MA control technology migrate computing process to control plane node which releases the burden of NMS and improves process efficiently. Experiments are conducted on Multi-layer and multi-region Simulation Platform for Optical Network (MSPON) to assess the performance of the scheme.

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.

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

KAUST Repository

Ringk, Andreas; Lignie, Adrien; Hou, Yuanfang; Alshareef, Husam N.; Beaujuge, Pierre

2016-01-01

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.

A unified plant information network

International Nuclear Information System (INIS)

Niederauer, G.F.

1986-01-01

Technology is bringing power plants fully into the age of computerization. Microcomputers, data base managers, networking, and friendly, expert software are principal technology factors. Monitoring will improve, and the number and power of computers is increasing. The huge information flow will cause computers to be integrated into a communication network. The total plant operating triangle includes process, engineering, and management systems. The total network will integrate all of these into a Total Unified Plant Information Network (TUPIN). Software will take the type of information beyond monitored data. Analysis will improve through direct access to logical, physical, and procedural models by end users. Information management will improve through widespread use of hierarchical, relational, and expert data base managers. Expert systems will aid in diagnostics and interpretation. The goal is to automate plant operations to enhance safety and performance and to reduce cost by making both the plants and the personnel more expert

Managing Cisco network security

CERN Document Server

Knipp, Eric

2002-01-01

An in-depth knowledge of how to configure Cisco IP network security is a MUST for anyone working in today''s internetworked world"There''s no question that attacks on enterprise networks are increasing in frequency and sophistication..."-Mike Fuhrman, Cisco Systems Manager, Security ConsultingManaging Cisco Network Security, Second Edition offers updated and revised information covering many of Cisco''s security products that provide protection from threats, detection of network security incidents, measurement of vulnerability and policy compliance and management of security policy across an extended organization. These are the tools that network administrators have to mount defenses against threats. Chapters also cover the improved functionality and ease of the Cisco Secure Policy Manger software used by thousands of small-to-midsized businesses and a special section on the Cisco Aironet Wireless Security Solutions.Security from a real-world perspectiveKey coverage of the new technologies offered by the Cisc...

Managing collaborative innovation networks

DEFF Research Database (Denmark)

Stevens, Vidar; Agger, Annika

2017-01-01

Collaborative innovation networks are increasingly used as vehicles for fostering innovative policy solutions. However, scholars have noted that the extent to which collaborative networks can actually contribute to the development of innovative policy solutions depends on how they are managed...... a Flemish administrative network to develop a radical new Spatial Planning Policy Plan. This study shows that the best way to manage collaborative innovation networks is not to press directly for results, but take the time to invest in relationship-building and together agree on a planning and clear process...... steps. Such a management approach allows actors to get to know each other and from thereon expand, with more background and appreciation for the others’ goals, behaviors, and intentions, their group activities concerning the formulation of a radical and innovative policy plan....

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

Temporal Databases in Network Management

National Research Council Canada - National Science Library

Gupta, Ajay

1998-01-01

.... This thesis discusses issues involved with performing network management, specifically with means of reducing and storing the large quantity of data that networks management tools and systems generate...

Transparent conducting films of hierarchically nanostructured polyaniline networks on flexible substrates for high-performance gas sensors.

Science.gov (United States)

Bai, Shouli; Sun, Chaozheng; Wan, Pengbo; Wang, Cheng; Luo, Ruixian; Li, Yaping; Liu, Junfeng; Sun, Xiaoming

2015-01-21

Transparent chemical gas sensors are assembled from a transparent conducting film of hierarchically nanostructured polyaniline (PANI) networks fabricated on a flexible PET substrate, by coating silver nanowires (Ag NWs) followed by the in situ polymerization of aniline near the sacrificial Ag NW template. The sensor exhibits enhanced gas sensing performance at room temperature in both sensitivity and selectivity to NH3 compared to pure PANI film. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hierarchical self-organization of non-cooperating individuals.

Directory of Open Access Journals (Sweden)

Tamás Nepusz

Full Text Available 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 hierarchical self-organization and the specific structures we obtain possess the two, perhaps most important features of complex systems: a simultaneous presence of adaptability and stability. In addition, the performance (success score of the emerging networks is significantly higher than the average expected score of the individuals without letting them copy the decisions of the others. The results of our calculations are in agreement with a related experiment and can be useful from the point of designing the optimal conditions for constructing a given complex social structure as well as understanding the hierarchical organization of such biological structures of major importance as the regulatory pathways or the dynamics of neural networks.

Hierarchical Planning Methodology for a Supply Chain Management

Directory of Open Access Journals (Sweden)

Virna ORTIZ-ARAYA

2012-01-01

Full Text Available Hierarchical production planning is a widely utilized methodology for real world capacitated production planning systems with the aim of establishing different decision–making levels of the planning issues on the time horizon considered. This paper presents a hierarchical approach proposed to a company that produces reusable shopping bags in Chile and Perú, to determine the optimal allocation of resources at the tactical level as well as over the most immediate planning horizon to meet customer demands for the next weeks. Starting from an aggregated production planning model, the aggregated decisions are disaggregated into refined decisions in two levels, using a couple of optimization models that impose appropriate constraints to keep coherence of the plan on the production system. The main features of the hierarchical solution approach are presented.

A Very Large Area Network (VLAN) knowledge-base applied to space communication problems

Science.gov (United States)

Zander, Carol S.

1988-01-01

This paper first describes a hierarchical model for very large area networks (VLAN). Space communication problems whose solution could profit by the model are discussed and then an enhanced version of this model incorporating the knowledge needed for the missile detection-destruction problem is presented. A satellite network or VLAN is a network which includes at least one satellite. Due to the complexity, a compromise between fully centralized and fully distributed network management has been adopted. Network nodes are assigned to a physically localized group, called a partition. Partitions consist of groups of cell nodes with one cell node acting as the organizer or master, called the Group Master (GM). Coordinating the group masters is a Partition Master (PM). Knowledge is also distributed hierarchically existing in at least two nodes. Each satellite node has a back-up earth node. Knowledge must be distributed in such a way so as to minimize information loss when a node fails. Thus the model is hierarchical both physically and informationally.

Hierarchical anatomical brain networks for MCI prediction: revisiting volumetric measures.

Directory of Open Access Journals (Sweden)

Luping Zhou

results. Without requiring new sources of information, our proposed approach improves the accuracy of MCI prediction from 80.83% (of conventional volumetric features to 84.35% (of hierarchical network features, evaluated using data sets randomly drawn from the ADNI (Alzheimer's Disease Neuroimaging Initiative dataset.

ENERGY AWARE NETWORK: BAYESIAN BELIEF NETWORKS BASED DECISION MANAGEMENT SYSTEM

Directory of Open Access Journals (Sweden)

Santosh Kumar Chaudhari

2011-06-01

Full Text Available A Network Management System (NMS plays a very important role in managing an ever-evolving telecommunication network. Generally an NMS monitors & maintains the health of network elements. The growing size of the network warrants extra functionalities from the NMS. An NMS provides all kinds of information about networks which can be used for other purposes apart from monitoring & maintaining networks like improving QoS & saving energy in the network. In this paper, we add another dimension to NMS services, namely, making an NMS energy aware. We propose a Decision Management System (DMS framework which uses a machine learning technique called Bayesian Belief Networks (BBN, to make the NMS energy aware. The DMS is capable of analysing and making control decisions based on network traffic. We factor in the cost of rerouting and power saving per port. Simulations are performed on standard network topologies, namely, ARPANet and IndiaNet. It is found that ~2.5-6.5% power can be saved.

Policy-based Network Management in Home Area Networks: Interim Test Results

OpenAIRE

Ibrahim Rana, Annie; Ó Foghlú, Mícheál

2009-01-01

This paper argues that Home Area Networks (HANs) are a good candidate for advanced network management automation techniques, such as Policy-Based Network Management (PBNM). What is proposed is a simple use of policy based network management to introduce some level of Quality of Service (QoS) and Security management in the HAN, whilst hiding this complexity from the home user. In this paper we have presented the interim test results of our research experiments (based on a scenario) using the H...

Growth strategies and governance of horizontal business networks: the case of the biggest German cooperative food retail network

Directory of Open Access Journals (Sweden)

Douglas Wegner

2011-08-01

Full Text Available Several growth strategies may be adopted by cooperative retail networks, but these strategies create dilemmas about how to organize business networks with a large number of participants and the adjustments in the governance system that are necessary to facilitate growth. The article examines the relations between the growth strategies adopted by a horizontal business network and its governance system. We analyze the case of Edeka, a centennial cooperative network, leader in food retail in Germany, showing its growth strategies and implications for the network structure. The case study was based on various secondary data sources and focuses the whole network – and not the networked firms – as the unit of analysis. Results indicate that, in order to grow, the network changed its governance structure and the process of participation of members in decision making, creating a hierarchical structure with professional management. The paper contributes to the discussions on cooperative governance and demonstrates that governance systems are transient and adapt to the network strategies. From a management viewpoint, the results show the effects of the growth strategies adopted by business networks, regarding the role of network managers and entrepreneurs in network management.

Hierarchical Downlink Resource Management Framework for OFDMA based WiMAX Systems

DEFF Research Database (Denmark)

Wang, Hua; Iversen, Villy Bæk

2008-01-01

IEEE 802.16, known as WiMAX, has received much attention for its capability to support multiple types of applications with diverse QoS requirements. Beyond what the standard has defined, radio resource management (RRM) still remains an open issue. In this paper, we propose a hierarchical downlink...... belonging to different service classes with the objective of increasing the spectral efficiency while satisfying the diverse QoS requirements in each service class. CAC highlights how to limit the number of ongoing connections preventing the system capacity from being overused. Through system...

Knowledge management in international networks

NARCIS (Netherlands)

Man, de A.P.

2006-01-01

Networks and knowledge are intimately connected. Networks are believed to be innovative because of the smooth transfer, combination and creation of knowledge that can take place in them. Interestingly however, knowledge management research has hardly studied knowledge management techniques in

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

Managing the systems approach to training using a flexible Hierarchical data base

International Nuclear Information System (INIS)

Housman, E.; Bush, E.R.

1993-01-01

Task analysis/curriculum design for a nuclear power station results in a massive amount of data, which must be sequenced and ordered to create an effective program design. This is an almost impossible task without the use of computerized data base. Beginning in 1989, San Onofre nuclear generating station (SONGS) undertook a task analysis/program design project to verify the structure and sequence (design) of all accredited training program. A flex hierarchical data-base management system was designed to store and manage the data collected during the project. For the Operations Training Programm alone ∼8000 tasks, 90,000 knowledges and abilities, and 10,000 learning objectives were entered into this data base

Network management, status and directions

International Nuclear Information System (INIS)

Cottrell, R.L.A.; Streater, T.C.

1992-09-01

It has been said that the ''network is the system''. This implies providing levels of service, reliability, predictability and availability that are commensurate with or better than those that individual computers provide today. To provide this requires integrated network management for interconnected networks of heterogeneous devices covering both the local campus and across the world and spanning many administrative domains. This talk will review the status of existing tools to address management for networks. It draws on experience from both within and outside the HEP community

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.

Hierarchical artificial bee colony algorithm for RFID network planning optimization.

Science.gov (United States)

Ma, Lianbo; Chen, Hanning; Hu, Kunyuan; Zhu, Yunlong

2014-01-01

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.

The Network Information Management System (NIMS) in the Deep Space Network

Science.gov (United States)

Wales, K. J.

1983-01-01

In an effort to better manage enormous amounts of administrative, engineering, and management data that is distributed worldwide, a study was conducted which identified the need for a network support system. The Network Information Management System (NIMS) will provide the Deep Space Network with the tools to provide an easily accessible source of valid information to support management activities and provide a more cost-effective method of acquiring, maintaining, and retrieval data.

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

dependencies between the number of nodes and the distances in the structures. The perfect square mesh is introduced for hierarchies, and it is shown that applying ordered hierarchies in this way results in logarithmic dependencies between the number of nodes and the distances, resulting in better scaling...... structures. For example, in a mesh of 391876 nodes the average distance is reduced from 417.33 to 17.32 by adding hierarchical lines. This is gained by increasing the number of lines by 4.20% compared to the non-hierarchical structure. A similar hierarchical extension of the torus structure also results...

Network Security: Policies and Guidelines for Effective Network Management

Directory of Open Access Journals (Sweden)

Jonathan Gana KOLO

2008-12-01

Full Text Available Network security and management in Information and Communication Technology (ICT is the ability to maintain the integrity of a system or network, its data and its immediate environment. The various innovations and uses to which networks are being put are growing by the day and hence are becoming complex and invariably more difficult to manage by the day. Computers are found in every business such as banking, insurance, hospital, education, manufacturing, etc. The widespread use of these systems implies crime and insecurity on a global scale. In addition, the tremendous benefits brought about by Internet have also widened the scope of crime and insecurity at an alarming rate. Also, ICT has fast become a primary differentiator for institution/organization leaders as it offers effective and convenient means of interaction with each other across the globe. This upsurge in the population of organizations depending on ICT for business transaction has brought with it a growing number of security threats and attacks on poorly managed and secured networks primarily to steal personal data, particularly financial information and password.This paper therefore proposes some policies and guidelines that should be followed by network administrators in organizations to help them ensure effective network management and security of ICT facilities and data.

Adaptive Capacity Management in Bluetooth Networks

DEFF Research Database (Denmark)

Son, L.T.

, such as limited wireless bandwidth operation, routing, scheduling, network control, etc. Currently Bluetooth specification particularly does not describe in details about how to implement Quality of Service and Resource Management in Bluetooth protocol stacks. These issues become significant, when the number...... of Bluetooth devices is increasing, a larger-scale ad hoc network, scatternet, is formed, as well as the booming of Internet has demanded for large bandwidth and low delay mobile access. This dissertation is to address the capacity management issues in Bluetooth networks. The main goals of the network capacity...... capacity allocation, network traffic control, inter-piconet scheduling, and buffer management. First, after a short presentation about Bluetooth technology, and QoS issues, queueing models and a simulation-based buffer management have been constructed. Then by using analysis and simulation, it shows some...

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. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A Scalable Policy and SNMP Based Network Management Framework

Institute of Scientific and Technical Information of China (English)

LIU Su-ping; DING Yong-sheng

2009-01-01

Traditional SNMP-based network management can not deal with the task of managing large-scaled distributed network,while policy-based management is one of the effective solutions in network and distributed systems management. However,cross-vendor hardware compatibility is one of the limitations in policy-based management. Devices existing in current network mostly support SNMP rather than Common Open Policy Service (COPS) protocol. By analyzing traditional network management and policy-based network management, a scalable network management framework is proposed. It is combined with Internet Engineering Task Force (IETF) framework for policybased management and SNMP-based network management. By interpreting and translating policy decision to SNMP message,policy can be executed in traditional SNMP-based device.

A policy-based hierarchical approach for management of grids and networks

NARCIS (Netherlands)

Fioreze, Tiago; Neisse, R.; Granville, L.; Almeida, M.J.; Pras, Aiko

2006-01-01

Grids are distributed infrastructures that have been used as an important and powerful resource for distributed computing. Since the nodes of a grid can potentially be located in different administrative domains, the underlying network infrastructure that supports grid communications has to be

Network management for 900-1300 MW PWR power plant industrial network

International Nuclear Information System (INIS)

Schlosser, J.G.; Maillart, H.; Lopinto, Y.

1993-07-01

Communication networks are a vital element in industrial information system projects. Because of the complexity of these networks, which are heterogeneous in terms of hardware, protocols and communication software, the need is now clear to consider them as applications in and of themselves. For this reason, EDF communication networks are now covered by system requirement specifications with SPRINT, and by an acceptance policy which calls for conformance certificates and defines methods for interoperability tests. Network management completes the picture, and attempts to provide the resources with which to assess present network status and manage communication networks. For this purpose, EDF has selected the OSI standard, which is based on four key concepts: - the ''Manager - Agent'' structural model, - a service (CMISE) and a protocol (CMIP) which enable exchange of management information, - an object-oriented management data model, -functions for: configuration, anomaly, performance and alarm management. This document presents the results of a project to integrate into a single management platform communication systems which do not conform to the OSI management recommendations. There were three major phases to the project: - a review of the OSI management model, and most particularly of the information model advocated; - a review of the resources to be managed and a comparison of the information provided by the different agents. Specifications were proposed for the management object and attribute classes which can usefully be implemented; - integration of ARLIC. During development of a breadboard version based on a BULL ISM platform for management of the power plant local area network, one possible solution for integration of ARLIC was proposed, describing the ARLIC information modeling along the lines of the OSI model. This project showed that it is possible to use the OSI modeling to represent management data manipulated by the communication software used on

Accessing ANSA Objects from OSI Network Management

OpenAIRE

Berrah, Karrim; Gay, David; Genilloud, Guy

1994-01-01

OSI network management provides a general framework for the management of OSI systems, and by extension of any distributed system. However, it is not yet possible to tell to what extent the tools developed for network management will be applicable to distributed systems management. This paper assumes that network managers will want to have some control of the distributed infrastructure and applications. It examines how access to some of the ANSA management interfaces can be given to OSI netwo...

Managing the Cooperative Network.

Science.gov (United States)

Segal, JoAn S.

1983-01-01

Discussion of the management of not-for-profit corporations which provide computerized library networks highlights marketing, nonprofit constraints, multiple goals, consumer demands, professional commitment, external influences, motivation and control, dependence on charisma, management and altruism, hybrid organizations, and rational management.…

Software Defined Networking for Improved Wireless Sensor Network Management: A Survey.

Science.gov (United States)

Ndiaye, Musa; Hancke, Gerhard P; Abu-Mahfouz, Adnan M

2017-05-04

Wireless sensor networks (WSNs) are becoming increasingly popular with the advent of the Internet of things (IoT). Various real-world applications of WSNs such as in smart grids, smart farming and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software Defined Networking (SDN) provides a promising solution in flexible management WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. This paper highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail while drawing attention to the advantages that SDN brings to traditional WSN management. This paper also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management.

Software Defined Networking for Improved Wireless Sensor Network Management: A Survey

Directory of Open Access Journals (Sweden)

Musa Ndiaye

2017-05-01

Full Text Available Wireless sensor networks (WSNs are becoming increasingly popular with the advent of the Internet of things (IoT. Various real-world applications of WSNs such as in smart grids, smart farming and smart health would require a potential deployment of thousands or maybe hundreds of thousands of sensor nodes/actuators. To ensure proper working order and network efficiency of such a network of sensor nodes, an effective WSN management system has to be integrated. However, the inherent challenges of WSNs such as sensor/actuator heterogeneity, application dependency and resource constraints have led to challenges in implementing effective traditional WSN management. This difficulty in management increases as the WSN becomes larger. Software Defined Networking (SDN provides a promising solution in flexible management WSNs by allowing the separation of the control logic from the sensor nodes/actuators. The advantage with this SDN-based management in WSNs is that it enables centralized control of the entire WSN making it simpler to deploy network-wide management protocols and applications on demand. This paper highlights some of the recent work on traditional WSN management in brief and reviews SDN-based management techniques for WSNs in greater detail while drawing attention to the advantages that SDN brings to traditional WSN management. This paper also investigates open research challenges in coming up with mechanisms for flexible and easier SDN-based WSN configuration and management.

MANAGING WITHIN DISTRIBUTED INNOVATION NETWORKS

OpenAIRE

LAWRENCE DOOLEY; DAVID O'SULLIVAN

2007-01-01

Business competitiveness and sustainability depends on the effective management of innovation. To be effective, innovation needs to take place within every area of an organisation and by association within organisational networks that include key suppliers, customers and other strategic partners. Distributed innovation management is the process of managing innovation both within and across networks of organisations that have come together to co-design, co-produce and co-service the needs of c...

UNCERTAINTY HANDLING IN DISASTER MANAGEMENT USING HIERARCHICAL ROUGH SET GRANULATION

Directory of Open Access Journals (Sweden)

H. Sheikhian

2015-08-01

Full Text Available Uncertainty is one of the main concerns in geospatial data analysis. It affects different parts of decision making based on such data. In this paper, a new methodology to handle uncertainty for multi-criteria decision making problems is proposed. It integrates hierarchical rough granulation and rule extraction to build an accurate classifier. Rough granulation provides information granules with a detailed quality assessment. The granules are the basis for the rule extraction in granular computing, which applies quality measures on the rules to obtain the best set of classification rules. The proposed methodology is applied to assess seismic physical vulnerability in Tehran. Six effective criteria reflecting building age, height and material, topographic slope and earthquake intensity of the North Tehran fault have been tested. The criteria were discretized and the data set was granulated using a hierarchical rough method, where the best describing granules are determined according to the quality measures. The granules are fed into the granular computing algorithm resulting in classification rules that provide the highest prediction quality. This detailed uncertainty management resulted in 84% accuracy in prediction in a training data set. It was applied next to the whole study area to obtain the seismic vulnerability map of Tehran. A sensitivity analysis proved that earthquake intensity is the most effective criterion in the seismic vulnerability assessment of Tehran.

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.

Topology of foreign exchange markets using hierarchical structure methods

Science.gov (United States)

Naylor, Michael J.; Rose, Lawrence C.; Moyle, Brendan J.

2007-08-01

This paper uses two physics derived hierarchical techniques, a minimal spanning tree and an ultrametric hierarchical tree, to extract a topological influence map for major currencies from the ultrametric distance matrix for 1995-2001. We find that these two techniques generate a defined and robust scale free network with meaningful taxonomy. The topology is shown to be robust with respect to method, to time horizon and is stable during market crises. This topology, appropriately used, gives a useful guide to determining the underlying economic or regional causal relationships for individual currencies and to understanding the dynamics of exchange rate price determination as part of a complex network.

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.

Network-Embedded Management and Applications Understanding Programmable Networking Infrastructure

CERN Document Server

Wolter, Ralf

2013-01-01

Despite the explosion of networking services and applications in the past decades, the basic technological underpinnings of the Internet have remained largely unchanged. At its heart are special-purpose appliances that connect us to the digital world, commonly known as switches and routers. Now, however, the traditional framework is being increasingly challenged by new methods that are jostling for a position in the next-generation Internet. The concept of a network that is becoming more programmable is one of the aspects that are taking center stage. This opens new possibilities to embed software applications inside the network itself and to manage networks and communications services with unprecedented ease and efficiency. In this edited volume, distinguished experts take the reader on a tour of different facets of programmable network infrastructure and application exploit it. Presenting the state of the art in network embedded management and applications and programmable network infrastructure, the book c...

Networked business process management

NARCIS (Netherlands)

Grefen, P.W.P.J.

2013-01-01

In the current economy, a shift can be seen from stand-alone business organizations to networks of tightly collaborating business organizations. To allow this tight collaboration, business process management in these collaborative networks is becoming increasingly important. This paper discusses

Predictive brain networks for major depression in a semi-multimodal fusion hierarchical feature reduction framework.

Science.gov (United States)

Yang, Jie; Yin, Yingying; Zhang, Zuping; Long, Jun; Dong, Jian; Zhang, Yuqun; Xu, Zhi; Li, Lei; Liu, Jie; Yuan, Yonggui

2018-02-05

Major depressive disorder (MDD) is characterized by dysregulation of distributed structural and functional networks. It is now recognized that structural and functional networks are related at multiple temporal scales. The recent emergence of multimodal fusion methods has made it possible to comprehensively and systematically investigate brain networks and thereby provide essential information for influencing disease diagnosis and prognosis. However, such investigations are hampered by the inconsistent dimensionality features between structural and functional networks. Thus, a semi-multimodal fusion hierarchical feature reduction framework is proposed. Feature reduction is a vital procedure in classification that can be used to eliminate irrelevant and redundant information and thereby improve the accuracy of disease diagnosis. Our proposed framework primarily consists of two steps. The first step considers the connection distances in both structural and functional networks between MDD and healthy control (HC) groups. By adding a constraint based on sparsity regularization, the second step fully utilizes the inter-relationship between the two modalities. However, in contrast to conventional multi-modality multi-task methods, the structural networks were considered to play only a subsidiary role in feature reduction and were not included in the following classification. The proposed method achieved a classification accuracy, specificity, sensitivity, and area under the curve of 84.91%, 88.6%, 81.29%, and 0.91, respectively. Moreover, the frontal-limbic system contributed the most to disease diagnosis. Importantly, by taking full advantage of the complementary information from multimodal neuroimaging data, the selected consensus connections may be highly reliable biomarkers of MDD. Copyright © 2017 Elsevier B.V. All rights reserved.

Managing Network Partitions in Structured P2P Networks

Science.gov (United States)

Shafaat, Tallat M.; Ghodsi, Ali; Haridi, Seif

Structured overlay networks form a major class of peer-to-peer systems, which are touted for their abilities to scale, tolerate failures, and self-manage. Any long-lived Internet-scale distributed system is destined to face network partitions. Consequently, the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems. This makes it a crucial requirement for building any structured peer-to-peer systems to be resilient to network partitions. Although the problem of network partitions and mergers is highly related to fault-tolerance and self-management in large-scale systems, it has hardly been studied in the context of structured peer-to-peer systems. Structured overlays have mainly been studied under churn (frequent joins/failures), which as a side effect solves the problem of network partitions, as it is similar to massive node failures. Yet, the crucial aspect of network mergers has been ignored. In fact, it has been claimed that ring-based structured overlay networks, which constitute the majority of the structured overlays, are intrinsically ill-suited for merging rings. In this chapter, we motivate the problem of network partitions and mergers in structured overlays. We discuss how a structured overlay can automatically detect a network partition and merger. We present an algorithm for merging multiple similar ring-based overlays when the underlying network merges. We examine the solution in dynamic conditions, showing how our solution is resilient to churn during the merger, something widely believed to be difficult or impossible. We evaluate the algorithm for various scenarios and show that even when falsely detecting a merger, the algorithm quickly terminates and does not clutter the network with many messages. The algorithm is flexible as the tradeoff between message complexity and time complexity can be adjusted by a parameter.

Hierarchical fiber-optic-based sensing system: impact damage monitoring of large-scale CFRP structures

International Nuclear Information System (INIS)

Minakuchi, Shu; Banshoya, Hidehiko; Takeda, Nobuo; Tsukamoto, Haruka

2011-01-01

This study proposes a novel fiber-optic-based hierarchical sensing concept for monitoring randomly induced damage in large-scale composite structures. In a hierarchical system, several kinds of specialized devices are hierarchically combined to form a sensing network. Specifically, numerous three-dimensionally structured sensor devices are distributed throughout the whole structural area and connected with an optical fiber network through transducing mechanisms. The distributed devices detect damage, and the fiber-optic network gathers the damage signals and transmits the information to a measuring instrument. This study began by discussing the basic concept of a hierarchical sensing system through comparison with existing fiber-optic-based systems, and an impact damage detection system was then proposed to validate the new concept. The sensor devices were developed based on comparative vacuum monitoring (CVM), and Brillouin-based distributed strain measurement was utilized to identify damaged areas. Verification tests were conducted step-by-step, beginning with a basic test using a single sensor unit, and, finally, the proposed monitoring system was successfully verified using a carbon fiber reinforced plastic (CFRP) fuselage demonstrator. It was clearly confirmed that the hierarchical system has better repairability, higher robustness, and a wider monitorable area compared to existing systems

An agent-based QoS provisioning mechanism for WDM optical networks

Science.gov (United States)

Ouyang, Yong; Zeng, Qingji; Yue, Ling

2004-04-01

This paper addresses QoS provisioning mechanisms in the WDM optical networks. With the appearance of metropolitan optical network, a hierarchical metro and wide area optical network will be envisioned in the near future. This hierarchical optical transport network is often divided into optical domains by geography, administration and technology, which usually employ different QoS routing algorithms and policies. To provide end-to-end optical QoS is becoming a new challenge for the optical network design. In this paper, we first give an overview of issues on the QoS provisioning in data, control and management planes of the WDM optical network. And then three provisioning approaches are analyzed and compared. Finally, we propose an agent-based hybrid centralized/distributed QoS provisioning mechanism based on the concept of domain agent. This agent-based hybrid mechanism employs centralized approach in the domain and distributed approach between domains. It offers scalability and intra-domain optimal QoS routing. It also keeps independence and interoperability between domains.

DETERMINANTS OF NETWORK OUTCOMES: THE IMPACT OF MANAGEMENT STRATEGIES.

Science.gov (United States)

Ysa, Tamyko; Sierra, Vicenta; Esteve, Marc

2014-09-01

The literature on network management is extensive. However, it generally explores network structures, neglecting the impact of management strategies. In this article we assess the effect of management strategies on network outcomes, providing empirical evidence from 119 urban revitalization networks. We go beyond current work by testing a path model for the determinants of network outcomes and considering the interactions between the constructs: management strategies, trust, complexity, and facilitative leadership. Our results suggest that management strategies have a strong effect on network outcomes and that they enhance the level of trust. We also found that facilitative leadership has a positive impact on network management as well as on trust in the network. Our findings also show that complexity has a negative impact on trust. A key finding of our research is that managers may wield more influence on network dynamics than previously theorized.

A Hierarchical Convolutional Neural Network for vesicle fusion event classification.

Science.gov (United States)

Li, Haohan; Mao, Yunxiang; Yin, Zhaozheng; Xu, Yingke

2017-09-01

Quantitative analysis of vesicle exocytosis and classification of different modes of vesicle fusion from the fluorescence microscopy are of primary importance for biomedical researches. In this paper, we propose a novel Hierarchical Convolutional Neural Network (HCNN) method to automatically identify vesicle fusion events in time-lapse Total Internal Reflection Fluorescence Microscopy (TIRFM) image sequences. Firstly, a detection and tracking method is developed to extract image patch sequences containing potential fusion events. Then, a Gaussian Mixture Model (GMM) is applied on each image patch of the patch sequence with outliers rejected for robust Gaussian fitting. By utilizing the high-level time-series intensity change features introduced by GMM and the visual appearance features embedded in some key moments of the fusion process, the proposed HCNN architecture is able to classify each candidate patch sequence into three classes: full fusion event, partial fusion event and non-fusion event. Finally, we validate the performance of our method on 9 challenging datasets that have been annotated by cell biologists, and our method achieves better performances when comparing with three previous methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Hierarchically structured distributed microprocessor network for control

International Nuclear Information System (INIS)

Greenwood, J.R.; Holloway, F.W.; Rupert, P.R.; Ozarski, R.G.; Suski, G.J.

1979-01-01

To satisfy a broad range of control-analysis and data-acquisition requirements for Shiva, a hierarchical, computer-based, modular-distributed control system was designed. This system handles the more than 3000 control elements and 1000 data acquisition units in a severe high-voltage, high-current environment. The control system design gives one a flexible and reliable configuration to meet the development milestones for Shiva within critical time limits

Hierarchical Brokering with Feedback Control Framework in Mobile Device-Centric Clouds

Directory of Open Access Journals (Sweden)

Chao-Lieh Chen

2016-01-01

Full Text Available We propose a hierarchical brokering architecture (HiBA and Mobile Multicloud Networking (MMCN feedback control framework for mobile device-centric cloud (MDC2 computing. Exploiting the MMCN framework and RESTful web-based interconnection, each tier broker probes resource state of its federation for control and management. Real-time and seamless services were developed. Case studies including intrafederation energy-aware balancing based on fuzzy feedback control and higher tier load balancing are further demonstrated to show how HiBA with MMCN relieves the embedding of algorithms when developing services. Theoretical performance model and real-world experiments both show that an MDC2 based on HiBA features better quality in terms of resource availability and network latency if it federates devices with enough resources distributed in lower tier hierarchy. The proposed HiBA realizes a development platform for MDC2 computing which is a feasible solution to User-Centric Networks (UCNs.

Social Networks and Welfare in Future Animal Management.

Science.gov (United States)

Koene, Paul; Ipema, Bert

2014-03-17

It may become advantageous to keep human-managed animals in the social network groups to which they have adapted. Data concerning the social networks of farm animal species and their ancestors are scarce but essential to establishing the importance of a natural social network for farmed animal species. Social Network Analysis (SNA) facilitates the characterization of social networking at group, subgroup and individual levels. SNA is currently used for modeling the social behavior and management of wild animals and social welfare of zoo animals. It has been recognized for use with farm animals but has yet to be applied for management purposes. Currently, the main focus is on cattle, because in large groups (poultry), recording of individuals is expensive and the existence of social networks is uncertain due to on-farm restrictions. However, in many cases, a stable social network might be important to individual animal fitness, survival and welfare. For instance, when laying hens are not too densely housed, simple networks may be established. We describe here small social networks in horses, brown bears, laying hens and veal calves to illustrate the importance of measuring social networks among animals managed by humans. Emphasis is placed on the automatic measurement of identity, location, nearest neighbors and nearest neighbor distance for management purposes. It is concluded that social networks are important to the welfare of human-managed animal species and that welfare management based on automatic recordings will become available in the near future.

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

Carrier Ethernet is becoming a favorable access technology for Next Generation Network (NGN). The features of cost-efficiency, operation flexibility and high bandwidth have a great attraction to service providers. However, to achieve these characteristics, Carrier Ethernet needs to have Quality o....... This work has been carried out as a part of the research project HIPT (High quality IP network for IPTV and VoIP) founded by Danish Advanced Technology Foundation....

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.

Brain networks for confidence weighting and hierarchical inference during probabilistic learning

Science.gov (United States)

Meyniel, Florent; Dehaene, Stanislas

2017-01-01

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. PMID:28439014

A Process Management System for Networked Manufacturing

Science.gov (United States)

Liu, Tingting; Wang, Huifen; Liu, Linyan

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

Cloud services, networking, and management

CERN Document Server

da Fonseca, Nelson L S

2015-01-01

Cloud Services, Networking and Management provides a comprehensive overview of the cloud infrastructure and services, as well as their underlying management mechanisms, including data center virtualization and networking, cloud security and reliability, big data analytics, scientific and commercial applications. Special features of the book include: State-of-the-art content. Self-contained chapters for readers with specific interests. Includes commercial applications on Cloud (video services and games).

Forest Monitoring and Wildland Early Fire Detection by a Hierarchical Wireless Sensor Network

Directory of Open Access Journals (Sweden)

Antonio Molina-Pico

2016-01-01

Full Text Available A wildland fire is an uncontrolled fire that occurs mainly in forest areas, although it can also invade urban or agricultural areas. Among the main causes of wildfires, human factors, either intentional or accidental, are the most usual ones. The number and impact of forest fires are expected to grow as a consequence of the global warming. In order to fight against these disasters, it is necessary to adopt a comprehensive, multifaceted approach that enables a continuous situational awareness and instant responsiveness. This paper describes a hierarchical wireless sensor network aimed at early fire detection in risky areas, integrated with the fire fighting command centres, geographical information systems, and fire simulators. This configuration has been successfully tested in two fire simulations involving all the key players in fire fighting operations: fire brigades, communication systems, and aerial, coordination, and land means.

A note on hierarchical hubbing for a generalization of the VPN problem

NARCIS (Netherlands)

N.K. Olver (Neil)

2014-01-01

htmlabstractRobust 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

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].

Research on optical access network remote management technology

Science.gov (United States)

Wang, Wayne; Zou, Chen; Luo, Wenyi

2008-11-01

This paper goal is to provide a framework for the remote configuration and management of services for PON (Passive Optical Network) access and fiber access. Also it defines how Auto-Configuration Servers (ACS) in the network can remotely configure, troubleshoot and manage a Passive Optical Network (PON) optical network termination (ONT) with layer 3 capabilities using the CPE WAN management protocol, TR-069.

Fuzzy hierarchical model for risk assessment principles, concepts, and practical applications

CERN Document Server

Chan, Hing Kai

2013-01-01

Risk management is often complicated by situational uncertainties and the subjective preferences of decision makers. Fuzzy Hierarchical Model for Risk Assessment introduces a fuzzy-based hierarchical approach to solve risk management problems considering both qualitative and quantitative criteria to tackle imprecise information.   This approach is illustrated through number of case studies using examples from the food, fashion and electronics sectors to cover a range of applications including supply chain management, green product design and green initiatives. These practical examples explore how this method can be adapted and fine tuned to fit other industries as well.   Supported by an extensive literature review, Fuzzy Hierarchical Model for Risk Assessment  comprehensively introduces a new method for project managers across all industries as well as researchers in risk management.

The Analysis of User Behaviour of a Network Management Training Tool using a Neural Network

Directory of Open Access Journals (Sweden)

Helen Donelan

2005-10-01

Full Text Available A novel method for the analysis and interpretation of data that describes the interaction between trainee network managers and a network management training tool is presented. A simulation based approach is currently being used to train network managers, through the use of a simulated network. The motivation is to provide a tool for exposing trainees to a life like situation without disrupting a live network. The data logged by this system describes the detailed interaction between trainee network manager and simulated network. The work presented here provides an analysis of this interaction data that enables an assessment of the capabilities of the trainee network manager as well as an understanding of how the network management tasks are being approached. A neural network architecture is implemented in order to perform an exploratory data analysis of the interaction data. The neural network employs a novel form of continuous self-organisation to discover key features in the data and thus provide new insights into the learning and teaching strategies employed.

Analysis of the Spatial Variation of Network-Constrained Phenomena Represented by a Link Attribute Using a Hierarchical Bayesian Model

Directory of Open Access Journals (Sweden)

Zhensheng Wang

2017-02-01

Full Text Available The spatial variation of geographical phenomena is a classical problem in spatial data analysis and can provide insight into underlying processes. Traditional exploratory methods mostly depend on the planar distance assumption, but many spatial phenomena are constrained to a subset of Euclidean space. In this study, we apply a method based on a hierarchical Bayesian model to analyse the spatial variation of network-constrained phenomena represented by a link attribute in conjunction with two experiments based on a simplified hypothetical network and a complex road network in Shenzhen that includes 4212 urban facility points of interest (POIs for leisure activities. Then, the methods named local indicators of network-constrained clusters (LINCS are applied to explore local spatial patterns in the given network space. The proposed method is designed for phenomena that are represented by attribute values of network links and is capable of removing part of random variability resulting from small-sample estimation. The effects of spatial dependence and the base distribution are also considered in the proposed method, which could be applied in the fields of urban planning and safety research.

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. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Wireless Sensor Networks Database: Data Management and Implementation

Directory of Open Access Journals (Sweden)

Ping Liu

2014-04-01

Full Text Available As the core application of wireless sensor network technology, Data management and processing have become the research hotspot in the new database. This article studied mainly data management in wireless sensor networks, in connection with the characteristics of the data in wireless sensor networks, discussed wireless sensor network data query, integrating technology in-depth, proposed a mobile database structure based on wireless sensor network and carried out overall design and implementation for the data management system. In order to achieve the communication rules of above routing trees, network manager uses a simple maintenance algorithm of routing trees. Design ordinary node end, server end in mobile database at gathering nodes and mobile client end that can implement the system, focus on designing query manager, storage modules and synchronous module at server end in mobile database at gathering nodes.

Hierarchical energy management mechanisms for an electricity market with microgrids

Directory of Open Access Journals (Sweden)

Hong-Tzer Yang

2014-08-01

Full Text Available This study addresses a micro-grid electricity market (MGEM with day-ahead (DA and real-time market mechanisms integrated. The bidding mechanisms for the market are described in this study, considering the generation cost of different distributed energy resources (DERs, like distributed generator, energy storage system and demand response. Including load and renewable generation forecasting systems and a fuzzy decision supporting system, a hierarchical micro-grid energy management system (MG-EMS is then proposed to ensure the benefits of involved micro-grid central controller, DER owners and customers. To verify the feasibility of the proposed system, the whole-year historical pricing and load data for New England independent system operator are employed. The numerical results show that the proposed MG-EMS is promising and effective for the operations of MGEM.

COORDINATION IN MULTILEVEL NETWORK-CENTRIC CONTROL SYSTEMS OF REGIONAL SECURITY: APPROACH AND FORMAL MODEL

Directory of Open Access Journals (Sweden)

A. V. Masloboev

2015-01-01

Full Text Available The paper deals with development of methods and tools for mathematical and computer modeling of the multilevel network-centric control systems of regional security. This research is carried out under development strategy implementation of the Arctic zone of the Russian Federation and national safeguarding for the period before 2020 in the Murmansk region territory. Creation of unified interdepartmental multilevel computer-aided system is proposed intended for decision-making information support and socio-economic security monitoring of the Arctic regions of Russia. The distinctive features of the investigated system class are openness, self-organization, decentralization of management functions and decision-making, weak hierarchy in the decision-making circuit and goal generation capability inside itself. Research techniques include functional-target approach, mathematical apparatus of multilevel hierarchical system theory and principles of network-centric control of distributed systems with pro-active components and variable structure. The work considers network-centric management local decisions coordination problem-solving within the multilevel distributed systems intended for information support of regional security. The coordination problem-solving approach and problem formalization in the multilevel network-centric control systems of regional security have been proposed based on developed multilevel recurrent hierarchical model of regional socio-economic system complex security. The model provides coordination of regional security indexes, optimized by the different elements of multilevel control systems, subject to decentralized decision-making. The model specificity consists in application of functional-target technology and mathematical apparatus of multilevel hierarchical system theory for coordination procedures implementation of the network-centric management local decisions. The work-out and research results can find further

Managing logistical processes in franchise retail trade networks

OpenAIRE

Grigorenko Tatyana N.; Kochubey Dmitriy V.

2013-01-01

The article analyses approaches to organisation of internal logistics of franchise trade networks and methodical provision of assessment of results of logistical activity at companies of franchise networks. The article justifies urgency of application of referent models of management of supply chains in construction of a system of management of logistical activity of franchise networks. It offers classification of models of management of internal logistics of franchise retail trade networks. ...

VNML: Virtualized Network Management Laboratory for Educational ...

African Journals Online (AJOL)

VNML: Virtualized Network Management Laboratory for Educational Purposes. ... Journal of Fundamental and Applied Sciences ... In this paper, we implement a Virtualized Network Management Laboratory named (VNML) linked to college ...

Do Policy Networks lead to Network Governing?

DEFF Research Database (Denmark)

Damgaard, Bodil

This paper challenges the notion that creation of local policy networks necessarily leads to network governing. Through actor-centred case studies in the area of municipally implemented employment policy in Denmark it was found that the local governing mode is determined mainly by the municipality......’s approach to local co-governing as well as by the capacity and interest of key private actors. It is argued that national legislation requesting the creation of local policy networks was not enough to assure network governing and the case studies show that local policy networks may subsist also under...... hierarchical governing modes. Reasons why hierarchical governing modes prevail over network governing in some settings are identified pointing to both actor borne and structural factors. Output indicators of the four cases do not show that a particular governing mode is more efficient in its employment policy...

Strategy Implementation through Hierarchical Couplings in a Management Control Package: An Explorative Case Study

OpenAIRE

van der Kolk, Berend; Schokker, Tom

2016-01-01

We examine how couplings of management control (MC) elements help to implement an organization’s strategy. Despite prior research stating that couplings between MC elements form fruitful soil for further research, empirical studies in this area are still scarce. We draw on coupling theory to explore three hierarchical relations between MC elements, and examine how these couplings help to implement the organization’s strategy. We conducted a single case study in a medium-sized Dutch municipali...

Evaluation of options for energy recovery from municipal solid waste in India using the hierarchical analytical network process

International Nuclear Information System (INIS)

Nixon, J.D.; Dey, P.K.; Ghosh, S.K.; Davies, P.A.

2013-01-01

In this paper a Hierarchical Analytical Network Process (HANP) model is demonstrated for evaluating alternative technologies for generating electricity from MSW in India. The technological alternatives and evaluation criteria for the HANP study are characterised by reviewing the literature and consulting experts in the field of waste management. Technologies reviewed in the context of India include landfill, anaerobic digestion, incineration, pelletisation and gasification. To investigate the sensitivity of the result, we examine variations in expert opinions and carry out an Analytical Hierarchy Process (AHP) analysis for comparison. We find that anaerobic digestion is the preferred technology for generating electricity from MSW in India. Gasification is indicated as the preferred technology in an AHP model due to the exclusion of criteria dependencies and in an HANP analysis when placing a high priority on net output and retention time. We conclude that HANP successfully provides a structured framework for recommending which technologies to pursue in India, and the adoption of such tools is critical at a time when key investments in infrastructure are being made. Therefore the presented methodology is thought to have a wider potential for investors, policy makers, researchers and plant developers in India and elsewhere. - Highlights: • We evaluate alternative technologies for generating electricity from waste. • The methodology we develop is based on the analytical network process. • Assessment is made against technical, financial, environmental and risk criteria. • Anaerobic digestion and gasification are the preferred technologies for India. • The method reduces risk and ensures sustainability in energy project planning

The Managing Epilepsy Well Network:: Advancing Epilepsy Self-Management.

Science.gov (United States)

Sajatovic, Martha; Jobst, Barbara C; Shegog, Ross; Bamps, Yvan A; Begley, Charles E; Fraser, Robert T; Johnson, Erica K; Pandey, Dilip K; Quarells, Rakale C; Scal, Peter; Spruill, Tanya M; Thompson, Nancy J; Kobau, Rosemarie

2017-03-01

Epilepsy, a complex spectrum of disorders, affects about 2.9 million people in the U.S. Similar to other chronic disorders, people with epilepsy face challenges related to management of the disorder, its treatment, co-occurring depression, disability, social disadvantages, and stigma. Two national conferences on public health and epilepsy (1997, 2003) and a 2012 IOM report on the public health dimensions of epilepsy highlighted important knowledge gaps and emphasized the need for evidence-based, scalable epilepsy self-management programs. The Centers for Disease Control and Prevention translated recommendations on self-management research and dissemination into an applied research program through the Prevention Research Centers Managing Epilepsy Well (MEW) Network. MEW Network objectives are to advance epilepsy self-management research by developing effective interventions that can be broadly disseminated for use in people's homes, healthcare providers' offices, or in community settings. The aim of this report is to provide an update on the MEW Network research pipeline, which spans efficacy, effectiveness, and dissemination. Many of the interventions use e-health strategies to eliminate barriers to care (e.g., lack of transportation, functional limitations, and stigma). Strengths of this mature research network are the culture of collaboration, community-based partnerships, e-health methods, and its portfolio of prevention activities, which range from efficacy studies engaging hard-to-reach groups, to initiatives focused on provider training and knowledge translation. The MEW Network works with organizations across the country to expand its capacity, help leverage funding and other resources, and enhance the development, dissemination, and sustainability of MEW Network programs and tools. Guided by national initiatives targeting chronic disease or epilepsy burden since 2007, the MEW Network has been responsible for more than 43 scientific journal articles, two

Using Bayesian belief networks in adaptive management.

Science.gov (United States)

J.B. Nyberg; B.G. Marcot; R. Sulyma

2006-01-01

Bayesian belief and decision networks are relatively new modeling methods that are especially well suited to adaptive-management applications, but they appear not to have been widely used in adaptive management to date. Bayesian belief networks (BBNs) can serve many purposes for practioners of adaptive management, from illustrating system relations conceptually to...

Hierarchical Energy Management of Microgrids including Storage and Demand Response

Directory of Open Access Journals (Sweden)

Songli Fan

2018-05-01

Full Text Available Battery energy storage (BES and demand response (DR are considered to be promising technologies to cope with the uncertainty of renewable energy sources (RES and the load in the microgrid (MG. Considering the distinct prediction accuracies of the RES and load at different timescales, it is essential to incorporate the multi-timescale characteristics of BES and DR in MG energy management. Under this background, a hierarchical energy management framework is put forward for an MG including multi-timescale BES and DR to optimize operation with the uncertainty of RES as well as load. This framework comprises three stages of scheduling: day-ahead scheduling (DAS, hour-ahead scheduling (HAS, and real-time scheduling (RTS. In DAS, a scenario-based stochastic optimization model is established to minimize the expected operating cost of MG, while ensuring its safe operation. The HAS is utilized to bridge DAS and RTS. In RTS, a control strategy is proposed to eliminate the imbalanced power owing to the fluctuations of RES and load. Then, a decomposition-based algorithm is adopted to settle the models in DAS and HAS. Simulation results on a seven-bus MG validate the effectiveness of the proposed methodology.

Management continuity in local health networks

Directory of Open Access Journals (Sweden)

Mylaine Breton

2012-04-01

Full Text Available Introduction: Patients increasingly receive care from multiple providers in a variety of settings. They expect management continuity that crosses boundaries and bridges gaps in the healthcare system. To our knowledge, little research has been done to assess coordination across organizational and professional boundaries from the patients' perspective. Our objective was to assess whether greater local health network integration is associated with management continuity as perceived by patients. Method: We used the data from a research project on the development and validation of a generic and comprehensive continuity measurement instrument that can be applied to a variety of patient conditions and settings. We used the results of a cross-sectional survey conducted in 2009 with 256 patients in two local health networks in Quebec, Canada. We compared four aspects of management continuity between two contrasting network types (highly integrated vs. poorly integrated. Results: The scores obtained in the highly integrated network are better than those of the poorly integrated network on all dimensions of management continuity (coordinator role, role clarity and coordination between clinics, and information gaps between providers except for experience of care plan. Conclusion: Some aspects of care coordination among professionals and organizations are noticed by patients and may be valid indicators to assess care coordination.

Social network analysis and supply chain management

Directory of Open Access Journals (Sweden)

Raúl Rodríguez Rodríguez

2016-01-01

Full Text Available This paper deals with social network analysis and how it could be integrated within supply chain management from a decision-making point of view. Even though the benefits of using social analysis have are widely accepted at both academic and industry/services context, there is still a lack of solid frameworks that allow decision-makers to connect the usage and obtained results of social network analysis – mainly both information and knowledge flows and derived results- with supply chain management objectives and goals. This paper gives an overview of social network analysis, the main social network analysis metrics, supply chain performance and, finally, it identifies how future frameworks could close the gap and link the results of social network analysis with the supply chain management decision-making processes.

Energy management in wireless cellular and ad-hoc networks

CERN Document Server

Imran, Muhammad; Qaraqe, Khalid; Alouini, Mohamed-Slim; Vasilakos, Athanasios

2016-01-01

This book investigates energy management approaches for energy efficient or energy-centric system design and architecture and presents end-to-end energy management in the recent heterogeneous-type wireless network medium. It also considers energy management in wireless sensor and mesh networks by exploiting energy efficient transmission techniques and protocols. and explores energy management in emerging applications, services and engineering to be facilitated with 5G networks such as WBANs, VANETS and Cognitive networks. A special focus of the book is on the examination of the energy management practices in emerging wireless cellular and ad hoc networks. Considering the broad scope of energy management in wireless cellular and ad hoc networks, this book is organized into six sections covering range of Energy efficient systems and architectures; Energy efficient transmission and techniques; Energy efficient applications and services. .

An Intelligent Alternative Approach to the efficient Network Management

Directory of Open Access Journals (Sweden)

MARTÍN, A.

2012-12-01

Full Text Available Due to the increasing complexity and heterogeneity of networks and services, many efforts have been made to develop intelligent techniques for management. Network intelligent management is a key technology for operating large heterogeneous data transmission networks. This paper presents a proposal for an architecture that integrates management object specifications and the knowledge of expert systems. We present a new approach named Integrated Expert Management, for learning objects based on expert management rules and describe the design and implementation of an integrated intelligent management platform based on OSI and Internet management models. The main contributions of our approach is the integration of both expert system and managed models, so we can make use of them to construct more flexible intelligent management network. The prototype SONAP (Software for Network Assistant and Performance is accuracy-aware since it can control and manage a network. We have tested our system on real data to the fault diagnostic in a telecommunication system of a power utility. The results validate the model and show a significant improvement with respect to the number of rules and the error rate in others systems.

Studying citizen-centred implementation networks in the age of governance

DEFF Research Database (Denmark)

Jacobi, Claus Brygger

This paper is suggesting pathways on how to investigate and analyze the implementation of public policies at a time where the idea of governance is leaving no public policy process untouched in any advanced liberal democracy. But due to the bewildering variety of ways in which the concept......, it is suggested that manifestations of hierarchical governance can be studied by using insights from network management combined with Pierre Bourdieu’s concept of the political and administrative fields. This gives the added value of enabling to the analyst to identify hierarchical forms of governance...

Managing a network vulnerability assessment

CERN Document Server

Peltier, Thomas R; Blackley, John A

2003-01-01

Managing a Network Vulnerability Assessment provides a formal framework for finding and eliminating network security threats, ensuring that no vulnerabilities are overlooked. This thorough overview focuses on the steps necessary to successfully manage an assessment, including the development of a scope statement, the understanding and proper use of assessment methodology, the creation of an expert assessment team, and the production of a valuable response report. The book also details what commercial, freeware, and shareware tools are available, how they work, and how to use them.

Linking social capital to knowledge productivity : an explorative study on the relationship between social capital and learning in knowledge-productive networks

NARCIS (Netherlands)

de Jong, Tjip

2010-01-01

Why are some networks more successful in achieving innovation than others? Why do some groups within organizations manage to operate without hierarchical boundaries, and at the same time achieve extraordinary, innovative results? How do they learn? And what kinds of network characteristics do they

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.

Complexity in the governance of tourism networks : Balancing between external pressure and internal expectations

NARCIS (Netherlands)

van der Zee, Egbert; Gerrets, Anne-Mara; Vanneste, Dominique

2017-01-01

Tourism destinations are complex systems of interrelated entities without a hierarchical chain of command. In order to enhance the ability of destinations to create a high quality, authentic tourism experience, a management perspective based on networks, personal relationships, trust, and

Self-assembly of nano/micro-structured Fe3O4 microspheres among 3D rGO/CNTs hierarchical networks with superior lithium storage performances

International Nuclear Information System (INIS)

Liu, Jinlong; Feng, Haibo; Wang, Xipeng; Qian, Dong; Jiang, Jianbo; Li, Junhua; Peng, Sanjun; Deng, Miao; Liu, Youcai

2014-01-01

Nano/micro-structured Fe 3 O 4 microspheres among three-dimensional (3D) reduced graphene oxide (rGO)/carbon nanotubes (CNTs) hierarchical networks (the ternary composite is denoted as rGCFs) have been synthesized using a facile, self-assembled and one-pot hydrothermal approach. The rGCFs composite exhibits superior lithium storage performances: initial discharge and charge capacities of 1452 and 1036 mAh g −1 , respectively, remarkable rate capability at current densities from 100 mA g −1 to 10 A g −1 and outstanding cycling performance up to 200 cycles. The highly enhanced electrochemical performances of rGCFs depend heavily on the robust 3D rGO/CNTs hierarchical networks, the stable nano/microstructures of active Fe 3 O 4 microspheres and the positive synergistic effects of building components. The systematic structure characterizations and electrochemical investigations provide insightful understanding towards the relationship between structure/morphology and lithium storage performances, which may pave the way for the rational design of composite materials with desirable goals. (papers)

Small cell networks deployment, management, and optimization

CERN Document Server

Claussen, Holger; Ho, Lester; Razavi, Rouzbeh; Kucera, Stepan

2018-01-01

Small Cell Networks: Deployment, Management, and Optimization addresses key problems of the cellular network evolution towards HetNets. It focuses on the latest developments in heterogeneous and small cell networks, as well as their deployment, operation, and maintenance. It also covers the full spectrum of the topic, from academic, research, and business to the practice of HetNets in a coherent manner. Additionally, it provides complete and practical guidelines to vendors and operators interested in deploying small cells. The first comprehensive book written by well-known researchers and engineers from Nokia Bell Labs, Small Cell Networks begins with an introduction to the subject--offering chapters on capacity scaling and key requirements of future networks. It then moves on to sections on coverage and capacity optimization, and interference management. From there, the book covers mobility management, energy efficiency, and small cell deployment, ending with a section devoted to future trends and applicat...

Management of mandated networks from a dynamic perspective

NARCIS (Netherlands)

Segato, Federica; Raab, J.

2017-01-01

The management of networks has received increasing attention in recent years in the form of systematic empirical research. The general thrust of the results seem to indicate that network management resembles what we know about general management. However, there are also specific characteristics of

Urban pattern: Layout design by hierarchical domain splitting

KAUST Repository

Yang, Yongliang; Wang, Jun; Vouga, Etienne; Wonka, Peter

2013-01-01

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.

Urban pattern: Layout design by hierarchical domain splitting

KAUST Repository

Yang, Yongliang

2013-11-06

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.

Performance Evaluation Of Macro amp Micro Mobility In HMIP Networks

Directory of Open Access Journals (Sweden)

Osama Ali Abdelgadir

2015-08-01

Full Text Available Abstract Changing the location of mobile node during transmission or receiving of data always caused changing of the address of the mobile node which results in packet loss as well as delay in time taken to locate the new address of the Mobile Node therefore delay of data receiving is caused this problem was known as micro-mobility issue. To resolve this problem and ascurrently mobile IP is the most promising solution for mobility management in the Internet. Several IP micro mobility approaches have been proposed to enhance the performance of mobile IP which supports quality of service minimum packet loss limited handoff delay and scalability and power conservation but they are not scalable for macro mobility. A practical solution would therefore require integration of mobile IP and micro mobility protocols where mobile IP handles macro mobility and HMIP cellular IP HAWAII handles micro mobility. In this paper an integrated mobility management protocol for IP based wireless networks is proposed and analyzed.HIERARCHICAL MICRO MOBILITY PROTOCOL is used. To identify the impact of micro-mobility in IP based Wireless Network to implement selected micro-mobility model of Hierarchal Micro Mobility Protocol in network simulator and for more analysis and measurements results and for the purpose of performance comparison between both Macro and Micro mobility Protocol Management.. Simulation results presented in this paper are based on ns 2

Data management issues in mobile ad hoc networks.

Science.gov (United States)

Hara, Takahiro

2017-01-01

Research on mobile ad hoc networks (MANETs) has become a hot research topic since the middle 1990's. Over the first decade, most research focused on networking techniques, ignoring data management issues. We, however, realized early the importance of data management in MANETs, and have been conducting studies in this area for 15 years. In this review, we summarize some key technical issues related to data management in MANETs, and the studies we have done in addressing these issues, which include placement of data replicas, update management, and query processing with security management. The techniques proposed in our studies have been designed with deep considerations of MANET features including network partitioning, node participation/disappearance, limited network bandwidth, and energy efficiency. Our studies published in early 2000's have developed a new research field as data management in MANETs. Also, our recent studies are expected to be significant guidelines of new research directions. We conclude the review by discussing some future directions for research.

A note on hierarchical hubbing for a generalization of the VPN problem

NARCIS (Netherlands)

N.K. Olver (Neil)

2016-01-01

textabstractRobust network design refers to a class of optimization problems that occur when designing networks to efficiently handle variable demands. In this context, Fréchette et al. (2013) recently explored hierarchical hubbing: a routing strategy involving a multiplicity of "hubs" connected to

A note on hierarchical hubbing for a generalization of the VPN problem

NARCIS (Netherlands)

Olver, Neil

2016-01-01

Robust network design refers to a class of optimization problems that occur when designing networks to efficiently handle variable demands. In this context, Fréchette et al. (2013) recently explored hierarchical hubbing: a routing strategy involving a multiplicity of "hubs" connected to terminals

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

A class of vertex-edge-growth small-world network models having scale-free, self-similar and hierarchical characters

Science.gov (United States)

Ma, Fei; Su, Jing; Hao, Yongxing; Yao, Bing; Yan, Guanghui

2018-02-01

The problem of uncovering the internal operating function of network models is intriguing, demanded and attractive in researches of complex networks. Notice that, in the past two decades, a great number of artificial models are built to try to answer the above mentioned task. Based on the different growth ways, these previous models can be divided into two categories, one type, possessing the preferential attachment, follows a power-law P(k) ∼k-γ, 2 motivated from a new attachment way, vertex-edge-growth network-operation, more precisely, the couple of both them. We report that this model is sparse, small world and hierarchical. And then, not only is scale-free feature in our model, but also lies the degree parameter γ(≈ 3 . 242) out the typical range. Note that, we suggest that the coexistence of multiple vertex growth ways will have a prominent effect on the power-law parameter γ, and the preferential attachment plays a dominate role on the development of networks over time. At the end of this paper, we obtain an exact analytical expression for the total number of spanning trees of models and also capture spanning trees entropy which we have compared with those of their corresponding component elements.

Thermal conductivity from hierarchical heat sinks using carbon nanotubes and graphene nanosheets.

Science.gov (United States)

Hsieh, Chien-Te; Lee, Cheng-En; Chen, Yu-Fu; Chang, Jeng-Kuei; Teng, Hsi-sheng

2015-11-28

The in-plane (kip) and through-plane (ktp) thermal conductivities of heat sinks using carbon nanotubes (CNTs), graphene nanosheets (GNs), and CNT/GN composites are extracted from two experimental setups within the 323-373 K temperature range. Hierarchical three-dimensional CNT/GN frameworks display higher kip and ktp values, as compared to the CNT- and GN-based heat sinks. The kip and ktp values of the CNT/GN-based heat sink reach as high as 1991 and 76 W m(-1) K(-1) at 323 K, respectively. This improved thermal conductivity is attributed to the fact that the hierarchical heat sink offers a stereo thermal conductive network that combines point, line, and plane contact, leading to better heat transport. Furthermore, the compression treatment provided an efficient route to increase both kip and ktp values. This result reveals that the hierarchical carbon structures become denser, inducing more thermal conductive area and less thermal resistivity, i.e., a reduced possibility of phonon-boundary scattering. The correlation between thermal and electrical conductivity (ε) can be well described by two empirical equations: kip = 567 ln(ε) + 1120 and ktp = 20.6 ln(ε) + 36.1. The experimental results are obtained within the temperature range of 323-373 K, suitably complementing the thermal management of chips for consumer electronics.

Hierarchical Neural Representation of Dreamed Objects Revealed by Brain Decoding with Deep Neural Network Features.

Science.gov (United States)

Horikawa, Tomoyasu; Kamitani, Yukiyasu

2017-01-01

Dreaming is generally thought to be generated by spontaneous brain activity during sleep with patterns common to waking experience. This view is supported by a recent study demonstrating that dreamed objects can be predicted from brain activity during sleep using statistical decoders trained with stimulus-induced brain activity. However, it remains unclear whether and how visual image features associated with dreamed objects are represented in the brain. In this study, we used a deep neural network (DNN) model for object recognition as a proxy for hierarchical visual feature representation, and DNN features for dreamed objects were analyzed with brain decoding of fMRI data collected during dreaming. The decoders were first trained with stimulus-induced brain activity labeled with the feature values of the stimulus image from multiple DNN layers. The decoders were then used to decode DNN features from the dream fMRI data, and the decoded features were compared with the averaged features of each object category calculated from a large-scale image database. We found that the feature values decoded from the dream fMRI data positively correlated with those associated with dreamed object categories at mid- to high-level DNN layers. Using the decoded features, the dreamed object category could be identified at above-chance levels by matching them to the averaged features for candidate categories. The results suggest that dreaming recruits hierarchical visual feature representations associated with objects, which may support phenomenal aspects of dream experience.

The prevention research centers' managing epilepsy well network.

Science.gov (United States)

DiIorio, Colleen K; Bamps, Yvan A; Edwards, Ariele L; Escoffery, Cam; Thompson, Nancy J; Begley, Charles E; Shegog, Ross; Clark, Noreen M; Selwa, Linda; Stoll, Shelley C; Fraser, Robert T; Ciechanowski, Paul; Johnson, Erica K; Kobau, Rosemarie; Price, Patricia H

2010-11-01

The Managing Epilepsy Well (MEW) Network was created in 2007 by the Centers for Disease Control and Prevention's (CDC) Prevention Research Centers and Epilepsy Program to promote epilepsy self-management research and to improve the quality of life for people with epilepsy. MEW Network membership comprises four collaborating centers (Emory University, University of Texas Health Science Center at Houston, University of Michigan, and University of Washington), representatives from CDC, affiliate members, and community stakeholders. This article describes the MEW Network's background, mission statement, research agenda, and structure. Exploratory and intervention studies conducted by individual collaborating centers are described, as are Network collaborative projects, including a multisite depression prevention intervention and the development of a standard measure of epilepsy self-management. Communication strategies and examples of research translation programs are discussed. The conclusion outlines the Network's role in the future development and dissemination of evidence-based epilepsy self-management programs. Copyright © 2010 Elsevier Inc. All rights reserved.

Maintenance Management in Network Utilities Framework and Practical Implementation

CERN Document Server

Gómez Fernández, Juan F

2012-01-01

In order to satisfy the needs of their customers, network utilities require specially developed maintenance management capabilities. Maintenance Management information systems are essential to ensure control, gain knowledge and improve-decision making in companies dealing with network infrastructure, such as distribution of gas, water, electricity and telecommunications. Maintenance Management in Network Utilities studies specified characteristics of maintenance management in this sector to offer a practical approach to defining and implementing  the best management practices and suitable frameworks.   Divided into three major sections, Maintenance Management in Network Utilities defines a series of stages which can be followed to manage maintenance frameworks properly. Different case studies provide detailed descriptions which illustrate the experience in real company situations. An introduction to the concepts is followed by main sections including: • A Literature Review: covering the basic concepts an...

Hierarchical thinking in network biology: the unbiased modularization of biochemical networks.

Science.gov (United States)

Papin, Jason A; Reed, Jennifer L; Palsson, Bernhard O

2004-12-01

As reconstructed biochemical reaction networks continue to grow in size and scope, there is a growing need to describe the functional modules within them. Such modules facilitate the study of biological processes by deconstructing complex biological networks into conceptually simple entities. The definition of network modules is often based on intuitive reasoning. As an alternative, methods are being developed for defining biochemical network modules in an unbiased fashion. These unbiased network modules are mathematically derived from the structure of the whole network under consideration.

Risk and reliability assessment for telecommunications networks

Energy Technology Data Exchange (ETDEWEB)

Wyss, G.D.; Schriner, H.K.; Gaylor, T.R.

1996-08-01

Sandia National Laboratories has assembled an interdisciplinary team to explore the applicability of probabilistic logic modeling (PLM) techniques to model network reliability for a wide variety of communications network architectures. The authors have found that the reliability and failure modes of current generation network technologies can be effectively modeled using fault tree PLM techniques. They have developed a ``plug-and-play`` fault tree analysis methodology that can be used to model connectivity and the provision of network services in a wide variety of current generation network architectures. They have also developed an efficient search algorithm that can be used to determine the minimal cut sets of an arbitrarily-interconnected (non-hierarchical) network without the construction of a fault tree model. This paper provides an overview of these modeling techniques and describes how they are applied to networks that exhibit hybrid network structures (i.e., a network in which some areas are hierarchical and some areas are not hierarchical).

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

Sustained oscillations, irregular firing and chaotic dynamics in hierarchical modular networks with mixtures of electrophysiological cell types

Directory of Open Access Journals (Sweden)

Petar eTomov

2014-09-01

Full Text Available The cerebral cortex exhibits neural activity even in the absence of externalstimuli. This self-sustained activity is characterized by irregular firing ofindividual neurons and population oscillations with a broad frequency range.Questions that arise in this context, are: What are the mechanismsresponsible for the existence of neuronal spiking activity in the cortexwithout external input? Do these mechanisms depend on the structural organization of the cortical connections? Do they depend onintrinsic characteristics of the cortical neurons? To approach the answers to these questions, we have used computer simulations of cortical network models. Our networks have hierarchical modular architecture and are composedof combinations of neuron models that reproduce the firing behavior of the five main cortical electrophysiological cell classes: regular spiking (RS, chattering (CH, intrinsically bursting (IB, low threshold spiking (LTS and fast spiking (FS. The population of excitatory neurons is built of RS cells(always present and either CH or IB cells. Inhibitoryneurons belong to the same class, either LTS or FS. Long-lived self-sustained activity states in our networksimulations display irregular single neuron firing and oscillatoryactivity similar to experimentally measured ones. The duration of self-sustained activity strongly depends on the initial conditions,suggesting a transient chaotic regime. Extensive analysis of the self-sustainedactivity states showed that their lifetime expectancy increases with the numberof network modules and is favored when the network is composed of excitatory neurons of the RS and CH classes combined with inhibitory neurons of the LTS class. These results indicate that the existence and properties of the self-sustained cortical activity states depend on both the topology of the network and the neuronal mixture that comprises the network.

Picture this: Managed change and resistance in business network settings

DEFF Research Database (Denmark)

Kragh, Hanne; Andersen, Poul Houman

2009-01-01

This paper discusses change management in networks. The literature on business networks tends to downplay the role of managerial initiative in network change. The change management literature addresses such initiative, but with its single-firm perspective it overlooks the interdependence of network...... actors. In exploring the void between these two streams of literature, we deploy the concept of network pictures to discuss managed change in network settings. We analyze a change project from the furniture industry and address the consequences of attempting to manage change activities in a network...... context characterized by limited managerial authority over these activities. Our analysis suggests that change efforts unfold as a negotiated process during which the change project is re-negotiated to fit the multiple actor constituencies. The degree of overlap in the co-existing network pictures...

Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

Directory of Open Access Journals (Sweden)

Jun Ren

2014-01-01

Full Text Available Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes.

Network position and related power : how they affect and are affected by network management and outcomes

NARCIS (Netherlands)

Oukes, Tamara

2018-01-01

In network position and related power you learn more about how network position and related power affect and are affected by network management and outcomes. First, I expand our present understanding of how startups with a fragile network position manage business relationships by taking an

Exploring Neural Network Models with Hierarchical Memories and Their Use in Modeling Biological Systems

Science.gov (United States)

Pusuluri, Sai Teja

Energy landscapes are often used as metaphors for phenomena in biology, social sciences and finance. Different methods have been implemented in the past for the construction of energy landscapes. Neural network models based on spin glass physics provide an excellent mathematical framework for the construction of energy landscapes. This framework uses a minimal number of parameters and constructs the landscape using data from the actual phenomena. In the past neural network models were used to mimic the storage and retrieval process of memories (patterns) in the brain. With advances in the field now, these models are being used in machine learning, deep learning and modeling of complex phenomena. Most of the past literature focuses on increasing the storage capacity and stability of stored patterns in the network but does not study these models from a modeling perspective or an energy landscape perspective. This dissertation focuses on neural network models both from a modeling perspective and from an energy landscape perspective. I firstly show how the cellular interconversion phenomenon can be modeled as a transition between attractor states on an epigenetic landscape constructed using neural network models. The model allows the identification of a reaction coordinate of cellular interconversion by analyzing experimental and simulation time course data. Monte Carlo simulations of the model show that the initial phase of cellular interconversion is a Poisson process and the later phase of cellular interconversion is a deterministic process. Secondly, I explore the static features of landscapes generated using neural network models, such as sizes of basins of attraction and densities of metastable states. The simulation results show that the static landscape features are strongly dependent on the correlation strength and correlation structure between patterns. Using different hierarchical structures of the correlation between patterns affects the landscape features

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.

Network structure of subway passenger flows

Science.gov (United States)

Xu, Q.; Mao, B. H.; Bai, Y.

2016-03-01

The results of transportation infrastructure network analyses have been used to analyze complex networks in a topological context. However, most modeling approaches, including those based on complex network theory, do not fully account for real-life traffic patterns and may provide an incomplete view of network functions. This study utilizes trip data obtained from the Beijing Subway System to characterize individual passenger movement patterns. A directed weighted passenger flow network was constructed from the subway infrastructure network topology by incorporating trip data. The passenger flow networks exhibit several properties that can be characterized by power-law distributions based on flow size, and log-logistic distributions based on the fraction of boarding and departing passengers. The study also characterizes the temporal patterns of in-transit and waiting passengers and provides a hierarchical clustering structure for passenger flows. This hierarchical flow organization varies in the spatial domain. Ten cluster groups were identified, indicating a hierarchical urban polycentric structure composed of large concentrated flows at urban activity centers. These empirical findings provide insights regarding urban human mobility patterns within a large subway network.

A class Hierarchical, object-oriented approach to virtual memory management

Science.gov (United States)

Russo, Vincent F.; Campbell, Roy H.; Johnston, Gary M.

1989-01-01

The Choices family of operating systems exploits class hierarchies and object-oriented programming to facilitate the construction of customized operating systems for shared memory and networked multiprocessors. The software is being used in the Tapestry laboratory to study the performance of algorithms, mechanisms, and policies for parallel systems. Described here are the architectural design and class hierarchy of the Choices virtual memory management system. The software and hardware mechanisms and policies of a virtual memory system implement a memory hierarchy that exploits the trade-off between response times and storage capacities. In Choices, the notion of a memory hierarchy is captured by abstract classes. Concrete subclasses of those abstractions implement a virtual address space, segmentation, paging, physical memory management, secondary storage, and remote (that is, networked) storage. Captured in the notion of a memory hierarchy are classes that represent memory objects. These classes provide a storage mechanism that contains encapsulated data and have methods to read or write the memory object. Each of these classes provides specializations to represent the memory hierarchy.

Organization of managed clinical networking for home parenteral nutrition.

Science.gov (United States)

Baxter, Janet P; McKee, Ruth F

2006-05-01

Home parenteral nutrition (HPN) is an established treatment for intestinal failure, and organization of HPN is variable throughout the UK and Europe. Managed clinical networking is the single most important feature of the UK National Health Service strategy for acute services in Scotland and has the potential to improve the management of HPN patients. This review addresses the role of managed clinical networking in HPN and compares outcome data between centres. The Scottish HPN Managed Clinical Network has published the main body of the current literature supporting the concept of managed clinical networking in this context. The Network is responsible for the organization and quality assurance of HPN provision in Scotland, and has been established for 5 years. It has captured significant patient data for the purpose of clinical audit and illustrates that this is an effective model for the management of this patient population. This review provides advice for other areas wishing to improve equity of access, and to smooth the patient journey between primary, secondary and tertiary health care in the context of artificial nutrition support.

Dynamic Trust Management for Mobile Networks and Its Applications

Science.gov (United States)

Bao, Fenye

2013-01-01

Trust management in mobile networks is challenging due to dynamically changing network environments and the lack of a centralized trusted authority. In this dissertation research, we "design" and "validate" a class of dynamic trust management protocols for mobile networks, and demonstrate the utility of dynamic trust management…

Public management and policy networks: foundations of a network approach to governance

NARCIS (Netherlands)

E-H. Klijn (Erik-Hans); J.F.M. Koppenjan (Joop)

2006-01-01

markdownabstract__Abstract__ In this article we address the elaboratlon of the central concepts of a theory of networks and of network management. We suggest that the network approach builds on several theoretical traditions After this we clarify the theoretical concepts and axioms of the policy

Intelligent Resource Management for Local Area Networks: Approach and Evolution

Science.gov (United States)

Meike, Roger

1988-01-01

The Data Management System network is a complex and important part of manned space platforms. Its efficient operation is vital to crew, subsystems and experiments. AI is being considered to aid in the initial design of the network and to augment the management of its operation. The Intelligent Resource Management for Local Area Networks (IRMA-LAN) project is concerned with the application of AI techniques to network configuration and management. A network simulation was constructed employing real time process scheduling for realistic loads, and utilizing the IEEE 802.4 token passing scheme. This simulation is an integral part of the construction of the IRMA-LAN system. From it, a causal model is being constructed for use in prediction and deep reasoning about the system configuration. An AI network design advisor is being added to help in the design of an efficient network. The AI portion of the system is planned to evolve into a dynamic network management aid. The approach, the integrated simulation, project evolution, and some initial results are described.

Mobility management in LTE heterogeneous networks

CERN Document Server

Karandikar, Abhay; Mehta, Mahima

2017-01-01

This book is the first of its kind, compiling information on the Long-Term Evolution (LTE) standards, which are enhanced to address new mobility-related challenges in Heterogeneous Networks (HetNets). It identifies the related challenges and discusses solutions and the simulation methodology for modeling HetNet mobility – cutting-edge information that was previously accessible only in the form of 3GPP specifications and documents, and research papers. The book reviews the current LTE mobility framework and discusses some of the changes for enhancing mobility management in HetNets. It describes the measurement procedures, handover (HO) mechanisms and HO success/failure scenarios. HetNets are intended to provide very high spectral efficiency while ensuring seamless coverage by deploying low-power nodes within the umbrella macrocell network. While mobility management in homogeneous networks is well understood, LTE standards are being enhanced to address the HetNet-specific mobility management challenges emergi...

Hierarchical Modelling of Flood Risk for Engineering Decision Analysis

DEFF Research Database (Denmark)

Custer, Rocco

protection structures in the hierarchical flood protection system - is identified. To optimise the design of protection structures, fragility and vulnerability models must allow for consideration of decision alternatives. While such vulnerability models are available for large protection structures (e...... systems, as well as the implementation of the flood risk analysis methodology and the vulnerability modelling approach are illustrated with an example application. In summary, the present thesis provides a characterisation of hierarchical flood protection systems as well as several methodologies to model...... and robust. Traditional risk management solutions, e.g. dike construction, are not particularly flexible, as they are difficult to adapt to changing risk. Conversely, the recent concept of integrated flood risk management, entailing a combination of several structural and non-structural risk management...

Social Networks and Sales Performance

Directory of Open Access Journals (Sweden)

Danny Pimentel Claro

2011-05-01

Full Text Available This paper argues that an informal network can itself be a basis for the increase in a sales manager’s performance. Informal networks create a structure that surpasses the formal hierarchical structure defined by the firm. We concentrated on the advice network and considered two different views of network structure that claim to have impact on performance. To explore this claim, we examined whether sales managers develop either a highly cohesive network structure (i.e. Coleman’s view or one containing structural holes (i.e. Burt’s view in order to achieve higher sales. We also investigated the matter of tie strength put forward by Granovetter in his seminal 1973 work. Census data was collected from about 500 personnel from an agricultural input retailer having 23 divisions. Estimates from a sample of 101 sales managers showed the importance of a highly cohesive structure (degree centrality for the three measures of sales manager’s performance. The strong ties have a positive impact on performance, suggesting the importance of building up strong bonds with network contacts. Sales managers’ age, time within the retailer and education also influence performance. These results imply that firms should stimulate contacts among personnel to spread technical and commercial information.

QoE management in wireless networks

CERN Document Server

Wang, Ying; Zhang, Ping

2017-01-01

This SpringerBrief presents research results on QoE management schemes for mobile services, including user services, and resource allocation. Along with a review of the research literature, it offers a data-driven architecture for personalized QoE management in wireless networks. The primary focus is on introducing efficient personalized character extraction mechanisms, e.g., context-aware Bayesian graph model, and cooperative QoE management mechanisms. Moreover, in order to demonstrate in the effectiveness of the QoE model, a QoE measurement platform is described and its collected data examined. The brief concludes with a discussion of future research directions. The example mechanisms and the data-driven architecture provide useful insights into the designs of QoE management, and motivate a new line of thinking for users' satisfaction in future wireless networks.

Resource Management in Broadband Communication Networks

DEFF Research Database (Denmark)

Hansen, Mads Stenhuus

2003-01-01

. The first part gives a brief description of some of the existing protocols for routing and controlling resources, such as RSVP, OSPF, BGP, PNNI, etc. The remaining part concerns the following two fundamentally different approaches to resource management etc.: - Software agents - Simulated ants......This thesis - Resource Management in Broadband Communication Networks - deals with different ways of optimizing the available resources of data- or telecommunication networks. Especially topics like optimal routing, load balancing and fast recovery of routes in case of link failures are covered...

MR-AFS: a global hierarchical file-system

International Nuclear Information System (INIS)

Reuter, H.

2000-01-01

The next generation of fusion experiments will use object-oriented technology creating the need for world wide sharing of an underlying hierarchical file-system. The Andrew file system (AFS) is a well known and widely spread global distributed file-system. Multiple-resident-AFS (MR-AFS) combines the features of AFS with hierarchical storage management systems. Files in MR-AFS therefore may be migrated on secondary storage, such as roboted tape libraries. MR-AFS is in use at IPP for the current experiments and data originating from super-computer applications. Experiences and scalability issues are discussed

Multiperiod Hierarchical Location Problem of Transit Hub in Urban Agglomeration Area

Directory of Open Access Journals (Sweden)

Ting-ting Li

2017-01-01

Full Text Available With the rapid urbanization in developing countries, urban agglomeration area (UAA forms. Also, transportation demand in UAA grows rapidly and presents hierarchical feature. Therefore, it is imperative to develop models for transit hubs to guide the development of UAA and better meet the time-varying and hierarchical transportation demand. In this paper, the multiperiod hierarchical location problem of transit hub in urban agglomeration area (THUAA is studied. A hierarchical service network of THUAA with a multiflow, nested, and noncoherent structure is described. Then a multiperiod hierarchical mathematical programming model is proposed, aiming at minimizing the total demand weighted travel time. Moreover, an improved adaptive clonal selection algorithm is presented to solve the model. Both the model and algorithm are verified by the application to a real-life problem of Beijing-Tianjin-Hebei Region in China. The results of different scenarios in the case show that urban population migration has a great impact on the THUAA location scheme. Sustained and appropriate urban population migration helps to reduce travel time for urban residents.

Managing Evolving Global Operations Networks

DEFF Research Database (Denmark)

Mykhaylenko, Alona; Wæhrens, Brian Vejrum; Johansen, John

2015-01-01

For many globally dispersed organisations, the home base (HB) is a historic locus of integrative and coordinating efforts that safeguard overall performance. However, the dynamism of global operations networks is increasingly pulling the centre of gravity away from the HB and dispersing it across...... the network, challenging the HB’s ability to sustain its centrality over time. To counteract this tendency, this paper addresses the gap in the literature regarding the development of the network management capability of the HB within the context of its network. Data was collected through a retrospective...... longitudinal case study of an intra-organisational operations network of one OEM and its three foreign subsidiaries. The findings suggest a row of strategic roles and corresponding managerial capabilities, which the HB needs to develop depending on the changing subsidiaries’ competencies and HB...

Restaurant Management System Over Private Network

Directory of Open Access Journals (Sweden)

Amanat Dhillon

2017-08-01

Full Text Available Restaurant Management System over Private Network is an automated business environment which allows restaurants to reduce operational costs increase efficiency of business improve customer satisfaction cut down labour costs decrease order processing time and provide better Quality-of-ServiceQ-S. This system manages a digital menu allowing the customers to place orders easily. Authentication fields for employees enable better administration of the restaurant. The whole restaurant is integrated into one private network thereby improving security and eliminating the need for a constant internet connection.

Key management issue in SCADA networks: A review

Directory of Open Access Journals (Sweden)

Abdalhossein Rezai

2017-02-01

Full Text Available Supervisory Control And Data Acquisition (SCADA networks have a vital role in Critical Infrastructures (CIs such as public transports, power generation systems, gas, water and oil industries, so that there are concerns on security issues in these networks. The utilized Remote Terminal Units (RTUs and Intelligence Electronic Devices (IEDs in these networks have resource limitations, which make security applications a challenging issue. Efficient key management schemes are required besides lightweight ciphers for securing the SCADA communications. Many key management schemes have been developed to address the tradeoff between SCADA constrain and security, but which scheme is the most effective is still debatable. This paper presents a review of the existing key management schemes in SCADA networks, which provides directions for further researches in this field.

Hierarchical structure of biological systems: a bioengineering approach.

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.

Obstacle Avoidance of a Mobile Robot with Hierarchical Structure

Energy Technology Data Exchange (ETDEWEB)

Park, Chan Gyu [Yeungnam College of Science and Technolgy, Taegu (Korea)

2001-06-01

This paper proposed a new hierarchical fuzzy-neural network algorithm for navigation of a mobile robot within unknown dynamic environment. Proposed navigation algorithm used the learning ability of the neural network and the feasibility of control highly nonlinear system of fuzzy theory. The proposed navigation algorithm used fuzzy algorithm for goal approach and fuzzy-network for effective collision avoidance. Some computer simulation results for a mobile robot equipped with ultrasonic range sensors show that the suggested navigation algorithm is very effective to escape in stationary and moving obstacles environment. (author). 11 refs., 14 figs., 2 tabs.

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.

Research of user access control for networked manufacturing system

Institute of Scientific and Technical Information of China (English)

ZHENG Xiao-lin; LEI Yu; CHEN De-ren

2006-01-01

An integrated user access control method was proposed to address the issues of security and management in networked manufacturing systems (NMS).Based on the analysis of the security issues in networked manufacturing system,an integrated user access control method composed of role-based access control (RBAC),task-based access control (TBAC),relationship-driven access control (RDAC)and coalition-based access control (CBAC) was proposed,including the hierarchical user relationship model,the reference model and the process model.The elements and their relationships were defined,and the expressions of constraints authorization were given.The extensible access control markup language (XACML) was used to implement this method.This method was used in the networked manufacturing system in the Shaoxing spinning region of China.The results show that the integrated user access control method can reduce the costs of system security maintenance and management.

Re-engineering Nascom's network management architecture

Science.gov (United States)

Drake, Brian C.; Messent, David

1994-01-01

The development of Nascom systems for ground communications began in 1958 with Project Vanguard. The low-speed systems (rates less than 9.6 Kbs) were developed following existing standards; but, there were no comparable standards for high-speed systems. As a result, these systems were developed using custom protocols and custom hardware. Technology has made enormous strides since the ground support systems were implemented. Standards for computer equipment, software, and high-speed communications exist and the performance of current workstations exceeds that of the mainframes used in the development of the ground systems. Nascom is in the process of upgrading its ground support systems and providing additional services. The Message Switching System (MSS), Communications Address Processor (CAP), and Multiplexer/Demultiplexer (MDM) Automated Control System (MACS) are all examples of Nascom systems developed using standards such as, X-windows, Motif, and Simple Network Management Protocol (SNMP). Also, the Earth Observing System (EOS) Communications (Ecom) project is stressing standards as an integral part of its network. The move towards standards has produced a reduction in development, maintenance, and interoperability costs, while providing operational quality improvement. The Facility and Resource Manager (FARM) project has been established to integrate the Nascom networks and systems into a common network management architecture. The maximization of standards and implementation of computer automation in the architecture will lead to continued cost reductions and increased operational efficiency. The first step has been to derive overall Nascom requirements and identify the functionality common to all the current management systems. The identification of these common functions will enable the reuse of processes in the management architecture and promote increased use of automation throughout the Nascom network. The MSS, CAP, MACS, and Ecom projects have indicated

Efficient network resource management for multimedia-on-demand services

Science.gov (United States)

Kuo, Chinhwa; Chiu, Jui-Hwa; Wu, Jong-Jyh; Chen, Dxo-Shin

1998-08-01

A Multimedia Instruction on Demand (MID) serves the purpose of providing an environment for lecture design, lecture annotation, and lecture review over networks. In order to support real-time multimedia interactive playback for such an application, the underlying networks are required to provide network resource management mechanism to enforce the reservation policy. In our design, the MID server and MID gateway consist of the following mechanisms, namely, resource management agent, admission control agent, packet classifier, and packet scheduler. We make use of the framework of the ReSerVation Protocol to devise and implement a network resource management mechanism, which control end-to-end packet delays and bandwidth allocation for the designed MID system. In the present paper, our contributions are as follows: (1) a network resource management scheme is designed to support real-time multimedia over the Internet and (2) an experimental test bed is established to measure the system performance. The developed scheme is currently being implemented in the Multimedia Information Networking laboratory at Tamkang University.

Optical Networks Solutions planning - performances - management

DEFF Research Database (Denmark)

Fenger, Christian

2002-01-01

It has been a decisive goal in the compilation of this thesis to make us capable of realizing the future national and regional telecommunication networks in an efficient and resource optimal way. By future telecommunication network is assumed an all optical network where the information in transit...... are kept optical and not converted into the optical domain. The focus is on the scientific results achieved throughout the Ph.D. period. Five subjects – all increasing the understanding of optical networks – are studied. Static wavelength routed optical networks are studied. Management on terms...... of lightpath allocation and design is considered. By using statistical models (simultaneous analysis of many networks) the correspondence between parameters determining the network topology and the performance of the optical network is found. These dependencies are important knowledge in the process...

Assembling nitrogen and oxygen co-doped graphene quantum dots onto hierarchical carbon networks for all-solid-state flexible supercapacitors

International Nuclear Information System (INIS)

Li, Zhen; Li, Yanfeng; Wang, Liang; Cao, Ling; Liu, Xiang; Chen, Zhiwen; Pan, Dengyu; Wu, Minghong

2017-01-01

Highlights: • The all-carbon ternary flexible electrodes have been fabricated by the electrode deposition of nitrogen and oxygen co-doped single-crystalline GQDs. • The flexible electrodes deliver ultrahigh specific capacitance (461 mF cm"−"2) by inducing a high concentration of active nitrogen and oxygen at edge. • Symmetrical N-O-GQD/CNT/CC all-solid-state flexible supercapacitors offer energy density up to 32 μWh cm"−"2 and demonstrate the good stability, high flexibility, and folding ability under different deformations. • Nitrogen and oxygen co-doped GQDs can function as a highly active, solution-processable pseudocapacitive materials applicable to high-performance supercapacitors. - Abstract: We present a novel approach for hierarchical fabrication of high-performance, all-solid-state, flexible supercapacitors from environmentally friendly all-carbon materials. Three-dimensional carbon nanotube/carbon cloth network (CNT/CC) is used as a conductive, flexible and free-standing scaffold for the electro-deposition of highly N/O co-doped graphene quantum dots to form the high-activity, all-carbon electrodes. The hierarchical structure of the CNT/CC network with high electrical conductivity and high surface area provides improved conductive pathways for the efficient activation of GQDs with high pseudocapacitance and electrical double layer capacitance. The obtained N-O-GQD/CNT/CC electrodes for all-solid-state flexible supercapacitors exhibit an ultrahigh areal capacitance of up to 461 mF cm"−"2 at a current density of 0.5 mA cm"−"2, while keeping high rate and cyclic performances. This work highlights the great potential of highly active GQDs in the construction of high-performance flexible energy-storage devices.

Automation of control and analysis of execution of official duties and instructions in the hierarchical organization

Directory of Open Access Journals (Sweden)

Demchenko A.I.

2017-01-01

Full Text Available The article considers the problem of monitoring over execution of official duties of employees. This problem is characteristic of the enterprises having a hierarchical management structure. The functions and the modes of monitoring are defined, the types of analysis of the staff activities are provided. The description of the program complex allowing distributing functions and instructions for between the employees is given. The developed computer program allows tracking the performance, creating reports. The computer program has a demarcation of access rights and provides the can be operated in both local, and a large-scale network.

Managing interdependencies in supplier networks

OpenAIRE

Catarina Roseira; Carlos Brito

2010-01-01

Building and managing a supplier base has been referred to in the literature as a key aspect of supplier management. Scholars have proposed a number of models aimed at enhancing the effectiveness of supplier network management, mainly based on a portfolio approach. In the IMP tradition of research, those models are often criticized as they ignore the interdependencies between the different existing dyadic relationships of a focal buyer company and its suppliers. Such interdependencies are the...

Nanoscale Analysis of a Hierarchical Hybrid Solar Cell in 3D.

Science.gov (United States)

Divitini, Giorgio; Stenzel, Ole; Ghadirzadeh, Ali; Guarnera, Simone; Russo, Valeria; Casari, Carlo S; Bassi, Andrea Li; Petrozza, Annamaria; Di Fonzo, Fabio; Schmidt, Volker; Ducati, Caterina

2014-05-01

A quantitative method for the characterization of nanoscale 3D morphology is applied to the investigation of a hybrid solar cell based on a novel hierarchical nanostructured photoanode. A cross section of the solar cell device is prepared by focused ion beam milling in a micropillar geometry, which allows a detailed 3D reconstruction of the titania photoanode by electron tomography. It is found that the hierarchical titania nanostructure facilitates polymer infiltration, thus favoring intermixing of the two semiconducting phases, essential for charge separation. The 3D nanoparticle network is analyzed with tools from stochastic geometry to extract information related to the charge transport in the hierarchical solar cell. In particular, the experimental dataset allows direct visualization of the percolation pathways that contribute to the photocurrent.

Earth-Mars Telecommunications and Information Management System (TIMS): Antenna Visibility Determination, Network Simulation, and Management Models

Science.gov (United States)

Odubiyi, Jide; Kocur, David; Pino, Nino; Chu, Don

1996-01-01

This report presents the results of our research on Earth-Mars Telecommunications and Information Management System (TIMS) network modeling and unattended network operations. The primary focus of our research is to investigate the feasibility of the TIMS architecture, which links the Earth-based Mars Operations Control Center, Science Data Processing Facility, Mars Network Management Center, and the Deep Space Network of antennae to the relay satellites and other communication network elements based in the Mars region. The investigation was enhanced by developing Build 3 of the TIMS network modeling and simulation model. The results of several 'what-if' scenarios are reported along with reports on upgraded antenna visibility determination software and unattended network management prototype.

Open Problems in Network-aware Data Management in Exa-scale Computing and Terabit Networking Era

Energy Technology Data Exchange (ETDEWEB)

Balman, Mehmet; Byna, Surendra

2011-12-06

Accessing and managing large amounts of data is a great challenge in collaborative computing environments where resources and users are geographically distributed. Recent advances in network technology led to next-generation high-performance networks, allowing high-bandwidth connectivity. Efficient use of the network infrastructure is necessary in order to address the increasing data and compute requirements of large-scale applications. We discuss several open problems, evaluate emerging trends, and articulate our perspectives in network-aware data management.

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

Wireless ad hoc and sensor networks management, performance, and applications

CERN Document Server

He, Jing

2013-01-01

Although wireless sensor networks (WSNs) have been employed across a wide range of applications, there are very few books that emphasize the algorithm description, performance analysis, and applications of network management techniques in WSNs. Filling this need, Wireless Ad Hoc and Sensor Networks: Management, Performance, and Applications summarizes not only traditional and classical network management techniques, but also state-of-the-art techniques in this area. The articles presented are expository, but scholarly in nature, including the appropriate history background, a review of current

Hierarchical control of vehicular fuel cell / battery hybrid powertrain

OpenAIRE

Xu, Liangfei; Ouyang, Minggao; Li, Jianqiu; Hua, Jianfeng

2010-01-01

In a proton exchange membrane (PEM) fuel cell/battery hybrid vehicle, a fuel cell system fulfills the stationary power demand, and a traction battery provides the accelerating power and recycles braking energy. The entire system is coordinated by a distributed control system, incorporating three key strategies: 1) vehicle control, 2) fuel cell control and 3) battery management. They make up a hierarchical control system. This paper introduces a hierarchical control strategy for a fuel cell / ...

A value network development model and implications for innovation and production network management

NARCIS (Netherlands)

Vermeulen, B.; Kok, de A.G.

2013-01-01

In managing their value network, firms have to balance current and future value concerns and own and network partners’ concerns. Firms generate immediate value through manufacturing and selling the current generation of products together with other firms in its production network and generate future

Hierarchical species distribution models

Science.gov (United States)

Hefley, Trevor J.; Hooten, Mevin B.

2016-01-01

Determining the distribution pattern of a species is important to increase scientific knowledge, inform management decisions, and conserve biodiversity. To infer spatial and temporal patterns, species distribution models have been developed for use with many sampling designs and types of data. Recently, it has been shown that count, presence-absence, and presence-only data can be conceptualized as arising from a point process distribution. Therefore, it is important to understand properties of the point process distribution. We examine how the hierarchical species distribution modeling framework has been used to incorporate a wide array of regression and theory-based components while accounting for the data collection process and making use of auxiliary information. The hierarchical modeling framework allows us to demonstrate how several commonly used species distribution models can be derived from the point process distribution, highlight areas of potential overlap between different models, and suggest areas where further research is needed.

SNMP-SI: A Network Management Tool Based on Slow Intelligence System Approach

Science.gov (United States)

Colace, Francesco; de Santo, Massimo; Ferrandino, Salvatore

The last decade has witnessed an intense spread of computer networks that has been further accelerated with the introduction of wireless networks. Simultaneously with, this growth has increased significantly the problems of network management. Especially in small companies, where there is no provision of personnel assigned to these tasks, the management of such networks is often complex and malfunctions can have significant impacts on their businesses. A possible solution is the adoption of Simple Network Management Protocol. Simple Network Management Protocol (SNMP) is a standard protocol used to exchange network management information. It is part of the Transmission Control Protocol/Internet Protocol (TCP/IP) protocol suite. SNMP provides a tool for network administrators to manage network performance, find and solve network problems, and plan for network growth. SNMP has a big disadvantage: its simple design means that the information it deals with is neither detailed nor well organized enough to deal with the expanding modern networking requirements. Over the past years much efforts has been given to improve the lack of Simple Network Management Protocol and new frameworks has been developed: A promising approach involves the use of Ontology. This is the starting point of this paper where a novel approach to the network management based on the use of the Slow Intelligence System methodologies and Ontology based techniques is proposed. Slow Intelligence Systems is a general-purpose systems characterized by being able to improve performance over time through a process involving enumeration, propagation, adaptation, elimination and concentration. Therefore, the proposed approach aims to develop a system able to acquire, according to an SNMP standard, information from the various hosts that are in the managed networks and apply solutions in order to solve problems. To check the feasibility of this model first experimental results in a real scenario are showed.

A Clustering Routing Protocol for Mobile Ad Hoc Networks

Directory of Open Access Journals (Sweden)

Jinke Huang

2016-01-01

Full Text Available The dynamic topology of a mobile ad hoc network poses a real challenge in the design of hierarchical routing protocol, which combines proactive with reactive routing protocols and takes advantages of both. And as an essential technique of hierarchical routing protocol, clustering of nodes provides an efficient method of establishing a hierarchical structure in mobile ad hoc networks. In this paper, we designed a novel clustering algorithm and a corresponding hierarchical routing protocol for large-scale mobile ad hoc networks. Each cluster is composed of a cluster head, several cluster gateway nodes, several cluster guest nodes, and other cluster members. The proposed routing protocol uses proactive protocol between nodes within individual clusters and reactive protocol between clusters. Simulation results show that the proposed clustering algorithm and hierarchical routing protocol provide superior performance with several advantages over existing clustering algorithm and routing protocol, respectively.

Design of IP Camera Access Control Protocol by Utilizing Hierarchical Group Key

Directory of Open Access Journals (Sweden)

Jungho Kang

2015-08-01

Full Text Available Unlike CCTV, security video surveillance devices, which we have generally known about, IP cameras which are connected to a network either with or without wire, provide monitoring services through a built-in web-server. Due to the fact that IP cameras can use a network such as the Internet, multiple IP cameras can be installed at a long distance and each IP camera can utilize the function of a web server individually. Even though IP cameras have this kind of advantage, it has difficulties in access control management and weakness in user certification, too. Particularly, because the market of IP cameras did not begin to be realized a long while ago, systems which are systematized from the perspective of security have not been built up yet. Additionally, it contains severe weaknesses in terms of access authority to the IP camera web server, certification of users, and certification of IP cameras which are newly installed within a network, etc. This research grouped IP cameras hierarchically to manage them systematically, and provided access control and data confidentiality between groups by utilizing group keys. In addition, IP cameras and users are certified by using PKI-based certification, and weak points of security such as confidentiality and integrity, etc., are improved by encrypting passwords. Thus, this research presents specific protocols of the entire process and proved through experiments that this method can be actually applied.

Social networks in cardiovascular disease management.

Science.gov (United States)

Shaya, Fadia T; Yan, Xia; Farshid, Maryam; Barakat, Samer; Jung, Miah; Low, Sara; Fedder, Donald

2010-12-01

Cardiovascular disease remains the leading cause of death in the USA. Social networks have a positive association with obesity, smoking cessation and weight loss. This article summarizes studies evaluating the impact of social networks on the management of cardiovascular disease. The 35 studies included in the article describe the impact of social networks on a decreased incidence of cardiovascular disease, depression and mortality. In addition, having a large-sized social network is also associated with better outcomes and improved health. The role of pharmacists is beginning to play an important role in the patient-centered medical home, which needs to be incorporated into social networks. The patient-centered medical home can serve as an adaptive source for social network evolvement.

IP, ethernet and MPLS networks resource and fault management

CERN Document Server

Perez, André

2013-01-01

This book summarizes the key Quality of Service technologies deployed in telecommunications networks: Ethernet, IP, and MPLS. The QoS of the network is made up of two parts: fault and resource management. Network operation quality is among the functions to be fulfilled in order to offer QoS to the end user. It is characterized by four parameters: packet loss, delay, jitter or the variation of delay over time, and availability. Resource management employs mechanisms that enable the first three parameters to be guaranteed or optimized. Fault management aims to ensure continuity of service.

Network Management System for (FUTON-like) Radio-over-Fiber Infrastructure

DEFF Research Database (Denmark)

Santiago, Carlos; Gangopadhyay, Bodhisattwa; Ramkumar, Venkata

2010-01-01

by the FUTON Middleware. Although a significant amount of prior research work can be found in the literature related to RoF, there is still significant lack of technologies concerning RoF networks management. RoF Manager and its sub-systems target to fill such gap, proposing a novel concept in the form...... operational costs. The RoF Network Manager manages the network equipment on the optical front haul between the Central Unit (CU) and all Remote Antenna Units (RAU)s connected by it, as well as the communication links, while enabling end-to-end service problem resolution and service quality management...

Self-management for unified heterogeneous radio access networks

NARCIS (Netherlands)

Litjens, R.; Gunnarsson, F.; Sayrac, B.; Spaey, K.; Willcock, C.; Eisenblätter, A.; Rodríguez, B.G.; Kürner, T.

2013-01-01

The development of self-management solutions for (multi-technology, multi-layer) mobile communication networks is driven by their increasing operational complexity. Initial stand-alone SON (Self-Organizing Networks) solutions are already available, but are not sufficient to handle the networks of

An Implementation of a Network Configuration Management System ...

African Journals Online (AJOL)

The job of the network administrator becomes difficult as the number of hosts in a computer network increase. Network management requires the network administrator to have vital configuration information about hosts so as to provide viable solutions. In situations where the hosts span a large area or in several buildings as ...

Value Systems Alignment Analysis in Collaborative Networked Organizations Management

Directory of Open Access Journals (Sweden)

Patricia Macedo

2017-11-01

Full Text Available The assessment of value systems alignment can play an important role in the formation and evolution of collaborative networks, contributing to reduce potential risks of collaboration. For this purpose, an assessment tool is proposed as part of a collaborative networks information system, supporting both the formation and evolution of long-term strategic alliances and goal-oriented networks. An implementation approach for value system alignment analysis is described, which is intended to assist managers in virtual and networked organizations management. The implementation of the assessment and analysis methods is supported by a set of software services integrated in the information system that supports the management of the networked organizations. A case study in the solar energy sector was conducted, and the data collected through this study allow us to confirm the practical applicability of the proposed methods and the software services.

SDN-Enabled Communication Network Framework for Energy Internet

Directory of Open Access Journals (Sweden)

Zhaoming Lu

2017-01-01

Full Text Available To support distributed energy generators and improve energy utilization, energy Internet has attracted global research focus. In China, energy Internet has been proposed as an important issue of government and institutes. However, managing a large amount of distributed generators requires smart, low-latency, reliable, and safe networking infrastructure, which cannot be supported by traditional networks in power grids. In order to design and construct smart and flexible energy Internet, we proposed a software defined network framework with both microgrid cluster level and global grid level designed by a hierarchical manner, which will bring flexibility, efficiency, and reliability for power grid networks. Finally, we evaluate and verify the performance of this framework in terms of latency, reliability, and security by both theoretical analysis and real-world experiments.

Statistical dynamics of ultradiffusion in hierarchical systems

International Nuclear Information System (INIS)

Gardner, S.

1987-01-01

In many types of disordered systems which exhibit frustration and competition, an ultrametric topology is found to exist in the space of allowable states. This ultrametric topology of states is associated with a hierarchical relaxation process called ultradiffusion. Ultradiffusion occurs in hierarchical non-linear (HNL) dynamical systems when constraints cause large scale, slow modes of motion to be subordinated to small scale, fast modes. Examples of ultradiffusion are found throughout condensed matter physics and critical phenomena (e.g. the states of spin glasses), in biophysics (e.g. the states of Hopfield networks) and in many other fields including layered computing based upon nonlinear dynamics. The statistical dynamics of ultradiffusion can be treated as a random walk on an ultrametric space. For reversible bifurcating ultrametric spaces the evolution equation governing the probability of a particle being found at site i at time t has a highly degenerate transition matrix. This transition matrix has a fractal geometry similar to the replica form proposed for spin glasses. The authors invert this fractal matrix using a recursive quad-tree (QT) method. Possible applications of hierarchical systems to communications and symbolic computing are discussed briefly

DARAL: A Dynamic and Adaptive Routing Algorithm for Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Francisco José Estévez

2016-06-01

Full Text Available The evolution of Smart City projects is pushing researchers and companies to develop more efficient embedded hardware and also more efficient communication technologies. These communication technologies are the focus of this work, presenting a new routing algorithm based on dynamically-allocated sub-networks and node roles. Among these features, our algorithm presents a fast set-up time, a reduced overhead and a hierarchical organization, which allows for the application of complex management techniques. This work presents a routing algorithm based on a dynamically-allocated hierarchical clustering, which uses the link quality indicator as a reference parameter, maximizing the network coverage and minimizing the control message overhead and the convergence time. The present work based its test scenario and analysis in the density measure, considered as a node degree. The routing algorithm is compared with some of the most well known routing algorithms for different scenario densities.

Algorithm of parallel: hierarchical transformation and its implementation on FPGA

Science.gov (United States)

Timchenko, Leonid I.; Petrovskiy, Mykola S.; Kokryatskay, Natalia I.; Barylo, Alexander S.; Dembitska, Sofia V.; Stepanikuk, Dmytro S.; Suleimenov, Batyrbek; Zyska, Tomasz; Uvaysova, Svetlana; Shedreyeva, Indira

2017-08-01

In this paper considers the algorithm of laser beam spots image classification in atmospheric-optical transmission systems. It discusses the need for images filtering using adaptive methods, using, for example, parallel-hierarchical networks. The article also highlights the need to create high-speed memory devices for such networks. Implementation and simulation results of the developed method based on the PLD are demonstrated, which shows that the presented method gives 15-20% better prediction results than similar methods.

Online professional networks for physicians: risk management.

Science.gov (United States)

Hyman, Jon L; Luks, Howard J; Sechrest, Randale

2012-05-01

The rapidly developing array of online physician-only communities represents a potential extraordinary advance in the availability of educational and informational resources to physicians. These online communities provide physicians with a new range of controls over the information they process, but use of this social media technology carries some risk. The purpose of this review was to help physicians manage the risks of online professional networking and discuss the potential benefits that may come with such networks. This article explores the risks and benefits of physicians engaging in online professional networking with peers and provides suggestions on risk management. Through an Internet search and literature review, we scrutinized available case law, federal regulatory code, and guidelines of conduct from professional organizations and consultants. We reviewed the OrthoMind.com site as a case example because it is currently the only online social network exclusively for orthopaedic surgeons. Existing case law suggests potential liability for orthopaedic surgeons who engage with patients on openly accessible social network platforms. Current society guidelines in both the United States and Britain provide sensible rules that may mitigate such risks. However, the overall lack of a strong body of legal opinions, government regulations as well as practical experience for most surgeons limit the suitability of such platforms. Closed platforms that are restricted to validated orthopaedic surgeons may limit these downside risks and hence allow surgeons to collaborate with one another both as clinicians and practice owners. Educating surgeons about the pros and cons of participating in these networking platforms is helping them more astutely manage risks and optimize benefits. This evolving online environment of professional interaction is one of few precedents, but the application of risk management strategies that physicians use in daily practice carries over

Modelling and Quantitative Analysis of LTRACK–A Novel Mobility Management Algorithm

Directory of Open Access Journals (Sweden)

Benedek Kovács

2006-01-01

Full Text Available This paper discusses the improvements and parameter optimization issues of LTRACK, a recently proposed mobility management algorithm. Mathematical modelling of the algorithm and the behavior of the Mobile Node (MN are used to optimize the parameters of LTRACK. A numerical method is given to determine the optimal values of the parameters. Markov chains are used to model both the base algorithm and the so-called loop removal effect. An extended qualitative and quantitative analysis is carried out to compare LTRACK to existing handover mechanisms such as MIP, Hierarchical Mobile IP (HMIP, Dynamic Hierarchical Mobility Management Strategy (DHMIP, Telecommunication Enhanced Mobile IP (TeleMIP, Cellular IP (CIP and HAWAII. LTRACK is sensitive to network topology and MN behavior so MN movement modelling is also introduced and discussed with different topologies. The techniques presented here can not only be used to model the LTRACK algorithm, but other algorithms too. There are many discussions and calculations to support our mathematical model to prove that it is adequate in many cases. The model is valid on various network levels, scalable vertically in the ISO-OSI layers and also scales well with the number of network elements.

Management and optimization of the CPCU network working

Energy Technology Data Exchange (ETDEWEB)

Silvain, D. (Compagnie Parisienne de Chauffage Urbain, 75 - Paris (FR))

1991-10-01

The CPCU steam distribution network is supplemented by a return network for the condensation water. The data system installed in 1988 provides, for the real time, management of the function of the two networks and a reduction in production costs. For the steam, data required in the network, the boiler houses and from external sources are processed by local network of five microprocessors and permit: - with time delay: technical and economic production optimizing calculations, or forecasts, for the following day, of the total required output and the procedure necessary for supplying this at the lowest cost; - in real time: on the basis of the forecasts for the previous day, creating the production instructions for the boiler houses and the instructions for the network remote control elements; - in case of an unexpected occurrence: immediate creation of new operating forecasts for the boiler houses for the establishing management data in real time. For the water, the system forecasts the volume to be returned to the boiler depending on the quantity of steam to be produced. Subsequently, an analysis is carried out in real time of pressures and outputs measured in the network for deriving valve movements and the pump stop/start procedure for guaranteeing the return of the water. The architecture, basic principles and software developed for this application can be used in other steam or water networks and, in a general manner, are adaptable for the management of any complex multi-supplier or multicustomer systems.

Cognitive resource management for heterogeneous cellular networks

CERN Document Server

Liu, Yongkang

2014-01-01

This Springer Brief focuses on cognitive resource management in heterogeneous cellular networks (Het Net) with small cell deployment for the LTE-Advanced system. It introduces the Het Net features, presents practical approaches using cognitive radio technology in accommodating small cell data relay and optimizing resource allocation and examines the effectiveness of resource management among small cells given limited coordination bandwidth and wireless channel uncertainty. The authors introduce different network characteristics of small cell, investigate the mesh of small cell access points in

ECO INVESTMENT PROJECT MANAGEMENT THROUGH TIME APPLYING ARTIFICIAL NEURAL NETWORKS

Directory of Open Access Journals (Sweden)

Tamara Gvozdenović

2007-06-01

Full Text Available he concept of project management expresses an indispensable approach to investment projects. Time is often the most important factor in these projects. The artificial neural network is the paradigm of data processing, which is inspired by the one used by the biological brain, and it is used in numerous, different fields, among which is the project management. This research is oriented to application of artificial neural networks in managing time of investment project. The artificial neural networks are used to define the optimistic, the most probable and the pessimistic time in PERT method. The program package Matlab: Neural Network Toolbox is used in data simulation. The feed-forward back propagation network is chosen.

Hierarchical Self Organizing Map for Novelty Detection using Mobile Robot with Robust Sensor

International Nuclear Information System (INIS)

Sha'abani, M N A H; Miskon, M F; Sakidin, H

2013-01-01

This paper presents a novelty detection method based on Self Organizing Map neural network using a mobile robot. Based on hierarchical neural network, the network is divided into three networks; position, orientation and sensor measurement network. A simulation was done to demonstrate and validate the proposed method using MobileSim. Three cases of abnormal events; new, missing and shifted objects are employed for performance evaluation. The result of detection was then filtered for false positive detection. The result shows that the inspection produced less than 2% false positive detection at high sensitivity settings

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.

Intentional risk management through complex networks analysis

CERN Document Server

Chapela, Victor; Moral, Santiago; Romance, Miguel

2015-01-01

This book combines game theory and complex networks to examine intentional technological risk through modeling. As information security risks are in constant evolution,  the methodologies and tools to manage them must evolve to an ever-changing environment. A formal global methodology is explained  in this book, which is able to analyze risks in cyber security based on complex network models and ideas extracted from the Nash equilibrium. A risk management methodology for IT critical infrastructures is introduced which provides guidance and analysis on decision making models and real situations. This model manages the risk of succumbing to a digital attack and assesses an attack from the following three variables: income obtained, expense needed to carry out an attack, and the potential consequences for an attack. Graduate students and researchers interested in cyber security, complex network applications and intentional risk will find this book useful as it is filled with a number of models, methodologies a...

Resource management: Hotel Zira human resource management department analysis

Directory of Open Access Journals (Sweden)

Petrović Jelena

2015-01-01

Full Text Available The world is changing at a fast pace in a number of different areas, economically, politically technologically and socially. All these facts have strong impact on how managers organize their work. Traditionally they focus on delivering efficiency through large bureaucracies which are hierarchical in nature, very much around process and stability. What this mitigates against perhaps it is innovation and flexibility. A demand is no longer predictable and service has to be equally flexible for demand that exists nowadays. The emergence of post bureaucratic organizations is about being leaner, flatter and being much more network-based. Within that network employees are being empowered to take responsibility for producing innovations themselves. In order to speed up the process it is critical to systematize the process of managing people in the back office. Human Resource Management strategies are being transformed by internal social networks and social human resource technologies to better collaborative, transition into social enterprises, and change the positioning of human resource departments from back office to front office activities. All of these subjects are applied and the case study of hotel Zira human resource department is explained and showed in detail with the specific questionnaire. One of the main challenges that human resource management is also facing is the talent management and the number one responsibility of leadership is how to manage talent, how to attract it, utilize and eventually retain it.

Revisiting the variation of clustering coefficient of biological networks suggests new modular structure.

Science.gov (United States)

Hao, Dapeng; Ren, Cong; Li, Chuanxing

2012-05-01

A central idea in biology is the hierarchical organization of cellular processes. A commonly used method to identify the hierarchical modular organization of network relies on detecting a global signature known as variation of clustering coefficient (so-called modularity scaling). Although several studies have suggested other possible origins of this signature, it is still widely used nowadays to identify hierarchical modularity, especially in the analysis of biological networks. Therefore, a further and systematical investigation of this signature for different types of biological networks is necessary. We analyzed a variety of biological networks and found that the commonly used signature of hierarchical modularity is actually the reflection of spoke-like topology, suggesting a different view of network architecture. We proved that the existence of super-hubs is the origin that the clustering coefficient of a node follows a particular scaling law with degree k in metabolic networks. To study the modularity of biological networks, we systematically investigated the relationship between repulsion of hubs and variation of clustering coefficient. We provided direct evidences for repulsion between hubs being the underlying origin of the variation of clustering coefficient, and found that for biological networks having no anti-correlation between hubs, such as gene co-expression network, the clustering coefficient doesn't show dependence of degree. Here we have shown that the variation of clustering coefficient is neither sufficient nor exclusive for a network to be hierarchical. Our results suggest the existence of spoke-like modules as opposed to "deterministic model" of hierarchical modularity, and suggest the need to reconsider the organizational principle of biological hierarchy.

Self-management of Hybrid Networks: Introduction, Pros and Cons

NARCIS (Netherlands)

Fioreze, Tiago; Pras, Aiko; Lehnert, Ralf

In the last decade ‘self-management’ has become a popular research theme within the networking community. While reading papers, one could get the impression that self-management is the obvious solution to solve many of the current network management problems. There are hardly any publications,

Evaluation of constrained mobility for programmability in network management

NARCIS (Netherlands)

Bohoris, C.; Liotta, A.; Pavlou, G.; Ambler, A.P.; Calo, S.B.; Kar, G.

2000-01-01

In recent years, a significant amount of research work has addressed the use of code mobility in network management. In this paper, we introduce first three aspects of code mobility and argue that constrained mobility offers a natural and easy approach to network management programmability. While

Security management of next generation telecommunications networks and services

CERN Document Server

Jacobs, Stuart

2014-01-01

This book will cover network management security issues and currently available security mechanisms by discussing how network architectures have evolved into the contemporary NGNs which support converged services (voice, video, TV, interactive information exchange, and classic data communications). It will also analyze existing security standards and their applicability to securing network management. This book will review 21st century security concepts of authentication, authorization, confidentiality, integrity, nonrepudiation, vulnerabilities, threats, risks, and effective approaches to enc

Strengthen Cloud Computing Security with Federal Identity Management Using Hierarchical Identity-Based Cryptography

Science.gov (United States)

Yan, Liang; Rong, Chunming; Zhao, Gansen

More and more companies begin to provide different kinds of cloud computing services for Internet users at the same time these services also bring some security problems. Currently the majority of cloud computing systems provide digital identity for users to access their services, this will bring some inconvenience for a hybrid cloud that includes multiple private clouds and/or public clouds. Today most cloud computing system use asymmetric and traditional public key cryptography to provide data security and mutual authentication. Identity-based cryptography has some attraction characteristics that seem to fit well the requirements of cloud computing. In this paper, by adopting federated identity management together with hierarchical identity-based cryptography (HIBC), not only the key distribution but also the mutual authentication can be simplified in the cloud.

Evolution of Hierarchical Structure and Spatial Pattern of Coastal Cities in China – Based on the Data of Distribution of Marine-Related Enterprises

Directory of Open Access Journals (Sweden)

Wang Lili

2017-11-01

Full Text Available In this paper, a comprehensive research of the evolution of the hierarchical structure and spatial pattern of coastal cities in China was conducted based on the data of distribution of the headquarters and subsidiaries of marine-related enterprises in 1995, 2005 and 2015 using the city network research method proposed by Taylor. The results of the empirical research showed: China’s coastal city network had an obvious hierarchical characteristics of “national coastal cityregional coastal city-sub-regional coastal city-local coastal city”, in the 20 years of development process, the hierarchies of coastal cities in China showed a hierarchical progressive evolution; in past 20 years, the spatial pattern and network structure of coastal cities in China tended to be complete, and the city network was more uniform, forming a “three tiers and three urban agglomerations” network structure; the strength of connection among the cities was obviously strengthened, and the efficiency of urban spatial connection was improved overall.

The Analysis of the Relationship between Communication Skills and the Establishment of Clark's Management Network among Sport Managers

Directory of Open Access Journals (Sweden)

Rasool NAZARI

2016-03-01

Full Text Available The purpose of this study was to analyze the relationship between communication skills and the establishment of Clark's Management Network among sport managers. This applied research is a kind of correlational – survey study. Statistical population consist ed of 140 sport managers working for sport organizations in Isfahan Province, which have been selected by stratified random sampling. Measurement tools included two questionnaires of Communication Skill (91% and Establishment of Clark's Management Network (87%. Descriptive and inferential statistical methods applied for statistical analysis using SPSS software. Results show that there is a relationship between communication skills and the establishment of Clark's Management Network among sport managers. I n addition, the feedback component has greater contribution to prediction of Clark's management network (p 0.05. In general, it can acknowledge that the communication skills are effective in the establishment of Clark's management network and cause to i mprove the management process of sport organizations' managers and to achieve to the organizational goals with high level of productivity.

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

In this paper, the control objectives of future active distribution networks with high penetration of renewables and flexible loads are analyzed and reviewed. From a state of the art review, the important control objectives seen from the perspective of a distribution system operator are identifie......-ordination and management of the network assets at different voltage levels and geographical locations. The paper finally shows the applicability of the multi-level control architecture to some of the key challenges in the distribution system operation by relevant scenarios....... to be hosting capacity improvement, high reliable operation and cost effective network management. Based on this review and a state of the art review concerning future distribution network control methods, a multi-level control architecture is constructed for an active distribution network, which satisfies...... 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...

Comparative Analysis of Different Protocols to Manage Large Scale Networks

OpenAIRE

Anil Rao Pimplapure; Dr Jayant Dubey; Prashant Sen

2013-01-01

In recent year the numbers, complexity and size is increased in Large Scale Network. The best example of Large Scale Network is Internet, and recently once are Data-centers in Cloud Environment. In this process, involvement of several management tasks such as traffic monitoring, security and performance optimization is big task for Network Administrator. This research reports study the different protocols i.e. conventional protocols like Simple Network Management Protocol and newly Gossip bas...

Evidence for a Functional Hierarchy of Association Networks.

Science.gov (United States)

Choi, Eun Young; Drayna, Garrett K; Badre, David

2018-05-01

Patient lesion and neuroimaging studies have identified a rostral-to-caudal functional gradient in the lateral frontal cortex (LFC) corresponding to higher-order (complex or abstract) to lower-order (simple or concrete) cognitive control. At the same time, monkey anatomical and human functional connectivity studies show that frontal regions are reciprocally connected with parietal and temporal regions, forming parallel and distributed association networks. Here, we investigated the link between the functional gradient of LFC regions observed during control tasks and the parallel, distributed organization of association networks. Whole-brain fMRI task activity corresponding to four orders of hierarchical control [Badre, D., & D'Esposito, M. Functional magnetic resonance imaging evidence for a hierarchical organization of the prefrontal cortex. Journal of Cognitive Neuroscience, 19, 2082-2099, 2007] was compared with a resting-state functional connectivity MRI estimate of cortical networks [Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., et al. The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106, 1125-1165, 2011]. Critically, at each order of control, activity in the LFC and parietal cortex overlapped onto a common association network that differed between orders. These results are consistent with a functional organization based on separable association networks that are recruited during hierarchical control. Furthermore, corticostriatal functional connectivity MRI showed that, consistent with their participation in functional networks, rostral-to-caudal LFC and caudal-to-rostral parietal regions had similar, order-specific corticostriatal connectivity that agreed with a striatal gating model of hierarchical rule use. Our results indicate that hierarchical cognitive control is subserved by parallel and distributed association networks, together forming

Querying on Federated Sensor Networks

Directory of Open Access Journals (Sweden)

Zuhal Can

2016-09-01

Full Text Available A Federated Sensor Network (FSN is a network of geographically distributed Wireless Sensor Networks (WSNs called islands. For querying on an FSN, we introduce the Layered Federated Sensor Network (L-FSN Protocol. For layered management, L-FSN provides communication among islands by its inter-island querying protocol by which a query packet routing path is determined according to some path selection policies. L-FSN allows autonomous management of each island by island-specific intra-island querying protocols that can be selected according to island properties. We evaluate the applicability of L-FSN and compare the L-FSN protocol with various querying protocols running on the flat federation model. Flat federation is a method to federate islands by running a single querying protocol on an entire FSN without distinguishing communication among and within islands. For flat federation, we select a querying protocol from geometrical, hierarchical cluster-based, hash-based, and tree-based WSN querying protocol categories. We found that a layered federation of islands by L-FSN increases the querying performance with respect to energy-efficiency, query resolving distance, and query resolving latency. Moreover, L-FSN’s flexibility of choosing intra-island querying protocols regarding the island size brings advantages on energy-efficiency and query resolving latency.

Easy synthesis of hierarchical carbon spheres with superior capacitive performance in supercapacitors.

Science.gov (United States)

Huang, Xinhua; Kim, Seok; Heo, Min Seon; Kim, Ji Eun; Suh, Hongsuk; Kim, Il

2013-10-01

An easy template-free approach to the fabrication of pure carbon microspheres has been achieved via direct pyrolysis of as-prepared polyaromatic hydrocarbons including polynaphthalene and polypyrene. The polyaromatics were synthesized from aromatic hydrocarbons (AHCs) using anhydrous zinc chloride as the Friedel-Crafts catalyst and chloromethyl methyl ether as a cross-linker. The experimental results show that the methylene bridges between phenyl rings generate a hierarchical porous polyaromatic precursor to form three-dimensionally (3D) interconnected micro-, meso-, and macroporous networks during carbonization. These hierarchical porous carbon aggregates of spherical carbon spheres exhibit faster ion transport/diffusion behavior and increased surface area usage in electric double-layer capacitors. Furthermore, micropores are present in the 3D interconnected network inside the cross-linked AHC-based carbon microspheres, thus imparting an exceptionally large, electrochemically accessible surface area for charge accumulation.

Fiber-wireless convergence in next-generation communication networks systems, architectures, and management

CERN Document Server

Chang, Gee-Kung; Ellinas, Georgios

2017-01-01

This book investigates new enabling technologies for Fi-Wi convergence. The editors discuss Fi-Wi technologies at the three major network levels involved in the path towards convergence: system level, network architecture level, and network management level. The main topics will be: a. At system level: Radio over Fiber (digitalized vs. analogic, standardization, E-band and beyond) and 5G wireless technologies; b. Network architecture level: NGPON, WDM-PON, BBU Hotelling, Cloud Radio Access Networks (C-RANs), HetNets. c. Network management level: SDN for convergence, Next-generation Point-of-Presence, Wi-Fi LTE Handover, Cooperative MultiPoint. • Addresses the Fi-Wi convergence issues at three different levels, namely at the system level, network architecture level, and network management level • Provides approaches in communication systems, network architecture, and management that are expected to steer the evolution towards fiber-wireless convergence • Contributions from leading experts in the field of...

Acquisition management of the Global Transportation Network

Science.gov (United States)

2001-08-02

This report discusses the acquisition management of the Global transportation Network by the U.S. Transportation Command. This report is one in a series of audit reports addressing DoD acquisition management of information technology systems. The Glo...

Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6.

Science.gov (United States)

Samuelraj, Ananthi Jebaseeli; Jayapal, Sundararajan

2015-01-01

Proxy Mobile IPV6 (PMIPV6) is a network based mobility management protocol which supports node's mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO) in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node's mobility should be modified to support group nodes' mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

Efficient Mobility Management Signalling in Network Mobility Supported PMIPV6

Directory of Open Access Journals (Sweden)

Ananthi Jebaseeli Samuelraj

2015-01-01

Full Text Available Proxy Mobile IPV6 (PMIPV6 is a network based mobility management protocol which supports node’s mobility without the contribution from the respective mobile node. PMIPV6 is initially designed to support individual node mobility and it should be enhanced to support mobile network movement. NEMO-BSP is an existing protocol to support network mobility (NEMO in PMIPV6 network. Due to the underlying differences in basic protocols, NEMO-BSP cannot be directly applied to PMIPV6 network. Mobility management signaling and data structures used for individual node’s mobility should be modified to support group nodes’ mobility management efficiently. Though a lot of research work is in progress to implement mobile network movement in PMIPV6, it is not yet standardized and each suffers with different shortcomings. This research work proposes modifications in NEMO-BSP and PMIPV6 to achieve NEMO support in PMIPV6. It mainly concentrates on optimizing the number and size of mobility signaling exchanged while mobile network or mobile network node changes its access point.

NETWORKS OF HEALTH CARE: A CHALLENGE TO SUS MANAGEMENT

Directory of Open Access Journals (Sweden)

Camila Dubow

2013-09-01

Full Text Available The article proposes a critical reflection, based on national law, scholarly, scientific, on the current development of Networks of Health Care, as a strategy for strengthening the Single Health System (SUS. Are weighted inefficiency of traditional ways of organizing care and management, the challenge of Network Health Care for comprehensive care and management mechanisms used in this process. The work provides subsidies for the care practices and health management are reflected, pointing strategies that result in disruptions of paradigms through a refocusing of attention in existing models. For networks of health care can be consolidated, is fundamental to political sensitivity of health managers with a commitment to build a new model of care, through the struggle to consolidate the SUS and the realization of the principles of universality, comprehensiveness and equity.

Numerical analysis of a neural network with hierarchically organized patterns

International Nuclear Information System (INIS)

Bacci, Silvia; Wiecko, Cristina; Parga, Nestor

1988-01-01

A numerical analysis of the retrieval behaviour of an associative memory model where the memorized patterns are stored hierarchically is performed. It is found that the model is able to categorize errors. For a finite number of categories, these are retrieved correctly even when the stored patterns are not. Instead, when they are allowed to increase with the number of neurons, their retrieval quality deteriorates above a critical category capacity. (Author)

Revisiting the variation of clustering coefficient of biological networks suggests new modular structure

Directory of Open Access Journals (Sweden)

Hao Dapeng

2012-05-01

Full Text Available Abstract Background A central idea in biology is the hierarchical organization of cellular processes. A commonly used method to identify the hierarchical modular organization of network relies on detecting a global signature known as variation of clustering coefficient (so-called modularity scaling. Although several studies have suggested other possible origins of this signature, it is still widely used nowadays to identify hierarchical modularity, especially in the analysis of biological networks. Therefore, a further and systematical investigation of this signature for different types of biological networks is necessary. Results We analyzed a variety of biological networks and found that the commonly used signature of hierarchical modularity is actually the reflection of spoke-like topology, suggesting a different view of network architecture. We proved that the existence of super-hubs is the origin that the clustering coefficient of a node follows a particular scaling law with degree k in metabolic networks. To study the modularity of biological networks, we systematically investigated the relationship between repulsion of hubs and variation of clustering coefficient. We provided direct evidences for repulsion between hubs being the underlying origin of the variation of clustering coefficient, and found that for biological networks having no anti-correlation between hubs, such as gene co-expression network, the clustering coefficient doesn’t show dependence of degree. Conclusions Here we have shown that the variation of clustering coefficient is neither sufficient nor exclusive for a network to be hierarchical. Our results suggest the existence of spoke-like modules as opposed to “deterministic model” of hierarchical modularity, and suggest the need to reconsider the organizational principle of biological hierarchy.

Memory Compression Techniques for Network Address Management in MPI

Energy Technology Data Exchange (ETDEWEB)

Guo, Yanfei; Archer, Charles J.; Blocksome, Michael; Parker, Scott; Bland, Wesley; Raffenetti, Ken; Balaji, Pavan

2017-05-29

MPI allows applications to treat processes as a logical collection of integer ranks for each MPI communicator, while internally translating these logical ranks into actual network addresses. In current MPI implementations the management and lookup of such network addresses use memory sizes that are proportional to the number of processes in each communicator. In this paper, we propose a new mechanism, called AV-Rankmap, for managing such translation. AV-Rankmap takes advantage of logical patterns in rank-address mapping that most applications naturally tend to have, and it exploits the fact that some parts of network address structures are naturally more performance critical than others. It uses this information to compress the memory used for network address management. We demonstrate that AV-Rankmap can achieve performance similar to or better than that of other MPI implementations while using significantly less memory.

Network resiliency through memory health monitoring and proactive management

Science.gov (United States)

Andrade Costa, Carlos H.; Cher, Chen-Yong; Park, Yoonho; Rosenburg, Bryan S.; Ryu, Kyung D.

2017-11-21

A method for managing a network queue memory includes receiving sensor information about the network queue memory, predicting a memory failure in the network queue memory based on the sensor information, and outputting a notification through a plurality of nodes forming a network and using the network queue memory, the notification configuring communications between the nodes.

A Hierarchical Feature Extraction Model for Multi-Label Mechanical Patent Classification

Directory of Open Access Journals (Sweden)

Jie Hu

2018-01-01

Full Text Available Various studies have focused on feature extraction methods for automatic patent classification in recent years. However, most of these approaches are based on the knowledge from experts in related domains. Here we propose a hierarchical feature extraction model (HFEM for multi-label mechanical patent classification, which is able to capture both local features of phrases as well as global and temporal semantics. First, a n-gram feature extractor based on convolutional neural networks (CNNs is designed to extract salient local lexical-level features. Next, a long dependency feature extraction model based on the bidirectional long–short-term memory (BiLSTM neural network model is proposed to capture sequential correlations from higher-level sequence representations. Then the HFEM algorithm and its hierarchical feature extraction architecture are detailed. We establish the training, validation and test datasets, containing 72,532, 18,133, and 2679 mechanical patent documents, respectively, and then check the performance of HFEMs. Finally, we compared the results of the proposed HFEM and three other single neural network models, namely CNN, long–short-term memory (LSTM, and BiLSTM. The experimental results indicate that our proposed HFEM outperforms the other compared models in both precision and recall.

Topics in Computational Bayesian Statistics With Applications to Hierarchical Models in Astronomy and Sociology

Science.gov (United States)

Sahai, Swupnil

This thesis includes three parts. The overarching theme is how to analyze structured hierarchical data, with applications to astronomy and sociology. The first part discusses how expectation propagation can be used to parallelize the computation when fitting big hierarchical bayesian models. This methodology is then used to fit a novel, nonlinear mixture model to ultraviolet radiation from various regions of the observable universe. The second part discusses how the Stan probabilistic programming language can be used to numerically integrate terms in a hierarchical bayesian model. This technique is demonstrated on supernovae data to significantly speed up convergence to the posterior distribution compared to a previous study that used a Gibbs-type sampler. The third part builds a formal latent kernel representation for aggregate relational data as a way to more robustly estimate the mixing characteristics of agents in a network. In particular, the framework is applied to sociology surveys to estimate, as a function of ego age, the age and sex composition of the personal networks of individuals in the United States.

Advanced information processing system: Input/output network management software

Science.gov (United States)

Nagle, Gail; Alger, Linda; Kemp, Alexander

1988-01-01

The purpose of this document is to provide the software requirements and specifications for the Input/Output Network Management Services for the Advanced Information Processing System. This introduction and overview section is provided to briefly outline the overall architecture and software requirements of the AIPS system before discussing the details of the design requirements and specifications of the AIPS I/O Network Management software. A brief overview of the AIPS architecture followed by a more detailed description of the network architecture.

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.

Dynamic spectrum management in green cognitive radio cellular networks

KAUST Repository

Sboui, Lokman; Ghazzai, Hakim; Rezki, Zouheir; Alouini, Mohamed-Slim

2018-01-01

In this paper, we propose a new cellular network operation scheme fulfilling the 5G requirements related to spectrum management and green communications. We focus on cognitive radio cellular networks in which both the primary network (PN

Research on University Network Teaching Platform (Blackboard in Teaching Management

Directory of Open Access Journals (Sweden)

Gou Zhao Xia

2016-01-01

Full Text Available With rapid development of online education; teaching platform based on the network, as a new instructional mode has become a hot topic in online teaching. In this paper, the he teaching situation and existing problems on online was analyzed by comparing the difference between network teaching platform and traditional classroom teaching. Then the strategies of network teaching management and the case, which is focusing on the characteristics of Blackboard with the application of network teaching management was presents.

Business communication in social networks: Content management and experiences

Directory of Open Access Journals (Sweden)

Miguel Ángel Nicolás

2014-11-01

Full Text Available Currently, management of communication in social networks has become an indispensable strategic activity and contributes directly to change the mode of relationship between business and its stakeholders. The first section of this paper presents a brief analysis of the results reported in different specialized national studies in social networks. We analyse the general activities that users prefer to do and activities that users value most brands on networks. If an organization wants to successfully manage their communication in social networks is very important to know the behaviour of the users and design strategies based on their status and economic activity. This paper presents a brief analysis of social branding through the classification of different corporate content posted on their networks.

Interoperable Communications for Hierarchical Heterogeneous Wireless Networks

Science.gov (United States)

2016-04-01

International Conference on Advanced Networks and Telecommuncations Systems (ANTS). 14-DEC-13, Kattankulathur, India. : , Husheng Li, Qi Zeng , Lijun Qian. GPS...correlation in space is too large, which implies that the correlation is overestimated. Other methods may be more accurate, faster or less memory ...limited, an intelligent mechanism is needed for the information selection and signaling design of the cross-network communication for collaborative

Wireless Sensing Node Network Management for Monitoring Landslide Disaster

International Nuclear Information System (INIS)

Takayama, S; Akiyama, J; Fujiki, T; Mokhtar, N A B

2013-01-01

This paper shows the network management and operation to monitor landslide disaster at slop of mountain and hill. Natural disasters damage a measuring system easily. It is necessary for the measuring system to be flexible and robust. The measuring network proposed in this paper is the telemetry system consisted of host system (HS) and local sensing nodes network system (LSNNS). LSNNS operates autonomously and sometimes is controlled by commands from HS. HS collects data/information of landslide disaster from LSNNS, and controls LSNNS remotely. HS and LSNNS are communicated by using 'cloud' system. The dual communication is very effective and convenient to manage a network system operation

Quantifying loopy network architectures.

Directory of Open Access Journals (Sweden)

Eleni Katifori

Full Text Available Biology presents many examples of planar distribution and structural networks having dense sets of closed loops. An archetype of this form of network organization is the vasculature of dicotyledonous leaves, which showcases a hierarchically-nested architecture containing closed loops at many different levels. Although a number of approaches have been proposed to measure aspects of the structure of such networks, a robust metric to quantify their hierarchical organization is still lacking. We present an algorithmic framework, the hierarchical loop decomposition, that allows mapping loopy networks to binary trees, preserving in the connectivity of the trees the architecture of the original graph. We apply this framework to investigate computer generated graphs, such as artificial models and optimal distribution networks, as well as natural graphs extracted from digitized images of dicotyledonous leaves and vasculature of rat cerebral neocortex. We calculate various metrics based on the asymmetry, the cumulative size distribution and the Strahler bifurcation ratios of the corresponding trees and discuss the relationship of these quantities to the architectural organization of the original graphs. This algorithmic framework decouples the geometric information (exact location of edges and nodes from the metric topology (connectivity and edge weight and it ultimately allows us to perform a quantitative statistical comparison between predictions of theoretical models and naturally occurring loopy graphs.

Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots.

Science.gov (United States)

Hagiwara, Yoshinobu; Inoue, Masakazu; Kobayashi, Hiroyoshi; Taniguchi, Tadahiro

2018-01-01

In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., "I am in my home" and "I am in front of the table," a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA). Object recognition results using convolutional neural network (CNN), hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL), and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

Hierarchical Spatial Concept Formation Based on Multimodal Information for Human Support Robots

Directory of Open Access Journals (Sweden)

Yoshinobu Hagiwara

2018-03-01

Full Text Available In this paper, we propose a hierarchical spatial concept formation method based on the Bayesian generative model with multimodal information e.g., vision, position and word information. Since humans have the ability to select an appropriate level of abstraction according to the situation and describe their position linguistically, e.g., “I am in my home” and “I am in front of the table,” a hierarchical structure of spatial concepts is necessary in order for human support robots to communicate smoothly with users. The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA. Object recognition results using convolutional neural network (CNN, hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL, and a set of location names are used, respectively, as features in vision, position, and word information. Experiments in forming hierarchical spatial concepts and evaluating how the proposed method can predict unobserved location names and position categories are performed using a robot in the real world. Results verify that, relative to comparable baseline methods, the proposed method enables a robot to predict location names and position categories closer to predictions made by humans. As an application example of the proposed method in a home environment, a demonstration in which a human support robot moves to an instructed place based on human speech instructions is achieved based on the formed hierarchical spatial concept.

Managing Actors, Resources, and Activities in Innovation Ecosystems – A Design Science Approach

OpenAIRE

Valkokari , Katri; Amitrano , Cristina ,; Bifulco , Francesco; Valjakka , Tiina

2016-01-01

Part 13: Design Science and Business Models - Design Science Research; International audience; Through a design science approach, the paper explores how actors in a network create and sustain competitive advantage independently and through participation in a system of actors (i.e., a collaborative network) who are not hierarchically managed but, rather, act toward their own goals within the innovation ecosystem. In accordance with design studies, the relevance of research and its quality are ...

Velocity-Aware Handover Management in Two-Tier Cellular Networks

KAUST Repository

Arshad, Rabe; Elsawy, Hesham; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

2017-01-01

by network densification. Hence, user mobility imposes a nontrivial challenge to harvest capacity gains via network densification. In this paper, we propose a velocity-aware HO management scheme for two-tier downlink cellular network to mitigate the HO effect

Dynamic Subsidy Method for Congestion Management in Distribution Networks

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei

2016-01-01

Dynamic subsidy (DS) is a locational price paid by the distribution system operator (DSO) to its customers in order to shift energy consumption to designated hours and nodes. It is promising for demand side management and congestion management. This paper proposes a new DS method for congestion...... management in distribution networks, including the market mechanism, the mathematical formulation through a two-level optimization, and the method solving the optimization by tightening the constraints and linearization. Case studies were conducted with a one node system and the Bus 4 distribution network...... of the Roy Billinton Test System (RBTS) with high penetration of electric vehicles (EVs) and heat pumps (HPs). The case studies demonstrate the efficacy of the DS method for congestion management in distribution networks. Studies in this paper show that the DS method offers the customers a fair opportunity...

Modeling for the management of peak loads on a radiology image management network

International Nuclear Information System (INIS)

Dwyer, S.J.; Cox, G.G.; Templeton, A.W.; Cook, L.T.; Anderson, W.H.; Hensley, K.S.

1987-01-01

The design of a radiology image management network for a radiology department can now be assisted by a queueing model. The queueing model requires that the designers specify the following parameters: the number of tasks to be accomplished (acquisition of image data, transmission of data, archiving of data, displaying and manipulation of data, and generation of hard copies); the average times to complete each task; the patient scheduled arrival times; and the number/type of computer nodes interfaced to the network (acquisition nodes, interactive diagnostic display stations, archiving nodes, hard copy nodes, and gateways to hospital systems). The outcomes from the queuering model include mean throughput data rates and identified bottlenecks, and peak throughput data rates and identified bottlenecks. This exhibit presents the queueing model and illustrates its use in managing peak loads on an image management network

An Overview of Optical Network Bandwidth and Fault Management

Directory of Open Access Journals (Sweden)

J.A. Zubairi

2010-09-01

Full Text Available This paper discusses the optical network management issues and identifies potential areas for focused research. A general outline of the main components in optical network management is given and specific problems in GMPLS based model are explained. Later, protection and restoration issues are discussed in the broader context of fault management and the tools developed for fault detection are listed. Optical networks need efficient and reliable protection schemes that restore the communications quickly on the occurrence of faults without causing failure of real-time applications using the network. A holistic approach is required that provides mechanisms for fault detection, rapid restoration and reversion in case of fault resolution. Since the role of SDH/SONET is diminishing, the modern optical networks are poised towards the IP-centric model where high performance IP-MPLS routers manage a core intelligent network of IP over WDM. Fault management schemes are developed for both the IP layer and the WDM layer. Faults can be detected and repaired locally and also through centralized network controller. A hybrid approach works best in detecting the faults where the domain controller verifies the established LSPs in addition to the link tests at the node level. On detecting a fault, rapid restoration can perform localized routing of traffic away from the affected port and link. The traffic may be directed to pre-assigned backup paths that are established as shared or dedicated resources. We examine the protection issues in detail including the choice of layer for protection, implementing protection or restoration, backup path routing, backup resource efficiency, subpath protection, QoS traffic survival and multilayer protection triggers and alarm propagation. The complete protection cycle is described and mechanisms incorporated into RSVP-TE and other protocols for detecting and recording path errors are outlined. In addition, MPLS testbed

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.

Traffic Steering Framework for Mobile-Assisted Resource Management in Heterogeneous Networks

DEFF Research Database (Denmark)

Dogadaev, Anton Konstantinovich; Checko, Aleksandra; Popovska Avramova, Andrijana

2013-01-01

With the expected growth of mobile data traffic it is essential to manage the network resources efficiently. In order to undertake this challenge, we propose a framework for network-centric, mobile-assisted resource management, which facilitates traffic offloading from mobile network to Wi-Fi...... to the network backbone. What is more, we give an overview of existing standardization activities on offloading the mobile traffic through Wi-Fi....

Emergency Communications Network for Disasters Management in Venezuela

Science.gov (United States)

Burguillos, C.; Deng, H.

2018-04-01

The integration and use of different space technology applications for disasters management, play an important role at the time of prevents the causes and mitigates the effects of the natural disasters. Nevertheless, the space technology counts with the appropriate technological resources to provide the accurate and timely information required to support in the decision making in case of disasters. Considering the aforementioned aspects, in this research is presented the design and implementation of an Emergency Communications Network for Disasters Management in Venezuela. Network based on the design of a topology that integrates the satellites platforms in orbit operation under administration of Venezuelan state, such as: the communications satellite VENESAT-1 and the remote sensing satellites VRSS-1 and VRSS-2; as well as their ground stations with the aim to implement an emergency communications network to be activated in case of disasters which affect the public and private communications infrastructures in Venezuela. In this regard, to design the network several technical and operational specifications were formulated, between them: Emergency Strategies to Maneuver the VRSS-1 and VRSS-2 satellites for optimal images capture and processing, characterization of the VENESAT-1 transponders and radiofrequencies for emergency communications services, technologies solutions formulation and communications links design for disaster management. As result, the emergency network designed allows to put in practice diverse communications technologies solutions and different scheme or media for images exchange between the areas affected for disasters and the entities involved in the disasters management tasks, providing useful data for emergency response and infrastructures recovery.

Design and Management of Networked Information Systems

DEFF Research Database (Denmark)

Havn, Erling; Bansler, Jørgen P.

1996-01-01

In this paper, we present a newly started research project at the Center for Tele-Information at the Technical University of Denmark. The project focuses on the design and management of networked information systems, that is computer-based IS linked by a wide area network and supporting...... research questions:1. What is the essence of the new managerial theories and models and how do they define the role of telecommunications and IT in organizations?2. How are these organizational theories and models implemented in practice?3. How is the design and implementation of information systems...... and networks actually organized and carried out?4. What are the consequences for work content, skills, working conditions, etc.? The research project consists of a theoretical analysis of contemporary management theories as well as a number of in-depth case studies of firms engaged in the design...

An Efficient Method for Detecting Misbehaving Zone Manager in MANET

Science.gov (United States)

Rafsanjani, Marjan Kuchaki; Pakzad, Farzaneh; Asadinia, Sanaz

In recent years, one of the wireless technologies increased tremendously is mobile ad hoc networks (MANETs) in which mobile nodes organize themselves without the help of any predefined infrastructure. MANETs are highly vulnerable to attack due to the open medium, dynamically changing network topology, cooperative algorithms, lack of centralized monitoring, management point and lack of a clear defense line. In this paper, we report our progress in developing intrusion detection (ID) capabilities for MANET. In our proposed scheme, the network with distributed hierarchical architecture is partitioned into zones, so that in each of them there is one zone manager. The zone manager is responsible for monitoring the cluster heads in its zone and cluster heads are in charge of monitoring their members. However, the most important problem is how the trustworthiness of the zone manager can be recognized. So, we propose a scheme in which "honest neighbors" of zone manager specify the validation of their zone manager. These honest neighbors prevent false accusations and also allow manager if it is wrongly misbehaving. However, if the manger repeats its misbehavior, then it will lose its management degree. Therefore, our scheme will be improved intrusion detection and also provide a more reliable network.

Virtualized cloud data center networks issues in resource management

CERN Document Server

Tsai, Linjiun

2016-01-01

This book discusses the characteristics of virtualized cloud networking, identifies the requirements of cloud network management, and illustrates the challenges in deploying virtual clusters in multi-tenant cloud data centers. The book also introduces network partitioning techniques to provide contention-free allocation, topology-invariant reallocation, and highly efficient resource utilization, based on the Fat-tree network structure. Managing cloud data center resources without considering resource contentions among different cloud services and dynamic resource demands adversely affects the performance of cloud services and reduces the resource utilization of cloud data centers. These challenges are mainly due to strict cluster topology requirements, resource contentions between uncooperative cloud services, and spatial/temporal data center resource fragmentation. Cloud data center network resource allocation/reallocation which cope well with such challenges will allow cloud services to be provisioned with ...

Design Management in the Textile Industry - A Network Perspective

DEFF Research Database (Denmark)

Christensen, Poul Rind; Bang, Anne Louise

In this paper we explore textile design activities and textile design management from an industrial network perspective. The textile industry is probably one of the most globalized manufacturing industries in the world and thus one of the most dispersed industries on the globe. Most studies on de...... management in order to maintain the relationships in their network of customers and suppliers....