SOCIOLOGICAL UNDERSTANDING OF INTERNET: THEORETICAL APPROACHES TO THE NETWORK ANALYSIS
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D. E. Dobrinskaya
2016-01-01
Full Text Available The network is an efficient way of social structure analysis for contemporary sociologists. It gives broad opportunities for detailed and fruitful research of different patterns of ties and social relations by quantitative analytical methods and visualization of network models. The network metaphor is used as the most representative tool for description of a new type of society. This new type is characterized by flexibility, decentralization and individualization. Network organizational form became the dominant form in modern societies. The network is also used as a mode of inquiry. Actually three theoretical network approaches in the Internet research case are the most relevant: social network analysis, “network society” theory and actor-network theory. Every theoretical approach has got its own notion of network. Their special methodological and theoretical features contribute to the Internet studies in different ways. The article represents a brief overview of these network approaches. This overview demonstrates the absence of a unified semantic space of the notion of “network” category. This fact, in turn, points out the need for detailed analysis of these approaches to reveal their theoretical and empirical possibilities in application to the Internet studies.
Mathematical and theoretical neuroscience cell, network and data analysis
Nieus, Thierry
2017-01-01
This volume gathers contributions from theoretical, experimental and computational researchers who are working on various topics in theoretical/computational/mathematical neuroscience. The focus is on mathematical modeling, analytical and numerical topics, and statistical analysis in neuroscience with applications. The following subjects are considered: mathematical modelling in Neuroscience, analytical and numerical topics; statistical analysis in Neuroscience; Neural Networks; Theoretical Neuroscience. The book is addressed to researchers involved in mathematical models applied to neuroscience.
SOCIOLOGICAL UNDERSTANDING OF INTERNET: THEORETICAL APPROACHES TO THE NETWORK ANALYSIS
Directory of Open Access Journals (Sweden)
D. E. Dobrinskaya
2016-01-01
Full Text Available Internet studies are carried out by various scientific disciplines and in different research perspectives. Sociological studies of the Internet deal with a new technology, a revolutionary means of mass communication and a social space. There is a set of research difficulties associated with the Internet. Firstly, the high speed and wide spread of Internet technologies’ development. Secondly, the collection and filtration of materials concerning with Internet studies. Lastly, the development of new conceptual categories, which are able to reflect the impact of the Internet development in contemporary world. In that regard the question of the “network” category use is essential. Network is the base of Internet functioning, on the one hand. On the other hand, network is the ground for almost all social interactions in modern society. So such society is called network society. Three theoretical network approaches in the Internet research case are the most relevant: network society theory, social network analysis and actor-network theory. Each of these theoretical approaches contributes to the study of the Internet. They shape various images of interactions between human beings in their entity and dynamics. All these approaches also provide information about the nature of these interactions.
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.
Graph theoretical analysis of resting magnetoencephalographic functional connectivity networks
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Lindsay eRutter
2013-07-01
Full Text Available Complex networks have been observed to comprise small-world properties, believed to represent an optimal organization of local specialization and global integration of information processing at reduced wiring cost. Here, we applied magnitude squared coherence to resting magnetoencephalographic time series in reconstructed source space, acquired from controls and patients with schizophrenia, and generated frequency-dependent adjacency matrices modeling functional connectivity between virtual channels. After configuring undirected binary and weighted graphs, we found that all human networks demonstrated highly localized clustering and short characteristic path lengths. The most conservatively thresholded networks showed efficient wiring, with topographical distance between connected vertices amounting to one-third as observed in surrogate randomized topologies. Nodal degrees of the human networks conformed to a heavy-tailed exponentially truncated power-law, compatible with the existence of hubs, which included theta and alpha bilateral cerebellar tonsil, beta and gamma bilateral posterior cingulate, and bilateral thalamus across all frequencies. We conclude that all networks showed small-worldness, minimal physical connection distance, and skewed degree distributions characteristic of physically-embedded networks, and that these calculations derived from graph theoretical mathematics did not quantifiably distinguish between subject populations, independent of bandwidth. However, post-hoc measurements of edge computations at the scale of the individual vertex revealed trends of reduced gamma connectivity across the posterior medial parietal cortex in patients, an observation consistent with our prior resting activation study that found significant reduction of synthetic aperture magnetometry gamma power across similar regions. The basis of these small differences remains unclear.
Haraldsdóttir, Hulda S.; Fleming, Ronan M. T.
2016-01-01
Conserved moieties are groups of atoms that remain intact in all reactions of a metabolic network. Identification of conserved moieties gives insight into the structure and function of metabolic networks and facilitates metabolic modelling. All moiety conservation relations can be represented as nonnegative integer vectors in the left null space of the stoichiometric matrix corresponding to a biochemical network. Algorithms exist to compute such vectors based only on reaction stoichiometry but their computational complexity has limited their application to relatively small metabolic networks. Moreover, the vectors returned by existing algorithms do not, in general, represent conservation of a specific moiety with a defined atomic structure. Here, we show that identification of conserved moieties requires data on reaction atom mappings in addition to stoichiometry. We present a novel method to identify conserved moieties in metabolic networks by graph theoretical analysis of their underlying atom transition networks. Our method returns the exact group of atoms belonging to each conserved moiety as well as the corresponding vector in the left null space of the stoichiometric matrix. It can be implemented as a pipeline of polynomial time algorithms. Our implementation completes in under five minutes on a metabolic network with more than 4,000 mass balanced reactions. The scalability of the method enables extension of existing applications for moiety conservation relations to genome-scale metabolic networks. We also give examples of new applications made possible by elucidating the atomic structure of conserved moieties. PMID:27870845
Deep neural networks for texture classification-A theoretical analysis.
Basu, Saikat; Mukhopadhyay, Supratik; Karki, Manohar; DiBiano, Robert; Ganguly, Sangram; Nemani, Ramakrishna; Gayaka, Shreekant
2018-01-01
We investigate the use of Deep Neural Networks for the classification of image datasets where texture features are important for generating class-conditional discriminative representations. To this end, we first derive the size of the feature space for some standard textural features extracted from the input dataset and then use the theory of Vapnik-Chervonenkis dimension to show that hand-crafted feature extraction creates low-dimensional representations which help in reducing the overall excess error rate. As a corollary to this analysis, we derive for the first time upper bounds on the VC dimension of Convolutional Neural Network as well as Dropout and Dropconnect networks and the relation between excess error rate of Dropout and Dropconnect networks. The concept of intrinsic dimension is used to validate the intuition that texture-based datasets are inherently higher dimensional as compared to handwritten digits or other object recognition datasets and hence more difficult to be shattered by neural networks. We then derive the mean distance from the centroid to the nearest and farthest sampling points in an n-dimensional manifold and show that the Relative Contrast of the sample data vanishes as dimensionality of the underlying vector space tends to infinity. Copyright © 2017 Elsevier Ltd. All rights reserved.
Peer influence in network markets: a theoretical and empirical analysis
J. Henkel (Joachim); J.H. Block (Jörn)
2013-01-01
textabstractNetwork externalities spur the growth of networks and the adoption of network goods in two ways. First, they make it more attractive to join a network the larger its installed base. Second, they create incentives for network members to actively recruit new members. Despite indications
Graph theoretic analysis of protein interaction networks of eukaryotes
Goh, K.-I.; Kahng, B.; Kim, D.
2005-11-01
Owing to the recent progress in high-throughput experimental techniques, the datasets of large-scale protein interactions of prototypical multicellular species, the nematode worm Caenorhabditis elegans and the fruit fly Drosophila melanogaster, have been assayed. The datasets are obtained mainly by using the yeast hybrid method, which contains false-positive and false-negative simultaneously. Accordingly, while it is desirable to test such datasets through further wet experiments, here we invoke recent developed network theory to test such high-throughput datasets in a simple way. Based on the fact that the key biological processes indispensable to maintaining life are conserved across eukaryotic species, and the comparison of structural properties of the protein interaction networks (PINs) of the two species with those of the yeast PIN, we find that while the worm and yeast PIN datasets exhibit similar structural properties, the current fly dataset, though most comprehensively screened ever, does not reflect generic structural properties correctly as it is. The modularity is suppressed and the connectivity correlation is lacking. Addition of interologs to the current fly dataset increases the modularity and enhances the occurrence of triangular motifs as well. The connectivity correlation function of the fly, however, remains distinct under such interolog additions, for which we present a possible scenario through an in silico modeling.
Graph theoretical analysis and application of fMRI-based brain network in Alzheimer's disease
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LIU Xue-na
2012-08-01
Full Text Available Alzheimer's disease (AD, a progressive neurodegenerative disease, is clinically characterized by impaired memory and many other cognitive functions. However, the pathophysiological mechanisms underlying the disease are not thoroughly understood. In recent years, using functional magnetic resonance imaging (fMRI as well as advanced graph theory based network analysis approach, several studies of patients with AD suggested abnormal topological organization in both global and regional properties of functional brain networks, specifically, as demonstrated by a loss of small-world network characteristics. These studies provide novel insights into the pathophysiological mechanisms of AD and could be helpful in developing imaging biomarkers for disease diagnosis. In this paper we introduce the essential concepts of complex brain networks theory, and review recent advances of the study on human functional brain networks in AD, especially focusing on the graph theoretical analysis of small-world network based on fMRI. We also propound the existent problems and research orientation.
Song, Kaida; Wang, Rui; Liu, Yi; Qian, Depei; Zhang, Han; Cai, Jihong
2015-01-01
Community networks, the distinguishing feature of which is membership admittance, appear on P2P networks, social networks, and conventional Web networks. Joining the network costs money, time or network bandwidth, but the individuals get access to special resources owned by the community in return. The prosperity and stability of the community are determined by both the policy of admittance and the attraction of the privileges gained by joining. However, some misbehaving users can get the dedicated resources with some illicit and low-cost approaches, which introduce instability into the community, a phenomenon that will destroy the membership policy. In this paper, we analyze on the stability using game theory on such a phenomenon. We propose a game-theoretical model of stability analysis in community networks and provide conditions for a stable community. We then extend the model to analyze the effectiveness of different incentive policies, which could be used when the community cannot maintain its members in certain situations. Then we verify those models through a simulation. Finally, we discuss several ways to promote community network's stability by adjusting the network's properties and give some proposal on the designs of these types of networks from the points of game theory and stability.
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Kaida Song
Full Text Available Community networks, the distinguishing feature of which is membership admittance, appear on P2P networks, social networks, and conventional Web networks. Joining the network costs money, time or network bandwidth, but the individuals get access to special resources owned by the community in return. The prosperity and stability of the community are determined by both the policy of admittance and the attraction of the privileges gained by joining. However, some misbehaving users can get the dedicated resources with some illicit and low-cost approaches, which introduce instability into the community, a phenomenon that will destroy the membership policy. In this paper, we analyze on the stability using game theory on such a phenomenon. We propose a game-theoretical model of stability analysis in community networks and provide conditions for a stable community. We then extend the model to analyze the effectiveness of different incentive policies, which could be used when the community cannot maintain its members in certain situations. Then we verify those models through a simulation. Finally, we discuss several ways to promote community network's stability by adjusting the network's properties and give some proposal on the designs of these types of networks from the points of game theory and stability.
New Theoretical Analysis of the LRRM Calibration Technique for Vector Network Analyzers
Purroy Martín, Francesc; Pradell i Cara, Lluís
2001-01-01
In this paper, a new theoretical analysis of the four-standards line-reflect-reflect-match (LRRM) vector network-analyzer (VNA) calibration technique is presented. As a result, it is shown that the reference-impedance (to which the LRRM calibration is referred) cannot generally be defined whenever nonideal standards are used. Based on this consideration, a new algorithm to determine the on-wafer match standard is proposed that improves the LRRM calibration accuracy. Experimental verification ...
Graph theoretical analysis of functional network for comprehension of sign language.
Liu, Lanfang; Yan, Xin; Liu, Jin; Xia, Mingrui; Lu, Chunming; Emmorey, Karen; Chu, Mingyuan; Ding, Guosheng
2017-09-15
Signed languages are natural human languages using the visual-motor modality. Previous neuroimaging studies based on univariate activation analysis show that a widely overlapped cortical network is recruited regardless whether the sign language is comprehended (for signers) or not (for non-signers). Here we move beyond previous studies by examining whether the functional connectivity profiles and the underlying organizational structure of the overlapped neural network may differ between signers and non-signers when watching sign language. Using graph theoretical analysis (GTA) and fMRI, we compared the large-scale functional network organization in hearing signers with non-signers during the observation of sentences in Chinese Sign Language. We found that signed sentences elicited highly similar cortical activations in the two groups of participants, with slightly larger responses within the left frontal and left temporal gyrus in signers than in non-signers. Crucially, further GTA revealed substantial group differences in the topologies of this activation network. Globally, the network engaged by signers showed higher local efficiency (t (24) =2.379, p=0.026), small-worldness (t (24) =2.604, p=0.016) and modularity (t (24) =3.513, p=0.002), and exhibited different modular structures, compared to the network engaged by non-signers. Locally, the left ventral pars opercularis served as a network hub in the signer group but not in the non-signer group. These findings suggest that, despite overlap in cortical activation, the neural substrates underlying sign language comprehension are distinguishable at the network level from those for the processing of gestural action. Copyright © 2017 Elsevier B.V. All rights reserved.
Zhuang, Jun
2015-01-01
Maximizing reader insights into the roles of intelligent agents in networks, air traffic and emergency departments, this volume focuses on congestion in systems where safety and security are at stake, devoting special attention to applying game theoretic analysis of congestion to: protocols in wired and wireless networks; power generation, air transportation and emergency department overcrowding. Reviewing exhaustively the key recent research into the interactions between game theory, excessive crowding, and safety and security elements, this book establishes a new research angle by illustrating linkages between the different research approaches and serves to lay the foundations for subsequent analysis. Congestion (excessive crowding) is defined in this work as all kinds of flows; e.g., road/sea/air traffic, people, data, information, water, electricity, and organisms. Analyzing systems where congestion occurs – which may be in parallel, series, interlinked, or interdependent, with flows one way or both way...
Li, Yue; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Yue Li; Jha, Devesh K; Ray, Asok; Wettergren, Thomas A; Wettergren, Thomas A; Li, Yue; Ray, Asok; Jha, Devesh K
2018-06-01
This paper presents information-theoretic performance analysis of passive sensor networks for detection of moving targets. The proposed method falls largely under the category of data-level information fusion in sensor networks. To this end, a measure of information contribution for sensors is formulated in a symbolic dynamics framework. The network information state is approximately represented as the largest principal component of the time series collected across the network. To quantify each sensor's contribution for generation of the information content, Markov machine models as well as x-Markov (pronounced as cross-Markov) machine models, conditioned on the network information state, are constructed; the difference between the conditional entropies of these machines is then treated as an approximate measure of information contribution by the respective sensors. The x-Markov models represent the conditional temporal statistics given the network information state. The proposed method has been validated on experimental data collected from a local area network of passive sensors for target detection, where the statistical characteristics of environmental disturbances are similar to those of the target signal in the sense of time scale and texture. A distinctive feature of the proposed algorithm is that the network decisions are independent of the behavior and identity of the individual sensors, which is desirable from computational perspectives. Results are presented to demonstrate the proposed method's efficacy to correctly identify the presence of a target with very low false-alarm rates. The performance of the underlying algorithm is compared with that of a recent data-driven, feature-level information fusion algorithm. It is shown that the proposed algorithm outperforms the other algorithm.
Lindelauf, R.; Hamers, H.J.M.; Husslage, B.G.M.
2011-01-01
The identification of key players in a terrorist network can lead to prevention of attacks, due to efficient allocation of surveillance means or isolation of key players in order to destabilize the network. In this paper we introduce a game theoretic approach to identify key players in terrorist
PAGANI Toolkit: Parallel graph-theoretical analysis package for brain network big data.
Du, Haixiao; Xia, Mingrui; Zhao, Kang; Liao, Xuhong; Yang, Huazhong; Wang, Yu; He, Yong
2018-05-01
The recent collection of unprecedented quantities of neuroimaging data with high spatial resolution has led to brain network big data. However, a toolkit for fast and scalable computational solutions is still lacking. Here, we developed the PArallel Graph-theoretical ANalysIs (PAGANI) Toolkit based on a hybrid central processing unit-graphics processing unit (CPU-GPU) framework with a graphical user interface to facilitate the mapping and characterization of high-resolution brain networks. Specifically, the toolkit provides flexible parameters for users to customize computations of graph metrics in brain network analyses. As an empirical example, the PAGANI Toolkit was applied to individual voxel-based brain networks with ∼200,000 nodes that were derived from a resting-state fMRI dataset of 624 healthy young adults from the Human Connectome Project. Using a personal computer, this toolbox completed all computations in ∼27 h for one subject, which is markedly less than the 118 h required with a single-thread implementation. The voxel-based functional brain networks exhibited prominent small-world characteristics and densely connected hubs, which were mainly located in the medial and lateral fronto-parietal cortices. Moreover, the female group had significantly higher modularity and nodal betweenness centrality mainly in the medial/lateral fronto-parietal and occipital cortices than the male group. Significant correlations between the intelligence quotient and nodal metrics were also observed in several frontal regions. Collectively, the PAGANI Toolkit shows high computational performance and good scalability for analyzing connectome big data and provides a friendly interface without the complicated configuration of computing environments, thereby facilitating high-resolution connectomics research in health and disease. © 2018 Wiley Periodicals, Inc.
Information theoretic description of networks
Wilhelm, Thomas; Hollunder, Jens
2007-11-01
We present a new information theoretic approach for network characterizations. It is developed to describe the general type of networks with n nodes and L directed and weighted links, i.e., it also works for the simpler undirected and unweighted networks. The new information theoretic measures for network characterizations are based on a transmitter-receiver analogy of effluxes and influxes. Based on these measures, we classify networks as either complex or non-complex and as either democracy or dictatorship networks. Directed networks, in particular, are furthermore classified as either information spreading and information collecting networks. The complexity classification is based on the information theoretic network complexity measure medium articulation (MA). It is proven that special networks with a medium number of links ( L∼n1.5) show the theoretical maximum complexity MA=(log n)2/2. A network is complex if its MA is larger than the average MA of appropriately randomized networks: MA>MAr. A network is of the democracy type if its redundancy Rdictatorship network. In democracy networks all nodes are, on average, of similar importance, whereas in dictatorship networks some nodes play distinguished roles in network functioning. In other words, democracy networks are characterized by cycling of information (or mass, or energy), while in dictatorship networks there is a straight through-flow from sources to sinks. The classification of directed networks into information spreading and information collecting networks is based on the conditional entropies of the considered networks ( H(A/B)=uncertainty of sender node if receiver node is known, H(B/A)=uncertainty of receiver node if sender node is known): if H(A/B)>H(B/A), it is an information collecting network, otherwise an information spreading network. Finally, different real networks (directed and undirected, weighted and unweighted) are classified according to our general scheme.
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Matthias Dehmer
Full Text Available This paper aims to investigate information-theoretic network complexity measures which have already been intensely used in mathematical- and medicinal chemistry including drug design. Numerous such measures have been developed so far but many of them lack a meaningful interpretation, e.g., we want to examine which kind of structural information they detect. Therefore, our main contribution is to shed light on the relatedness between some selected information measures for graphs by performing a large scale analysis using chemical networks. Starting from several sets containing real and synthetic chemical structures represented by graphs, we study the relatedness between a classical (partition-based complexity measure called the topological information content of a graph and some others inferred by a different paradigm leading to partition-independent measures. Moreover, we evaluate the uniqueness of network complexity measures numerically. Generally, a high uniqueness is an important and desirable property when designing novel topological descriptors having the potential to be applied to large chemical databases.
Liu, Yuelu; Hong, Xiangfei; Bengson, Jesse J; Kelley, Todd A; Ding, Mingzhou; Mangun, George R
2017-08-15
The neural mechanisms by which intentions are transformed into actions remain poorly understood. We investigated the network mechanisms underlying spontaneous voluntary decisions about where to focus visual-spatial attention (willed attention). Graph-theoretic analysis of two independent datasets revealed that regions activated during willed attention form a set of functionally-distinct networks corresponding to the frontoparietal network, the cingulo-opercular network, and the dorsal attention network. Contrasting willed attention with instructed attention (where attention is directed by external cues), we observed that the dorsal anterior cingulate cortex was allied with the dorsal attention network in instructed attention, but shifted connectivity during willed attention to interact with the cingulo-opercular network, which then mediated communications between the frontoparietal network and the dorsal attention network. Behaviorally, greater connectivity in network hubs, including the dorsolateral prefrontal cortex, the dorsal anterior cingulate cortex, and the inferior parietal lobule, was associated with faster reaction times. These results, shown to be consistent across the two independent datasets, uncover the dynamic organization of functionally-distinct networks engaged to support intentional acts. Copyright © 2017 Elsevier Inc. All rights reserved.
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Dean HRISTOV
2015-06-01
Full Text Available The extant literature on networks in tourism management research has traditionally acknowledged destinations as the primary unit of analysis. This paper takes an alternative perspective and positions Destination Management Organisations (DMOs at the forefront of today’s tourism management research agenda. Whilst providing a relatively structured approach to generating enquiry, network research vis-à-vis Social Network Analysis (SNA in DMOs is often surrounded by serious impediments. Embedded in the network literature, this conceptual article aims to provide a practitioner perspective on addressing the obstacles to undertaking network studies in DMO organisations. A simple, three-step methodological framework for investigating DMOs as interorganisational networks of member organisations is proposed in response to complexities in network research. The rationale behind introducing such framework lies in the opportunity to trigger discussions and encourage further academic contributions embedded in both theory and practice. Academic and practitioner contributions are likely to yield insights into the importance of network methodologies applied to DMO organisations.
Ye, Zheng; Doñamayor, Nuria; Münte, Thomas F
2014-02-01
A set of cortical and sub-cortical brain structures has been linked with sentence-level semantic processes. However, it remains unclear how these brain regions are organized to support the semantic integration of a word into sentential context. To look into this issue, we conducted a functional magnetic resonance imaging (fMRI) study that required participants to silently read sentences with semantically congruent or incongruent endings and analyzed the network properties of the brain with two approaches, independent component analysis (ICA) and graph theoretical analysis (GTA). The GTA suggested that the whole-brain network is topologically stable across conditions. The ICA revealed a network comprising the supplementary motor area (SMA), left inferior frontal gyrus, left middle temporal gyrus, left caudate nucleus, and left angular gyrus, which was modulated by the incongruity of sentence ending. Furthermore, the GTA specified that the connections between the left SMA and left caudate nucleus as well as that between the left caudate nucleus and right thalamus were stronger in response to incongruent vs. congruent endings. Copyright © 2012 Wiley Periodicals, Inc.
Graph Theoretical Analysis of Developmental Patterns of the White Matter Network
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Zhang eChen
2013-11-01
Full Text Available Understanding the development of human brain organization is critical for gaining insight into how the enhancement of cognitive processes is related to the fine-tuning of the brain network. However, the developmental trajectory of the large-scale white matter (WM network is not fully understood. Here, using graph theory, we examine developmental changes in the organization of WM networks in 180 typically-developing participants. WM networks were constructed using whole brain tractography and 78 cortical regions of interest were extracted from each participant. The subjects were first divided into 5 equal sample size (n=36 groups (early childhood: 6.0-9.7 years; late childhood: 9.8-12.7 years; adolescence: 12.9-17.5 years; young adult: 17.6-21.8 years; adult: 21.9-29.6 years. Most prominent changes in the topological properties of developing brain networks occur at late childhood and adolescence. During late childhood period, the structural brain network showed significant increase in the global efficiency but decrease in modularity, suggesting a shift of topological organization toward a more randomized configuration. However, while preserving most topological features, there was a significant increase in the local efficiency at adolescence, suggesting the dynamic process of rewiring and rebalancing brain connections at different growth stages. In addition, several pivotal hubs were identified that are vital for the global coordination of information flow over the whole brain network across all age groups. Significant increases of nodal efficiency were present in several regions such as precuneus at late childhood. Finally, a stable and functionally/anatomically related modular organization was identified throughout the development of the WM network. This study used network analysis to elucidate the topological changes in brain maturation, paving the way for developing novel methods for analyzing disrupted brain connectivity in
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Jesús René Luna Hernández
2008-05-01
Full Text Available Immigration is currently a source of much, sometimes divisive, social debate. However, what the immigrants themselves have to say about their own situation often goes unreported. One of the least-studied aspects of immigration is the immigrant's relationship with new information and communication technologies (ICTs. Here I suggest, as a project for investigation, the analysis of the metaphors that immigrants (from sub-Saharan Africa to Spain use to represent ICTs and the practices that surround them. These immigrants are of special interest because they come from places where contact with ICTs is minimal, and also because the jobs they find on arrival in Spain tend not to involve the use of ICTs. I propose the adoption of a perspective in which context and social relationships take precedence over individualistic factors, such as attitudes or attributions. I argue that social network analysis, and more specifically, discursive network analysis, is the investigative strategy most appropriate to such a project.
Vecchio, Fabrizio; Miraglia, Francesca; Bramanti, Placido; Rossini, Paolo Maria
2014-01-01
Modern analysis of electroencephalographic (EEG) rhythms provides information on dynamic brain connectivity. To test the hypothesis that aging processes modulate the brain connectivity network, EEG recording was conducted on 113 healthy volunteers. They were divided into three groups in accordance with their ages: 36 Young (15-45 years), 46 Adult (50-70 years), and 31 Elderly (>70 years). To evaluate the stability of the investigated parameters, a subgroup of 10 subjects underwent a second EEG recording two weeks later. Graph theory functions were applied to the undirected and weighted networks obtained by the lagged linear coherence evaluated by eLORETA on cortical sources. EEG frequency bands of interest were: delta (2-4 Hz), theta (4-8 Hz), alpha1 (8-10.5 Hz), alpha2 (10.5-13 Hz), beta1 (13-20 Hz), beta2 (20-30 Hz), and gamma (30-40 Hz). The spectral connectivity analysis of cortical sources showed that the normalized Characteristic Path Length (λ) presented the pattern Young > Adult>Elderly in the higher alpha band. Elderly also showed a greater increase in delta and theta bands than Young. The correlation between age and λ showed that higher ages corresponded to higher λ in delta and theta and lower in the alpha2 band; this pattern reflects the age-related modulation of higher (alpha) and decreased (delta) connectivity. The Normalized Clustering coefficient (γ) and small-world network modeling (σ) showed non-significant age-modulation. Evidence from the present study suggests that graph theory can aid in the analysis of connectivity patterns estimated from EEG and can facilitate the study of the physiological and pathological brain aging features of functional connectivity networks.
Wang, Junjing; Qiu, Shijun; Xu, Yong; Liu, Zhenyin; Wen, Xue; Hu, Xiangshu; Zhang, Ruibin; Li, Meng; Wang, Wensheng; Huang, Ruiwang
2014-09-01
Temporal lobe epilepsy (TLE) is one of the most common forms of drug-resistant epilepsy. Previous studies have indicated that the TLE-related impairments existed in extensive local functional networks. However, little is known about the alterations in the topological properties of whole brain functional networks. In this study, we acquired resting-state BOLD-fMRI (rsfMRI) data from 26 TLE patients and 25 healthy controls, constructed their whole brain functional networks, compared the differences in topological parameters between the TLE patients and the controls, and analyzed the correlation between the altered topological properties and the epilepsy duration. The TLE patients showed significant increases in clustering coefficient and characteristic path length, but significant decrease in global efficiency compared to the controls. We also found altered nodal parameters in several regions in the TLE patients, such as the bilateral angular gyri, left middle temporal gyrus, right hippocampus, triangular part of left inferior frontal gyrus, left inferior parietal but supramarginal and angular gyri, and left parahippocampus gyrus. Further correlation analysis showed that the local efficiency of the TLE patients correlated positively with the epilepsy duration. Our results indicated the disrupted topological properties of whole brain functional networks in TLE patients. Our findings indicated the TLE-related impairments in the whole brain functional networks, which may help us to understand the clinical symptoms of TLE patients and offer a clue for the diagnosis and treatment of the TLE patients. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
International Nuclear Information System (INIS)
Wang, Jieqiong; Li, Ting; Xian, Junfang; Wang, Ningli; He, Huiguang
2016-01-01
Most previous glaucoma studies with resting-state fMRI have focused on the neuronal activity in the individual structure of the brain, yet ignored the functional communication of anatomically separated structures. The purpose of this study is to investigate the efficiency of the functional communication change or not in glaucoma patients. We applied the resting-state fMRI data to construct the connectivity network of 25 normal controls and 25 age-gender-matched primary open angle glaucoma patients. Graph theoretical analysis was performed to assess brain network pattern differences between the two groups. No significant differences of the global network measures were found between the two groups. However, the local measures were radically reorganized in glaucoma patients. Comparing with the hub regions in normal controls' network, we found that six hub regions disappeared and nine hub regions appeared in the network of patients. In addition, the betweenness centralities of two altered hub regions, right fusiform gyrus and right lingual gyrus, were significantly correlated with the visual field mean deviation. Although the efficiency of functional communication is preserved in the brain network of the glaucoma at the global level, the efficiency of functional communication is altered in some specialized regions of the glaucoma. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Wang, Jieqiong [Chinese Academy of Sciences, State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Beijing (China); Li, Ting; Xian, Junfang [Capital Medical University, Department of Radiology, Beijing Tongren Hospital, Beijing (China); Wang, Ningli [Capital Medical University, Department of Ophthalmology, Beijing Tongren Hospital, Beijing (China); He, Huiguang [Chinese Academy of Sciences, State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Beijing (China); Chinese Academy of Sciences, Research Center for Brain-Inspired Intelligence, Institute of Automation, Beijing (China)
2016-11-15
Most previous glaucoma studies with resting-state fMRI have focused on the neuronal activity in the individual structure of the brain, yet ignored the functional communication of anatomically separated structures. The purpose of this study is to investigate the efficiency of the functional communication change or not in glaucoma patients. We applied the resting-state fMRI data to construct the connectivity network of 25 normal controls and 25 age-gender-matched primary open angle glaucoma patients. Graph theoretical analysis was performed to assess brain network pattern differences between the two groups. No significant differences of the global network measures were found between the two groups. However, the local measures were radically reorganized in glaucoma patients. Comparing with the hub regions in normal controls' network, we found that six hub regions disappeared and nine hub regions appeared in the network of patients. In addition, the betweenness centralities of two altered hub regions, right fusiform gyrus and right lingual gyrus, were significantly correlated with the visual field mean deviation. Although the efficiency of functional communication is preserved in the brain network of the glaucoma at the global level, the efficiency of functional communication is altered in some specialized regions of the glaucoma. (orig.)
Graph Theoretical Analysis of Network Centric Operations Using Multi-Layer Models
National Research Council Canada - National Science Library
Wong-Jiru, Ann
2006-01-01
.... The research incorporates the importance of understanding network topology for evaluating an environment for net-centricity and using network characteristics to help commanders assess the effects...
The application of graph theoretical analysis to complex networks in the brain.
Reijneveld, Jaap C; Ponten, Sophie C; Berendse, Henk W; Stam, Cornelis J
2007-11-01
Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in network sciences, such as the discovery of small world and scale free networks, to data on anatomical and functional connectivity in the brain. In this review we start with some background knowledge on the history and recent advances in network theories in general. We emphasize the correlation between the structural properties of networks and the dynamics of these networks. We subsequently demonstrate through evidence from computational studies, in vivo experiments, and functional MRI, EEG and MEG studies in humans, that both the functional and anatomical connectivity of the healthy brain have many features of a small world network, but only to a limited extent of a scale free network. The small world structure of neural networks is hypothesized to reflect an optimal configuration associated with rapid synchronization and information transfer, minimal wiring costs, resilience to certain types of damage, as well as a balance between local processing and global integration. Eventually, we review the current knowledge on the effects of focal and diffuse brain disease on neural network characteristics, and demonstrate increasing evidence that both cognitive and psychiatric disturbances, as well as risk of epileptic seizures, are correlated with (changes in) functional network architectural features.
The application of graph theoretical analysis to complex networks in the brain
Reijneveld, Jaap C.; Ponten, Sophie C.; Berendse, Henk W.; Stam, Cornelis J.
2007-01-01
Considering the brain as a complex network of interacting dynamical systems offers new insights into higher level brain processes such as memory, planning, and abstract reasoning as well as various types of brain pathophysiology. This viewpoint provides the opportunity to apply new insights in
The Mathematics of Networks Science: Scale-Free, Power-Law Graphs and Continuum Theoretical Analysis
Padula, Janice
2012-01-01
When hoping to initiate or sustain students' interest in mathematics teachers should always consider relevance, relevance to students' lives and in the middle and later years of instruction in high school and university, accessibility. A topic such as the mathematics behind networks science, more specifically scale-free graphs, is up-to-date,…
Hosseini, S M Hadi; Hoeft, Fumiko; Kesler, Shelli R
2012-01-01
In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT) that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI) that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC) and functional data analyses (FDA), in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL) and healthy matched Controls (CON). The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.
Directory of Open Access Journals (Sweden)
S M Hadi Hosseini
Full Text Available In recent years, graph theoretical analyses of neuroimaging data have increased our understanding of the organization of large-scale structural and functional brain networks. However, tools for pipeline application of graph theory for analyzing topology of brain networks is still lacking. In this report, we describe the development of a graph-analysis toolbox (GAT that facilitates analysis and comparison of structural and functional network brain networks. GAT provides a graphical user interface (GUI that facilitates construction and analysis of brain networks, comparison of regional and global topological properties between networks, analysis of network hub and modules, and analysis of resilience of the networks to random failure and targeted attacks. Area under a curve (AUC and functional data analyses (FDA, in conjunction with permutation testing, is employed for testing the differences in network topologies; analyses that are less sensitive to the thresholding process. We demonstrated the capabilities of GAT by investigating the differences in the organization of regional gray-matter correlation networks in survivors of acute lymphoblastic leukemia (ALL and healthy matched Controls (CON. The results revealed an alteration in small-world characteristics of the brain networks in the ALL survivors; an observation that confirm our hypothesis suggesting widespread neurobiological injury in ALL survivors. Along with demonstration of the capabilities of the GAT, this is the first report of altered large-scale structural brain networks in ALL survivors.
Game Theoretic Analysis of Cooperative Message Forwarding in Opportunistic Mobile Networks.
Pal, Sujata; Saha, Barun Kumar; Misra, Sudip
2017-12-01
In cooperative communication, a set of players forming a coalition ensures communal behavior among themselves by helping one another in message forwarding. Opportunistic mobile networks (OMNs) require multihop communications for transferring messages from the source to the destination nodes. However, noncooperative nodes only forward their own messages to others, and drop others' messages upon receiving them. So, the message delivery overhead increases in OMN. For minimizing the overhead and maximizing the delivery rate, we propose two coalition-based cooperative schemes: 1) simple coalition formation (SCF) and 2) overlapping coalition formation (OCF) game. In SCF, we consider the presence of a central information center, whereas OCF is a fully distributed scheme. In SCF, coalitions are disjoint, whereas in OCF, a node may be the member of multiple coalitions at the same time. All nodes in a coalition help each other cooperatively by forwarding group messages to the intermediate or destination nodes. The goal of the nodes is to achieve high success rate in delivering messages. The proposed SCF scheme is cohesive, in which disjoint coalitions always combine to form grand coalition. In OCF, a node reaches a stable grand coalition when all the nodes of the OMN are members of overlapping coalition of the node. No node gains by deviating from the grand coalition in SCF and OCF. Simulation results based on synthetic mobility model and real-life traces show that the message delivery ratio of OMNs increase by up to 67%, as compared to the noncooperative scenario. Moreover, the message overhead ratio using the proposed coalition-based schemes reduces by up to about (1/3)rd of that of the noncooperative communication scheme.
Towards a theoretical framework for analyzing complex linguistic networks
Lücking, Andy; Banisch, Sven; Blanchard, Philippe; Job, Barbara
2016-01-01
The aim of this book is to advocate and promote network models of linguistic systems that are both based on thorough mathematical models and substantiated in terms of linguistics. In this way, the book contributes first steps towards establishing a statistical network theory as a theoretical basis of linguistic network analysis the boarder of the natural sciences and the humanities.This book addresses researchers who want to get familiar with theoretical developments, computational models and their empirical evaluation in the field of complex linguistic networks. It is intended to all those who are interested in statisticalmodels of linguistic systems from the point of view of network research. This includes all relevant areas of linguistics ranging from phonological, morphological and lexical networks on the one hand and syntactic, semantic and pragmatic networks on the other. In this sense, the volume concerns readers from many disciplines such as physics, linguistics, computer science and information scien...
Theoretical foundations for nervous networks
International Nuclear Information System (INIS)
Hasslacher, B.; Tilden, M.W.
1997-01-01
Following three years of study into experimental Nervous Net (Nv) control devices, various successes and several amusing failures have implied some general principles on the nature of capable control systems for autonomous machines and perhaps, we conjecture, even biological organisms. These systems are minimal, elegant, and, depending upon their implementation in a open-quotes creatureclose quotes structure, astonishingly robust. Their only problem seems to be that as they are collections of non-linear asynchronous elements, only complex analysis can adequately extract and explain the emergent competency of their operation. The implications are that so long as Nv non-linear topologies can retain some measure of sub-critically coupled planar stability, the Piexito theorem will guarantee a form of plastic mode-locking necessary for broad-behavior competency. Further experimental evidence also suggests that if Nv topologies are kept in sub-chaotically stable regimes, they can be implemented at any scale and still automatically fall into effective survival strategies in unstructured environments. An explanation for how this is be possible in such minimal structures is presented. copyright 1997 American Institute of Physics
Park, Bong Soo; Lee, Yoo Jin; Park, Jin-Han; Kim, Il Hwan; Park, Si Hyung; Lee, Ho-Joon; Park, Kang Min
2018-06-01
We evaluated global topology and organization of regional hubs in the brain networks and microstructural abnormalities in the white matter of patients with reflex syncope. Twenty patients with reflex syncope and thirty healthy subjects were recruited, and they underwent diffusion tensor imaging (DTI) scans. Graph theory was applied to obtain network measures based on extracted DTI data, using DSI Studio. We then investigated differences in the network measures between the patients with reflex syncope and the healthy subjects. We also analyzed microstructural abnormalities of white matter using tract-based spatial statistics analysis (TBSS). Measures of global topology were not different between patients with reflex syncope and healthy subjects. However, in reflex syncope patients, the strength measures of the right angular, left inferior frontal, left middle orbitofrontal, left superior medial frontal, and left middle temporal gyrus were lower than in healthy subjects. The betweenness centrality measures of the left middle orbitofrontal, left fusiform, and left lingual gyrus in patients were lower than those in healthy subjects. The PageRank centrality measures of the right angular, left middle orbitofrontal, and left superior medial frontal gyrus in patients were lower than those in healthy subjects. Regarding the analysis of the white matter microstructure, there were no differences in the fractional anisotropy and mean diffusivity values between the two groups. We have identified a reorganization of network hubs in the brain network of patients with reflex syncope. These alterations in brain network may play a role in the pathophysiologic mechanism underlying reflex syncope. © 2018 The Authors. Brain and Behavior published by Wiley Periodicals, Inc.
Multifractal analysis of complex networks
International Nuclear Information System (INIS)
Wang Dan-Ling; Yu Zu-Guo; Anh V
2012-01-01
Complex networks have recently attracted much attention in diverse areas of science and technology. Many networks such as the WWW and biological networks are known to display spatial heterogeneity which can be characterized by their fractal dimensions. Multifractal analysis is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we introduce a new box-covering algorithm for multifractal analysis of complex networks. This algorithm is used to calculate the generalized fractal dimensions D q of some theoretical networks, namely scale-free networks, small world networks, and random networks, and one kind of real network, namely protein—protein interaction networks of different species. Our numerical results indicate the existence of multifractality in scale-free networks and protein—protein interaction networks, while the multifractal behavior is not clear-cut for small world networks and random networks. The possible variation of D q due to changes in the parameters of the theoretical network models is also discussed. (general)
Directory of Open Access Journals (Sweden)
Dagiuklas Tasos
2011-01-01
Full Text Available This paper presents a Wireless Information-Theoretic Security (WITS scheme, which has been recently introduced as a robust physical layer-based security solution, especially for infrastructureless networks. An autonomic network of moving users was implemented via 802.11n nodes of an ad hoc network for an outdoor topology with obstacles. Obstructed-Line-of-Sight (OLOS and Non-Line-of-Sight (NLOS propagation scenarios were examined. Low-speed user movement was considered, so that Doppler spread could be discarded. A transmitter and a legitimate receiver exchanged information in the presence of a moving eavesdropper. Average Signal-to-Noise Ratio (SNR values were acquired for both the main and the wiretap channel, and the Probability of Nonzero Secrecy Capacity was calculated based on theoretical formula. Experimental results validate theoretical findings stressing the importance of user location and mobility schemes on the robustness of Wireless Information-Theoretic Security and call for further theoretical analysis.
Teschendorff, Andrew E; Sollich, Peter; Kuehn, Reimer
2014-06-01
A key challenge in systems biology is the elucidation of the underlying principles, or fundamental laws, which determine the cellular phenotype. Understanding how these fundamental principles are altered in diseases like cancer is important for translating basic scientific knowledge into clinical advances. While significant progress is being made, with the identification of novel drug targets and treatments by means of systems biological methods, our fundamental systems level understanding of why certain treatments succeed and others fail is still lacking. We here advocate a novel methodological framework for systems analysis and interpretation of molecular omic data, which is based on statistical mechanical principles. Specifically, we propose the notion of cellular signalling entropy (or uncertainty), as a novel means of analysing and interpreting omic data, and more fundamentally, as a means of elucidating systems-level principles underlying basic biology and disease. We describe the power of signalling entropy to discriminate cells according to differentiation potential and cancer status. We further argue the case for an empirical cellular entropy-robustness correlation theorem and demonstrate its existence in cancer cell line drug sensitivity data. Specifically, we find that high signalling entropy correlates with drug resistance and further describe how entropy could be used to identify the achilles heels of cancer cells. In summary, signalling entropy is a deep and powerful concept, based on rigorous statistical mechanical principles, which, with improved data quality and coverage, will allow a much deeper understanding of the systems biological principles underlying normal and disease physiology. Copyright © 2014 Elsevier Inc. All rights reserved.
Wang, Jin-Hui; Zuo, Xi-Nian; Gohel, Suril; Milham, Michael P.; Biswal, Bharat B.; He, Yong
2011-01-01
Graph-based computational network analysis has proven a powerful tool to quantitatively characterize functional architectures of the brain. However, the test-retest (TRT) reliability of graph metrics of functional networks has not been systematically examined. Here, we investigated TRT reliability of topological metrics of functional brain networks derived from resting-state functional magnetic resonance imaging data. Specifically, we evaluated both short-term (5 months apart) TRT reliability for 12 global and 6 local nodal network metrics. We found that reliability of global network metrics was overall low, threshold-sensitive and dependent on several factors of scanning time interval (TI, long-term>short-term), network membership (NM, networks excluding negative correlations>networks including negative correlations) and network type (NT, binarized networks>weighted networks). The dependence was modulated by another factor of node definition (ND) strategy. The local nodal reliability exhibited large variability across nodal metrics and a spatially heterogeneous distribution. Nodal degree was the most reliable metric and varied the least across the factors above. Hub regions in association and limbic/paralimbic cortices showed moderate TRT reliability. Importantly, nodal reliability was robust to above-mentioned four factors. Simulation analysis revealed that global network metrics were extremely sensitive (but varying degrees) to noise in functional connectivity and weighted networks generated numerically more reliable results in compared with binarized networks. For nodal network metrics, they showed high resistance to noise in functional connectivity and no NT related differences were found in the resistance. These findings provide important implications on how to choose reliable analytical schemes and network metrics of interest. PMID:21818285
Game Theoretic Problems in Network Economics and Mechanism Design Solutions
Narahari, Y; Narayanam, Ramasuri; Prakash, Hastagiri
2009-01-01
Explores game theoretic modeling and mechanism design for problem solving in Internet and network economics. This monograph contains an exposition of representative game theoretic problems in three different network economics situations and a systematic exploration of mechanism design solutions to these problems.
Field-theoretic approach to fluctuation effects in neural networks
International Nuclear Information System (INIS)
Buice, Michael A.; Cowan, Jack D.
2007-01-01
A well-defined stochastic theory for neural activity, which permits the calculation of arbitrary statistical moments and equations governing them, is a potentially valuable tool for theoretical neuroscience. We produce such a theory by analyzing the dynamics of neural activity using field theoretic methods for nonequilibrium statistical processes. Assuming that neural network activity is Markovian, we construct the effective spike model, which describes both neural fluctuations and response. This analysis leads to a systematic expansion of corrections to mean field theory, which for the effective spike model is a simple version of the Wilson-Cowan equation. We argue that neural activity governed by this model exhibits a dynamical phase transition which is in the universality class of directed percolation. More general models (which may incorporate refractoriness) can exhibit other universality classes, such as dynamic isotropic percolation. Because of the extremely high connectivity in typical networks, it is expected that higher-order terms in the systematic expansion are small for experimentally accessible measurements, and thus, consistent with measurements in neocortical slice preparations, we expect mean field exponents for the transition. We provide a quantitative criterion for the relative magnitude of each term in the systematic expansion, analogous to the Ginsburg criterion. Experimental identification of dynamic universality classes in vivo is an outstanding and important question for neuroscience
Theoretical analysis of rolled joints
International Nuclear Information System (INIS)
Sinha, R.K.
1975-01-01
A procedure for theoretically analysing the case of an externally restrained sandwich joint formed by a hypothetical uniform hydrostatic expansion process is outlined. Reference is made to a computer program based on this theory. Results illustrating the effect of major joint variables on residual contact pressure are presented and analysed. The applicability and limitations of this theory are discussed. (author)
THE NETWORKS IN TOURISM: A THEORETICAL APPROACH
Directory of Open Access Journals (Sweden)
Maria TĂTĂRUȘANU
2016-12-01
Full Text Available The economic world in which tourism companies act today is in a continuous changing process. The most important factor of these changes is the globalization of their environment, both in economic, social, natural and cultural aspects. The tourism companies can benefit from the opportunities brought by globalization, but also could be menaced by the new context. How could react the companies to these changes in order to create and maintain long term competitive advantage for their business? In the present paper we make a literature review of the new tourism companies´ business approach: the networks - a result and/or a reason for exploiting the opportunities or, on the contrary, for keeping their actual position on the market. It’s a qualitative approach and the research methods used are analyses, synthesis, abstraction, which are considered the most appropriate to achieve the objective of the paper.
Kürble, Peter
2010-01-01
Two of the main issues for firms concerning to the creation of new markets are: whether or not be a part of this process and if so, how to participate. This paper deals with this questions concerning to the development of multimedia markets for private households on the one side and networking companies on the other side. The first question will be answered by using the "five forces"-approach for the market for movies and the broadcasting market. The second question will be discussed by the t...
Ecological network analysis: network construction
Fath, B.D.; Scharler, U.M.; Ulanowicz, R.E.; Hannon, B.
2007-01-01
Ecological network analysis (ENA) is a systems-oriented methodology to analyze within system interactions used to identify holistic properties that are otherwise not evident from the direct observations. Like any analysis technique, the accuracy of the results is as good as the data available, but
Detecting Network Vulnerabilities Through Graph TheoreticalMethods
Energy Technology Data Exchange (ETDEWEB)
Cesarz, Patrick; Pomann, Gina-Maria; Torre, Luis de la; Villarosa, Greta; Flournoy, Tamara; Pinar, Ali; Meza Juan
2007-09-30
Identifying vulnerabilities in power networks is an important problem, as even a small number of vulnerable connections can cause billions of dollars in damage to a network. In this paper, we investigate a graph theoretical formulation for identifying vulnerabilities of a network. We first try to find the most critical components in a network by finding an optimal solution for each possible cutsize constraint for the relaxed version of the inhibiting bisection problem, which aims to find loosely coupled subgraphs with significant demand/supply mismatch. Then we investigate finding critical components by finding a flow assignment that minimizes the maximum among flow assignments on all edges. We also report experiments on IEEE 30, IEEE 118, and WSCC 179 benchmark power networks.
Information-Theoretic Inference of Large Transcriptional Regulatory Networks
Directory of Open Access Journals (Sweden)
Meyer Patrick
2007-01-01
Full Text Available The paper presents MRNET, an original method for inferring genetic networks from microarray data. The method is based on maximum relevance/minimum redundancy (MRMR, an effective information-theoretic technique for feature selection in supervised learning. The MRMR principle consists in selecting among the least redundant variables the ones that have the highest mutual information with the target. MRNET extends this feature selection principle to networks in order to infer gene-dependence relationships from microarray data. The paper assesses MRNET by benchmarking it against RELNET, CLR, and ARACNE, three state-of-the-art information-theoretic methods for large (up to several thousands of genes network inference. Experimental results on thirty synthetically generated microarray datasets show that MRNET is competitive with these methods.
Information-Theoretic Inference of Large Transcriptional Regulatory Networks
Directory of Open Access Journals (Sweden)
Patrick E. Meyer
2007-06-01
Full Text Available The paper presents MRNET, an original method for inferring genetic networks from microarray data. The method is based on maximum relevance/minimum redundancy (MRMR, an effective information-theoretic technique for feature selection in supervised learning. The MRMR principle consists in selecting among the least redundant variables the ones that have the highest mutual information with the target. MRNET extends this feature selection principle to networks in order to infer gene-dependence relationships from microarray data. The paper assesses MRNET by benchmarking it against RELNET, CLR, and ARACNE, three state-of-the-art information-theoretic methods for large (up to several thousands of genes network inference. Experimental results on thirty synthetically generated microarray datasets show that MRNET is competitive with these methods.
Modular analysis of biological networks.
Kaltenbach, Hans-Michael; Stelling, Jörg
2012-01-01
The analysis of complex biological networks has traditionally relied on decomposition into smaller, semi-autonomous units such as individual signaling pathways. With the increased scope of systems biology (models), rational approaches to modularization have become an important topic. With increasing acceptance of de facto modularity in biology, widely different definitions of what constitutes a module have sparked controversies. Here, we therefore review prominent classes of modular approaches based on formal network representations. Despite some promising research directions, several important theoretical challenges remain open on the way to formal, function-centered modular decompositions for dynamic biological networks.
Wireless Networks under a Backoff Attack: A Game Theoretical Perspective.
Parras, Juan; Zazo, Santiago
2018-01-30
We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi's network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.
Wireless Networks under a Backoff Attack: A Game Theoretical Perspective
Directory of Open Access Journals (Sweden)
Juan Parras
2018-01-01
Full Text Available We study a wireless sensor network using CSMA/CA in the MAC layer under a backoff attack: some of the sensors of the network are malicious and deviate from the defined contention mechanism. We use Bianchi’s network model to study the impact of the malicious sensors on the total network throughput, showing that it causes the throughput to be unfairly distributed among sensors. We model this conflict using game theory tools, where each sensor is a player. We obtain analytical solutions and propose an algorithm, based on Regret Matching, to learn the equilibrium of the game with an arbitrary number of players. Our approach is validated via simulations, showing that our theoretical predictions adjust to reality.
Advances in neural networks computational and theoretical issues
Esposito, Anna; Morabito, Francesco
2015-01-01
This book collects research works that exploit neural networks and machine learning techniques from a multidisciplinary perspective. Subjects covered include theoretical, methodological and computational topics which are grouped together into chapters devoted to the discussion of novelties and innovations related to the field of Artificial Neural Networks as well as the use of neural networks for applications, pattern recognition, signal processing, and special topics such as the detection and recognition of multimodal emotional expressions and daily cognitive functions, and bio-inspired memristor-based networks. Providing insights into the latest research interest from a pool of international experts coming from different research fields, the volume becomes valuable to all those with any interest in a holistic approach to implement believable, autonomous, adaptive, and context-aware Information Communication Technologies.
Optimal information transfer in enzymatic networks: A field theoretic formulation
Samanta, Himadri S.; Hinczewski, Michael; Thirumalai, D.
2017-07-01
Signaling in enzymatic networks is typically triggered by environmental fluctuations, resulting in a series of stochastic chemical reactions, leading to corruption of the signal by noise. For example, information flow is initiated by binding of extracellular ligands to receptors, which is transmitted through a cascade involving kinase-phosphatase stochastic chemical reactions. For a class of such networks, we develop a general field-theoretic approach to calculate the error in signal transmission as a function of an appropriate control variable. Application of the theory to a simple push-pull network, a module in the kinase-phosphatase cascade, recovers the exact results for error in signal transmission previously obtained using umbral calculus [Hinczewski and Thirumalai, Phys. Rev. X 4, 041017 (2014), 10.1103/PhysRevX.4.041017]. We illustrate the generality of the theory by studying the minimal errors in noise reduction in a reaction cascade with two connected push-pull modules. Such a cascade behaves as an effective three-species network with a pseudointermediate. In this case, optimal information transfer, resulting in the smallest square of the error between the input and output, occurs with a time delay, which is given by the inverse of the decay rate of the pseudointermediate. Surprisingly, in these examples the minimum error computed using simulations that take nonlinearities and discrete nature of molecules into account coincides with the predictions of a linear theory. In contrast, there are substantial deviations between simulations and predictions of the linear theory in error in signal propagation in an enzymatic push-pull network for a certain range of parameters. Inclusion of second-order perturbative corrections shows that differences between simulations and theoretical predictions are minimized. Our study establishes that a field theoretic formulation of stochastic biological signaling offers a systematic way to understand error propagation in
Directory of Open Access Journals (Sweden)
Xiaojin Li
2013-01-01
Full Text Available Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY and scale-free gene duplication model (SF-GD, that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.
Theoretical Guidelines for the Utilization of Instructional Social Networking Websites
Directory of Open Access Journals (Sweden)
Ilker YAKIN
2015-10-01
Full Text Available interaction and communication technologies. Indeed, there has been an emerging movement in the interaction and communication technologies. More specifically, the growth of Web 2.0 technologies has acted as a catalyst for change in the disciplines of education. The social networking websites have gained popularity in recent years; therefore, many research studies have been conducted to explain how the use of social networking websites for instructional purposes. For the best practices, it is essential to understand theories associated with social networking studies because related theories for any subject may provide insights and guideline for professionals and researchers. This theoretical paper was designed to offer a road map through the literature in relation to the utilization of social networking websites by presenting main understandings of theories associated with social networking. The Uses and Gratification Theory, social network theory, connectives, and constructivism were selected to serve as a basis for designing social networking studies regarding instructional purposes. Moreover, common attributes of the theories and specific application areas were also discussed. This paper contributes to this emerging movement by explaining the role of these theories for researchers and practitioners to find ways to beneficially integrate them into their future research endeavors
Set theoretical aspects of real analysis
Kharazishvili, Alexander B
2014-01-01
This book addresses a number of questions in real analysis and classical measure theory that are of a set-theoretic flavor. Accessible to graduate students, the beginning of the book presents introductory topics on real analysis and Lebesque measure theory. These topics highlight the boundary between fundamental concepts of measurability and non-measurability for point sets and functions. The remainder of the book deals with more specialized material on set-theoretical real analysis. Problems are included at the end of each chapter.
Networks and network analysis for defence and security
Masys, Anthony J
2014-01-01
Networks and Network Analysis for Defence and Security discusses relevant theoretical frameworks and applications of network analysis in support of the defence and security domains. This book details real world applications of network analysis to support defence and security. Shocks to regional, national and global systems stemming from natural hazards, acts of armed violence, terrorism and serious and organized crime have significant defence and security implications. Today, nations face an uncertain and complex security landscape in which threats impact/target the physical, social, economic
Epidemiologic Considerations in Network Modeling of Theoretical Disease Events
National Research Council Canada - National Science Library
Lem, Marcus
2006-01-01
.... Network analysis has shown utility in the study of a range of communicable disease outbreaks affecting both health and commerce, including SARS, tuberculosis, syphilis and foot-and mouth-disease...
Structural Analysis of Complex Networks
Dehmer, Matthias
2011-01-01
Filling a gap in literature, this self-contained book presents theoretical and application-oriented results that allow for a structural exploration of complex networks. The work focuses not only on classical graph-theoretic methods, but also demonstrates the usefulness of structural graph theory as a tool for solving interdisciplinary problems. Applications to biology, chemistry, linguistics, and data analysis are emphasized. The book is suitable for a broad, interdisciplinary readership of researchers, practitioners, and graduate students in discrete mathematics, statistics, computer science,
Theoretical numerical analysis a functional analysis framework
Atkinson, Kendall
2005-01-01
This textbook prepares graduate students for research in numerical analysis/computational mathematics by giving to them a mathematical framework embedded in functional analysis and focused on numerical analysis. This helps the student to move rapidly into a research program. The text covers basic results of functional analysis, approximation theory, Fourier analysis and wavelets, iteration methods for nonlinear equations, finite difference methods, Sobolev spaces and weak formulations of boundary value problems, finite element methods, elliptic variational inequalities and their numerical solu
A NETWORK-THEORETICAL APPROACH TO UNDERSTANDING INTERSTELLAR CHEMISTRY
International Nuclear Information System (INIS)
Jolley, Craig C.; Douglas, Trevor
2010-01-01
Recent years have seen dramatic advances in computational models of chemical processes in the interstellar medium (ISM). Typically, these models have been used to calculate changes in chemical abundances with time; the calculated abundances can then be compared with chemical abundances derived from observations. In this study, the output from an astrochemical simulation has been used to generate directed graphs with weighted edges; these have been analyzed with the tools of network theory to uncover whole-network properties of reaction systems in dark molecular clouds. The results allow the development of a model in which global network properties can be rationalized in terms of the basic physical properties of the reaction system. The ISM network exhibits an exponential degree distribution, which is likely to be a generic feature of chemical networks involving a broad range of reaction rate constants. While species abundances span several orders of magnitude, the formation and destruction rates for most species are approximately balanced-departures from this rule indicate species (such as CO) that play a critical role in shaping the dynamics of the system. Future theoretical or observational studies focusing on individual molecular species will be able to situate them in terms of their role in the complete system or quantify the degree to which they deviate from the typical system behavior.
Theoretical analysis of polarized structure functions
International Nuclear Information System (INIS)
Altarelli, G.; ); Ball, R.D.; Forte, S.; Ridolfi, G.
1998-01-01
We review the analysis of polarized structure function data using perturbative QCD and NLO We use the most recent experimental data to obtain updated results for polarized parton distributions, first moments and the strong coupling. We also discuss several theoretical issues involving in this analysis and in the interpretation of its results. Finally, we compare our results with other similar analyses in the recent literature. (author)
Theoretical Analysis of Polarized Structure Functions
Altarelli, Guido; Forte, Stefano; Ridolfi, G
1998-01-01
We review the analysis of polarized structure function data using perturbative QCD at next-to-leading order. We use the most recent experimental data to obtain updated results for polarized parton distributions, first moments and the strong coupling. We also discuss several theoretical issues involved in this analysis and in the interpretation of its results. Finally, we compare our results with other similar analyses in the recent literature.
A game theoretic investigation of deception in network security
Energy Technology Data Exchange (ETDEWEB)
Carroll, Thomas E.; Grosu, Daniel
2010-12-03
We perform a game theoretic investigation of the effects of deception on the interactions between an attacker and a defender of a computer network. The defender can employ camouflage by either disguising a normal system as a honeypot or by disguising a honeypot as a normal system. We model the interactions between defender and attacker using a signaling game, a non-cooperative two player dynamic game of incomplete information. For this model, we determine which strategies admit perfect Bayesian equilibria. These equilibria are refined Nash equilibria in which neither the defender nor the attacker will unilaterally choose to deviate from their strategies. Finally, we discuss the benefits of employing deceptive equilibrium strategies in the defense of a computer network.
Game Theoretic Risk Analysis of Security Threats
Bier, Vicki M
2008-01-01
Introduces reliability and risk analysis in the face of threats by intelligent agents. This book covers applications to networks, including problems in both telecommunications and transportation. It provides a set of tools for applying game theory TO reliability problems in the presence of intentional, intelligent threats
Communication Network Analysis Methods.
Farace, Richard V.; Mabee, Timothy
This paper reviews a variety of analytic procedures that can be applied to network data, discussing the assumptions and usefulness of each procedure when applied to the complexity of human communication. Special attention is paid to the network properties measured or implied by each procedure. Factor analysis and multidimensional scaling are among…
Theoretical analysis of magnetic sensor output voltage
International Nuclear Information System (INIS)
Liu Haishun; Dun Chaochao; Dou Linming; Yang Weiming
2011-01-01
The output voltage is an important parameter to determine the stress state in magnetic stress measurement, the relationship between the output voltage and the difference in the principal stresses was investigated by a comprehensive application of magnetic circuit theory, magnetization theory, stress analysis as well as the law of electromagnetic induction, and a corresponding quantitative equation was derived. It is drawn that the output voltage is proportional to the difference in the principal stresses, and related to the angle between the principal stress and the direction of the sensor. This investigation provides a theoretical basis for the principle stresses measurement by output voltage. - Research highlights: → A comprehensive investigation of magnetic stress signal. → Derived a quantitative equation about output voltage and the principal stresses. → The output voltage is proportional to the difference of the principal stresses. → Provide a theoretical basis for the principle stresses measurement.
Community, Collective or Movement? Evaluating Theoretical Perspectives on Network Building
Spitzer, W.
2015-12-01
Since 2007, the New England Aquarium has led a national effort to increase the capacity of informal science venues to effectively communicate about climate change. We are now leading the NSF-funded National Network for Ocean and Climate Change Interpretation (NNOCCI), partnering with the Association of Zoos and Aquariums, FrameWorks Institute, Woods Hole Oceanographic Institution, Monterey Bay Aquarium, and National Aquarium, with evaluation conducted by the New Knowledge Organization, Pennsylvania State University, and Ohio State University. NNOCCI enables teams of informal science interpreters across the country to serve as "communication strategists" - beyond merely conveying information they can influence public perceptions, given their high level of commitment, knowledge, public trust, social networks, and visitor contact. We provide in-depth training as well as an alumni network for ongoing learning, implementation support, leadership development, and coalition building. Our goals are to achieve a systemic national impact, embed our work within multiple ongoing regional and national climate change education networks, and leave an enduring legacy. What is the most useful theoretical model for conceptualizing the work of the NNOCCI community? This presentation will examine the pros and cons of three perspectives -- community of practice, collective impact, and social movements. The community of practice approach emphasizes use of common tools, support for practice, social learning, and organic development of leadership. A collective impact model focuses on defining common outcomes, aligning activities toward a common goal, structured collaboration. A social movement emphasizes building group identity and creating a sense of group efficacy. This presentation will address how these models compare in terms of their utility in program planning and evaluation, their fit with the unique characteristics of the NNOCCI community, and their relevance to our program goals.
A Game-Theoretical Approach to Multimedia Social Networks Security
Liu, Enqiang; Liu, Zengliang; Shao, Fei; Zhang, Zhiyong
2014-01-01
The contents access and sharing in multimedia social networks (MSNs) mainly rely on access control models and mechanisms. Simple adoptions of security policies in the traditional access control model cannot effectively establish a trust relationship among parties. This paper proposed a novel two-party trust architecture (TPTA) to apply in a generic MSN scenario. According to the architecture, security policies are adopted through game-theoretic analyses and decisions. Based on formalized utilities of security policies and security rules, the choice of security policies in content access is described as a game between the content provider and the content requester. By the game method for the combination of security policies utility and its influences on each party's benefits, the Nash equilibrium is achieved, that is, an optimal and stable combination of security policies, to establish and enhance trust among stakeholders. PMID:24977226
Review Essay: Does Qualitative Network Analysis Exist?
Directory of Open Access Journals (Sweden)
Rainer Diaz-Bone
2007-01-01
Full Text Available Social network analysis was formed and established in the 1970s as a way of analyzing systems of social relations. In this review the theoretical-methodological standpoint of social network analysis ("structural analysis" is introduced and the different forms of social network analysis are presented. Structural analysis argues that social actors and social relations are embedded in social networks, meaning that action and perception of actors as well as the performance of social relations are influenced by the network structure. Since the 1990s structural analysis has integrated concepts such as agency, discourse and symbolic orientation and in this way structural analysis has opened itself. Since then there has been increasing use of qualitative methods in network analysis. They are used to include the perspective of the analyzed actors, to explore networks, and to understand network dynamics. In the reviewed book, edited by Betina HOLLSTEIN and Florian STRAUS, the twenty predominantly empirically orientated contributions demonstrate the possibilities of combining quantitative and qualitative methods in network analyses in different research fields. In this review we examine how the contributions succeed in applying and developing the structural analysis perspective, and the self-positioning of "qualitative network analysis" is evaluated. URN: urn:nbn:de:0114-fqs0701287
Game-theoretic pricing for video streaming in mobile networks.
Lin, W Sabrina; Liu, K J Ray
2012-05-01
Mobile phones are among the most popular consumer devices, and the recent developments of 3G networks and smart phones enable users to watch video programs by subscribing data plans from service providers. Due to the ubiquity of mobile phones and phone-to-phone communication technologies, data-plan subscribers can redistribute the video content to nonsubscribers. Such a redistribution mechanism is a potential competitor for the mobile service provider and is very difficult to trace given users' high mobility. The service provider has to set a reasonable price for the data plan to prevent such unauthorized redistribution behavior to protect or maximize his/her own profit. In this paper, we analyze the optimal price setting for the service provider by investigating the equilibrium between the subscribers and the secondary buyers in the content-redistribution network. We model the behavior between the subscribers and the secondary buyers as a noncooperative game and find the optimal price and quantity for both groups of users. Based on the behavior of users in the redistribution network, we investigate the evolutionarily stable ratio of mobile users who decide to subscribe to the data plan. Such an analysis can help the service provider preserve his/her profit under the threat of the redistribution networks and can improve the quality of service for end users.
Theoretical and methodological approaches in discourse analysis.
Stevenson, Chris
2004-01-01
Discourse analysis (DA) embodies two main approaches: Foucauldian DA and radical social constructionist DA. Both are underpinned by social constructionism to a lesser or greater extent. Social constructionism has contested areas in relation to power, embodiment, and materialism, although Foucauldian DA does focus on the issue of power Embodiment and materialism may be especially relevant for researchers of nursing where the physical body is prominent. However, the contested nature of social constructionism allows a fusion of theoretical and methodological approaches tailored to a specific research interest. In this paper, Chris Stevenson suggests a framework for working out and declaring the DA approach to be taken in relation to a research area, as well as to aid anticipating methodological critique. Method, validity, reliability and scholarship are discussed from within a discourse analytic frame of reference.
Theoretical and methodological approaches in discourse analysis.
Stevenson, Chris
2004-10-01
Discourse analysis (DA) embodies two main approaches: Foucauldian DA and radical social constructionist DA. Both are underpinned by social constructionism to a lesser or greater extent. Social constructionism has contested areas in relation to power, embodiment, and materialism, although Foucauldian DA does focus on the issue of power. Embodiment and materialism may be especially relevant for researchers of nursing where the physical body is prominent. However, the contested nature of social constructionism allows a fusion of theoretical and methodological approaches tailored to a specific research interest. In this paper, Chris Stevenson suggests a frame- work for working out and declaring the DA approach to be taken in relation to a research area, as well as to aid anticipating methodological critique. Method, validity, reliability and scholarship are discussed from within a discourse analytic frame of reference.
Functional Module Analysis for Gene Coexpression Networks with Network Integration.
Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K
2015-01-01
Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.
Bonald, Thomas
2013-01-01
The book presents some key mathematical tools for the performance analysis of communication networks and computer systems.Communication networks and computer systems have become extremely complex. The statistical resource sharing induced by the random behavior of users and the underlying protocols and algorithms may affect Quality of Service.This book introduces the main results of queuing theory that are useful for analyzing the performance of these systems. These mathematical tools are key to the development of robust dimensioning rules and engineering methods. A number of examples i
Network systems security analysis
Yilmaz, Ä.°smail
2015-05-01
Network Systems Security Analysis has utmost importance in today's world. Many companies, like banks which give priority to data management, test their own data security systems with "Penetration Tests" by time to time. In this context, companies must also test their own network/server systems and take precautions, as the data security draws attention. Based on this idea, the study cyber-attacks are researched throughoutly and Penetration Test technics are examined. With these information on, classification is made for the cyber-attacks and later network systems' security is tested systematically. After the testing period, all data is reported and filed for future reference. Consequently, it is found out that human beings are the weakest circle of the chain and simple mistakes may unintentionally cause huge problems. Thus, it is clear that some precautions must be taken to avoid such threats like updating the security software.
Game Theoretic Analysis of Road Traffic Problems in Nigeria ...
African Journals Online (AJOL)
Game Theoretic Analysis of Road Traffic Problems in Nigeria. ... problems in Nigeria are analysed in the context of a social dilemma. Game theoretic models based on the famous ... AJOL African Journals Online. HOW TO USE AJOL.
Gebali, Fayez
2015-01-01
This textbook presents the mathematical theory and techniques necessary for analyzing and modeling high-performance global networks, such as the Internet. The three main building blocks of high-performance networks are links, switching equipment connecting the links together, and software employed at the end nodes and intermediate switches. This book provides the basic techniques for modeling and analyzing these last two components. Topics covered include, but are not limited to: Markov chains and queuing analysis, traffic modeling, interconnection networks and switch architectures and buffering strategies. · Provides techniques for modeling and analysis of network software and switching equipment; · Discusses design options used to build efficient switching equipment; · Includes many worked examples of the application of discrete-time Markov chains to communication systems; · Covers the mathematical theory and techniques necessary for ana...
Game Theoretic Solutions to Cyber Attack and Network Defense Problems
National Research Council Canada - National Science Library
Shen, Dan; Chen, Genshe; Cruz, Jr., , Jose B; Blasch, Erik; Kruger, Martin
2007-01-01
.... The protection and defense against cyber attacks to computer network is becoming inadequate as the hacker knowledge sophisticates and as the network and each computer system become more complex...
Nanoscale molecular communication networks: a game-theoretic perspective
Jiang, Chunxiao; Chen, Yan; Ray Liu, K. J.
2015-12-01
Currently, communication between nanomachines is an important topic for the development of novel devices. To implement a nanocommunication system, diffusion-based molecular communication is considered as a promising bio-inspired approach. Various technical issues about molecular communications, including channel capacity, noise and interference, and modulation and coding, have been studied in the literature, while the resource allocation problem among multiple nanomachines has not been well investigated, which is a very important issue since all the nanomachines share the same propagation medium. Considering the limited computation capability of nanomachines and the expensive information exchange cost among them, in this paper, we propose a game-theoretic framework for distributed resource allocation in nanoscale molecular communication systems. We first analyze the inter-symbol and inter-user interference, as well as bit error rate performance, in the molecular communication system. Based on the interference analysis, we formulate the resource allocation problem as a non-cooperative molecule emission control game, where the Nash equilibrium is found and proved to be unique. In order to improve the system efficiency while guaranteeing fairness, we further model the resource allocation problem using a cooperative game based on the Nash bargaining solution, which is proved to be proportionally fair. Simulation results show that the Nash bargaining solution can effectively ensure fairness among multiple nanomachines while achieving comparable social welfare performance with the centralized scheme.
Physical Violence between Siblings: A Theoretical and Empirical Analysis
Hoffman, Kristi L.; Kiecolt, K. Jill; Edwards, John N.
2005-01-01
This study develops and tests a theoretical model to explain sibling violence based on the feminist, conflict, and social learning theoretical perspectives and research in psychology and sociology. A multivariate analysis of data from 651 young adults generally supports hypotheses from all three theoretical perspectives. Males with brothers have…
Sone, Daichi; Matsuda, Hiroshi; Ota, Miho; Maikusa, Norihide; Kimura, Yukio; Sumida, Kaoru; Yokoyama, Kota; Imabayashi, Etsuko; Watanabe, Masako; Watanabe, Yutaka; Okazaki, Mitsutoshi; Sato, Noriko
2016-09-01
Graph theory is an emerging method to investigate brain networks. Altered cerebral blood flow (CBF) has frequently been reported in temporal lobe epilepsy (TLE), but graph theoretical findings of CBF are poorly understood. Here, we explored graph theoretical networks of CBF in TLE using arterial spin labeling imaging. We recruited patients with TLE and unilateral hippocampal sclerosis (HS) (19 patients with left TLE, and 21 with right TLE) and 20 gender- and age-matched healthy control subjects. We obtained all participants' CBF maps using pseudo-continuous arterial spin labeling and analyzed them using the Graph Analysis Toolbox (GAT) software program. As a result, compared to the controls, the patients with left TLE showed a significantly low clustering coefficient (p=0.024), local efficiency (p=0.001), global efficiency (p=0.010), and high transitivity (p=0.015), whereas the patients with right TLE showed significantly high assortativity (p=0.046) and transitivity (p=0.011). The group with right TLE also had high characteristic path length values (p=0.085), low global efficiency (p=0.078), and low resilience to targeted attack (p=0.101) at a trend level. Lower normalized clustering coefficient (p=0.081) in the left TLE and higher normalized characteristic path length (p=0.089) in the right TLE were found also at a trend level. Both the patients with left and right TLE showed significantly decreased clustering in similar areas, i.e., the cingulate gyri, precuneus, and occipital lobe. Our findings revealed differing left-right network metrics in which an inefficient CBF network in left TLE and vulnerability to irritation in right TLE are suggested. The left-right common finding of regional decreased clustering might reflect impaired default-mode networks in TLE. Copyright © 2016 Elsevier Inc. All rights reserved.
Competitive game theoretic optimal routing in optical networks
Yassine, Abdulsalam; Kabranov, Ognian; Makrakis, Dimitrios
2002-09-01
Optical transport service providers need control and optimization strategies for wavelength management, network provisioning, restoration and protection, allowing them to define and deploy new services and maintain competitiveness. In this paper, we investigate a game theory based model for wavelength and flow assignment in multi wavelength optical networks, consisting of several backbone long-haul optical network transport service providers (TSPs) who are offering their services -in terms of bandwidth- to Internet service providers (ISPs). The ISPs act as brokers or agents between the TSP and end user. The agent (ISP) buys services (bandwidth) from the TSP. The TSPs compete among themselves to sell their services and maintain profitability. We present a case study, demonstrating the impact of different bandwidth broker demands on the supplier's profit and the price paid by the network broker.
Sensor and ad-hoc networks theoretical and algorithmic aspects
Makki, S Kami; Pissinou, Niki; Makki, Shamila; Karimi, Masoumeh; Makki, Kia
2008-01-01
This book brings together leading researchers and developers in the field of wireless sensor networks to explain the special problems and challenges of the algorithmic aspects of sensor and ad-hoc networks. The book also fosters communication not only between the different sensor and ad-hoc communities, but also between those communities and the distributed systems and information systems communities. The topics addressed pertain to the sensors and mobile environment.
THEORETICAL EVALUATION OF NONLINEAR EFFECTS ON OPTICAL WDM NETWORKS WITH VARIOUS FIBER TYPES
Directory of Open Access Journals (Sweden)
YASIN M. KARFAA
2010-09-01
Full Text Available A theoretical study is carried out to evaluate the performance of an opticalwavelength division multiplexing (WDM network transmission system in the presenceof crosstalk due to optical fiber nonlinearities. The most significant nonlinear effects inthe optical fiber which are Cross-Phase Modulation (XPM, Four-Wave Mixing (FWM,and Stimulated Raman Scattering (SRS are investigated. Four types of optical fiber areincluded in the analysis; these are: single-mode fiber (SMF, dispersion compensationfiber (DCF, non-zero dispersion fiber (NZDF, and non-zero dispersion shifted fiber(NZDSF. The results represent the standard deviation of nonlinearity induced crosstalknoise power due to FWM and SRS, XPM power penalty for SMF, DCF, NZDF, andNZDSF types of fiber, besides the Bit Error Rate (BER for the three nonlinear effectsusing standard fiber type (SMF. It is concluded that three significant fiber nonlinearitiesare making huge limitations against increasing the launched power which is desired,otherwise, lower values of launched power limit network expansion including length,distance, covered areas, and number of users accessing the WDM network, unlesssuitable precautions are taken to neutralize the nonlinear effects. Besides, various fibertypes are not behaving similarly towards network parameters.
Study of network resource allocation based on market and game theoretic mechanism
Liu, Yingmei; Wang, Hongwei; Wang, Gang
2004-04-01
We work on the network resource allocation issue concerning network management system function based on market-oriented mechanism. The scheme is to model the telecommunication network resources as trading goods in which the various network components could be owned by different competitive, real-world entities. This is a multidisciplinary framework concentrating on the similarity between resource allocation in network environment and the market mechanism in economic theory. By taking an economic (market-based and game theoretic) approach in routing of communication network, we study the dynamic behavior under game-theoretic framework in allocating network resources. Based on the prior work of Gibney and Jennings, we apply concepts of utility and fitness to the market mechanism with an intention to close the gap between experiment environment and real world situation.
Adaptation in Food Networks: Theoretical Framework and Empirical Evidences
Directory of Open Access Journals (Sweden)
Gaetano Martino
2013-03-01
Full Text Available The paper concerns the integration in food networks under a governance point of view. We conceptualize the integration processes in terms of the adaptation theory and focus the issues related under a transaction cost economics perspective. We conjecture that the allocation of decisions rights between the parties to a transaction is a key instrument in order to cope with the sources of basic uncertainty in food networks: technological innovation, sustainability strategies, quality and safety objectives. Six case studies are proposed which contribute to corroborate our conjecture. Managerial patters based on a joint decision approach also are documented
Game-theoretic strategies for asymmetric networked systems
Energy Technology Data Exchange (ETDEWEB)
Rao, Nageswara S. [ORNL; Ma, Chris Y. T. [Hang Seng Management College, Hon Kong; Hausken, Kjell [University of Stavanger, Norway; He, Fei [Texas A& M University, Kingsville, TX, USA; Yau, David K. Y. [Singapore University of Technology and Design; Zhuang, Jun [University at Buffalo (SUNY)
2017-07-01
Abstract—We consider an infrastructure consisting of a network of systems each composed of discrete components that can be reinforced at a certain cost to guard against attacks. The network provides the vital connectivity between systems, and hence plays a critical, asymmetric role in the infrastructure operations. We characterize the system-level correlations using the aggregate failure correlation function that specifies the infrastructure failure probability given the failure of an individual system or network. The survival probabilities of systems and network satisfy first-order differential conditions that capture the component-level correlations. We formulate the problem of ensuring the infrastructure survival as a game between anattacker and a provider, using the sum-form and product-form utility functions, each composed of a survival probability term and a cost term. We derive Nash Equilibrium conditions which provide expressions for individual system survival probabilities, and also the expected capacity specified by the total number of operational components. These expressions differ only in a single term for the sum-form and product-form utilities, despite their significant differences.We apply these results to simplified models of distributed cloud computing infrastructures.
Network Analysis, Architecture, and Design
McCabe, James D
2007-01-01
Traditionally, networking has had little or no basis in analysis or architectural development, with designers relying on technologies they are most familiar with or being influenced by vendors or consultants. However, the landscape of networking has changed so that network services have now become one of the most important factors to the success of many third generation networks. It has become an important feature of the designer's job to define the problems that exist in his network, choose and analyze several optimization parameters during the analysis process, and then prioritize and evalua
A measure theoretic approach to traffic flow optimization on networks
Cacace, Simone; Camilli, Fabio; De Maio, Raul; Tosin, Andrea
2018-01-01
We consider a class of optimal control problems for measure-valued nonlinear transport equations describing traffic flow problems on networks. The objective isto minimise/maximise macroscopic quantities, such as traffic volume or average speed,controlling few agents, for example smart traffic lights and automated cars. The measuretheoretic approach allows to study in a same setting local and nonlocal drivers interactionsand to consider the control variables as additional measures interacting ...
SEMANTIC NETWORKS: THEORETICAL, TECHNICAL, METHODOLOGIC AND ANALYTICAL ASPECTS
Directory of Open Access Journals (Sweden)
José Ángel Vera Noriega
2005-09-01
Full Text Available This work is a review of the methodological procedures and cares for the measurement of the connotative meanings which will be used in the elaboration of instruments with ethnic validity. Beginning from the techniques originally proposed by Figueroa et al. (1981 and later described by Lagunes (1993, the intention is to offer a didactic panorama to carry out the measurement by semantic networks introducing some recommendations derived from the studies performed with this method.
A theoretical design for learning model addressing the networked society
DEFF Research Database (Denmark)
Levinsen, Karin; Nielsen, Janni; Sørensen, Birgitte Holm
2010-01-01
The transition from the industrial to the networked society produces contradictions that challenges the educational system and force it to adapt to new conditions. In a Danish virtual Master in Information and Communication Technologies and Learning (MIL) these contradictions appear as a field of...... which enables students to develop Networked Society competencies and maintain progression in the learning process also during the online periods. Additionally we suggest that our model contributes to the innovation of a networked society's design for learning....... is continuously decreasing. We teach for deep learning but are confronted by students' cost-benefit strategies when they navigate through the study programme under time pressure. To meet these challenges a Design for Learning Model has been developed. The aim is to provide a scaffold that ensures students......' acquisition of the subject matter within a time limit and at a learning quality that support their deep learning process during a subsequent period of on-line study work. In the process of moving from theory to application the model passes through three stages: 1) Conceptual modelling; 2) Orchestration, and 3...
On the design of a hierarchical SS7 network: A graph theoretical approach
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.
Energy Technology Data Exchange (ETDEWEB)
Kalb, Jeffrey L.; Lee, David S.
2008-01-01
Emerging high-bandwidth, low-latency network technology has made network-based architectures both feasible and potentially desirable for use in satellite payload architectures. The selection of network topology is a critical component when developing these multi-node or multi-point architectures. This study examines network topologies and their effect on overall network performance. Numerous topologies were reviewed against a number of performance, reliability, and cost metrics. This document identifies a handful of good network topologies for satellite applications and the metrics used to justify them as such. Since often multiple topologies will meet the requirements of the satellite payload architecture under development, the choice of network topology is not easy, and in the end the choice of topology is influenced by both the design characteristics and requirements of the overall system and the experience of the developer.
Space Debris Removal: A Game Theoretic Analysis
Directory of Open Access Journals (Sweden)
Richard Klima
2016-08-01
Full Text Available We analyse active space debris removal efforts from a strategic, game-theoretical perspective. Space debris is non-manoeuvrable, human-made objects orbiting Earth, which pose a significant threat to operational spacecraft. Active debris removal missions have been considered and investigated by different space agencies with the goal to protect valuable assets present in strategic orbital environments. An active debris removal mission is costly, but has a positive effect for all satellites in the same orbital band. This leads to a dilemma: each agency is faced with the choice between the individually costly action of debris removal, which has a positive impact on all players; or wait and hope that others jump in and do the ‘dirty’ work. The risk of the latter action is that, if everyone waits, the joint outcome will be catastrophic, leading to what in game theory is referred to as the ‘tragedy of the commons’. We introduce and thoroughly analyse this dilemma using empirical game theory and a space debris simulator. We consider two- and three-player settings, investigate the strategic properties and equilibria of the game and find that the cost/benefit ratio of debris removal strongly affects the game dynamics.
Landscape analysis: Theoretical considerations and practical needs
Godfrey, A.E.; Cleaves, E.T.
1991-01-01
Numerous systems of land classification have been proposed. Most have led directly to or have been driven by an author's philosophy of earth-forming processes. However, the practical need of classifying land for planning and management purposes requires that a system lead to predictions of the results of management activities. We propose a landscape classification system composed of 11 units, from realm (a continental mass) to feature (a splash impression). The classification concerns physical aspects rather than economic or social factors; and aims to merge land inventory with dynamic processes. Landscape units are organized using a hierarchical system so that information may be assembled and communicated at different levels of scale and abstraction. Our classification uses a geomorphic systems approach that emphasizes the geologic-geomorphic attributes of the units. Realm, major division, province, and section are formulated by subdividing large units into smaller ones. For the larger units we have followed Fenneman's delineations, which are well established in the North American literature. Areas and districts are aggregated into regions and regions into sections. Units smaller than areas have, in practice, been subdivided into zones and smaller units if required. We developed the theoretical framework embodied in this classification from practical applications aimed at land use planning and land management in Maryland (eastern Piedmont Province near Baltimore) and Utah (eastern Uinta Mountains). ?? 1991 Springer-Verlag New York Inc.
Shi, Chenguang; Salous, Sana; Wang, Fei; Zhou, Jianjiang
2017-08-01
Distributed radar network systems have been shown to have many unique features. Due to their advantage of signal and spatial diversities, radar networks are attractive for target detection. In practice, the netted radars in radar networks are supposed to maximize their transmit power to achieve better detection performance, which may be in contradiction with low probability of intercept (LPI). Therefore, this paper investigates the problem of adaptive power allocation for radar networks in a cooperative game-theoretic framework such that the LPI performance can be improved. Taking into consideration both the transmit power constraints and the minimum signal to interference plus noise ratio (SINR) requirement of each radar, a cooperative Nash bargaining power allocation game based on LPI is formulated, whose objective is to minimize the total transmit power by optimizing the power allocation in radar networks. First, a novel SINR-based network utility function is defined and utilized as a metric to evaluate power allocation. Then, with the well-designed network utility function, the existence and uniqueness of the Nash bargaining solution are proved analytically. Finally, an iterative Nash bargaining algorithm is developed that converges quickly to a Pareto optimal equilibrium for the cooperative game. Numerical simulations and theoretic analysis are provided to evaluate the effectiveness of the proposed algorithm.
Theoretical analysis of the PCA experiment
International Nuclear Information System (INIS)
Minsart, G.
1980-01-01
A very brief description of the PCA-PVF facility is given, and the studied configurations are mentioned. The analysis of the experiment has been divided into two parts: study of the fission density distribution across the PCA core and neutronic analysis of the flux spectra and spatial distributions in the whole facility. For both parts, the procedure of calculation is explained: cross section sets, one- and two-dimensional models, group collapsing, choice of bucklings, ... . The obtained results are shortly compared with the measured values, and illustrated by a figure and several tables. The computations of the fission map in the PCA core yield results in good agreement with the experimental ones (within a few percents for nearly all points). The discrepancies observed for relative reaction rates and spectral indices of a series of threshold detectors at the selected locations in and between steel and iron layers in the water reflector are briefly discussed
Empirical and theoretical analysis of complex systems
Zhao, Guannan
This thesis is an interdisciplinary work under the heading of complexity science which focuses on an arguably common "hard" problem across physics, finance and biology [1], to quantify and mimic the macroscopic "emergent phenomenon" in large-scale systems consisting of many interacting "particles" governed by microscopic rules. In contrast to traditional statistical physics, we are interested in systems whose dynamics are subject to feedback, evolution, adaption, openness, etc. Global financial markets, like the stock market and currency market, are ideal candidate systems for such a complexity study: there exists a vast amount of accurate data, which is the aggregate output of many autonomous agents continuously competing with each other. We started by examining the ultrafast "mini flash crash (MFC)" events in the US stock market. An abrupt system-wide composition transition from a mixed human machine phase to a new all-machine phase is uncovered, and a novel theory developed to explain this observation. Then in the study of FX market, we found an unexpected variation in the synchronicity of price changes in different market subsections as a function of the overall trading activity. Several survival models have been tested in analyzing the distribution of waiting times to the next price change. In the region of long waiting-times, the distribution for each currency pair exhibits a power law with exponent in the vicinity of 3.5. By contrast, for short waiting times only, the market activity can be mimicked by the fluctuations emerging from a finite resource competition model containing multiple agents with limited rationality (so called El Farol Model). Switching to the biomedical domain, we present a minimal mathematical model built around a co-evolving resource network and cell population, yielding good agreement with primary tumors in mice experiment and with clinical metastasis data. In the quest to understand contagion phenomena in systems where social group
Theoretical basis for graphite stress analysis in BERSAFE
International Nuclear Information System (INIS)
Harper, P.G.
1980-03-01
The BERSAFE finite element computer program for structural analysis has been extended to deal with structures made from irradiated graphite. This report describes the material behaviour which has been modelled and gives the theoretical basis for the solution procedure. (author)
Prompt radiation activation analysis, (1) Theoretical study
International Nuclear Information System (INIS)
EL Barouni, A. M.; Araddad, S. Y.; Mosbah, D. S.; Elfakhri, S. M.; Rateb, J. M.; Benghzail, M. A.
2004-01-01
The measurement of the prompt γ following neutron capture in the reaction has been extensively developed. In this method the gamma-ray intensity is depended only upon the radiative capture cross-section and not upon the half-life of the product nucleus. The prompt gamma-ray activation analysis method stems from the radiative capture process which results in the decay of the compound nucleus by the emission of characteristic gamma radiation, either as a single photon with kinetic energy equal to the excitation energy less the recoil energy or, more likely, by a cascade of two or more photons with the same energy. The equations and the computer program required to calculate the yield, the intensity and the K χ emission probability per disintegration, are given in this study.(author)
Gender and Physics: a Theoretical Analysis
Rolin, Kristina
This article argues that the objections raised by Koertge (1998), Gross and Levitt (1994), and Weinberg (1996) against feminist scholarship on gender and physics are unwarranted. The objections are that feminist science studies perpetuate gender stereotypes, are irrelevant to the content of physics, or promote epistemic relativism. In the first part of this article I argue that the concept of gender, as it has been developed in feminist theory, is a key to understanding why the first objection is misguided. Instead of reinforcing gender stereotypes, feminist science studies scholars can formulate empirically testable hypotheses regarding local and contested beliefs about gender. In the second part of this article I argue that a social analysis of scientific knowledge is a key to understanding why the second and the third objections are misguided. The concept of gender is relevant for understanding the social practice of physics, and the social practice of physics can be of epistemic importance. Instead of advancing epistemic relativism, feminist science studies scholars can make important contributions to a subfield of philosophy called social epistemology.
Theoretical characterization of the topology of connected carbon nanotubes in random networks
International Nuclear Information System (INIS)
Heitz, Jerome; Leroy, Yann; Hebrard, Luc; Lallement, Christophe
2011-01-01
In recent years, a lot of attention has been paid to carbon nanotube (CNT) networks and their applications to electronic devices. Many studies concentrate on the percolation threshold and the characterization of the conduction in such materials. Nevertheless, no theoretical study has yet attempted to characterize the CNT features inside finite size CNT networks. We present a theoretical approach based on geometrical and statistical considerations. We demonstrate the possibility of explicitly determining some relations existing between two neighbor CNTs and their contact efficiency in random networks of identical CNTs. We calculate the contact probability of rigid identical CNTs and we obtain a probability of 0.2027, which turns out to be independent of the CNT density. Based on this probability, we establish also the dependence of the number of contacts per CNT as a function of the CNT density. All the theoretical results are validated by very good agreement with Monte Carlo simulations.
Directory of Open Access Journals (Sweden)
Anderson Tiago Peixoto Gonçalves
2016-08-01
Full Text Available This theoretical essay aims to reflect on three models of text interpretation used in qualitative research, which is often confused in its concepts and methodologies (Content Analysis, Discourse Analysis, and Conversation Analysis. After the presentation of the concepts, the essay proposes a preliminary discussion on conceptual and theoretical methodological differences perceived between them. A review of the literature was performed to support the conceptual and theoretical methodological discussion. It could be verified that the models have differences related to the type of strategy used in the treatment of texts, the type of approach, and the appropriate theoretical position.
Artificial Neural Network Analysis System
2001-02-27
Contract No. DASG60-00-M-0201 Purchase request no.: Foot in the Door-01 Title Name: Artificial Neural Network Analysis System Company: Atlantic... Artificial Neural Network Analysis System 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) Powell, Bruce C 5d. PROJECT NUMBER 5e. TASK NUMBER...34) 27-02-2001 Report Type N/A Dates Covered (from... to) ("DD MON YYYY") 28-10-2000 27-02-2001 Title and Subtitle Artificial Neural Network Analysis
Theoretical Neuroanatomy:Analyzing the Structure, Dynamics,and Function of Neuronal Networks
Seth, Anil K.; Edelman, Gerald M.
The mammalian brain is an extraordinary object: its networks give rise to our conscious experiences as well as to the generation of adaptive behavior for the organism within its environment. Progress in understanding the structure, dynamics and function of the brain faces many challenges. Biological neural networks change over time, their detailed structure is difficult to elucidate, and they are highly heterogeneous both in their neuronal units and synaptic connections. In facing these challenges, graph-theoretic and information-theoretic approaches have yielded a number of useful insights and promise many more.
Mathematical Analysis of Urban Spatial Networks
Blanchard, Philippe
2009-01-01
Cities can be considered to be among the largest and most complex artificial networks created by human beings. Due to the numerous and diverse human-driven activities, urban network topology and dynamics can differ quite substantially from that of natural networks and so call for an alternative method of analysis. The intent of the present monograph is to lay down the theoretical foundations for studying the topology of compact urban patterns, using methods from spectral graph theory and statistical physics. These methods are demonstrated as tools to investigate the structure of a number of real cities with widely differing properties: medieval German cities, the webs of city canals in Amsterdam and Venice, and a modern urban structure such as found in Manhattan. Last but not least, the book concludes by providing a brief overview of possible applications that will eventually lead to a useful body of knowledge for architects, urban planners and civil engineers.
Computational Social Network Analysis
Hassanien, Aboul-Ella
2010-01-01
Presents insight into the social behaviour of animals (including the study of animal tracks and learning by members of the same species). This book provides web-based evidence of social interaction, perceptual learning, information granulation and the behaviour of humans and affinities between web-based social networks
Network analysis applications in hydrology
Price, Katie
2017-04-01
Applied network theory has seen pronounced expansion in recent years, in fields such as epidemiology, computer science, and sociology. Concurrent development of analytical methods and frameworks has increased possibilities and tools available to researchers seeking to apply network theory to a variety of problems. While water and nutrient fluxes through stream systems clearly demonstrate a directional network structure, the hydrological applications of network theory remain underexplored. This presentation covers a review of network applications in hydrology, followed by an overview of promising network analytical tools that potentially offer new insights into conceptual modeling of hydrologic systems, identifying behavioral transition zones in stream networks and thresholds of dynamical system response. Network applications were tested along an urbanization gradient in Atlanta, Georgia, USA. Peachtree Creek and Proctor Creek. Peachtree Creek contains a nest of five longterm USGS streamflow and water quality gages, allowing network application of longterm flow statistics. The watershed spans a range of suburban and heavily urbanized conditions. Summary flow statistics and water quality metrics were analyzed using a suite of network analysis techniques, to test the conceptual modeling and predictive potential of the methodologies. Storm events and low flow dynamics during Summer 2016 were analyzed using multiple network approaches, with an emphasis on tomogravity methods. Results indicate that network theory approaches offer novel perspectives for understanding long term and eventbased hydrological data. Key future directions for network applications include 1) optimizing data collection, 2) identifying "hotspots" of contaminant and overland flow influx to stream systems, 3) defining process domains, and 4) analyzing dynamic connectivity of various system components, including groundwatersurface water interactions.
Abnormalities of functional brain networks in pathological gambling: a graph-theoretical approach
Tschernegg, Melanie; Crone, Julia S.; Eigenberger, Tina; Schwartenbeck, Philipp; Fauth-Bühler, Mira; Lemènager, Tagrid; Mann, Karl; Thon, Natasha; Wurst, Friedrich M.; Kronbichler, Martin
2013-01-01
Functional neuroimaging studies of pathological gambling (PG) demonstrate alterations in frontal and subcortical regions of the mesolimbic reward system. However, most investigations were performed using tasks involving reward processing or executive functions. Little is known about brain network abnormalities during task-free resting state in PG. In the present study, graph-theoretical methods were used to investigate network properties of resting state functional magnetic resonance imaging data in PG. We compared 19 patients with PG to 19 healthy controls (HCs) using the Graph Analysis Toolbox (GAT). None of the examined global metrics differed between groups. At the nodal level, pathological gambler showed a reduced clustering coefficient in the left paracingulate cortex and the left juxtapositional lobe (supplementary motor area, SMA), reduced local efficiency in the left SMA, as well as an increased node betweenness for the left and right paracingulate cortex and the left SMA. At an uncorrected threshold level, the node betweenness in the left inferior frontal gyrus was decreased and increased in the caudate. Additionally, increased functional connectivity between fronto-striatal regions and within frontal regions has also been found for the gambling patients. These findings suggest that regions associated with the reward system demonstrate reduced segregation but enhanced integration while regions associated with executive functions demonstrate reduced integration. The present study makes evident that PG is also associated with abnormalities in the topological network structure of the brain during rest. Since alterations in PG cannot be explained by direct effects of abused substances on the brain, these findings will be of relevance for understanding functional connectivity in other addictive disorders. PMID:24098282
Abnormalities of Functional Brain Networks in Pathological Gambling: A Graph-Theoretical Approach
Directory of Open Access Journals (Sweden)
Melanie eTschernegg
2013-09-01
Full Text Available Functional neuroimaging studies of pathological gambling demonstrate alterations in frontal and subcortical regions of the mesolimbic reward system. However, most investigations were performed using tasks involving reward processing or executive functions. Little is known about brain network abnormalities during task-free resting state in pathological gambling. In the present study, graph-theoretical methods were used to investigate network properties of resting state functional MRI data in pathological gambling. We compared 19 patients with pathological gambling to 19 healthy controls using the Graph Analysis Toolbox (GAT. None of the examined global metrics differed between groups. At the nodal level, pathological gambler showed a reduced clustering coefficient in the left paracingulate cortex and the left juxtapositional lobe (SMA, reduced local efficiency in the left SMA, as well as an increased node betweenness for the left and right paracingulate cortex and the left SMA. At an uncorrected threshold level, the node betweenness in the left inferior frontal gyrus was decreased and increased in the caudate. Additionally, increased functional connectivity between fronto-striatal regions and within frontal regions has also been found for the gambling patients.These findings suggest that regions associated with the reward system demonstrate reduced segregation but enhanced integration while regions associated with executive functions demonstrate reduced integration. The present study makes evident that pathological gambling is also associated with abnormalities in the topological network structure of the brain during rest. Since alterations in pathological gambling cannot be explained by direct effects of abused substances on the brain, these findings will be of relevance for understanding functional connectivity in other addictive disorders.
Integrating neural network technology and noise analysis
International Nuclear Information System (INIS)
Uhrig, R.E.; Oak Ridge National Lab., TN
1995-01-01
The integrated use of neural network and noise analysis technologies offers advantages not available by the use of either technology alone. The application of neural network technology to noise analysis offers an opportunity to expand the scope of problems where noise analysis is useful and unique ways in which the integration of these technologies can be used productively. The two-sensor technique, in which the responses of two sensors to an unknown driving source are related, is used to demonstration such integration. The relationship between power spectral densities (PSDs) of accelerometer signals is derived theoretically using noise analysis to demonstrate its uniqueness. This relationship is modeled from experimental data using a neural network when the system is working properly, and the actual PSD of one sensor is compared with the PSD of that sensor predicted by the neural network using the PSD of the other sensor as an input. A significant deviation between the actual and predicted PSDs indicate that system is changing (i.e., failing). Experiments carried out on check values and bearings illustrate the usefulness of the methodology developed. (Author)
Graph theoretical analysis of EEG functional connectivity during music perception.
Wu, Junjie; Zhang, Junsong; Liu, Chu; Liu, Dongwei; Ding, Xiaojun; Zhou, Changle
2012-11-05
The present study evaluated the effect of music on large-scale structure of functional brain networks using graph theoretical concepts. While most studies on music perception used Western music as an acoustic stimulus, Guqin music, representative of Eastern music, was selected for this experiment to increase our knowledge of music perception. Electroencephalography (EEG) was recorded from non-musician volunteers in three conditions: Guqin music, noise and silence backgrounds. Phase coherence was calculated in the alpha band and between all pairs of EEG channels to construct correlation matrices. Each resulting matrix was converted into a weighted graph using a threshold, and two network measures: the clustering coefficient and characteristic path length were calculated. Music perception was found to display a higher level mean phase coherence. Over the whole range of thresholds, the clustering coefficient was larger while listening to music, whereas the path length was smaller. Networks in music background still had a shorter characteristic path length even after the correction for differences in mean synchronization level among background conditions. This topological change indicated a more optimal structure under music perception. Thus, prominent small-world properties are confirmed in functional brain networks. Furthermore, music perception shows an increase of functional connectivity and an enhancement of small-world network organizations. Copyright © 2012 Elsevier B.V. All rights reserved.
A study of brain networks associated with swallowing using graph-theoretical approaches.
Directory of Open Access Journals (Sweden)
Bo Luan
Full Text Available Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, [Formula: see text] years of age. To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia.
Directory of Open Access Journals (Sweden)
Chenguang Shi
2014-01-01
Full Text Available Widely distributed radar network architectures can provide significant performance improvement for target detection and localization. For a fixed radar network, the achievable target detection performance may go beyond a predetermined threshold with full transmitted power allocation, which is extremely vulnerable in modern electronic warfare. In this paper, we study the problem of low probability of intercept (LPI design for radar network and propose two novel LPI optimization schemes based on information-theoretic criteria. For a predefined threshold of target detection, Schleher intercept factor is minimized by optimizing transmission power allocation among netted radars in the network. Due to the lack of analytical closed-form expression for receiver operation characteristics (ROC, we employ two information-theoretic criteria, namely, Bhattacharyya distance and J-divergence as the metrics for target detection performance. The resulting nonconvex and nonlinear LPI optimization problems associated with different information-theoretic criteria are cast under a unified framework, and the nonlinear programming based genetic algorithm (NPGA is used to tackle the optimization problems in the framework. Numerical simulations demonstrate that our proposed LPI strategies are effective in enhancing the LPI performance for radar network.
Trimming of mammalian transcriptional networks using network component analysis
Directory of Open Access Journals (Sweden)
Liao James C
2010-10-01
Full Text Available Abstract Background Network Component Analysis (NCA has been used to deduce the activities of transcription factors (TFs from gene expression data and the TF-gene binding relationship. However, the TF-gene interaction varies in different environmental conditions and tissues, but such information is rarely available and cannot be predicted simply by motif analysis. Thus, it is beneficial to identify key TF-gene interactions under the experimental condition based on transcriptome data. Such information would be useful in identifying key regulatory pathways and gene markers of TFs in further studies. Results We developed an algorithm to trim network connectivity such that the important regulatory interactions between the TFs and the genes were retained and the regulatory signals were deduced. Theoretical studies demonstrated that the regulatory signals were accurately reconstructed even in the case where only three independent transcriptome datasets were available. At least 80% of the main target genes were correctly predicted in the extreme condition of high noise level and small number of datasets. Our algorithm was tested with transcriptome data taken from mice under rapamycin treatment. The initial network topology from the literature contains 70 TFs, 778 genes, and 1423 edges between the TFs and genes. Our method retained 1074 edges (i.e. 75% of the original edge number and identified 17 TFs as being significantly perturbed under the experimental condition. Twelve of these TFs are involved in MAPK signaling or myeloid leukemia pathways defined in the KEGG database, or are known to physically interact with each other. Additionally, four of these TFs, which are Hif1a, Cebpb, Nfkb1, and Atf1, are known targets of rapamycin. Furthermore, the trimmed network was able to predict Eno1 as an important target of Hif1a; this key interaction could not be detected without trimming the regulatory network. Conclusions The advantage of our new algorithm
Agha Mohammad Ali Kermani, Mehrdad; Fatemi Ardestani, Seyed Farshad; Aliahmadi, Alireza; Barzinpour, Farnaz
2017-01-01
Influence maximization deals with identification of the most influential nodes in a social network given an influence model. In this paper, a game theoretic framework is developed that models a competitive influence maximization problem. A novel competitive influence model is additionally proposed that incorporates user heterogeneity, message content, and network structure. The proposed game-theoretic model is solved using Nash Equilibrium in a real-world dataset. It is shown that none of the well-known strategies are stable and at least one player has the incentive to deviate from the proposed strategy. Moreover, violation of Nash equilibrium strategy by each player leads to their reduced payoff. Contrary to previous works, our results demonstrate that graph topology, as well as the nodes' sociability and initial tendency measures have an effect on the determination of the influential node in the network.
Heiden, Uwe
1980-01-01
The purpose of this work is a unified and general treatment of activity in neural networks from a mathematical pOint of view. Possible applications of the theory presented are indica ted throughout the text. However, they are not explored in de tail for two reasons : first, the universal character of n- ral activity in nearly all animals requires some type of a general approach~ secondly, the mathematical perspicuity would suffer if too many experimental details and empirical peculiarities were interspersed among the mathematical investigation. A guide to many applications is supplied by the references concerning a variety of specific issues. Of course the theory does not aim at covering all individual problems. Moreover there are other approaches to neural network theory (see e.g. Poggio-Torre, 1978) based on the different lev els at which the nervous system may be viewed. The theory is a deterministic one reflecting the average be havior of neurons or neuron pools. In this respect the essay is writt...
Transmission analysis in WDM networks
DEFF Research Database (Denmark)
Rasmussen, Christian Jørgen
1999-01-01
This thesis describes the development of a computer-based simulator for transmission analysis in optical wavelength division multiplexing networks. A great part of the work concerns fundamental optical network simulator issues. Among these issues are identification of the versatility and user...... the different component models are invoked during the simulation of a system. A simple set of rules which makes it possible to simulate any network architectures is laid down. The modelling of the nonlinear fibre and the optical receiver is also treated. The work on the fibre concerns the numerical solution...
Inform: Efficient Information-Theoretic Analysis of Collective Behaviors
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Douglas G. Moore
2018-06-01
Full Text Available The study of collective behavior has traditionally relied on a variety of different methodological tools ranging from more theoretical methods such as population or game-theoretic models to empirical ones like Monte Carlo or multi-agent simulations. An approach that is increasingly being explored is the use of information theory as a methodological framework to study the flow of information and the statistical properties of collectives of interacting agents. While a few general purpose toolkits exist, most of the existing software for information theoretic analysis of collective systems is limited in scope. We introduce Inform, an open-source framework for efficient information theoretic analysis that exploits the computational power of a C library while simplifying its use through a variety of wrappers for common higher-level scripting languages. We focus on two such wrappers here: PyInform (Python and rinform (R. Inform and its wrappers are cross-platform and general-purpose. They include classical information-theoretic measures, measures of information dynamics and information-based methods to study the statistical behavior of collective systems, and expose a lower-level API that allow users to construct measures of their own. We describe the architecture of the Inform framework, study its computational efficiency and use it to analyze three different case studies of collective behavior: biochemical information storage in regenerating planaria, nest-site selection in the ant Temnothorax rugatulus, and collective decision making in multi-agent simulations.
PRICE DISCRIMINATION AND MARKET POWER: A THEORETICAL ANALYSIS
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Olga Smirnova
2015-07-01
Full Text Available This paper analyzes the contemporary theoretical and empirical research in the field of impact assessment of market power and conclusions about the possibilities of the company to implement price discrimination in different market structures. The results of the analysis allow to evaluate current approaches to antitrust regulation of price discrimination.
Information-theoretical analysis of private content identification
Voloshynovskiy, S.; Koval, O.; Beekhof, F.; Farhadzadeh, F.; Holotyak, T.
2010-01-01
In recent years, content identification based on digital fingerprinting attracts a lot of attention in different emerging applications. At the same time, the theoretical analysis of digital fingerprinting systems for finite length case remains an open issue. Additionally, privacy leaks caused by
SiSn diodes: Theoretical analysis and experimental verification
Hussain, Aftab M.; Wehbe, Nimer; Hussain, Muhammad Mustafa
2015-01-01
We report a theoretical analysis and experimental verification of change in band gap of silicon lattice due to the incorporation of tin (Sn). We formed SiSn ultra-thin film on the top surface of a 4 in. silicon wafer using thermal diffusion of Sn
Reliability Analysis of Wireless Sensor Networks Using Markovian Model
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Jin Zhu
2012-01-01
Full Text Available This paper investigates reliability analysis of wireless sensor networks whose topology is switching among possible connections which are governed by a Markovian chain. We give the quantized relations between network topology, data acquisition rate, nodes' calculation ability, and network reliability. By applying Lyapunov method, sufficient conditions of network reliability are proposed for such topology switching networks with constant or varying data acquisition rate. With the conditions satisfied, the quantity of data transported over wireless network node will not exceed node capacity such that reliability is ensured. Our theoretical work helps to provide a deeper understanding of real-world wireless sensor networks, which may find its application in the fields of network design and topology control.
Antenna analysis using neural networks
Smith, William T.
1992-01-01
Conventional computing schemes have long been used to analyze problems in electromagnetics (EM). The vast majority of EM applications require computationally intensive algorithms involving numerical integration and solutions to large systems of equations. The feasibility of using neural network computing algorithms for antenna analysis is investigated. The ultimate goal is to use a trained neural network algorithm to reduce the computational demands of existing reflector surface error compensation techniques. Neural networks are computational algorithms based on neurobiological systems. Neural nets consist of massively parallel interconnected nonlinear computational elements. They are often employed in pattern recognition and image processing problems. Recently, neural network analysis has been applied in the electromagnetics area for the design of frequency selective surfaces and beam forming networks. The backpropagation training algorithm was employed to simulate classical antenna array synthesis techniques. The Woodward-Lawson (W-L) and Dolph-Chebyshev (D-C) array pattern synthesis techniques were used to train the neural network. The inputs to the network were samples of the desired synthesis pattern. The outputs are the array element excitations required to synthesize the desired pattern. Once trained, the network is used to simulate the W-L or D-C techniques. Various sector patterns and cosecant-type patterns (27 total) generated using W-L synthesis were used to train the network. Desired pattern samples were then fed to the neural network. The outputs of the network were the simulated W-L excitations. A 20 element linear array was used. There were 41 input pattern samples with 40 output excitations (20 real parts, 20 imaginary). A comparison between the simulated and actual W-L techniques is shown for a triangular-shaped pattern. Dolph-Chebyshev is a different class of synthesis technique in that D-C is used for side lobe control as opposed to pattern
Tube Bulge Process : Theoretical Analysis and Finite Element Simulations
International Nuclear Information System (INIS)
Velasco, Raphael; Boudeau, Nathalie
2007-01-01
This paper is focused on the determination of mechanics characteristics for tubular materials, using tube bulge process. A comparative study is made between two different models: theoretical model and finite element analysis. The theoretical model is completely developed, based first on a geometrical analysis of the tube profile during bulging, which is assumed to strain in arc of circles. Strain and stress analysis complete the theoretical model, which allows to evaluate tube thickness and state of stress, at any point of the free bulge region. Free bulging of a 304L stainless steel is simulated using Ls-Dyna 970. To validate FE simulations approach, a comparison between theoretical and finite elements models is led on several parameters such as: thickness variation at the free bulge region pole with bulge height, tube thickness variation with z axial coordinate, and von Mises stress variation with plastic strain. Finally, the influence of geometrical parameters deviations on flow stress curve is observed using analytical model: deviations of the tube outer diameter, its initial thickness and the bulge height measurement are taken into account to obtain a resulting error on plastic strain and von Mises stress
NET-2 Network Analysis Program
International Nuclear Information System (INIS)
Malmberg, A.F.
1974-01-01
The NET-2 Network Analysis Program is a general purpose digital computer program which solves the nonlinear time domain response and the linearized small signal frequency domain response of an arbitrary network of interconnected components. NET-2 is capable of handling a variety of components and has been applied to problems in several engineering fields, including electronic circuit design and analysis, missile flight simulation, control systems, heat flow, fluid flow, mechanical systems, structural dynamics, digital logic, communications network design, solid state device physics, fluidic systems, and nuclear vulnerability due to blast, thermal, gamma radiation, neutron damage, and EMP effects. Network components may be selected from a repertoire of built-in models or they may be constructed by the user through appropriate combinations of mathematical, empirical, and topological functions. Higher-level components may be defined by subnetworks composed of any combination of user-defined components and built-in models. The program provides a modeling capability to represent and intermix system components on many levels, e.g., from hole and electron spatial charge distributions in solid state devices through discrete and integrated electronic components to functional system blocks. NET-2 is capable of simultaneous computation in both the time and frequency domain, and has statistical and optimization capability. Network topology may be controlled as a function of the network solution. (U.S.)
Game-theoretic cooperativity in networks of self-interested units
Barto, Andrew G.
1986-08-01
The behavior of theoretical neural networks is often described in terms of competition and cooperation. I present an approach to network learning that is related to game and team problems in which competition and cooperation have more technical meanings. I briefly describe the application of stochastic learning automata to game and team problems and then present an adaptive element that is a synthesis of aspects of stochastic learning automata and typical neuron-like adaptive elements. These elements act as self-interested agents that work toward improving their performance with respect to their individual preference orderings. Networks of these elements can solve a variety of team decision problems, some of which take the form of layered networks in which the ``hidden units'' become appropriate functional components as they attempt to improve their own payoffs.
Game theoretic analysis of physical protection system design
International Nuclear Information System (INIS)
Canion, B.; Schneider, E.; Bickel, E.; Hadlock, C.; Morton, D.
2013-01-01
The physical protection system (PPS) of a fictional small modular reactor (SMR) facility have been modeled as a platform for a game theoretic approach to security decision analysis. To demonstrate the game theoretic approach, a rational adversary with complete knowledge of the facility has been modeled attempting a sabotage attack. The adversary adjusts his decisions in response to investments made by the defender to enhance the security measures. This can lead to a conservative physical protection system design. Since defender upgrades were limited by a budget, cost benefit analysis may be conducted upon security upgrades. One approach to cost benefit analysis is the efficient frontier, which depicts the reduction in expected consequence per incremental increase in the security budget
Theoretical analysis of balanced truncation for linear switched systems
DEFF Research Database (Denmark)
Petreczky, Mihaly; Wisniewski, Rafal; Leth, John-Josef
2012-01-01
In this paper we present theoretical analysis of model reduction of linear switched systems based on balanced truncation, presented in [1,2]. More precisely, (1) we provide a bound on the estimation error using L2 gain, (2) we provide a system theoretic interpretation of grammians and their singu......In this paper we present theoretical analysis of model reduction of linear switched systems based on balanced truncation, presented in [1,2]. More precisely, (1) we provide a bound on the estimation error using L2 gain, (2) we provide a system theoretic interpretation of grammians...... for showing this independence is realization theory of linear switched systems. [1] H. R. Shaker and R. Wisniewski, "Generalized gramian framework for model/controller order reduction of switched systems", International Journal of Systems Science, Vol. 42, Issue 8, 2011, 1277-1291. [2] H. R. Shaker and R....... Wisniewski, "Switched Systems Reduction Framework Based on Convex Combination of Generalized Gramians", Journal of Control Science and Engineering, 2009....
Meagher, Kate
2009-01-01
Do network theory really offer a suitable concept for the theorization of informal processes of economic regulation and institutional change? This working paper challenges both essentialist and skeptical attitudes to networks through an examination of the positive and negative effects of network governance in contemporary societies in a range of regional contexts. The analysis focuses on three broad principles of non-state organization - culture, agency and power - and their role in shaping p...
Network Analysis Tools: from biological networks to clusters and pathways.
Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques
2008-01-01
Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.
Statistical network analysis for analyzing policy networks
DEFF Research Database (Denmark)
Robins, Garry; Lewis, Jenny; Wang, Peng
2012-01-01
and policy network methodology is the development of statistical modeling approaches that can accommodate such dependent data. In this article, we review three network statistical methods commonly used in the current literature: quadratic assignment procedures, exponential random graph models (ERGMs......To analyze social network data using standard statistical approaches is to risk incorrect inference. The dependencies among observations implied in a network conceptualization undermine standard assumptions of the usual general linear models. One of the most quickly expanding areas of social......), and stochastic actor-oriented models. We focus most attention on ERGMs by providing an illustrative example of a model for a strategic information network within a local government. We draw inferences about the structural role played by individuals recognized as key innovators and conclude that such an approach...
SiSn diodes: Theoretical analysis and experimental verification
Hussain, Aftab M.
2015-08-24
We report a theoretical analysis and experimental verification of change in band gap of silicon lattice due to the incorporation of tin (Sn). We formed SiSn ultra-thin film on the top surface of a 4 in. silicon wafer using thermal diffusion of Sn. We report a reduction of 0.1 V in the average built-in potential, and a reduction of 0.2 V in the average reverse bias breakdown voltage, as measured across the substrate. These reductions indicate that the band gap of the silicon lattice has been reduced due to the incorporation of Sn, as expected from the theoretical analysis. We report the experimentally calculated band gap of SiSn to be 1.11 ± 0.09 eV. This low-cost, CMOS compatible, and scalable process offers a unique opportunity to tune the band gap of silicon for specific applications.
Statistical analysis of network data with R
Kolaczyk, Eric D
2014-01-01
Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk’s book Statistical Analysis of Network Data (Springer, 2009).
Experimental and theoretical analysis of cracking in drying soils
Lakshmikantha, M.R.
2009-01-01
The thesis focuses on the experimental and theoretical aspects of the process of cracking in drying soils. The results and conclusions were drawn from an exhaustive experimental campaign characterised by innovative multidisciplinary aspects incorporating Fracture Mechanics and classical Soil mechanics, aided with image analysis techniques. A detailed study of the previous works on the topic showed the absence of large scale fully monitored laboratory tests, while the existing studies were per...
Theoretical analysis of the rotational barrier of ethane.
Mo, Yirong; Gao, Jiali
2007-02-01
The understanding of the ethane rotation barrier is fundamental for structural theory and the conformational analysis of organic molecules and requires a consistent theoretical model to differentiate the steric and hyperconjugation effects. Due to recently renewed controversies over the barrier's origin, we developed a computational approach to probe the rotation barriers of ethane and its congeners in terms of steric repulsion, hyperconjugative interaction, and electronic and geometric relaxations. Our study reinstated that the conventional steric repulsion overwhelmingly dominates the barriers.
Monetary circuit and economy financing: a theoretical analysis.
Cavalieri, Duccio
1999-01-01
This is a theoretical analysis of the role of money and other less liquid financial assets in the financing of the private sector of a market economy. It is concerned, basically, with the functional relations between households, firms, banks and other financial institutions, and with those between certain financial instruments (money, deposits, credits and bonds). Attention is focused on the determinants of the money, credit and financial structure of the economy.
Arguel, Amaël; Perez-Concha, Oscar; Li, Simon Y W; Lau, Annie Y S
2018-02-01
The aim of this review was to identify general theoretical frameworks used in online social network interventions for behavioral change. To address this research question, a PRISMA-compliant systematic review was conducted. A systematic review (PROSPERO registration number CRD42014007555) was conducted using 3 electronic databases (PsycINFO, Pubmed, and Embase). Four reviewers screened 1788 abstracts. 15 studies were selected according to the eligibility criteria. Randomized controlled trials and controlled studies were assessed using Cochrane Collaboration's "risk-of-bias" tool, and narrative synthesis. Five eligible articles used the social cognitive theory as a framework to develop interventions targeting behavioral change. Other theoretical frameworks were related to the dynamics of social networks, intention models, and community engagement theories. Only one of the studies selected in the review mentioned a well-known theory from the field of health psychology. Conclusions were that guidelines are lacking in the design of online social network interventions for behavioral change. Existing theories and models from health psychology that are traditionally used for in situ behavioral change should be considered when designing online social network interventions in a health care setting. © 2016 John Wiley & Sons, Ltd.
A Game Theoretic Approach for Balancing Energy Consumption in Clustered Wireless Sensor Networks.
Yang, Liu; Lu, Yinzhi; Xiong, Lian; Tao, Yang; Zhong, Yuanchang
2017-11-17
Clustering is an effective topology control method in wireless sensor networks (WSNs), since it can enhance the network lifetime and scalability. To prolong the network lifetime in clustered WSNs, an efficient cluster head (CH) optimization policy is essential to distribute the energy among sensor nodes. Recently, game theory has been introduced to model clustering. Each sensor node is considered as a rational and selfish player which will play a clustering game with an equilibrium strategy. Then it decides whether to act as the CH according to this strategy for a tradeoff between providing required services and energy conservation. However, how to get the equilibrium strategy while maximizing the payoff of sensor nodes has rarely been addressed to date. In this paper, we present a game theoretic approach for balancing energy consumption in clustered WSNs. With our novel payoff function, realistic sensor behaviors can be captured well. The energy heterogeneity of nodes is considered by incorporating a penalty mechanism in the payoff function, so the nodes with more energy will compete for CHs more actively. We have obtained the Nash equilibrium (NE) strategy of the clustering game through convex optimization. Specifically, each sensor node can achieve its own maximal payoff when it makes the decision according to this strategy. Through plenty of simulations, our proposed game theoretic clustering is proved to have a good energy balancing performance and consequently the network lifetime is greatly enhanced.
Directory of Open Access Journals (Sweden)
JongHyup Lee
2016-08-01
Full Text Available For practical deployment of wireless sensor networks (WSN, WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections.
Lee, JongHyup; Pak, Dohyun
2016-01-01
For practical deployment of wireless sensor networks (WSN), WSNs construct clusters, where a sensor node communicates with other nodes in its cluster, and a cluster head support connectivity between the sensor nodes and a sink node. In hybrid WSNs, cluster heads have cellular network interfaces for global connectivity. However, when WSNs are active and the load of cellular networks is high, the optimal assignment of cluster heads to base stations becomes critical. Therefore, in this paper, we propose a game theoretic model to find the optimal assignment of base stations for hybrid WSNs. Since the communication and energy cost is different according to cellular systems, we devise two game models for TDMA/FDMA and CDMA systems employing power prices to adapt to the varying efficiency of recent wireless technologies. The proposed model is defined on the assumptions of the ideal sensing field, but our evaluation shows that the proposed model is more adaptive and energy efficient than local selections. PMID:27589743
Flory-Stockmayer analysis on reprocessable polymer networks
Li, Lingqiao; Chen, Xi; Jin, Kailong; Torkelson, John
Reprocessable polymer networks can undergo structure rearrangement through dynamic chemistries under proper conditions, making them a promising candidate for recyclable crosslinked materials, e.g. tires. This research field has been focusing on various chemistries. However, there has been lacking of an essential physical theory explaining the relationship between abundancy of dynamic linkages and reprocessability. Based on the classical Flory-Stockmayer analysis on network gelation, we developed a similar analysis on reprocessable polymer networks to quantitatively predict the critical condition for reprocessability. Our theory indicates that it is unnecessary for all bonds to be dynamic to make the resulting network reprocessable. As long as there is no percolated permanent network in the system, the material can fully rearrange. To experimentally validate our theory, we used a thiol-epoxy network model system with various dynamic linkage compositions. The stress relaxation behavior of resulting materials supports our theoretical prediction: only 50 % of linkages between crosslinks need to be dynamic for a tri-arm network to be reprocessable. Therefore, this analysis provides the first fundamental theoretical platform for designing and evaluating reprocessable polymer networks. We thank McCormick Research Catalyst Award Fund and ISEN cluster fellowship (L. L.) for funding support.
Directory of Open Access Journals (Sweden)
Martha Fabiola Contreras Higuera
2013-06-01
transmission of information using the grid as a physical means of transmission. The analysis considers the influence of the size of the packages, number of stations, mechanisms of access to the medium, the window size of initial containment, among other important aspects; in order to analyze the behavior of the Throughput on LAN networks, making use of PLC technology for their implementation at the theoretical level.
Directory of Open Access Journals (Sweden)
Jonathan Laney
2015-01-01
Full Text Available The assessment of neuroplasticity after stroke through functional magnetic resonance imaging (fMRI analysis is a developing field where the objective is to better understand the neural process of recovery and to better target rehabilitation interventions. The challenge in this population stems from the large amount of individual spatial variability and the need to summarize entire brain maps by generating simple, yet discriminating features to highlight differences in functional connectivity. Independent vector analysis (IVA has been shown to provide superior performance in preserving subject variability when compared with widely used methods such as group independent component analysis. Hence, in this paper, graph-theoretical (GT analysis is applied to IVA-generated components to effectively exploit the individual subjects' connectivity to produce discriminative features. The analysis is performed on fMRI data collected from individuals with chronic stroke both before and after a 6-week arm and hand rehabilitation intervention. Resulting GT features are shown to capture connectivity changes that are not evident through direct comparison of the group t-maps. The GT features revealed increased small worldness across components and greater centrality in key motor networks as a result of the intervention, suggesting improved efficiency in neural communication. Clinically, these results bring forth new possibilities as a means to observe the neural processes underlying improvements in motor function.
Theoretical analysis of radiographic images by nonstationary Poisson processes
International Nuclear Information System (INIS)
Tanaka, Kazuo; Uchida, Suguru; Yamada, Isao.
1980-01-01
This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process. (author)
The Application of Social Network Analysis to Accounting and Auditing
DEFF Research Database (Denmark)
Kacanski, Slobodan; Lusher, Dean
2017-01-01
This article aims to extend methodological possibilities for conducting research in accounting and auditing by providing an overview of how current developments in social network analysis (SNA) could serve as a powerful set of theoretical and methodological tools for this purpose. SNA focuses...
A Theoretical Analysis of Why Hybrid Ensembles Work
Directory of Open Access Journals (Sweden)
Kuo-Wei Hsu
2017-01-01
Full Text Available Inspired by the group decision making process, ensembles or combinations of classifiers have been found favorable in a wide variety of application domains. Some researchers propose to use the mixture of two different types of classification algorithms to create a hybrid ensemble. Why does such an ensemble work? The question remains. Following the concept of diversity, which is one of the fundamental elements of the success of ensembles, we conduct a theoretical analysis of why hybrid ensembles work, connecting using different algorithms to accuracy gain. We also conduct experiments on classification performance of hybrid ensembles of classifiers created by decision tree and naïve Bayes classification algorithms, each of which is a top data mining algorithm and often used to create non-hybrid ensembles. Therefore, through this paper, we provide a complement to the theoretical foundation of creating and using hybrid ensembles.
Analysis of Semantic Networks using Complex Networks Concepts
DEFF Research Database (Denmark)
Ortiz-Arroyo, Daniel
2013-01-01
In this paper we perform a preliminary analysis of semantic networks to determine the most important terms that could be used to optimize a summarization task. In our experiments, we measure how the properties of a semantic network change, when the terms in the network are removed. Our preliminar...
Spectral Analysis of Rich Network Topology in Social Networks
Wu, Leting
2013-01-01
Social networks have received much attention these days. Researchers have developed different methods to study the structure and characteristics of the network topology. Our focus is on spectral analysis of the adjacency matrix of the underlying network. Recent work showed good properties in the adjacency spectral space but there are few…
Information theoretic analysis of canny edge detection in visual communication
Jiang, Bo; Rahman, Zia-ur
2011-06-01
In general edge detection evaluation, the edge detectors are examined, analyzed, and compared either visually or with a metric for specific an application. This analysis is usually independent of the characteristics of the image-gathering, transmission and display processes that do impact the quality of the acquired image and thus, the resulting edge image. We propose a new information theoretic analysis of edge detection that unites the different components of the visual communication channel and assesses edge detection algorithms in an integrated manner based on Shannon's information theory. The edge detection algorithm here is considered to achieve high performance only if the information rate from the scene to the edge approaches the maximum possible. Thus, by setting initial conditions of the visual communication system as constant, different edge detection algorithms could be evaluated. This analysis is normally limited to linear shift-invariant filters so in order to examine the Canny edge operator in our proposed system, we need to estimate its "power spectral density" (PSD). Since the Canny operator is non-linear and shift variant, we perform the estimation for a set of different system environment conditions using simulations. In our paper we will first introduce the PSD of the Canny operator for a range of system parameters. Then, using the estimated PSD, we will assess the Canny operator using information theoretic analysis. The information-theoretic metric is also used to compare the performance of the Canny operator with other edge-detection operators. This also provides a simple tool for selecting appropriate edgedetection algorithms based on system parameters, and for adjusting their parameters to maximize information throughput.
Complex Network Analysis of Guangzhou Metro
Yasir Tariq Mohmand; Fahad Mehmood; Fahd Amjad; Nedim Makarevic
2015-01-01
The structure and properties of public transportation networks can provide suggestions for urban planning and public policies. This study contributes a complex network analysis of the Guangzhou metro. The metro network has 236 kilometers of track and is the 6th busiest metro system of the world. In this paper topological properties of the network are explored. We observed that the network displays small world properties and is assortative in nature. The network possesses a high average degree...
Sie, Rory
2012-01-01
Sie, R. L. L. (2012). COalitions in COOperation Networks (COCOON): Social Network Analysis and Game Theory to Enhance Cooperation Networks (Unpublished doctoral dissertation). September, 28, 2012, Open Universiteit in the Netherlands (CELSTEC), Heerlen, The Netherlands.
Phenolic Analysis and Theoretic Design for Chinese Commercial Wines' Authentication.
Li, Si-Yu; Zhu, Bao-Qing; Reeves, Malcolm J; Duan, Chang-Qing
2018-01-01
To develop a robust tool for Chinese commercial wines' varietal, regional, and vintage authentication, phenolic compounds in 121 Chinese commercial dry red wines were detected and quantified by using high-performance liquid chromatography triple-quadrupole mass spectrometry (HPLC-QqQ-MS/MS), and differentiation abilities of principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were compared. Better than PCA and PLS-DA, OPLS-DA models used to differentiate wines according to their varieties (Cabernet Sauvignon or other varieties), regions (east or west Cabernet Sauvignon wines), and vintages (young or old Cabernet Sauvignon wines) were ideally established. The S-plot provided in OPLS-DA models showed the key phenolic compounds which were both statistically and biochemically significant in sample differentiation. Besides, the potential of the OPLS-DA models in deeper sample differentiating of more detailed regional and vintage information of wines was proved optimistic. On the basis of our results, a promising theoretic design for wine authentication was further proposed for the first time, which might be helpful in practical authentication of more commercial wines. The phenolic data of 121 Chinese commercial dry red wines was processed with different statistical tools for varietal, regional, and vintage differentiation. A promising theoretical design was summarized, which might be helpful for wine authentication in practical situation. © 2017 Institute of Food Technologists®.
Theoretical analysis of the graphitization of a nanodiamond
Energy Technology Data Exchange (ETDEWEB)
Kwon, S Joon; Park, Jae-Gwan [Nano Science and Technology Division, Korea Institute of Science and Technology (KIST), PO Box 131, Cheongryang, Seoul, 130-650 (Korea, Republic of)
2007-09-26
We report on a theoretical analysis of the graphitization of a nanosize diamond (nanodiamond) in the metastable state. A nanodiamond annealed at a relatively lower temperature suffers morphological transition into a nanodiamond-graphite core-shell structure. Thermodynamic stability analysis of the nanodiamond showed that the phase diagram (relationship between the annealing temperature and radius) of the nanodiamond-graphite has three regimes: smaller nanodiamond, nanodiamond-graphite, and larger nanodiamond. These regimes of nanodiamond-graphite are due to an additional phase boundary from finding the maximum size of the nanodiamond which can be graphitized. In the theoretical analysis, the most probable and the maximum volume fractions of graphite in the nanodiamond were 0.76 and 0.84 respectively, which were independent of the annealing temperature and the initial radius of the nanodiamond. Therefore, the nanodiamond is not completely transformed into graphite by simple annealing at relatively lower process temperature and pressure. The highest graphitization probability decreased with increasing annealing temperature. Raman spectra for the F{sub 2g} vibration mode of nanodiamond were also calculated, and we found that the variation in properties of the spectral line was strongly dependent on the graphitization temperature and the initial size of the nanodiamond.
Theoretical analysis of the graphitization of a nanodiamond
International Nuclear Information System (INIS)
Kwon, S Joon; Park, Jae-Gwan
2007-01-01
We report on a theoretical analysis of the graphitization of a nanosize diamond (nanodiamond) in the metastable state. A nanodiamond annealed at a relatively lower temperature suffers morphological transition into a nanodiamond-graphite core-shell structure. Thermodynamic stability analysis of the nanodiamond showed that the phase diagram (relationship between the annealing temperature and radius) of the nanodiamond-graphite has three regimes: smaller nanodiamond, nanodiamond-graphite, and larger nanodiamond. These regimes of nanodiamond-graphite are due to an additional phase boundary from finding the maximum size of the nanodiamond which can be graphitized. In the theoretical analysis, the most probable and the maximum volume fractions of graphite in the nanodiamond were 0.76 and 0.84 respectively, which were independent of the annealing temperature and the initial radius of the nanodiamond. Therefore, the nanodiamond is not completely transformed into graphite by simple annealing at relatively lower process temperature and pressure. The highest graphitization probability decreased with increasing annealing temperature. Raman spectra for the F 2g vibration mode of nanodiamond were also calculated, and we found that the variation in properties of the spectral line was strongly dependent on the graphitization temperature and the initial size of the nanodiamond
Fragkoulis, Alexandros; Kondi, Lisimachos P.; Parsopoulos, Konstantinos E.
2015-03-01
We propose a method for the fair and efficient allocation of wireless resources over a cognitive radio system network to transmit multiple scalable video streams to multiple users. The method exploits the dynamic architecture of the Scalable Video Coding extension of the H.264 standard, along with the diversity that OFDMA networks provide. We use a game-theoretic Nash Bargaining Solution (NBS) framework to ensure that each user receives the minimum video quality requirements, while maintaining fairness over the cognitive radio system. An optimization problem is formulated, where the objective is the maximization of the Nash product while minimizing the waste of resources. The problem is solved by using a Swarm Intelligence optimizer, namely Particle Swarm Optimization. Due to the high dimensionality of the problem, we also introduce a dimension-reduction technique. Our experimental results demonstrate the fairness imposed by the employed NBS framework.
Information theoretic analysis of edge detection in visual communication
Jiang, Bo; Rahman, Zia-ur
2010-08-01
Generally, the designs of digital image processing algorithms and image gathering devices remain separate. Consequently, the performance of digital image processing algorithms is evaluated without taking into account the artifacts introduced into the process by the image gathering process. However, experiments show that the image gathering process profoundly impacts the performance of digital image processing and the quality of the resulting images. Huck et al. proposed one definitive theoretic analysis of visual communication channels, where the different parts, such as image gathering, processing, and display, are assessed in an integrated manner using Shannon's information theory. In this paper, we perform an end-to-end information theory based system analysis to assess edge detection methods. We evaluate the performance of the different algorithms as a function of the characteristics of the scene, and the parameters, such as sampling, additive noise etc., that define the image gathering system. The edge detection algorithm is regarded to have high performance only if the information rate from the scene to the edge approaches the maximum possible. This goal can be achieved only by jointly optimizing all processes. People generally use subjective judgment to compare different edge detection methods. There is not a common tool that can be used to evaluate the performance of the different algorithms, and to give people a guide for selecting the best algorithm for a given system or scene. Our information-theoretic assessment becomes this new tool to which allows us to compare the different edge detection operators in a common environment.
THEORETICAL ANALYSIS STUDY OF FORMATION OF FUTURE LEGAL LAWYERS
Directory of Open Access Journals (Sweden)
Eugene Stepanovich Shevlakov
2015-09-01
Full Text Available The article deals with topical issues of formation of legal consciousness of future lawyers in high school. Obtained kinds of legal consciousness of future lawyers, determined its structure. Dedicated components of justice are mutually reinforcing, and provide an opportunity for further development of the personality of the future specialist, their personal growth.The purpose: to carry out theoretical analysis of the problem of formation of legal consciousness of future lawyers.The novelty is based. On the analysis of theoretical appro-aches of pedagogy, psychology, law, the notion of «lawfulness of the future of the law student», which is regarded as a form of social consciousness, which is a set of legal views and feelings, expressing the attitude to the law and legal phenomena that have regulatory in character and which includes know-ledge of legal phenomena and their evaluation from the point of view of fairness and justice, formed in the process of studying in the University.Results: this article analyzes different approaches to understanding the content and essence of the concept of legal consciousness of the legal profession. Define the types and structure of legal consciousness of future lawyers.
A Game-theoretic Framework for Network Coding Based Device-to-Device Communications
Douik, Ahmed S.; Sorour, Sameh; Tembine, Hamidou; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2016-01-01
This paper investigates the delay minimization problem for instantly decodable network coding (IDNC) based deviceto- device (D2D) communications. In D2D enabled systems, users cooperate to recover all their missing packets. The paper proposes a game theoretic framework as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. The session is modeled by self-interested players in a non-cooperative potential game. The utility functions are designed so as increasing individual payoff results in a collective behavior achieving both a desirable system performance in a shared network environment and the Nash equilibrium. Three games are developed whose first reduces the completion time, the second the maximum decoding delay and the third the sum decoding delay. The paper, further, improves the formulations by including a punishment policy upon collision occurrence so as to achieve the Nash bargaining solution. Learning algorithms are proposed for systems with complete and incomplete information, and for the imperfect feedback scenario. Numerical results suggest that the proposed game-theoretical formulation provides appreciable performance gain against the conventional point-to-multipoint (PMP), especially for reliable user-to-user channels.
A Game-theoretic Framework for Network Coding Based Device-to-Device Communications
Douik, Ahmed
2016-06-29
This paper investigates the delay minimization problem for instantly decodable network coding (IDNC) based deviceto- device (D2D) communications. In D2D enabled systems, users cooperate to recover all their missing packets. The paper proposes a game theoretic framework as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. The session is modeled by self-interested players in a non-cooperative potential game. The utility functions are designed so as increasing individual payoff results in a collective behavior achieving both a desirable system performance in a shared network environment and the Nash equilibrium. Three games are developed whose first reduces the completion time, the second the maximum decoding delay and the third the sum decoding delay. The paper, further, improves the formulations by including a punishment policy upon collision occurrence so as to achieve the Nash bargaining solution. Learning algorithms are proposed for systems with complete and incomplete information, and for the imperfect feedback scenario. Numerical results suggest that the proposed game-theoretical formulation provides appreciable performance gain against the conventional point-to-multipoint (PMP), especially for reliable user-to-user channels.
Social Network Analysis and informal trade
DEFF Research Database (Denmark)
Walther, Olivier
networks can be applied to better understand informal trade in developing countries, with a particular focus on Africa. The paper starts by discussing some of the fundamental concepts developed by social network analysis. Through a number of case studies, we show how social network analysis can...... illuminate the relevant causes of social patterns, the impact of social ties on economic performance, the diffusion of resources and information, and the exercise of power. The paper then examines some of the methodological challenges of social network analysis and how it can be combined with other...... approaches. The paper finally highlights some of the applications of social network analysis and their implications for trade policies....
Analysis of the theoretical bias in dark matter direct detection
International Nuclear Information System (INIS)
Catena, Riccardo
2014-01-01
Fitting the model ''A'' to dark matter direct detection data, when the model that underlies the data is ''B'', introduces a theoretical bias in the fit. We perform a quantitative study of the theoretical bias in dark matter direct detection, with a focus on assumptions regarding the dark matter interactions, and velocity distribution. We address this problem within the effective theory of isoscalar dark matter-nucleon interactions mediated by a heavy spin-1 or spin-0 particle. We analyze 24 benchmark points in the parameter space of the theory, using frequentist and Bayesian statistical methods. First, we simulate the data of future direct detection experiments assuming a momentum/velocity dependent dark matter-nucleon interaction, and an anisotropic dark matter velocity distribution. Then, we fit a constant scattering cross section, and an isotropic Maxwell-Boltzmann velocity distribution to the simulated data, thereby introducing a bias in the analysis. The best fit values of the dark matter particle mass differ from their benchmark values up to 2 standard deviations. The best fit values of the dark matter-nucleon coupling constant differ from their benchmark values up to several standard deviations. We conclude that common assumptions in dark matter direct detection are a source of potentially significant bias
Analysis of Network Parameters Influencing Performance of Hybrid Multimedia Networks
Directory of Open Access Journals (Sweden)
Dominik Kovac
2013-10-01
Full Text Available Multimedia networks is an emerging subject that currently attracts the attention of research and industrial communities. This environment provides new entertainment services and business opportunities merged with all well-known network services like VoIP calls or file transfers. Such a heterogeneous system has to be able satisfy all network and end-user requirements which are increasing constantly. Therefore the simulation tools enabling deep analysis in order to find the key performance indicators and factors which influence the overall quality for specific network service the most are highly needed. This paper provides a study on the network parameters like communication technology, routing protocol, QoS mechanism, etc. and their effect on the performance of hybrid multimedia network. The analysis was performed in OPNET Modeler environment and the most interesting results are discussed at the end of this paper
Growth of cortical neuronal network in vitro: Modeling and analysis
International Nuclear Information System (INIS)
Lai, P.-Y.; Jia, L. C.; Chan, C. K.
2006-01-01
We present a detailed analysis and theoretical growth models to account for recent experimental data on the growth of cortical neuronal networks in vitro [Phys. Rev. Lett. 93, 088101 (2004)]. The experimentally observed synchronized firing frequency of a well-connected neuronal network is shown to be proportional to the mean network connectivity. The growth of the network is consistent with the model of an early enhanced growth of connection, but followed by a retarded growth once the synchronized cluster is formed. Microscopic models with dominant excluded volume interactions are consistent with the observed exponential decay of the mean connection probability as a function of the mean network connectivity. The biological implications of the growth model are also discussed
Network clustering coefficient approach to DNA sequence analysis
Energy Technology Data Exchange (ETDEWEB)
Gerhardt, Guenther J.L. [Universidade Federal do Rio Grande do Sul-Hospital de Clinicas de Porto Alegre, Rua Ramiro Barcelos 2350/sala 2040/90035-003 Porto Alegre (Brazil); Departamento de Fisica e Quimica da Universidade de Caxias do Sul, Rua Francisco Getulio Vargas 1130, 95001-970 Caxias do Sul (Brazil); Lemke, Ney [Programa Interdisciplinar em Computacao Aplicada, Unisinos, Av. Unisinos, 950, 93022-000 Sao Leopoldo, RS (Brazil); Corso, Gilberto [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, Campus Universitario, 59072 970 Natal, RN (Brazil)]. E-mail: corso@dfte.ufrn.br
2006-05-15
In this work we propose an alternative DNA sequence analysis tool based on graph theoretical concepts. The methodology investigates the path topology of an organism genome through a triplet network. In this network, triplets in DNA sequence are vertices and two vertices are connected if they occur juxtaposed on the genome. We characterize this network topology by measuring the clustering coefficient. We test our methodology against two main bias: the guanine-cytosine (GC) content and 3-bp (base pairs) periodicity of DNA sequence. We perform the test constructing random networks with variable GC content and imposed 3-bp periodicity. A test group of some organisms is constructed and we investigate the methodology in the light of the constructed random networks. We conclude that the clustering coefficient is a valuable tool since it gives information that is not trivially contained in 3-bp periodicity neither in the variable GC content.
A Game Theoretic Approach to Minimize the Completion Time of Network Coded Cooperative Data Exchange
Douik, Ahmed S.
2014-05-11
In this paper, we introduce a game theoretic framework for studying the problem of minimizing the completion time of instantly decodable network coding (IDNC) for cooperative data exchange (CDE) in decentralized wireless network. In this configuration, clients cooperate with each other to recover the erased packets without a central controller. Game theory is employed herein as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. We model the session by self-interested players in a non-cooperative potential game. The utility function is designed such that increasing individual payoff results in a collective behavior achieving both a desirable system performance in a shared network environment and the Pareto optimal solution. Through extensive simulations, our approach is compared to the best performance that could be found in the conventional point-to-multipoint (PMP) recovery process. Numerical results show that our formulation largely outperforms the conventional PMP scheme in most practical situations and achieves a lower delay.
A Game Theoretic Approach to Minimize the Completion Time of Network Coded Cooperative Data Exchange
Douik, Ahmed S.; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim; Sorour, Sameh; Tembine, Hamidou
2014-01-01
In this paper, we introduce a game theoretic framework for studying the problem of minimizing the completion time of instantly decodable network coding (IDNC) for cooperative data exchange (CDE) in decentralized wireless network. In this configuration, clients cooperate with each other to recover the erased packets without a central controller. Game theory is employed herein as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. We model the session by self-interested players in a non-cooperative potential game. The utility function is designed such that increasing individual payoff results in a collective behavior achieving both a desirable system performance in a shared network environment and the Pareto optimal solution. Through extensive simulations, our approach is compared to the best performance that could be found in the conventional point-to-multipoint (PMP) recovery process. Numerical results show that our formulation largely outperforms the conventional PMP scheme in most practical situations and achieves a lower delay.
Theoretical analysis of sound transmission loss through graphene sheets
International Nuclear Information System (INIS)
Natsuki, Toshiaki; Ni, Qing-Qing
2014-01-01
We examine the potential of using graphene sheets (GSs) as sound insulating materials that can be used for nano-devices because of their small size, super electronic, and mechanical properties. In this study, a theoretical analysis is proposed to predict the sound transmission loss through multi-layered GSs, which are formed by stacks of GS and bound together by van der Waals (vdW) forces between individual layers. The result shows that the resonant frequencies of the sound transmission loss occur in the multi-layered GSs and the values are very high. Based on the present analytical solution, we predict the acoustic insulation property for various layers of sheets under both normal incident wave and acoustic field of random incidence source. The scheme could be useful in vibration absorption application of nano devices and materials
Theoretical analysis of sound transmission loss through graphene sheets
Energy Technology Data Exchange (ETDEWEB)
Natsuki, Toshiaki, E-mail: natsuki@shinshu-u.ac.jp [Faculty of Textile Science and Technology, Shinshu University, 3-15-1 Tokida, Ueda 386-8567 (Japan); Institute of Carbon Science and Technology, Shinshu University, 4-17-1 Wakasato, Nagano 380-8553 (Japan); Ni, Qing-Qing [Faculty of Textile Science and Technology, Shinshu University, 3-15-1 Tokida, Ueda 386-8567 (Japan)
2014-11-17
We examine the potential of using graphene sheets (GSs) as sound insulating materials that can be used for nano-devices because of their small size, super electronic, and mechanical properties. In this study, a theoretical analysis is proposed to predict the sound transmission loss through multi-layered GSs, which are formed by stacks of GS and bound together by van der Waals (vdW) forces between individual layers. The result shows that the resonant frequencies of the sound transmission loss occur in the multi-layered GSs and the values are very high. Based on the present analytical solution, we predict the acoustic insulation property for various layers of sheets under both normal incident wave and acoustic field of random incidence source. The scheme could be useful in vibration absorption application of nano devices and materials.
A theoretical analysis on vibrational-energy transfers in gases
International Nuclear Information System (INIS)
Mastrocinque, G.
1981-01-01
In order to investigate the relationships between three-dimensional and colinear molecular-collision models with particular emphasis on the role of repulsive and attractive forces in vibrational-energy transfers in gases, a theoretical analysis is developed in this paper. A few known results - mainly the Cottrell and Ream equation, the Takayanagi and the Shin expressions of the transfer probability - relevant to repulsive-force-dominated processes are obtained and/or discussed in the proposed frame. Light is also given on long-range, attractive-forces-dominated processes. The main result of this investigation is that, when a suitable hypothesis is done on the transfer probability, centrifugal effects on the intermolecular trajectories due to standard potentials are negligible in the low-temperature range. A quasi-colinear collision model, which is found to be correlated to the Cottrell and Ream expression for the transfer probability, is regained from a three-dimensional geometry in these conditions. (author)
American and Canadian environmental federalism: A game-theoretic analysis
Energy Technology Data Exchange (ETDEWEB)
Gillroy, J.M.
1999-07-01
To understand why environmental federalism is different in Canada and the United States, one might begin with the initial strategic realities that faced the Fathers of Canadian Confederation and the Framers of the Constitution of the US. This essay examined federalism from a game theoretic point of view, to integrate and expose the rational properties of the decision to federate and the logical entailments of that choice for environmental policy within two specific strategic contexts. Specifically, the author suggests that American environmental federalism has arisen in response to the strategic reality of a prisoner's dilemma, while Canadian environmental federalism can be analyzed as an effort to regulate confrontations within a game of chicken. In addition to the analysis of each federated structure, evidence from five case studies demonstrates the usefulness of games to the study of comparative federalism.
Game-theoretic equilibrium analysis applications to deregulated electricity markets
Joung, Manho
This dissertation examines game-theoretic equilibrium analysis applications to deregulated electricity markets. In particular, three specific applications are discussed: analyzing the competitive effects of ownership of financial transmission rights, developing a dynamic game model considering the ramp rate constraints of generators, and analyzing strategic behavior in electricity capacity markets. In the financial transmission right application, an investigation is made of how generators' ownership of financial transmission rights may influence the effects of the transmission lines on competition. In the second application, the ramp rate constraints of generators are explicitly modeled using a dynamic game framework, and the equilibrium is characterized as the Markov perfect equilibrium. Finally, the strategic behavior of market participants in electricity capacity markets is analyzed and it is shown that the market participants may exaggerate their available capacity in a Nash equilibrium. It is also shown that the more conservative the independent system operator's capacity procurement, the higher the risk of exaggerated capacity offers.
Geometrical methods for power network analysis
Energy Technology Data Exchange (ETDEWEB)
Bellucci, Stefano; Tiwari, Bhupendra Nath [Istituto Nazioneale di Fisica Nucleare, Frascati, Rome (Italy). Lab. Nazionali di Frascati; Gupta, Neeraj [Indian Institute of Technology, Kanpur (India). Dept. of Electrical Engineering
2013-02-01
Uses advanced geometrical methods to analyse power networks. Provides a self-contained and tutorial introduction. Includes a fully worked-out example for the IEEE 5 bus system. This book is a short introduction to power system planning and operation using advanced geometrical methods. The approach is based on well-known insights and techniques developed in theoretical physics in the context of Riemannian manifolds. The proof of principle and robustness of this approach is examined in the context of the IEEE 5 bus system. This work addresses applied mathematicians, theoretical physicists and power engineers interested in novel mathematical approaches to power network theory.
A Network Approach to Environmental Impact in Psychotic Disorder : Brief Theoretical Framework
Isvoranu, A.M.; Borsboom, D.; van Os, J.; Guloksuz, S.
2016-01-01
The spectrum of psychotic disorder represents a multifactorial and heterogeneous condition and is thought to result from a complex interplay between genetic and environmental factors. In the current paper, we analyze this interplay using network analysis, which has been recently proposed as a novel
Wang, Chao; Xu, Jin; Zhao, Songzhen; Lou, Wutao
2016-01-01
The study was dedicated to investigating the change in information processing in brain networks of vascular dementia (VaD) patients during the process of decision making. EEG was recorded from 18 VaD patients and 19 healthy controls when subjects were performing a visual oddball task. The whole task was divided into several stages by using global field power analysis. In the stage related to the decision-making process, graph theoretical analysis was applied to the binary directed network derived from EEG signals at nine electrodes in the frontal, central, and parietal regions in δ (0.5-3.5Hz), θ (4-7Hz), α1 (8-10Hz), α2 (11-13Hz), and β (14-30Hz) frequency bands based on directed transfer function. A weakened outgoing information flow, a decrease in out-degree, and an increase in in-degree were found in the parietal region in VaD patients, compared to healthy controls. In VaD patients, the parietal region may also lose its hub status in brain networks. In addition, the clustering coefficient was significantly lower in VaD patients. Impairment might be present in the parietal region or its connections with other regions, and it may serve as one of the causes for cognitive decline in VaD patients. The brain networks of VaD patients were significantly altered toward random networks. The present study extended our understanding of VaD from the perspective of brain functional networks, and it provided possible interpretations for cognitive deficits in VaD patients. Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Game-theoretic modeling of curtailment rules and network investments with distributed generation
International Nuclear Information System (INIS)
Andoni, Merlinda; Robu, Valentin; Früh, Wolf-Gerrit; Flynn, David
2017-01-01
to validate our model. We show that charging a transmission fee as a proportion of the feed-in tariff price between 15% and 75% would allow both investors to implement their projects and achieve desirable distribution of the profit. Overall, our results show how using game-theoretic tools can help network operators to bridge the knowledge gap about setting the optimal curtailment rule and determining transmission charges for private network infrastructure.
Google matrix analysis of directed networks
Ermann, Leonardo; Frahm, Klaus M.; Shepelyansky, Dima L.
2015-10-01
In the past decade modern societies have developed enormous communication and social networks. Their classification and information retrieval processing has become a formidable task for the society. Because of the rapid growth of the World Wide Web, and social and communication networks, new mathematical methods have been invented to characterize the properties of these networks in a more detailed and precise way. Various search engines extensively use such methods. It is highly important to develop new tools to classify and rank a massive amount of network information in a way that is adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency using various examples including the World Wide Web, Wikipedia, software architectures, world trade, social and citation networks, brain neural networks, DNA sequences, and Ulam networks. The analytical and numerical matrix methods used in this analysis originate from the fields of Markov chains, quantum chaos, and random matrix theory.
Capacity Analysis of Wireless Mesh Networks
Directory of Open Access Journals (Sweden)
M. I. Gumel
2012-06-01
Full Text Available The next generation wireless networks experienced a great development with emergence of wireless mesh networks (WMNs, which can be regarded as a realistic solution that provides wireless broadband access. The limited available bandwidth makes capacity analysis of the network very essential. While the network offers broadband wireless access to community and enterprise users, the problems that limit the network capacity must be addressed to exploit the optimum network performance. The wireless mesh network capacity analysis shows that the throughput of each mesh node degrades in order of l/n with increasing number of nodes (n in a linear topology. The degradation is found to be higher in a fully mesh network as a result of increase in interference and MAC layer contention in the network.
Social network analysis community detection and evolution
Missaoui, Rokia
2015-01-01
This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edit
Analysis and Design of Complex Network Environments
2012-03-01
and J. Lowe, “The myths and facts behind cyber security risks for industrial control systems ,” in the Proceedings of the VDE Kongress, VDE Congress...questions about 1) how to model them, 2) the design of experiments necessary to discover their structure (and thus adapt system inputs to optimize the...theoretical work that clarifies fundamental limitations of complex networks with network engineering and systems biology to implement specific designs and
Network analysis literacy a practical approach to the analysis of networks
Zweig, Katharina A
2014-01-01
Network Analysis Literacy focuses on design principles for network analytics projects. The text enables readers to: pose a defined network analytic question; build a network to answer the question; choose or design the right network analytic methods for a particular purpose, and more.
Energy Technology Data Exchange (ETDEWEB)
Abercrombie, Robert K [ORNL; Sheldon, Frederick T. [University of Idaho
2015-01-01
Cyber physical computing infrastructures typically consist of a number of sites are interconnected. Its operation critically depends both on cyber components and physical components. Both types of components are subject to attacks of different kinds and frequencies, which must be accounted for the initial provisioning and subsequent operation of the infrastructure via information security analysis. Information security analysis can be performed using game theory implemented in dynamic Agent Based Game Theoretic (ABGT) simulations. Such simulations can be verified with the results from game theory analysis and further used to explore larger scale, real world scenarios involving multiple attackers, defenders, and information assets. We concentrated our analysis on the electric sector failure scenarios and impact analyses by the NESCOR Working Group Study, From the Section 5 electric sector representative failure scenarios; we extracted the four generic failure scenarios and grouped them into three specific threat categories (confidentiality, integrity, and availability) to the system. These specific failure scenarios serve as a demonstration of our simulation. The analysis using our ABGT simulation demonstrates how to model the electric sector functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the cyber physical infrastructure network with respect to CIA.
Theoretical analysis of ejector refrigeration system performance under overall modes
International Nuclear Information System (INIS)
Chen, Weixiong; Shi, Chaoyin; Zhang, Shuangping; Chen, Huiqiang; Chong, Daotong; Yan, Junjie
2017-01-01
Highlights: • Real gas theoretical model is used to get ejector performance at critical/sub-critical modes. • The model has a better accuracy against the experiment results compared to ideal gas model. • The overall performances of two refrigerants are analyzed based on the parameter analysis. - Abstract: The ejector refrigeration integrated in the air-conditioning system is a promising technology, because it could be driven by the low grade energy. In the present study, a theoretical calculation based on the real gas property is put forward to estimate the ejector refrigeration system performance under overall modes (critical/sub-critical modes). The experimental data from literature are applied to validate the proposed model. The findings show that the proposed model has higher accuracy compared to the model using the ideal gas law, especially when the ejector operates at sub-critical mode. Then, the performances of the ejector refrigeration circle using different refrigerants are analyzed. R290 and R134a are selected as typical refrigerants by considering the aspects of COP, environmental impact, safety and economy. Finally, the ejector refrigeration performance is investigated under variable operation conditions with R290 and R134a as refrigerants. The results show that the R290 ejector circle has higher COP under critical mode and could operate at low evaporator temperature. However, the performance would decrease rapidly at high condenser temperature. The performance of R134a ejector circle is the opposite, with relatively lower COP, and higher COP at high condenser temperature compared to R290.
Ponten, S.C.; Daffertshofer, A.; Hillebrand, A.; Stam, C.J.
2010-01-01
We investigated the relationship between structural network properties and both synchronization strength and functional characteristics in a combined neural mass and graph theoretical model of the electroencephalogram (EEG). Thirty-two neural mass models (NMMs), each representing the lump activity
A game theoretical approach for QoS provisioning in heterogeneous networks
Directory of Open Access Journals (Sweden)
A.S.M. Zadid Shifat
2015-09-01
Full Text Available With the proliferation of mobile phone users, interference management is a big concern in this neoteric years. To cope with this problem along with ensuring better Quality of Service (QoS, femtocell plays an imperious preamble in heterogeneous networks (HetNets for some of its noteworthy characteristics. In this paper, we propose a game theoretic algorithm along with dynamic channel allocation and hybrid access mechanism with self-organizing power control scheme. With a view to resolving prioritized access issue, the concept of primary and secondary users is applied. Existence of pure strategy Nash equilibrium (NE has been investigated and comes to a perfection that our proposed scheme can be adopted both increasing capacity and increasing revenue of operators considering optimal price for consumers.
Networks and Bargaining in Policy Analysis
DEFF Research Database (Denmark)
Bogason, Peter
2006-01-01
A duscussion of the fight between proponents of rationalistic policy analysis and more political interaction models for policy analysis. The latter group is the foundation for the many network models of policy analysis of today.......A duscussion of the fight between proponents of rationalistic policy analysis and more political interaction models for policy analysis. The latter group is the foundation for the many network models of policy analysis of today....
Analysis and logical modeling of biological signaling transduction networks
Sun, Zhongyao
The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.
Energy Technology Data Exchange (ETDEWEB)
Carriger, John F. [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States); Martin, Todd M. [U.S. Environmental Protection Agency, Office of Research and Development, Sustainable Technology Division, Cincinnati, OH, 45220 (United States); Barron, Mace G., E-mail: barron.mace@epa.gov [U.S. Environmental Protection Agency, Office of Research and Development, Gulf Ecology Division, Gulf Breeze, FL, 32561 (United States)
2016-11-15
Highlights: • A Bayesian network was developed to classify chemical mode of action (MoA). • The network was based on the aquatic toxicity MoA for over 1000 chemicals. • A Markov blanket algorithm selected a subset of theoretical molecular descriptors. • Sensitivity analyses found influential descriptors for classifying the MoAs. • Overall precision of the Bayesian MoA classification model was 80%. - Abstract: The mode of toxic action (MoA) has been recognized as a key determinant of chemical toxicity, but development of predictive MoA classification models in aquatic toxicology has been limited. We developed a Bayesian network model to classify aquatic toxicity MoA using a recently published dataset containing over one thousand chemicals with MoA assignments for aquatic animal toxicity. Two dimensional theoretical chemical descriptors were generated for each chemical using the Toxicity Estimation Software Tool. The model was developed through augmented Markov blanket discovery from the dataset of 1098 chemicals with the MoA broad classifications as a target node. From cross validation, the overall precision for the model was 80.2%. The best precision was for the AChEI MoA (93.5%) where 257 chemicals out of 275 were correctly classified. Model precision was poorest for the reactivity MoA (48.5%) where 48 out of 99 reactive chemicals were correctly classified. Narcosis represented the largest class within the MoA dataset and had a precision and reliability of 80.0%, reflecting the global precision across all of the MoAs. False negatives for narcosis most often fell into electron transport inhibition, neurotoxicity or reactivity MoAs. False negatives for all other MoAs were most often narcosis. A probabilistic sensitivity analysis was undertaken for each MoA to examine the sensitivity to individual and multiple descriptor findings. The results show that the Markov blanket of a structurally complex dataset can simplify analysis and interpretation by
Analysis of Recurrent Analog Neural Networks
Directory of Open Access Journals (Sweden)
Z. Raida
1998-06-01
Full Text Available In this paper, an original rigorous analysis of recurrent analog neural networks, which are built from opamp neurons, is presented. The analysis, which comes from the approximate model of the operational amplifier, reveals causes of possible non-stable states and enables to determine convergence properties of the network. Results of the analysis are discussed in order to enable development of original robust and fast analog networks. In the analysis, the special attention is turned to the examination of the influence of real circuit elements and of the statistical parameters of processed signals to the parameters of the network.
Directory of Open Access Journals (Sweden)
Jun Huang
2015-08-01
Full Text Available Device-to-Device (D2D communication has recently emerged as a promising technology to improve the capacity and coverage of cellular systems. To successfully implement D2D communications underlaying a cellular network, resource allocation for D2D links plays a critical role. While most of prior resource allocation mechanisms for D2D communications have focused on interference within a single-cell system, this paper investigates the resource allocation problem for a multicell cellular network in which a D2D link reuses available spectrum resources of multiple cells. A repeated game theoretic approach is proposed to address the problem. In this game, the base stations (BSs act as players that compete for resource supply of D2D, and the utility of each player is formulated as revenue collected from both cellular and D2D users using resources. Extensive simulations are conducted to verify the proposed approach and the results show that it can considerably enhance the system performance in terms of sum rate and sum rate gain.
Egocentric Social Network Analysis of Pathological Gambling
Meisel, Matthew K.; Clifton, Allan D.; MacKillop, James; Miller, Joshua D.; Campbell, W. Keith; Goodie, Adam S.
2012-01-01
Aims To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family, and co-workers. is an innovative way to look at relationships among individuals; the current study was the first to our knowledge to apply SNA to gambling behaviors. Design Egocentric social network analysis was used to formally characterize the relationships between social network characteristics and gambling pathology. Setting Laboratory-based questionnaire and interview administration. Participants Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. Findings The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers, and drinkers in their social networks than did nonpathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked, and drank with than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked, and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Conclusions Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers, and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. PMID:23072641
Egocentric social network analysis of pathological gambling.
Meisel, Matthew K; Clifton, Allan D; Mackillop, James; Miller, Joshua D; Campbell, W Keith; Goodie, Adam S
2013-03-01
To apply social network analysis (SNA) to investigate whether frequency and severity of gambling problems were associated with different network characteristics among friends, family and co-workers is an innovative way to look at relationships among individuals; the current study was the first, to our knowledge, to apply SNA to gambling behaviors. Egocentric social network analysis was used to characterize formally the relationships between social network characteristics and gambling pathology. Laboratory-based questionnaire and interview administration. Forty frequent gamblers (22 non-pathological gamblers, 18 pathological gamblers) were recruited from the community. The SNA revealed significant social network compositional differences between the two groups: pathological gamblers (PGs) had more gamblers, smokers and drinkers in their social networks than did non-pathological gamblers (NPGs). PGs had more individuals in their network with whom they personally gambled, smoked and drank than those with who were NPG. Network ties were closer to individuals in their networks who gambled, smoked and drank more frequently. Associations between gambling severity and structural network characteristics were not significant. Pathological gambling is associated with compositional but not structural differences in social networks. Pathological gamblers differ from non-pathological gamblers in the number of gamblers, smokers and drinkers in their social networks. Homophily within the networks also indicates that gamblers tend to be closer with other gamblers. This homophily may serve to reinforce addictive behaviors, and may suggest avenues for future study or intervention. © 2012 The Authors, Addiction © 2012 Society for the Study of Addiction.
Stochastic sensitivity analysis and Langevin simulation for neural network learning
International Nuclear Information System (INIS)
Koda, Masato
1997-01-01
A comprehensive theoretical framework is proposed for the learning of a class of gradient-type neural networks with an additive Gaussian white noise process. The study is based on stochastic sensitivity analysis techniques, and formal expressions are obtained for stochastic learning laws in terms of functional derivative sensitivity coefficients. The present method, based on Langevin simulation techniques, uses only the internal states of the network and ubiquitous noise to compute the learning information inherent in the stochastic correlation between noise signals and the performance functional. In particular, the method does not require the solution of adjoint equations of the back-propagation type. Thus, the present algorithm has the potential for efficiently learning network weights with significantly fewer computations. Application to an unfolded multi-layered network is described, and the results are compared with those obtained by using a back-propagation method
Dispersion-theoretical analysis of the nucleon electromagnetic form factors
Energy Technology Data Exchange (ETDEWEB)
Belushkin, M.
2007-09-29
The structure of the proton and the neutron is of fundamental importance for the study of the strong interaction dynamics over a wide range of momentum transfers. The nucleon form factors encode information on the internal structure of the nucleon as probed by the electromagnetic interaction, and, to a certain extent, reflect the charge and magnetisation distributions within the proton and the neutron. In this thesis we report on our investigation of the electromagnetic form factors of the proton and the neutron with dispersion relation techniques, including known experimental input on the {pi}{pi}, K anti K and the {rho}{pi} continua and perturbative QCD constraints. We include new experimental data on the pion form factor and the nucleon form factors in our simultaneous analysis of all four form factors in both the space- and the timelike regions for all momentum transfers, and perform Monte- Carlo sampling in order to obtain theoretical uncertainty bands. Finally, we discuss the implications of our results on the pion cloud of the nucleon, the nucleon radii and the Okubo-Zweig-Iizuka rule, and present our results of a model-independent approach to estimating two-photon effects in elastic electron-proton scattering. (orig.)
Thermoelectric Generation Of Current - Theoretical And Experimental Analysis
Ruciński, Adam; Rusowicz, Artur
2017-12-01
This paper provides some information about thermoelectric technology. Some new materials with improved figures of merit are presented. These materials in Peltier modules make it possible to generate electric current thanks to a temperature difference. The paper indicates possible applications of thermoelectric modules as interesting tools for using various waste heat sources. Some zero-dimensional equations describing the conditions of electric power generation are given. Also, operating parameters of Peltier modules, such as voltage and electric current, are analyzed. The paper shows chosen characteristics of power generation parameters. Then, an experimental stand for ongoing research and experimental measurements are described. The authors consider the resistance of a receiver placed in the electric circuit with thermoelectric elements. Finally, both the analysis of experimental results and conclusions drawn from theoretical findings are presented. Voltage generation of about 1.5 to 2.5 V for the temperature difference from 65 to 85 K was observed when a bismuth telluride thermoelectric couple (traditionally used in cooling technology) was used.
Thermoelectric Generation Of Current – Theoretical And Experimental Analysis
Directory of Open Access Journals (Sweden)
Ruciński Adam
2017-12-01
Full Text Available This paper provides some information about thermoelectric technology. Some new materials with improved figures of merit are presented. These materials in Peltier modules make it possible to generate electric current thanks to a temperature difference. The paper indicates possible applications of thermoelectric modules as interesting tools for using various waste heat sources. Some zero-dimensional equations describing the conditions of electric power generation are given. Also, operating parameters of Peltier modules, such as voltage and electric current, are analyzed. The paper shows chosen characteristics of power generation parameters. Then, an experimental stand for ongoing research and experimental measurements are described. The authors consider the resistance of a receiver placed in the electric circuit with thermoelectric elements. Finally, both the analysis of experimental results and conclusions drawn from theoretical findings are presented. Voltage generation of about 1.5 to 2.5 V for the temperature difference from 65 to 85 K was observed when a bismuth telluride thermoelectric couple (traditionally used in cooling technology was used.
Dispersion-theoretical analysis of the nucleon electromagnetic form factors
International Nuclear Information System (INIS)
Belushkin, M.
2007-01-01
The structure of the proton and the neutron is of fundamental importance for the study of the strong interaction dynamics over a wide range of momentum transfers. The nucleon form factors encode information on the internal structure of the nucleon as probed by the electromagnetic interaction, and, to a certain extent, reflect the charge and magnetisation distributions within the proton and the neutron. In this thesis we report on our investigation of the electromagnetic form factors of the proton and the neutron with dispersion relation techniques, including known experimental input on the ππ, K anti K and the ρπ continua and perturbative QCD constraints. We include new experimental data on the pion form factor and the nucleon form factors in our simultaneous analysis of all four form factors in both the space- and the timelike regions for all momentum transfers, and perform Monte- Carlo sampling in order to obtain theoretical uncertainty bands. Finally, we discuss the implications of our results on the pion cloud of the nucleon, the nucleon radii and the Okubo-Zweig-Iizuka rule, and present our results of a model-independent approach to estimating two-photon effects in elastic electron-proton scattering. (orig.)
Optimal design of an activated sludge plant: theoretical analysis
Islam, M. A.; Amin, M. S. A.; Hoinkis, J.
2013-06-01
The design procedure of an activated sludge plant consisting of an activated sludge reactor and settling tank has been theoretically analyzed assuming that (1) the Monod equation completely describes the growth kinetics of microorganisms causing the degradation of biodegradable pollutants and (2) the settling characteristics are fully described by a power law. For a given reactor height, the design parameter of the reactor (reactor volume) is reduced to the reactor area. Then the sum total area of the reactor and the settling tank is expressed as a function of activated sludge concentration X and the recycled ratio α. A procedure has been developed to calculate X opt, for which the total required area of the plant is minimum for given microbiological system and recycled ratio. Mathematical relations have been derived to calculate the α-range in which X opt meets the requirements of F/ M ratio. Results of the analysis have been illustrated for varying X and α. Mathematical formulae have been proposed to recalculate the recycled ratio in the events, when the influent parameters differ from those assumed in the design.
Notes on economic time series analysis system theoretic perspectives
Aoki, Masanao
1983-01-01
In seminars and graduate level courses I have had several opportunities to discuss modeling and analysis of time series with economists and economic graduate students during the past several years. These experiences made me aware of a gap between what economic graduate students are taught about vector-valued time series and what is available in recent system literature. Wishing to fill or narrow the gap that I suspect is more widely spread than my personal experiences indicate, I have written these notes to augment and reor ganize materials I have given in these courses and seminars. I have endeavored to present, in as much a self-contained way as practicable, a body of results and techniques in system theory that I judge to be relevant and useful to economists interested in using time series in their research. I have essentially acted as an intermediary and interpreter of system theoretic results and perspectives in time series by filtering out non-essential details, and presenting coherent accounts of wha...
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.
Theoretical Models of Deliberative Democracy: A Critical Analysis
Directory of Open Access Journals (Sweden)
Tutui Viorel
2015-07-01
Full Text Available Abstract: My paper focuses on presenting and analyzing some of the most important theoretical models of deliberative democracy and to emphasize their limits. Firstly, I will mention James Fishkin‟s account of deliberative democracy and its relations with other democratic models. He differentiates between four democratic theories: competitive democracy, elite deliberation, participatory democracy and deliberative democracy. Each of these theories makes an explicit commitment to two of the following four “principles”: political equality, participation, deliberation, nontyranny. Deliberative democracy is committed to political equality and deliberation. Secondly, I will present Philip Pettit‟s view concerning the main constraints of deliberative democracy: the inclusion constraint, the judgmental constraint and the dialogical constraint. Thirdly, I will refer to Amy Gutmann and Dennis Thompson‟s conception regarding the “requirements” or characteristics of deliberative democracy: the reason-giving requirement, the accessibility of reasons, the binding character of the decisions and the dynamic nature of the deliberative process. Finally, I will discuss Joshua Cohen‟s “ideal deliberative procedure” which has the following features: it is free, reasoned, the parties are substantively equal and the procedure aims to arrive at rationally motivated consensus. After presenting these models I will provide a critical analysis of each one of them with the purpose of revealing their virtues and limits. I will make some suggestions in order to combine the virtues of these models, to transcend their limitations and to offer a more systematical account of deliberative democracy. In the next four sections I will take into consideration four main strategies for combining political and epistemic values (“optimistic”, “deliberative”, “democratic” and “pragmatic” and the main objections they have to face. In the concluding section
The Network Protocol Analysis Technique in Snort
Wu, Qing-Xiu
Network protocol analysis is a network sniffer to capture data for further analysis and understanding of the technical means necessary packets. Network sniffing is intercepted by packet assembly binary format of the original message content. In order to obtain the information contained. Required based on TCP / IP protocol stack protocol specification. Again to restore the data packets at protocol format and content in each protocol layer. Actual data transferred, as well as the application tier.
Ecological network analysis for a virtual water network.
Fang, Delin; Chen, Bin
2015-06-02
The notions of virtual water flows provide important indicators to manifest the water consumption and allocation between different sectors via product transactions. However, the configuration of virtual water network (VWN) still needs further investigation to identify the water interdependency among different sectors as well as the network efficiency and stability in a socio-economic system. Ecological network analysis is chosen as a useful tool to examine the structure and function of VWN and the interactions among its sectors. A balance analysis of efficiency and redundancy is also conducted to describe the robustness (RVWN) of VWN. Then, network control analysis and network utility analysis are performed to investigate the dominant sectors and pathways for virtual water circulation and the mutual relationships between pairwise sectors. A case study of the Heihe River Basin in China shows that the balance between efficiency and redundancy is situated on the left side of the robustness curve with less efficiency and higher redundancy. The forestation, herding and fishing sectors and industrial sectors are found to be the main controllers. The network tends to be more mutualistic and synergic, though some competitive relationships that weaken the virtual water circulation still exist.
Basic general concepts in the network analysis
Directory of Open Access Journals (Sweden)
Boja Nicolae
2004-01-01
Full Text Available This survey is concerned oneself with the study of those types of material networks which can be met both in civil engineering and also in electrotechnics, in mechanics, or in hydrotechnics, and of which behavior lead to linear problems, solvable by means of Finite Element Method and adequate algorithms. Here, it is presented a unitary theory of networks met in the domains mentioned above and this one is illustrated with examples for the structural networks in civil engineering, electric circuits, and water supply networks, but also planar or spatial mechanisms can be comprised in this theory. The attention is focused to make evident the essential proper- ties and concepts in the network analysis, which differentiate the networks under force from other types of material networks. To such a network a planar, connected, and directed or undirected graph is associated, and with some vector fields on the vertex set this graph is endowed. .
Network Analysis on Attitudes: A Brief Tutorial.
Dalege, Jonas; Borsboom, Denny; van Harreveld, Frenk; van der Maas, Han L J
2017-07-01
In this article, we provide a brief tutorial on the estimation, analysis, and simulation on attitude networks using the programming language R. We first discuss what a network is and subsequently show how one can estimate a regularized network on typical attitude data. For this, we use open-access data on the attitudes toward Barack Obama during the 2012 American presidential election. Second, we show how one can calculate standard network measures such as community structure, centrality, and connectivity on this estimated attitude network. Third, we show how one can simulate from an estimated attitude network to derive predictions from attitude networks. By this, we highlight that network theory provides a framework for both testing and developing formalized hypotheses on attitudes and related core social psychological constructs.
4th International Conference in Network Analysis
Koldanov, Petr; Pardalos, Panos
2016-01-01
The contributions in this volume cover a broad range of topics including maximum cliques, graph coloring, data mining, brain networks, Steiner forest, logistic and supply chain networks. Network algorithms and their applications to market graphs, manufacturing problems, internet networks and social networks are highlighted. The "Fourth International Conference in Network Analysis," held at the Higher School of Economics, Nizhny Novgorod in May 2014, initiated joint research between scientists, engineers and researchers from academia, industry and government; the major results of conference participants have been reviewed and collected in this Work. Researchers and students in mathematics, economics, statistics, computer science and engineering will find this collection a valuable resource filled with the latest research in network analysis.
An investigation and comparison on network performance analysis
Lanxiaopu, Mi
2012-01-01
This thesis is generally about network performance analysis. It contains two parts. The theory part summarizes what network performance is and inducts the methods of doing network performance analysis. To answer what network performance is, a study into what network services are is done. And based on the background research, there are two important network performance metrics: Network delay and Throughput should be included in network performance analysis. Among the methods of network a...
Investigating biofuels through network analysis
International Nuclear Information System (INIS)
Curci, Ylenia; Mongeau Ospina, Christian A.
2016-01-01
Biofuel policies are motivated by a plethora of political concerns related to energy security, environmental damages, and support of the agricultural sector. In response to this, much scientific work has chiefly focussed on analysing the biofuel domain and on giving policy advice and recommendations. Although innovation has been acknowledged as one of the key factors in sustainable and cost-effective biofuel development, there is an urgent need to investigate technological trajectories in the biofuel sector by starting from consistent data and appropriate methodological tools. To do so, this work proposes a procedure to select patent data unequivocally related to the investigated sector, it uses co-occurrence of technological terms to compute patent similarity and highlights content and interdependencies of biofuels technological trajectories by revealing hidden topics from unstructured patent text fields. The analysis suggests that there is a breaking trend towards modern generation biofuels and that innovators seem to focus increasingly on the ability of alternative energy sources to adapt to the transport/industrial sector. - Highlights: • Innovative effort is devoted to biofuels additives and modern biofuels technologies. • A breaking trend can be observed from the second half of the last decade. • A patent network is identified via text mining techniques that extract latent topics.
Extracting neuronal functional network dynamics via adaptive Granger causality analysis.
Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash
2018-04-24
Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.
Group theoretical analysis of octahedral tilting in perovskites
International Nuclear Information System (INIS)
Howard, C.J.; Stokes, H.T.
1998-01-01
Full text: Structures of the perovskite family, ABX 3 , have interested crystallographers over many years, and continue to attract attention on account of their fascinating electrical and magnetic properties, for example the giant magnetoresistive effects exhibited by certain perovskite materials. The ideal perovskite (cubic, space group Pm -/3 m) is a particularly simple structure, but also a demanding one, since aside from the lattice parameter there are no variable parameters in the structure. Consequently, the majority of perovskite structures are distorted perovskites (hettotypes), the most common distortion being the corner-linked tilting of the practically rigid BX 6 octahedral units. In this work, group theoretical methods have been applied to the study of octahedral tilting in perovskites. The only irreducible representations of the parent group (Pm -/3 m) which produce octahedral tilting subject to corner-linking constraints are M + / 3 and R 4 ' + . A six-dimensional order parameter in the reducible representation space of M + / 3 + R + / 4 describes the different possible tilting patterns. The space groups for the different perovskites are then simply the isotropy subgroups, comprising those operations which leave the order parameter invariant. The isotropy subgroups are obtained from a computer program or tabulations. The analysis yields a list of fifteen possible space groups for perovskites derived through octahedral tilting. A connection is made to the (twenty-three) tilt systems given previously by Glazer. The group-subgroup relationships have been derived and displayed. It is interesting to note that all known perovskites based on octahedral tilting conform with the fifteen space groups on our list, with the exception of one perovskite at high temperature, the structure of which seems poorly determined
Weighted Complex Network Analysis of Pakistan Highways
Directory of Open Access Journals (Sweden)
Yasir Tariq Mohmand
2013-01-01
Full Text Available The structure and properties of public transportation networks have great implications in urban planning, public policies, and infectious disease control. This study contributes a weighted complex network analysis of travel routes on the national highway network of Pakistan. The network is responsible for handling 75 percent of the road traffic yet is largely inadequate, poor, and unreliable. The highway network displays small world properties and is assortative in nature. Based on the betweenness centrality of the nodes, the most important cities are identified as this could help in identifying the potential congestion points in the network. Keeping in view the strategic location of Pakistan, such a study is of practical importance and could provide opportunities for policy makers to improve the performance of the highway network.
Noise Analysis studies with neural networks
International Nuclear Information System (INIS)
Seker, S.; Ciftcioglu, O.
1996-01-01
Noise analysis studies with neural network are aimed. Stochastic signals at the input of the network are used to obtain an algorithmic multivariate stochastic signal modeling. To this end, lattice modeling of a stochastic signal is performed to obtain backward residual noise sources which are uncorrelated among themselves. There are applied together with an additional input to the network to obtain an algorithmic model which is used for signal detection for early failure in plant monitoring. The additional input provides the information to the network to minimize the difference between the signal and the network's one-step-ahead prediction. A stochastic algorithm is used for training where the errors reflecting the measurement error during the training are also modelled so that fast and consistent convergence of network's weights is obtained. The lattice structure coupled to neural network investigated with measured signals from an actual power plant. (authors)
The structure and dynamics of cities urban data analysis and theoretical modeling
Barthelemy, Marc
2016-01-01
With over half of the world's population now living in urban areas, the ability to model and understand the structure and dynamics of cities is becoming increasingly valuable. Combining new data with tools and concepts from statistical physics and urban economics, this book presents a modern and interdisciplinary perspective on cities and urban systems. Both empirical observations and theoretical approaches are critically reviewed, with particular emphasis placed on derivations of classical models and results, along with analysis of their limits and validity. Key aspects of cities are thoroughly analyzed, including mobility patterns, the impact of multimodality, the coupling between different transportation modes, the evolution of infrastructure networks, spatial and social organisation, and interactions between cities. Drawing upon knowledge and methods from areas of mathematics, physics, economics and geography, the resulting quantitative description of cities will be of interest to all those studying and r...
Game Theoretical Approaches for Transport-Aware Channel Selection in Cognitive Radio Networks
Directory of Open Access Journals (Sweden)
Chen Shih-Ho
2010-01-01
Full Text Available Effectively sharing channels among secondary users (SUs is one of the greatest challenges in cognitive radio network (CRN. In the past, many studies have proposed channel selection schemes at the physical or the MAC layer that allow SUs swiftly respond to the spectrum states. However, they may not lead to enhance performance due to slow response of the transport layer flow control mechanism. This paper presents a cross-layer design framework called Transport Aware Channel Selection (TACS scheme to optimize the transport throughput based on states, such as RTT and congestion window size, of TCP flow control mechanism. We formulate the TACS problem as two different game theoretic approaches: Selfish Spectrum Sharing Game (SSSG and Cooperative Spectrum Sharing Game (CSSG and present novel distributed heuristic algorithms to optimize TCP throughput. Computer simulations show that SSSG and CSSG could double the SUs throughput of current MAC-based scheme when primary users (PUs use their channel infrequently, and with up to 12% to 100% throughput increase when PUs are more active. The simulation results also illustrated that CSSG performs up to 20% better than SSSG in terms of the throughput.
Dynamics of the Drosophila circadian clock: theoretical anti-jitter network and controlled chaos.
Directory of Open Access Journals (Sweden)
Hassan M Fathallah-Shaykh
Full Text Available BACKGROUND: Electronic clocks exhibit undesirable jitter or time variations in periodic signals. The circadian clocks of humans, some animals, and plants consist of oscillating molecular networks with peak-to-peak time of approximately 24 hours. Clockwork orange (CWO is a transcriptional repressor of Drosophila direct target genes. METHODOLOGY/PRINCIPAL FINDINGS: Theory and data from a model of the Drosophila circadian clock support the idea that CWO controls anti-jitter negative circuits that stabilize peak-to-peak time in light-dark cycles (LD. The orbit is confined to chaotic attractors in both LD and dark cycles and is almost periodic in LD; furthermore, CWO diminishes the Euclidean dimension of the chaotic attractor in LD. Light resets the clock each day by restricting each molecular peak to the proximity of a prescribed time. CONCLUSIONS/SIGNIFICANCE: The theoretical results suggest that chaos plays a central role in the dynamics of the Drosophila circadian clock and that a single molecule, CWO, may sense jitter and repress it by its negative loops.
Hyperconnectivity in juvenile myoclonic epilepsy: a network analysis.
Caeyenberghs, K; Powell, H W R; Thomas, R H; Brindley, L; Church, C; Evans, J; Muthukumaraswamy, S D; Jones, D K; Hamandi, K
2015-01-01
Juvenile myoclonic epilepsy (JME) is a common idiopathic (genetic) generalized epilepsy (IGE) syndrome characterized by impairments in executive and cognitive control, affecting independent living and psychosocial functioning. There is a growing consensus that JME is associated with abnormal function of diffuse brain networks, typically affecting frontal and fronto-thalamic areas. Using diffusion MRI and a graph theoretical analysis, we examined bivariate (network-based statistic) and multivariate (global and local) properties of structural brain networks in patients with JME (N = 34) and matched controls. Neuropsychological assessment was performed in a subgroup of 14 patients. Neuropsychometry revealed impaired visual memory and naming in JME patients despite a normal full scale IQ (mean = 98.6). Both JME patients and controls exhibited a small world topology in their white matter networks, with no significant differences in the global multivariate network properties between the groups. The network-based statistic approach identified one subnetwork of hyperconnectivity in the JME group, involving primary motor, parietal and subcortical regions. Finally, there was a significant positive correlation in structural connectivity with cognitive task performance. Our findings suggest that structural changes in JME patients are distributed at a network level, beyond the frontal lobes. The identified subnetwork includes key structures in spike wave generation, along with primary motor areas, which may contribute to myoclonic jerks. We conclude that analyzing the affected subnetworks may provide new insights into understanding seizure generation, as well as the cognitive deficits observed in JME patients.
Classification and Analysis of Computer Network Traffic
Bujlow, Tomasz
2014-01-01
Traffic monitoring and analysis can be done for multiple different reasons: to investigate the usage of network resources, assess the performance of network applications, adjust Quality of Service (QoS) policies in the network, log the traffic to comply with the law, or create realistic models of traffic for academic purposes. We define the objective of this thesis as finding a way to evaluate the performance of various applications in a high-speed Internet infrastructure. To satisfy the obje...
Wireless Sensor Network Security Analysis
Hemanta Kumar Kalita; Avijit Kar
2009-01-01
The emergence of sensor networks as one of the dominant technology trends in the coming decades hasposed numerous unique challenges to researchers. These networks are likely to be composed of hundreds,and potentially thousands of tiny sensor nodes, functioning autonomously, and in many cases, withoutaccess to renewable energy resources. Cost constraints and the need for ubiquitous, invisibledeployments will result in small sized, resource-constrained sensor nodes. While the set of challenges ...
NEXCADE: perturbation analysis for complex networks.
Directory of Open Access Journals (Sweden)
Gitanjali Yadav
Full Text Available Recent advances in network theory have led to considerable progress in our understanding of complex real world systems and their behavior in response to external threats or fluctuations. Much of this research has been invigorated by demonstration of the 'robust, yet fragile' nature of cellular and large-scale systems transcending biology, sociology, and ecology, through application of the network theory to diverse interactions observed in nature such as plant-pollinator, seed-dispersal agent and host-parasite relationships. In this work, we report the development of NEXCADE, an automated and interactive program for inducing disturbances into complex systems defined by networks, focusing on the changes in global network topology and connectivity as a function of the perturbation. NEXCADE uses a graph theoretical approach to simulate perturbations in a user-defined manner, singly, in clusters, or sequentially. To demonstrate the promise it holds for broader adoption by the research community, we provide pre-simulated examples from diverse real-world networks including eukaryotic protein-protein interaction networks, fungal biochemical networks, a variety of ecological food webs in nature as well as social networks. NEXCADE not only enables network visualization at every step of the targeted attacks, but also allows risk assessment, i.e. identification of nodes critical for the robustness of the system of interest, in order to devise and implement context-based strategies for restructuring a network, or to achieve resilience against link or node failures. Source code and license for the software, designed to work on a Linux-based operating system (OS can be downloaded at http://www.nipgr.res.in/nexcade_download.html. In addition, we have developed NEXCADE as an OS-independent online web server freely available to the scientific community without any login requirement at http://www.nipgr.res.in/nexcade.html.
Industrial entrepreneurial network: Structural and functional analysis
Medvedeva, M. A.; Davletbaev, R. H.; Berg, D. B.; Nazarova, J. J.; Parusheva, S. S.
2016-12-01
Structure and functioning of two model industrial entrepreneurial networks are investigated in the present paper. One of these networks is forming when implementing an integrated project and consists of eight agents, which interact with each other and external environment. The other one is obtained from the municipal economy and is based on the set of the 12 real business entities. Analysis of the networks is carried out on the basis of the matrix of mutual payments aggregated over the certain time period. The matrix is created by the methods of experimental economics. Social Network Analysis (SNA) methods and instruments were used in the present research. The set of basic structural characteristics was investigated: set of quantitative parameters such as density, diameter, clustering coefficient, different kinds of centrality, and etc. They were compared with the random Bernoulli graphs of the corresponding size and density. Discovered variations of random and entrepreneurial networks structure are explained by the peculiarities of agents functioning in production network. Separately, were identified the closed exchange circuits (cyclically closed contours of graph) forming an autopoietic (self-replicating) network pattern. The purpose of the functional analysis was to identify the contribution of the autopoietic network pattern in its gross product. It was found that the magnitude of this contribution is more than 20%. Such value allows using of the complementary currency in order to stimulate economic activity of network agents.
3rd International Conference on Network Analysis
Kalyagin, Valery; Pardalos, Panos
2014-01-01
This volume compiles the major results of conference participants from the "Third International Conference in Network Analysis" held at the Higher School of Economics, Nizhny Novgorod in May 2013, with the aim to initiate further joint research among different groups. The contributions in this book cover a broad range of topics relevant to the theory and practice of network analysis, including the reliability of complex networks, software, theory, methodology, and applications. Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network has brought together researchers, practitioners from numerous fields such as operations research, computer science, transportation, energy, biomedicine, computational neuroscience and social sciences. In addition, new approaches and computer environments such as parallel computing, grid computing, cloud computing, and quantum computing have helped to solve large scale...
A Theoretical Analysis of Agricultural Policy in Nigeria.
African Journals Online (AJOL)
The colonial and post-colonial Nigerian State inherited agricultural policy antithetical to its development and the realization of domestic objectives. This paper establishes a theoretical nexus between a neo-colonial state, poverty, agricultural practices and policies. It examines the agricultural policies of the Nigerian state ...
Theoretical bases analysis of scientific prediction on marketing principles
A.S. Rosohata
2012-01-01
The article presents an overview categorical apparatus of scientific predictions and theoretical foundations results of scientific forecasting. They are integral part of effective management of economic activities. The approaches to the prediction of scientists in different fields of Social science and the categories modification of scientific prediction, based on principles of marketing are proposed.
Directory of Open Access Journals (Sweden)
Jun Lv
Full Text Available Functional brain networks of human have been revealed to have small-world properties by both analyzing electroencephalogram (EEG and functional magnetic resonance imaging (fMRI time series.In our study, by using graph theoretical analysis, we attempted to investigate the changes of paralimbic-limbic cortex between wake and sleep states. Ten healthy young people were recruited to our experiment. Data from 2 subjects were excluded for the reason that they had not fallen asleep during the experiment. For each subject, blood oxygen level dependency (BOLD images were acquired to analyze brain network, and peripheral pulse signals were obtained continuously to identify if the subject was in sleep periods. Results of fMRI showed that brain networks exhibited stronger small-world characteristics during sleep state as compared to wake state, which was in consistent with previous studies using EEG synchronization. Moreover, we observed that compared with wake state, paralimbic-limbic cortex had less connectivity with neocortical system and centrencephalic structure in sleep.In conclusion, this is the first study, to our knowledge, has observed that small-world properties of brain functional networks altered when human sleeps without EEG synchronization. Moreover, we speculate that paralimbic-limbic cortex organization owns an efficient defense mechanism responsible for suppressing the external environment interference when humans sleep, which is consistent with the hypothesis that the paralimbic-limbic cortex may be functionally disconnected from brain regions which directly mediate their interactions with the external environment. Our findings also provide a reasonable explanation why stable sleep exhibits homeostasis which is far less susceptible to outside world.
Custom Ontologies for Expanded Network Analysis
2006-12-01
for Expanded Network Analysis. In Visualising Network Information (pp. 6-1 – 6-10). Meeting Proceedings RTO-MP-IST-063, Paper 6. Neuilly-sur-Seine...Even to this day, current research groups are working to develop an approach that involves taking all available text, video, imagery and audio and
Analysis of complex networks using aggressive abstraction.
Energy Technology Data Exchange (ETDEWEB)
Colbaugh, Richard; Glass, Kristin.; Willard, Gerald
2008-10-01
This paper presents a new methodology for analyzing complex networks in which the network of interest is first abstracted to a much simpler (but equivalent) representation, the required analysis is performed using the abstraction, and analytic conclusions are then mapped back to the original network and interpreted there. We begin by identifying a broad and important class of complex networks which admit abstractions that are simultaneously dramatically simplifying and property preserving we call these aggressive abstractions -- and which can therefore be analyzed using the proposed approach. We then introduce and develop two forms of aggressive abstraction: 1.) finite state abstraction, in which dynamical networks with uncountable state spaces are modeled using finite state systems, and 2.) onedimensional abstraction, whereby high dimensional network dynamics are captured in a meaningful way using a single scalar variable. In each case, the property preserving nature of the abstraction process is rigorously established and efficient algorithms are presented for computing the abstraction. The considerable potential of the proposed approach to complex networks analysis is illustrated through case studies involving vulnerability analysis of technological networks and predictive analysis for social processes.
Consistency analysis of network traffic repositories
Lastdrager, Elmer; Lastdrager, E.E.H.; Pras, Aiko
Traffic repositories with TCP/IP header information are very important for network analysis. Researchers often assume that such repositories reliably represent all traffic that has been flowing over the network; little thoughts are made regarding the consistency of these repositories. Still, for
A game-theoretic approach to optimize ad hoc networks inspired by small-world network topology
Tan, Mian; Yang, Tinghong; Chen, Xing; Yang, Gang; Zhu, Guoqing; Holme, Petter; Zhao, Jing
2018-03-01
Nodes in ad hoc networks are connected in a self-organized manner. Limited communication radius makes information transmit in multi-hop mode, and each forwarding needs to consume the energy of nodes. Insufficient communication radius or exhaustion of energy may cause the absence of some relay nodes and links, further breaking network connectivity. On the other hand, nodes in the network may refuse to cooperate due to objective faulty or personal selfish, hindering regular communication in the network. This paper proposes a model called Repeated Game in Small World Networks (RGSWN). In this model, we first construct ad hoc networks with small-world feature by forming "communication shortcuts" between multiple-radio nodes. Small characteristic path length reduces average forwarding times in networks; meanwhile high clustering coefficient enhances network robustness. Such networks still maintain relative low global power consumption, which is beneficial to extend the network survival time. Then we use MTTFT strategy (Mend-Tolerance Tit-for-Tat) for repeated game as a rule for the interactions between neighbors in the small-world networks. Compared with other five strategies of repeated game, this strategy not only punishes the nodes' selfishness more reasonably, but also has the best tolerance to the network failure. This work is insightful for designing an efficient and robust ad hoc network.
Boolean Factor Analysis by Attractor Neural Network
Czech Academy of Sciences Publication Activity Database
Frolov, A. A.; Húsek, Dušan; Muraviev, I. P.; Polyakov, P.Y.
2007-01-01
Roč. 18, č. 3 (2007), s. 698-707 ISSN 1045-9227 R&D Projects: GA AV ČR 1ET100300419; GA ČR GA201/05/0079 Institutional research plan: CEZ:AV0Z10300504 Keywords : recurrent neural network * Hopfield-like neural network * associative memory * unsupervised learning * neural network architecture * neural network application * statistics * Boolean factor analysis * dimensionality reduction * features clustering * concepts search * information retrieval Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.769, year: 2007
Spectrum-Based and Collaborative Network Topology Analysis and Visualization
Hu, Xianlin
2013-01-01
Networks are of significant importance in many application domains, such as World Wide Web and social networks, which often embed rich topological information. Since network topology captures the organization of network nodes and links, studying network topology is very important to network analysis. In this dissertation, we study networks by…
Analysis and Testing of Mobile Wireless Networks
Alena, Richard; Evenson, Darin; Rundquist, Victor; Clancy, Daniel (Technical Monitor)
2002-01-01
Wireless networks are being used to connect mobile computing elements in more applications as the technology matures. There are now many products (such as 802.11 and 802.11b) which ran in the ISM frequency band and comply with wireless network standards. They are being used increasingly to link mobile Intranet into Wired networks. Standard methods of analyzing and testing their performance and compatibility are needed to determine the limits of the technology. This paper presents analytical and experimental methods of determining network throughput, range and coverage, and interference sources. Both radio frequency (BE) domain and network domain analysis have been applied to determine wireless network throughput and range in the outdoor environment- Comparison of field test data taken under optimal conditions, with performance predicted from RF analysis, yielded quantitative results applicable to future designs. Layering multiple wireless network- sooners can increase performance. Wireless network components can be set to different radio frequency-hopping sequences or spreading functions, allowing more than one sooner to coexist. Therefore, we ran multiple 802.11-compliant systems concurrently in the same geographical area to determine interference effects and scalability, The results can be used to design of more robust networks which have multiple layers of wireless data communication paths and provide increased throughput overall.
Complex Network Analysis of Guangzhou Metro
Directory of Open Access Journals (Sweden)
Yasir Tariq Mohmand
2015-11-01
Full Text Available The structure and properties of public transportation networks can provide suggestions for urban planning and public policies. This study contributes a complex network analysis of the Guangzhou metro. The metro network has 236 kilometers of track and is the 6th busiest metro system of the world. In this paper topological properties of the network are explored. We observed that the network displays small world properties and is assortative in nature. The network possesses a high average degree of 17.5 with a small diameter of 5. Furthermore, we also identified the most important metro stations based on betweenness and closeness centralities. These could help in identifying the probable congestion points in the metro system and provide policy makers with an opportunity to improve the performance of the metro system.
Extending Stochastic Network Calculus to Loss Analysis
Directory of Open Access Journals (Sweden)
Chao Luo
2013-01-01
Full Text Available Loss is an important parameter of Quality of Service (QoS. Though stochastic network calculus is a very useful tool for performance evaluation of computer networks, existing studies on stochastic service guarantees mainly focused on the delay and backlog. Some efforts have been made to analyse loss by deterministic network calculus, but there are few results to extend stochastic network calculus for loss analysis. In this paper, we introduce a new parameter named loss factor into stochastic network calculus and then derive the loss bound through the existing arrival curve and service curve via this parameter. We then prove that our result is suitable for the networks with multiple input flows. Simulations show the impact of buffer size, arrival traffic, and service on the loss factor.
Computer network environment planning and analysis
Dalphin, John F.
1989-01-01
The GSFC Computer Network Environment provides a broadband RF cable between campus buildings and ethernet spines in buildings for the interlinking of Local Area Networks (LANs). This system provides terminal and computer linkage among host and user systems thereby providing E-mail services, file exchange capability, and certain distributed computing opportunities. The Environment is designed to be transparent and supports multiple protocols. Networking at Goddard has a short history and has been under coordinated control of a Network Steering Committee for slightly more than two years; network growth has been rapid with more than 1500 nodes currently addressed and greater expansion expected. A new RF cable system with a different topology is being installed during summer 1989; consideration of a fiber optics system for the future will begin soon. Summmer study was directed toward Network Steering Committee operation and planning plus consideration of Center Network Environment analysis and modeling. Biweekly Steering Committee meetings were attended to learn the background of the network and the concerns of those managing it. Suggestions for historical data gathering have been made to support future planning and modeling. Data Systems Dynamic Simulator, a simulation package developed at NASA and maintained at GSFC was studied as a possible modeling tool for the network environment. A modeling concept based on a hierarchical model was hypothesized for further development. Such a model would allow input of newly updated parameters and would provide an estimation of the behavior of the network.
UMA/GAN network architecture analysis
Yang, Liang; Li, Wensheng; Deng, Chunjian; Lv, Yi
2009-07-01
This paper is to critically analyze the architecture of UMA which is one of Fix Mobile Convergence (FMC) solutions, and also included by the third generation partnership project(3GPP). In UMA/GAN network architecture, UMA Network Controller (UNC) is the key equipment which connects with cellular core network and mobile station (MS). UMA network could be easily integrated into the existing cellular networks without influencing mobile core network, and could provides high-quality mobile services with preferentially priced indoor voice and data usage. This helps to improve subscriber's experience. On the other hand, UMA/GAN architecture helps to integrate other radio technique into cellular network which includes WiFi, Bluetooth, and WiMax and so on. This offers the traditional mobile operators an opportunity to integrate WiMax technique into cellular network. In the end of this article, we also give an analysis of potential influence on the cellular core networks ,which is pulled by UMA network.
Constructing an Intelligent Patent Network Analysis Method
Directory of Open Access Journals (Sweden)
Chao-Chan Wu
2012-11-01
Full Text Available Patent network analysis, an advanced method of patent analysis, is a useful tool for technology management. This method visually displays all the relationships among the patents and enables the analysts to intuitively comprehend the overview of a set of patents in the field of the technology being studied. Although patent network analysis possesses relative advantages different from traditional methods of patent analysis, it is subject to several crucial limitations. To overcome the drawbacks of the current method, this study proposes a novel patent analysis method, called the intelligent patent network analysis method, to make a visual network with great precision. Based on artificial intelligence techniques, the proposed method provides an automated procedure for searching patent documents, extracting patent keywords, and determining the weight of each patent keyword in order to generate a sophisticated visualization of the patent network. This study proposes a detailed procedure for generating an intelligent patent network that is helpful for improving the efficiency and quality of patent analysis. Furthermore, patents in the field of Carbon Nanotube Backlight Unit (CNT-BLU were analyzed to verify the utility of the proposed method.
Spectroscopic Analysis of Neurotransmitters: A Theoretical and Experimental Raman Study
Alonzo, Matthew
Surface-enhanced Raman spectroscopy (SERS) was applied to investigate the feasibility in the detection and monitoring of the dopamine (DA) neurotransmitter adsorbed onto silver nanoparticles (Ag NPs) at 10-11 molar, a concentration far below physiological levels. In addition, density functional theory (DFT) calculations were obtained with the Gaussian-09 analytical suite software to generate the theoretical molecular configuration of DA in its neutral, cationic, anionic, and dopaminequinone states for the conversion of computer-simulated Raman spectra. Comparison of theoretical and experimental results show good agreement and imply the presence of dopamine in all of its molecular forms in the experimental setting. The dominant dopamine Raman bands at 750 cm-1 and 795 cm-1 suggest the adsorption of dopaminequinone onto the silver nanoparticle surface. The results of this experiment give good insight into the applicability of using Raman spectroscopy for the biodetection of neurotransmitters.
Techniques for Intelligence Analysis of Networks
National Research Council Canada - National Science Library
Cares, Jeffrey R
2005-01-01
...) there are significant intelligence analysis manifestations of these properties; and (4) a more satisfying theory of Networked Competition than currently exists for NCW/NCO is emerging from this research...
Ray-tracing toroidal axisymmetric devices. 1. theoretical analysis
International Nuclear Information System (INIS)
Cardinali, A.; Brambilla, M.
1981-06-01
Ray tracing technique for lower hybrid waves is used to obtain informations about accessibility, power deposition profiles and eventually electric field distribution. In the first part a critical discussion to establish the meaning and validity of this technique is presented, while in the second part of this work applications to small and to large, fat tokamaks are presented, which support and explain the theoretical arguments
Topological Analysis of Wireless Networks (TAWN)
2016-05-31
19b. TELEPHONE NUMBER (Include area code) 31-05-2016 FINAL REPORT 12-02-2015 -- 31-05-2016 Topological Analysis of Wireless Networks (TAWN) Robinson...Release, Distribution Unlimited) N/A The goal of this project was to develop topological methods to detect and localize vulnerabilities of wireless... topology U U U UU 32 Michael Robinson 202-885-3681 Final Report: May 2016 Topological Analysis of Wireless Networks Principal Investigator: Prof. Michael
Analysis of FOXO transcriptional networks
van der Vos, K.E.
2010-01-01
The PI3K-PKB-FOXO signalling module plays a pivotal role in a wide variety of cellular processes, including proliferation, survival, differentiation and metabolism. Inappropriate activation of this network is frequently observed in human cancer and causes uncontrolled proliferation and survival. In
Brain Network Analysis from High-Resolution EEG Signals
de Vico Fallani, Fabrizio; Babiloni, Fabio
lattice and a random structure. Such a model has been designated as "small-world" network in analogy with the concept of the small-world phenomenon observed more than 30 years ago in social systems. In a similar way, many types of functional brain networks have been analyzed according to this mathematical approach. In particular, several studies based on different imaging techniques (fMRI, MEG and EEG) have found that the estimated functional networks showed small-world characteristics. In the functional brain connectivity context, these properties have been demonstrated to reflect an optimal architecture for the information processing and propagation among the involved cerebral structures. However, the performance of cognitive and motor tasks as well as the presence of neural diseases has been demonstrated to affect such a small-world topology, as revealed by the significant changes of L and C. Moreover, some functional brain networks have been mostly found to be very unlike the random graphs in their degree-distribution, which gives information about the allocation of the functional links within the connectivity pattern. It was demonstrated that the degree distributions of these networks follow a power-law trend. For this reason those networks are called "scale-free". They still exhibit the small-world phenomenon but tend to contain few nodes that act as highly connected "hubs". Scale-free networks are known to show resistance to failure, facility of synchronization and fast signal processing. Hence, it would be important to see whether the scaling properties of the functional brain networks are altered under various pathologies or experimental tasks. The present Chapter proposes a theoretical graph approach in order to evaluate the functional connectivity patterns obtained from high-resolution EEG signals. In this way, the "Brain Network Analysis" (in analogy with the Social Network Analysis that has emerged as a key technique in modern sociology) represents an
Intrinsic functional brain architecture derived from graph theoretical analysis in the human fetus.
Directory of Open Access Journals (Sweden)
Moriah E Thomason
Full Text Available The human brain undergoes dramatic maturational changes during late stages of fetal and early postnatal life. The importance of this period to the establishment of healthy neural connectivity is apparent in the high incidence of neural injury in preterm infants, in whom untimely exposure to ex-uterine factors interrupts neural connectivity. Though the relevance of this period to human neuroscience is apparent, little is known about functional neural networks in human fetal life. Here, we apply graph theoretical analysis to examine human fetal brain connectivity. Utilizing resting state functional magnetic resonance imaging (fMRI data from 33 healthy human fetuses, 19 to 39 weeks gestational age (GA, our analyses reveal that the human fetal brain has modular organization and modules overlap functional systems observed postnatally. Age-related differences between younger (GA <31 weeks and older (GA≥31 weeks fetuses demonstrate that brain modularity decreases, and connectivity of the posterior cingulate to other brain networks becomes more negative, with advancing GA. By mimicking functional principles observed postnatally, these results support early emerging capacity for information processing in the human fetal brain. Current technical limitations, as well as the potential for fetal fMRI to one day produce major discoveries about fetal origins or antecedents of neural injury or disease are discussed.
Information-Theoretical Analysis of EEG Microstate Sequences in Python
Directory of Open Access Journals (Sweden)
Frederic von Wegner
2018-06-01
Full Text Available We present an open-source Python package to compute information-theoretical quantities for electroencephalographic data. Electroencephalography (EEG measures the electrical potential generated by the cerebral cortex and the set of spatial patterns projected by the brain's electrical potential on the scalp surface can be clustered into a set of representative maps called EEG microstates. Microstate time series are obtained by competitively fitting the microstate maps back into the EEG data set, i.e., by substituting the EEG data at a given time with the label of the microstate that has the highest similarity with the actual EEG topography. As microstate sequences consist of non-metric random variables, e.g., the letters A–D, we recently introduced information-theoretical measures to quantify these time series. In wakeful resting state EEG recordings, we found new characteristics of microstate sequences such as periodicities related to EEG frequency bands. The algorithms used are here provided as an open-source package and their use is explained in a tutorial style. The package is self-contained and the programming style is procedural, focusing on code intelligibility and easy portability. Using a sample EEG file, we demonstrate how to perform EEG microstate segmentation using the modified K-means approach, and how to compute and visualize the recently introduced information-theoretical tests and quantities. The time-lagged mutual information function is derived as a discrete symbolic alternative to the autocorrelation function for metric time series and confidence intervals are computed from Markov chain surrogate data. The software package provides an open-source extension to the existing implementations of the microstate transform and is specifically designed to analyze resting state EEG recordings.
Preventing Wormhole Attacks on Wireless Ad Hoc Networks: A Graph Theoretic Approach
National Research Council Canada - National Science Library
Lazos, L; Poovendran, Radha; Meadows, C; Syverson, P; Chang, L. W
2005-01-01
We study the problem of characterizing the wormhole attack, an attack that can be mounted on a wide range of wireless network protocols without compromising any cryptographic quantity or network node...
1st International Conference on Network Analysis
Kalyagin, Valery; Pardalos, Panos
2013-01-01
This volume contains a selection of contributions from the "First International Conference in Network Analysis," held at the University of Florida, Gainesville, on December 14-16, 2011. The remarkable diversity of fields that take advantage of Network Analysis makes the endeavor of gathering up-to-date material in a single compilation a useful, yet very difficult, task. The purpose of this volume is to overcome this difficulty by collecting the major results found by the participants and combining them in one easily accessible compilation. Network analysis has become a major research topic over the last several years. The broad range of applications that can be described and analyzed by means of a network is bringing together researchers, practitioners and other scientific communities from numerous fields such as Operations Research, Computer Science, Transportation, Energy, Social Sciences, and more. The contributions not only come from different fields, but also cover a broad range of topics relevant to the...
Artificial neural networks for plasma spectroscopy analysis
International Nuclear Information System (INIS)
Morgan, W.L.; Larsen, J.T.; Goldstein, W.H.
1992-01-01
Artificial neural networks have been applied to a variety of signal processing and image recognition problems. Of the several common neural models the feed-forward, back-propagation network is well suited for the analysis of scientific laboratory data, which can be viewed as a pattern recognition problem. The authors present a discussion of the basic neural network concepts and illustrate its potential for analysis of experiments by applying it to the spectra of laser produced plasmas in order to obtain estimates of electron temperatures and densities. Although these are high temperature and density plasmas, the neural network technique may be of interest in the analysis of the low temperature and density plasmas characteristic of experiments and devices in gaseous electronics
Visualization and Analysis of Complex Covert Networks
DEFF Research Database (Denmark)
Memon, Bisharat
systems that are covert and hence inherently complex. My Ph.D. is positioned within the wider framework of CrimeFighter project. The framework envisions a number of key knowledge management processes that are involved in the workflow, and the toolbox provides supporting tools to assist human end......This report discusses and summarize the results of my work so far in relation to my Ph.D. project entitled "Visualization and Analysis of Complex Covert Networks". The focus of my research is primarily on development of methods and supporting tools for visualization and analysis of networked......-users (intelligence analysts) in harvesting, filtering, storing, managing, structuring, mining, analyzing, interpreting, and visualizing data about offensive networks. The methods and tools proposed and discussed in this work can also be applied to analysis of more generic complex networks....
Historical Network Analysis of the Web
DEFF Research Database (Denmark)
Brügger, Niels
2013-01-01
This article discusses some of the fundamental methodological challenges related to doing historical network analyses of the web based on material in web archives. Since the late 1990s many countries have established extensive national web archives, and software supported network analysis...... of the online web has for a number of years gained currency within Internet studies. However, the combination of these two phenomena—historical network analysis of material in web archives—can at best be characterized as an emerging new area of study. Most of the methodological challenges within this new area...... revolve around the specific nature of archived web material. On the basis of an introduction to the processes involved in web archiving as well as of the characteristics of archived web material, the article outlines and scrutinizes some of the major challenges which may arise when doing network analysis...
Theoretical analysis on the probability of initiating persistent fission chain
International Nuclear Information System (INIS)
Liu Jianjun; Wang Zhe; Zhang Ben'ai
2005-01-01
For the finite multiplying system of fissile material in the presence of a weak neutron source, the authors analyses problems on the probability of initiating a persistent fission chain through reckoning the stochastic theory of neutron multiplication. In the theoretical treatment, the conventional point reactor conception model is developed to an improved form with position x and velocity v dependence. The estimated results including approximate value of the probability mentioned above and its distribution are given by means of diffusion approximation and compared with those with previous point reactor conception model. They are basically consistent, however the present model can provide details on the distribution. (authors)
Ultrasensitive Detection of Infrared Photon Using Microcantilever: Theoretical Analysis
International Nuclear Information System (INIS)
Li-Xin, Cao; Feng-Xin, Zhang; Yin-Fang, Zhu; Jin-Ling, Yang
2010-01-01
We present a new method for detecting near-infrared, mid-infrared, and far-infrared photons with an ultrahigh sensitivity. The infrared photon detection was carried out by monitoring the displacement change of a vibrating microcantilever under light pressure using a laser Doppler vibrometer. Ultrathin silicon cantilevers with high sensitivity were produced using micro/nano-fabrication technology. The photon detection system was set up. The response of the microcantilever to the photon illumination is theoretically estimated, and a nanowatt resolution for the infrared photon detection is expected at room temperature with this method
6 essays about auctions: a theoretical and empirical analysis. Application to power markets
International Nuclear Information System (INIS)
Lamy, L.
2007-06-01
This thesis is devoted to a theoretical and empirical analysis of auction mechanisms. Motivated by allocation issues in network industries, in particular by the liberalization of the electricity sector, it focus on auctions with externalities (either allocative or informational) and on multi-objects auctions. After an introduction which provides a survey of the use and the analysis of auctions in power markets, six chapters make this thesis. The first one considers standard auctions in Milgrom-Weber's model with interdependent valuations when the seller can not commit not to participate in the auction. The second and third chapters study the combinatorial auction mechanism proposed by Ausubel and Milgrom. The first of these two studies proposes a modification of this format with a final discount stage and clarifies the theoretical status of those formats, in particular the conditions such that truthful reporting is a dominant strategy. Motivated by the robustness issues of the generalizations of the Ausubel-Milgrom and the Vickrey combinatorial auctions to environments with allocative externalities between joint-purchasers, the second one characterizes the buyer-sub-modularity condition in a general model with allocative identity-dependent externalities between purchasers. In a complete information setup, the fourth chapter analyses the optimal design problem when the commitment abilities of the principal are reduced, namely she can not commit to a simultaneous participation game. The fifth chapter is devoted to the structural analysis of the private value auction model for a single-unit when the econometrician can not observe bidders' identities. The asymmetric independent private value (IPV) model is identified. A multi-step kernel-based estimator is proposed and shown to be asymptotically optimal. Using auctions data for the anglo-french electric Interconnector, the last chapter analyses a multi-unit ascending auctions through reduced forms. (author)
Theoretical Properties for Neural Networks with Weight Matrices of Low Displacement Rank
Zhao, Liang; Liao, Siyu; Wang, Yanzhi; Li, Zhe; Tang, Jian; Pan, Victor; Yuan, Bo
2017-01-01
Recently low displacement rank (LDR) matrices, or so-called structured matrices, have been proposed to compress large-scale neural networks. Empirical results have shown that neural networks with weight matrices of LDR matrices, referred as LDR neural networks, can achieve significant reduction in space and computational complexity while retaining high accuracy. We formally study LDR matrices in deep learning. First, we prove the universal approximation property of LDR neural networks with a ...
Directory of Open Access Journals (Sweden)
Minyoung Yea
2018-06-01
Full Text Available This study investigates a strategic alliance as a horizontal cooperation in the logistics and transportation industries by considering various sharing rules with a cooperative game approach. Through forging a strategic alliance, carriers gain extra benefits from resource sharing and high efficiency resource utilization. In particular, our research focuses on the cost savings from using larger vehicles utilizing collective market demand and regarding them as benefits of cooperation. The model conceptualizes the characteristic function of cost savings by coalitions that take into account the hub-spoke network which is common in transportation services. To share the improved profits fairly between members, we use different allocation schemes: the Shapley value, the core center, the τ -value, and the nucleolus. By analyzing those cooperative game theoretic solutions employing an alliance composed of three carriers, we investigate whether satisfaction in this specific coalition provides an incentive for carriers to join such a coalition. Our results from the analysis, with respect to fair allocation schemes, provide a practical and academic foundation for further research.
The International Trade Network: weighted network analysis and modelling
International Nuclear Information System (INIS)
Bhattacharya, K; Mukherjee, G; Manna, S S; Saramäki, J; Kaski, K
2008-01-01
Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN
Network Anomaly Detection Based on Wavelet Analysis
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Ali A. Ghorbani
2008-11-01
Full Text Available Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.
Network Anomaly Detection Based on Wavelet Analysis
Lu, Wei; Ghorbani, Ali A.
2008-12-01
Signal processing techniques have been applied recently for analyzing and detecting network anomalies due to their potential to find novel or unknown intrusions. In this paper, we propose a new network signal modelling technique for detecting network anomalies, combining the wavelet approximation and system identification theory. In order to characterize network traffic behaviors, we present fifteen features and use them as the input signals in our system. We then evaluate our approach with the 1999 DARPA intrusion detection dataset and conduct a comprehensive analysis of the intrusions in the dataset. Evaluation results show that the approach achieves high-detection rates in terms of both attack instances and attack types. Furthermore, we conduct a full day's evaluation in a real large-scale WiFi ISP network where five attack types are successfully detected from over 30 millions flows.
Task Analysis in Instructional Program Development. Theoretical Paper No. 52.
Bernard, Michael E.
A review of task analysis procedures beginning with the military training and systems development approach and covering the more recent work of Gagne, Klausmeier, Merrill, Resnick, and others is presented along with a plan for effective instruction based on the review of task analysis. Literature dealing with the use of task analysis in programmed…
Energy Technology Data Exchange (ETDEWEB)
Thomas, John (Massachusetts Institute of Technology)
2012-05-01
Systems Theoretic Process Analysis (STPA) is a powerful new hazard analysis method designed to go beyond traditional safety techniques - such as Fault Tree Analysis (FTA) - that overlook important causes of accidents like flawed requirements, dysfunctional component interactions, and software errors. While proving to be very effective on real systems, no formal structure has been defined for STPA and its application has been ad-hoc with no rigorous procedures or model-based design tools. This report defines a formal mathematical structure underlying STPA and describes a procedure for systematically performing an STPA analysis based on that structure. A method for using the results of the hazard analysis to generate formal safety-critical, model-based system and software requirements is also presented. Techniques to automate both the analysis and the requirements generation are introduced, as well as a method to detect conflicts between the safety and other functional model-based requirements during early development of the system.
Difference-theoretical Analysis of Aesthetic Media and Forms
Directory of Open Access Journals (Sweden)
Franz Kasper Krönig
2018-04-01
Full Text Available The general medium/form-difference-theory as proposed by Fritz Heider (cf. Heider, 1959 has been seized on by the sociological systems theory as an epistemological and heuristic basis of such a generality that it can be applied to virtually all conceivable fields of research. One could arguably speak of a new paradigm that overcomes traditional differences such as subject/object and cause/effect. This approach has been applied to all types of art, and various research questions in the fields of aesthetics and art theory. This paper proposes a differentiation and categorisation of aesthetic media and forms in order to lay the groundwork for art criticism on a third way between subjective appreciation and objective reasoning. Musical examples demonstrate the applicability of the medium/form-difference-theoretical approach for the aesthetics of music and music criticism.
Game theoretical analysis of safeguards effectiveness. Pt. 3
International Nuclear Information System (INIS)
Avenhaus, R.; Canty, M.J.
1989-12-01
In Part 1 of the present study on safeguards effectiveness it was shown that for attribute sampling problems the guaranteed probability of detection can be used as a measure for the effectiveness of safeguards procedures. In Part 2 this measure was used for variable sampling problems, with given false alarm probabilities as boundary conditions. In Part 3 we show that the measure can be justified by appropriate game theoretical models. Furthermore, we show that, for attribute sampling, the equilibrium strategy of the operator is legal behavior if appropriate effort conditions are fulfilled, whether or not the inspector announces his strategy in advance. For variable sampling, legal behavior is equilibrium strategy of the operator only if the inspector announces his strategy. (orig.)
Valente, Thomas W; Pitts, Stephanie R
2017-03-20
The use of social network theory and analysis methods as applied to public health has expanded greatly in the past decade, yielding a significant academic literature that spans almost every conceivable health issue. This review identifies several important theoretical challenges that confront the field but also provides opportunities for new research. These challenges include (a) measuring network influences, (b) identifying appropriate influence mechanisms, (c) the impact of social media and computerized communications, (d) the role of networks in evaluating public health interventions, and (e) ethics. Next steps for the field are outlined and the need for funding is emphasized. Recently developed network analysis techniques, technological innovations in communication, and changes in theoretical perspectives to include a focus on social and environmental behavioral influences have created opportunities for new theory and ever broader application of social networks to public health topics.
Social network analysis applied to team sports analysis
Clemente, Filipe Manuel; Mendes, Rui Sousa
2016-01-01
Explaining how graph theory and social network analysis can be applied to team sports analysis, This book presents useful approaches, models and methods that can be used to characterise the overall properties of team networks and identify the prominence of each team player. Exploring the different possible network metrics that can be utilised in sports analysis, their possible applications and variances from situation to situation, the respective chapters present an array of illustrative case studies. Identifying the general concepts of social network analysis and network centrality metrics, readers are shown how to generate a methodological protocol for data collection. As such, the book provides a valuable resource for students of the sport sciences, sports engineering, applied computation and the social sciences.
Fast network centrality analysis using GPUs
Directory of Open Access Journals (Sweden)
Shi Zhiao
2011-05-01
Full Text Available Abstract Background With the exploding volume of data generated by continuously evolving high-throughput technologies, biological network analysis problems are growing larger in scale and craving for more computational power. General Purpose computation on Graphics Processing Units (GPGPU provides a cost-effective technology for the study of large-scale biological networks. Designing algorithms that maximize data parallelism is the key in leveraging the power of GPUs. Results We proposed an efficient data parallel formulation of the All-Pairs Shortest Path problem, which is the key component for shortest path-based centrality computation. A betweenness centrality algorithm built upon this formulation was developed and benchmarked against the most recent GPU-based algorithm. Speedup between 11 to 19% was observed in various simulated scale-free networks. We further designed three algorithms based on this core component to compute closeness centrality, eccentricity centrality and stress centrality. To make all these algorithms available to the research community, we developed a software package gpu-fan (GPU-based Fast Analysis of Networks for CUDA enabled GPUs. Speedup of 10-50× compared with CPU implementations was observed for simulated scale-free networks and real world biological networks. Conclusions gpu-fan provides a significant performance improvement for centrality computation in large-scale networks. Source code is available under the GNU Public License (GPL at http://bioinfo.vanderbilt.edu/gpu-fan/.
Crawling Facebook for Social Network Analysis Purposes
Catanese, Salvatore A.; De Meo, Pasquale; Ferrara, Emilio; Fiumara, Giacomo; Provetti, Alessandro
2011-01-01
We describe our work in the collection and analysis of massive data describing the connections between participants to online social networks. Alternative approaches to social network data collection are defined and evaluated in practice, against the popular Facebook Web site. Thanks to our ad-hoc, privacy-compliant crawlers, two large samples, comprising millions of connections, have been collected; the data is anonymous and organized as an undirected graph. We describe a set of tools that w...
Automated Analysis of Security in Networking Systems
DEFF Research Database (Denmark)
Buchholtz, Mikael
2004-01-01
such networking systems are modelled in the process calculus LySa. On top of this programming language based formalism an analysis is developed, which relies on techniques from data and control ow analysis. These are techniques that can be fully automated, which make them an ideal basis for tools targeted at non...
Social Network Analysis and Critical Realism
DEFF Research Database (Denmark)
Buch-Hansen, Hubert
2014-01-01
in relation to established philosophies of science. This article argues that there is a tension between applied and methods-oriented SNA studies, on the one hand, and those addressing the social-theoretical nature and implications of networks, on the other. The former, in many cases, exhibits positivist...... tendencies, whereas the latter incorporate a number of assumptions that are directly compatible with core critical realist views on the nature of social reality and knowledge. This article suggests that SNA may be detached from positivist social science and come to constitute a valuable instrument...... in the critical realist toolbox....
Network Analysis in Community Psychology: Looking Back, Looking Forward
Neal, Zachary P.; Neal, Jennifer Watling
2017-01-01
Highlights Network analysis is ideally suited for community psychology research because it focuses on context. Use of network analysis in community psychology is growing. Network analysis in community psychology has employed some potentially problematic practices. Recommended practices are identified to improve network analysis in community psychology.
Stochastic analysis of epidemics on adaptive time varying networks
Kotnis, Bhushan; Kuri, Joy
2013-06-01
Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.
Brain Structure Network Analysis in Patients with Obstructive Sleep Apnea.
Directory of Open Access Journals (Sweden)
Yun-Gang Luo
Full Text Available Childhood obstructive sleep apnea (OSA is a sleeping disorder commonly affecting school-aged children and is characterized by repeated episodes of blockage of the upper airway during sleep. In this study, we performed a graph theoretical analysis on the brain morphometric correlation network in 25 OSA patients (OSA group; 5 female; mean age, 10.1 ± 1.8 years and investigated the topological alterations in global and regional properties compared with 20 healthy control individuals (CON group; 6 females; mean age, 10.4 ± 1.8 years. A structural correlation network based on regional gray matter volume was constructed respectively for each group. Our results revealed a significantly decreased mean local efficiency in the OSA group over the density range of 0.32-0.44 (p < 0.05. Regionally, the OSAs showed a tendency of decreased betweenness centrality in the left angular gyrus, and a tendency of decreased degree in the right lingual and inferior frontal (orbital part gyrus (p < 0.005, uncorrected. We also found that the network hubs in OSA and controls were distributed differently. To the best of our knowledge, this is the first study that characterizes the brain structure network in OSA patients and invests the alteration of topological properties of gray matter volume structural network. This study may help to provide new evidence for understanding the neuropathophysiology of OSA from a topological perspective.
Brain Structure Network Analysis in Patients with Obstructive Sleep Apnea.
Luo, Yun-Gang; Wang, Defeng; Liu, Kai; Weng, Jian; Guan, Yuefeng; Chan, Kate C C; Chu, Winnie C W; Shi, Lin
2015-01-01
Childhood obstructive sleep apnea (OSA) is a sleeping disorder commonly affecting school-aged children and is characterized by repeated episodes of blockage of the upper airway during sleep. In this study, we performed a graph theoretical analysis on the brain morphometric correlation network in 25 OSA patients (OSA group; 5 female; mean age, 10.1 ± 1.8 years) and investigated the topological alterations in global and regional properties compared with 20 healthy control individuals (CON group; 6 females; mean age, 10.4 ± 1.8 years). A structural correlation network based on regional gray matter volume was constructed respectively for each group. Our results revealed a significantly decreased mean local efficiency in the OSA group over the density range of 0.32-0.44 (p gyrus, and a tendency of decreased degree in the right lingual and inferior frontal (orbital part) gyrus (p < 0.005, uncorrected). We also found that the network hubs in OSA and controls were distributed differently. To the best of our knowledge, this is the first study that characterizes the brain structure network in OSA patients and invests the alteration of topological properties of gray matter volume structural network. This study may help to provide new evidence for understanding the neuropathophysiology of OSA from a topological perspective.
ANALYSIS OF A DIRECT SELLING NETWORK FOR AGRIFOOD PRODUCTS
Directory of Open Access Journals (Sweden)
Placido Rapisarda
2015-03-01
Full Text Available Sicily has become a food and wine area of great interest. However, conflicts within the supply chains have caused the selling process to become long and complex to the disadvantage of farmers, thereby leading to an information asymmetry between producers and consumers.In order to meet the new needs of the agrifood sector, we developed a theoretical model of organized direct selling that goes beyond regional boundaries, which is an alternative model to farmers’ markets and that helps to promote the creation of a network among the operators of Sicilian agrifood supply chains. The aims of this study was to verify the potential of the proposed theoretical model based on a SWOT analysis, which was achieved by collecting data from interviews with the producers involved in the Sicilian agrifood supply chains, and with the main stakeholders involved.
Analysis of blocking probability for OFDM-based variable bandwidth optical network
Gong, Lei; Zhang, Jie; Zhao, Yongli; Lin, Xuefeng; Wu, Yuyao; Gu, Wanyi
2011-12-01
Orthogonal Frequency Division Multiplexing (OFDM) has recently been proposed as a modulation technique. For optical networks, because of its good spectral efficiency, flexibility, and tolerance to impairments, optical OFDM is much more flexible compared to traditional WDM systems, enabling elastic bandwidth transmissions, and optical networking is the future trend of development. In OFDM-based optical network the research of blocking rate has very important significance for network assessment. Current research for WDM network is basically based on a fixed bandwidth, in order to accommodate the future business and the fast-changing development of optical network, our study is based on variable bandwidth OFDM-based optical networks. We apply the mathematical analysis and theoretical derivation, based on the existing theory and algorithms, research blocking probability of the variable bandwidth of optical network, and then we will build a model for blocking probability.
A network-base analysis of CMIP5 "historical" experiments
Bracco, A.; Foudalis, I.; Dovrolis, C.
2012-12-01
In computer science, "complex network analysis" refers to a set of metrics, modeling tools and algorithms commonly used in the study of complex nonlinear dynamical systems. Its main premise is that the underlying topology or network structure of a system has a strong impact on its dynamics and evolution. By allowing to investigate local and non-local statistical interaction, network analysis provides a powerful, but only marginally explored, framework to validate climate models and investigate teleconnections, assessing their strength, range, and impacts on the climate system. In this work we propose a new, fast, robust and scalable methodology to examine, quantify, and visualize climate sensitivity, while constraining general circulation models (GCMs) outputs with observations. The goal of our novel approach is to uncover relations in the climate system that are not (or not fully) captured by more traditional methodologies used in climate science and often adopted from nonlinear dynamical systems analysis, and to explain known climate phenomena in terms of the network structure or its metrics. Our methodology is based on a solid theoretical framework and employs mathematical and statistical tools, exploited only tentatively in climate research so far. Suitably adapted to the climate problem, these tools can assist in visualizing the trade-offs in representing global links and teleconnections among different data sets. Here we present the methodology, and compare network properties for different reanalysis data sets and a suite of CMIP5 coupled GCM outputs. With an extensive model intercomparison in terms of the climate network that each model leads to, we quantify how each model reproduces major teleconnections, rank model performances, and identify common or specific errors in comparing model outputs and observations.
Theoretical Aspects of Analysis of International Environmental Security
Directory of Open Access Journals (Sweden)
Juliya A. Rusakova
2015-01-01
Full Text Available Abstract: International environmental security is a very hot contemporary issue of world politics, which in a large part defines the future of our environment. Dealing with this issue is of outmost importance since its failure will render all other issues and challenges as negligible. The article examines the theoretical aspects of solving the problem of environmental security. In particular, it analyzes the problem of negative social externalities, and the related concept of "tragedy of the commons." These problems create a fundamental obstacle to the implementation of environmental security at the global level. Traditionally, the problem of externalities in the environmental field have been approached economically, states and their manufacturers were to pay for the externalities in the form of additional taxes. However, experience shows that the economic tools of dealing with environmental security are not effective. The author suggests alternative non-economic approaches: strengthening and developing the system of permanent institutions of international negotiations on environmental security and promotion of environmental awareness. Solving the acute environmental problems is impossible without a change of the political philosophy of the ruling elites in most states.
Modeling opinion dynamics: Theoretical analysis and continuous approximation
International Nuclear Information System (INIS)
Pinasco, Juan Pablo; Semeshenko, Viktoriya; Balenzuela, Pablo
2017-01-01
Highlights: • We study a simple model of persuasion dynamics with long range pairwise interactions. • The continuous limit of the master equation is a nonlinear, nonlocal, first order partial differential equation. • We compute the analytical solutions to this equation, and compare them with the simulations of the dynamics. - Abstract: Frequently we revise our first opinions after talking over with other individuals because we get convinced. Argumentation is a verbal and social process aimed at convincing. It includes conversation and persuasion and the agreement is reached because the new arguments are incorporated. Given the wide range of opinion formation mathematical approaches, there are however no models of opinion dynamics with nonlocal pair interactions analytically solvable. In this paper we present a novel analytical framework developed to solve the master equations with non-local kernels. For this we used a simple model of opinion formation where individuals tend to get more similar after each interactions, no matter their opinion differences, giving rise to nonlinear differential master equation with non-local terms. Simulation results show an excellent agreement with results obtained by the theoretical estimation.
The implementation of mindfulness in healthcare systems: a theoretical analysis.
Demarzo, M M P; Cebolla, A; Garcia-Campayo, J
2015-01-01
Evidence regarding the efficacy of mindfulness-based interventions (MBIs) is increasing exponentially; however, there are still challenges to their integration in healthcare systems. Our goal is to provide a conceptual framework that addresses these challenges in order to bring about scholarly dialog and support health managers and practitioners with the implementation of MBIs in healthcare. This is an opinative narrative review based on theoretical and empirical data that address key issues in the implementation of mindfulness in healthcare systems, such as the training of professionals, funding and costs of interventions, cost effectiveness and innovative delivery models. We show that even in the United Kingdom, where mindfulness has a high level of implementation, there is a high variability in the access to MBIs. In addition, we discuss innovative approaches based on "complex interventions," "stepped-care" and "low intensity-high volume" concepts that may prove fruitful in the development and implementation of MBIs in national healthcare systems, particularly in Primary Care. In order to better understand barriers and opportunities for mindfulness implementation in healthcare systems, it is necessary to be aware that MBIs are "complex interventions," which require innovative approaches and delivery models to implement these interventions in a cost-effective and accessible way. Copyright © 2015 Elsevier Inc. All rights reserved.
Theoretical analysis for the optical deformation of emulsion droplets.
Tapp, David; Taylor, Jonathan M; Lubansky, Alex S; Bain, Colin D; Chakrabarti, Buddhapriya
2014-02-24
We propose a theoretical framework to predict the three-dimensional shapes of optically deformed micron-sized emulsion droplets with ultra-low interfacial tension. The resulting shape and size of the droplet arises out of a balance between the interfacial tension and optical forces. Using an approximation of the laser field as a Gaussian beam, working within the Rayleigh-Gans regime and assuming isotropic surface energy at the oil-water interface, we numerically solve the resulting shape equations to elucidate the three-dimensional droplet geometry. We obtain a plethora of shapes as a function of the number of optical tweezers, their laser powers and positions, surface tension, initial droplet size and geometry. Experimentally, two-dimensional droplet silhouettes have been imaged from above, but their full side-on view has not been observed and reported for current optical configurations. This experimental limitation points to ambiguity in differentiating between droplets having the same two-dimensional projection but with disparate three-dimensional shapes. Our model elucidates and quantifies this difference for the first time. We also provide a dimensionless number that indicates the shape transformation (ellipsoidal to dumbbell) at a value ≈ 1.0, obtained by balancing interfacial tension and laser forces, substantiated using a data collapse.
Directory of Open Access Journals (Sweden)
Kim Hyun
2011-12-01
Full Text Available Abstract Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.
Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup
2011-01-01
Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.
Naive Bayesian classifiers for multinomial features: a theoretical analysis
CSIR Research Space (South Africa)
Van Dyk, E
2007-11-01
Full Text Available The authors investigate the use of naive Bayesian classifiers for multinomial feature spaces and derive error estimates for these classifiers. The error analysis is done by developing a mathematical model to estimate the probability density...
Theoretical and methodological analysis of personality theories of leadership
Оксана Григорівна Гуменюк
2016-01-01
The psychological analysis of personality theories of leadership, which is the basis for other conceptual approaches to understanding the nature of leadership, is conducted. Conceptual approach of leadership is analyzed taking into account the priority of personality theories, including: heroic, psychoanalytic, «trait» theory, charismatic and five-factor. It is noted that the psychological analysis of personality theories are important in understanding the nature of leadership
Social network analysis of study environment
Directory of Open Access Journals (Sweden)
Blaženka Divjak
2010-06-01
Full Text Available Student working environment influences student learning and achievement level. In this respect social aspects of students’ formal and non-formal learning play special role in learning environment. The main research problem of this paper is to find out if students' academic performance influences their position in different students' social networks. Further, there is a need to identify other predictors of this position. In the process of problem solving we use the Social Network Analysis (SNA that is based on the data we collected from the students at the Faculty of Organization and Informatics, University of Zagreb. There are two data samples: in the basic sample N=27 and in the extended sample N=52. We collected data on social-demographic position, academic performance, learning and motivation styles, student status (full-time/part-time, attitudes towards individual and teamwork as well as informal cooperation. Afterwards five different networks (exchange of learning materials, teamwork, informal communication, basic and aggregated social network were constructed. These networks were analyzed with different metrics and the most important were betweenness, closeness and degree centrality. The main result is, firstly, that the position in a social network cannot be forecast only by academic success and, secondly, that part-time students tend to form separate groups that are poorly connected with full-time students. In general, position of a student in social networks in study environment can influence student learning as well as her/his future employability and therefore it is worthwhile to be investigated.
Theoretical basis of quantification for layer of protection analysis (LOPA)
International Nuclear Information System (INIS)
Jin, Jianghong; Shuai, Bing; Wang, Xiaodong; Zhu, Zuogang
2016-01-01
Highlights: • When there is an IPL and λ 0 ⩾ 1, λ(t) and λ 0 don’t have logarithm linear relation any more. • The equations of scenario frequency of the low and high demand mode are different. • As long as an initiating event contributes more than 50% to the overall frequency, maximum is better than summation. • There are shared IPLs of initial events, so maximum is better than summation. • The bigger dependence degree of initial event is, the better maximum method is. - Abstract: In order to guide the corrective application of LOPA, this paper tries to discuss the theoretical basis of quantification for LOPA by comparing the computing methods of event tree consequences. It also discusses the computing equations for scenario frequency of the high demand mode by taking the scenario frequency of an initial event with one independent layer of protection (IPL) as example. Based on the probability theory, the computing method for scenario frequency of multiple initial events is improved and the application principle of two methods, i.e. summation and maximum value are brought forth. Research results show that the scenario frequency of the low demand mode has a specific computing equation. But for the high demand mode, the IPLs should be analyzed one by one, and the computing equation should be selected according to the demand mode of an IPL. As long as a single initiating event contributes more than 50% to the overall frequency of a particular consequence or the accident scenario induced by each initial event has the shared IPL, maximum value method is appropriate; otherwise, summation method should be adopted.
Accuracy Analysis of a Box-wing Theoretical SRP Model
Wang, Xiaoya; Hu, Xiaogong; Zhao, Qunhe; Guo, Rui
2016-07-01
For Beidou satellite navigation system (BDS) a high accuracy SRP model is necessary for high precise applications especially with Global BDS establishment in future. The BDS accuracy for broadcast ephemeris need be improved. So, a box-wing theoretical SRP model with fine structure and adding conical shadow factor of earth and moon were established. We verified this SRP model by the GPS Block IIF satellites. The calculation was done with the data of PRN 1, 24, 25, 27 satellites. The results show that the physical SRP model for POD and forecast for GPS IIF satellite has higher accuracy with respect to Bern empirical model. The 3D-RMS of orbit is about 20 centimeters. The POD accuracy for both models is similar but the prediction accuracy with the physical SRP model is more than doubled. We tested 1-day 3-day and 7-day orbit prediction. The longer is the prediction arc length, the more significant is the improvement. The orbit prediction accuracy with the physical SRP model for 1-day, 3-day and 7-day arc length are 0.4m, 2.0m, 10.0m respectively. But they are 0.9m, 5.5m and 30m with Bern empirical model respectively. We apply this means to the BDS and give out a SRP model for Beidou satellites. Then we test and verify the model with Beidou data of one month only for test. Initial results show the model is good but needs more data for verification and improvement. The orbit residual RMS is similar to that with our empirical force model which only estimate the force for along track, across track direction and y-bias. But the orbit overlap and SLR observation evaluation show some improvement. The remaining empirical force is reduced significantly for present Beidou constellation.
Mezher, Ahmad Mohamad; Igartua, Mónica Aguilar; de la Cruz Llopis, Luis J; Pallarès Segarra, Esteve; Tripp-Barba, Carolina; Urquiza-Aguiar, Luis; Forné, Jordi; Sanvicente Gargallo, Emilio
2015-04-17
The prevention of accidents is one of the most important goals of ad hoc networks in smart cities. When an accident happens, dynamic sensors (e.g., citizens with smart phones or tablets, smart vehicles and buses, etc.) could shoot a video clip of the accident and send it through the ad hoc network. With a video message, the level of seriousness of the accident could be much better evaluated by the authorities (e.g., health care units, police and ambulance drivers) rather than with just a simple text message. Besides, other citizens would be rapidly aware of the incident. In this way, smart dynamic sensors could participate in reporting a situation in the city using the ad hoc network so it would be possible to have a quick reaction warning citizens and emergency units. The deployment of an efficient routing protocol to manage video-warning messages in mobile Ad hoc Networks (MANETs) has important benefits by allowing a fast warning of the incident, which potentially can save lives. To contribute with this goal, we propose a multipath routing protocol to provide video-warning messages in MANETs using a novel game-theoretical approach. As a base for our work, we start from our previous work, where a 2-players game-theoretical routing protocol was proposed to provide video-streaming services over MANETs. In this article, we further generalize the analysis made for a general number of N players in the MANET. Simulations have been carried out to show the benefits of our proposal, taking into account the mobility of the nodes and the presence of interfering traffic. Finally, we also have tested our approach in a vehicular ad hoc network as an incipient start point to develop a novel proposal specifically designed for VANETs.
Directory of Open Access Journals (Sweden)
Ahmad Mohamad Mezher
2015-04-01
Full Text Available The prevention of accidents is one of the most important goals of ad hoc networks in smart cities. When an accident happens, dynamic sensors (e.g., citizens with smart phones or tablets, smart vehicles and buses, etc. could shoot a video clip of the accident and send it through the ad hoc network. With a video message, the level of seriousness of the accident could be much better evaluated by the authorities (e.g., health care units, police and ambulance drivers rather than with just a simple text message. Besides, other citizens would be rapidly aware of the incident. In this way, smart dynamic sensors could participate in reporting a situation in the city using the ad hoc network so it would be possible to have a quick reaction warning citizens and emergency units. The deployment of an efficient routing protocol to manage video-warning messages in mobile Ad hoc Networks (MANETs has important benefits by allowing a fast warning of the incident, which potentially can save lives. To contribute with this goal, we propose a multipath routing protocol to provide video-warning messages in MANETs using a novel game-theoretical approach. As a base for our work, we start from our previous work, where a 2-players game-theoretical routing protocol was proposed to provide video-streaming services over MANETs. In this article, we further generalize the analysis made for a general number of N players in the MANET. Simulations have been carried out to show the benefits of our proposal, taking into account the mobility of the nodes and the presence of interfering traffic. Finally, we also have tested our approach in a vehicular ad hoc network as an incipient start point to develop a novel proposal specifically designed for VANETs.
NAPS: Network Analysis of Protein Structures
Chakrabarty, Broto; Parekh, Nita
2016-01-01
Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue–residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein–protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/. PMID:27151201
Information flow analysis of interactome networks.
Directory of Open Access Journals (Sweden)
Patrycja Vasilyev Missiuro
2009-04-01
Full Text Available Recent studies of cellular networks have revealed modular organizations of genes and proteins. For example, in interactome networks, a module refers to a group of interacting proteins that form molecular complexes and/or biochemical pathways and together mediate a biological process. However, it is still poorly understood how biological information is transmitted between different modules. We have developed information flow analysis, a new computational approach that identifies proteins central to the transmission of biological information throughout the network. In the information flow analysis, we represent an interactome network as an electrical circuit, where interactions are modeled as resistors and proteins as interconnecting junctions. Construing the propagation of biological signals as flow of electrical current, our method calculates an information flow score for every protein. Unlike previous metrics of network centrality such as degree or betweenness that only consider topological features, our approach incorporates confidence scores of protein-protein interactions and automatically considers all possible paths in a network when evaluating the importance of each protein. We apply our method to the interactome networks of Saccharomyces cerevisiae and Caenorhabditis elegans. We find that the likelihood of observing lethality and pleiotropy when a protein is eliminated is positively correlated with the protein's information flow score. Even among proteins of low degree or low betweenness, high information scores serve as a strong predictor of loss-of-function lethality or pleiotropy. The correlation between information flow scores and phenotypes supports our hypothesis that the proteins of high information flow reside in central positions in interactome networks. We also show that the ranks of information flow scores are more consistent than that of betweenness when a large amount of noisy data is added to an interactome. Finally, we
Extracting Gene Networks for Low-Dose Radiation Using Graph Theoretical Algorithms
Energy Technology Data Exchange (ETDEWEB)
Voy, Brynn H [ORNL; Scharff, Jon [University of Tennessee, Knoxville (UTK); Perkins, Andy [University of Tennessee, Knoxville (UTK); Saxton, Arnold [University of Tennessee, Knoxville (UTK); Borate, Bhavesh [University of Tennessee, Knoxville (UTK); Chesler, Elissa J [ORNL; Branstetter, Lisa R [ORNL; Langston, Michael A [University of Tennessee, Knoxville (UTK)
2006-01-01
Genes with common functions often exhibit correlated expression levels, which can be used to identify sets of interacting genes from microarray data. Microarrays typically measure expression across genomic space, creating a massive matrix of co-expression that must be mined to extract only the most relevant gene interactions. We describe a graph theoretical approach to extracting co-expressed sets of genes, based on the computation of cliques. Unlike the results of traditional clustering algorithms, cliques are not disjoint and allow genes to be assigned to multiple sets of interacting partners, consistent with biological reality. A graph is created by thresholding the correlation matrix to include only the correlations most likely to signify functional relationships. Cliques computed from the graph correspond to sets of genes for which significant edges are present between all members of the set, representing potential members of common or interacting pathways. Clique membership can be used to infer function about poorly annotated genes, based on the known functions of better-annotated genes with which they share clique membership (i.e., ''guilt-by-association''). We illustrate our method by applying it to microarray data collected from the spleens of mice exposed to low-dose ionizing radiation. Differential analysis is used to identify sets of genes whose interactions are impacted by radiation exposure. The correlation graph is also queried independently of clique to extract edges that are impacted by radiation. We present several examples of multiple gene interactions that are altered by radiation exposure and thus represent potential molecular pathways that mediate the radiation response.
Extracting gene networks for low-dose radiation using graph theoretical algorithms.
Directory of Open Access Journals (Sweden)
Brynn H Voy
2006-07-01
Full Text Available Genes with common functions often exhibit correlated expression levels, which can be used to identify sets of interacting genes from microarray data. Microarrays typically measure expression across genomic space, creating a massive matrix of co-expression that must be mined to extract only the most relevant gene interactions. We describe a graph theoretical approach to extracting co-expressed sets of genes, based on the computation of cliques. Unlike the results of traditional clustering algorithms, cliques are not disjoint and allow genes to be assigned to multiple sets of interacting partners, consistent with biological reality. A graph is created by thresholding the correlation matrix to include only the correlations most likely to signify functional relationships. Cliques computed from the graph correspond to sets of genes for which significant edges are present between all members of the set, representing potential members of common or interacting pathways. Clique membership can be used to infer function about poorly annotated genes, based on the known functions of better-annotated genes with which they share clique membership (i.e., "guilt-by-association". We illustrate our method by applying it to microarray data collected from the spleens of mice exposed to low-dose ionizing radiation. Differential analysis is used to identify sets of genes whose interactions are impacted by radiation exposure. The correlation graph is also queried independently of clique to extract edges that are impacted by radiation. We present several examples of multiple gene interactions that are altered by radiation exposure and thus represent potential molecular pathways that mediate the radiation response.
A statistical analysis of UK financial networks
Chu, J.; Nadarajah, S.
2017-04-01
In recent years, with a growing interest in big or large datasets, there has been a rise in the application of large graphs and networks to financial big data. Much of this research has focused on the construction and analysis of the network structure of stock markets, based on the relationships between stock prices. Motivated by Boginski et al. (2005), who studied the characteristics of a network structure of the US stock market, we construct network graphs of the UK stock market using same method. We fit four distributions to the degree density of the vertices from these graphs, the Pareto I, Fréchet, lognormal, and generalised Pareto distributions, and assess the goodness of fit. Our results show that the degree density of the complements of the market graphs, constructed using a negative threshold value close to zero, can be fitted well with the Fréchet and lognormal distributions.
Handbook of Time Series Analysis Recent Theoretical Developments and Applications
Schelter, Björn; Timmer, Jens
2006-01-01
This handbook provides an up-to-date survey of current research topics and applications of time series analysis methods written by leading experts in their fields. It covers recent developments in univariate as well as bivariate and multivariate time series analysis techniques ranging from physics' to life sciences' applications. Each chapter comprises both methodological aspects and applications to real world complex systems, such as the human brain or Earth's climate. Covering an exceptionally broad spectrum of topics, beginners, experts and practitioners who seek to understand the latest de
An Optimality-Theoretic Analysis of Codas in Brazilian Portuguese
Goodin-Mayeda, C. Elizabeth
2015-01-01
Brazilian Portuguese allows only /s, N, l, r/ syllable finally, and of these, only /s/ is realized faithfully (as well as /r/ for some speakers). In order to avoid unacceptable codas, dialects of Brazilian Portuguese employ such strategies as epenthesis, nasal absorption, debucalization, and gliding. The current analysis argues that codas in…
A theoretical and experimental study of neuromorphic atomic switch networks for reservoir computing.
Sillin, Henry O; Aguilera, Renato; Shieh, Hsien-Hang; Avizienis, Audrius V; Aono, Masakazu; Stieg, Adam Z; Gimzewski, James K
2013-09-27
Atomic switch networks (ASNs) have been shown to generate network level dynamics that resemble those observed in biological neural networks. To facilitate understanding and control of these behaviors, we developed a numerical model based on the synapse-like properties of individual atomic switches and the random nature of the network wiring. We validated the model against various experimental results highlighting the possibility to functionalize the network plasticity and the differences between an atomic switch in isolation and its behaviors in a network. The effects of changing connectivity density on the nonlinear dynamics were examined as characterized by higher harmonic generation in response to AC inputs. To demonstrate their utility for computation, we subjected the simulated network to training within the framework of reservoir computing and showed initial evidence of the ASN acting as a reservoir which may be optimized for specific tasks by adjusting the input gain. The work presented represents steps in a unified approach to experimentation and theory of complex systems to make ASNs a uniquely scalable platform for neuromorphic computing.
Network Analysis of Rodent Transcriptomes in Spaceflight
Ramachandran, Maya; Fogle, Homer; Costes, Sylvain
2017-01-01
Network analysis methods leverage prior knowledge of cellular systems and the statistical and conceptual relationships between analyte measurements to determine gene connectivity. Correlation and conditional metrics are used to infer a network topology and provide a systems-level context for cellular responses. Integration across multiple experimental conditions and omics domains can reveal the regulatory mechanisms that underlie gene expression. GeneLab has assembled rich multi-omic (transcriptomics, proteomics, epigenomics, and epitranscriptomics) datasets for multiple murine tissues from the Rodent Research 1 (RR-1) experiment. RR-1 assesses the impact of 37 days of spaceflight on gene expression across a variety of tissue types, such as adrenal glands, quadriceps, gastrocnemius, tibalius anterior, extensor digitorum longus, soleus, eye, and kidney. Network analysis is particularly useful for RR-1 -omics datasets because it reinforces subtle relationships that may be overlooked in isolated analyses and subdues confounding factors. Our objective is to use network analysis to determine potential target nodes for therapeutic intervention and identify similarities with existing disease models. Multiple network algorithms are used for a higher confidence consensus.
The theoretical analysis content correctional massage for athletes with disabilities
Directory of Open Access Journals (Sweden)
Romanna Rudenko
2015-12-01
Full Text Available Purpose: to analyze the content authoring methodology of correction massage for athletes with disabilities. Material and Methods: analysis and synthesis of information for scientific, methodical and special literature; pedagogical supervision; analysis of medical cards; methods of mathematical statistics. The study involved 60 athletes with disabilities qualifications of different nosological groups. Results: of correction massage technique developed taking into account the level of physical activity, nosological group, physiological effects of massage techniques on the system. Forms of correction massage must meet the intensity of physical activity, main course and related diseases in the training cycle athletes with disabilities. Conclusions: apply total, partial, intermittent, local, segmental-reflex massage, paravertebral zones, taking into account intensity physical activity, individual tolerance for exercise
Theoretical analysis and experimental study of spray degassing method
International Nuclear Information System (INIS)
Wu Ruizhi; Shu Da; Sun Baode; Wang Jun; Li Fei; Chen Haiyan; Lu YanLing
2005-01-01
A new hydrogen-removal method of aluminum melt, spray degassing, is presented. The thermodynamic and kinetic analysis of the method are discussed. A comparison between the thermodynamics and kinetics of the spray degassing method and rotary impellor degassing method is made. The thermodynamic analysis shows that the relationship between the final hydrogen content of the aluminum melt and the ratio of purge gas flow rate to melt flow rate is linear. The result of thermodynamic calculation shows that, in spray degassing, when the ratio of G/q is larger than 2.2 x 10 -6 , the final hydrogen content will be less than 0.1 ml/100 g Al. From the kinetic analysis, the degassing effect is affected by both the size of melt droplets and the time that melt droplets move from sprayer to the bottom of the treatment tank. In numerical calculation, the hydrogen in aluminum melt can be degassed to 0.05 ml/100 g Al from 0.2 ml/100 g Al in 0.02 s with the spray degassing method. Finally, the water-model experiments are presented with the spray degassing method and rotary impellor degassing method. Melt experiments are also presented. Both the water-model experiments and the melt experiments show that the degassing effect of the spray degassing method is better than that of the rotary impeller method
Complex network analysis of state spaces for random Boolean networks
Energy Technology Data Exchange (ETDEWEB)
Shreim, Amer [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Berdahl, Andrew [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Sood, Vishal [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Grassberger, Peter [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada); Paczuski, Maya [Complexity Science Group, Department of Physics and Astronomy, University of Calgary, Calgary, AB, T2N 1N4 (Canada)
2008-01-15
We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains N Boolean elements each with K inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of these SSNs at both local and global scales, as well as sample to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity (Shreim A et al 2007 Phys. Rev. Lett. 98 198701) of an SSN as a global topological measure. RBNs with 2 {<=} K {<=} 5 exhibit non-trivial fluctuations at both local and global scales, while K = 2 exhibits the largest sample-to-sample (possibly non-self-averaging) fluctuations. We interpret the observed 'multi scale' fluctuations in the SSNs as indicative of the criticality and complexity of K = 2 RBNs. 'Garden of Eden' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for K > 1 SSNs can assume any integer value between 0 and 2{sup N}, for K = 1 all the non-GoE nodes in a given SSN have the same in-degree which is always a power of two.
Complex network analysis of state spaces for random Boolean networks
International Nuclear Information System (INIS)
Shreim, Amer; Berdahl, Andrew; Sood, Vishal; Grassberger, Peter; Paczuski, Maya
2008-01-01
We apply complex network analysis to the state spaces of random Boolean networks (RBNs). An RBN contains N Boolean elements each with K inputs. A directed state space network (SSN) is constructed by linking each dynamical state, represented as a node, to its temporal successor. We study the heterogeneity of these SSNs at both local and global scales, as well as sample to-sample fluctuations within an ensemble of SSNs. We use in-degrees of nodes as a local topological measure, and the path diversity (Shreim A et al 2007 Phys. Rev. Lett. 98 198701) of an SSN as a global topological measure. RBNs with 2 ≤ K ≤ 5 exhibit non-trivial fluctuations at both local and global scales, while K = 2 exhibits the largest sample-to-sample (possibly non-self-averaging) fluctuations. We interpret the observed 'multi scale' fluctuations in the SSNs as indicative of the criticality and complexity of K = 2 RBNs. 'Garden of Eden' (GoE) states are nodes on an SSN that have in-degree zero. While in-degrees of non-GoE nodes for K > 1 SSNs can assume any integer value between 0 and 2 N , for K = 1 all the non-GoE nodes in a given SSN have the same in-degree which is always a power of two
DEFF Research Database (Denmark)
Sindbæk, Søren Michael
2015-01-01
preserve patterns of thisinteraction. Formal network analysis and modelling holds the potential to identify anddemonstrate such patterns, where traditional methods often prove inadequate. Thearchaeological study of communication networks in the past, however, calls for radically different analytical...... this is not a problem of network analysis, but network synthesis: theclassic problem of cracking codes or reconstructing black-box circuits. It is proposedthat archaeological approaches to network synthesis must involve a contextualreading of network data: observations arising from individual contexts, morphologies...
A Game Theoretic Approach for Modeling Privacy Settings of an Online Social Network
Directory of Open Access Journals (Sweden)
Jundong Chen
2014-05-01
Full Text Available Users of online social networks often adjust their privacy settings to control how much information on their profiles is accessible to other users of the networks. While a variety of factors have been shown to affect the privacy strategies of these users, very little work has been done in analyzing how these factors influence each other and collectively contribute towards the users’ privacy strategies. In this paper, we analyze the influence of attribute importance, benefit, risk and network topology on the users’ attribute disclosure behavior by introducing a weighted evolutionary game model. Results show that: irrespective of risk, users aremore likely to reveal theirmost important attributes than their least important attributes; when the users’ range of influence is increased, the risk factor plays a smaller role in attribute disclosure; the network topology exhibits a considerable effect on the privacy in an environment with risk.
2017-08-01
platform for agent- based electric power and communication simulation built from commercial off-the-shelf components,” Power Systems, IEEE Transactions on... communication recovery. With the increasing attention on the national infrastructure, such as civilian and military telecommunication networks, power...grids, and transportation systems, these large-scale, inter-connected networks are vulnerable to WMD attacks. Under such attacks on communication
DEFF Research Database (Denmark)
Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa
The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....
General-Purpose Computation with Neural Networks: A Survey of Complexity Theoretic Results
Czech Academy of Sciences Publication Activity Database
Šíma, Jiří; Orponen, P.
2003-01-01
Roč. 15, č. 12 (2003), s. 2727-2778 ISSN 0899-7667 R&D Projects: GA AV ČR IAB2030007; GA ČR GA201/02/1456 Institutional research plan: AV0Z1030915 Keywords : computational power * computational complexity * perceptrons * radial basis functions * spiking neurons * feedforward networks * reccurent networks * probabilistic computation * analog computation Subject RIV: BA - General Mathematics Impact factor: 2.747, year: 2003
The interplay between social networks and culture: theoretically and among whales and dolphins
Cantor, Mauricio; Whitehead, Hal
2013-01-01
Culture is increasingly being understood as a driver of mammalian phenotypes. Defined as group-specific behaviour transmitted by social learning, culture is shaped by social structure. However, culture can itself affect social structure if individuals preferentially interact with others whose behaviour is similar, or cultural symbols are used to mark groups. Using network formalism, this interplay can be depicted by the coevolution of nodes and edges together with the coevolution of network t...
2016-12-22
for the global pattern. A network view has proven useful in modeling a supply - chain for patterns of interaction. Queuing theory can be used to...phenomena. Second, operations management and supply - chain management lack metrics for evolution and dynamism in supply networks. Third, developing...robust theories in the presence of 14 adaptation is a formidable task. Supply - chain management theory can be built by identifying CAS phenomena and
Nonstationary Hydrological Frequency Analysis: Theoretical Methods and Application Challenges
Xiong, L.
2014-12-01
Because of its great implications in the design and operation of hydraulic structures under changing environments (either climate change or anthropogenic changes), nonstationary hydrological frequency analysis has become so important and essential. Two important achievements have been made in methods. Without adhering to the consistency assumption in the traditional hydrological frequency analysis, the time-varying probability distribution of any hydrological variable can be established by linking the distribution parameters to some covariates such as time or physical variables with the help of some powerful tools like the Generalized Additive Model of Location, Scale and Shape (GAMLSS). With the help of copulas, the multivariate nonstationary hydrological frequency analysis has also become feasible. However, applications of the nonstationary hydrological frequency formula to the design and operation of hydraulic structures for coping with the impacts of changing environments in practice is still faced with many challenges. First, the nonstationary hydrological frequency formulae with time as covariate could only be extrapolated for a very short time period beyond the latest observation time, because such kind of formulae is not physically constrained and the extrapolated outcomes could be unrealistic. There are two physically reasonable methods that can be used for changing environments, one is to directly link the quantiles or the distribution parameters to some measureable physical factors, and the other is to use the derived probability distributions based on hydrological processes. However, both methods are with a certain degree of uncertainty. For the design and operation of hydraulic structures under changing environments, it is recommended that design results of both stationary and nonstationary methods be presented together and compared with each other, to help us understand the potential risks of each method.
A theoretical analysis of the median LMF adaptive algorithm
DEFF Research Database (Denmark)
Bysted, Tommy Kristensen; Rusu, C.
1999-01-01
Higher order adaptive algorithms are sensitive to impulse interference. In the case of the LMF (Least Mean Fourth), an easy and effective way to reduce this is to median filter the instantaneous gradient of the LMF algorithm. Although previous published simulations have indicated that this reduces...... the speed of convergence, no analytical studies have yet been made to prove this. In order to enhance the usability, this paper presents a convergence and steady-state analysis of the median LMF adaptive algorithm. As expected this proves that the median LMF has a slower convergence and a lower steady...
Theoretical concepts of X-ray nanoscale analysis theory and applications
Benediktovitch, Andrei; Ulyanenkov, Alexander
2013-01-01
This book provides a concise survey of modern theoretical concepts of X-ray materials analysis. The principle features of the book are: basics of X-ray scattering, interaction between X-rays and matter and new theoretical concepts of X-ray scattering. The various X-ray techniques are considered in detail: high-resolution X-ray diffraction, X-ray reflectivity, grazing-incidence small-angle X-ray scattering and X-ray residual stress analysis. All the theoretical methods presented use the unified physical approach. This makes the book especially useful for readers learning and performing data ana
A Game-Theoretic Response Strategy for Coordinator Attack in Wireless Sensor Networks
Liu, Jianhua; Yue, Guangxue; Shang, Huiliang; Li, Hongjie
2014-01-01
The coordinator is a specific node that controls the whole network and has a significant impact on the performance in cooperative multihop ZigBee wireless sensor networks (ZWSNs). However, the malicious node attacks coordinator nodes in an effort to waste the resources and disrupt the operation of the network. Attacking leads to a failure of one round of communication between the source nodes and destination nodes. Coordinator selection is a technique that can considerably defend against attack and reduce the data delivery delay, and increase network performance of cooperative communications. In this paper, we propose an adaptive coordinator selection algorithm using game and fuzzy logic aiming at both minimizing the average number of hops and maximizing network lifetime. The proposed game model consists of two interrelated formulations: a stochastic game for dynamic defense and a best response policy using evolutionary game formulation for coordinator selection. The stable equilibrium best policy to response defense is obtained from this game model. It is shown that the proposed scheme can improve reliability and save energy during the network lifetime with respect to security. PMID:25105171
Theoretical seismic analysis of butterfly valve for nuclear power plant
International Nuclear Information System (INIS)
Han, Sang Uk; Ahn, Jun Tae; Han, Seung Ho; Lee, Kyung Chul
2012-01-01
Valves are one of the most important components of a pipeline system in a nuclear power plant, and it is important to ensure their structural safety under seismic loads. A crucial aspect of structural safety verification is the seismic qualification, and therefore, an optimal shape design and experimental seismic qualification is necessary in case the configuration of the valve parts needs to be modified and their performance needs to be improved. Recently, intensive numerical analyses have been preformed before the experimental verification in order to determine the appropriate design variables that satisfy the performance requirements under seismic loads. In this study, static and dynamic numerical structural analyses of a 200A butterfly valve for a nuclear power plant were performed according to the KEPIC MFA. The result of static analysis considering an equivalent static load under SSE condition gave an applied stress of 135MPa. In addition, the result of dynamic analysis gave an applied stress of 183MPa, where the CQC method using response spectrums was taken into account. These values are under the allowable strength of the materials used for manufacturing the butterfly valve, and therefore, its structural safety satisfies the requirements of KEPIC MFA
Theoretical seismic analysis of butterfly valve for nuclear power plant
Energy Technology Data Exchange (ETDEWEB)
Han, Sang Uk; Ahn, Jun Tae; Han, Seung Ho [Donga Univ., Busan (Korea, Republic of); Lee, Kyung Chul [Dukwon Valve Co., Ltd., Busan (Korea, Republic of)
2012-09-15
Valves are one of the most important components of a pipeline system in a nuclear power plant, and it is important to ensure their structural safety under seismic loads. A crucial aspect of structural safety verification is the seismic qualification, and therefore, an optimal shape design and experimental seismic qualification is necessary in case the configuration of the valve parts needs to be modified and their performance needs to be improved. Recently, intensive numerical analyses have been preformed before the experimental verification in order to determine the appropriate design variables that satisfy the performance requirements under seismic loads. In this study, static and dynamic numerical structural analyses of a 200A butterfly valve for a nuclear power plant were performed according to the KEPIC MFA. The result of static analysis considering an equivalent static load under SSE condition gave an applied stress of 135MPa. In addition, the result of dynamic analysis gave an applied stress of 183MPa, where the CQC method using response spectrums was taken into account. These values are under the allowable strength of the materials used for manufacturing the butterfly valve, and therefore, its structural safety satisfies the requirements of KEPIC MFA.
Vulnerability analysis methods for road networks
Bíl, Michal; Vodák, Rostislav; Kubeček, Jan; Rebok, Tomáš; Svoboda, Tomáš
2014-05-01
Road networks rank among the most important lifelines of modern society. They can be damaged by either random or intentional events. Roads are also often affected by natural hazards, the impacts of which are both direct and indirect. Whereas direct impacts (e.g. roads damaged by a landslide or due to flooding) are localized in close proximity to the natural hazard occurrence, the indirect impacts can entail widespread service disabilities and considerable travel delays. The change in flows in the network may affect the population living far from the places originally impacted by the natural disaster. These effects are primarily possible due to the intrinsic nature of this system. The consequences and extent of the indirect costs also depend on the set of road links which were damaged, because the road links differ in terms of their importance. The more robust (interconnected) the road network is, the less time is usually needed to secure the serviceability of an area hit by a disaster. These kinds of networks also demonstrate a higher degree of resilience. Evaluating road network structures is therefore essential in any type of vulnerability and resilience analysis. There are a range of approaches used for evaluation of the vulnerability of a network and for identification of the weakest road links. Only few of them are, however, capable of simulating the impacts of the simultaneous closure of numerous links, which often occurs during a disaster. The primary problem is that in the case of a disaster, which usually has a large regional extent, the road network may remain disconnected. The majority of the commonly used indices use direct computation of the shortest paths or time between OD (origin - destination) pairs and therefore cannot be applied when the network breaks up into two or more components. Since extensive break-ups often occur in cases of major disasters, it is important to study the network vulnerability in these cases as well, so that appropriate
Diversity Performance Analysis on Multiple HAP Networks
Dong, Feihong; Li, Min; Gong, Xiangwu; Li, Hongjun; Gao, Fengyue
2015-01-01
One of the main design challenges in wireless sensor networks (WSNs) is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP) is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO) techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO) model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV). In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF) and cumulative distribution function (CDF) of the received signal-to-noise ratio (SNR) are derived. In addition, the average symbol error rate (ASER) with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI) and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques. PMID:26134102
Diversity Performance Analysis on Multiple HAP Networks
Directory of Open Access Journals (Sweden)
Feihong Dong
2015-06-01
Full Text Available One of the main design challenges in wireless sensor networks (WSNs is achieving a high-data-rate transmission for individual sensor devices. The high altitude platform (HAP is an important communication relay platform for WSNs and next-generation wireless networks. Multiple-input multiple-output (MIMO techniques provide the diversity and multiplexing gain, which can improve the network performance effectively. In this paper, a virtual MIMO (V-MIMO model is proposed by networking multiple HAPs with the concept of multiple assets in view (MAV. In a shadowed Rician fading channel, the diversity performance is investigated. The probability density function (PDF and cumulative distribution function (CDF of the received signal-to-noise ratio (SNR are derived. In addition, the average symbol error rate (ASER with BPSK and QPSK is given for the V-MIMO model. The system capacity is studied for both perfect channel state information (CSI and unknown CSI individually. The ergodic capacity with various SNR and Rician factors for different network configurations is also analyzed. The simulation results validate the effectiveness of the performance analysis. It is shown that the performance of the HAPs network in WSNs can be significantly improved by utilizing the MAV to achieve overlapping coverage, with the help of the V-MIMO techniques.
Mixed Methods Analysis of Enterprise Social Networks
DEFF Research Database (Denmark)
Behrendt, Sebastian; Richter, Alexander; Trier, Matthias
2014-01-01
The increasing use of enterprise social networks (ESN) generates vast amounts of data, giving researchers and managerial decision makers unprecedented opportunities for analysis. However, more transparency about the available data dimensions and how these can be combined is needed to yield accurate...
Nonlinear Time Series Analysis via Neural Networks
Volná, Eva; Janošek, Michal; Kocian, Václav; Kotyrba, Martin
This article deals with a time series analysis based on neural networks in order to make an effective forex market [Moore and Roche, J. Int. Econ. 58, 387-411 (2002)] pattern recognition. Our goal is to find and recognize important patterns which repeatedly appear in the market history to adapt our trading system behaviour based on them.
Signal correlations in biomass combustion. An information theoretic analysis
Energy Technology Data Exchange (ETDEWEB)
Ruusunen, M.
2013-09-01
Increasing environmental and economic awareness are driving the development of combustion technologies to efficient biomass use and clean burning. To accomplish these goals, quantitative information about combustion variables is needed. However, for small-scale combustion units the existing monitoring methods are often expensive or complex. This study aimed to quantify correlations between flue gas temperatures and combustion variables, namely typical emission components, heat output, and efficiency. For this, data acquired from four small-scale combustion units and a large circulating fluidised bed boiler was studied. The fuel range varied from wood logs, wood chips, and wood pellets to biomass residue. Original signals and a defined set of their mathematical transformations were applied to data analysis. In order to evaluate the strength of the correlations, a multivariate distance measure based on information theory was derived. The analysis further assessed time-varying signal correlations and relative time delays. Ranking of the analysis results was based on the distance measure. The uniformity of the correlations in the different data sets was studied by comparing the 10-quantiles of the measured signal. The method was validated with two benchmark data sets. The flue gas temperatures and the combustion variables measured carried similar information. The strongest correlations were mainly linear with the transformed signal combinations and explicable by the combustion theory. Remarkably, the results showed uniformity of the correlations across the data sets with several signal transformations. This was also indicated by simulations using a linear model with constant structure to monitor carbon dioxide in flue gas. Acceptable performance was observed according to three validation criteria used to quantify modelling error in each data set. In general, the findings demonstrate that the presented signal transformations enable real-time approximation of the studied
Theoretical analysis of steady state operating forces in control valves
Directory of Open Access Journals (Sweden)
Basavaraj Hubballi
2018-01-01
Full Text Available The controlling components, such as valves are used to regulate controlled fluid power. It is not always possible to calculate valve forces accurately, and with some types of valves even the existence of certain types of forces cannot be predicted with certainty. In many cases, however, the analysis can be made fairly completely and accurately. The assumption of steady state conditions is valid for the valve alone, but transient effects in the rest of the system may be large. These effects are particularly important with regard to the instability of valves, where the system may react on the valve in such a way as to make it squeal or oscillate, sometimes with large amplitude. The origin of the steady state flow force understood from a brief qualitative explanation. The following paper will summarize much of what is known about valve forces in the spool type controlling element.
Environmental accounting in Spain: structured review process and theoretical analysis
Directory of Open Access Journals (Sweden)
Fabricia Silva da Rosa
2012-12-01
Full Text Available One way to perceive and understand the level of development of environmental accounting is to study the main features of its publications. Thus, the purpose of this paper is to identify and analyze the profile of Spanish publications in accounting journals. To this end, 15 journals were selected and analyzed 74 articles in the period 2001 to 2010. The results show that the peak years of publication are 2001, 2003 and 2006, and authors with more articles in the sample are Moneva Abadía, Larrinaga González, Fernández Cuesta and Archel Domench. In terms of methodology, the works of review, case studies and content analysis, addressing standardization issues, fundamentals of environmental accounting, environmental sustainability indicators and reporting.
Reliability Analysis Techniques for Communication Networks in Nuclear Power Plant
International Nuclear Information System (INIS)
Lim, T. J.; Jang, S. C.; Kang, H. G.; Kim, M. C.; Eom, H. S.; Lee, H. J.
2006-09-01
The objectives of this project is to investigate and study existing reliability analysis techniques for communication networks in order to develop reliability analysis models for nuclear power plant's safety-critical networks. It is necessary to make a comprehensive survey of current methodologies for communication network reliability. Major outputs of this study are design characteristics of safety-critical communication networks, efficient algorithms for quantifying reliability of communication networks, and preliminary models for assessing reliability of safety-critical communication networks
Time series analysis of temporal networks
Sikdar, Sandipan; Ganguly, Niloy; Mukherjee, Animesh
2016-01-01
A common but an important feature of all real-world networks is that they are temporal in nature, i.e., the network structure changes over time. Due to this dynamic nature, it becomes difficult to propose suitable growth models that can explain the various important characteristic properties of these networks. In fact, in many application oriented studies only knowing these properties is sufficient. For instance, if one wishes to launch a targeted attack on a network, this can be done even without the knowledge of the full network structure; rather an estimate of some of the properties is sufficient enough to launch the attack. We, in this paper show that even if the network structure at a future time point is not available one can still manage to estimate its properties. We propose a novel method to map a temporal network to a set of time series instances, analyze them and using a standard forecast model of time series, try to predict the properties of a temporal network at a later time instance. To our aim, we consider eight properties such as number of active nodes, average degree, clustering coefficient etc. and apply our prediction framework on them. We mainly focus on the temporal network of human face-to-face contacts and observe that it represents a stochastic process with memory that can be modeled as Auto-Regressive-Integrated-Moving-Average (ARIMA). We use cross validation techniques to find the percentage accuracy of our predictions. An important observation is that the frequency domain properties of the time series obtained from spectrogram analysis could be used to refine the prediction framework by identifying beforehand the cases where the error in prediction is likely to be high. This leads to an improvement of 7.96% (for error level ≤20%) in prediction accuracy on an average across all datasets. As an application we show how such prediction scheme can be used to launch targeted attacks on temporal networks. Contribution to the Topical Issue
Network analysis for the visualization and analysis of qualitative data.
Pokorny, Jennifer J; Norman, Alex; Zanesco, Anthony P; Bauer-Wu, Susan; Sahdra, Baljinder K; Saron, Clifford D
2018-03-01
We present a novel manner in which to visualize the coding of qualitative data that enables representation and analysis of connections between codes using graph theory and network analysis. Network graphs are created from codes applied to a transcript or audio file using the code names and their chronological location. The resulting network is a representation of the coding data that characterizes the interrelations of codes. This approach enables quantification of qualitative codes using network analysis and facilitates examination of associations of network indices with other quantitative variables using common statistical procedures. Here, as a proof of concept, we applied this method to a set of interview transcripts that had been coded in 2 different ways and the resultant network graphs were examined. The creation of network graphs allows researchers an opportunity to view and share their qualitative data in an innovative way that may provide new insights and enhance transparency of the analytical process by which they reach their conclusions. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Capacity analysis of wireless mesh networks | Gumel | Nigerian ...
African Journals Online (AJOL)
... number of nodes (n) in a linear topology. The degradation is found to be higher in a fully mesh network as a result of increase in interference and MAC layer contention in the network. Key words: Wireless mesh network (WMN), Adhoc network, Network capacity analysis, Bottleneck collision domain, Medium access control ...
Theoretical analysis of the flow around a Savonius rotor
Energy Technology Data Exchange (ETDEWEB)
Aouachria, Z.; Djoumati, D. [Batna Univ., Batna (Algeria). Laboratoire de Physique Energetique Appliquee; Djamel, H. [Batna Univ., Batna (Algeria). Dept. de Mecanique Energetique
2009-07-01
While Savonius rotors do not perform as well as Darrieus wind turbine rotors, Savonius rotors work in all wind directions, do not require a rudder, and are capable of operating at relatively low speeds. A discrete vortex method was used to analyze the complex flow around a Savonius rotor. Velocity and pressure fields obtained in the analysis were used to determine both mechanical and energetic rotor performance. Savonius rotor bi-blades were considered in relation to 4 free eddies, the leakage points of each blade, and the distribution of basic eddies along the blades. Each blade was divided into equal elementary arcs. Linear equations and Kelvin theorem were reduced to a single equation. Results showed good agreement with data obtained in previous experimental studies. The study demonstrated that vortice emissions were unbalanced. The resistant blade had 2 vortice emissions, while the driving blade had only a single vortex. The results of the study will be used to clarify the mechanical and aerodynamic functions as well as to determine the different values between the blades and the speed of the turbine's engine. 9 refs., 4 figs.
Percolation-theoretic bounds on the cache size of nodes in mobile opportunistic networks.
Yuan, Peiyan; Wu, Honghai; Zhao, Xiaoyan; Dong, Zhengnan
2017-07-18
The node buffer size has a large influence on the performance of Mobile Opportunistic Networks (MONs). This is mainly because each node should temporarily cache packets to deal with the intermittently connected links. In this paper, we study fundamental bounds on node buffer size below which the network system can not achieve the expected performance such as the transmission delay and packet delivery ratio. Given the condition that each link has the same probability p to be active in the next time slot when the link is inactive and q to be inactive when the link is active, there exists a critical value p c from a percolation perspective. If p > p c , the network is in the supercritical case, where we found that there is an achievable upper bound on the buffer size of nodes, independent of the inactive probability q. When p network is in the subcritical case, and there exists a closed-form solution for buffer occupation, which is independent of the size of the network.
Capacity analysis of vehicular communication networks
Lu, Ning
2013-01-01
This SpringerBrief focuses on the network capacity analysis of VANETs, a key topic as fundamental guidance on design and deployment of VANETs is very limited. Moreover, unique characteristics of VANETs impose distinguished challenges on such an investigation. This SpringerBrief first introduces capacity scaling laws for wireless networks and briefly reviews the prior arts in deriving the capacity of VANETs. It then studies the unicast capacity considering the socialized mobility model of VANETs. With vehicles communicating based on a two-hop relaying scheme, the unicast capacity bound is deriv
Economy As A Phenomenon Of Culture: Theoretical And Methodological Analysis
Directory of Open Access Journals (Sweden)
S. N. Ivaskovsky
2017-01-01
Full Text Available The article redefines economy as a phenomenon of culture, a product of a historically and socially grounded set of values shared by members of a given society. The research shows that culture is not always identical to social utility, because there are multiple examples when archaic, traditionalist, irrational cultural norms hinder social and economic progress and trap nations into poverty and underdevelopment. One of the reasons for the lack of scholarly attention to cultural dimension of economy is the triumph of positivism in economics. Mathematics has become the dominant language of economic analysis. It leads to the transformation of the economics into a sort of «social physics», accompanied by the loss of its original humanitarian nature shared in the works of all the great economists of the past. The author emphasizes the importance of the interdisciplinary approach to the economic research and the incorporation of the achievements of the other social disciplines – history, philosophy, sociology and cultural studies - into the subject matter of economic theory. Substantiating the main thesis of the article, the author shows that there is a profound ontological bond between economy and culture, which primarily consists in the fact that these spheres of human relations are aimed at the solution of the same problem – the competitive selection of the best ways for survival of people, of satisfying the relevant living needs. In order to overcome the difficulties related to the inclusion of culture in the set of analytical tools used in the economic theory, the author suggests using a category of «cultural capital», which reestablishes the earlier and more familiar for the economists meaning of capital.
Dynamic analysis of stochastic bidirectional associative memory neural networks with delays
International Nuclear Information System (INIS)
Zhao Hongyong; Ding Nan
2007-01-01
In this paper, stochastic bidirectional associative memory neural networks model with delays is considered. By constructing Lyapunov functionals, and using stochastic analysis method and inequality technique, we give some sufficient criteria ensuring almost sure exponential stability, pth exponential stability and mean value exponential stability. The obtained criteria can be used as theoretic guidance to stabilize neural networks in practical applications when stochastic noise is taken into consideration
Bistability Analysis of Excitatory-Inhibitory Neural Networks in Limited-Sustained-Activity Regime
International Nuclear Information System (INIS)
Ni Yun; Wu Liang; Wu Dan; Zhu Shiqun
2011-01-01
Bistable behavior of neuronal complex networks is investigated in the limited-sustained-activity regime when the network is composed of excitatory and inhibitory neurons. The standard stability analysis is performed on the two metastable states separately. Both theoretical analysis and numerical simulations show consistently that the difference between time scales of excitatory and inhibitory populations can influence the dynamical behaviors of the neuronal networks dramatically, leading to the transition from bistable behaviors with memory effects to the collapse of bistable behaviors. These results may suggest one possible neuronal information processing by only tuning time scales. (interdisciplinary physics and related areas of science and technology)
Intentional risk management through complex networks analysis
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...
Delgado, JFR; Dalenoort, GJ; Gracia, AP
2000-01-01
For the study of psychological processes in cognitive science modelling two general approaches rule nowadays research: Artificial Intelligence (top-down) functional symbolic models, and Connectionist (bottom-up) neural networks modelling. Our goal in this paper is to show that analyzing the
Delgado, JFR; Dalenoort, GJ; Pitarque Gracia, A
2000-01-01
For the study of psychological processes in cognitive science modelling two general approaches rule nowadays research: Artificial Intelligence (top-down) functional symbolic models, and Connectionist (bottom-up) neural networks modelling. Our goal in this paper is to show that analyzing the
DEFF Research Database (Denmark)
Dey, Ramendra Sundar; Hjuler, Hans Aage; Chi, Qijin
2015-01-01
We report a facile and low-cost approach for the preparation of all-in-one supercapacitor electrodes using copper foam (CuF) integrated three-dimensional (3D) reduced graphene oxide (rGO) networks. The binderfree 3DrGO@CuF electrodes are capable of delivering high specific capacitance approaching...
The interplay between social networks and culture: theoretically and among whales and dolphins.
Cantor, Mauricio; Whitehead, Hal
2013-05-19
Culture is increasingly being understood as a driver of mammalian phenotypes. Defined as group-specific behaviour transmitted by social learning, culture is shaped by social structure. However, culture can itself affect social structure if individuals preferentially interact with others whose behaviour is similar, or cultural symbols are used to mark groups. Using network formalism, this interplay can be depicted by the coevolution of nodes and edges together with the coevolution of network topology and transmission patterns. We review attempts to model the links between the spread, persistence and diversity of culture and the network topology of non-human societies. We illustrate these processes using cetaceans. The spread of socially learned begging behaviour within a population of bottlenose dolphins followed the topology of the social network, as did the evolution of the song of the humpback whale between breeding areas. In three bottlenose dolphin populations, individuals preferentially associated with animals using the same socially learned foraging behaviour. Homogeneous behaviour within the tight, nearly permanent social structures of the large matrilineal whales seems to result from transmission bias, with cultural symbols marking social structures. We recommend the integration of studies of culture and society in species for which social learning is an important determinant of behaviour.
Studying Pensions Funds Through an Infinite Servers Nodes Network: A Theoretical Problem
International Nuclear Information System (INIS)
Ferreira, M A M; Andrade, M; Filipe, J A
2012-01-01
This study intends to present a representation of a pensions fund through a stochastic network with two infinite servers nodes. With this representation it is allowed to deduce an equilibrium condition of the system with basis on the identity of the random rates expected values, for which the contributions arrive to the fund and the pensions are paid by the fund. In our study a stochastic network is constructed where traffic is represented. This network allows to study the equilibrium in the system and it is admissible to get a balance to a pensions fund. A specific case is studied. When the arrivals from outside at nodes A and B are according to a Poisson process, with rates λ A and λ B , respectively, the system may be seen as a two nodes network where the first node is a M/G/∞ queue and second a M t /G/∞ queue. For this case in the long term the conditions of equilibrium are as follows: m A λ A α A = m B (ρλ A + λ B )α B . In this formula it is established a relationship among the two nodes. Several examples are given in the study.
A Game Theoretic Framework for Bandwidth Allocation and Pricing in Federated Wireless Networks
Gu, Bo; Yamori, Kyoko; Xu, Sugang; Tanaka, Yoshiaki
With the proliferation of IEEE 802.11 wireless local area networks, large numbers of wireless access points have been deployed, and it is often the case that a user can detect several access points simultaneously in dense metropolitan areas. Most owners, however, encrypt their networks to prevent the public from accessing them due to the increased traffic and security risk. In this work, we use pricing as an incentive mechanism to motivate the owners to share their networks with the public, while at the same time satisfying users' service demand. Specifically, we propose a “federated network” concept, in which radio resources of various wireless local area networks are managed together. Our algorithm identifies two candidate access points with the lowest price being offered (if available) to each user. We then model the price announcements of access points as a game, and characterize the Nash Equilibrium of the system. The efficiency of the Nash Equilibrium solution is evaluated via simulation studies as well.
Pursuit of Excellence in a Networked Society. : Theoretical and Practical Approaches.
J. J.J.M. Volker; Dr. Marca Wolfensberger; Drs. L. Drayer
2014-01-01
Pursuit of Excellence in a Networked Society gives an overview of research and practice, describing and exploring efforts toward continuous improvement in programming to promote excellence. The talent development of students and teachers is a hot topic in today’s knowledge-based society which
A Network Thermodynamic Approach to Compartmental Analysis
Mikulecky, D. C.; Huf, E. G.; Thomas, S. R.
1979-01-01
We introduce a general network thermodynamic method for compartmental analysis which uses a compartmental model of sodium flows through frog skin as an illustrative example (Huf and Howell, 1974a). We use network thermodynamics (Mikulecky et al., 1977b) to formulate the problem, and a circuit simulation program (ASTEC 2, SPICE2, or PCAP) for computation. In this way, the compartment concentrations and net fluxes between compartments are readily obtained for a set of experimental conditions involving a square-wave pulse of labeled sodium at the outer surface of the skin. Qualitative features of the influx at the outer surface correlate very well with those observed for the short circuit current under another similar set of conditions by Morel and LeBlanc (1975). In related work, the compartmental model is used as a basis for simulation of the short circuit current and sodium flows simultaneously using a two-port network (Mikulecky et al., 1977a, and Mikulecky et al., A network thermodynamic model for short circuit current transients in frog skin. Manuscript in preparation; Gary-Bobo et al., 1978). The network approach lends itself to computation of classic compartmental problems in a simple manner using circuit simulation programs (Chua and Lin, 1975), and it further extends the compartmental models to more complicated situations involving coupled flows and non-linearities such as concentration dependencies, chemical reaction kinetics, etc. PMID:262387
Li, Lin; Deng, Pengcheng; Liu, Jiuzhou; Li, Chao
2018-03-01
The paper deals with the vibration suppression of a bladed disk with a piezoelectric network. The piezoelectric network has a different period (so called bi-period) from that of the bladed disk and there is no inductor in it. The system is simulated by an electromechanical lumped parameter model with two DOFs per sector. The research focuses on suppressing the amplitude magnification or reducing the vibration localization of the mistuned bladed disk. The dynamic equations of the system are derived. Both mechanical mistuning and electrical mistuning have been taken into account. The Modified Modal Assurance Criterion (MMAC) is used to evaluate the vibration suppression ability of the bi-periodic piezoelectric network. The Monte Carlo simulation is used to calculate the MMAC of the system with the random mistuning. As a reference, the forced responses of the bladed disk with and without the piezoelectric network are given. The results show that the piezoelectric network would effectively suppress amplitude magnification induced by mistuning. The vibration amplitude is even smaller than that of the tuned system. The robustness analysis shows that the bi-periodic piezoelectric network can provide a reliable assurance for avoiding the forced response amplification of the mistuned bladed disk. The amplified response induced by the mechanical mistuning with standard deviation 0.2 can be effectively suppressed through the bi-periodic piezoelectric network.
da Silva, Jorge Alberto Valle; Modesto-Costa, Lucas; de Koning, Martijn C.; Borges, Itamar; França, Tanos Celmar Costa
2018-01-01
In this work, quaternary and non-quaternary oximes designed to bind at the peripheral site of acetylcholinesterase previously inhibited by organophosphates were investigated theoretically. Some of those oximes have a large number of degrees of freedom, thus requiring an accurate method to obtain molecular geometries. For this reason, the density functional theory (DFT) was employed to refine their molecular geometries after conformational analysis and to compare their 1H and 13C nuclear magnetic resonance (NMR) theoretical signals in gas-phase and in solvent. A good agreement with experimental data was achieved and the same theoretical approach was employed to obtain the geometries in water environment for further studies.
Safeguards Network Analysis Procedure (SNAP): overview
International Nuclear Information System (INIS)
Chapman, L.D; Engi, D.
1979-08-01
Nuclear safeguards systems provide physical protection and control of nuclear materials. The Safeguards Network Analysis Procedure (SNAP) provides a convenient and standard analysis methodology for the evaluation of physical protection system effectiveness. This is achieved through a standard set of symbols which characterize the various elements of safeguards systems and an analysis program to execute simulation models built using the SNAP symbology. The outputs provided by the SNAP simulation program supplements the safeguards analyst's evaluative capabilities and supports the evaluation of existing sites as well as alternative design possibilities. This paper describes the SNAP modeling technique and provides an example illustrating its use
Improved asymptotic stability analysis for uncertain delayed state neural networks
International Nuclear Information System (INIS)
Souza, Fernando O.; Palhares, Reinaldo M.; Ekel, Petr Ya.
2009-01-01
This paper presents a new linear matrix inequality (LMI) based approach to the stability analysis of artificial neural networks (ANN) subject to time-delay and polytope-bounded uncertainties in the parameters. The main objective is to propose a less conservative condition to the stability analysis using the Gu's discretized Lyapunov-Krasovskii functional theory and an alternative strategy to introduce slack matrices. Two computer simulations examples are performed to support the theoretical predictions. Particularly, in the first example, the Hopf bifurcation theory is used to verify the stability of the system when the origin falls into instability. The second example is presented to illustrate how the proposed approach can provide better stability performance when compared to other ones in the literature
Physical violence and psychological abuse among siblings :a theoretical and empirical analysis
Hoffman, Kristi L.
1996-01-01
This study develops and evaluates a theoretical model based on social learning, conflict, and feminist perspectives to explain teenage sibling physical violence and psychological abuse. Using regression analysis and data from 796 young adults, considerable support is found for all three theoretical approaches and suggests an integrated model best predicts acts of violence and abuse among siblings. For physical violence, males and brothers had significantly higher rates. Spousal...
DEFF Research Database (Denmark)
Poel, Mike van der; Gehrig, Edeltraud; Hess, Ortwin
2005-01-01
Ultrafast gain dynamics in an optical amplifier with an active layer of self-organized quantum dots (QDs) emitting near 1.3$muhbox m$is characterized experimentally in a pump-probe experiment and modeled theoretically on the basis of QD Maxwell–Bloch equations. Experiment and theory are in good......$factor) is theoretically predicted and demonstrated in the experiments. The fundamental analysis reveals the underlying physical processes and indicates limitations to QD-based devices....
Theoretical foundations of functional data analysis, with an introduction to linear operators
Hsing, Tailen
2015-01-01
Theoretical Foundations of Functional Data Analysis, with an Introduction to Linear Operators provides a uniquely broad compendium of the key mathematical concepts and results that are relevant for the theoretical development of functional data analysis (FDA).The self-contained treatment of selected topics of functional analysis and operator theory includes reproducing kernel Hilbert spaces, singular value decomposition of compact operators on Hilbert spaces and perturbation theory for both self-adjoint and non self-adjoint operators. The probabilistic foundation for FDA is described from the
Ghazzai, Hakim
2014-11-01
This paper investigates the collaboration between multiple mobile operators to optimize the energy efficiency of cellular networks, maximize their profits or achieve or tradeoff between both objectives. Mobile operators cooperate together by eliminating redundant base stations (BSs) using a low complexity algorithm that aims to maximize their objective functions subject to a quality of service constraint. The problem is modeled as a two-level Stackelberg game: a mobile operator level and a smart grid level. Indeed, in our framework, we assume that cellular networks are powered by multiple energy providers existing in the smart grid characterized by different pollutant levels in addition to renewable energy source deployed in BS sites. The objective is to find the best active BS combination and the optimal procurement decision needed to the network operation during collaboration by considering electricity real-time pricing. Our study includes the daily traffic variation in addition to the daily green energy availability. Our simulation results show a significant saving in terms of CO2 emissions compared to the non-collaboration case and that cooperative mobile operators exploiting renewables are more awarded than traditional operators. © 2014 IEEE.
Principal component analysis networks and algorithms
Kong, Xiangyu; Duan, Zhansheng
2017-01-01
This book not only provides a comprehensive introduction to neural-based PCA methods in control science, but also presents many novel PCA algorithms and their extensions and generalizations, e.g., dual purpose, coupled PCA, GED, neural based SVD algorithms, etc. It also discusses in detail various analysis methods for the convergence, stabilizing, self-stabilizing property of algorithms, and introduces the deterministic discrete-time systems method to analyze the convergence of PCA/MCA algorithms. Readers should be familiar with numerical analysis and the fundamentals of statistics, such as the basics of least squares and stochastic algorithms. Although it focuses on neural networks, the book only presents their learning law, which is simply an iterative algorithm. Therefore, no a priori knowledge of neural networks is required. This book will be of interest and serve as a reference source to researchers and students in applied mathematics, statistics, engineering, and other related fields.
International Nuclear Information System (INIS)
Hsu, T.R.; Bertels, A.W.M.; Banerjee, S.; Harrison, W.C.
1976-07-01
This report presents the theoretical basis for a transient thermal elastic-plastic stress analysis of a nuclear reactor fuel element subject to severe transient thermo-mechanical loading. A finite element formulation is used for both the non-linear stress analysis and thermal analysis. These two major components are linked together to form an integrated program capable of predicting fuel element transient behaviour in two dimensions. Specific case studies are presented to illustrate capabilities of the analysis. (author)
Service network analysis for agricultural mental health
Directory of Open Access Journals (Sweden)
Fuller Jeffrey D
2009-05-01
Full Text Available Abstract Background Farmers represent a subgroup of rural and remote communities at higher risk of suicide attributed to insecure economic futures, self-reliant cultures and poor access to health services. Early intervention models are required that tap into existing farming networks. This study describes service networks in rural shires that relate to the mental health needs of farming families. This serves as a baseline to inform service network improvements. Methods A network survey of mental health related links between agricultural support, health and other human services in four drought declared shires in comparable districts in rural New South Wales, Australia. Mental health links covered information exchange, referral recommendations and program development. Results 87 agencies from 111 (78% completed a survey. 79% indicated that two thirds of their clients needed assistance for mental health related problems. The highest mean number of interagency links concerned information exchange and the frequency of these links between sectors was monthly to three monthly. The effectiveness of agricultural support and health sector links were rated as less effective by the agricultural support sector than by the health sector (p Conclusion Aligning with agricultural agencies is important to build effective mental health service pathways to address the needs of farming populations. Work is required to ensure that these agricultural support agencies have operational and effective links to primary mental health care services. Network analysis provides a baseline to inform this work. With interventions such as local mental health training and joint service planning to promote network development we would expect to see over time an increase in the mean number of links, the frequency in which these links are used and the rated effectiveness of these links.
Zhu, Wenzhong; Liu, Dan
2014-01-01
Based on a review of the literature on ESP and needs analysis, this paper is intended to offer some theoretical supports and inspirations for BE instructors to develop BE curricula for business contexts. It discusses how the theory of need analysis can be used in Business English curriculum design, and proposes some principles of BE curriculum…
Social network analysis: Presenting an underused method for nursing research.
Parnell, James Michael; Robinson, Jennifer C
2018-06-01
This paper introduces social network analysis as a versatile method with many applications in nursing research. Social networks have been studied for years in many social science fields. The methods continue to advance but remain unknown to most nursing scholars. Discussion paper. English language and interpreted literature was searched from Ovid Healthstar, CINAHL, PubMed Central, Scopus and hard copy texts from 1965 - 2017. Social network analysis first emerged in nursing literature in 1995 and appears minimally through present day. To convey the versatility and applicability of social network analysis in nursing, hypothetical scenarios are presented. The scenarios are illustrative of three approaches to social network analysis and include key elements of social network research design. The methods of social network analysis are underused in nursing research, primarily because they are unknown to most scholars. However, there is methodological flexibility and epistemological versatility capable of supporting quantitative and qualitative research. The analytic techniques of social network analysis can add new insight into many areas of nursing inquiry, especially those influenced by cultural norms. Furthermore, visualization techniques associated with social network analysis can be used to generate new hypotheses. Social network analysis can potentially uncover findings not accessible through methods commonly used in nursing research. Social networks can be analysed based on individual-level attributes, whole networks and subgroups within networks. Computations derived from social network analysis may stand alone to answer a research question or incorporated as variables into robust statistical models. © 2018 John Wiley & Sons Ltd.
International Nuclear Information System (INIS)
Li, Huajiao; An, Haizhong; Fang, Wei; Jiang, Meng
2017-01-01
The logistical issues surrounding the timing and transport of flowback generated by each shale gas well to the next is a big challenge. Due to more and more flowback being stored temporarily near the shale gas well and reused in the shale gas development, both transportation cost and storage cost are the heavy burden for the developers. This research proposed a theoretical cost optimization model to get the optimal flowback distribution solution for regional multi shale gas wells in a holistic perspective. Then, we used some empirical data of Marcellus Shale to do the empirical study. In addition, we compared the optimal flowback distribution solution by considering both the transportation cost and storage cost with the flowback distribution solution which only minimized the transportation cost or only minimized the storage cost. - Highlights: • A theoretical cost optimization model to get optimal flowback distribution solution. • An empirical study using the shale gas data in Bradford County of Marcellus Shale. • Visualization of optimal flowback distribution solutions under different scenarios. • Transportation cost is a more important factor for reducing the cost. • Help the developers to cut the storage and transportation cost of reusing flowback.
CATHENA 4. A thermalhydraulics network analysis code
International Nuclear Information System (INIS)
Aydemir, N.U.; Hanna, B.N.
2009-01-01
Canadian Algorithm for THErmalhydraulic Network Analysis (CATHENA) is a one-dimensional, non-equilibrium, two-phase, two fluid network analysis code that has been in use for over two decades by various groups in Canada and around the world. The objective of the present paper is to describe the design, application and future development plans for the CATHENA 4 thermalhydraulics network analysis code, which is a modernized version of the present frozen CATHENA 3 code. The new code is designed in modular form, using the Fortran 95 (F95) programming language. The semi-implicit numerical integration scheme of CATHENA 3 is re-written to implement a fully-implicit methodology using Newton's iterative solution scheme suitable for nonlinear equations. The closure relations, as a first step, have been converted from the existing CATHENA 3 implementation to F95 but modularized to achieve ease of maintenance. The paper presents the field equations, followed by a description of the Newton's scheme used. The finite-difference form of the field equations is given, followed by a discussion of convergence criteria. Two applications of CATHENA 4 are presented to demonstrate the temporal and spatial convergence of the new code for problems with known solutions or available experimental data. (author)
Network value and optimum analysis on the mode of networked marketing in TV media
Directory of Open Access Journals (Sweden)
Xiao Dongpo
2012-12-01
Full Text Available Purpose: With the development of the networked marketing in TV media, it is important to do the research on network value and optimum analysis in this field.Design/methodology/approach: According to the research on the mode of networked marketing in TV media and Correlation theory, the essence of media marketing is creating, spreading and transferring values. The Participants of marketing value activities are in network, and value activities proceed in networked form. Network capability is important to TV media marketing activities.Findings: This article raises the direction of research of analysis and optimization about network based on the mode of networked marketing in TV media by studying TV media marketing Development Mechanism , network analysis and network value structure.
Directory of Open Access Journals (Sweden)
Lei Wang
2018-01-01
Full Text Available Device-to-Device communication underlaying cellular network can increase the spectrum efficiency due to direct proximity communication and frequency reuse. However, such performance improvement is influenced by the power interference caused by spectrum sharing and social characteristics in each social community jointly. In this investigation, we present a dynamic game theory with complete information based D2D resource allocation scheme for D2D communication underlaying cellular network. In this resource allocation method, we quantify both the rate influence from the power interference caused by the D2D transmitter to cellular users and rate enhancement brought by the social relationships between mobile users. Then, the utility function maximization game is formulated to optimize the overall transmission rate performance of the network, which synthetically measures the final influence from both power interference and sociality enhancement. Simultaneously, we discuss the Nash Equilibrium of the proposed utility function maximization game from a theoretical point of view and further put forward a utility priority searching algorithm based resource allocation scheme. Simulation results show that our proposed scheme attains better performance compared with the other two advanced proposals.
NIF ICCS network design and loading analysis
International Nuclear Information System (INIS)
Tietbohl, G; Bryant, R
1998-01-01
The National Ignition Facility (NIF) is housed within a large facility about the size of two football fields. The Integrated Computer Control System (ICCS) is distributed throughout this facility and requires the integration of about 40,000 control points and over 500 video sources. This integration is provided by approximately 700 control computers distributed throughout the NIF facility and a network that provides the communication infrastructure. A main control room houses a set of seven computer consoles providing operator access and control of the various distributed front-end processors (FEPs). There are also remote workstations distributed within the facility that allow provide operator console functions while personnel are testing and troubleshooting throughout the facility. The operator workstations communicate with the FEPs which implement the localized control and monitoring functions. There are different types of FEPs for the various subsystems being controlled. This report describes the design of the NIF ICCS network and how it meets the traffic loads that will are expected and the requirements of the Sub-System Design Requirements (SSDR's). This document supersedes the earlier reports entitled Analysis of the National Ignition Facility Network, dated November 6, 1996 and The National Ignition Facility Digital Video and Control Network, dated July 9, 1996. For an overview of the ICCS, refer to the document NIF Integrated Computer Controls System Description (NIF-3738)
Distinguishing manipulated stocks via trading network analysis
Sun, Xiao-Qian; Cheng, Xue-Qi; Shen, Hua-Wei; Wang, Zhao-Yang
2011-10-01
Manipulation is an important issue for both developed and emerging stock markets. For the study of manipulation, it is critical to analyze investor behavior in the stock market. In this paper, an analysis of the full transaction records of over a hundred stocks in a one-year period is conducted. For each stock, a trading network is constructed to characterize the relations among its investors. In trading networks, nodes represent investors and a directed link connects a stock seller to a buyer with the total trade size as the weight of the link, and the node strength is the sum of all edge weights of a node. For all these trading networks, we find that the node degree and node strength both have tails following a power-law distribution. Compared with non-manipulated stocks, manipulated stocks have a high lower bound of the power-law tail, a high average degree of the trading network and a low correlation between the price return and the seller-buyer ratio. These findings may help us to detect manipulated stocks.
Directory of Open Access Journals (Sweden)
González-Bailón, Sandra
2009-12-01
Full Text Available There is interdependence when the actions of an individual influence the decisions (and later actions of other individuals. This paper claims that social networks define the structure of that range of influence and unleash a number of mechanisms that go beyond those captured by rational action theory. Networks give access to the ideas and actions of other individuals, and this exposure determines the activation of thresholds, the timing of actions, and the emergence of contagion processes, informational cascades and epidemics. This paper sustains that rational action theory does not offer the necessary tools to model these processes if it is not inserted in a general theory of networks. This is especially the case in the context opened by new information and communication technologies, where the interdependence of individuals is acquiring greater empirical relevance.
Existe interdependencia cuando las acciones de unos individuos influyen en las decisiones (y posteriores acciones de otros individuos. Este artículo sostiene que las redes sociales definen la estructura de ese espacio de influencia y desatan una serie de mecanismos de los que la teoría de la elección racional no puede dar cuenta. Las redes sociales abren acceso a las ideas y acciones de otros individuos, y esta exposición determina la satisfacción de umbrales, el tempo con en el que se llevan a cabo las acciones y la emergencia de procesos de contagio, cascadas de información y epidemias. Este artículo defiende que la teoría de la elección racional no ofrece las herramientas necesarias para modelizar tales procesos si no se inserta en una teoría general de redes. Éste es especialmente el caso en unos momentos en los que la interdependencia de individuos está adquiriendo, al amparo de las nuevas tecnologías, mayor relevancia empírica.
Kennedy, Catriona M; Buchan, Iain; Powell, John; Ainsworth, John
2015-01-01
the effectiveness of online social networking within health promotion interventions. Most of the trials investigated the value of a “social networking condition” in general and did not identify specific features that might play a role in effectiveness. Issues about the usability and level of uptake of interventions were more common among pilot studies, while observational studies showed positive evidence about the role of social support. A total of 20 papers showed the use of theory in the design of interventions, but authors evaluated effectiveness in only 10 papers. Conclusions More research is needed in this area to understand the actual effect of social network technologies on health promotion. More RCTs of greater length need to be conducted taking into account contextual factors such as patient characteristics and types of a social network technology. Also, more evidence is needed regarding the actual usability of online social networking and how different interface design elements may help or hinder behavior change and engagement. Moreover, it is crucial to investigate further the effect of theory on the effectiveness of this type of technology for health promotion. Research is needed linking theoretical grounding with observation and analysis of health promotion in online networks. PMID:26068087
Balatsoukas, Panos; Kennedy, Catriona M; Buchan, Iain; Powell, John; Ainsworth, John
2015-06-11
networking within health promotion interventions. Most of the trials investigated the value of a "social networking condition" in general and did not identify specific features that might play a role in effectiveness. Issues about the usability and level of uptake of interventions were more common among pilot studies, while observational studies showed positive evidence about the role of social support. A total of 20 papers showed the use of theory in the design of interventions, but authors evaluated effectiveness in only 10 papers. More research is needed in this area to understand the actual effect of social network technologies on health promotion. More RCTs of greater length need to be conducted taking into account contextual factors such as patient characteristics and types of a social network technology. Also, more evidence is needed regarding the actual usability of online social networking and how different interface design elements may help or hinder behavior change and engagement. Moreover, it is crucial to investigate further the effect of theory on the effectiveness of this type of technology for health promotion. Research is needed linking theoretical grounding with observation and analysis of health promotion in online networks.
Directory of Open Access Journals (Sweden)
Wi Hoon eJung
2013-10-01
Full Text Available One major characteristic of experts is intuitive judgment, which is an automatic process whereby patterns stored in memory through long-term training are recognized. Indeed, long-term training may influence brain structure and function. A recent study revealed that chess experts at rest showed differences in structure and functional connectivity (FC in the head of caudate, which is associated with rapid best next-move generation. However, less is known about the structure and function of the brains of Baduk experts compared with those of experts in other strategy games. Therefore, we performed voxel-based morphometry and FC analyses in Baduk experts to investigate structural brain differences and to clarify the influence of these differences on functional interactions. We also conducted graph theoretical analysis to explore the topological organization of whole-brain functional networks. Compared to novices, Baduk experts exhibited decreased and increased gray matter volume in the amygdala and nucleus accumbens, respectively. We also found increased FC between the amygdala and medial orbitofrontal cortex and decreased FC between the nucleus accumbens and medial prefrontal cortex. Further graph theoretical analysis revealed differences in measures of the integration of the network and in the regional nodal characteristics of various brain regions activated during Baduk. This study provides evidence for structural and functional differences as well as altered topological organization of the whole-brain functional networks in Baduk experts. Our findings also offer novel suggestions about the cognitive mechanisms behind Baduk expertise, which involves intuitive decision-making mediated by somatic marker circuitry and visuospatial processing.
Gruenenfelder, Thomas M.; Recchia, Gabriel; Rubin, Tim; Jones, Michael N.
2016-01-01
We compared the ability of three different contextual models of lexical semantic memory (BEAGLE, Latent Semantic Analysis, and the Topic model) and of a simple associative model (POC) to predict the properties of semantic networks derived from word association norms. None of the semantic models were able to accurately predict all of the network…
Theoretical properties of the global optimizer of two layer neural network
Boob, Digvijay; Lan, Guanghui
2017-01-01
In this paper, we study the problem of optimizing a two-layer artificial neural network that best fits a training dataset. We look at this problem in the setting where the number of parameters is greater than the number of sampled points. We show that for a wide class of differentiable activation functions (this class involves "almost" all functions which are not piecewise linear), we have that first-order optimal solutions satisfy global optimality provided the hidden layer is non-singular. ...
An in-depth analysis of theoretical frameworks for the study of care coordination
Directory of Open Access Journals (Sweden)
Sabine Van Houdt
2013-06-01
Full Text Available Introduction: Complex chronic conditions often require long-term care from various healthcare professionals. Thus, maintaining quality care requires care coordination. Concepts for the study of care coordination require clarification to develop, study and evaluate coordination strategies. In 2007, the Agency for Healthcare Research and Quality defined care coordination and proposed five theoretical frameworks for exploring care coordination. This study aimed to update current theoretical frameworks and clarify key concepts related to care coordination. Methods: We performed a literature review to update existing theoretical frameworks. An in-depth analysis of these theoretical frameworks was conducted to formulate key concepts related to care coordination.Results: Our literature review found seven previously unidentified theoretical frameworks for studying care coordination. The in-depth analysis identified fourteen key concepts that the theoretical frameworks addressed. These were ‘external factors’, ‘structure’, ‘tasks characteristics’, ‘cultural factors’, ‘knowledge and technology’, ‘need for coordination’, ‘administrative operational processes’, ‘exchange of information’, ‘goals’, ‘roles’, ‘quality of relationship’, ‘patient outcome’, ‘team outcome’, and ‘(interorganizational outcome’.Conclusion: These 14 interrelated key concepts provide a base to develop or choose a framework for studying care coordination. The relational coordination theory and the multi-level framework are interesting as these are the most comprehensive.
The Application of Social Network Analysis to Team Sports
Lusher, Dean; Robins, Garry; Kremer, Peter
2010-01-01
This article reviews how current social network analysis might be used to investigate individual and group behavior in sporting teams. Social network analysis methods permit researchers to explore social relations between team members and their individual-level qualities simultaneously. As such, social network analysis can be seen as augmenting…
Analysis and visualization of citation networks
Zhao, Dangzhi
2015-01-01
Citation analysis-the exploration of reference patterns in the scholarly and scientific literature-has long been applied in a number of social sciences to study research impact, knowledge flows, and knowledge networks. It has important information science applications as well, particularly in knowledge representation and in information retrieval.Recent years have seen a burgeoning interest in citation analysis to help address research, management, or information service issues such as university rankings, research evaluation, or knowledge domain visualization. This renewed and growing interest
An Intelligent technical analysis using neural network
Directory of Open Access Journals (Sweden)
Reza Raei
2011-07-01
Full Text Available Technical analysis has been one of the most popular methods for stock market predictions for the past few decades. There have been enormous technical analysis methods to study the behavior of stock market for different kinds of trading markets such as currency, commodity or stock. In this paper, we propose two different methods based on volume adjusted moving average and ease of movement for stock trading. These methods are used with and without generalized regression neural network methods and the results are compared with each other. The preliminary results on historical stock price of 20 firms indicate that there is no meaningful difference between various proposed models of this paper.
Directory of Open Access Journals (Sweden)
Rosa Maria Leite Pedro
2007-12-01
Full Text Available The object of this paper is to discuss some of the theoretical and methodological controversies surrounding the emerging field of bioethics, especially focusing on reproduction biotechnologies, attempting to give some examples of its implications as a network of controversies. Initially, it presents the new reproduction biotechnologies in terms of the effect which they are producing on our understanding about human nature and life, as well as the context of the emergence of bioethics, traditionally conceived of as a critical and analytical example of the relationship between technology and humanity. As an alternative way of explaining these relationships, it outlines the aspect of bioethics as a network effect, in which the technology-society hybrid is shown both in the building of bioethical norms and in the instabilities which challenge these norms. As a way of understanding this heterogeneous and complex network, Controversy Analysis is proposed as a methodological tool. In order to illustrate the richness of such perspective, a brief empirical study is presented, in which an attempt is made to track controversies articulated around the relations between bioethics and reproduction biotechnologies, with a specific focus on stem cell research, as published by the on-line media from January of 2004 until July of 2006, raising questions about subjects such as: life, humanity, artifice and autonomy.
The network researchers' network: A social network analysis of the IMP Group 1985-2006
DEFF Research Database (Denmark)
Henneberg, Stephan C. M.; Ziang, Zhizhong; Naudé, Peter
The Industrial Marketing and Purchasing (IMP) Group is a network of academic researchers working in the area of business-to-business marketing. The group meets every year to discuss and exchange ideas, with a conference having been held every year since 1984 (there was no meeting in 1987......). In this paper, based upon the papers presented at the 22 conferences held to date, we undertake a Social Network Analysis in order to examine the degree of co-publishing that has taken place between this group of researchers. We identify the different components in this database, and examine the large main...
Concurrent Transmission Based on Channel Quality in Ad Hoc Networks: A Game Theoretic Approach
Chen, Chen; Gao, Xinbo; Li, Xiaoji; Pei, Qingqi
In this paper, a decentralized concurrent transmission strategy in shared channel in Ad Hoc networks is proposed based on game theory. Firstly, a static concurrent transmissions game is used to determine the candidates for transmitting by channel quality threshold and to maximize the overall throughput with consideration of channel quality variation. To achieve NES (Nash Equilibrium Solution), the selfish behaviors of node to attempt to improve the channel gain unilaterally are evaluated. Therefore, this game allows each node to be distributed and to decide whether to transmit concurrently with others or not depending on NES. Secondly, as there are always some nodes with lower channel gain than NES, which are defined as hunger nodes in this paper, a hunger suppression scheme is proposed by adjusting the price function with interferences reservation and forward relay, to fairly give hunger nodes transmission opportunities. Finally, inspired by stock trading, a dynamic concurrent transmission threshold determination scheme is implemented to make the static game practical. Numerical results show that the proposed scheme is feasible to increase concurrent transmission opportunities for active nodes, and at the same time, the number of hunger nodes is greatly reduced with the least increase of threshold by interferences reservation. Also, the good performance on network goodput of the proposed model can be seen from the results.
Chakraborty, Chiranjib; Sarkar, Bimal Kumar; Patel, Pratiksha; Agoramoorthy, Govindasamy
2012-01-01
In this paper, Shannon information theory has been applied to elaborate cell signaling. It is proposed that in the cellular network architecture, four components viz. source (DNA), transmitter (mRNA), receiver (protein) and destination (another protein) are involved. The message transmits from source (DNA) to transmitter (mRNA) and then passes through a noisy channel reaching finally the receiver (protein). The protein synthesis process is here considered as the noisy channel. Ultimately, signal is transmitted from receiver to destination (another protein). The genome network architecture elements were compared with genetic alphabet L = {A, C, G, T} with a biophysical model based on the popular Shannon information theory. This study found the channel capacity as maximum for zero error (sigma = 0) and at this condition, transition matrix becomes a unit matrix with rank 4. The transition matrix will be erroneous and finally at sigma = 1 channel capacity will be localized maxima with a value of 0.415 due to the increased value at sigma. On the other hand, minima exists at sigma = 0.75, where all transition probabilities become 0.25 and uncertainty will be maximum resulting in channel capacity with the minima value of zero.
A gene network bioinformatics analysis for pemphigoid autoimmune blistering diseases.
Barone, Antonio; Toti, Paolo; Giuca, Maria Rita; Derchi, Giacomo; Covani, Ugo
2015-07-01
In this theoretical study, a text mining search and clustering analysis of data related to genes potentially involved in human pemphigoid autoimmune blistering diseases (PAIBD) was performed using web tools to create a gene/protein interaction network. The Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was employed to identify a final set of PAIBD-involved genes and to calculate the overall significant interactions among genes: for each gene, the weighted number of links, or WNL, was registered and a clustering procedure was performed using the WNL analysis. Genes were ranked in class (leader, B, C, D and so on, up to orphans). An ontological analysis was performed for the set of 'leader' genes. Using the above-mentioned data network, 115 genes represented the final set; leader genes numbered 7 (intercellular adhesion molecule 1 (ICAM-1), interferon gamma (IFNG), interleukin (IL)-2, IL-4, IL-6, IL-8 and tumour necrosis factor (TNF)), class B genes were 13, whereas the orphans were 24. The ontological analysis attested that the molecular action was focused on extracellular space and cell surface, whereas the activation and regulation of the immunity system was widely involved. Despite the limited knowledge of the present pathologic phenomenon, attested by the presence of 24 genes revealing no protein-protein direct or indirect interactions, the network showed significant pathways gathered in several subgroups: cellular components, molecular functions, biological processes and the pathologic phenomenon obtained from the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database. The molecular basis for PAIBD was summarised and expanded, which will perhaps give researchers promising directions for the identification of new therapeutic targets.
System Theoretic Dependability Analysis of the LHC Superconducting Magnet Circuit Protection
AUTHOR|(CDS)2254970
Subject of the present work is the application of the methods STPA (System Theoretic Process Analysis) and CAST (Causal Analysis based on STAMP) to analyze the protection systems of the superconducting magnet circuit of the LHC at CERN, Geneva. The named methods are derived from the at MIT developed STAMP (System Theoretic Accident Model and Processes) accident model. The CAST method was applied to the analysis of the 2008 Incident during the Hardware Commissioning. An incorrect interconnection between two magnets damaged the accelerator severely. The analysis defines the control structure of the Commissioning and investigates every subsystem and the interaction between the components. The results were social and technical requirements. Among others, it shows the necessity for safety culture at CERN and a revision of the magnet interconnection process. The present analysis found the same root causes for the incident than a task force did in 2009. Further, the CAST analysis found more, socio-technica...
Simultaneity Analysis In A Wireless Sensor Network
Directory of Open Access Journals (Sweden)
Malović Miodrag
2015-06-01
Full Text Available An original wireless sensor network for vibration measurements was designed. Its primary purpose is modal analysis of vibrations of large structures. A number of experiments have been performed to evaluate the system, with special emphasis on the influence of different effects on simultaneity of data acquired from remote nodes, which is essential for modal analysis. One of the issues is that quartz crystal oscillators, which provide time reading on the devices, are optimized for use in the room temperature and exhibit significant frequency variations if operated outside the 20–30°C range. Although much research was performed to optimize algorithms of synchronization in wireless networks, the subject of temperature fluctuations was not investigated and discussed in proportion to its significance. This paper describes methods used to evaluate data simultaneity and some algorithms suitable for its improvement in small to intermediate size ad-hoc wireless sensor networks exposed to varying temperatures often present in on-site civil engineering measurements.
Institute of Scientific and Technical Information of China (English)
SHI Shi-liang; LIU Hai-bo; LIU Ai-hua
2004-01-01
Based on the integration analysis of goods and shortcomings of various methods used in safety assessment of coal mines, combining nonlinear feature of mine safety sub-system, this paper establishes the neural network assessment model of mine safety, analyzes the ability of artificial neural network to evaluate mine safety state, and lays the theoretical foundation of artificial neural network using in the systematic optimization of mine safety assessment and getting reasonable accurate safety assessment result.
A game theoretic algorithm to detect overlapping community structure in networks
Zhou, Xu; Zhao, Xiaohui; Liu, Yanheng; Sun, Geng
2018-04-01
Community detection can be used as an important technique for product and personalized service recommendation. A game theory based approach to detect overlapping community structure is introduced in this paper. The process of the community formation is converted into a game, when all agents (nodes) cannot improve their own utility, the game process will be terminated. The utility function is composed of a gain and a loss function and we present a new gain function in this paper. In addition, different from choosing action randomly among join, quit and switch for each agent to get new label, two new strategies for each agent to update its label are designed during the game, and the strategies are also evaluated and compared for each agent in order to find its best result. The overlapping community structure is naturally presented when the stop criterion is satisfied. The experimental results demonstrate that the proposed algorithm outperforms other similar algorithms for detecting overlapping communities in networks.
Understanding resilience in industrial symbiosis networks: insights from network analysis.
Chopra, Shauhrat S; Khanna, Vikas
2014-08-01
Industrial symbiotic networks are based on the principles of ecological systems where waste equals food, to develop synergistic networks. For example, industrial symbiosis (IS) at Kalundborg, Denmark, creates an exchange network of waste, water, and energy among companies based on contractual dependency. Since most of the industrial symbiotic networks are based on ad-hoc opportunities rather than strategic planning, gaining insight into disruptive scenarios is pivotal for understanding the balance of resilience and sustainability and developing heuristics for designing resilient IS networks. The present work focuses on understanding resilience as an emergent property of an IS network via a network-based approach with application to the Kalundborg Industrial Symbiosis (KIS). Results from network metrics and simulated disruptive scenarios reveal Asnaes power plant as the most critical node in the system. We also observe a decrease in the vulnerability of nodes and reduction in single points of failure in the system, suggesting an increase in the overall resilience of the KIS system from 1960 to 2010. Based on our findings, we recommend design strategies, such as increasing diversity, redundancy, and multi-functionality to ensure flexibility and plasticity, to develop resilient and sustainable industrial symbiotic networks. Copyright © 2014 Elsevier Ltd. All rights reserved.
NATbox: a network analysis toolbox in R.
Chavan, Shweta S; Bauer, Michael A; Scutari, Marco; Nagarajan, Radhakrishnan
2009-10-08
There has been recent interest in capturing the functional relationships (FRs) from high-throughput assays using suitable computational techniques. FRs elucidate the working of genes in concert as a system as opposed to independent entities hence may provide preliminary insights into biological pathways and signalling mechanisms. Bayesian structure learning (BSL) techniques and its extensions have been used successfully for modelling FRs from expression profiles. Such techniques are especially useful in discovering undocumented FRs, investigating non-canonical signalling mechanisms and cross-talk between pathways. The objective of the present study is to develop a graphical user interface (GUI), NATbox: Network Analysis Toolbox in the language R that houses a battery of BSL algorithms in conjunction with suitable statistical tools for modelling FRs in the form of acyclic networks from gene expression profiles and their subsequent analysis. NATbox is a menu-driven open-source GUI implemented in the R statistical language for modelling and analysis of FRs from gene expression profiles. It provides options to (i) impute missing observations in the given data (ii) model FRs and network structure from gene expression profiles using a battery of BSL algorithms and identify robust dependencies using a bootstrap procedure, (iii) present the FRs in the form of acyclic graphs for visualization and investigate its topological properties using network analysis metrics, (iv) retrieve FRs of interest from published literature. Subsequently, use these FRs as structural priors in BSL (v) enhance scalability of BSL across high-dimensional data by parallelizing the bootstrap routines. NATbox provides a menu-driven GUI for modelling and analysis of FRs from gene expression profiles. By incorporating readily available functions from existing R-packages, it minimizes redundancy and improves reproducibility, transparency and sustainability, characteristic of open-source environments
Multilayer modeling and analysis of human brain networks
2017-01-01
Abstract Understanding how the human brain is structured, and how its architecture is related to function, is of paramount importance for a variety of applications, including but not limited to new ways to prevent, deal with, and cure brain diseases, such as Alzheimer’s or Parkinson’s, and psychiatric disorders, such as schizophrenia. The recent advances in structural and functional neuroimaging, together with the increasing attitude toward interdisciplinary approaches involving computer science, mathematics, and physics, are fostering interesting results from computational neuroscience that are quite often based on the analysis of complex network representation of the human brain. In recent years, this representation experienced a theoretical and computational revolution that is breaching neuroscience, allowing us to cope with the increasing complexity of the human brain across multiple scales and in multiple dimensions and to model structural and functional connectivity from new perspectives, often combined with each other. In this work, we will review the main achievements obtained from interdisciplinary research based on magnetic resonance imaging and establish de facto, the birth of multilayer network analysis and modeling of the human brain. PMID:28327916
Pavlogiannis, Andreas; Mozhayskiy, Vadim; Tagkopoulos, Ilias
2013-04-24
Biological networks tend to have high interconnectivity, complex topologies and multiple types of interactions. This renders difficult the identification of sub-networks that are involved in condition- specific responses. In addition, we generally lack scalable methods that can reveal the information flow in gene regulatory and biochemical pathways. Doing so will help us to identify key participants and paths under specific environmental and cellular context. This paper introduces the theory of network flooding, which aims to address the problem of network minimization and regulatory information flow in gene regulatory networks. Given a regulatory biological network, a set of source (input) nodes and optionally a set of sink (output) nodes, our task is to find (a) the minimal sub-network that encodes the regulatory program involving all input and output nodes and (b) the information flow from the source to the sink nodes of the network. Here, we describe a novel, scalable, network traversal algorithm and we assess its potential to achieve significant network size reduction in both synthetic and E. coli networks. Scalability and sensitivity analysis show that the proposed method scales well with the size of the network, and is robust to noise and missing data. The method of network flooding proves to be a useful, practical approach towards information flow analysis in gene regulatory networks. Further extension of the proposed theory has the potential to lead in a unifying framework for the simultaneous network minimization and information flow analysis across various "omics" levels.
Applications of social media and social network analysis
Kazienko, Przemyslaw
2015-01-01
This collection of contributed chapters demonstrates a wide range of applications within two overlapping research domains: social media analysis and social network analysis. Various methodologies were utilized in the twelve individual chapters including static, dynamic and real-time approaches to graph, textual and multimedia data analysis. The topics apply to reputation computation, emotion detection, topic evolution, rumor propagation, evaluation of textual opinions, friend ranking, analysis of public transportation networks, diffusion in dynamic networks, analysis of contributors to commun
Critical supply network protection against intentional attacks: A game-theoretical model
International Nuclear Information System (INIS)
Bricha, Naji; Nourelfath, Mustapha
2013-01-01
A crucial issue in today's critical supply chains is how to protect facilities against intentional attacks, since it has become unacceptable to ignore the high impact of low probability disruptions caused by these attacks. This article develops a game-theoretical model to deal with the protection of facilities, in the context of the uncapacitated fixed-charge location problem. Given a set of investment alternatives for protecting the facilities against identified threats, the objective is to select the optimal defence strategy. The attacker is considered as a player who tries to maximise the expected damage while weighing against the attacks expenditures. The conflict on facilities vulnerability is modelled using the concept of contest. The vulnerability of a facility is defined by its destruction probability. Contest success functions determine the vulnerability of each facility dependent on the relative investments of the defender and the attacker on each facility, and on the characteristics of the contest. A method is developed to evaluate the utilities of the players (i.e., the defender and the attacker). This method evaluates many expected costs, including the cost needed to restore disabled facilities, the backorder cost, and the cost incurred because of the increase in transportation costs after attacks. In fact, when one or several facilities are unavailable, transportation costs will increase since reassigned customers may receive shipments from facilities which are farther away. The model considers a non-cooperative two-period game between the players, and an algorithm is presented to determine the equilibrium solution and the optimal defence strategy. An illustrative example is presented. The approach is compared to other suggested strategies, and some managerial insights are provided in the context of facility location
Analysis of complex systems using neural networks
International Nuclear Information System (INIS)
Uhrig, R.E.
1992-01-01
The application of neural networks, alone or in conjunction with other advanced technologies (expert systems, fuzzy logic, and/or genetic algorithms), to some of the problems of complex engineering systems has the potential to enhance the safety, reliability, and operability of these systems. Typically, the measured variables from the systems are analog variables that must be sampled and normalized to expected peak values before they are introduced into neural networks. Often data must be processed to put it into a form more acceptable to the neural network (e.g., a fast Fourier transformation of the time-series data to produce a spectral plot of the data). Specific applications described include: (1) Diagnostics: State of the Plant (2) Hybrid System for Transient Identification, (3) Sensor Validation, (4) Plant-Wide Monitoring, (5) Monitoring of Performance and Efficiency, and (6) Analysis of Vibrations. Although specific examples described deal with nuclear power plants or their subsystems, the techniques described can be applied to a wide variety of complex engineering systems
Network-based analysis of proteomic profiles
Wong, Limsoon
2016-01-26
Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for profiling systems-wide protein expression changes. It can be applied for various purposes, e.g. biomarker discovery in diseases and study of drug responses. Although RNA-based high-throughput methods have been useful in providing glimpses into the underlying molecular processes, the evidences they provide are indirect. Furthermore, RNA and corresponding protein levels have been known to have poor correlation. On the other hand, MS-based proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement) and coverage issues (inability to detect the entire proteome) that need to be urgently addressed. In this talk, I will discuss how these issues can be addressed by proteomic profile analysis techniques that use biological networks (especially protein complexes) as the biological context. In particular, I will describe several techniques that we have been developing for network-based analysis of proteomics profile. And I will present evidence that these techniques are useful in identifying proteomics-profile analysis results that are more consistent, more reproducible, and more biologically coherent, and that these techniques allow expansion of the detected proteome to uncover and/or discover novel proteins.
DEFF Research Database (Denmark)
Mørk, Jesper; Kjær, Rasmus; Poel, Mike van der
2005-01-01
Experimental demonstration and theoretical analysis of slow light in a semiconductor waveguide at GHz frequencies slow-down of light by a factor of two in a semiconductor waveguide at room temperature with a bandwidth of 16.7 GHz using the effect of coherent pulsations of the carrier density...
Social sciences via network analysis and computation
Kanduc, Tadej
2015-01-01
In recent years information and communication technologies have gained significant importance in the social sciences. Because there is such rapid growth of knowledge, methods and computer infrastructure, research can now seamlessly connect interdisciplinary fields such as business process management, data processing and mathematics. This study presents some of the latest results, practices and state-of-the-art approaches in network analysis, machine learning, data mining, data clustering and classifications in the contents of social sciences. It also covers various real-life examples such as t
Analysis of Time Delay Simulation in Networked Control System
Nyan Phyo Aung; Zaw Min Naing; Hla Myo Tun
2016-01-01
The paper presents a PD controller for the Networked Control Systems (NCS) with delay. The major challenges in this networked control system (NCS) are the delay of the data transmission throughout the communication network. The comparative performance analysis is carried out for different delays network medium. In this paper, simulation is carried out on Ac servo motor control system using CAN Bus as communication network medium. The True Time toolbox of MATLAB is used for simulation to analy...
Stamoulis, Catherine; Schomer, Donald L; Chang, Bernard S
2013-08-01
How a seizure terminates is still under-studied and, despite its clinical importance, remains an obscure phase of seizure evolution. Recent studies of seizure-related scalp EEGs at frequencies >100 Hz suggest that neural activity, in the form of oscillations and/or neuronal network interactions, may play an important role in preictal/ictal seizure evolution (Andrade-Valenca et al., 2011; Stamoulis et al., 2012). However, the role of high-frequency activity in seizure termination, is unknown, if it exists at all. Using information theoretic measures of network coordination, this study investigated ictal and immediate postictal neurodynamic interactions encoded in scalp EEGs from a relatively small sample of 8 patients with focal epilepsy and multiple seizures originating in temporal and/or frontal brain regions, at frequencies ≤ 100 Hz and >100 Hz, respectively. Despite some heterogeneity in the dynamics of these interactions, consistent patterns were also estimated. Specifically, in several seizures, linear or non-linear increase in high-frequency neuronal coordination during ictal intervals, coincided with a corresponding decrease in coordination at frequencies interval, which continues during the postictal interval. This may be one of several possible mechanisms that facilitate seizure termination. In fact, inhibition of pairwise interactions between EEGs by other signals in their spatial neighborhood, quantified by negative interaction information, was estimated at frequencies ≤ 100 Hz, at least in some seizures. Copyright © 2013 Elsevier B.V. All rights reserved.
Models as Tools of Analysis of a Network Organisation
Directory of Open Access Journals (Sweden)
Wojciech Pająk
2013-06-01
Full Text Available The paper presents models which may be applied as tools of analysis of a network organisation. The starting point of the discussion is defining the following terms: supply chain and network organisation. Further parts of the paper present basic assumptions analysis of a network organisation. Then the study characterises the best known models utilised in analysis of a network organisation. The purpose of the article is to define the notion and the essence of network organizations and to present the models used for their analysis.
Spatial analysis of bus transport networks using network theory
Shanmukhappa, Tanuja; Ho, Ivan Wang-Hei; Tse, Chi Kong
2018-07-01
In this paper, we analyze the bus transport network (BTN) structure considering the spatial embedding of the network for three cities, namely, Hong Kong (HK), London (LD), and Bengaluru (BL). We propose a novel approach called supernode graph structuring for modeling the bus transport network. A static demand estimation procedure is proposed to assign the node weights by considering the points of interests (POIs) and the population distribution in the city over various localized zones. In addition, the end-to-end delay is proposed as a parameter to measure the topological efficiency of the bus networks instead of the shortest distance measure used in previous works. With the aid of supernode graph representation, important network parameters are analyzed for the directed, weighted and geo-referenced bus transport networks. It is observed that the supernode concept has significant advantage in analyzing the inherent topological behavior. For instance, the scale-free and small-world behavior becomes evident with supernode representation as compared to conventional or regular graph representation for the Hong Kong network. Significant improvement in clustering, reduction in path length, and increase in centrality values are observed in all the three networks with supernode representation. The correlation between topologically central nodes and the geographically central nodes reveals the interesting fact that the proposed static demand estimation method for assigning node weights aids in better identifying the geographically significant nodes in the network. The impact of these geographically significant nodes on the local traffic behavior is demonstrated by simulation using the SUMO (Simulation of Urban Mobility) tool which is also supported by real-world empirical data, and our results indicate that the traffic speed around a particular bus stop can reach a jammed state from a free flow state due to the presence of these geographically important nodes. A comparison
A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network
Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.
2018-02-01
Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.
Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming
2015-01-01
This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919
Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming
2015-11-17
This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.
Outage Analysis and Optimization of SWIPT in Network-Coded Two-Way Relay Networks
Directory of Open Access Journals (Sweden)
Ruihong Jiang
2017-01-01
Full Text Available This paper investigates the outage performance of simultaneous wireless information and power transfer (SWIPT in network-coded two-way relay systems, where a relay first harvests energy from the signals transmitted by two sources and then uses the harvested energy to forward the received information to the two sources. We consider two transmission protocols, power splitting two-way relay (PS-TWR and time switching two-way relay (TS-TWR protocols. We present two explicit expressions for the system outage probability of the two protocols and further derive approximate expressions for them in high and low SNR cases. To explore the system performance limits, two optimization problems are formulated to minimize the system outage probability. Since the problems are nonconvex and have no known solution methods, a genetic algorithm- (GA- based algorithm is designed. Numerical and simulation results validate our theoretical analysis. It is shown that, by jointly optimizing the time assignment and SWIPT receiver parameters, a great performance gain can be achieved for both PS-TWR and TS-TWR. Moreover, the optimized PS-TWR always outperforms the optimized TS-TWR in terms of outage performance. Additionally, the effects of parameters including relay location and transmit powers are also discussed, which provide some insights for the SWIPT-enabled two-way relay networks.
Directory of Open Access Journals (Sweden)
Jian Jiao
2017-01-01
Full Text Available Space Information Network (SIN with backbone satellites relaying for vehicular network (VN communications is regarded as an effective strategy to provide diverse vehicular services in a seamless, efficient, and cost-effective manner in rural areas and highways. In this paper, we investigate the performance of SIN return channel cooperative communications via an amplify-and-forward (AF backbone satellite relaying for VN communications, where we assume that both of the source-destination and relay-destination links undergo Shadowed-Rician fading and the source-relay link follows Rician fading, respectively. In this SIN-assisted VN communication scenario, we first obtain the approximate statistical distributions of the equivalent end-to-end signal-to-noise ratio (SNR of the system. Then, we derive the closed-form expressions to efficiently evaluate the average symbol error rate (ASER of the system. Furthermore, the ASER expressions are taking into account the effect of satellite perturbation of the backbone relaying satellite, which reveal the accumulated error of the antenna pointing error. Finally, simulation results are provided to verify the accuracy of our theoretical analysis and show the impact of various parameters on the system performance.
Robustness Analysis of Real Network Topologies Under Multiple Failure Scenarios
DEFF Research Database (Denmark)
Manzano, M.; Marzo, J. L.; Calle, E.
2012-01-01
on topological characteristics. Recently approaches also consider the services supported by such networks. In this paper we carry out a robustness analysis of five real backbone telecommunication networks under defined multiple failure scenarios, taking into account the consequences of the loss of established......Nowadays the ubiquity of telecommunication networks, which underpin and fulfill key aspects of modern day living, is taken for granted. Significant large-scale failures have occurred in the last years affecting telecommunication networks. Traditionally, network robustness analysis has been focused...... connections. Results show which networks are more robust in response to a specific type of failure....
Identifying changes in the support networks of end-of-life carers using social network analysis.
Leonard, Rosemary; Horsfall, Debbie; Noonan, Kerrie
2015-06-01
End-of-life caring is often associated with reduced social networks for both the dying person and for the carer. However, those adopting a community participation and development approach, see the potential for the expansion and strengthening of networks. This paper uses Knox, Savage and Harvey's definitions of three generations social network analysis to analyse the caring networks of people with a terminal illness who are being cared for at home and identifies changes in these caring networks that occurred over the period of caring. Participatory network mapping of initial and current networks was used in nine focus groups. The analysis used key concepts from social network analysis (size, density, transitivity, betweenness and local clustering) together with qualitative analyses of the group's reflections on the maps. The results showed an increase in the size of the networks and that ties between the original members of the network strengthened. The qualitative data revealed the importance between core and peripheral network members and the diverse contributions of the network members. The research supports the value of third generation social network analysis and the potential for end-of-life caring to build social capital. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Spectral Analysis Methods of Social Networks
Directory of Open Access Journals (Sweden)
P. G. Klyucharev
2017-01-01
Full Text Available Online social networks (such as Facebook, Twitter, VKontakte, etc. being an important channel for disseminating information are often used to arrange an impact on the social consciousness for various purposes - from advertising products or services to the full-scale information war thereby making them to be a very relevant object of research. The paper reviewed the analysis methods of social networks (primarily, online, based on the spectral theory of graphs. Such methods use the spectrum of the social graph, i.e. a set of eigenvalues of its adjacency matrix, and also the eigenvectors of the adjacency matrix.Described measures of centrality (in particular, centrality based on the eigenvector and PageRank, which reflect a degree of impact one or another user of the social network has. A very popular PageRank measure uses, as a measure of centrality, the graph vertices, the final probabilities of the Markov chain, whose matrix of transition probabilities is calculated on the basis of the adjacency matrix of the social graph. The vector of final probabilities is an eigenvector of the matrix of transition probabilities.Presented a method of dividing the graph vertices into two groups. It is based on maximizing the network modularity by computing the eigenvector of the modularity matrix.Considered a method for detecting bots based on the non-randomness measure of a graph to be computed using the spectral coordinates of vertices - sets of eigenvector components of the adjacency matrix of a social graph.In general, there are a number of algorithms to analyse social networks based on the spectral theory of graphs. These algorithms show very good results, but their disadvantage is the relatively high (albeit polynomial computational complexity for large graphs.At the same time it is obvious that the practical application capacity of the spectral graph theory methods is still underestimated, and it may be used as a basis to develop new methods.The work
Grunspan, Daniel Z.; Wiggins, Benjamin L.; Goodreau, Steven M.
2014-01-01
Social interactions between students are a major and underexplored part of undergraduate education. Understanding how learning relationships form in undergraduate classrooms, as well as the impacts these relationships have on learning outcomes, can inform educators in unique ways and improve educational reform. Social network analysis (SNA)…
Directory of Open Access Journals (Sweden)
Hadeed A. Sher
2017-04-01
Full Text Available In this paper theoretical and experimental analysis of an AC–DC–AC inverter under DC link capacitor failure is presented. The failure study conducted for this paper is the open circuit of the DC link capacitor. The presented analysis incorporates the results for both single and three phase AC input. It has been observed that the higher ripple frequency provides better ride through capability for this fault. Furthermore, the effects of this fault on electrical characteristics of AC–DC–AC inverter and mechanical properties of the induction motor are also presented. Moreover, the effect of pulsating torque as a result of an open circuited DC link capacitor is also taken into consideration. Theoretical analysis is supported by computer aided simulation as well as with a real time experimental prototype.
Exploring intellectual capital through social network analysis: a conceptual framework
Directory of Open Access Journals (Sweden)
Ivana Tichá
2011-01-01
Full Text Available The purpose of this paper is to develop a framework to assess intellectual capital. Intellectual capital is a key element in an organization’s future earning potential. Theoretical and empirical studies show that it is the unique combination of the different elements of intellectual capital and tangible investments that determines an enterprise´s competitive advantage. Intellectual capital has been defined as the combination of an organization´s human, organizational and relational resources and activities. It includes the knowledge, skills, experience and abilities of the employees, its R&D activities, organizational, routines, procedures, systems, databases and its Intellectual Property Rights, as well as all the resources linked to its external relationships, such as with its customers, suppliers, R&D partners, etc. This paper focuses on the relational capital and attempts to suggest a conceptual framework to assess this part of intellectual capital applying social network analysis approach. The SNA approach allows for mapping and measuring of relationships and flows between, people, groups, organizations, computers, URLs, and other connected information/knowledge entities. The conceptual framework is developed for the assessment of collaborative networks in the Czech higher education sector as the representation of its relational capital. It also builds on the previous work aiming at proposal of methodology guiding efforts to report intellectual capital at the Czech public universities.
Sundarraj, Pradeepkumar; Taylor, Robert A.; Banerjee, Debosmita; Maity, Dipak; Sinha Roy, Susanta
2017-01-01
Hybrid solar thermoelectric generators (HSTEGs) have garnered significant research attention recently due to their potential ability to cogenerate heat and electricity. In this paper, theoretical and experimental investigations of the electrical and thermal performance of a HSTEG system are reported. In order to validate the theoretical model, a laboratory scale HSTEG system (based on forced convection cooling) is developed. The HSTEG consists of six thermoelectric generator modules, an electrical heater, and a stainless steel cooling block. Our experimental analysis shows that the HSTEG is capable of producing a maximum electrical power output of 4.7 W, an electrical efficiency of 1.2% and thermal efficiency of 61% for an average temperature difference of 92 °C across the TEG modules with a heater power input of 382 W. These experimental results of the HSTEG system are found to be in good agreement with the theoretical prediction. This experimental/theoretical analysis can also serve as a guide for evaluating the performance of the HSTEG system with forced convection cooling.
Analysis and monitoring design for networks
Energy Technology Data Exchange (ETDEWEB)
Fedorov, V.; Flanagan, D.; Rowan, T.; Batsell, S.
1998-06-01
The idea of applying experimental design methodologies to develop monitoring systems for computer networks is relatively novel even though it was applied in other areas such as meteorology, seismology, and transportation. One objective of a monitoring system should always be to collect as little data as necessary to be able to monitor specific parameters of the system with respect to assigned targets and objectives. This implies a purposeful monitoring where each piece of data has a reason to be collected and stored for future use. When a computer network system as large and complex as the Internet is the monitoring subject, providing an optimal and parsimonious observing system becomes even more important. Many data collection decisions must be made by the developers of a monitoring system. These decisions include but are not limited to the following: (1) The type data collection hardware and software instruments to be used; (2) How to minimize interruption of regular network activities during data collection; (3) Quantification of the objectives and the formulation of optimality criteria; (4) The placement of data collection hardware and software devices; (5) The amount of data to be collected in a given time period, how large a subset of the available data to collect during the period, the length of the period, and the frequency of data collection; (6) The determination of the data to be collected (for instance, selection of response and explanatory variables); (7) Which data will be retained and how long (i.e., data storage and retention issues); and (8) The cost analysis of experiments. Mathematical statistics, and, in particular, optimal experimental design methods, may be used to address the majority of problems generated by 3--7. In this study, the authors focus their efforts on topics 3--5.
6th International Conference on Network Analysis
Nikolaev, Alexey; Pardalos, Panos; Prokopyev, Oleg
2017-01-01
This valuable source for graduate students and researchers provides a comprehensive introduction to current theories and applications in optimization methods and network models. Contributions to this book are focused on new efficient algorithms and rigorous mathematical theories, which can be used to optimize and analyze mathematical graph structures with massive size and high density induced by natural or artificial complex networks. Applications to social networks, power transmission grids, telecommunication networks, stock market networks, and human brain networks are presented. Chapters in this book cover the following topics: Linear max min fairness Heuristic approaches for high-quality solutions Efficient approaches for complex multi-criteria optimization problems Comparison of heuristic algorithms New heuristic iterative local search Power in network structures Clustering nodes in random graphs Power transmission grid structure Network decomposition problems Homogeneity hypothesis testing Network analy...
Artificial neural network for violation analysis
International Nuclear Information System (INIS)
Zhang, Z.; Polet, P.; Vanderhaegen, F.; Millot, P.
2004-01-01
Barrier removal (BR) is a safety-related violation, and it can be analyzed in terms of benefits, costs, and potential deficits. In order to allow designers to integrate BR into the risk analysis during the initial design phase or during re-design work, we propose a connectionist method integrating self-organizing maps (SOM). The basic SOM is an artificial neural network that, on the basis of the information contained in a multi-dimensional space, generates a space of lesser dimensions. Three algorithms--Unsupervised SOM, Supervised SOM, and Hierarchical SOM--have been developed to permit BR classification and prediction in terms of the different criteria. The proposed method can be used, on the one hand, to foresee/predict the possibility level of a new/changed barrier (prospective analysis), and on the other hand, to synthetically regroup/rearrange the BR of a given human-machine system (retrospective analysis). We applied this method to the BR analysis of an experimental railway simulator, and our preliminary results are presented here
Indications of marine bioinvasion from network theory. An analysis of the global cargo ship network
Kölzsch, A.; Blasius, B.
2011-01-01
The transport of huge amounts of small aquatic organisms in the ballast tanks and at the hull of large cargo ships leads to ever increasing rates of marine bioinvasion. In this study, we apply a network theoretic approach to examine the introduction of invasive species into new ports by global
Directory of Open Access Journals (Sweden)
Aracy ERNST-PEREIRA
2014-12-01
Full Text Available From the analysis of the front cover of the magazine Época – awarded the best Brazilian magazine cover of 2010 by the Associação Nacional dos Editores de Revista (ANER –, this article aims at a double goal: to propose a reflection on the image status within the Discourse Analysis based on Pêcheux’s theory and to develop an exercise in applying theoretical concepts to the verbal and visual materiality, chiefly those related to the discursive sequences (that we adapt to discursive sections and to the visual statements. With this goal in mind, we start at a the theoretical level from a conceptual proposition of conceiving of image with grounds on the principles of French Discourse Analysis and at an analytical level from the analysis of strangeness as a clue (as developed by Ernst-Pereira to problematize the image in its opacity, that is, by means of a game of visibilities and invisibilities formed by the conditions of production of the discourses that materialize in that image. In the present case, given its specificity, we still consider in theoretical and analytical terms reading of the image managed by the verbal dimension.
The analysis of time-resolved optically stimulated luminescence: I. Theoretical considerations
International Nuclear Information System (INIS)
Chithambo, M L
2007-01-01
This is the first of two linked papers on the analysis of time-resolved optically stimulated luminescence. This paper focusses on a theoretical basis of analytical methods and on methods for interpretation of time-resolved luminescence spectra and calculation of luminescence throughput. Using a comparative analysis of the principal features of time-resolved luminescence and relevant analogues from steady state optical stimulation, formulae for configuring a measurement system for optimum performance are presented. We also examine the possible use of stretched-exponential functions for analysis of time-resolved optically stimulated luminescence spectra
Theoretical study on X-Ray Fluorescence Analysis: Contribution of the self-excitation phenomenon
International Nuclear Information System (INIS)
RAKOTONDRAJAONA, H.N.J.L.
1999-01-01
This work consist in setting up, firstly, fluorescence intensities due to the contribution of secondary and tertiary excitation phenomena which settle among the elements of the same sample during the analysis through X fluorescence, inspired by Sherman calculations. Secondly, we have experimentally checked these expression from the analysis of twelve samples; containing all the following elements: Iron, Copper and Zinc. The difference between the theoretical results and the experimental results has been valued from the formula of the test of χ 2 . We consider that this difference is noticeable compared to other errors due to analysis method. [fr
The Design and Analysis of Virtual Network Configuration for a Wireless Mobile ATM Network
Bush, Stephen F.
1999-01-01
This research concentrates on the design and analysis of an algorithm referred to as Virtual Network Configuration (VNC) which uses predicted future states of a system for faster network configuration and management. VNC is applied to the configuration of a wireless mobile ATM network. VNC is built on techniques from parallel discrete event simulation merged with constraints from real-time systems and applied to mobile ATM configuration and handoff. Configuration in a mobile network is a dyna...
Analysis of robustness of urban bus network
Tao, Ren; Yi-Fan, Wang; Miao-Miao, Liu; Yan-Jie, Xu
2016-02-01
In this paper, the invulnerability and cascade failures are discussed for the urban bus network. Firstly, three static models(bus stop network, bus transfer network, and bus line network) are used to analyse the structure and invulnerability of urban bus network in order to understand the features of bus network comprehensively. Secondly, a new way is proposed to study the invulnerability of urban bus network by modelling two layered networks, i.e., the bus stop-line network and the bus line-transfer network and then the interactions between different models are analysed. Finally, by modelling a new layered network which can reflect the dynamic passenger flows, the cascade failures are discussed. Then a new load redistribution method is proposed to study the robustness of dynamic traffic. In this paper, the bus network of Shenyang City which is one of the biggest cities in China, is taken as a simulation example. In addition, some suggestions are given to improve the urban bus network and provide emergency strategies when traffic congestion occurs according to the numerical simulation results. Project supported by the National Natural Science Foundation of China (Grant Nos. 61473073, 61374178, 61104074, and 61203329), the Fundamental Research Funds for the Central Universities (Grant Nos. N130417006, L1517004), and the Program for Liaoning Excellent Talents in University (Grant No. LJQ2014028).
Theoretical Proposal for Pragmatic-Rhetorical Analysis of Argument in the Tourist Guide
Directory of Open Access Journals (Sweden)
MSc. Iliana Rosabal-Pérez
2015-10-01
Full Text Available The purpose of the article is to present a useful theoretical proposal for the analysis of argumentation within the guidebook genre. The study perspective is supported on the rhetorical-pragmatic perspective of argumentation provided by some authors as well as the theoretical models applied to the study of persuasion in guidebooks suggested by Adam/Bonhomme (1997, Hernández-Santaolalla and Cobo-Durán (2010. The analysis of argumentation in this kind of text must consider a tactical and strategic view of the rhetorical actions; that is to say, not to abstain from the elocution traditional examination since argumentation is an essential devise obtainable in the whole test. Keywords: rhetorical, argumentation, guidebook, rhetorical operations, topical.
Theoretical analysis of two ACO approaches for the traveling salesman problem
DEFF Research Database (Denmark)
Kötzing, Timo; Neumann, Frank; Röglin, Heiko
2012-01-01
Bioinspired algorithms, such as evolutionary algorithms and ant colony optimization, are widely used for different combinatorial optimization problems. These algorithms rely heavily on the use of randomness and are hard to understand from a theoretical point of view. This paper contributes...... to the theoretical analysis of ant colony optimization and studies this type of algorithm on one of the most prominent combinatorial optimization problems, namely the traveling salesperson problem (TSP). We present a new construction graph and show that it has a stronger local property than one commonly used...... for constructing solutions of the TSP. The rigorous runtime analysis for two ant colony optimization algorithms, based on these two construction procedures, shows that they lead to good approximation in expected polynomial time on random instances. Furthermore, we point out in which situations our algorithms get...
Theoretical analysis of stack gas emission velocity measurement by optical scintillation
International Nuclear Information System (INIS)
Yang Yang; Dong Feng-Zhong; Ni Zhi-Bo; Pang Tao; Zeng Zong-Yong; Wu Bian; Zhang Zhi-Rong
2014-01-01
Theoretical analysis for an online measurement of the stack gas flow velocity based on the optical scintillation method with a structure of two parallel optical paths is performed. The causes of optical scintillation in a stack are first introduced. Then, the principle of flow velocity measurement and its mathematical expression based on cross correlation of the optical scintillation are presented. The field test results show that the flow velocity measured by the proposed technique in this article is consistent with the value tested by the Pitot tube. It verifies the effectiveness of this method. Finally, by use of the structure function of logarithmic light intensity fluctuations, the theoretical explanation of optical scintillation spectral characteristic in low frequency is given. The analysis of the optical scintillation spectrum provides the basis for the measurement of the stack gas flow velocity and particle concentration simultaneously. (general)
Theoretical analysis of moiré fringe multiplication under a scanning electron microscope
International Nuclear Information System (INIS)
Li, Yanjie; Xie, Huimin; Chen, Pengwan; Zhang, Qingming
2011-01-01
In this study, theoretical analysis and experimental verification of fringe multiplication under a scanning electron microscope (SEM) are presented. Fringe multiplication can be realized by enhancing the magnification or the number of scanning lines under the SEM. A universal expression of the pitch of moiré fringes is deduced. To apply this method to deformation measurement, the calculation formulas of strain and displacement are derived. Compared to natural moiré, the displacement sensitivity is increased by fringe multiplication while the strain sensitivity may be retained or enhanced depending on the number of scanning lines used. The moiré patterns are formed by the interference of a 2000 lines mm −1 grating with the scanning lines of SEM, and the measured parameters of moiré fringes from experimental results agree well with theoretical analysis
Abnormal brain white matter network in young smokers: a graph theory analysis study.
Zhang, Yajuan; Li, Min; Wang, Ruonan; Bi, Yanzhi; Li, Yangding; Yi, Zhang; Liu, Jixin; Yu, Dahua; Yuan, Kai
2018-04-01
Previous diffusion tensor imaging (DTI) studies had investigated the white matter (WM) integrity abnormalities in some specific fiber bundles in smokers. However, little is known about the changes in topological organization of WM structural network in young smokers. In current study, we acquired DTI datasets from 58 male young smokers and 51 matched nonsmokers and constructed the WM networks by the deterministic fiber tracking approach. Graph theoretical analysis was used to compare the topological parameters of WM network (global and nodal) and the inter-regional fractional anisotropy (FA) weighted WM connections between groups. The results demonstrated that both young smokers and nonsmokers had small-world topology in WM network. Further analysis revealed that the young smokers exhibited the abnormal topological organization, i.e., increased network strength, global efficiency, and decreased shortest path length. In addition, the increased nodal efficiency predominately was located in frontal cortex, striatum and anterior cingulate gyrus (ACG) in smokers. Moreover, based on network-based statistic (NBS) approach, the significant increased FA-weighted WM connections were mainly found in the PFC, ACG and supplementary motor area (SMA) regions. Meanwhile, the network parameters were correlated with the nicotine dependence severity (FTND) scores, and the nodal efficiency of orbitofrontal cortex was positive correlation with the cigarette per day (CPD) in young smokers. We revealed the abnormal topological organization of WM network in young smokers, which may improve our understanding of the neural mechanism of young smokers form WM topological organization level.
Method and tool for network vulnerability analysis
Swiler, Laura Painton [Albuquerque, NM; Phillips, Cynthia A [Albuquerque, NM
2006-03-14
A computer system analysis tool and method that will allow for qualitative and quantitative assessment of security attributes and vulnerabilities in systems including computer networks. The invention is based on generation of attack graphs wherein each node represents a possible attack state and each edge represents a change in state caused by a single action taken by an attacker or unwitting assistant. Edges are weighted using metrics such as attacker effort, likelihood of attack success, or time to succeed. Generation of an attack graph is accomplished by matching information about attack requirements (specified in "attack templates") to information about computer system configuration (contained in a configuration file that can be updated to reflect system changes occurring during the course of an attack) and assumed attacker capabilities (reflected in "attacker profiles"). High risk attack paths, which correspond to those considered suited to application of attack countermeasures given limited resources for applying countermeasures, are identified by finding "epsilon optimal paths."
Network-Based Visual Analysis of Tabular Data
Liu, Zhicheng
2012-01-01
Tabular data is pervasive in the form of spreadsheets and relational databases. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look…
Analysis of Computer Network Information Based on "Big Data"
Li, Tianli
2017-11-01
With the development of the current era, computer network and large data gradually become part of the people's life, people use the computer to provide convenience for their own life, but at the same time there are many network information problems has to pay attention. This paper analyzes the information security of computer network based on "big data" analysis, and puts forward some solutions.
Road Transport Network Analysis In Port-Harcourt Metropolics ...
African Journals Online (AJOL)
Road transport network contributes to the economy of an area as it connects points of origin to destinations. The thrust of this article therefore, is on the analysis of the road networks in Port – Harcourt metropolis with the aim of determining the connectivity of the road networks and the most accessible node. Consequently ...
Fortuna, Cinira Magali; Mesquita, Luana Pinho de; Matumoto, Silvia; Monceau, Gilles
2016-09-19
This qualitative study is based on institutional analysis as the methodological theoretical reference with the objective of analyzing researchers' implication during a research-intervention and the interferences caused by this analysis. The study involved researchers from courses in medicine, nursing, and dentistry at two universities and workers from a Regional Health Department in follow-up on the implementation of the Stork Network in São Paulo State, Brazil. The researchers worked together in the intervention and in analysis workshops, supported by an external institutional analysis. Two institutions stood out in the analysis: the research, established mainly with characteristics of neutrality, and management, with Taylorist characteristics. Differences between researchers and difficulties in identifying actions proper to network management and research were some of the interferences that were identified. The study concludes that implication analysis is a powerful tool for such studies.
Tavakoli Taba, Seyedamir; Hossain, Liaquat; Heard, Robert; Brennan, Patrick; Lee, Warwick; Lewis, Sarah
2017-03-01
Rationale and objectives: Observer performance has been widely studied through examining the characteristics of individuals. Applying a systems perspective, while understanding of the system's output, requires a study of the interactions between observers. This research explains a mixed methods approach to applying a social network analysis (SNA), together with a more traditional approach of examining personal/ individual characteristics in understanding observer performance in mammography. Materials and Methods: Using social networks theories and measures in order to understand observer performance, we designed a social networks survey instrument for collecting personal and network data about observers involved in mammography performance studies. We present the results of a study by our group where 31 Australian breast radiologists originally reviewed 60 mammographic cases (comprising of 20 abnormal and 40 normal cases) and then completed an online questionnaire about their social networks and personal characteristics. A jackknife free response operating characteristic (JAFROC) method was used to measure performance of radiologists. JAFROC was tested against various personal and network measures to verify the theoretical model. Results: The results from this study suggest a strong association between social networks and observer performance for Australian radiologists. Network factors accounted for 48% of variance in observer performance, in comparison to 15.5% for the personal characteristics for this study group. Conclusion: This study suggest a strong new direction for research into improving observer performance. Future studies in observer performance should consider social networks' influence as part of their research paradigm, with equal or greater vigour than traditional constructs of personal characteristics.
Characteristics of a micro-fin evaporator: Theoretical analysis and experimental verification
Zheng Hui-Fan; Fan Xiao-Wei; Wang Fang; Liang Yao-Hua
2013-01-01
A theoretical analysis and experimental verification on the characteristics of a micro-fin evaporator using R290 and R717 as refrigerants were carried out. The heat capacity and heat transfer coefficient of the micro-fin evaporator were investigated under different water mass flow rate, different refrigerant mass flow rate, and different inner tube diameter of micro-fin evaporator. The simulation results of the heat transfer coefficient are fairly in good a...
S Walby
1994-01-01
The aim in this paper is to contribute to the development of a research agenda for the comparative analysis of gender relations in Western Europe. Its focus is the clarification of the methodological and theoretical issues involved. Several different indices of gender inequality are assessed. It is argued that it is important to distinguish between the form and degree of patriarchy, rather than assuming that these are closely associated. Data from the EC and Scandinavia are used to illustrate...
An exploratory game-theoretic analysis of biomass electricity generation supply chain
International Nuclear Information System (INIS)
Nasiri, Fuzhan; Zaccour, Georges
2009-01-01
This study proposes a game-theoretic approach to model and analyze the process of utilizing biomass for power generation considering three players: distributor, facility developer, and participating farmer. We characterize the Nash equilibrium of the sequential game and discuss its features. A special attention is devoted to the analysis of the impact of incentives and initial target on the equilibrium, in which the biomass is part of electricity production.
Almquist, Zack W.; Butts, Carter T.
2013-01-01
Methods for analysis of network dynamics have seen great progress in the past decade. This article shows how Dynamic Network Logistic Regression techniques (a special case of the Temporal Exponential Random Graph Models) can be used to implement decision theoretic models for network dynamics in a panel data context. We also provide practical heuristics for model building and assessment. We illustrate the power of these techniques by applying them to a dynamic blog network sampled during the 2...
Directory of Open Access Journals (Sweden)
Wingender Edgar
2008-05-01
Full Text Available Abstract Background Currently, there is a gap between purely theoretical studies of the topology of large bioregulatory networks and the practical traditions and interests of experimentalists. While the theoretical approaches emphasize the global characterization of regulatory systems, the practical approaches focus on the role of distinct molecules and genes in regulation. To bridge the gap between these opposite approaches, one needs to combine 'general' with 'particular' properties and translate abstract topological features of large systems into testable functional characteristics of individual components. Here, we propose a new topological parameter – the pairwise disconnectivity index of a network's element – that is capable of such bridging. Results The pairwise disconnectivity index quantifies how crucial an individual element is for sustaining the communication ability between connected pairs of vertices in a network that is displayed as a directed graph. Such an element might be a vertex (i.e., molecules, genes, an edge (i.e., reactions, interactions, as well as a group of vertices and/or edges. The index can be viewed as a measure of topological redundancy of regulatory paths which connect different parts of a given network and as a measure of sensitivity (robustness of this network to the presence (absence of each individual element. Accordingly, we introduce the notion of a path-degree of a vertex in terms of its corresponding incoming, outgoing and mediated paths, respectively. The pairwise disconnectivity index has been applied to the analysis of several regulatory networks from various organisms. The importance of an individual vertex or edge for the coherence of the network is determined by the particular position of the given element in the whole network. Conclusion Our approach enables to evaluate the effect of removing each element (i.e., vertex, edge, or their combinations from a network. The greatest potential value of
Energy Technology Data Exchange (ETDEWEB)
Jarjis, J; Galiana, F D
1980-03-01
A set theoretic analysis of loadflow feasibility of a general power network with arbitrary PQ, PV and slack buses is presented. Load-flow feasibility is that property of a power network defining the theoretical limitations on the bus injections under which a steady state equilibrium exists. The set theoretic analysis is based on the study of the conical loadflow feasibility region. This region is characterised by a set of supporting hyperplanes each of which defines an explicit necessary condition for loadflow feasibility on the bus injections. A quantitative measure of loadflow feasibility for an arbitrary given operating injection vector is defined through a computable scalar stability margin. This stability margin permits the loadflow feasibility of different injections and network structures to be quantitatively compared and analysed.
Analysis of Municipal Pipe Network Franchise Institution
Yong, Sun; Haichuan, Tian; Feng, Xu; Huixia, Zhou
Franchise institution of municipal pipe network has some particularity due to the characteristic of itself. According to the exposition of Chinese municipal pipe network industry franchise institution, the article investigates the necessity of implementing municipal pipe network franchise institution in China, the role of government in the process and so on. And this offers support for the successful implementation of municipal pipe network franchise institution in China.
Advanced functional network analysis in the geosciences: The pyunicorn package
Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen
2013-04-01
Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.
Agrawal, L.; Bhardwaj, A.; Pal, S.; Kumar, A.
2007-11-01
This article presents the results of a detailed theoretical and experimental analysis carried out on a folded Z-shaped polarization coupled, electro-optically Q-switched laser resonator with Porro prisms and waveplates. The advantages of adding waveplates in a Porro prism resonator have been explored for creating high loss condition prior to Q-switching and obtaining variable reflectivity with fixed orientation of Porro prism. Generalized expressions have been derived in terms of azimuth angles and phase shifts introduced by the polarizing elements. These expressions corroborate with known reported results under appropriate substitutions. A specific case of a crossed Porro prism diode-pumped Nd:YAG laser has been theoretically and experimentally investigated. In the feedback arm, a 0.57λ waveplate oriented at 135° completely compensates the phase shift of a fused silica Porro prism and provides better tolerances than a BK-7 prism/0.60λ waveplate combination to stop prelasing. The fused silica prism/0.57λ combination with waveplate at 112° acts like a 100% mirror and was utilized for optimization of free running performance. The effective reflectivity was determined for various orientations of the quarter waveplate in the gain arm to numerically estimate the Q-switched laser pulse parameters through rate equation analysis. Experimental results match well with the theoretical analysis.
Au36(SePh)24 nanomolecules: synthesis, optical spectroscopy and theoretical analysis.
Rambukwella, Milan; Chang, Le; Ravishanker, Anish; Fortunelli, Alessandro; Stener, Mauro; Dass, Amala
2018-05-16
Here, we report the synthesis of selenophenol (HSePh) protected Au36(SePh)24 nanomolecules via a ligand-exchange reaction of 4-tert-butylbenzenethiol (HSPh-tBu) protected Au36(SPh-tBu)24 with selenophenol, and its spectroscopic and theoretical analysis. Matrix assisted laser desorption ionization (MALDI) mass spectrometry, electrospray ionization (ESI) mass spectrometry and optical characterization confirm that the composition of the as synthesized product is predominantly Au36(SePh)24 nanomolecules. Size exclusion chromatography (SEC) was employed to isolate the Au36(SePh)24 and temperature dependent optical absorption studies and theoretical analysis were performed. Theoretically, an Independent Component Maps of Oscillator Strength (ICM-OS) analysis of simulated spectra shows that the enhancement in absorption intensity in Au36(SePh)24 with respect to Au36(SPh)24 can be ascribed to the absence of interference and/or increased long-range coupling between interband metal core and ligand excitations. This work demonstrates and helps to understand the effect of Au-Se bridging on the properties of gold nanomolecules.
Analysis of neural networks through base functions
van der Zwaag, B.J.; Slump, Cornelis H.; Spaanenburg, L.
Problem statement. Despite their success-story, neural networks have one major disadvantage compared to other techniques: the inability to explain comprehensively how a trained neural network reaches its output; neural networks are not only (incorrectly) seen as a "magic tool" but possibly even more
Synchronization analysis of coloured delayed networks under ...
Indian Academy of Sciences (India)
This paper investigates synchronization of coloured delayed networks under decentralized pinning intermittent control. To begin with, the time delays are taken into account in the coloured networks. In addition, we propose a decentralized pinning intermittent control for coloured delayed networks, which is different from that ...
A Social Network Analysis of Occupational Segregation
DEFF Research Database (Denmark)
Buhai, Ioan Sebastian; van der Leij, Marco
We develop a social network model of occupational segregation between different social groups, generated by the existence of positive inbreeding bias among individuals from the same group. If network referrals are important for job search, then expected homophily in the contact network structure...
Pareto distance for multi-layer network analysis
DEFF Research Database (Denmark)
Magnani, Matteo; Rossi, Luca
2013-01-01
services, e.g., Facebook, Twitter, LinkedIn and Foursquare. As a result, the analysis of on-line social networks requires a wider scope and, more technically speaking, models for the representation of this fragmented scenario. The recent introduction of more realistic layered models has however determined......Social Network Analysis has been historically applied to single networks, e.g., interaction networks between co-workers. However, the advent of on-line social network sites has emphasized the stratified structure of our social experience. Individuals usually spread their identities over multiple...
Theoretical analysis of recirculation zone and buffer zone in the ADS windowless spallation target
International Nuclear Information System (INIS)
Liu, Jie; Pan, Chang-zhao; Tong, Jian-fei; Lu, Wen-qiang
2015-01-01
Highlights: • Height of recirculation zone is very important in windowless target design. • A theoretical formula for the height is derived based on the Bernoulli equation. • Numerical simulation for the LBE is performed and the height of recirculation zone is also obtained. • The theoretically-derived simulation-predicted recirculation zone heights agree with each other very well and the theoretical derivation is proved to be correct. - Abstract: The thermo-hydraulic analysis including reduction of the height of recirculation zone and stability of the free surface is very important in the design and optimization of ADS windowless spallation targets. In the present study, the Bernoulli equation is used to analyze the entire flow process in the target. Formulae for the height of the recirculation zone and the buffer zone are both obtained explicitly. Furthermore, numerical simulation for the heavy metal lead–bismuth eutectic liquid and vapor with cavitation phase change is also performed, and a novel method to calculate the height of the recirculation zone is put forward. By comparison of the theoretical formulae and numerical results, it is clearly shown that they agree with each other very well, and the heights predicted by the two methods are both determined by their own upstream flow parameters
An asymptotic analysis of closed queueing networks with branching populations
Bayer, N.; Coffman, E.G.; Kogan, Y.A.
1995-01-01
textabstractClosed queueing networks have proven to be valuable tools for system performance analysis. In this paper, we broaden the applications of such networks by incorporating populations of {em branching customers: whenever a customer completes service at some node of the network, it is replaced by N>=0 customers, each routed independently to a next node, where N has a given, possibly node-dependent branching distribution. Applications of these branching and queueing networks focus on {e...
Directory of Open Access Journals (Sweden)
Cécile Bordier
2017-08-01
Full Text Available Neuroimaging data can be represented as networks of nodes and edges that capture the topological organization of the brain connectivity. Graph theory provides a general and powerful framework to study these networks and their structure at various scales. By way of example, community detection methods have been widely applied to investigate the modular structure of many natural networks, including brain functional connectivity networks. Sparsification procedures are often applied to remove the weakest edges, which are the most affected by experimental noise, and to reduce the density of the graph, thus making it theoretically and computationally more tractable. However, weak links may also contain significant structural information, and procedures to identify the optimal tradeoff are the subject of active research. Here, we explore the use of percolation analysis, a method grounded in statistical physics, to identify the optimal sparsification threshold for community detection in brain connectivity networks. By using synthetic networks endowed with a ground-truth modular structure and realistic topological features typical of human brain functional connectivity networks, we show that percolation analysis can be applied to identify the optimal sparsification threshold that maximizes information on the networks' community structure. We validate this approach using three different community detection methods widely applied to the analysis of brain connectivity networks: Newman's modularity, InfoMap and Asymptotical Surprise. Importantly, we test the effects of noise and data variability, which are critical factors to determine the optimal threshold. This data-driven method should prove particularly useful in the analysis of the community structure of brain networks in populations characterized by different connectivity strengths, such as patients and controls.
Data Farming Process and Initial Network Analysis Capabilities
Directory of Open Access Journals (Sweden)
Gary Horne
2016-01-01
Full Text Available Data Farming, network applications and approaches to integrate network analysis and processes to the data farming paradigm are presented as approaches to address complex system questions. Data Farming is a quantified approach that examines questions in large possibility spaces using modeling and simulation. It evaluates whole landscapes of outcomes to draw insights from outcome distributions and outliers. Social network analysis and graph theory are widely used techniques for the evaluation of social systems. Incorporation of these techniques into the data farming process provides analysts examining complex systems with a powerful new suite of tools for more fully exploring and understanding the effect of interactions in complex systems. The integration of network analysis with data farming techniques provides modelers with the capability to gain insight into the effect of network attributes, whether the network is explicitly defined or emergent, on the breadth of the model outcome space and the effect of model inputs on the resultant network statistics.
THEORETICAL AND METHODOLOGICAL PRINCIPLES OF THE STRATEGIC FINANCIAL ANALYSIS OF CAPITAL
Directory of Open Access Journals (Sweden)
Olha KHUDYK
2016-07-01
Full Text Available The article is devoted to the theoretical and methodological principles of strategic financial analysis of capital. The necessity of strategic financial analysis of capital as a methodological basis for study strategies is proved in modern conditions of a high level of dynamism, uncertainty and risk. The methodological elements of the strategic financial analysis of capital (the object of investigation, the indicators, the factors, the methods of study, the subjects of analysis, the sources of incoming and outgoing information are justified in the system of financial management, allowing to improve its theoretical foundations. It is proved that the strategic financial analysis of capital is a continuous process, carried out in an appropriate sequence at each stage of capital circulation. The system of indexes is substantiated, based on the needs of the strategic financial analysis. The classification of factors determining the size and structure of company’s capital is grounded. The economic nature of capital of the company is clarified. We consider that capital is a stock of economic resources in the form of cash, tangible and intangible assets accumulated by savings, which is used by its owner as a factor of production and investment resource in the economic process in order to obtain profit, to ensure the growth of owners’ prosperity and to achieve social effect.
Sekkar, Venkataraman; Alex, Ancy Smitha; Kumar, Vijendra; Bandyopadhyay, G. G.
2018-01-01
Polyurethane networks between hydroxyl terminated polybutadiene (HTPB) and butanediol (BD) were prepared using toluene diisocyanate (TDI) as the curative. HTPB and BD were taken at equivalent ratios viz.: 1:0, 1:1, 1:2, 1:4, and 1:8. Crosslink density (CLD) was theoretically calculated using α-model equations developed by Marsh. CLD for the polyurethane networks was experimentally evaluated from equilibrium swell and stress-strain data. Young's modulus and Mooney-Rivlin approaches were adopted to calculate CLD from stress-strain data. Experimentally obtained CLD values were enormously higher than theoretical values especially at higher BD/HTPB equivalent ratios. The difference in the theoretical and experimental values for CLD was explained in terms of local crystallization due to the formation of hard segments and hydrogen bonded interactions.
Characterizing Social Interaction in Tobacco-Oriented Social Networks: An Empirical Analysis
Liang, Yunji; Zheng, Xiaolong; Zeng, Daniel Dajun; Zhou, Xingshe; Leischow, Scott James; Chung, Wingyan
2015-01-01
Social media is becoming a new battlefield for tobacco ?wars?. Evaluating the current situation is very crucial for the advocacy of tobacco control in the age of social media. To reveal the impact of tobacco-related user-generated content, this paper characterizes user interaction and social influence utilizing social network analysis and information theoretic approaches. Our empirical studies demonstrate that the exploding pro-tobacco content has long-lasting effects with more active users a...
Privacy Breach Analysis in Social Networks
Nagle, Frank
This chapter addresses various aspects of analyzing privacy breaches in social networks. We first review literature that defines three types of privacy breaches in social networks: interactive, active, and passive. We then survey the various network anonymization schemes that have been constructed to address these privacy breaches. After exploring these breaches and anonymization schemes, we evaluate a measure for determining the level of anonymity inherent in a network graph based on its topological structure. Finally, we close by emphasizing the difficulty of anonymizing social network data while maintaining usability for research purposes and offering areas for future work.
Deep Learning Neural Networks and Bayesian Neural Networks in Data Analysis
Directory of Open Access Journals (Sweden)
Chernoded Andrey
2017-01-01
Full Text Available Most of the modern analyses in high energy physics use signal-versus-background classification techniques of machine learning methods and neural networks in particular. Deep learning neural network is the most promising modern technique to separate signal and background and now days can be widely and successfully implemented as a part of physical analysis. In this article we compare Deep learning and Bayesian neural networks application as a classifiers in an instance of top quark analysis.
Understanding rapid theoretical change in particle physics: a month-by-month co-citation analysis
International Nuclear Information System (INIS)
Sullivan, D.; Koester, D.; White, D.H.; Kern, R.
1979-01-01
While co-citation analysis has proved a powerful tool in the study of changes in intellectual foci in science, no one has ever used the technique to study very rapid changes in the theoretical structure of a scientific field. This paper presents month-by-month co-citation analyses of key phases in the weak-electromagnetic unification research program within particle physics, and shows that these analyses capture and illuminate very rapid intellectual changes. These data provide yet another illustration of the utility of co-citation analysis for understanding the history of science. 8 figures
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.
Mallik, Mrinmay Kumar
2018-02-07
Biological networks can be analyzed using "Centrality Analysis" to identify the more influential nodes and interactions in the network. This study was undertaken to create and visualize a biological network comprising of protein-protein interactions (PPIs) amongst proteins which are preferentially over-expressed in glioma cancer stem cell component (GCSC) of glioblastomas as compared to the glioma non-stem cancer cell (GNSC) component and then to analyze this network through centrality analyses (CA) in order to identify the essential proteins in this network and their interactions. In addition, this study proposes a new centrality analysis method pertaining exclusively to transcription factors (TFs) and interactions amongst them. Moreover the relevant molecular functions, biological processes and biochemical pathways amongst these proteins were sought through enrichment analysis. A protein interaction network was created using a list of proteins which have been shown to be preferentially expressed or over-expressed in GCSCs isolated from glioblastomas as compared to the GNSCs. This list comprising of 38 proteins, created using manual literature mining, was submitted to the Reactome FIViz tool, a web based application integrated into Cytoscape, an open source software platform for visualizing and analyzing molecular interaction networks and biological pathways to produce the network. This network was subjected to centrality analyses utilizing ranked lists of six centrality measures using the FIViz application and (for the first time) a dedicated centrality analysis plug-in ; CytoNCA. The interactions exclusively amongst the transcription factors were nalyzed through a newly proposed centrality analysis method called "Gene Expression Associated Degree Centrality Analysis (GEADCA)". Enrichment analysis was performed using the "network function analysis" tool on Reactome. The CA was able to identify a small set of proteins with consistently high centrality ranks that
Classification of Networks in Higher Education: A Marketing Analysis of the Club of Ten (Russia
Directory of Open Access Journals (Sweden)
Irina V.
2018-03-01
Full Text Available Introduction: the networking as a development practice in business has not yet become widespread. Moreover, there are very few studies of network interactions in the field of science and education. Advances in marketing evaluation of network entities are very rare. The goal of this article is to develop methodological criteria for such an assessment. These methods were tested on findings from the network partnership established by federal universities in Russia. Materials and Methods: to study and generalise real-world experience, a case study method was used, which the authors understand as an empirical research method aimed at studying phenomena in real time and in the context of real life. Results: the authors proposed a comprehensive methodology for estimation of networks. The application of this method of analysis enabled identification of the key problems and barriers to the implementation of the project. One of the main problems is the lack of marketing analysis, lack of understanding of its target audience, and, accordingly, the lack of a transparent vision of development. Besides, the authors have developed a classification of network partnerships. Тhe analysis empowers classification of the network of Russian universities as an inter-organisational polycentric partnership of a quasi-integration type, based on a neoclassical contract with relational elements. The analysis of the network development has revealed significant deviations of the results from the initially claimed ones. Discussion and Conclusions: the theoretical significance of the work consists in the application of the network theory to an atypical object for the economic theory, i.e. the analysis of the sphere of higher education. Practical significance lies in the possibility of application of results obtained through real projects in real-time mode. The results of the study are applicable to educational systems for practically all countries with a transition type of
A network of spiking neurons that can represent interval timing: mean field analysis.
Gavornik, Jeffrey P; Shouval, Harel Z
2011-04-01
Despite the vital importance of our ability to accurately process and encode temporal information, the underlying neural mechanisms are largely unknown. We have previously described a theoretical framework that explains how temporal representations, similar to those reported in the visual cortex, can form in locally recurrent cortical networks as a function of reward modulated synaptic plasticity. This framework allows networks of both linear and spiking neurons to learn the temporal interval between a stimulus and paired reward signal presented during training. Here we use a mean field approach to analyze the dynamics of non-linear stochastic spiking neurons in a network trained to encode specific time intervals. This analysis explains how recurrent excitatory feedback allows a network structure to encode temporal representations.
Network Analysis Approach to Stroke Care and Assistance Provision: An Empirical Study
Directory of Open Access Journals (Sweden)
Szczygiel Nina
2017-06-01
Full Text Available To model and analyse stroke care and assistance provision in the Portuguese context from the network perspective. We used the network theory as a theoretical foundation for the study. The model proposed by Frey et al. (2006 was used to elicit and comprehend possible interactions and relations between organisations expected to be involved in the provision of care and assistance to stroke patients in their pathway to rehabilitation. Providers were identified and contacted to evaluate the nature and intensity of relationships. Network analysis was performed with the NodeXL software package. Analysis of 509 entities based on about 260 000 entries indicates that stroke care provision in the evaluated context is best captured in the coalition-collaboration setting, which appears to best demonstrate the character of the network. Information from analysis of the collaboration stage was not sufficient to determine the network dynamics. Application of the network theory to understand interorganisational dynamics of the complex health care context. Empirical validation of the model proposed by Frey et al. (2006 in terms of its operationalisation and the way it actually reflects the practical context. Examination and analysis of interorganisational relationships and its contribution to management of compound health care context involving actors from various sectors.
THEORETICAL AND METHODOLOGICAL PRINCIPLES OF THE STRATEGIC FINANCIAL ANALYSIS OF CAPITAL
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Olha KHUDYK
2016-07-01
Full Text Available The article is devoted to the theoretical and methodological principles of strategic financial analysis of capital. The necessity of strategic financial analysis of capital as a methodological basis for study strategies is proved in modern conditions of a high level of dynamism, uncertainty and risk. The methodological elements of the strategic indicators, the factors, the methods of study, the subjects of analysis, the sources of incoming and outgoing information are justified in the system of financial management, allowing to improve its theoretical foundations. It is proved that the strategic financial analysis of capital is a continuous process, carried out in an appropriate sequence at each stage of capital circulation. The system of indexes is substantiated, based on the needs of the strategic financial analysis. The classification of factors determining the size and structure of company’s capital is grounded. The economic nature of capital of the company is clarified. We consider that capital is a stock of economic resources in the form of cash, tangible and intangible assets accumulated by savings, which is used by its owner as a factor of production and investment resource in the economic process in order to obtain profit, to ensure the growth of owners’ prosperity and to achieve social effect.
State of the art applications of social network analysis
Can, Fazli; Polat, Faruk
2014-01-01
Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user
Network analysis and synthesis a modern systems theory approach
Anderson, Brian D O
2006-01-01
Geared toward upper-level undergraduates and graduate students, this book offers a comprehensive look at linear network analysis and synthesis. It explores state-space synthesis as well as analysis, employing modern systems theory to unite the classical concepts of network theory. The authors stress passive networks but include material on active networks. They avoid topology in dealing with analysis problems and discuss computational techniques. The concepts of controllability, observability, and degree are emphasized in reviewing the state-variable description of linear systems. Explorations
Theoretical analysis of ridge gratings for long-range surface plasmon polaritons
DEFF Research Database (Denmark)
Søndergaard, Thomas; Bozhevolnyi, Sergey I.; Boltasseva, Alexandra
2006-01-01
Optical properties of ridge gratings for long-range surface plasmon polaritons (LRSPPs) are analyzed theoretically in a two-dimensional configuration via the Lippmann-Schwinger integral equation method. LRSPPs being supported by a thin planar gold film embedded in dielectric are considered...... to be scattered by an array of equidistant gold ridges on each side of the film designed for in-plane Bragg scattering of LRSPPs at the wavelength ~1550 nm. Out-of-plane scattering (OUPS), LRSPP transmission, reflection, and absorption are investigated with respect to the wavelength, the height of the ridges...... peak it is preferable to use longer gratings with smaller ridges compared to gratings with larger ridges, because the former result in a smaller OUPS from the grating facets than the latter. The theoretical analysis and its conclusions are supported with experimental results on the LRSPP reflection...
Theoretical and simulation analysis of piezoelectric liquid resistance captor filled with pipeline
Zheng, Li; Zhigang, Yang; Junwu, Kan; Lisheng; Bo, Yan; Dan, Lu
2018-03-01
This paper designs a kind of Piezoelectric liquid resistance capture energy device, by using the superposition theory of the sheet deformation, the calculation model of the displacement curve of the circular piezoelectric vibrator and the power generation capacity under the concentrated load is established. The results show that the radius ratio, thickness ratio and Young’s modulus of the circular piezoelectric vibrator have greater influence on the power generation capacity. When the material of piezoelectric oscillator is determined, the best radius ratio and thickness ratio make the power generation capacity the largest. Excessive or small radius ratio and thickness ratio will reduce the generating capacity and even generate zero power. In addition, the electromechanical equivalent model is established. Equivalent analysis is made by changing the circuit impedance. The results are consistent with the theoretical simulation results, indicating that the established circuit model can truly reflect the characteristics of the theoretical model.
Energy Technology Data Exchange (ETDEWEB)
Ko, Han Gyul; Kim, Hong Seok [Seoul Nat' l Univ., Seoul (Korea, Republic of)
2013-01-15
A cyclone separator has been widely used in various industrial processes for removing fine particulate matter because it is easy to fabricate, cost effective, and adaptable to extremely harsh conditions. However, owing to the complex flow field in cyclones, a complete understanding of the detailed mechanisms of particulate removal has not yet been gained. In this study, a theoretical analysis was performed for calculating the collection efficiency and cut off size in cyclones by taking into account the effects of geometrical and flow parameters. The collection efficiency and cut off size values predicted by the theoretical model showed good agreement with experimental measurements for particles with a diameter of 0.5-30{mu}m. It was also revealed that the surface friction, along with the flow and geometrical parameters, has a significant effect on the cyclone performance.
Directory of Open Access Journals (Sweden)
Stevan M. Berber
2014-06-01
Full Text Available Chaotic spreading sequences can increase secrecy and resistance to interception in signal transmission. Chaos-based CDMA systems have been well investigated in the case of flat fading and noise presence in the channel. However, these systems operating in wideband channels, characterized by the frequency selective fading and white Gaussian noise, have not been investigated to the level of understanding their practical applications. This paper presents a detailed mathematical model of a CDMA system based on chaotic spreading sequences. In a theoretical analysis, all signals are represented in the discrete time domain. Using the theory of discrete time stochastic processes, the probability of error expressions are derived in a closed form for a multi-user chaos based CDMA system. For the sake of comparison, the expressions for the probability of error are derived separately for narrowband and wideband channels. The application of the system interleaving technique is investigated in particular, which showed that this technique can substantially improve probability of error in the system. The system is simulated and the findings of the simulation confirmed theoretically expected results. Possible improvements in the probability of bit error due to multipath channel nature, with and without interleavers, are quantified depending on the random delay and the number of users in the system. In the analyzed system, a simplified version of the wideband channel model, proposed for modern wideband wireless networks, is used. Introduction Over the past years, the demand for wireless communications has increased substantially due to advancements in mobile communication systems and networks. Following these increasing demands, modern communication systems require the ability to handle a large number of users to process and transmit wideband signals through complex frequency selective channels. One of the techniques for transmission of multi-user signals is the
Statistical Network Analysis for Functional MRI: Mean Networks and Group Comparisons.
Directory of Open Access Journals (Sweden)
Cedric E Ginestet
2014-05-01
Full Text Available Comparing networks in neuroscience is hard, because the topological properties of a given network are necessarily dependent on the number of edges of that network. This problem arises in the analysis of both weighted and unweighted networks. The term density is often used in this context, in order to refer to the mean edge weight of a weighted network, or to the number of edges in an unweighted one. Comparing families of networks is therefore statistically difficult because differences in topology are necessarily associated with differences in density. In this review paper, we consider this problem from two different perspectives, which include (i the construction of summary networks, such as how to compute and visualize the mean network from a sample of network-valued data points; and (ii how to test for topological differences, when two families of networks also exhibit significant differences in density. In the first instance, we show that the issue of summarizing a family of networks can be conducted by either adopting a mass-univariate approach, which produces a statistical parametric network (SPN, or by directly computing the mean network, provided that a metric has been specified on the space of all networks with a given number of nodes. In the second part of this review, we then highlight the inherent problems associated with the comparison of topological functions of families of networks that differ in density. In particular, we show that a wide range of topological summaries, such as global efficiency and network modularity are highly sensitive to differences in density. Moreover, these problems are not restricted to unweighted metrics, as we demonstrate that the same issues remain present when considering the weighted versions of these metrics. We conclude by encouraging caution, when reporting such statistical comparisons, and by emphasizing the importance of constructing summary networks.
Tahmassebi, Amirhessam; Pinker-Domenig, Katja; Wengert, Georg; Lobbes, Marc; Stadlbauer, Andreas; Romero, Francisco J.; Morales, Diego P.; Castillo, Encarnacion; Garcia, Antonio; Botella, Guillermo; Meyer-Bäse, Anke
2017-05-01
Graph network models in dementia have become an important computational technique in neuroscience to study fundamental organizational principles of brain structure and function of neurodegenerative diseases such as dementia. The graph connectivity is reflected in the connectome, the complete set of structural and functional connections of the graph network, which is mostly based on simple Pearson correlation links. In contrast to simple Pearson correlation networks, the partial correlations (PC) only identify direct correlations while indirect associations are eliminated. In addition to this, the state-of-the-art techniques in brain research are based on static graph theory, which is unable to capture the dynamic behavior of the brain connectivity, as it alters with disease evolution. We propose a new research avenue in neuroimaging connectomics based on combining dynamic graph network theory and modeling strategies at different time scales. We present the theoretical framework for area aggregation and time-scale modeling in brain networks as they pertain to disease evolution in dementia. This novel paradigm is extremely powerful, since we can derive both static parameters pertaining to node and area parameters, as well as dynamic parameters, such as system's eigenvalues. By implementing and analyzing dynamically both disease driven PC-networks and regular concentration networks, we reveal differences in the structure of these network that play an important role in the temporal evolution of this disease. The described research is key to advance biomedical research on novel disease prediction trajectories and dementia therapies.
Centrality measures in temporal networks with time series analysis
Huang, Qiangjuan; Zhao, Chengli; Zhang, Xue; Wang, Xiaojie; Yi, Dongyun
2017-05-01
The study of identifying important nodes in networks has a wide application in different fields. However, the current researches are mostly based on static or aggregated networks. Recently, the increasing attention to networks with time-varying structure promotes the study of node centrality in temporal networks. In this paper, we define a supra-evolution matrix to depict the temporal network structure. With using of the time series analysis, the relationships between different time layers can be learned automatically. Based on the special form of the supra-evolution matrix, the eigenvector centrality calculating problem is turned into the calculation of eigenvectors of several low-dimensional matrices through iteration, which effectively reduces the computational complexity. Experiments are carried out on two real-world temporal networks, Enron email communication network and DBLP co-authorship network, the results of which show that our method is more efficient at discovering the important nodes than the common aggregating method.
Veliz-Cuba, Alan; Aguilar, Boris; Hinkelmann, Franziska; Laubenbacher, Reinhard
2014-06-26
A key problem in the analysis of mathematical models of molecular networks is the determination of their steady states. The present paper addresses this problem for Boolean network models, an increasingly popular modeling paradigm for networks lacking detailed kinetic information. For small models, the problem can be solved by exhaustive enumeration of all state transitions. But for larger models this is not feasible, since the size of the phase space grows exponentially with the dimension of the network. The dimension of published models is growing to over 100, so that efficient methods for steady state determination are essential. Several methods have been proposed for large networks, some of them heuristic. While these methods represent a substantial improvement in scalability over exhaustive enumeration, the problem for large networks is still unsolved in general. This paper presents an algorithm that consists of two main parts. The first is a graph theoretic reduction of the wiring diagram of the network, while preserving all information about steady states. The second part formulates the determination of all steady states of a Boolean network as a problem of finding all solutions to a system of polynomial equations over the finite number system with two elements. This problem can be solved with existing computer algebra software. This algorithm compares favorably with several existing algorithms for steady state determination. One advantage is that it is not heuristic or reliant on sampling, but rather determines algorithmically and exactly all steady states of a Boolean network. The code for the algorithm, as well as the test suite of benchmark networks, is available upon request from the corresponding author. The algorithm presented in this paper reliably determines all steady states of sparse Boolean networks with up to 1000 nodes. The algorithm is effective at analyzing virtually all published models even those of moderate connectivity. The problem for
Neural Network Analysis of LEAP Energy Spectra
Energy Technology Data Exchange (ETDEWEB)
Holdridge, Robert E
2002-09-10
The Laser Electron Acceleration Project (LEAP) group has been conducting a proof of principle experiment on the acceleration of electrons with a pair of crossed laser beams. To date there has been no experimental verification of electron acceleration with crossed laser beams in a dielectric loaded vacuum, although the energy profile of an accelerated electron bunch has been well described by theory. The experiment is subject to unavoidable time dependent fluctuations in the independent variables. Changes in the experimental parameters can dramatically alter the beam profile incident near the focal plane of a high-resolution spectrometer located downstream from the accelerator cell. Neural networks (NNs) appear to provide an ideal tool for the positive determination of an acceleration event, being adaptable and able to handle highly complex nonlinear problems. Typical NNs under such conditions require a training set consisting of a representative data set along with ''answers'' which have been determined to be consistent with the variable state of the experimental parameters. A strategy of pattern recognition with respect to the status of independent variables can be employed to determine the signature characteristics of a laser perturbed electron bunch. Data cuts representing characteristics that were thought to be distinctive to accelerated beam profile images were implemented in the algorithm employed. Statistical analysis of the results of data cuts made on the energy profile images from the experiment is presented, as well as conclusions drawn from the results of this analysis. Finally, a discussion of future directions to be taken in this work is given including the orientation towards on-line, real-time analysis.
Social Network Analysis and Nutritional Behavior: An Integrated Modeling Approach.
Senior, Alistair M; Lihoreau, Mathieu; Buhl, Jerome; Raubenheimer, David; Simpson, Stephen J
2016-01-01
Animals have evolved complex foraging strategies to obtain a nutritionally balanced diet and associated fitness benefits. Recent research combining state-space models of nutritional geometry with agent-based models (ABMs), show how nutrient targeted foraging behavior can also influence animal social interactions, ultimately affecting collective dynamics and group structures. Here we demonstrate how social network analyses can be integrated into such a modeling framework and provide a practical analytical tool to compare experimental results with theory. We illustrate our approach by examining the case of nutritionally mediated dominance hierarchies. First we show how nutritionally explicit ABMs that simulate the emergence of dominance hierarchies can be used to generate social networks. Importantly the structural properties of our simulated networks bear similarities to dominance networks of real animals (where conflicts are not always directly related to nutrition). Finally, we demonstrate how metrics from social network analyses can be used to predict the fitness of agents in these simulated competitive environments. Our results highlight the potential importance of nutritional mechanisms in shaping dominance interactions in a wide range of social and ecological contexts. Nutrition likely influences social interactions in many species, and yet a theoretical framework for exploring these effects is currently lacking. Combining social network analyses with computational models from nutritional ecology may bridge this divide, representing a pragmatic approach for generating theoretical predictions for nutritional experiments.
Exploratory social network analysis with Pajek. - 2nd ed.
de Nooy, W.; Mrvar, A.; Batagelj, V.
2011-01-01
This is an extensively revised and expanded second edition of the successful textbook on social network analysis integrating theory, applications, and network analysis using Pajek. The main structural concepts and their applications in social research are introduced with exercises. Pajek software
International Nuclear Information System (INIS)
Hassan, H.Z.; Mohamad, A.A.
2013-01-01
Due to the intermittent nature of the solar radiation, the day-long continuous production of cold is a challenge for solar-driven adsorption cooling systems. In the present study, a developed solar-powered adsorption cooling system is introduced. The proposed system is able to produce cold continuously along the 24-h of the day. The theoretical thermodynamic operating cycle of the system is based on adsorption at constant temperature. Both the cooling system operating procedure as well as the theoretical thermodynamic cycle are described and explained. Moreover, a steady state differential thermodynamic analysis is performed for all components and processes of the introduced system. The analysis is based on the energy conservation principle and the equilibrium dynamics of the adsorption and desorption processes. The Dubinin–Astakhov adsorption equilibrium equation is used in this analysis. Furthermore, the thermodynamic properties of the refrigerant are calculated from its equation of state. The case studied represents a water chiller which uses activated carbon–methanol as the working pair. The chiller is found to produce a daily mass of 2.63 kg cold water at 0 °C from water at 25 °C per kg of adsorbent. Moreover, the proposed system attains a cooling coefficient of performance of 0.66. - Highlights: • A new continuous operation solar-driven adsorption refrigeration system is introduced. • The theoretical thermodynamic cycle is presented and explained. • A complete thermodynamic analysis is performed for all components and processes of the system. • Activated carbon–methanol is used as the working pair in the case study
Network meta-analysis: an introduction for pharmacists.
Xu, Yina; Amiche, Mohamed Amine; Tadrous, Mina
2018-05-21
Network meta-analysis is a new tool used to summarize and compare studies for multiple interventions, irrespective of whether these interventions have been directly evaluated against each other. Network meta-analysis is quickly becoming the standard in conducting therapeutic reviews and clinical guideline development. However, little guidance is available to help pharmacists review network meta-analysis studies in their practice. Major institutions such as the Cochrane Collaboration, Agency for Healthcare Research and Quality, Canadian Agency for Drugs and Technologies in Health, and National Institute for Health and Care Excellence Decision Support Unit have endorsed utilizing network meta-analysis to establish therapeutic evidence and inform decision making. Our objective is to introduce this novel technique to pharmacy practitioners, and highlight key assumptions behind network meta-analysis studies.
Application of OLAM network in X-ray spectral analysis
International Nuclear Information System (INIS)
Liu Yinbing; Zhou Rongsheng
2001-01-01
The author describes a new approach to the automatic radioisotope identification problem based on the use of OLAM network. Different from the traditional methods, the OLAM network takes the spectrum as a whole comparing its shape with the patterns learned during the training period of the network. It is found that the OLAM network, once adequately trained, is quite suitable to identify a given isotope present in a mixture of elements as well as the relative proportions of each identified substance. Preliminary results are good enough to consider OLAM network as powerful and simple tools in the automatic spectrum analysis
Error performance analysis in K-tier uplink cellular networks using a stochastic geometric approach
Afify, Laila H.
2015-09-14
In this work, we develop an analytical paradigm to analyze the average symbol error probability (ASEP) performance of uplink traffic in a multi-tier cellular network. The analysis is based on the recently developed Equivalent-in-Distribution approach that utilizes stochastic geometric tools to account for the network geometry in the performance characterization. Different from the other stochastic geometry models adopted in the literature, the developed analysis accounts for important communication system parameters and goes beyond signal-to-interference-plus-noise ratio characterization. That is, the presented model accounts for the modulation scheme, constellation type, and signal recovery techniques to model the ASEP. To this end, we derive single integral expressions for the ASEP for different modulation schemes due to aggregate network interference. Finally, all theoretical findings of the paper are verified via Monte Carlo simulations.
A P-value model for theoretical power analysis and its applications in multiple testing procedures
Directory of Open Access Journals (Sweden)
Fengqing Zhang
2016-10-01
Full Text Available Abstract Background Power analysis is a critical aspect of the design of experiments to detect an effect of a given size. When multiple hypotheses are tested simultaneously, multiplicity adjustments to p-values should be taken into account in power analysis. There are a limited number of studies on power analysis in multiple testing procedures. For some methods, the theoretical analysis is difficult and extensive numerical simulations are often needed, while other methods oversimplify the information under the alternative hypothesis. To this end, this paper aims to develop a new statistical model for power analysis in multiple testing procedures. Methods We propose a step-function-based p-value model under the alternative hypothesis, which is simple enough to perform power analysis without simulations, but not too simple to lose the information from the alternative hypothesis. The first step is to transform distributions of different test statistics (e.g., t, chi-square or F to distributions of corresponding p-values. We then use a step function to approximate each of the p-value’s distributions by matching the mean and variance. Lastly, the step-function-based p-value model can be used for theoretical power analysis. Results The proposed model is applied to problems in multiple testing procedures. We first show how the most powerful critical constants can be chosen using the step-function-based p-value model. Our model is then applied to the field of multiple testing procedures to explain the assumption of monotonicity of the critical constants. Lastly, we apply our model to a behavioral weight loss and maintenance study to select the optimal critical constants. Conclusions The proposed model is easy to implement and preserves the information from the alternative hypothesis.
Energy Technology Data Exchange (ETDEWEB)
Soares, Breno Almeida; Firme, Caio Lima, E-mail: firme.caio@gmail.com, E-mail: caiofirme@quimica.ufrn.br [Universidade Federal do Rio Grande do Norte (UFRN), Natal, RN (Brazil). Instituto de Quimica; Maciel, Maria Aparecida Medeiros [Universidade Potiguar, Natal, RN (Brazil). Programa de Pos-graduacao em Biotecnologia; Kaiser, Carlos R. [Universidade Federal do Rio de Janeiro (UFRJ), RJ (Brazil). Instituto de Quimica; Schilling, Eduardo; Bortoluzzi, Adailton J. [Universidade Federal de Santa Catarina (UFSC), Florianopolis, SC (Brazil). Departamento de Quimica
2014-04-15
trans-Dehydrocrotonin (t-DCTN) a bioactive 19-nor-diterpenoid clerodane type isolated from Croton cajucara Benth, is one of the most investigated clerodane in the current literature. In this work, a new approach joining X-ray diffraction data, nuclear magnetic resonance (NMR) data and theoretical calculations was applied to the thorough characterization of t-DCTN. For that, the geometry of t-DCTN was reevaluated by X-ray diffraction as well as {sup 1}H and {sup 13}C NMR data, whose geometrical parameters where compared to those obtained from B3LYP/6-311G++(d,p) level of theory. From the evaluation of both calculated and experimental values of {sup 1}H and {sup 13}C NMR chemical shifts and spin-spin coupling constants, it was found very good correlations between theoretical and experimental magnetic properties of t-DCTN. Additionally, the delocalization indexes between hydrogen atoms correlated accurately with theoretical and experimental spin-spin coupling constants. An additional topological analysis from quantum theory of atoms in molecules (QTAIM) showed intramolecular interactions for t-DCTN. (author)
International Nuclear Information System (INIS)
Soares, Breno Almeida; Firme, Caio Lima; Maciel, Maria Aparecida Medeiros; Kaiser, Carlos R.; Schilling, Eduardo; Bortoluzzi, Adailton J.
2014-01-01
trans-Dehydrocrotonin (t-DCTN) a bioactive 19-nor-diterpenoid clerodane type isolated from Croton cajucara Benth, is one of the most investigated clerodane in the current literature. In this work, a new approach joining X-ray diffraction data, nuclear magnetic resonance (NMR) data and theoretical calculations was applied to the thorough characterization of t-DCTN. For that, the geometry of t-DCTN was reevaluated by X-ray diffraction as well as 1 H and 13 C NMR data, whose geometrical parameters where compared to those obtained from B3LYP/6-311G++(d,p) level of theory. From the evaluation of both calculated and experimental values of 1 H and 13 C NMR chemical shifts and spin-spin coupling constants, it was found very good correlations between theoretical and experimental magnetic properties of t-DCTN. Additionally, the delocalization indexes between hydrogen atoms correlated accurately with theoretical and experimental spin-spin coupling constants. An additional topological analysis from quantum theory of atoms in molecules (QTAIM) showed intramolecular interactions for t-DCTN. (author)
Analysis of the airport network of India as a complex weighted network
Bagler, Ganesh
2008-05-01
Transportation infrastructure of a country is one of the most important indicators of its economic growth. Here we study the Airport Network of India (ANI) which represents India’s domestic civil aviation infrastructure as a complex network. We find that ANI, a network of domestic airports connected by air links, is a small-world network characterized by a truncated power-law degree distribution and has a signature of hierarchy. We investigate ANI as a weighted network to explore its various properties and compare them with their topological counterparts. The traffic in ANI, as in the World-wide Airport Network (WAN), is found to be accumulated on interconnected groups of airports and is concentrated between large airports. In contrast to WAN, ANI is found to be having disassortative mixing which is offset by the traffic dynamics. The analysis indicates possible mechanism of formation of a national transportation network, which is different from that on a global scale.
WGCNA: an R package for weighted correlation network analysis.
Langfelder, Peter; Horvath, Steve
2008-12-29
Correlation networks are increasingly being used in bioinformatics applications. For example, weighted gene co-expression network analysis is a systems biology method for describing the correlation patterns among genes across microarray samples. Weighted correlation network analysis (WGCNA) can be used for finding clusters (modules) of highly correlated genes, for summarizing such clusters using the module eigengene or an intramodular hub gene, for relating modules to one another and to external sample traits (using eigengene network methodology), and for calculating module membership measures. Correlation networks facilitate network based gene screening methods that can be used to identify candidate biomarkers or therapeutic targets. These methods have been successfully applied in various biological contexts, e.g. cancer, mouse genetics, yeast genetics, and analysis of brain imaging data. While parts of the correlation network methodology have been described in separate publications, there is a need to provide a user-friendly, comprehensive, and consistent software implementation and an accompanying tutorial. The WGCNA R software package is a comprehensive collection of R functions for performing various aspects of weighted correlation network analysis. The package includes functions for network construction, module detection, gene selection, calculations of topological properties, data simulation, visualization, and interfacing with external software. Along with the R package we also present R software tutorials. While the methods development was motivated by gene expression data, the underlying data mining approach can be applied to a variety of different settings. The WGCNA package provides R functions for weighted correlation network analysis, e.g. co-expression network analysis of gene expression data. The R package along with its source code and additional material are freely available at http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA.
Robustness analysis of the Zhang neural network for online time-varying quadratic optimization
International Nuclear Information System (INIS)
Zhang Yunong; Ruan Gongqin; Li Kene; Yang Yiwen
2010-01-01
A general type of recurrent neural network (termed as Zhang neural network, ZNN) has recently been proposed by Zhang et al for the online solution of time-varying quadratic-minimization (QM) and quadratic-programming (QP) problems. Global exponential convergence of the ZNN could be achieved theoretically in an ideal error-free situation. In this paper, with the normal differentiation and dynamics-implementation errors considered, the robustness properties of the ZNN model are investigated for solving these time-varying problems. In addition, linear activation functions and power-sigmoid activation functions could be applied to such a perturbed ZNN model. Both theoretical-analysis and computer-simulation results demonstrate the good ZNN robustness and superior performance for online time-varying QM and QP problem solving, especially when using power-sigmoid activation functions.
Directory of Open Access Journals (Sweden)
Keith Stuart
2009-12-01
Full Text Available This article describes research undertaken in order to design a methodology for the reticular representation of knowledge of a specific discourse community. To achieve this goal, a representative corpus of the scientific production of the members of this discourse community (Universidad Politécnica de Valencia, UPV was created. The article presents the practical analysis (frequency, keyword, collocation and cluster analysis that was carried out in the initial phases of the study aimed at establishing the theoretical and practical background and framework for our matrix and network analysis of the scientific discourse of the UPV. In the methodology section, the processes that have allowed us to extract from the corpus the linguistic elements needed to develop co-occurrence matrices, as well as the computer tools used in the research, are described. From these co-occurrence matrices, semantic networks of subject and discipline knowledge were generated. Finally, based on the results obtained, we suggest that it may be viable to extract and to represent the intellectual capital of an academic institution using corpus linguistics methods in combination with the formulations of network theory.En este artículo describimos la investigación que se ha desarrollado en el diseño de una metodología para la representación reticular del conocimiento que se genera en el seno de una institución a partir de un corpus representativo de la producción científica de los integrantes de dicha comunidad discursiva, la Universidad Politécnica de Valencia.. Para ello, presentamos las acciones que se realizaron en las fases iniciales del estudio encaminadas a establecer el marco teórico y práctico en el que se inscribe nuestro análisis. En la sección de metodología se describen las herramientas informáticas utilizadas, así como los procesos que nos permitieron disponer de aquellos elementos presentes en el corpus, que nos llevarían al desarrollo de
Dream-reality confusion in Borderline Personality Disorder: A theoretical analysis
Directory of Open Access Journals (Sweden)
Dagna eSkrzypińska
2015-09-01
Full Text Available This paper presents an analysis of dream-reality confusion (DRC in relation to the characteristics of borderline personality disorder (BPD, based on research findings and theoretical considerations. It is hypothesized that people with BPD are more likely to experience DRC compared to people in non-clinical population. Several variables related to this hypothesis were identified through a theoretical analysis of the scientific literature. Sleep disturbances: Problems with sleep are found in 15-95.5% of people with BPD (Hafizi, 2013, and unstable sleep and wake cycles, which occur in BPD (Fleischer et al., 2012, are linked to DRC. Dissociation: Nearly two-thirds of people with BPD experience dissociative symptoms (Korzekwa and Pain, 2009 and dissociative symptoms are correlated with a fantasy proneness; both dissociative symptoms and fantasy proneness are related to DRC (Giesbrecht and Merckelbach, 2006. Negative dream content: People with BPD have nightmares more often than other people (Semiz et al., 2008; dreams that are more likely to be confused with reality tend to be more realistic and unpleasant, and are reflected in waking behavior (Rassin et al., 2001. Cognitive disturbances: Many BPD patients experience various cognitive disturbances, including problems with reality testing (Fiqueierdo, 2006; Mosquera et al., 2011, which can foster DRC. Thin boundaries: People with thin boundaries are more prone to DRC than people with thick boundaries, and people with BPD tend to have thin boundaries (Hartmann, 2011. The theoretical analysis on the basis of these findings suggests that people who suffer from BPD may be more susceptible to confusing dream content with actual waking events.
Network Analysis of Earth's Co-Evolving Geosphere and Biosphere
Hazen, R. M.; Eleish, A.; Liu, C.; Morrison, S. M.; Meyer, M.; Consortium, K. D.
2017-12-01
A fundamental goal of Earth science is the deep understanding of Earth's dynamic, co-evolving geosphere and biosphere through deep time. Network analysis of geo- and bio- `big data' provides an interactive, quantitative, and predictive visualization framework to explore complex and otherwise hidden high-dimension features of diversity, distribution, and change in the evolution of Earth's geochemistry, mineralogy, paleobiology, and biochemistry [1]. Networks also facilitate quantitative comparison of different geological time periods, tectonic settings, and geographical regions, as well as different planets and moons, through network metrics, including density, centralization, diameter, and transitivity.We render networks by employing data related to geographical, paragenetic, environmental, or structural relationships among minerals, fossils, proteins, and microbial taxa. An important recent finding is that the topography of many networks reflects parameters not explicitly incorporated in constructing the network. For example, networks for minerals, fossils, and protein structures reveal embedded qualitative time axes, with additional network geometries possibly related to extinction and/or other punctuation events (see Figure). Other axes related to chemical activities and volatile fugacities, as well as pressure and/or depth of formation, may also emerge from network analysis. These patterns provide new insights into the way planets evolve, especially Earth's co-evolving geosphere and biosphere. 1. Morrison, S.M. et al. (2017) Network analysis of mineralogical systems. American Mineralogist 102, in press. Figure Caption: A network of Phanerozoic Era fossil animals from the past 540 million years includes blue, red, and black circles (nodes) representing family-level taxa and grey lines (links) between coexisting families. Age information was not used in the construction of this network; nevertheless an intrinsic timeline is embedded in the network topology. In
Topology design and performance analysis of an integrated communication network
Li, V. O. K.; Lam, Y. F.; Hou, T. C.; Yuen, J. H.
1985-01-01
A research study on the topology design and performance analysis for the Space Station Information System (SSIS) network is conducted. It is begun with a survey of existing research efforts in network topology design. Then a new approach for topology design is presented. It uses an efficient algorithm to generate candidate network designs (consisting of subsets of the set of all network components) in increasing order of their total costs, and checks each design to see if it forms an acceptable network. This technique gives the true cost-optimal network, and is particularly useful when the network has many constraints and not too many components. The algorithm for generating subsets is described in detail, and various aspects of the overall design procedure are discussed. Two more efficient versions of this algorithm (applicable in specific situations) are also given. Next, two important aspects of network performance analysis: network reliability and message delays are discussed. A new model is introduced to study the reliability of a network with dependent failures. For message delays, a collection of formulas from existing research results is given to compute or estimate the delays of messages in a communication network without making the independence assumption. The design algorithm coded in PASCAL is included as an appendix.
Applications of social network analysis to obesity: a systematic review.
Zhang, S; de la Haye, K; Ji, M; An, R
2018-04-20
People's health behaviours and outcomes can be profoundly shaped by the social networks they are embedded in. Based on graph theory, social network analysis is a research framework for the study of social interactions and the structure of these interactions among social actors. A literature search was conducted in PubMed and Web of Science for articles published until August 2017 that applied social network analysis to examine obesity and social networks. Eight studies (three cross-sectional and five longitudinal) conducted in the US (n = 6) and Australia (n = 2) were identified. Seven focused on adolescents' and one on adults' friendship networks. They examined structural features of these networks that were associated with obesity, including degree distribution, popularity, modularity maximization and K-clique percolation. All three cross-sectional studies that used exponential random graph models found individuals with similar body weight status and/or weight-related behaviour were more likely to share a network tie than individuals with dissimilar traits. Three longitudinal studies using stochastic actor-based models found friendship network characteristics influenced change in individuals' body weight status and/or weight-related behaviour over time. Future research should focus on diverse populations and types of social networks and identifying the mechanisms by which social networks influence obesity to inform network-based interventions. © 2018 World Obesity Federation.
Jarnuczak, Andrew F; Eyers, Claire E; Schwartz, Jean-Marc; Grant, Christopher M; Hubbard, Simon J
2015-09-01
Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC-based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs. © 2015 The Authors. PROTEOMICS published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Theoretical analysis and experimental evaluation of a CsI(Tl) based electronic portal imaging system
International Nuclear Information System (INIS)
Sawant, Amit; Zeman, Herbert; Samant, Sanjiv; Lovhoiden, Gunnar; Weinberg, Brent; DiBianca, Frank
2002-01-01
This article discusses the design and analysis of a portal imaging system based on a thick transparent scintillator. A theoretical analysis using Monte Carlo simulation was performed to calculate the x-ray quantum detection efficiency (QDE), signal to noise ratio (SNR) and the zero frequency detective quantum efficiency [DQE(0)] of the system. A prototype electronic portal imaging device (EPID) was built, using a 12.7 mm thick, 20.32 cm diameter, CsI(Tl) scintillator, coupled to a liquid nitrogen cooled CCD TV camera. The system geometry of the prototype EPID was optimized to achieve high spatial resolution. The experimental evaluation of the prototype EPID involved the determination of contrast resolution, depth of focus, light scatter and mirror glare. Images of humanoid and contrast detail phantoms were acquired using the prototype EPID and were compared with those obtained using conventional and high contrast portal film and a commercial EPID. A theoretical analysis was also carried out for a proposed full field of view system using a large area, thinned CCD camera and a 12.7 mm thick CsI(Tl) crystal. Results indicate that this proposed design could achieve DQE(0) levels up to 11%, due to its order of magnitude higher QDE compared to phosphor screen-metal plate based EPID designs, as well as significantly higher light collection compared to conventional TV camera based systems
Why social network analysis is important to Air Force applications
Havig, Paul R.; McIntire, John P.; Geiselman, Eric; Mohd-Zaid, Fairul
2012-06-01
Social network analysis is a powerful tool used to help analysts discover relationships amongst groups of people as well as individuals. It is the mathematics behind such social networks as Facebook and MySpace. These networks alone cause a huge amount of data to be generated and the issue is only compounded once one adds in other electronic media such as e-mails and twitter. In this paper we outline the basics of social network analysis and how it may be used in current and future Air Force applications.
Economic and game-theoretical analysis of CO2 reduction agreements
International Nuclear Information System (INIS)
Tahvonen, O.
1994-01-01
The possibility of climate change and suggestions to stabilize CO 2 emissions have led to several different fields of research in resource and environmental economics. These include: 1. Studies on country specific and global greenhouse gas abatement costs. 2. Studies on global and country specific adaptation costs. 3. Game-theoretical analysis of greenhouse gas reduction agreements. 4. Studies on the relationship between CO 2 accumulation and natural resource utilization. 5. Models of climate change and intertemporal efficiency and equity. 6. Studies on emissions taxes and emissions permit markets for greenhouse gas abatement. The aim of this project is to contribute to the economic literature in fields 3, and 4
Theoretical conformational analysis of the bovine adrenal medulla 12 residue peptide molecule
Akhmedov, N. A.; Tagiyev, Z. H.; Hasanov, E. M.; Akverdieva, G. A.
2003-02-01
The spatial structure and conformational properties of the bovine adrenal medulla 12 residue peptide Tyr1-Gly2-Gly3-Phe4-Met5-Arg6-Arg7-Val8-Gly9-Arg10-Pro11-Glu12 (BAM-12P) molecule were studied by theoretical conformational analysis. It is revealed that this molecule can exist in several stable states. The energy and geometrical parameters for the low-energy conformations are obtained. The conformationally rigid and labile segments of this molecule were revealed.
An experimental and theoretical analysis of void fraction dynamics in a boiling channel
International Nuclear Information System (INIS)
Romberg, T.M.
1977-01-01
This paper describes an experimental and theoretical investigation of the void fraction dynamics at the exit of a test boiling channel which is operated near the 'instability threshold power' (the power level at which coolant flow instabilities occur). Dynamic measurements of the perturbations in channel inlet flow-rate, power input and exit void fraction are analysed using multivariate spectral analysis. The resulting experimental cross-spectral density functions between flow-rate/exit void fraction and power input/exit void fraction agree favourably with those calculated by a linearised hydrodynamic model in the frequency domain. (Author)
DEFF Research Database (Denmark)
Tsilipakos, O.; Pitilakis, A.; Yioultsis, T. V.
2012-01-01
A comprehensive theoretical analysis of end-fire coupling between dielectric-loaded surface plasmon polariton and rib/wire silicon-on-insulator (SOI) waveguides is presented. Simulations are based on the 3-D vector finite element method. The geometrical parameters of the interface are varied...... in order to identify the ones leading to optimum performance, i.e., maximum coupling efficiency. Fabrication tolerances about the optimum parameter values are also assessed. In addition, the effect of a longitudinal metallic stripe gap on coupling efficiency is quantified, since such gaps have been...
Kenkre, V. M.; Scott, J. E.; Pease, E. A.; Hurd, A. J.
1998-05-01
A theoretical framework for the analysis of the stress distribution in granular materials is presented. It makes use of a transformation of the vertical spatial coordinate into a formal time variable and the subsequent study of a generally non-Markoffian, i.e., memory-possessing (nonlocal) propagation equation. Previous treatments are obtained as particular cases corresponding to, respectively, wavelike and diffusive limits of the general evolution. Calculations are presented for stress propagation in bounded and unbounded media. They can be used to obtain desired features such as a prescribed stress distribution within the compact.
Theoretical and experimental analysis of daylight performance for various shading systems
Energy Technology Data Exchange (ETDEWEB)
Tsangrassoulis, A [Group Building Enviromental Studies, Lab. of Meteorology, Dept. of Applied Physics, Univ. of Athens (Greece); Santamouris, M [Group Building Enviromental Studies, Lab. of Meteorology, Dept. of Applied Physics, Univ. of Athens (Greece); Asimakopoulos, D [Group Building Enviromental Studies, Lab. of Meteorology, Dept. of Applied Physics, Univ. of Athens (Greece)
1997-12-31
The daylight coefficient approach is used for the theoretical analysis of various shading systems. Once a set of these coefficients has been calculated, it is very easy to calculate illuminance in the interior of a room under various sky luminance distributions. The present paper examines a method based on daylight coefficients to evaluate daylight in the interior of a room. The method is compared with existing radiosity and ray-tracing methods. The examined method is experimentaly validated using measurements obtained in a PASSYS test-cell equipped with shading devices. (orig.)
The theoretical study of full spectrum analysis method for airborne gamma-ray spectrometric data
International Nuclear Information System (INIS)
Ni Weichong
2011-01-01
Spectra of airborne gamma-ray spectrometry was found to be the synthesis of spectral components of radioelement sources by analyzing the constitution of radioactive sources for airborne gamma-ray spectrometric survey and establishing the models of gamma-ray measurement. The mathematical equation for analysising airborne gamma-ray full spectrometric data can be expressed into matrix and related expansions were developed for the mineral resources exploration, environmental radiation measurement, nuclear emergency monitoring, and so on. Theoretical study showed that the atmospheric radon could be directly computed by airborne gamma-ray spectrometric data with full spectrum analysis without the use of the accessional upward-looking detectors. (authors)
Neto, A.; Bolt, R.; Gerini, G.; Schmitt, D.
2003-01-01
In this contribution we present a theoretical model for the analysis of finite arrays of open-ended waveguides mounted on finite mounting platforms or having radome coverages. This model is based on a Multimode Equivalent Network (MEN) [1] representation of the radiating waveguides complete with
Lee, Moosung
2014-01-01
This article proposes an analytical consideration for social capital research in education by exploring a pragmatic combination of social network analysis (SNA) and symbolic interactionism (SI) as a research method. The article first delineates the theoretical linkages of social capital theory with SNA and SI. The article then discusses how SNA…
Weighted Complex Network Analysis of Shanghai Rail Transit System
Directory of Open Access Journals (Sweden)
Yingying Xing
2016-01-01
Full Text Available With increasing passenger flows and construction scale, Shanghai rail transit system (RTS has entered a new era of networking operation. In addition, the structure and properties of the RTS network have great implications for urban traffic planning, design, and management. Thus, it is necessary to acquire their network properties and impacts. In this paper, the Shanghai RTS, as well as passenger flows, will be investigated by using complex network theory. Both the topological and dynamic properties of the RTS network are analyzed and the largest connected cluster is introduced to assess the reliability and robustness of the RTS network. Simulation results show that the distribution of nodes strength exhibits a power-law behavior and Shanghai RTS network shows a strong weighted rich-club effect. This study also indicates that the intentional attacks are more detrimental to the RTS network than to the random weighted network, but the random attacks can cause slightly more damage to the random weighted network than to the RTS network. Our results provide a richer view of complex weighted networks in real world and possibilities of risk analysis and policy decisions for the RTS operation department.