GRETNA: a graph theoretical network analysis toolbox for imaging connectomics
Directory of Open Access Journals (Sweden)
Jinhui eWang
2015-06-01
Full Text Available Recent studies have suggested that the brain’s structural and functional networks (i.e., connectomics can be constructed by various imaging technologies (e.g., EEG/MEG; structural, diffusion and functional MRI and further characterized by graph theory. Given the huge complexity of network construction, analysis and statistics, toolboxes incorporating these functions are largely lacking. Here, we developed the GRaph thEoreTical Network Analysis (GRETNA toolbox for imaging connectomics. The GRETNA contains several key features as follows: (i an open-source, Matlab-based, cross-platform (Windows and UNIX OS package with a graphical user interface; (ii allowing topological analyses of global and local network properties with parallel computing ability, independent of imaging modality and species; (iii providing flexible manipulations in several key steps during network construction and analysis, which include network node definition, network connectivity processing, network type selection and choice of thresholding procedure; (iv allowing statistical comparisons of global, nodal and connectional network metrics and assessments of relationship between these network metrics and clinical or behavioral variables of interest; and (v including functionality in image preprocessing and network construction based on resting-state functional MRI (R-fMRI data. After applying the GRETNA to a publicly released R-fMRI dataset of 54 healthy young adults, we demonstrated that human brain functional networks exhibit efficient small-world, assortative, hierarchical and modular organizations and possess highly connected hubs and that these findings are robust against different analytical strategies. With these efforts, we anticipate that GRETNA will accelerate imaging connectomics in an easy, quick and flexible manner. GRETNA is freely available on the NITRC website (http://www.nitrc.org/projects/gretna/.
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.
Directory of Open Access Journals (Sweden)
David I Spivak
Full Text Available Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we describe an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other olog. We consider simple cases of beta-helical and amyloid-like protein filaments subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog for the social network feature identical category-theoretic representations, and we proceed to precisely explicate the analogy or isomorphism between them. The examples presented here demonstrate that the intrinsic nature of a complex system, which in particular includes a precise relationship between structure and function at different hierarchical levels, can be effectively represented by an olog. This, in turn, allows for comparative studies between disparate materials or fields of application, and results in novel approaches to derive functionality in the design of de novo hierarchical systems. We discuss opportunities and challenges associated with the description of complex biological materials by using ologs as a powerful tool for analysis and design in the context of materiomics, and we present the potential impact of this approach for engineering, life sciences, and medicine.
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.
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
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 th
Category theoretic analysis of hierarchical protein materials and social networks
Spivak, David I; Buehler, Markus J
2011-01-01
Materials in biology span all the scales from Angstroms to meters and typically consist of complex hierarchical assemblies of simple building blocks. Here we review an application of category theory to describe structural and resulting functional properties of biological protein materials by developing so-called ologs. An olog is like a "concept web" or "semantic network" except that it follows a rigorous mathematical formulation based on category theory. This key difference ensures that an olog is unambiguous, highly adaptable to evolution and change, and suitable for sharing concepts with other ologs. We consider a simple example of an alpha-helical and an amyloid-like protein filament subjected to axial extension and develop an olog representation of their structural and resulting mechanical properties. We also construct a representation of a social network in which people send text-messages to their nearest neighbors and act as a team to perform a task. We show that the olog for the protein and the olog f...
Graph theoretical analysis and application of fMRI-based brain network in Alzheimer's disease
Directory of Open Access Journals (Sweden)
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.
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...
Theoretical Analysis of Measurement in Operation Efficiency in Optical Cable Transmission Networks
Institute of Scientific and Technical Information of China (English)
无
2000-01-01
It is necessary to study dynamic operation efficiency of transmission networks in order to realize high intensification of communication networks. The operation efficiency discussed here should exist not only in logic-circuit layer, but also in both path layer and medium layer. A theoretical method of the measurement of layers and comprehensive evaluations is presented based on the concept of transmission efficiency.
Directory of Open Access Journals (Sweden)
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.
Why Network? Theoretical Perspectives on Networking
Muijs, Daniel; West, Mel; Ainscow, Mel
2010-01-01
In recent years, networking and collaboration have become increasingly popular in education. However, there is at present a lack of attention to the theoretical basis of networking, which could illuminate when and when not to network and under what conditions networks are likely to be successful. In this paper, we will attempt to sketch the…
Directory of Open Access Journals (Sweden)
Suresh Muknahallipatna
2007-08-01
Full Text Available Fibre channel storage area networks (SAN are widely implemented in production data center environments. Recently the storage industry has moved towards deployment of distributed SANs (DSAN, geographically dispersed across large physical distances. In a DSAN, specialized gateway devices interconnect the individual Fibre Channel (FC fabrics over IP networks using TCP/IP based protocols (iFCP or FCIP or over metro to long distance optical networks such as Dense Wavelength Division Multiplexing (DWDM based networks that utilize native FC ports supporting large numbers of link credits. When using TCP/IP based storage networking protocols to interconnect local FC fabrics in a DSAN, the sustained throughput achievable depends upon the link characteristics and TCP/IP stack implementation. Sustaining maximum possible storage traffic throughput across the wide area network enables practical DSAN deployments by maintaining the required site to site service level agreements.This study explores the effects of several TCP/IP modifications on sustained traffic throughput for a DSAN interconnected via iFCP gateways across an impaired network. The TCP/IP stack modifications, known as storage friendly, include changes to the window scaling, congestion avoidance, and fast recovery algorithms. The theoretical background and experimental results are presented to explain and illustrate these modifications.
Directory of Open Access Journals (Sweden)
Yuliang Su
Full Text Available Stimulated reservoir volume (SRV fracturing in tight oil reservoirs often induces complex fracture-network growth, which has a fundamentally different formation mechanism from traditional planar bi-winged fracturing. To reveal the mechanism of fracture network propagation, this paper employs a modified displacement discontinuity method (DDM, mechanical mechanism analysis and initiation and propagation criteria for the theoretical model of fracture network propagation and its derivation. A reasonable solution of the theoretical model for a tight oil reservoir is obtained and verified by a numerical discrete method. Through theoretical calculation and computer programming, the variation rules of formation stress fields, hydraulic fracture propagation patterns (FPP and branch fracture propagation angles and pressures are analyzed. The results show that during the process of fracture propagation, the initial orientation of the principal stress deflects, and the stress fields at the fracture tips change dramatically in the region surrounding the fracture. Whether the ideal fracture network can be produced depends on the geological conditions and on the engineering treatments. This study has both theoretical significance and practical application value by contributing to a better understanding of fracture network propagation mechanisms in unconventional oil/gas reservoirs and to the improvement of the science and design efficiency of reservoir fracturing.
Su, Yuliang; Ren, Long; Meng, Fankun; Xu, Chen; Wang, Wendong
2015-01-01
Stimulated reservoir volume (SRV) fracturing in tight oil reservoirs often induces complex fracture-network growth, which has a fundamentally different formation mechanism from traditional planar bi-winged fracturing. To reveal the mechanism of fracture network propagation, this paper employs a modified displacement discontinuity method (DDM), mechanical mechanism analysis and initiation and propagation criteria for the theoretical model of fracture network propagation and its derivation. A reasonable solution of the theoretical model for a tight oil reservoir is obtained and verified by a numerical discrete method. Through theoretical calculation and computer programming, the variation rules of formation stress fields, hydraulic fracture propagation patterns (FPP) and branch fracture propagation angles and pressures are analyzed. The results show that during the process of fracture propagation, the initial orientation of the principal stress deflects, and the stress fields at the fracture tips change dramatically in the region surrounding the fracture. Whether the ideal fracture network can be produced depends on the geological conditions and on the engineering treatments. This study has both theoretical significance and practical application value by contributing to a better understanding of fracture network propagation mechanisms in unconventional oil/gas reservoirs and to the improvement of the science and design efficiency of reservoir fracturing.
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.
Illuminating the theoretical components of alexithymia using bifactor modeling and network analysis.
Watters, Carolyn A; Taylor, Graeme J; Bagby, R Michael
2016-06-01
Alexithymia is a multifaceted personality construct that reflects deficits in affect awareness (difficulty identifying feelings, DIF; difficulty describing feelings, DDF) and operative thinking (externally oriented thinking, EOT; restricted imaginal processes, IMP), and is associated with several common psychiatric disorders. Over the years, researchers have debated the components that comprise the construct with some suggesting that IMP and EOT may reflect constructs somewhat distinct from alexithymia. In this investigation, we attempt to clarify the components and their interrelationships using a large heterogeneous multilanguage sample (N = 839), and an interview-based assessment of alexithymia (Toronto Structured Interview for Alexithymia; TSIA). To this end, we used 2 distinctly different but complementary methods, bifactor modeling and network analysis. Results of the confirmatory bifactor model and related reliability estimates supported a strong general factor of alexithymia; however, the majority of reliable variance for IMP was independent of this general factor. In contrast, network analysis results were based on a network comprised of only substantive partial correlations among TSIA items. Modularity analysis revealed 3 communities of items, where DIF and DDF formed 1 community, and EOT and IMP formed separate communities. Network metrics supported that the majority of central items resided in the DIF/DDF community and that IMP items were connected to the network primarily through EOT. Taken together, results suggest that IMP, at least as measured by the TSIA, may not be as salient a component of the alexithymia construct as are the DIF, DDF, and EOT components. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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.)
Kazumata, Ken; Tha, Khin Khin; Narita, Hisashi; Shichinohe, Hideo; Ito, Masaki; Uchino, Haruto; Abumiya, Takeo
2016-05-01
Chronic ischemia in adult moyamoya disease (MMD) reduces the integrity of normal-appearing white matter (WM). We investigated whether covert WM impairment alters large-scale brain networks and specific neural circuits associated with neurocognitive dysfunction in MMD. Forty-six participants (control, n = 23; MMD, n = 23) were examined using diffusion tensor imaging and streamline tractography. Structural connectivity among 90 cortical and subcortical brain regions was evaluated using the mean fractional anisotropy along the fiber tracts. Graph theoretical analysis was used to measure network parameters and inter-regional connectivity. Global network parameters were reduced in patients with MMD, including cluster coefficient (controls vs. MMD: 3.62 ± 0.24 vs. 3.26 ± 0.36; P < 0.0001), characteristic path length (controls vs. MMD: 1.20 ± 0.02 vs. 1.17 ± 0.01; P < 0.001), and small-world property (controls vs. MMD: 3.07 ± 0.18 vs. 2.83 ± 0.27; P < 0.001). Reduced pairwise connectivity was found in prefrontal neural circuits within the middle/inferior frontal gyrus; supplementary motor area; and insular, inferior temporal, and dorsal cingulate cortices. Covert WM microstructural changes in patients with MMD alter large-scale brain networks, as well as lateral prefrontal neural circuits. Evaluation of structural connectivity may be useful to assess the severity of chronic ischemic injury from a network perspective.
Vulnerability of Network Traffic under Node Capture Attacks using Circuit Theoretic Analysis
2008-04-01
of a single, fixed path, as in AODV or DSR [11] in a static network. The second class of protocols yield routes consisting of multiple independent...the circuit mapping. We compute the vulnerability metric as a function of the routing and the cryptographic protocols used to secure the network traffic... routing and cryptographic protocols . I. INTRODUCTION The successful commercialization of many applications of wireless networks relies on the assurance of
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Murray eShanahan
2013-07-01
Full Text Available Many species of birds, including pigeons, possess demonstrable cognitive capacities, and some are capable of cognitive feats matching those of apes. Since mammalian cortex is laminar while the avian telencephalon is nucleated, it is natural to ask whether the brains of these two cognitively capable taxa, despite their apparent anatomical dissimilarities, might exhibit common principles of organisation on some level. Complementing recent investigations of macro-scale brain connectivity in mammals, including humans and macaques, we here present the first large-scale wiring diagram for the forebrain of a bird. Using graph theory, we show that the pigeon telencephalon is organised along similar lines to that of a mammal. Both are modular, small-world networks with a connective core of hub nodes that includes prefrontal-like and hippocampal structures. These hub nodes are, topologically speaking, the most central regions of the pigeon's brain, as well as being the most richly connected, implying a crucial role in information flow. Overall, our analysis suggests that indeed, despite the absence of cortical layers and close to 300 million years of separate evolution, the connectivity of the avian brain conforms to the same organisational principles as the mammalian brain.
Tejedor, A.; Foufoula-Georgiou, E.; Longjas, A.; Zaliapin, I. V.
2014-12-01
River deltas are intricate landscapes with complex channel networks that self-organize to deliver water, sediment, and nutrients from the apex to the delta top and eventually to the coastal zone. The natural balance of material and energy fluxes which maintains a stable hydrologic, geomorphologic, and ecological state of a river delta, is often disrupted by external factors causing topological and dynamical changes in the delta structure and function. A formal quantitative framework for studying river delta topology and transport dynamics and their response to change is lacking. Here we present such a framework based on spectral graph theory and demonstrate its value in quantifying the complexity of the delta network topology, computing its steady state fluxes, and identifying upstream (contributing) and downstream (nourishment) areas from any point in the network. We use this framework to construct vulnerability maps that quantify the relative change of sediment and water delivery to the shoreline outlets in response to possible perturbations in hundreds of upstream links. This enables us to evaluate which links (hotspots) and what management scenarios would most influence flux delivery to the outlets, paving the way of systematically examining how local or spatially distributed delta interventions can be studied within a systems approach for delta sustainability.
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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.
Advances in theoretical models of network science
Institute of Scientific and Technical Information of China (English)
FANG Jin-qing; BI Qiao; LI Yong
2007-01-01
In this review article, we will summarize the main advances in network science investigated by the CIAE Group of Complex Network in this field. Several theoretical models of network science were proposed and their topological and dynamical properties are reviewed and compared with the other models. Our models mainly include a harmonious unifying hybrid preferential model, a large unifying hybrid network model, a quantum interference network, a hexagonal nanowire network, and a small-world network with the same degree. The models above reveal some new phenomena and findings, which are useful for deeply understanding and investigating complex networks and their applications.
Institute of Scientific and Technical Information of China (English)
张闯; 赵洪林; 贾敏
2015-01-01
In non-dedicated cooperative relay networks, each node is autonomous and selfish in nature, and thus spontaneous cooperation among nodes is challenged. To stimulate the selfish node to participate in cooperation, a pricing-based cooperation engine using game theory was designed. Firstly, the feasible regions of the charge price and reimbursement price were deduced. Then, the non-cooperative and cooperative games were adopted to analyze the amount of bandwidth that initiating cooperation node (ICN) forwards data through participating cooperation node (PCN) and the amount of bandwidth that PCN helps ICN to relay data. Meanwhile, the Nash equilibrium solutions of cooperation bandwidth allocations (CBAs) were obtained through geometrical interpretation. Secondly, a pricing-based cooperation engine was proposed and a cooperative communication system model with cooperation engines was depicted. Finally, an algorithm based on game theory was proposed to realize the cooperation engine. The simulation results demonstrate that, compared with the system without pricing-based incentive, the proposed system can significantly improve the ICN’s metric measured by bit-per-Joule and increase the PCN’s revenue.
Theoretical numerical analysis
Wendroff, Burton
1966-01-01
Theoretical Numerical Analysis focuses on the presentation of numerical analysis as a legitimate branch of mathematics. The publication first elaborates on interpolation and quadrature and approximation. Discussions focus on the degree of approximation by polynomials, Chebyshev approximation, orthogonal polynomials and Gaussian quadrature, approximation by interpolation, nonanalytic interpolation and associated quadrature, and Hermite interpolation. The text then ponders on ordinary differential equations and solutions of equations. Topics include iterative methods for nonlinear systems, matri
Lee, Jungsoo; Lee, Minji; Kim, Dae-Shik; Kim, Yun-Hee
2015-01-01
This study investigated the changes in the network topological configuration of the ipsilesional and contralesional hemispheres after a stroke and the indicators for the prediction of motor recovery using a graph theoretical approach in networks obtained from functional magnetic resonance imaging (fMRI). A longitudinal observational experiments (2 weeks and 1, 3, and 6 months after onset) were conducted on 12 patients after a stroke. We investigated the network reorganization during recovery in the ipsilesional and contralesional hemispheres by examining changes of graph indices related to network randomization. We predicted the recovery of motor function by examining the relationship between specific network measures and improved motor function scores. The ipsilesional hemispheric network showed active reorganization during recovery after a stroke. The randomness of the network significantly increased for 3 months post-stroke. We described an indicator for the prediction of the recovery of motor function from graph indices: the characteristic path length. As the path length of the ipsilesional network was lower immediately after onset, the better recovery could be expected after 3 months. This approach were helpful for understanding dynamic reorganizations of both hemispheric networks after a stroke and finding the implication for recovery.
Theoretical Foundations of Wireless Networks
2015-07-22
wireless networks. The interesting aspect of imperfect CSI in a networked setting is that different terminals are likely to have different perceptions ...Regarding asymptotic behaviors, observe that agents’ stage payoffs capture the kind of trade-off exemplified by the Keynesian beauty contest: each...imperfect CSI in a networked setting is that different terminals are likely to have different perceptions on the values of different channels. In
Unified Hybrid Network Theoretical Model Trilogy
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
The first of the unified hybrid network theoretical model trilogy (UHNTF) is the harmonious unification hybrid preferential model (HUHPM), seen in the inner loop of Fig. 1, the unified hybrid ratio is defined.
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...
Artificial neural networks: theoretical background and pharmaceutical applications: a review.
Wesolowski, Marek; Suchacz, Bogdan
2012-01-01
In recent times, there has been a growing interest in artificial neural networks, which are a rough simulation of the information processing ability of the human brain, as modern and vastly sophisticated computational techniques. This interest has also been reflected in the pharmaceutical sciences. This paper presents a review of articles on the subject of the application of neural networks as effective tools assisting the solution of various problems in science and the pharmaceutical industry, especially those characterized by multivariate and nonlinear dependencies. After a short description of theoretical background and practical basics concerning the computations performed by means of neural networks, the most important pharmaceutical applications of neural networks, with suitable references, are demonstrated. The huge role played by neural networks in pharmaceutical analysis, pharmaceutical technology, and searching for the relationships between the chemical structure and the properties of newly synthesized compounds as candidates for drugs is discussed.
Multifractal analysis of complex networks
Institute of Scientific and Technical Information of China (English)
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 muttifractal analysis of complex networks.This algorithm is used to calculate the generalized fractal dimensions Dq 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 Dq due to changes in the parameters of the theoretical network models is also discussed.
Theoretical research progress in complexity of complex dynamical networks
Institute of Scientific and Technical Information of China (English)
Fang Jinqing
2007-01-01
This article reviews the main progress in dynamical complexity of theoretical models for nonlinear complex networks proposed by our Joint Complex Network Research Group (JCNRG). The topological and dynamical properties of these theoretical models are numerically and analytically studied. Several findings are useful for understanding and deeply studying complex networks from macroscopic to microscopic levels and have a potential of applications in real-world networks.
Directory of Open Access Journals (Sweden)
Seung-Goo eKim
2013-07-01
Full Text Available As one of the most widely accepted neuroanatomical models on OCD, it has been hypothesized that imbalance between an excitatory direct (ventral pathway and an inhibitory indirect (dorsal pathway in cortico-striato-thalamic circuit underlies the emergence of OCD. Here we examine the structural network in drug-free patients with OCD in terms of graph theoretical measures for the first time. We used a measure called efficiency which quantifies how a node transfers information efficiently. To construct brain networks, cortical thickness was automatically estimated using T1-weighted magnetic resonance imaging. We found that the network of the OCD patients was as efficient as that of healthy controls so that the both networks were in the small-world regime. More importantly, however, disparity between the dorsal and the ventral networks in the OCD patients was found, suggesting a positive evidence to the imbalance theory on the underlying pathophysiology of OCD.
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.
A theoretical estimation for the optimal network robustness measure R against malicious node attacks
Ma, Liangliang; Liu, Jing; Duan, Boping; Zhou, Mingxing
2015-07-01
In a recent work (Schneider C. M. et al., Proc. Natl. Acad. Sci. U.S.A., 108 (2011) 3838), Schneider et al. introduced an effective measure R to evaluate the network robustness against malicious attacks on nodes. Take R as the objective function, they used a heuristic algorithm to optimize the network robustness. In this paper, a theoretical analysis is conducted to estimate the value of R for different types of networks, including regular networks, WS networks, ER networks, and BA networks. The experimental results show that the theoretical value of R is approximately equal to that of optimized networks. Furthermore, the theoretical analysis also shows that regular networks are the most robust than other networks. To validate this result, a heuristic method is proposed to optimize the network structure, in which the degree distribution can be changed and the number of nodes and edges remains invariant. The optimization results show that the degree of most nodes in the optimal networks is close to the average degree, and the optimal network topology is close to regular networks, which confirms the 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.
Unification of theoretical approaches for epidemic spreading on complex networks
Wang, Wei; Tang, Ming; Stanley, H. Eugene; Braunstein, Lidia A.
2017-03-01
Models of epidemic spreading on complex networks have attracted great attention among researchers in physics, mathematics, and epidemiology due to their success in predicting and controlling scenarios of epidemic spreading in real-world scenarios. To understand the interplay between epidemic spreading and the topology of a contact network, several outstanding theoretical approaches have been developed. An accurate theoretical approach describing the spreading dynamics must take both the network topology and dynamical correlations into consideration at the expense of increasing the complexity of the equations. In this short survey we unify the most widely used theoretical approaches for epidemic spreading on complex networks in terms of increasing complexity, including the mean-field, the heterogeneous mean-field, the quench mean-field, dynamical message-passing, link percolation, and pairwise approximation. We build connections among these approaches to provide new insights into developing an accurate theoretical approach to spreading dynamics on complex networks.
Directory of Open Access Journals (Sweden)
Lin Wang
2012-01-01
Full Text Available Studies were done on analysis of biological processes in the same high expression (fold change ≥2 activated PTHLH feedback-mediated cell adhesion gene ontology (GO network of human hepatocellular carcinoma (HCC compared with the corresponding low expression activated GO network of no-tumor hepatitis/cirrhotic tissues (HBV or HCV infection. Activated PTHLH feedback-mediated cell adhesion network consisted of anaphase-promoting complex-dependent proteasomal ubiquitin-dependent protein catabolism, cell adhesion, cell differentiation, cell-cell signaling, G-protein-coupled receptor protein signaling pathway, intracellular transport, metabolism, phosphoinositide-mediated signaling, positive regulation of transcription, regulation of cyclin-dependent protein kinase activity, regulation of transcription, signal transduction, transcription, and transport in HCC. We proposed activated PTHLH coupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network. Our hypothesis was verified by the different activated PTHLH feedback-mediated cell adhesion GO network of HCC compared with the corresponding inhibited GO network of no-tumor hepatitis/cirrhotic tissues, or the same compared with the corresponding inhibited GO network of HCC. Activated PTHLH coupling feedback phosphoinositide to G-protein receptor signal-induced cell adhesion network included BUB1B, GNG10, PTHR2, GNAZ, RFC4, UBE2C, NRXN3, BAP1, PVRL2, TROAP, and VCAN in HCC from GEO dataset using gene regulatory network inference method and our programming.
Network Complexity Measures. An Information-Theoretic Approach.
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Matthias Dehmer
2015-04-01
Full Text Available Quantitative graph analysis by using structural indices has been intricate in a sense that it often remains unclear which structural graph measures is the most suitable one, see [1, 12, 13]. In general, quantitative graph analysis deals with quantifying structural information of networks by using a measurement approach [5]. As special problem thereof is to characterize a graph quantitatively, that means to determine a measure that captures structural features of a network meaningfully. Various classical structural graph measures have been used to tackle this problem [13]. A fruitful approach by using information-theoretic [21] and statistical methods is to quantify the structural information content of a graph [1, 8, 18]. In this note, we sketch some classical information measures. Also, we briefly address the problem what kind of measures capture structural information uniquely. This relates to determine the discrimination power (or also called uniqueness of a graph measure, that is, how is the ability of the measures to discriminate non-isomorphic graphs structurally. [1] D. Bonchev. Information Theoretic Indices for Characterization of Chemical Structures. Research Studies Press, Chichester, 1983. [5] M. Dehmer and F. Emmert-Streib. Quantitative Graph Theory. Theory and Applications. CRC Press, 2014. [8] M. Dehmer, M. Grabner, and K. Varmuza. Information indices with high discriminative power for graphs. PLoS ONE, 7:e31214, 2012. [12] F. Emmert-Streib and M. Dehmer. Exploring statistical and population aspects of network complexity. PLoS ONE, 7:e34523, 2012. [13] F. Harary. Graph Theory. Addison Wesley Publishing Company, 1969. Reading, MA, USA. [18] A. Mowshowitz. Entropy and the complexity of the graphs I: An index of the relative complexity of a graph. Bull. Math. Biophys., 30:175–204, 1968. [21] C. E. Shannon and W. Weaver. The Mathematical Theory of Communication. University of Illinois Press, 1949.
Game theoretic approach for cooperative feature extraction in camera networks
Redondi, Alessandro E. C.; Baroffio, Luca; Cesana, Matteo; Tagliasacchi, Marco
2016-07-01
Visual sensor networks (VSNs) consist of several camera nodes with wireless communication capabilities that can perform visual analysis tasks such as object identification, recognition, and tracking. Often, VSN deployments result in many camera nodes with overlapping fields of view. In the past, such redundancy has been exploited in two different ways: (1) to improve the accuracy/quality of the visual analysis task by exploiting multiview information or (2) to reduce the energy consumed for performing the visual task, by applying temporal scheduling techniques among the cameras. We propose a game theoretic framework based on the Nash bargaining solution to bridge the gap between the two aforementioned approaches. The key tenet of the proposed framework is for cameras to reduce the consumed energy in the analysis process by exploiting the redundancy in the reciprocal fields of view. Experimental results in both simulated and real-life scenarios confirm that the proposed scheme is able to increase the network lifetime, with a negligible loss in terms of visual analysis accuracy.
ALOHA networks: A game-theoretic approach
Marbán, S.; Ven, P. van de; Borm, P.; Hamers, H.
2013-01-01
In this paper we consider a wireless network consisting of various nodes, where transmissions are regulated by the slotted ALOHA protocol. Nodes using the protocol behave autonomously, and decide at random whether to transmit in a particular time slot. Simultaneous transmissions by multiple nodes ca
Lin, Hong; Wang, Lin; Jiang, Minghu; Huang, Juxiang; Qi, Lianxiu
2012-10-01
We constructed the significant low-expression P-glycoprotein (ABCB1) inhibited transport and signal network in chimpanzee compared with high-expression (fold change ≥2) the human left cerebrum in GEO data set, by using integration of gene regulatory activated and inhibited network inference method with gene ontology (GO) analysis. Our result showed that ABCB1 transport and signal upstream network RAB2A inhibited ABCB1, and downstream ABCB1-inhibited SMAD1_2, NCK2, SLC25A46, GDF10, RASGRP1, EGFR, LRPPRC, RASSF2, RASA4, CA2, CBLB, UBR5, SLC25A16, ITGB3BP, DDIT4, PDPN, RAB2A in chimpanzee left cerebrum. We obtained that the different biological processes of ABCB1 inhibited transport and signal network repressed carbon dioxide transport, ER to Golgi vesicle-mediated transport, folic acid transport, mitochondrion transport along microtubule, water transport, BMP signaling pathway, Ras protein signal transduction, transforming growth factor beta receptor signaling pathway in chimpanzee compared with the inhibited network of the human left cerebrum, as a result of inducing inhibition of mitochondrion transport along microtubule and BMP signal-induced cell shape in chimpanzee left cerebrum. Our hypothesis was verified by the same and different biological processes of ABCB1 inhibited transport and signal network of chimpanzee compared with the corresponding activated network of chimpanzee and the human left cerebrum, respectively. Copyright © 2012 John Wiley & Sons, Ltd.
THE NETWORKS IN TOURISM: A THEORETICAL APPROACH
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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.
Theoretical perspectives of terrorist enemies as networks.
Energy Technology Data Exchange (ETDEWEB)
Spulak, Robert George, Jr.; Glicken, Jessica
2005-08-01
This perspective of terrorist enemies as networks by two distinguished associate fellows of the Joint Special Operations University (JSOU) follows as a result of its recent initiative to support USSOCOM strategic planning for the Global War on Terrorism. The paper is a manifestation of JSOU's goals for contributing products that will advance SOF strategic art and generating strategic outreach to the military, civilian, and academic communities to enrich those products. Dr. Robert Spulak and Dr. Jessica Glicken Turnley presented the findings of this paper to assembled strategic planners from USSOCOM, other combatant commands, and interagency players at the Center for Special Operations plan development conference, September 2005, in Tampa, Florida. At that meeting, the authors put forward a number of helpful planning concepts based on their professional studies in science and the humanities and their experiences in government and business. The JSOU Strategic Studies Department is pleased to facilitate the association of USSOCOM strategic planners with civilian expertise and insights that can broaden military thought and encourage planning decisions directly relevant to the changing global environment. Through JSOU's strategic outreach initiative, experts in many professional disciplines have signaled their willingness to support the Nation's counterterrorism efforts. In that spirit, JSOU is proud to commend this paper to SOF readers and appreciates the support of Dr. Spulak and Dr. Turnley.
Institute of Scientific and Technical Information of China (English)
项蕾(综述); 卢光明(审校)
2014-01-01
癫痫作为一种脑网络异常疾病，目前已有用复杂网络分析方法分析磁共振和脑电图数据等构建出全脑的结构和功能网络；这种源于图论分析的复杂网络方法，可以对连接所构网络进行量化分析，提供多种量化指标，可以帮助我们提高对癫痫发展及癫痫发作产生机制的认识。本文介绍了当前复杂网络的基本概念及其在癫痫疾病上的应用情况。%Epilepsy is a disease of aberrant network .Recent advances in MRI and electrophysiology with the complex brain networks based on graph theoretical analysis now make it possible to investigate structural and functional network of the entire brain ,and these techniques are able to quantify the analyses of functional connectivity network by a set of values and currently contribute to our understanding of the mechanisms underlying the development of epilepsy and the generation of epileptic seizures .In this paper ,the authors discuss the multiple basic concepts in complex networks and the current ap-plications of complex network in epilepsy .
Epidemiologic Considerations in Network Modeling of Theoretical Disease Events
2006-12-01
networks in the one Canadian province [9] and networks of livestock movements in Great Britain [10], [11]. GIS and the common use of geocodes , such as...privacy, and network visualization is no exception. Like other analysis tools such as data mining, or Geographic Information Systems ( GIS ), network...Depending on the population density of the area under study, the precision of the geocode , the background detail on the map, and the visualization
DEVELOPMENT OF INTERNATIONAL TRADE NETWORKS: THEORETICAL AND PRACTICAL ASPECTS
Directory of Open Access Journals (Sweden)
Ishkhanov A. V.
2015-09-01
Full Text Available Both the research of the theoretical aspects and the experience of formation and development of trade networks are now becoming increasingly important. Network trade is one of the fastest growing sectors of the economy in many countries. Economic globalization and liberalization of international trade predetermined active distribution network and rapid growth companies. The article considers the details of the processes of creation and development of trade networks in Western Europe and the USA, as well as experience in the development of multinational companies overseas consumer markets (mainly developing countries. The basic stages of development of a network of trade are identified and the characteristics of each stage are described in details. We have studied in detail the work of Russian and foreign scientists of different economic schools of thought on the problems of integration of the enterprises and the development of a network of trade. The authors conclude that the change in the conditions of doing business in today's environment requires additional research and theoretical studies on the problems of accelerated integration of enterprises and the development of international trade networks
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.
Dental Photothermal Radiometry: Theoretical Analysis.
Matvienko, Anna; Jeon, Raymond; Mandelis, Andreas; Abrams, Stephen
2007-03-01
Dental enamel demineralization in its early stages is very difficult to detect with conventional x-rays or visual examination. High-resolution techniques, such as scanning electron microscopy, usually require destruction of the tooth. Photothermal Radiomety (PTR) was recently applied as a safe, non-destructive, and highly sensitive tool for the detection of early dental demineralization, artificially created on the enamel surface. The experiments showed very high sensitivity of the measured signal to incipient changes in the surface structure, emphasizing the clinical capabilities of the method. In order to analyze the biothermophotonic phenomena in a tooth sample during the photothermal excitation, a theoretical model featuring coupled diffuse-photon-density-wave and thermal-wave fields was developed. Numerical simulations identified the effects on the PTR signal of changes in optical and thermal properties of enamel and dentin as a result of demineralization. The model predictions and experimental results will be compared and discussed.
An information theoretic approach for combining neural network process models.
Sridhar, D V.; Bartlett, E B.; Seagrave, R C.
1999-07-01
Typically neural network modelers in chemical engineering focus on identifying and using a single, hopefully optimal, neural network model. Using a single optimal model implicitly assumes that one neural network model can extract all the information available in a given data set and that the other candidate models are redundant. In general, there is no assurance that any individual model has extracted all relevant information from the data set. Recently, Wolpert (Neural Networks, 5(2), 241 (1992)) proposed the idea of stacked generalization to combine multiple models. Sridhar, Seagrave and Barlett (AIChE J., 42, 2529 (1996)) implemented the stacked generalization for neural network models by integrating multiple neural networks into an architecture known as stacked neural networks (SNNs). SNNs consist of a combination of the candidate neural networks and were shown to provide improved modeling of chemical processes. However, in Sridhar's work SNNs were limited to using a linear combination of artificial neural networks. While a linear combination is simple and easy to use, it can utilize only those model outputs that have a high linear correlation to the output. Models that are useful in a nonlinear sense are wasted if a linear combination is used. In this work we propose an information theoretic stacking (ITS) algorithm for combining neural network models. The ITS algorithm identifies and combines useful models regardless of the nature of their relationship to the actual output. The power of the ITS algorithm is demonstrated through three examples including application to a dynamic process modeling problem. The results obtained demonstrate that the SNNs developed using the ITS algorithm can achieve highly improved performance as compared to selecting and using a single hopefully optimal network or using SNNs based on a linear combination of neural networks.
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.
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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.
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
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
Theoretical Guidelines for the Utilization of Instructional Social Networking Websites
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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
Mathias, Carlos Leonardo Kelmer
2014-01-01
In general, the paper develops a historiographical debate about the methodology of social network analysis. More than responding questions using such methodology, this article tries to introduce the historian to the founder bibliography of social network analysis. Since the publication of the famous article by John Barnes in 1954, sociologists linked to sociometric studies have usually employed the social network analysis in their studies. On the other hand, this methodology is not widespread...
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 Treatment of Target Coverage in Wireless Sensor Networks
Institute of Scientific and Technical Information of China (English)
Yu Gu; Bao-Hua Zhao; Yu-Sheng Ji; Jie Li
2011-01-01
The target coverage is an important yet challenging problem in wireless sensor networks, especially when both coverage and energy constraints should be taken into account. Due to its nonlinear nature, previous studies of this problem have mainly focused on heuristic algorithms; the theoretical bound remains unknown. Moreover, the most popular method used in the previous literature, I.e., discretization of continuous time, has yet to be justified. This paper fills in these gaps with two theoretical results. The first one is a formal justification for the method. We use a simple example to illustrate the procedure of transforming a solution in time domain into a corresponding solution in the pattern domain with the same network lifetime and obtain two key observations. After that, we formally prove these two observations and use them as the basis to justify the method. The second result is an algorithm that can guarantee the network lifetime to be at least (1 -ε) of the optimal network lifetime, where ε can be made arbitrarily small depending on the required precision. The algorithm is based on the column generation (CG) theory, which decomposes the original problem into two sub-problems and iteratively solves them in a way that approaches the optimal solution. Moreover, we developed several constructive approaches to further optimize the algorithm. Numerical results verify the efficiency of our CG-based algorithm.
Reverse Engineering Cellular Networks with Information Theoretic Methods
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Julio R. Banga
2013-05-01
Full Text Available Building mathematical models of cellular networks lies at the core of systems biology. It involves, among other tasks, the reconstruction of the structure of interactions between molecular components, which is known as network inference or reverse engineering. Information theory can help in the goal of extracting as much information as possible from the available data. A large number of methods founded on these concepts have been proposed in the literature, not only in biology journals, but in a wide range of areas. Their critical comparison is difficult due to the different focuses and the adoption of different terminologies. Here we attempt to review some of the existing information theoretic methodologies for network inference, and clarify their differences. While some of these methods have achieved notable success, many challenges remain, among which we can mention dealing with incomplete measurements, noisy data, counterintuitive behaviour emerging from nonlinear relations or feedback loops, and computational burden of dealing with large data sets.
Theoretical properties of recursive neural networks with linear neurons.
Bianchini, M; Gori, M
2001-01-01
Recursive neural networks are a powerful tool for processing structured data, thus filling the gap between connectionism, which is usually related to poorly organized data, and a great variety of real-world problems, where the information is naturally encoded in the relationships among the basic entities. In this paper, some theoretical results about linear recursive neural networks are presented that allow one to establish conditions on their dynamical properties and their capability to encode and classify structured information. A lot of the limitations of the linear model, intrinsically related to recursive processing, are inherited by the general model, thus establishing their computational capabilities and range of applicability. As a byproduct of our study some connections with the classical linear system theory are given where the processing is extended from sequences to graphs.
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 Theoretical Analysis of Ball Spinning
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
As a special method of manufacturing thin wall tubes, the ball spinning process has been used for nearly 30 years because of its less investment of equipment, higher precision, and more perfect properties of products. However, the application is limited since the process parameters are determined based on empirical data and laboratory experiments for lack of a whole theoretical analysis. In this paper, some basic parameters such as the force and power parameters have been studied based on an analysis of geometry and mechanics of the process. The calculation of forming forces and the selection of the working angle are carried out. At the end, a perfect comparison between the results of the experiments and the theoretical analysis is made.
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
Phylogeny of metabolic networks: a spectral graph theoretical approach.
Deyasi, Krishanu; Banerjee, Anirban; Deb, Bony
2015-10-01
Many methods have been developed for finding the commonalities between different organisms in order to study their phylogeny. The structure of metabolic networks also reveals valuable insights into metabolic capacity of species as well as into the habitats where they have evolved. We constructed metabolic networks of 79 fully sequenced organisms and compared their architectures. We used spectral density of normalized Laplacian matrix for comparing the structure of networks. The eigenvalues of this matrix reflect not only the global architecture of a network but also the local topologies that are produced by different graph evolutionary processes like motif duplication or joining. A divergence measure on spectral densities is used to quantify the distances between various metabolic networks, and a split network is constructed to analyse the phylogeny from these distances. In our analysis, we focused on the species that belong to different classes, but appear more related to each other in the phylogeny. We tried to explore whether they have evolved under similar environmental conditions or have similar life histories. With this focus, we have obtained interesting insights into the phylogenetic commonality between different organisms.
Phylogeny of metabolic networks: A spectral graph theoretical approach
Indian Academy of Sciences (India)
Krishanu Deyasi; Anirban Banerjee; Bony Deb
2015-10-01
Many methods have been developed for finding the commonalities between different organisms in order to study their phylogeny. The structure of metabolic networks also reveals valuable insights into metabolic capacity of species as well as into the habitats where they have evolved. We constructed metabolic networks of 79 fully sequenced organisms and compared their architectures. We used spectral density of normalized Laplacian matrix for comparing the structure of networks. The eigenvalues of this matrix reflect not only the global architecture of a network but also the local topologies that are produced by different graph evolutionary processes like motif duplication or joining. A divergence measure on spectral densities is used to quantify the distances between various metabolic networks, and a split network is constructed to analyse the phylogeny from these distances. In our analysis, we focused on the species that belong to different classes, but appear more related to each other in the phylogeny. We tried to explore whether they have evolved under similar environmental conditions or have similar life histories. With this focus, we have obtained interesting insights into the phylogenetic commonality between different organisms.
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
Distributed game-theoretic topology control in cognitive networks
van den Berg, Eric; Fecko, Mariusz A.; Samtani, Sunil; Lacatus, Catalin; Patel, Mitesh
2010-04-01
Existing distributed approaches to topology control are poor at exploiting the large configuration space of cognitive radios and use extensive inter-node synchronization to aim at optimality. We have created a framework to design and study distributed topology control algorithms that combine network-formation games with machine learning. In our approach, carefully designed incentive mechanisms drive distributed autonomous agents towards a pre-determined system-wide optimum. The algorithms rely on game players to pursue selfish actions through low-complexity greedy algorithms with low or no signaling overhead. Convergence and stability are ensured through proper mechanism design that eliminates infinite adaptation process. The framework also includes game-theoretic extensions to influence behavior such as fragment merging and preferring links to weakly connected neighbors. Learning allows adaptations that prevent node starvation, reduce link flapping, and minimize routing disruptions by incorporating network layer feedback in cost/utility tradeoffs. The algorithms are implemented in Telcordia Wireless IP Scalable Network Emulator. Using greedy utility maximization as a benchmark, we show improvements of 13-40% for metrics such as the numbers of disconnected fragments and weakly connected nodes, topology stability, and disruption to user flows. The proposed framework is particularly suitable to cognitive radio networks because it can be extended to handle heterogeneous users with different utility functions and conflicting objectives. Desired outcome is then achieved by application of standard cooperation techniques such as utility transfer (payments). Additional cross-layer optimizations are possible by playing games at multiple layers in a highly scalable manner.
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.
A perturbation-theoretic approach to Lagrangian flow networks
Fujiwara, Naoya; Kirchen, Kathrin; Donges, Jonathan F.; Donner, Reik V.
2017-03-01
Complex network approaches have been successfully applied for studying transport processes in complex systems ranging from road, railway, or airline infrastructures over industrial manufacturing to fluid dynamics. Here, we utilize a generic framework for describing the dynamics of geophysical flows such as ocean currents or atmospheric wind fields in terms of Lagrangian flow networks. In this approach, information on the passive advection of particles is transformed into a Markov chain based on transition probabilities of particles between the volume elements of a given partition of space for a fixed time step. We employ perturbation-theoretic methods to investigate the effects of modifications of transport processes in the underlying flow for three different problem classes: efficient absorption (corresponding to particle trapping or leaking), constant input of particles (with additional source terms modeling, e.g., localized contamination), and shifts of the steady state under probability mass conservation (as arising if the background flow is perturbed itself). Our results demonstrate that in all three cases, changes to the steady state solution can be analytically expressed in terms of the eigensystem of the unperturbed flow and the perturbation itself. These results are potentially relevant for developing more efficient strategies for coping with contaminations of fluid or gaseous media such as ocean and atmosphere by oil spills, radioactive substances, non-reactive chemicals, or volcanic aerosols.
Theoretical discussions on the geometrical phase analysis
Energy Technology Data Exchange (ETDEWEB)
Rouviere, J.L. [CEA-Grenoble, Departement de Recherche Fondamentale sur la Matiere Condensee, SP2M, 17 rue des Martyrs, 38054 Grenoble Cedex 9 (France)]. E-mail: rouvierej@cea.fr; Sarigiannidou, E. [CEA-Grenoble, Departement de Recherche Fondamentale sur la Matiere Condensee, SP2M, 17 rue des Martyrs, 38054 Grenoble Cedex 9 (France)
2005-12-15
The Geometrical phase analysis, which is a very efficient method to measure deformation from High resolution transmission electron microscopy images, is studied from a theoretical point of view. We point out that the basic property of this method is its ability to measure local reciprocal lattice parameters with a high level of accuracy. We attempt to provide some insights into (a) different formula used in the geometrical phase analysis such as the well-known relation between phase and displacement: P{sub g}(r)=-2{pi}g.u(r), (b) the two different definitions of strain, each of which corresponding to a different lattice reference and (c) the meaning of a continuous displacement in a dot-like high resolution image. The case of one-dimensional analysis is also presented. Finally, we show that the method is able to give the position of the dot that is nearest to a given pixel in the image.
W. de Nooy
2009-01-01
Social network analysis (SNA) focuses on the structure of ties within a set of social actors, e.g., persons, groups, organizations, and nations, or the products of human activity or cognition such as web sites, semantic concepts, and so on. It is linked to structuralism in sociology stressing the si
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
Social Network Analysis Based on Network Motifs
2014-01-01
Based on the community structure characteristics, theory, and methods of frequent subgraph mining, network motifs findings are firstly introduced into social network analysis; the tendentiousness evaluation function and the importance evaluation function are proposed for effectiveness assessment. Compared with the traditional way based on nodes centrality degree, the new approach can be used to analyze the properties of social network more fully and judge the roles of the nodes effectively. I...
Intermittency in Switching Power Converters: Theoretical Analysis
Institute of Scientific and Technical Information of China (English)
ZHOU Yu-fei; CHEN Jun-ning; TSE Chi K.; QIU Shui-sheng; KE Dao-ming; SHI Long-xing; SUN Wei-feng
2006-01-01
In view of reasonable explanation of intermittent subharmonics and chaos that can be gained from coupling filter between circuits,this paper discusses a method that maps time bifurcation with parameter bifurcation.Based on this mapping method,the general analysis method of characteristic multiplier,which is originally aimed at parameter bifurcation,can be used for the study of intermittency,i.e.,time bifurcation.In this paper,all researches coming from characteristic multipliers,parameter-bifurcation diagrams,and the largest Lyapunov exponent indicate the same results as those produced by simulation and experiment.Thus,it is proved theoretically that the intermittency in switching power converter can be explained in terms of coupling of spurious interference.
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.
Analysis of a theoretically optimized transonic airfoil
Lores, M. E.; Burdges, K. P.; Shrewsbury, G. D.
1978-01-01
Numerical optimization was used in conjunction with an inviscid, full potential equation, transonic flow analysis computer code to design an upper surface contour for a conventional airfoil to improve its supercritical performance. The modified airfoil was tested in a compressible flow wind tunnel. The modified airfoil's performance was evaluated by comparison with test data for the baseline airfoil and for an airfoil developed by optimization of leading edge of the baseline airfoil. While the leading edge modification performed as expected, the upper surface re-design did not produce all of the expected performance improvements. Theoretical solutions computed using a full potential, transonic airfoil code corrected for viscosity were compared to experimental data for the baseline airfoil and the upper surface modification. These correlations showed that the theory predicted the aerodynamics of the baseline airfoil fairly well, but failed to accurately compute drag characteristics for the upper surface modification.
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.
Directory of Open Access Journals (Sweden)
Abdullah Ozkanlar
2014-03-01
Full Text Available Intermolecular chemical networks defined by the hydrogen bonds formed at the α-quartz|water interface have been data-mined using graph theoretical methods so as to identify and quantify structural patterns and dynamic behavior. Using molecular-dynamics simulations data, the hydrogen bond (H-bond distributions for the water-water and water-silanol H-bond networks have been determined followed by the calculation of the persistence of the H-bond, the dipole-angle oscillations that water makes with the surface silanol groups over time, and the contiguous H-bonded chains formed at the interface. Changes in these properties have been monitored as a function of surface coverage. Using the H-bond distribution between water and the surface silanol groups, the actual number of waters adsorbed to the surface is found to be 0.6 H2O/10 Å2, irrespective of the total concentration of waters within the system. The unbroken H-bond network of interfacial waters extends farther than in the bulk liquid; however, it is more fluxional at low surface coverages (i.e., the H-bond persistence in a monolayer of water is shorter than in the bulk Concentrations of H2O at previously determined water adsorption sites have also been quantified. This work demonstrates the complementary information that can be obtained through graph theoretical analysis of the intermolecular H-bond networks relative to standard analyses of molecular simulation data.
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...
Network Decomposition and Maximum Independent Set Part Ⅰ: Theoretic Basis
Institute of Scientific and Technical Information of China (English)
朱松年; 朱嫱
2003-01-01
The structure and characteristics of a connected network are analyzed, and a special kind of sub-network, which can optimize the iteration processes, is discovered. Then, the sufficient and necessary conditions for obtaining the maximum independent set are deduced. It is found that the neighborhood of this sub-network possesses the similar characters, but both can never be allowed incorporated together. Particularly, it is identified that the network can be divided into two parts by a certain style, and then both of them can be transformed into a pair sets network, where the special sub-networks and their neighborhoods appear alternately distributed throughout the entire pair sets network. By use of this characteristic, the network decomposed enough without losing any solutions is obtained. All of these above will be able to make well ready for developing a much better algorithm with polynomial time bound for an odd network in the the application research part of this subject.
The Analysis of Social Networks.
O'Malley, A James; Marsden, Peter V
2008-12-01
Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them to network data. This article reviews fundamentals of, and recent innovations in, social network analysis using a physician influence network as an example. After introducing forms of network data, basic network statistics, and common descriptive measures, it describes two distinct types of statistical models for network data: individual-outcome models in which networks enter the construction of explanatory variables, and relational models in which the network itself is a multivariate dependent variable. Complexities in estimating both types of models arise due to the complex correlation structures among outcome measures.
Collective Learning: Theoretical Perspectives and Ways To Support Networked Learning.
de Laat, Maarten; Simons, Robert-Jan
2002-01-01
Reviews three types of collective learning networks, teams, and communities. Advocates learning communities as a powerful way to stimulate shared learning. Warns that, although technology enables networked learning, group dynamics are crucial and must be considered. Describes progressive inquiry and team roles as ways to support collective…
Theoretical analysis of sheet metal formability
Zhu, Xinhai
Sheet metal forming processes are among the most important metal-working operations. These processes account for a sizable proportion of manufactured goods made in industrialized countries each year. Furthermore, to reduce the cost and increase the performance of manufactured products, in addition to the environmental concern, more and more light weight and high strength materials have been used as a substitute to the conventional steel. These materials usually have limited formability, thus, a thorough understanding of the deformation processes and the factors limiting the forming of sound parts is important, not only from a scientific or engineering viewpoint, but also from an economic point of view. An extensive review of previous studies pertaining to theoretical analyses of Forming Limit Diagrams (FLDs) is contained in Chapter I. A numerical model to analyze the neck evolution process is outlined in Chapter II. With the use of strain gradient theory, the effect of initial defect profile on the necking process is analyzed. In the third chapter, the method proposed by Storen and Rice is adopted to analyze the initiation of localized neck and predict the corresponding FLDs. In view of the fact that the width of the localized neck is narrow, the deformation inside the neck region is constrained by the material in the neighboring homogeneous region. The relative rotation effect may then be assumed to be small and is thus neglected. In Chapter IV, Hill's 1948 yield criterion and strain gradient theory are employed to obtain FLDs, for planar anisotropic sheet materials by using bifurcation analysis. The effects of the strain gradient coefficient c and the material anisotropic parameters R's on the orientation of the neck and FLDs are analyzed in a systematic manner and compared with experiments. In Chapter V, Hill's 79 non-quadratic yield criterion with a deformation theory of plasticity is used along with bifurcation analyses to derive a general analytical
Network analysis in public health: history, methods, and applications.
Luke, Douglas A; Harris, Jenine K
2007-01-01
Network analysis is an approach to research that is uniquely suited to describing, exploring, and understanding structural and relational aspects of health. It is both a methodological tool and a theoretical paradigm that allows us to pose and answer important ecological questions in public health. In this review we trace the history of network analysis, provide a methodological overview of network techniques, and discuss where and how network analysis has been used in public health. We show how network analysis has its roots in mathematics, statistics, sociology, anthropology, psychology, biology, physics, and computer science. In public health, network analysis has been used to study primarily disease transmission, especially for HIV/AIDS and other sexually transmitted diseases; information transmission, particularly for diffusion of innovations; the role of social support and social capital; the influence of personal and social networks on health behavior; and the interorganizational structure of health systems. We conclude with future directions for network analysis in public health.
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.
Information theoretic derivation of network architecture and learning algorithms
Energy Technology Data Exchange (ETDEWEB)
Jones, R.D.; Barnes, C.W.; Lee, Y.C.; Mead, W.C.
1991-01-01
Using variational techniques, we derive a feedforward network architecture that minimizes a least squares cost function with the soft constraint that the mutual information between input and output be maximized. This permits optimum generalization for a given accuracy. A set of learning algorithms are also obtained. The network and learning algorithms are tested on a set of test problems which emphasize time series prediction. 6 refs., 1 fig.
The Connectivity Analysis of Intermittent Connected Wireless Network
Institute of Scientific and Technical Information of China (English)
Li Yun; Zhou Yahui; Liu Qilie; Wang Xiaoying
2009-01-01
The connectivity is a basic and important characteristic to the network, it expresses the situation of link connectivity directly, and provides important reference for the entire network plan. Using statistics and probability Theory, this article emphasizes the probability between any two nodes in the network which nodes are equally distributed and the connectivity of whole network. At last, this article has made verification through simulation and has made out a conclusion, the simulation result agrees with theoretical analysis.
Spectral entropies as information-theoretic tools for complex network comparison
De Domenico, Manlio
2016-01-01
Any physical system can be viewed from the perspective that information is implicitly represented in its state. However, the quantification of this information when it comes to complex networks has remained largely elusive. In this work, we use techniques inspired by quantum statistical mechanics to define an entropy measure for complex networks and to develop a set of information-theoretic tools, based on network spectral properties, such as Renyi q-entropy, generalized Kullback-Leibler and Jensen-Shannon divergences, the latter allowing us to define a natural distance measure between complex networks. First we show that by minimizing the Kullback-Leibler divergence between an observed network and a parametric network model, inference of model parameter(s) by means of maximum-likelihood estimation can be achieved and model selection can be performed appropriate information criteria. Second, we show that the information-theoretic metric quantifies the distance between pairs of networks and we can use it, for ...
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
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
Theoretical Investigation of Optical Computing Based on Neural Network Models.
1987-09-29
associated output vectors ym. Alternatively, error driven algorithms such as the perceptron or adaline can be used to iteratively train the memory by...from which the state of the entire network can be calculated). The perceptron [21] and adaline [221 algorithms are examples of error driven learning
Jamming in Mobile Networks: A Game-Theoretic Approach
2013-03-01
of maintaining connectiv - ity among autonomous agents. Based on tools from potential field methods and algebraic graph theory, centralized algorithms...special conditions the new notion provides a sufficient condition for global connectiv - ity of the network. In [31], the authors use the weighted graph
Disability and Humans Rights: A Theoretical Analysis
Directory of Open Access Journals (Sweden)
PATRICIA CUENCA GÓMEZ
2015-06-01
Full Text Available Since Enlightenment, theories of justice and, in particular, theories of human rights have been based on principles which are excludable for people with disabilities. The exclusion has not been resolved by contemporary theories of justice. A profound review of some basic assumptions is required to get a full and sound theory of human rights including people with disabilities in equal terms. The inclusion of people with disabilities is an urgent theoretical challenge which must be face in order to perform a sound reform of rules in legal practice.
Identifying Tipping Points in a Decision-Theoretic Model of Network Security
Heimann, C. F. Larry; Nochenson, Alan
2012-01-01
Although system administrators are frequently urged to protect the machines in their network, the fact remains that the decision to protect is far from universal. To better understand this decision, we formulate a decision-theoretic model of a system administrator responsible for a network of size n against an attacker attempting to penetrate the network and infect the machines with a virus or similar exploit. By analyzing the model we are able to demonstrate the cost sensitivity of smaller n...
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.
Theoretical model for mesoscopic-level scale-free self-organization of functional brain networks.
Piersa, Jaroslaw; Piekniewski, Filip; Schreiber, Tomasz
2010-11-01
In this paper, we provide theoretical and numerical analysis of a geometric activity flow network model which is aimed at explaining mathematically the scale-free functional graph self-organization phenomena emerging in complex nervous systems at a mesoscale level. In our model, each unit corresponds to a large number of neurons and may be roughly seen as abstracting the functional behavior exhibited by a single voxel under functional magnetic resonance imaging (fMRI). In the course of the dynamics, the units exchange portions of formal charge, which correspond to waves of activity in the underlying microscale neuronal circuit. The geometric model abstracts away the neuronal complexity and is mathematically tractable, which allows us to establish explicit results on its ground states and the resulting charge transfer graph modeling functional graph of the network. We show that, for a wide choice of parameters and geometrical setups, our model yields a scale-free functional connectivity with the exponent approaching 2, which is in agreement with previous empirical studies based on fMRI. The level of universality of the presented theory allows us to claim that the model does shed light on mesoscale functional self-organization phenomena of the nervous system, even without resorting to closer details of brain connectivity geometry which often remain unknown. The material presented here significantly extends our previous work where a simplified mean-field model in a similar spirit was constructed, ignoring the underlying network geometry.
Optimization Techniques for Analysis of Biological and Social Networks
2012-03-28
systematic fashion under a unifying theoretical and algorithmic framework . Optimization, Complex Networks, Social Network Analysis, Computational...analyzing a new metaheuristic technique, variable objective search. 3. Experimentation and application: Implement the proposed algorithms, test and fine...exact solutions are presented. In [3], we introduce the variable objective search framework for combinatorial optimization. The method utilizes
Biomass Rapid Analysis Network (BRAN)
Energy Technology Data Exchange (ETDEWEB)
2003-10-01
Helping the emerging biotechnology industry develop new tools and methods for real-time analysis of biomass feedstocks, process intermediates and The Biomass Rapid Analysis Network is designed to fast track the development of modern tools and methods for biomass analysis to accelerate the development of the emerging industry. The network will be led by industry and organized and coordinated through the National Renewable Energy Lab. The network will provide training and other activities of interest to BRAN members. BRAN members will share the cost and work of rapid analysis method development, validate the new methods, and work together to develop the training for the future biomass conversion workforce.
Introduction to Social Network Analysis
Zaphiris, Panayiotis; Ang, Chee Siang
Social Network analysis focuses on patterns of relations between and among people, organizations, states, etc. It aims to describe networks of relations as fully as possible, identify prominent patterns in such networks, trace the flow of information through them, and discover what effects these relations and networks have on people and organizations. Social network analysis offers a very promising potential for analyzing human-human interactions in online communities (discussion boards, newsgroups, virtual organizations). This Tutorial provides an overview of this analytic technique and demonstrates how it can be used in Human Computer Interaction (HCI) research and practice, focusing especially on Computer Mediated Communication (CMC). This topic acquires particular importance these days, with the increasing popularity of social networking websites (e.g., youtube, myspace, MMORPGs etc.) and the research interest in studying them.
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.
A theoretical analysis of the electrogastrogram (EGG).
Calder, Stefan; Cheng, Leo K; Peng Du
2014-01-01
In this study, a boundary element model was developed to investigate the relationship between the gastric electrical activity, also known as slow waves, and the electrogastrogram (EGG). A dipole was calculated to represent the equivalent net activity of gastric slow waves. The dipole was then placed in an anatomically-realistic torso model to simulate EGG. The torso model was constructed from a laser-scanned geometry of an adult male torso phantom with 190 electrode sites equally distributed around the torso so that simulated EGG could be directly compared between the physical model and the mathematical model. The results were analyzed using the Fast Fourier Transforms (FFT), spatial distribution of EGG potential and a resultant EGG based on a 3-lead configuration. The FFT results showed both the dipole and EGG contained identical dominant frequency component of 3 cycles per minute (cpm), with this result matching known physiological phenomenon. The -3 dB point of the EGG was 110 mm from the region directly above the dipole source. Finally, the results indicated that electrode coupling could theoretically be used in a similar fashion to ECG coupling to gain greater understanding of how EGG correlate to gastric slow waves.
Catalytic efficiency of enzymes: a theoretical analysis.
Hammes-Schiffer, Sharon
2013-03-26
This brief review analyzes the underlying physical principles of enzyme catalysis, with an emphasis on the role of equilibrium enzyme motions and conformational sampling. The concepts are developed in the context of three representative systems, namely, dihydrofolate reductase, ketosteroid isomerase, and soybean lipoxygenase. All of these reactions involve hydrogen transfer, but many of the concepts discussed are more generally applicable. The factors that are analyzed in this review include hydrogen tunneling, proton donor-acceptor motion, hydrogen bonding, pKa shifting, electrostatics, preorganization, reorganization, and conformational motions. The rate constant for the chemical step is determined primarily by the free energy barrier, which is related to the probability of sampling configurations conducive to the chemical reaction. According to this perspective, stochastic thermal motions lead to equilibrium conformational changes in the enzyme and ligands that result in configurations favorable for the breaking and forming of chemical bonds. For proton, hydride, and proton-coupled electron transfer reactions, typically the donor and acceptor become closer to facilitate the transfer. The impact of mutations on the catalytic rate constants can be explained in terms of the factors enumerated above. In particular, distal mutations can alter the conformational motions of the enzyme and therefore the probability of sampling configurations conducive to the chemical reaction. Methods such as vibrational Stark spectroscopy, in which environmentally sensitive probes are introduced site-specifically into the enzyme, provide further insight into these aspects of enzyme catalysis through a combination of experiments and theoretical calculations.
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.
The Analysis of Social Networks
O’Malley, A James; Marsden, Peter V.
2008-01-01
Many questions about the social organization of medicine and health services involve interdependencies among social actors that may be depicted by networks of relationships. Social network studies have been pursued for some time in social science disciplines, where numerous descriptive methods for analyzing them have been proposed. More recently, interest in the analysis of social network data has grown among statisticians, who have developed more elaborate models and methods for fitting them...
A theoretical design for learning model addressing the networked society
DEFF Research Database (Denmark)
Levinsen, Karin; Nielsen, Janni; Sørensen, Birgitte Holm
2010-01-01
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......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 tension between time resources and the demand for educational quality. Our approach is based on constructivist and social constructivist traditions but we are required to measure students according to a list of learning goals. The size of curriculum is growing while the time available for learning...
Theoretical analysis of HVAC duct hanger systems
Miller, R. D.
1987-01-01
Several methods are presented which, together, may be used in the analysis of duct hanger systems over a wide range of frequencies. The finite element method (FEM) and component mode synthesis (CMS) method are used for low- to mid-frequency range computations and have been shown to yield reasonably close results. The statistical energy analysis (SEA) method yields predictions which agree with the CMS results for the 800 to 1000 Hz range provided that a sufficient number of modes participate. The CMS approach has been shown to yield valuable insight into the mid-frequency range of the analysis. It has been demonstrated that it is possible to conduct an analysis of a duct/hanger system in a cost-effective way for a wide frequency range, using several methods which overlap for several frequency bands.
Multifractal analysis of weighted networks by a modified sandbox algorithm
Song, Yu-Qin; Yu, Zu-Guo; Li, Bao-Gen
2015-01-01
Complex networks have attracted growing attention in many fields. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. Some algorithms for MFA of unweighted complex networks have been proposed in the past a few years, including the sandbox (SB) algorithm recently employed by our group. In this paper, a modified SB algorithm (we call it SBw algorithm) is proposed for MFA of weighted networks.First, we use the SBw algorithm to study the multifractal property of two families of weighted fractal networks (WFNs): "Sierpinski" WFNs and "Cantor dust" WFNs. We also discuss how the fractal dimension and generalized fractal dimensions change with the edge-weights of the WFN. From the comparison between the theoretical and numerical fractal dimensions of these networks, we can find that the proposed SBw algorithm is efficient and feasible for MFA of weighted networks. Then, we apply...
Theoretical mean-variance relationship of IP network traffic based on ON/OFF model
Institute of Scientific and Technical Information of China (English)
JIN Yi; ZHOU Gang; JIANG DongChen; YUAN Shuai; WANG LiLi; CAO JianTing
2009-01-01
Mean-variance relationship (MVR), nowadays agreed in power law form, is an important function. It Is currently used by traffic matrix estimation as a basic statistical assumption. Because all the existing papers obtain MVR only through empirical ways, they cannot provide theoretical support to power law MVR or the definition of its power exponent. Furthermore, because of the lack of theoretical model, all traffic matrix estimation methods based on MVR have not been theoretically supported yet. By observ-ing both our laboratory and campus network for more than one year, we find that such an empirical MVR is not sufficient to describe actual network traffic. In this paper, we derive a theoretical MVR from ON/OFF model. Then we prove that current empirical power law MVR is generally reasonable by the fact that it is an approximate form of theoretical MVR under specific precondition, which can theoretically support those traffic matrix estimation algorithms of using MVR. Through verifying our MVR by actual observation and public DECPKT traces, we verify that our theoretical MVR Is valid and more capable of describing actual network traffic than power law MVR.
Artificial Neural Network Analysis System
2007-11-02
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
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...... with a view of reducing the required number of bits....
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.
A network analysis of Sibiu County, Romania
Grama, Cristina-Nicol
2013-01-01
Network science methods have proved to be able to provide useful insights from both a theoretical and a practical point of view in that they can better inform governance policies in complex dynamic environments. The tourism research community has provided an increasing number of works that analyse destinations from a network science perspective. However, most of the studies refer to relatively small samples of actors and linkages. With this note we provide a full network study, although at a preliminary stage, that reports a complete analysis of a Romanian destination (Sibiu). Our intention is to increase the set of similar studies with the aim of supporting the investigations in structural and dynamical characteristics of tourism destinations.
An Approach to Structural Approximation Analysis by Artificial Neural Networks
Institute of Scientific and Technical Information of China (English)
陆金桂; 周济; 王浩; 陈新度; 余俊; 肖世德
1994-01-01
This paper theoretically proves that a three-layer neural network can be applied to implementing exactly the function between the stresses and displacements and the design variables of any elastic structure based on the Kolmogorov’s mapping neural network existence theorem. A new approach to the structural approximation analysis with the global characteristic based on artificial neural networks is presented. The computer simulation experiments made by this paper show that the new approach is effective.
Theoretical reflections on Wilhelm Reich's Character Analysis.
Shapiro, David
2002-01-01
The ideas contained in Wilhelm Reich's Character Analysis, while very influential, have not been thoroughly exploited in psychoanalysis and psychotherapy. These ideas, aimed particularly at producing genuine change rather than mere intellectual understanding, are reexamined. Further implications of them are discussed.
Active disturbance rejection control: methodology and theoretical analysis.
Huang, Yi; Xue, Wenchao
2014-07-01
The methodology of ADRC and the progress of its theoretical analysis are reviewed in the paper. Several breakthroughs for control of nonlinear uncertain systems, made possible by ADRC, are discussed. The key in employing ADRC, which is to accurately determine the "total disturbance" that affects the output of the system, is illuminated. The latest results in theoretical analysis of the ADRC-based control systems are introduced.
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
Katz Centrality of Markovian Temporal Networks: Analysis and Optimization
Ogura, Masaki
2016-01-01
Identifying important nodes in complex networks is a fundamental problem in network analysis. Although a plethora of measures has been proposed to identify important nodes in static (i.e., time-invariant) networks, there is a lack of tools in the context of temporal networks (i.e., networks whose connectivity dynamically changes over time). The aim of this paper is to propose a system-theoretic approach for identifying important nodes in temporal networks. In this direction, we first propose a generalization of the popular Katz centrality measure to the family of Markovian temporal networks using tools from the theory of Markov jump linear systems. We then show that Katz centrality in Markovian temporal networks can be efficiently computed using linear programming. Finally, we propose a convex program for optimizing the Katz centrality of a given node by tuning the weights of the temporal network in a cost-efficient manner. Numerical simulations illustrate the effectiveness of the obtained results.
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.
Hedging rule for reservoir operations: 1. A theoretical analysis
You, Jiing-Yun; Cai, Ximing
2008-01-01
Hedging rule policies for reservoir operations accept small deficits in current supply to reduce the probability of a severe water shortage later. This paper expands a theoretical analysis and develops a conceptual two-period model for reservoir operation with hedging that includes uncertain future reservoir inflow explicitly. Extended analysis of the model properties and influencing factors is presented with a general utility function, addressing (1) the starting and ending water availability for hedging, (2) the range of hedging that is related to water demand levels, (3) inflow uncertainty, and (4) evaporation loss. Some intuitive knowledge on reservoir operation is proved or reconfirmed analytically; and new knowledge is derived. This theoretical analysis provides an updated basis for further theoretical study, and the theoretical findings can be used to improve numerical modeling for reservoir operation.
Institute of Scientific and Technical Information of China (English)
曹琳琳
2011-01-01
目前,网络的发展极大推动了人类文明的进步,网络犯罪问题也络绎不绝的出现,而且呈现出平民化、反社会化、加速化、恶性化的特点,因此越来越成为社会关注的重点问题。网络犯罪作为新世纪各国共同面临的社会问题,理应也从社会学角度出发进行研究分析,本文试图应用社会解体理论,从网络犯罪所处的＂虚拟社会＂出发,探究其形成的原因,并提出相应的对策。%Currently,the network has greatly promoted the development of human civilization and progress,a constant stream of network crime problems also appear,and show a civilian、antisocial、accelerating technology,the characteristics of malignancy,it has increasingly become a social concern key issues.Network crime as the new century,the social problems facing all countries,should also be studied from a sociological point of view of analysis,this paper attempts to apply social disintegration theory,from which network crime ＂virtual society＂ starting to explore the reasons for its formation,and propose corresponding countermeasures.
A Theoretical Model for Understanding the Dynamics of Online Social Networks Decay
Abufouda, Mohammed
2016-01-01
Online social networks represent a main source of communication and information exchange in today's life. They facilitate exquisitely news sharing, knowledge elicitation, and forming groups of same interests. Researchers in the last two decades studied the growth dynamics of the online social networks extensively questing a clear understanding of the behavior of humans in online social networks that helps in many directions, like engineering better recommendation systems and attracting new members. However, not all of social networks achieved the desired growth, for example, online social networks like MySpace, Orkut, and Friendster are out of service today. In this work, we present a probabilistic theoretical model that captures the dynamics of the social decay due to the inactivity of the members of a social network. The model is proved to have some interesting mathematical properties, namely \\textit{submodularity}, which imply achieving the model optimization in a reasonable performance. That means the max...
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.
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.
Institute of Scientific and Technical Information of China (English)
Yan ZHANG; Hongmei ZHENG; Bin CHEN; Naijin YANG
2013-01-01
An important and practical pattern of industrial symbiosis is rapidly developing:eco-industrial parks.In this study,we used social network analysis to study the network connectedness (i.e.,the proportion of the theoretical number of connections that had been achieved) and related attributes of these hybrid ecological and industrial symbiotic systems.This approach provided insights into details of the network's interior and analyzed the overall degree of connectedness and the relationships among the nodes within the network.We then characterized the structural attributes of the network and subnetwork nodes at two levels (core and periphery),thereby providing insights into the operational problems within each eco-industrial park.We chose ten typical ecoindustrial parks in China and around the world and compared the degree of network connectedness of these systems that resulted from exchanges of products,byproducts,and wastes.By analyzing the density and nodal degree,we determined the relative power and status of the nodes in these networks,as well as other structural attributes such as the core-periphery structure and the degree of sub-network connectedness.The results reveal the operational problems created by the structure of the industrial networks and provide a basis for improving the degree of completeness,thereby increasing their potential for sustainable development and enriching the methods available for the study of industrial symbiosis.
Medial Cochlear Efferent Function: A Theoretical Analysis
Mountain, David C.
2011-11-01
Since the discovery of the cochlear efferent system, many hypotheses have been put forth for its function. These hypotheses for its function range from protecting the cochlea from over stimulation to improving the detection of sounds in noise. It is known that the medial efferent system innervates the outer hair cells and that stimulation of this system reduces basilar membrane and auditory nerve sensitivity which suggests that this system acts to decrease the gain of the cochlear amplifier. Here I present modeling results as well as analysis of published experimental data that suggest that the function of the medial efferent reflex is to decrease the cochlear amplifier gain by just the right amount so that the nonlinearity in the basilar membrane response lines up perfectly with the inner hair cell nonlinear transduction process to produce a hair cell receptor potential that is proportional to the logarithm of the sound pressure level.
Todinov, Michael T
2013-01-01
Repairable flow networks are a new area of research, which analyzes the repair and flow disruption caused by failures of components in static flow networks. This book addresses a gap in current network research by developing the theory, algorithms and applications related to repairable flow networks and networks with disturbed flows. The theoretical results presented in the book lay the foundations of a new generation of ultra-fast algorithms for optimizing the flow in networks after failures or congestion, and the high computational speed creates the powerful possibility of optimal control
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
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 Analysis of Reinforcement Tunnel Lining Corrosion
Directory of Open Access Journals (Sweden)
ZhiQiang Zhangand
2013-05-01
Full Text Available The main cause of ageing damage in reinforced concrete structures is reinforcement corrosion. Damage can be detected visually as coincident cracks along the reinforcement bar, which are significant of both reduction of the re-bar, cross-section and loss of bond strength for reinforced concrete. The reinforced concrete is one of the most widely used engineering materials as final lining of tunnels. The corrosion is common durability problems that have significant effect on the tunnel performance. This study intends to analysis reinforcement concrete corrosion at the tunnel lining by applying temperature expansion theory on steel through numerical simulation process, with expansive force effect. The thickness of concrete cover and the diameter of steel bar have an impact on the stress for reinforcement concrete during propagation of corrosion process. The corrosion cracks appear at the corner of a tunnel lining then in invert and vault because the maximum stress will be in the corner then in invert and vault. The internal force in the concrete lining changes differently when the corrosion rate change.
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
Institute of Scientific and Technical Information of China (English)
唐红涛
2015-01-01
虚拟商圈的不断扩大使之成为学者关注的焦点。本文在深入分析虚拟商圈成长机理的基础上，利用面板数据的变系数模型测算了虚拟商圈的网络外部性，结论显示不同虚拟商圈的网络外部性具有显著差异，并且这种差异主要是来自于虚拟商圈性质、品牌以及商品专业化程度。平台式虚拟商圈的网络外部性强于自营式虚拟商圈，知名度大的虚拟商圈网络外部性大，商业综合化程度高的虚拟商圈网络外部性大。%Virtual business circle expansion has increasingly become the focus of scholars .We use the variable coefficient panel data model to measure the network externality basing on the analysis of the growth mechanism of virtual business circle .Results show that network externalities of different virtual business circle has significant differences , and this difference is mainly from nature , brand and product specialization degree the of the virtual business circle .Network externality of platform virtual business cir-cle is stronger than the proprietary virtual business circle , and well-known virtual business circle and large integrated commercial .
A Theoretical Framework for Building Online Communities of Practice with Social Networking Tools
Gunawardena, Charlotte N.; Hermans, Mary Beth; Sanchez, Damien; Richmond, Carol; Bohley, Maribeth; Tuttle, Rebekah
2009-01-01
This paper proposes a theoretical framework as a foundation for building online communities of practice when a suite of social networking applications referred to as collective intelligence tools are utilized to develop a product or solutions to a problem. Drawing on recent developments in Web 2.0 tools, research on communities of practice and…
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.
Reliability Analysis of Wireless Sensor Networks Using Markovian Model
Directory of Open Access Journals (Sweden)
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.
Adaptive categorization of ART networks in robot behavior learning using game-theoretic formulation.
Fung, Wai-keung; Liu, Yun-hui
2003-12-01
Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to specify learning tasks accuracy and control learning attention before learning. In order to remedy the aforementioned difficulties, an adaptive categorization mechanism is introduced in ART networks for perceptual and action patterns categorization in this paper. A game-theoretic formulation of adaptive categorization for ART networks is proposed for vigilance parameter adaptation for category size control on the categories formed. The proposed vigilance parameter update rule can help improving categorization performance in the aspect of category number stability and solve the problem of selecting initial vigilance parameter prior to pattern categorization in traditional ART networks. Behavior learning using physical robot is conducted to demonstrate the effectiveness of the proposed adaptive categorization mechanism in ART networks.
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...
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.
Vulnerability Analysis for Complex Networks Using Aggressive Abstraction
Colbaugh, Richard
2010-01-01
Large, complex networks are ubiquitous in nature and society, and there is great interest in developing rigorous, scalable methods for identifying and characterizing their vulnerabilities. This paper presents an approach for analyzing the dynamics of complex networks in which the network of interest is first abstracted to a much simpler, but mathematically equivalent, representation, the required analysis is performed on 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 vulnerability-preserving, finite state abstractions, and develop efficient algorithms for computing these abstractions. We then propose a vulnerability analysis methodology which combines these finite state abstractions with formal analytics from theoretical computer science to yield a comprehensive vulnerability analysis process for networks of realworld scale and complexity. The potential of the prop...
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
Barreiro, Andrea K; Gautam, Shree Hari; Shew, Woodrow L; Ly, Cheng
2017-10-02
Determining how synaptic coupling within and between regions is modulated during sensory processing is an important topic in neuroscience. Electrophysiological recordings provide detailed information about neural spiking but have traditionally been confined to a particular region or layer of cortex. Here we develop new theoretical methods to study interactions between and within two brain regions, based on experimental measurements of spiking activity simultaneously recorded from the two regions. By systematically comparing experimentally-obtained spiking statistics to (efficiently computed) model spike rate statistics, we identify regions in model parameter space that are consistent with the experimental data. We apply our new technique to dual micro-electrode array in vivo recordings from two distinct regions: olfactory bulb (OB) and anterior piriform cortex (PC). Our analysis predicts that: i) inhibition within the afferent region (OB) has to be weaker than the inhibition within PC, ii) excitation from PC to OB is generally stronger than excitation from OB to PC, iii) excitation from PC to OB and inhibition within PC have to both be relatively strong compared to presynaptic inputs from OB. These predictions are validated in a spiking neural network model of the OB-PC pathway that satisfies the many constraints from our experimental data. We find when the derived relationships are violated, the spiking statistics no longer satisfy the constraints from the data. In principle this modeling framework can be adapted to other systems and be used to investigate relationships between other neural attributes besides network connection strengths. Thus, this work can serve as a guide to further investigations into the relationships of various neural attributes within and across different regions during sensory processing.
NEAT: an efficient network enrichment analysis test
Signorelli, Mirko; Vinciotti, Veronica; Wit, Ernst C
2016-01-01
Background Network enrichment analysis is a powerful method, which allows to integrate gene enrichment analysis with the information on relationships between genes that is provided by gene networks. Existing tests for network enrichment analysis deal only with undirected networks, they can be computationally slow and are based on normality assumptions. Results We propose NEAT, a test for network enrichment analysis. The test is based on the hypergeometric distribution, which naturally arises ...
A Theoretical and Empirical Analysis of Expected Sarsa
van Seijen, Harm; van Hasselt, Hado; Whiteson, Shimon; Wiering, Marco
2009-01-01
This paper presents a theoretical and empirical analysis of Expected Sarsa, a variation on Sarsa, the classic on policy temporal-difference method for model-free reinforcement learning. Expected Sarsa exploits knowledge about stochasticity in the behavior policy to perform updates with lower varianc
A theoretical and empirical analysis of expected sarsa
Seijen, H.H. van; Hasselt, H. van; Whiteson, S.; Wiering, M.
2009-01-01
This paper presents a theoretical and empirical analysis of Expected Sarsa, a variation on Sarsa, the classic onpolicy temporal-difference method for model-free reinforcement learning. Expected Sarsa exploits knowledge about stochasticity in the behavior policy to perform updates with lower variance
Theoretical Analysis and Restructuring of Capacity Building for Sustainable Development
Institute of Scientific and Technical Information of China (English)
ZHOU Hailin; HUANG Jing
2001-01-01
On the basis of the interpretation of capacity building for sustainable development (CBSD) provided in Agenda 21, the paper develops a definition of CBSD for the first time by giving a full account of this basic concept and its essential connotation. Besides, a theoretical analysis of the importance, approach and role of capacity building in implementing the strategy of sustainable development is presented.
PRICE DISCRIMINATION AND MARKET POWER: A THEORETICAL ANALYSIS
Directory of Open Access Journals (Sweden)
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.
Institute of Scientific and Technical Information of China (English)
卢志刚; 李学平
2011-01-01
输电网在线理论线损分析有时需要根据公共信息模型自动生成电网单线图,此时必须实现电网布局的自动生成;对于大电网,需要较短的求解时间。自动布局一般存在容易陷入局部最优解和求解时间长2种问题。文中将输电网单线图布局转化为二次分配问题,并且采用蚁群算法和3-opt优化,解决了以上问题。考虑可能的并行计算扩展,算法忽略各蚂蚁间的信息素更新,选择局部最优解和全局最优解更新信息素。仿真结果布局清晰,求解时间短,能够满足输电网在线理论线损分析要求。%To meet occasional needs for automatic generation of power network single-line diagrams from the common information model（CIM） in power transmission network online theoretical line loss analysis,it is necessary for the big power network to automatically generate its network layout and ask for rather short solving-time.In view of the problems with automatic plating,namely,local optimum and the long solving time,the plating of single-line diagrams for power transmission networks is transformed into a quadratic assignment problem using the ant colony algorithm with 3-opt optimization.By taking into consideration potential parallel computation,local optimum and global optimum are chosen to update the pheromone while ignoring pheromone updating between ants.Simulation results show that the requirement of the power transmission network online theoretical line loss analysis is met by clear layout and short solving time. This work is supported by National Natural Science Foundation of China（No.61071201） and Natural Science Foundation of Hebei Province（No.F2010001319）.
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).
Hayashi, Yohei; Senda, Toshiya; Sano, Norihiko; Horikoshi, Masami
2009-07-01
A rapid increase in research on the relationship between histone modifications and their subsequent reactions in the nucleus has revealed that the histone modification system is complex, and robust against point mutations. The prevailing theoretical framework (the histone code hypothesis) is inadequate to explain either the complexity or robustness, making the formulation of a new theoretical framework both necessary and desirable. Here, we develop a model of the regulatory network of histone modifications in which we encode histone modifications as nodes and regulatory interactions between histone modifications as links. This network has scale-free properties and subnetworks with a pseudo-mirror symmetry structure, which supports the robustness of the histone modification network. In addition, we show that the unstructured tail regions of histones are suitable for the acquisition of this scale-free property. Our model and related insights provide the first framework for an overall architecture of a histone modification network system, particularly with regard to the structural and functional roles of the unstructured histone tail region. In general, the post-translational "modification webs" of natively unfolded regions (proteins) may function as signal routers for the robust processing of the large amounts of signaling information.
Security Analysis of Selected AMI Failure Scenarios Using Agent Based Game Theoretic Simulation
Energy Technology Data Exchange (ETDEWEB)
Abercrombie, Robert K [ORNL; Schlicher, Bob G [ORNL; Sheldon, Frederick T [ORNL
2014-01-01
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 Advanced Metering Infrastructure (AMI) functional domain which the National Electric Sector Cyber security Organization Resource (NESCOR) working group has currently documented 29 failure scenarios. The strategy for the game was developed by analyzing five electric sector representative failure scenarios contained in the AMI functional domain. From these five selected scenarios, we characterize them into three specific threat categories affecting confidentiality, integrity and availability (CIA). The analysis using our ABGT simulation demonstrates how to model the AMI functional domain using a set of rationalized game theoretic rules decomposed from the failure scenarios in terms of how those scenarios might impact the AMI network with respect to CIA.
Multifractal analysis of weighted networks by a modified sandbox algorithm
Song, Yu-Qin; Liu, Jin-Long; Yu, Zu-Guo; Li, Bao-Gen
2015-12-01
Complex networks have attracted growing attention in many fields. As a generalization of fractal analysis, multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. Some algorithms for MFA of unweighted complex networks have been proposed in the past a few years, including the sandbox (SB) algorithm recently employed by our group. In this paper, a modified SB algorithm (we call it SBw algorithm) is proposed for MFA of weighted networks. First, we use the SBw algorithm to study the multifractal property of two families of weighted fractal networks (WFNs): “Sierpinski” WFNs and “Cantor dust” WFNs. We also discuss how the fractal dimension and generalized fractal dimensions change with the edge-weights of the WFN. From the comparison between the theoretical and numerical fractal dimensions of these networks, we can find that the proposed SBw algorithm is efficient and feasible for MFA of weighted networks. Then, we apply the SBw algorithm to study multifractal properties of some real weighted networks — collaboration networks. It is found that the multifractality exists in these weighted networks, and is affected by their edge-weights.
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...... has much to offer in analyzing the policy process....
GRAPH THEORETICAL AND NETWORKS APPROACH FOR THE DEVELOPMENT OF A LEARNING MODEL – A CASE STUDY
Directory of Open Access Journals (Sweden)
PROF. DR. P. K. SRIMANI
2012-08-01
Full Text Available This paper deals with the graph theoretical approach for developing a framework for the Learning model used to optimise the Mathematical Pathway in children at the elementary level and verifying it by usingNetworks model. Data collected pertaining to the mathematical concepts a child needs to learn at elementary level [Class I to VII] is represented by using Concept Flow Graphs and are optimized by using graph theory techniques and algorithms by rearranging nodes as per the learning progression, partitioning the graphs into subgraphsto represent levels of learning, optimizing the sub-graphs using merging and elimination technique and identifying / marking the optional nodes. The design of the framework by using the graph theoretical approach is validated by the application of the Networks approach and this is used to design the Mathematical Pathwaydriver which is the core component of the Learning model. This approach is novel and the Learning model developed is highly accurate.
Category theoretic analysis of single-photon decision maker
Kim, Makoto Naruse Song-Ju; Berthel, Martin; Drezet, Aurélien; Huant, Serge; Hori, Hirokazu
2016-01-01
Decision making is a vital function in the era of artificial intelligence; however, its physical realizations and their theoretical fundamentals are not yet known. In our former study [Sci. Rep. 5, 513253 (2015)], we demonstrated that single photons can be used to make decisions in uncertain, dynamically changing environments. The multi-armed bandit problem was successfully solved using the dual probabilistic and particle attributes of single photons. Herein, we present the category theoretic foundation of the single-photon-based decision making, including quantitative analysis that agrees well with the experimental results. The category theoretic model unveils complex interdependencies of the entities of the subject matter in the most simplified manner, including a dynamically changing environment. In particular, the octahedral structure in triangulated categories provides a clear understanding of the underlying mechanisms of the single-photon decision maker. This is the first demonstration of a category the...
A Game Theoretic Framework for Power Control in Wireless Sensor Networks (POSTPRINT)
2010-02-01
IEEE Published by the IEEE Computer Society Authorized licensed use limited to: ROME AFB. Downloaded on July 20,2010 at 10:57:32 UTC from IEEE Xplore . Restrictions...from IEEE Xplore . Restrictions apply. sensor network using repeated stage games [19]. A game theoretic energy balance routing (GTEBR) algorithm has...AFB. Downloaded on July 20,2010 at 10:57:32 UTC from IEEE Xplore . Restrictions apply. Fig. 1 shows node w as the receiver under consideration. Node
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 theoretical capacitance of graphene and exhibiting high charge–discharge cycling stability....
Directory of Open Access Journals (Sweden)
Daichi Sone
Full Text Available Psychosis is one of the most important psychiatric comorbidities in temporal lobe epilepsy (TLE, and its pathophysiology still remains unsolved. We aimed to explore the connectivity differences of structural neuroimaging between TLE with and without psychosis using a graph theoretical analysis, which is an emerging mathematical method to investigate network connections in the brain as a small-world system.We recruited 11 TLE patients with unilateral hippocampal sclerosis (HS presenting psychosis or having a history of psychosis (TLE-P group. As controls, 15 TLE patients with unilateral HS without any history of psychotic episodes were also recruited (TLE-N group. For graph theoretical analysis, the normalized gray matter images of both groups were subjected to Graph Analysis Toolbox (GAT. As secondary analyses, each group was compared to 14 age- and gender-matched healthy subjects.The hub node locations were found predominantly in the ipsilateral hemisphere in the TLE-N group, and mainly on the contralateral side in the TLE-P group. The TLE-P group showed significantly higher characteristic path length, transitivity, lower global efficiency, and resilience to random or targeted attack than those of the TLE-N group. The regional comparison in betweenness centrality revealed significantly decreased connectivity in the contralateral temporal lobe, ipsilateral middle frontal gyrus, and bilateral postcentral gyri in the TLE-P group. The healthy subjects showed well-balanced nodes/edges distributions, similar metrics to TLE-N group except for higher small-worldness/modularity/assortativity, and various differences of regional betweenness/clustering.In TLE with psychosis, graph theoretical analysis of structural imaging revealed disrupted connectivity in the contralateral hemisphere. The network metrics suggested that the existence of psychosis can bring vulnerability and decreased efficiency of the whole-brain network. The sharp differences in
Arguel, Amaël; Perez-Concha, Oscar; Li, Simon Y W; Lau, Annie Y S
2016-10-06
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.
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…
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…
Directory of Open Access Journals (Sweden)
R.Valli
2010-07-01
Full Text Available Power management is one of the vital issue in wireless sensor networks, where the lifetime of the networkrelies on battery powered nodes. Transmitting at high power reduces the lifetime of both the nodes andthe network. One efficient way of power management is to control the power at which the nodes transmit.In this paper, a virtual multiple input multiple output wireless sensor network (VMIMO-WSNcommunication architecture is considered and the power control of sensor nodes based on the approachof game theory is formulated. The use of game theory has proliferated, with a broad range of applicationsin wireless sensor networking. Approaches from game theory can be used to optimize node level as wellas network wide performance. The game here is categorized as an incomplete information game, in whichthe nodes do not have complete information about the strategies taken by other nodes. For virtualmultiple input multiple output wireless sensor network architecture considered, the Nash equilibrium isused to decide the optimal power level at which a node needs to transmit, to maximize its utility. Outcomeshows that the game theoretic approach considered for VMIMO-WSN architecture achieves the bestutility, by consuming less power.
Lee, JongHyup; Pak, Dohyun
2016-08-29
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.
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.
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.
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.
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.
Theoretical Analysis and Simulation of Jacking Procedure of Pantadome System
Institute of Scientific and Technical Information of China (English)
WANG Xiaodun; SHI Yongjiu; WANG Yuanqing; Kawaguchi Mamoru
2005-01-01
In order to obtain the principle of Pantadome lifting process and make theoretical foundation for practical applications, the core idea of Pantadome was introduced, which is to make a structure become a mechanism by temporarily removing some members during the process of construction.The abstract motion model was built. By determining the change of the coordinates of the hinge joint and that of each point of the structure, simulative analysis of the mechanical motion of Pantadome was realized. Then general program that simulates the lifting process of Pantadome was developed based on AutoCAD environment by Auto Lisp language. By completing the theoretical analysis of the lifting process of Pantadome, three-dimensional simulation of the lifting process of Pantadome was realized. And it is successfully applied to bidding work of practical engineering.
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 Heuristic Search Methods for Online POMDPs.
Ross, Stéphane; Pineau, Joelle; Chaib-Draa, Brahim
2008-01-01
Planning in partially observable environments remains a challenging problem, despite significant recent advances in offline approximation techniques. A few online methods have also been proposed recently, and proven to be remarkably scalable, but without the theoretical guarantees of their offline counterparts. Thus it seems natural to try to unify offline and online techniques, preserving the theoretical properties of the former, and exploiting the scalability of the latter. In this paper, we provide theoretical guarantees on an anytime algorithm for POMDPs which aims to reduce the error made by approximate offline value iteration algorithms through the use of an efficient online searching procedure. The algorithm uses search heuristics based on an error analysis of lookahead search, to guide the online search towards reachable beliefs with the most potential to reduce error. We provide a general theorem showing that these search heuristics are admissible, and lead to complete and ε-optimal algorithms. This is, to the best of our knowledge, the strongest theoretical result available for online POMDP solution methods. We also provide empirical evidence showing that our approach is also practical, and can find (provably) near-optimal solutions in reasonable time.
Reliability Analysis of Sensor Networks
Institute of Scientific and Technical Information of China (English)
JIN Yan; YANG Xiao-zong; WANG Ling
2005-01-01
To Integrate the capacity of sensing, communication, computing, and actuating, one of the compelling technological advances of these years has been the appearance of distributed wireless sensor network (DSN) for information gathering tasks. In order to save the energy, multi-hop routing between the sensor nodes and the sink node is necessary because of limited resource. In addition, the unpredictable conditional factors make the sensor nodes unreliable. In this paper, the reliability of routing designed for sensor network and some dependability issues of DSN, such as MTTF(mean time to failure) and the probability of connectivity between the sensor nodes and the sink node are analyzed.Unfortunately, we could not obtain the accurate result for the arbitrary network topology, which is # P-hard problem.And the reliability analysis of restricted topologies clustering-based is given. The method proposed in this paper will show us a constructive idea about how to place energyconstrained sensor nodes in the network efficiently from the prospective of reliability.
Rodríguez, J; Clemente, G; Sanjuán, N; Bon, J
2014-01-01
The drying kinetics of thyme was analyzed by considering different conditions: air temperature of between 40°C and 70°C , and air velocity of 1 m/s. A theoretical diffusion model and eight different empirical models were fitted to the experimental data. From the theoretical model application, the effective diffusivity per unit area of the thyme was estimated (between 3.68 × 10(-5) and 2.12 × 10 (-4) s(-1)). The temperature dependence of the effective diffusivity was described by the Arrhenius relationship with activation energy of 49.42 kJ/mol. Eight different empirical models were fitted to the experimental data. Additionally, the dependence of the parameters of each model on the drying temperature was determined, obtaining equations that allow estimating the evolution of the moisture content at any temperature in the established range. Furthermore, artificial neural networks were developed and compared with the theoretical and empirical models using the percentage of the relative errors and the explained variance. The artificial neural networks were found to be more accurate predictors of moisture evolution with VAR ≥ 99.3% and ER ≤ 8.7%.
Theoretical analysis of radiographic images by nonstationary Poisson processes
Energy Technology Data Exchange (ETDEWEB)
Tanaka, K.; Uchida, S. (Gifu Univ. (Japan)); Yamada, I.
1980-12-01
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.
Theoretical Analysis of Radiographic Images by Nonstationary Poisson Processes
Tanaka, Kazuo; Yamada, Isao; Uchida, Suguru
1980-12-01
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 of the 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.
Automated drawing of network plots in network meta-analysis.
Rücker, Gerta; Schwarzer, Guido
2016-03-01
In systematic reviews based on network meta-analysis, the network structure should be visualized. Network plots often have been drawn by hand using generic graphical software. A typical way of drawing networks, also implemented in statistical software for network meta-analysis, is a circular representation, often with many crossing lines. We use methods from graph theory in order to generate network plots in an automated way. We give a number of requirements for graph drawing and present an algorithm that fits prespecified ideal distances between the nodes representing the treatments. The method was implemented in the function netgraph of the R package netmeta and applied to a number of networks from the literature. We show that graph representations with a small number of crossing lines are often preferable to circular representations.
A network-theoretic approach for decompositional translation across Open Biological Ontologies.
Patel, Chintan O; Cimino, James J
2010-08-01
Biological ontologies are now being widely used for annotation, sharing and retrieval of the biological data. Many of these ontologies are hosted under the umbrella of the Open Biological Ontologies Foundry. In order to support interterminology mapping, composite terms in these ontologies need to be translated into atomic or primitive terms in other, orthogonal ontologies, for example, gluconeogenesis (biological process term) to glucose (chemical ontology term). Identifying such decompositional ontology translations is a challenging problem. In this paper, we propose a network-theoretic approach based on the structure of the integrated OBO relationship graph. We use a network-theoretic measure, called the clustering coefficient, to find relevant atomic terms in the neighborhood of a composite term. By eliminating the existing GO to ChEBI Ontology mappings from OBO, we evaluate whether the proposed approach can re-identify the corresponding relationships. The results indicate that the network structure provides strong cues for decompositional ontology translation and the existing relationships can be used to identify new translations.
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.
Theoretical analysis on x-ray cylindrical grating interferometer
Cong, Wenxiang; Wang, Ge
2015-01-01
Grating interferometer is a state of art x-ray imaging approach, which can simultaneously acquire information of x-ray attenuation, phase shift, and small angle scattering. This approach is very sensitive to micro-structural variation and offers superior contrast resolution for biological soft tissues. The present grating interferometer often uses flat gratings, with serious limitations in the field of view and the flux of photons. The use of curved gratings allows perpendicular incidence of x-rays on the gratings, and gives higher visibility over a larger field of view than a conventional interferometer with flat gratings. In the study, we present a rigorous theoretical analysis of the self-imaging of curved transmission gratings based on Rayleigh-Sommerfeld diffraction. Numerical simulations have demonstrated the self-imaging phenomenon of cylindrical grating interferometer. The theoretical results are in agreement with the results of numerical simulations.
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...... 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....
Information-Theoretical Complexity Analysis of Selected Elementary Chemical Reactions
Molina-Espíritu, M.; Esquivel, R. O.; Dehesa, J. S.
We investigate the complexity of selected elementary chemical reactions (namely, the hydrogenic-abstraction reaction and the identity SN2 exchange reaction) by means of the following single and composite information-theoretic measures: disequilibrium (D), exponential entropy(L), Fisher information (I), power entropy (J), I-D, D-L and I-J planes and Fisher-Shannon (FS) and Lopez-Mancini-Calbet (LMC) shape complexities. These quantities, which are functionals of the one-particle density, are computed in both position (r) and momentum (p) spaces. The analysis revealed that the chemically significant regions of these reactions can be identified through most of the single information-theoretic measures and the two-component planes, not only the ones which are commonly revealed by the energy, such as the reactant/product (R/P) and the transition state (TS), but also those that are not present in the energy profile such as the bond cleavage energy region (BCER), the bond breaking/forming regions (B-B/F) and the charge transfer process (CT). The analysis of the complexities shows that the energy profile of the abstraction reaction bears the same information-theoretical features of the LMC and FS measures, however for the identity SN2 exchange reaction does not hold a simple behavior with respect to the LMC and FS measures. Most of the chemical features of interest (BCER, B-B/F and CT) are only revealed when particular information-theoretic aspects of localizability (L or J), uniformity (D) and disorder (I) are considered.
Berezovska, Ganna; Mostarda, Stefano; Rao, Francesco
2012-01-01
Molecular simulations as well as single molecule experiments have been widely analyzed in terms order parameters, the latter representing candidate probes for the relevant degrees of freedom. Notwithstanding this approach is very intuitive, mounting evidence showed that such description is not accurate, leading to ambiguous definitions of states and wrong kinetics. To overcome these limitations a framework making use of order parameter fluctuations in conjunction with complex network analysis is investigated. Derived from recent advances in the analysis of single molecule time traces, this approach takes into account of the fluctuations around each time point to distinguish between states that have similar values of the order parameter but different dynamics. Snapshots with similar fluctuations are used as nodes of a transition network, the clusterization of which into states provides accurate Markov-State-Models of the system under study. Application of the methodology to theoretical models with a noisy orde...
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.
Web Page Design and Network Analysis.
Wan, Hakman A.; Chung, Chi-wai
1998-01-01
Examines problems in Web-site design from the perspective of network analysis. In view of the similarity between the hypertext structure of Web pages and a generic network, network analysis presents concepts and theories that provide insight for Web-site design. Describes the problem of home-page location and control of number of Web pages and…
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....
Energy-Efficient Resource Allocation in Wireless Networks: An Overview of Game-Theoretic Approaches
Meshkati, Farhad; Schwartz, Stuart C
2007-01-01
An overview of game-theoretic approaches to energy-efficient resource allocation in wireless networks is presented. Focusing on multiple-access networks, it is demonstrated that game theory can be used as an effective tool to study resource allocation in wireless networks with quality-of-service (QoS) constraints. A family of non-cooperative (distributed) games is presented in which each user seeks to choose a strategy that maximizes its own utility while satisfying its QoS requirements. The utility function considered here measures the number of reliable bits that are transmitted per joule of energy consumed and, hence, is particulary suitable for energy-constrained networks. The actions available to each user in trying to maximize its own utility are at least the choice of the transmit power and, depending on the situation, the user may also be able to choose its transmission rate, modulation, packet size, multiuser receiver, multi-antenna processing algorithm, or carrier allocation strategy. The best-respo...
Topological Analysis of Urban Drainage Networks
Yang, Soohyun; Paik, Kyungrock; McGrath, Gavan; Rao, Suresh
2016-04-01
Urban drainage networks are an essential component of infrastructure, and comprise the aggregation of underground pipe networks carrying storm water and domestic waste water for eventual discharge to natural stream networks. Growing urbanization has contributed to rapid expansion of sewer networks, vastly increasing their complexity and scale. Importance of sewer networks has been well studied from an engineering perspective, including resilient management, optimal design, and malfunctioning impact. Yet, analysis of the urban drainage networks using complex networks approach are lacking. Urban drainage networks consist of manholes and conduits, which correspond to nodes and edges, analogous to junctions and streams in river networks. Converging water flows in these two networks are driven by elevation gradient. In this sense, engineered urban drainage networks share several attributes of flows in river networks. These similarities between the two directed, converging flow networks serve the basis for us to hypothesize that the functional topology of sewer networks, like river networks, is scale-invariant. We analyzed the exceedance probability distribution of upstream area for practical sewer networks in South Korea. We found that the exceedance probability distributions of upstream area follow power-law, implying that the sewer networks exhibit topological self-similarity. The power-law exponents for the sewer networks were similar, and within the range reported from analysis of natural river networks. Thus, in line with our hypothesis, these results suggest that engineered urban drainage networks share functional topological attributes regardless of their structural dissimilarity or different underlying network evolution processes (natural vs. engineered). Implications of these findings for optimal design of sewer networks and for modeling sewer flows will be discussed.
2017-08-01
deforming objects using particle filtering for geometric active contours,” Pattern Analysis and Machine Intelligence , IEEE Transactions on, vol. 29, pp...on to the analysis and evaluation of physical networks by extending our models to smart grids, which are also known as the next generation power grid...of magnitude more efficient than any previous approach. Contents 1 Objectives and Status of Efforts 7 2 Mobility Modeling and Analysis of Coverage
Theoretical Analysis and Simulation of BJFET Obstructive Characteristics
Institute of Scientific and Technical Information of China (English)
ZENG Yun; YAN Min; YAN Yong-hong; FAN Wei
2005-01-01
A new bipolar junction field-effect transistor (BJFET) was described. The theoretical analysis and computer simulation of BJFET obstructive characteristic are achieved. The gate bias voltage affects the BJFET obstructive voltage greatly. The BJFET obstructive characteristic is relevant to structure parameters of channel width W and channel length L.The decrease-bias-voltage operation can weaken the device obstructive characteristic. The forward turn in device forward obstructive region can also affect the BJFET obstructive characteristic. BJFET has a good high temperature obstructive characteristic and can be applying to high temperature status as high voltage switch devices.
Theoretical analysis of bubble nucleation in GASAR materials
Institute of Scientific and Technical Information of China (English)
刘源; 李言祥
2003-01-01
Nucleation of gaseous hydrogen bubbles is the initial stage of GASAR process. Through the theoretical analysis, it has been identified that heterogeneous nucleation of bubbles as caps on the solid surfaces of impurities is impossible and only the heterogeneous nucleation in pits and cracks in impurities is the most feasible way in the GASAR process. The results also show that the probability of bubble nucleation progressively decreases from Al, Cu and Ni to Fe molten metal, which is the result of the increasing adhesion work of liquid metal on alumina.
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
A Network Approach to Environmental Impact in Psychotic Disorder: Brief Theoretical Framework.
Isvoranu, Adela-Maria; Borsboom, Denny; van Os, Jim; Guloksuz, Sinan
2016-07-01
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 psychometric framework for the study of mental disorders. Using general population data, we construct network models for the relation between 3 environmental risk factors (cannabis use, developmental trauma, and urban environment), dimensional measures of psychopathology (anxiety, depression, interpersonal sensitivity, obsessive-compulsive disorder, phobic anxiety, somatizations, and hostility), and a composite measure of psychosis expression. Results indicate the existence of specific paths between environmental factors and symptoms. These paths most often involve cannabis use. In addition, the analyses suggest that symptom networks are more strongly connected for people exposed to environmental risk factors, implying that environmental exposure may lead to less resilient symptom networks.
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.
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.
Google matrix analysis of directed networks
Ermann, Leonardo; Shepelyansky, Dima L
2014-01-01
In past ten years, modern societies developed enormous communication and social networks. Their classification and information retrieval processing become a formidable task for the society. Due to the rapid growth of World Wide Web, social and communication networks, new mathematical methods have been invented to characterize the properties of these networks on a more detailed and precise level. Various search engines are essentially using such methods. It is highly important to develop new tools to classify and rank enormous amount of network information in a way adapted to internal network structures and characteristics. This review describes the Google matrix analysis of directed complex networks demonstrating its efficiency on various examples including World Wide Web, Wikipedia, software architecture, 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 chain...
Gladilin, Evgeny
2017-01-01
Malignant transformation is known to involve substantial rearrangement of the molecular genetic landscape of the cell. A common approach to analysis of these alterations is a reductionist one and consists of finding a compact set of differentially expressed genes or associated signaling pathways. However, due to intrinsic tumor heterogeneity and tissue specificity, biomarkers defined by a small number of genes/pathways exhibit substantial variability. As an alternative to compact differential signatures, global features of genetic cell machinery are conceivable. Global network descriptors suggested in previous works are, however, known to potentially be biased by overrepresentation of interactions between frequently studied genes-proteins. Here, we construct a cellular network of 74538 directional and differential gene expression weighted protein-protein and gene regulatory interactions, and perform graph-theoretical analysis of global human interactome using a novel, degree-independent feature-the normalized total communicability (NTC). We apply this framework to assess differences in total information flow between different cancer (BRCA/COAD/GBM) and non-cancer interactomes. Our experimental results reveal that different cancer interactomes are characterized by significant enhancement of long-range NTC, which arises from circulation of information flow within robustly organized gene subnetworks. Although enhancement of NTC emerges in different cancer types from different genomic profiles, we identified a subset of 90 common genes that are related to elevated NTC in all studied tumors. Our ontological analysis shows that these genes are associated with enhanced cell division, DNA replication, stress response, and other cellular functions and processes typically upregulated in cancer. We conclude that enhancement of long-range NTC manifested in the correlated activity of genes whose tight coordination is required for survival and proliferation of all tumor cells
Geometrical Methods for Power Network Analysis
Bellucci, Stefano; Gupta, Neeraj
2013-01-01
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.
End-to-end delay analysis for networked systems
Institute of Scientific and Technical Information of China (English)
Jie SHEN; Wen-bo HE; Xue LIU; Zhi-bo WANG; Zhi WANG; Jian-guo YAO
2015-01-01
End-to-end delay measurement has been an essential element in the deployment of real-time services in networked systems. Traditional methods of delay measurement based on time domain analysis, however, are not eﬃcient as the network scale and the complexity increase. We propose a novel theoretical framework to analyze the end-to-end delay distributions of networked systems from the frequency domain. We use a signal fl ow graph to model the delay distribution of a networked system and prove that the end-to-end delay distribution is indeed the inverse Laplace transform of the transfer function of the signal fl ow graph. Two eﬃcient methods, Cramer’s rule-based method and the Mason gain rule-based method, are adopted to obtain the transfer function. By analyzing the time responses of the transfer function, we obtain the end-to-end delay distribution. Based on our framework, we propose an eﬃcient method using the dominant poles of the transfer function to work out the bottleneck links of the network. Moreover, we use the framework to study the network protocol performance. Theoretical analysis and extensive evaluations show the effectiveness of the proposed approach.
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.
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
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.
Social network analysis and dual rover communications
Litaker, Harry L.; Howard, Robert L.
2013-10-01
Social network analysis (SNA) refers to the collection of techniques, tools, and methods used in sociometry aiming at the analysis of social networks to investigate decision making, group communication, and the distribution of information. Human factors engineers at the National Aeronautics and Space Administration (NASA) conducted a social network analysis on communication data collected during a 14-day field study operating a dual rover exploration mission to better understand the relationships between certain network groups such as ground control, flight teams, and planetary science. The analysis identified two communication network structures for the continuous communication and Twice-a-Day Communication scenarios as a split network and negotiated network respectfully. The major nodes or groups for the networks' architecture, transmittal status, and information were identified using graphical network mapping, quantitative analysis of subjective impressions, and quantified statistical analysis using Sociometric Statue and Centrality. Post-questionnaire analysis along with interviews revealed advantages and disadvantages of each network structure with team members identifying the need for a more stable continuous communication network, improved robustness of voice loops, and better systems training/capabilities for scientific imagery data and operational data during Twice-a-Day Communications.
ONLINE SOCIAL NETWORK INTERNETWORKING ANALYSIS
Directory of Open Access Journals (Sweden)
Bassant E.Youssef
2014-10-01
Full Text Available Online social networks (OSNs contain data about users, their relations, interests and daily activities andthe great value of this data results in ever growing popularity of OSNs. There are two types of OSNs data,semantic and topological. Both can be used to support decision making processes in many applicationssuch as in information diffusion, viral marketing and epidemiology. Online Social network analysis (OSNAresearch is used to maximize the benefits gained from OSNs’ data. This paper provides a comprehensive study of OSNs and OSNA to provide analysts with the knowledge needed to analyse OSNs. OSNs’internetworking was found to increase the wealth of the analysed data by depending on more than one OSNas the source of the analysed data. Paper proposes a generic model of OSNs’ internetworking system that an analyst can rely on. Twodifferent data sources in OSNs were identified in our efforts to provide a thorough study of OSNs, whichare the OSN User data and the OSN platform data. Additionally, we propose a classification of the OSNUser data according to its analysis models for different data types to shed some light into the current usedOSNA methodologies. We also highlight the different metrics and parameters that analysts can use toevaluate semantic or topologic OSN user data. Further, we present a classification of the other data typesand OSN platform data that can be used to compare the capabilities of different OSNs whether separate orin a OSNs’ internetworking system. To increase analysts’ awareness about the available tools they can use,we overview some of the currently publically available OSNs’ datasets and simulation tools and identifywhether they are capable of being used in semantic, topological OSNA, or both. The overview identifiesthat only few datasets includes both data types (semantic and topological and there are few analysis toolsthat can perform analysis on both data types. Finally paper present a scenario that
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
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.
Institute of Scientific and Technical Information of China (English)
Zhao Qin; Markus J. Buehler
2012-01-01
Intermediate filaments,in addition to microtubules and actin microfilaments,are one of the three major components of the cytoskeleton in eukaryotic cells.It was discovered during the recent decades that in most cells,intermediate filament proteins play key roles to reinforce cells subjected to large-deformation,and that they participate in signal transduction,and it was proposed that their nanomechanical properties are critical to perform those functions.However,it is still poorly understood how the nanoscopic structure,as well as the combination of chemical composition,molecular structure and interfacial properties of these protein molecules contribute to the biomechanical properties of filaments and filament networks. Here we review recent progress in computational and theoretical studies of the intermediate filaments network at various levels in the protein's structure. A multiple scale method is discussed,used to couple molecular modeling with atomistic detail to larger-scale material properties of the networked material. It is shown that a finer-trains-coarser methodology as discussed here provides a useful tool in understanding the biomechanical property and disease mechanism of intermediate filaments,coupling experiment and simulation. It further allows us to improve the understanding of associated disease mechanisms and lays the foundation for engineering the mechanical properties of biomaterials.
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....
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....
Applications of Social Network Analysis
Thilagam, P. Santhi
A social network [2] is a description of the social structure between actors, mostly persons, groups or organizations. It indicates the ways in which they are connected with each other by some relationship such as friendship, kinship, finance exchange etc. In a nutshell, when the person uses already known/unknown people to create new contacts, it forms social networking. The social network is not a new concept rather it can be formed when similar people interact with each other directly or indirectly to perform particular task. Examples of social networks include a friendship networks, collaboration networks, co-authorship networks, and co-employees networks which depict the direct interaction among the people. There are also other forms of social networks, such as entertainment networks, business Networks, citation networks, and hyperlink networks, in which interaction among the people is indirect. Generally, social networks operate on many levels, from families up to the level of nations and assists in improving interactive knowledge sharing, interoperability and collaboration.
Inner strength--a theoretical analysis of salutogenic concepts.
Lundman, Berit; Aléx, Lena; Jonsén, Elisabeth; Norberg, Astrid; Nygren, Björn; Santamäki Fischer, Regina; Strandberg, Gunilla
2010-02-01
Theoretical and empirical overlaps between the concepts of resilience, sense of coherence, hardiness, purpose in life, and self-transcendence have earlier been described as some kind of inner strength, but no studies have been found that focus on what attributes these concepts have in common. The objective of this study was to perform a theoretical analysis of the concepts of resilience, sense of coherence, hardiness, purpose in life, and self-transcendence, in order to identify their core dimensions in an attempt to get an overarching understanding of inner strength. PRINT METHOD: An analysis inspired by the procedure of meta-theory construction was performed. The main questions underlying the development of the concepts, the major paradigms and the most prominent assumptions, the critical attributes and the characteristics of the various concepts were identified. The analysis resulted in the identification of four core dimensions of inner strength and the understanding that inner strength relies on the interaction of these dimensions: connectedness, firmness, flexibility, and creativity. These dimensions were validated through comparison with the original descriptions of the concepts. An overarching understanding of inner strength is that it means both to stand steady, to be firm, with both feet on the ground and to be connected to; family, friends, society, nature and spiritual dimensions and to be able to transcend. Having inner strength is to be creative and stretchable, which is to believe in own possibilities to act and to make choices and influence life's trajectory in a perceived meaningful direction. Inner strength is to shoulder responsibility for oneself and others, to endure and deal with difficulties and adversities. This knowledge about inner strength will raise the awareness of the concept and, in turn, hopefully increase our potential to support people's inner strength. Copyright 2009 Elsevier Ltd. All rights reserved.
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.
Le Guyader, P; Trelles, F; Savard, P
2001-10-01
The passive electrical properties of cardiac tissue, such as the intracellular and interstitial conductivities along the longitudinal and transverse axes, have not been often measured because intracellular electrodes are usually needed for these measurements. In this paper, we present a theoretical analysis of two myocardial models developed to estimate these properties by analyzing potentials recorded with a pair of extracellular electrodes while injecting alternating current between another pair of electrodes. First, the cardiac tissue is represented by a standard bidomain model which includes a membrane capacitance; second, this model is modified by adding an intracellular capacitance representing the intercalated disks. Numerical solutions are computed with a fast Fourier transform algorithm without constraining the anisotropy ratios of the interstitial and intracellular domains. We systematically investigate the effects of changes in the bidomain parameters on the voltage-to-current ratio curves. We also demonstrate how the bidomain parameters can be theoretically estimated by fitting, with a modified Shor's r algorithm, the simulated potentials along the longitudinal and transverse axes for different frequencies between 10 and 10,000 Hz. An important finding is that the interelectrode distance must be similar to the myocardial space constant so as to obtain frequency dependent measurements.
Statistical Analysis of Bus Networks in India
Chatterjee, Atanu; Ramadurai, Gitakrishnan
2015-01-01
Through the past decade the field of network science has established itself as a common ground for the cross-fertilization of exciting inter-disciplinary studies which has motivated researchers to model almost every physical system as an interacting network consisting of nodes and links. Although public transport networks such as airline and railway networks have been extensively studied, the status of bus networks still remains in obscurity. In developing countries like India, where bus networks play an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer some of the basic questions on its evolution, growth, robustness and resiliency. In this paper, we model the bus networks of major Indian cities as graphs in \\textit{L}-space, and evaluate their various statistical properties using concepts from network science. Our analysis reveals a wide spectrum of network topology with the common underlying feature of small-world property. We observe tha...
Analysis of the Features of Network Words
Institute of Scientific and Technical Information of China (English)
阳艳萍
2015-01-01
The information society makes people’s lives gradually enter a digital state for living. And the popularity of the Inter⁃net has led to the unique phenomenon of network words. What impact will network and the combination of language bring about? This article will explore the relation between the phenomenon of network words and social context from the angle of so⁃cial linguistic through the analysis of network words and grammatical features.
Neural Networks for Rapid Design and Analysis
Sparks, Dean W., Jr.; Maghami, Peiman G.
1998-01-01
Artificial neural networks have been employed for rapid and efficient dynamics and control analysis of flexible systems. Specifically, feedforward neural networks are designed to approximate nonlinear dynamic components over prescribed input ranges, and are used in simulations as a means to speed up the overall time response analysis process. To capture the recursive nature of dynamic components with artificial neural networks, recurrent networks, which use state feedback with the appropriate number of time delays, as inputs to the networks, are employed. Once properly trained, neural networks can give very good approximations to nonlinear dynamic components, and by their judicious use in simulations, allow the analyst the potential to speed up the analysis process considerably. To illustrate this potential speed up, an existing simulation model of a spacecraft reaction wheel system is executed, first conventionally, and then with an artificial neural network in place.
Mathematical analysis techniques for modeling the space network activities
Foster, Lisa M.
1992-01-01
The objective of the present work was to explore and identify mathematical analysis techniques, and in particular, the use of linear programming. This topic was then applied to the Tracking and Data Relay Satellite System (TDRSS) in order to understand the space network better. Finally, a small scale version of the system was modeled, variables were identified, data was gathered, and comparisons were made between actual and theoretical data.
Theoretical Analysis of Dynamic Processes for Interacting Molecular Motors.
Teimouri, Hamid; Kolomeisky, Anatoly B; Mehrabiani, Kareem
2015-02-13
Biological transport is supported by collective dynamics of enzymatic molecules that are called motor proteins or molecular motors. Experiments suggest that motor proteins interact locally via short-range potentials. We investigate the fundamental role of these interactions by analyzing a new class of totally asymmetric exclusion processes where interactions are accounted for in a thermodynamically consistent fashion. It allows us to connect explicitly microscopic features of motor proteins with their collective dynamic properties. Theoretical analysis that combines various mean-field calculations and computer simulations suggests that dynamic properties of molecular motors strongly depend on interactions, and correlations are stronger for interacting motor proteins. Surprisingly, it is found that there is an optimal strength of interactions (weak repulsion) that leads to a maximal particle flux. It is also argued that molecular motors transport is more sensitive to attractive interactions. Applications of these results for kinesin motor proteins are discussed.
Theoretical Analysis of Rayleigh Backscattering Noise in Fiber Raman Amplifiers
Institute of Scientific and Technical Information of China (English)
无
2005-01-01
In this paper, a new theoretical model for Rayleigh backscattering (RB) analysis of fiber Raman amplifiers is proposed. The model includes all the interactions among the pumps, signals, and all orders of RB. The results show that the higher order RB has a negligible influence on the performance of the amplifier. The co-propagating and counterpropagating RB power of the signal grow quadratically with the net-gain of the amplifier. The signal to double Rayleigh backscattering noise ratio (OSNRDRB ) of backward-pumped FRAs is better than that of the forward-pumped ones at high net-gain level (＞ 13 dB), while at low net-gain level the OSNRDrb of the forward-pumped FRAs is slightly better than that of the backward-pumped ones.
Two-Dimensional Electronic Spectroscopy Using Incoherent Light: Theoretical Analysis
Turner, Daniel B; Sutor, Erika J; Hendrickson, Rebecca A; Gealy, M W; Ulness, Darin J
2012-01-01
Electronic energy transfer in photosynthesis occurs over a range of time scales and under a variety of intermolecular coupling conditions. Recent work has shown that electronic coupling between chromophores can lead to coherent oscillations in two-dimensional electronic spectroscopy measurements of pigment-protein complexes measured with femtosecond laser pulses. A persistent issue in the field is to reconcile the results of measurements performed using femtosecond laser pulses with physiological illumination conditions. Noisy-light spectroscopy can begin to address this question. In this work we present the theoretical analysis of incoherent two-dimensional electronic spectroscopy, I(4) 2D ES. Simulations reveal diagonal peaks, cross peaks, and coherent oscillations similar to those observed in femtosecond two-dimensional electronic spectroscopy experiments. The results also expose fundamental differences between the femtosecond-pulse and noisy-light techniques; the differences lead to new challenges and opp...
Convergence of the discrete dipole approximation. I. Theoretical analysis
Yurkin, Maxim A; Hoekstra, Alfons G
2006-01-01
We performed a rigorous theoretical convergence analysis of the discrete dipole approximation (DDA). We prove that errors in any measured quantity are bounded by a sum of a linear and quadratic term in the size of a dipole d, when the latter is in the range of DDA applicability. Moreover, the linear term is significantly smaller for cubically than for non-cubically shaped scatterers. Therefore, for small d errors for cubically shaped particles are much smaller than for non-cubically shaped. The relative importance of the linear term decreases with increasing size, hence convergence of DDA for large enough scatterers is quadratic in the common range of d. Extensive numerical simulations were carried out for a wide range of d. Finally we discuss a number of new developments in DDA and their consequences for convergence.
Theoretical analysis of tsunami generation by pyroclastic flows
Watts, P.; Waythomas, C.F.
2003-01-01
Pyroclastic flows are a common product of explosive volcanism and have the potential to initiate tsunamis whenever thick, dense flows encounter bodies of water. We evaluate the process of tsunami generation by pyroclastic flow by decomposing the pyroclastic flow into two components, the dense underflow portion, which we term the pyroclastic debris flow, and the plume, which includes the surge and coignimbrite ash cloud parts of the flow. We consider five possible wave generation mechanisms. These mechanisms consist of steam explosion, pyroclastic debris flow, plume pressure, plume shear, and pressure impulse wave generation. Our theoretical analysis of tsunami generation by these mechanisms provides an estimate of tsunami features such as a characteristic wave amplitude and wavelength. We find that in most situations, tsunami generation is dominated by the pyroclastic debris flow component of a pyroclastic flow. This work presents information sufficient to construct tsunami sources for an arbitrary pyroclastic flow interacting with most bodies of water. Copyright 2003 by the American Geophysical Union.
Deep and Structured Robust Information Theoretic Learning for Image Analysis.
Deng, Yue; Bao, Feng; Deng, Xuesong; Wang, Ruiping; Kong, Youyong; Dai, Qionghai
2016-07-07
This paper presents a robust information theoretic (RIT) model to reduce the uncertainties, i.e. missing and noisy labels, in general discriminative data representation tasks. The fundamental pursuit of our model is to simultaneously learn a transformation function and a discriminative classifier that maximize the mutual information of data and their labels in the latent space. In this general paradigm, we respectively discuss three types of the RIT implementations with linear subspace embedding, deep transformation and structured sparse learning. In practice, the RIT and deep RIT are exploited to solve the image categorization task whose performances will be verified on various benchmark datasets. The structured sparse RIT is further applied to a medical image analysis task for brain MRI segmentation that allows group-level feature selections on the brain tissues.
Theoretical analysis of the coherence-brightened laser in air
Yuan, Luqi; Hokr, Brett H.; Traverso, Andrew J.; Voronine, Dmitri V.; Rostovtsev, Yuri; Sokolov, Alexei V.; Scully, Marlan O.
2013-02-01
We present a detailed theoretical study of a recent experiment [A. J. Traverso , Proc. Natl. Acad. Sci. USAPNASA60027-842410.1073/pnas.1211481109 109, 15185 (2012)] in which a laserlike source is created in air by pumping with a nanosecond pulse. The source generates radiation in the forward and backward directions. The temporal behavior of the emitted pulses is investigated for different pump shapes and durations. Our analysis indicates that the spiky emission is due to quantum coherence via cooperation between atoms of an ensemble, which leads to strong-oscillatory superfluorescence. We show that these cooperative nonadiabatic coherence effects cannot be described by rate equations and instead a full set of the Maxwell-Bloch equations must be used. We consider a range of parameters and study transitions between various regimes. Understanding these coherence-brightened processes in air should lead to improvements in environmental, atmospheric remote sensing and other applications.
How Do Pseudocapacitors Store Energy? Theoretical Analysis and Experimental Illustration.
Costentin, Cyrille; Porter, Thomas R; Savéant, Jean-Michel
2017-03-15
Batteries and electrochemical double layer charging capacitors are two classical means of storing electrical energy. These two types of charge storage can be unambiguously distinguished from one another by the shape and scan-rate dependence of their cyclic voltammetric (CV) current-potential responses. The former shows peak-shaped current-potential responses, proportional to the scan rate v or to v(1/2), whereas the latter displays a quasi-rectangular response proportional to the scan rate. On the contrary, the notion of pseudocapacitance, popularized in the 1980s and 1990s for metal oxide systems, has been used to describe a charge storage process that is faradaic in nature yet displays capacitive CV signatures. It has been speculated that a quasi-rectangular CV response resembling that of a truly capacitive response arises from a series of faradaic redox couples with a distribution of potentials, yet this idea has never been justified theoretically. We address this problem by first showing theoretically that this distribution-of-potentials approach is closely equivalent to the more physically meaningful consideration of concentration-dependent activity coefficients resulting from interactions between reactants. The result of the ensuing analysis is that, in either case, the CV responses never yield a quasi-rectangular response ∝ ν, identical to that of double layer charging. Instead, broadened peak-shaped responses are obtained. It follows that whenever a quasi-rectangular CV response proportional to scan rate is observed, such reputed pseudocapacitive behaviors should in fact be ascribed to truly capacitive double layer charging. We compare these results qualitatively with pseudocapacitor reports taken from the literature, including the classic RuO2 and MnO2 examples, and we present a quantitative analysis with phosphate cobalt oxide films. Our conclusions do not invalidate the numerous experimental studies carried out under the pseudocapacitance banner but
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.
Field theory of unification in nonlinear and linear network (I)——Theoretical grounds of field theory
Institute of Scientific and Technical Information of China (English)
陈燊年; 何煜光; 王建成
1995-01-01
A field theory has been proposed. The laws of conservation of charge and energy can be obtained from the Maxwell’s equations, which are placed in nonlinear network for simultaneous solution, and therefore the Kirchhoff’s law with its most fundamental integral formulae in nonlinear network can be obtained. Thus, it will strictly push forward the total basic equations from non-linear network to linear network as well as other important new relationships to provide the theoretical grounds for the field theory.
Social network analysis and supply chain management
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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.
Graph theoretical analysis indicates cognitive impairment in MS stems from neural disconnection.
Van Schependom, Jeroen; Gielen, Jeroen; Laton, Jorne; D'hooghe, Marie B; De Keyser, Jacques; Nagels, Guy
2014-01-01
The mechanisms underlying cognitive impairment in MS are still poorly understood. However, due to the specific pathology of MS, one can expect alterations in connectivity leading to physical and cognitive impairment. In this study we aimed at assessing connectivity differences in EEG between cognitively impaired (CI) and cognitively preserved (CP) MS patients. We also investigated the influence of the measures used to construct networks. We included 308 MS patients and divided them into two groups based on their cognitive score. Graph theoretical network analyses were conducted based on networks constructed using different connectivity measures, i.e. correlation, correlation in the frequency domain, coherence, partial correlation, the phase lag index and the imaginary part of coherency. The most commonly encountered network parameters were calculated and compared between the two groups using Wilcoxon's rank test. Clustering coefficients and path lengths were normalized to a randomized mean clustering coefficient and path length for each patient. False discovery rate was used to correct for the multiple comparisons and Cohen's d effect sizes are reported. Coherence analysis suggests that theta and delta connectivity is significantly smaller in cognitively impaired patients. Small-worldness differences are found in networks based on correlation, theta and delta coherence and correlation in the frequency domain. Modularity was related to age but not to cognition. Cognitive deterioration in MS is a symptom that seems to be caused by neural disconnections, probably the white matter tracts connecting both hemispheres, and leads to a wide range in network differences which can be assessed by applying GTA to EEG data. In the future, these results may lead to cheaper and more objective assessments of cognitive impairment in MS.
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.
Mean field game theoretic approach for security in mobile ad-hoc networks
Wang, Yanwei; Tang, Helen; Yu, F. Richard; Huang, Minyi
2013-05-01
Game theory can provide a useful tool to study the security problem in mobile ad hoc networks (MANETs). Most existing work on applying game theories to security only considers two players in the security game model: an attacker and a defender. While this assumption is valid for a network with centralized administration, it may not be realistic in MANETs, where centralized administration is not available. Consequently, each individual node in a MANET should be treated separately in the security game model. In this paper, using recent advances in mean field game theory, we propose a novel game theoretic approach for security in MANETs. Mean field game theory provides a powerful mathematical tool for problems with a large number of players. Since security defence mechanisms consume precious system resources (e.g., energy), the proposed scheme considers not only the security requirement of MANETs but also the system resources. In addition, each node only needs to know its own state information and the aggregate effect of the other nodes in the MANET. Therefore, the proposed scheme is a fully distributed scheme. Simulation results are presented to illustrate the effectiveness of the proposed scheme.
A Game-Theoretic Approach to Energy-Efficient Modulation in CDMA Networks with Delay Constraints
Meshkati, Farhad; Poor, H Vincent; Schwartz, Stuart C
2007-01-01
A game-theoretic framework is used to study the effect of constellation size on the energy efficiency of wireless networks for M-QAM modulation. A non-cooperative game is proposed in which each user seeks to choose its transmit power (and possibly transmit symbol rate) as well as the constellation size in order to maximize its own utility while satisfying its delay quality-of-service (QoS) constraint. The utility function used here measures the number of reliable bits transmitted per joule of energy consumed, and is particularly suitable for energy-constrained networks. The best-response strategies and Nash equilibrium solution for the proposed game are derived. It is shown that in order to maximize its utility (in bits per joule), a user must choose the lowest constellation size that can accommodate the user's delay constraint. Using this framework, the tradeoffs among energy efficiency, delay, throughput and constellation size are also studied and quantified. The effect of trellis-coded modulation on energy...
Kannan, Srinivasa Ramanujam; Chandrasekar, V.
2016-05-01
Even though both the rain measuring instruments, radar and radiometer onboard the TRMM observe the same rain scenes, they both are fundamentally different instruments. Radar is an active instrument and measures backscatter component from vertical rain structure; whereas radiometer is a passive instrument that obtains integrated observation of full depth of the cloud and rain structure. Further, their spatial resolutions on ground are different. Nevertheless, both the instruments are observing the same rain scene and retrieve three dimensional rainfall products. Hence it is only natural to seek answer to the question, what type of information about radiometric observations can be directly retrieved from radar observations. While there are several ways to answer this question, an informational theoretic approach using neural networks has been described in the present work to find if radiometer observations can be predicted from radar observations. A database of TMI brightness temperature and collocated TRMM vertical attenuation corrected reflectivity factor from the year 2012 was considered. The entire database is further classified according to surface type. Separate neural networks were trained for land and ocean and the results are presented.
Directory of Open Access Journals (Sweden)
Arienzo Loredana
2010-01-01
Full Text Available The problem of collaborative tracking of mobile nodes in wireless sensor networks is addressed. By using a novel metric derived from the energy model in LEACH (W.B. Heinzelman, A.P. Chandrakasan and H. Balakrishnan, Energy-Efficient Communication Protocol for Wireless Microsensor Networks, in: Proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS '00, 2000 and aiming at an efficient resource solution, the approach adopts a strategy of combining target tracking with node selection procedures in order to select informative sensors to minimize the energy consumption of the tracking task. We layout a cluster-based architecture to address the limitations in computational power, battery capacity and communication capacities of the sensor devices. The computation of the posterior Cramer-Rao bound (PCRB based on received signal strength measurements has been considered. To track mobile nodes two particle filters are used: the bootstrap particle filter and the unscented particle filter, both in the centralized and in the distributed manner. Their performances are compared with the theoretical lower bound PCRB. To save energy, a node selection procedure based on greedy algorithms is proposed. The node selection problem is formulated as a cross-layer optimization problem and it is solved using greedy algorithms.
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.
Hernández-Lemus, Enrique; Velázquez-Fernández, David; Estrada-Gil, Jesús K.; Silva-Zolezzi, Irma; Herrera-Hernández, Miguel F.; Jiménez-Sánchez, Gerardo
2009-12-01
Most common pathologies in humans are not caused by the mutation of a single gene, rather they are complex diseases that arise due to the dynamic interaction of many genes and environmental factors. This plethora of interacting genes generates a complexity landscape that masks the real effects associated with the disease. To construct dynamic maps of gene interactions (also called genetic regulatory networks) we need to understand the interplay between thousands of genes. Several issues arise in the analysis of experimental data related to gene function: on the one hand, the nature of measurement processes generates highly noisy signals; on the other hand, there are far more variables involved (number of genes and interactions among them) than experimental samples. Another source of complexity is the highly nonlinear character of the underlying biochemical dynamics. To overcome some of these limitations, we generated an optimized method based on the implementation of a Maximum Entropy Formalism (MaxEnt) to deconvolute a genetic regulatory network based on the most probable meta-distribution of gene-gene interactions. We tested the methodology using experimental data for Papillary Thyroid Cancer (PTC) and Thyroid Goiter tissue samples. The optimal MaxEnt regulatory network was obtained from a pool of 25,593,993 different probability distributions. The group of observed interactions was validated by several (mostly in silico) means and sources. For the associated Papillary Thyroid Cancer Gene Regulatory Network (PTC-GRN) the majority of the nodes (genes) have very few links (interactions) whereas a small number of nodes are highly connected. PTC-GRN is also characterized by high clustering coefficients and network heterogeneity. These properties have been recognized as characteristic of topological robustness, and they have been largely described in relation to biological networks. A number of biological validity outcomes are discussed with regard to both the
Theoretical analysis of the state of balance in bipedal walking.
Firmani, Flavio; Park, Edward J
2013-04-01
This paper presents a theoretical analysis based on classic mechanical principles of balance of forces in bipedal walking. Theories on the state of balance have been proposed in the area of humanoid robotics and although the laws of classical mechanics are equivalent to both humans and humanoid robots, the resulting motion obtained with these theories is unnatural when compared to normal human gait. Humanoid robots are commonly controlled using the zero moment point (ZMP) with the condition that the ZMP cannot exit the foot-support area. This condition is derived from a physical model in which the biped must always walk under dynamically balanced conditions, making the centre of pressure (CoP) and the ZMP always coincident. On the contrary, humans follow a different strategy characterized by a 'controlled fall' at the end of the swing phase. In this paper, we present a thorough theoretical analysis of the state of balance and show that the ZMP can exit the support area, and its location is representative of the imbalance state characterized by the separation between the ZMP and the CoP. Since humans exhibit this behavior, we also present proof-of-concept results of a single subject walking on an instrumented treadmill at different speeds (from slow 0.7 m/s to fast 2.0 m/s walking with increments of 0.1 m/s) with the motion recorded using an optical motion tracking system. In order to evaluate the experimental results of this model, the coefficient of determination (R2) is used to correlate the measured ground reaction forces and the resultant of inertial and gravitational forces (anteroposterior R² = 0.93, mediolateral R² = 0.89, and vertical R² = 0.86) indicating that there is a high correlation between the measurements. The results suggest that the subject exhibits a complete dynamically balanced gait during slow speeds while experiencing a controlled fall (end of swing phase) with faster speeds. This is quantified with the root-mean-square deviation (RMSD
Foreign Scholars′ Theoretical Approaches to Using Social Networks as Educational Strategies
Directory of Open Access Journals (Sweden)
Pazyura Natalia
2017-06-01
Full Text Available Modern trends in development of information and communication technologies change many aspects in the process of education: from the role of participants to the forms and methods of knowledge delivery. ICTs make it possible to develop students′ creative potential. The emergence of online social groups was an important event in the sphere of communication but with time they began to be used by both teachers and students not only for communication, but also to achieve learning goals. Without any doubt, skillful use of social networks allows teachers to communicate with students at modern technological level, make classes more attractive and effective. An efficient teacher can prove that social networks are not only means of entertainment and communication with friends but are a working tool. The main aim of foreign language teaching is students′ communicative activity or practical use of a target language. The teacher is to activate every student’s activity in the process of learning, make situations for their creativity. The main objective of foreign language teaching is to educate an individual, who is able to communicate, continue education, including selfeducation. Different theories lay the basis for the study of social networks’ influence on different aspects of human activity and, particularly, education. The main theories are sociocultural theory and social constructivist theory. According to sociocultural theory, man is an integral part of the world they live in, so students are not independent in their activities. Social constructivist theory recognizes that students act in a certain environment, which under certain conditions enlarges their practical knowledge. These theories are focused on the effect of social interaction, language and culture in the learning process. Thus, theoretical basis proves positive effect of social networks, namely, they enhance substantial interaction in the educational environment of social groups as
Universality in complex networks: random matrix analysis.
Bandyopadhyay, Jayendra N; Jalan, Sarika
2007-08-01
We apply random matrix theory to complex networks. We show that nearest neighbor spacing distribution of the eigenvalues of the adjacency matrices of various model networks, namely scale-free, small-world, and random networks follow universal Gaussian orthogonal ensemble statistics of random matrix theory. Second, we show an analogy between the onset of small-world behavior, quantified by the structural properties of networks, and the transition from Poisson to Gaussian orthogonal ensemble statistics, quantified by Brody parameter characterizing a spectral property. We also present our analysis for a protein-protein interaction network in budding yeast.
Dynamic Analysis of Structures Using Neural Networks
Directory of Open Access Journals (Sweden)
N. Ahmadi
2008-01-01
Full Text Available In the recent years, neural networks are considered as the best candidate for fast approximation with arbitrary accuracy in the time consuming problems. Dynamic analysis of structures against earthquake has the time consuming process. We employed two kinds of neural networks: Generalized Regression neural network (GR and Back-Propagation Wavenet neural network (BPW, for approximating of dynamic time history response of frame structures. GR is a traditional radial basis function neural network while BPW categorized as a wavelet neural network. In BPW, sigmoid activation functions of hidden layer neurons are substituted with wavelets and weights training are achieved using Scaled Conjugate Gradient (SCG algorithm. Comparison the results of BPW with those of GR in the dynamic analysis of eight story steel frame indicates that accuracy of the properly trained BPW was better than that of GR and therefore, BPW can be efficiently used for approximate dynamic analysis of structures.
Measuring Road Network Vulnerability with Sensitivity Analysis
Jun-qiang, Leng; Long-hai, Yang; Liu, Wei-yi; Zhao, Lin
2017-01-01
This paper focuses on the development of a method for road network vulnerability analysis, from the perspective of capacity degradation, which seeks to identify the critical infrastructures in the road network and the operational performance of the whole traffic system. This research involves defining the traffic utility index and modeling vulnerability of road segment, route, OD (Origin Destination) pair and road network. Meanwhile, sensitivity analysis method is utilized to calculate the change of traffic utility index due to capacity degradation. This method, compared to traditional traffic assignment, can improve calculation efficiency and make the application of vulnerability analysis to large actual road network possible. Finally, all the above models and calculation method is applied to actual road network evaluation to verify its efficiency and utility. This approach can be used as a decision-supporting tool for evaluating the performance of road network and identifying critical infrastructures in transportation planning and management, especially in the resource allocation for mitigation and recovery. PMID:28125706
Comment on "Network analysis of the state space of discrete dynamical systems"
Li, Chengqing; Shu, Shi
2016-01-01
This paper comments the letter entitled "Network analysis of the state space of discrete dynamical systems" by A. Shreim et al. [Physical Review Letters, 98, 198701 (2007)]. We found that some theoretical analyses are wrong and the proposed indicators based on parameters of phase network can not discriminate dynamical complexity of the discrete dynamical systems composed by 1-D Cellular Automata.
Fronczak, Piotr
2015-01-01
Using the formalism of the biased random walk in random uncorrelated networks with arbitrary degree distributions, we develop theoretical approach to the critical packet generation rate in traffic based on routing strategy with local information. We explain microscopic origins of the transition from the flow to the jammed phase and discuss how the node neighbourhood topology affects the transport capacity in uncorrelated and correlated networks.
Sandbox algorithm for multifractal analysis of complex networks
Liu, Jin-Long; Anh, Vo
2014-01-01
Complex networks have attracted much attention in diverse areas of science and technology. Multifractal analysis (MFA) is a useful way to systematically describe the spatial heterogeneity of both theoretical and experimental fractal patterns. In this paper, we introduce a new algorithm --- the sandbox (SB) algorithm, for MFA of complex networks. First we compare the SB algorithm with two existing algorithms of MFA for complex networks: the compact-box-burning (CBB) algorithm proposed by Furuya and Yakubo ( Phys. Rev. E, 84 (2011) 036118), and the improved box-counting (BC) algorithm proposed by Li et al. ( J. Stat. Mech.: Theor. Exp., 2014 (2014) P02020) by calculating the mass exponents tau(q) of some deterministic model networks. We make a detailed comparison between the numerical and theoretical results of these model networks. The comparison results show that the SB algorithm is the most effective and feasible algorithm to calculate the mass exponents tau(q) and to explore the multifractal behavior of com...
Advances in multiscale theoretical analysis and imaging aspects of turbulence
Shockro, Jennifer
The work presented in this dissertation is focused on two aspects related to turbulent flow. The first of these is the one-dimensional theoretical analysis of the logarithmic spiral in terms of fractal dimension and spectrum. The second is on imaging methodologies and analysis of turbulent jet scalar interfaces in atmospheric conditions, with broad applicability to various studies where turbulence has a key role, such as urban contaminant dispersion or free space laser communications. The logarithmic spiral is of particular interest to studies of turbulence and natural phenomena as it appears frequently in nature with the "Golden Ratio" and is thought to play an important role in turbulent mixing. It is also an inherently anisotropic geometric structure and therefore provides information towards examining phenomena in which anisotropic properties might be expected to appear and is thought to be present as a structure within the fine scales of the turbulent hierarchy. In this work it is subjected to one-dimensional theoretical analysis, focusing on the development of a probability density function (pdf) for the spiral and the relation of the pdf to its fractal dimension. Results indicate that the logarithmic spiral does not have a constant fractal dimension and thus that it does not exhibit any form of self-similar statistical behavior, supporting previous theoretical suppositions about behavior at the fine scales within the turbulent hierarchy. A signal is developed from the pdf in order to evaluate its power spectrum. Results of this analysis provide information about the manner in which energy is carried at different scales of the spiral. To our knowledge, the logarithmic spiral in particular has not yet been examined in this fashion in literature. In order to further investigate this object, the multiscale minima meshless (M(3) ) method isextended and employed computationally to the two-dimensional logarithmic spiral as well as to experimental images of a
Filtering Genes for Cluster and Network Analysis
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Parkhomenko Elena
2009-06-01
Full Text Available Abstract Background Prior to cluster analysis or genetic network analysis it is customary to filter, or remove genes considered to be irrelevant from the set of genes to be analyzed. Often genes whose variation across samples is less than an arbitrary threshold value are deleted. This can improve interpretability and reduce bias. Results This paper introduces modular models for representing network structure in order to study the relative effects of different filtering methods. We show that cluster analysis and principal components are strongly affected by filtering. Filtering methods intended specifically for cluster and network analysis are introduced and compared by simulating modular networks with known statistical properties. To study more realistic situations, we analyze simulated "real" data based on well-characterized E. coli and S. cerevisiae regulatory networks. Conclusion The methods introduced apply very generally, to any similarity matrix describing gene expression. One of the proposed methods, SUMCOV, performed well for all models simulated.
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.)
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.)
Theoretical Model and Dynamic Analysis of Soft Yoke Mooring System
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
As a popular solution for mooring an FPSO (Floating Production, Storage and Offloading) permanently in shallow water, the soft yoke mooring system has been widely used in ocean oil production activities in the Bohai Bay of China. In order to simulate the interaction mechanism and conduct dynamic analysis of the soft yoke mooring system, a theoretical model with basic dynamic equations is established. A numerical iteration algorithm based on error estimation is developed to solve the equations and calculate the dynamic response of the mooring system due to FPSO motions. Validation is conducted by wave basin experimentation. It is shown that the numerical simulation takes only a few iteration times and the final errors are small. Furthermore, the calculated results of both the static and dynamic responses agree well with those ones obtained by the model test. It indicates that the efficiency, the precision, the reliability and the validity of the developed numerical algorithm and program are rather good. It is proposed to develop a real-time monitoring system to further monitor the dynamic performance of the FPSO with a soft yoke mooring system under various real sea environments.
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...
Dynamic network-based epistasis analysis: Boolean examples
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Eugenio eAzpeitia
2011-12-01
Full Text Available In this review we focus on how the hierarchical and single-path assumptions of epistasis analysis can bias the topologies of gene interactions infered. This has been acknowledged in several previous papers and reviews, but here we emphasize the critical importance of dynamic analyses, and specifically illustrate the use of Boolean network models. Epistasis in a broad sense refers to gene interactions, however, as originally proposed by Bateson (herein, classical epistasis, defined as the blocking of a particular allelic effect due to the effect of another allele at a different locus. Classical epistasis analysis has proven powerful and useful, allowing researchers to infer and assign directionality to gene interactions. As larger data sets are becoming available, the analysis of classical epistasis is being complemented with computer science tools and system biology approaches. We show that when the hierarchical and single-path assumptions are not met in classical epistasis analysis, the access to relevant information and the correct gene interaction topologies are hindered, and it becomes necessary to consider the temporal dynamics of gene interactions. The use of dynamical networks can overcome these limitations. We particularly focus on the use of Boolean networks that, like classical epistasis analysis, relies on logical formalisms, and hence can complement classical epistasis analysis and relax its assumptions. We develop a couple of theoretical examples and analyze them from a dynamic Boolean network model perspective. Boolean networks could help to guide additional experiments and discern among alternative regulatory schemes that would be impossible or difficult to infer without the elimination of these assumption from the classical epistasis analysis. We also use examples from the literature to show how a Boolean network-based approach has resolved ambiguities and guided epistasis analysis. Our review complements previous accounts, not
SELECTING LEADERSHIP STYLES PROBLEM IN MANAGEMENT CULTURE: THEORETICAL ANALYSIS
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T. N. DUKHINA
2016-01-01
Full Text Available The article carried out a theoretical analysis of the problem of choosing the team leadership styles, which is regarded as the most important component of the control system, due to the content management tasks. At the basis of individual management style management ideologies are implemented in practice through professional management experience as a manager, supervisor used the style or styles of synthesis will depend on the specific situations and managerial abilities. It is proved that the optimum style of management as a set of business and personal qualities of the head is one of the important criteria for successful completion of the collective tasks and the organization as a whole. The estimation of moral and functional components of the formal authority of the head. It is noted that a formal or official authority deterministic set of powers and the rights that assumes his position and that it provides no more than 60% effect on subordinates. Psychological authority consists of the elements of moral and functional authority. The basis of the moral authority of a manager is moral and ideological qualities of the person. Administrative capacity head examined on the basis of three criteria: personal, functional-activity and structure-psychological. There is analysis of the democratic, liberal and authoritarian leadership styles and the conclusion of the discussion of the problem.
Theoretical Analysis of Shrouded Horizontal Axis Wind Turbines
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Tariq Abdulsalam Khamlaj
2017-01-01
Full Text Available Numerous analytical studies for power augmentation systems can be found in the literature with the goal to improve the performance of wind turbines by increasing the energy density of the air at the rotor. All methods to date are only concerned with the effects of a diffuser as the power augmentation, and this work extends the semi-empirical shrouded wind turbine model introduced first by Foreman to incorporate a converging-diverging nozzle into the system. The analysis is based on assumptions and approximations of the conservation laws to calculate optimal power coefficients and power extraction, as well as augmentation ratios. It is revealed that the power enhancement is proportional to the mass stream rise produced by the nozzle diffuser-augmented wind turbine (NDAWT. Such mass flow rise can only be accomplished through two essential principles: the increase in the area ratios and/or by reducing the negative back pressure at the exit. The thrust coefficient for optimal power production of a conventional bare wind turbine is known to be 8/9, whereas the theoretical analysis of the NDAWT predicts an ideal thrust coefficient either lower or higher than 8/9 depending on the back pressure coefficient at which the shrouded turbine operates. Computed performance expectations demonstrate a good agreement with numerical and experimental results, and it is demonstrated that much larger power coefficients than for traditional wind turbines are achievable. Lastly, the developed model is very well suited for the preliminary design of a shrouded wind turbine where typically many trade-off studies need to be conducted inexpensively.
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.
Multilayer motif analysis of brain networks
Battiston, Federico; Chavez, Mario; Latora, Vito
2016-01-01
In the last decade network science has shed new light on the anatomical connectivity and on correlations in the activity of different areas of the human brain. The study of brain networks has made possible in fact to detect the central areas of a neural system, and to identify its building blocks by looking at overabundant small subgraphs, known as motifs. However, network analysis of the brain has so far mainly focused on structural and functional networks as separate entities. The recently developed mathematical framework of multi-layer networks allows to perform a multiplex analysis of the human brain where the structural and functional layers are considered at the same time. In this work we describe how to classify subgraphs in multiplex networks, and we extend motif analysis to networks with many layers. We then extract multi-layer motifs in brain networks of healthy subjects by considering networks with two layers, respectively obtained from diffusion and functional magnetic resonance imaging. Results i...
NEXCADE: perturbation analysis for complex networks.
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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.
SOCIAL NETWORK ANALYSIS IN AN ONLINE BLOGOSPHERE
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DR. M. MOHAMED SATHIK
2011-01-01
Full Text Available Social network is a social structure that exists among the similar interest of individuals, organizations or even on relations like friendship. Social network analysis is the measure of relationship between people, organizations and processing entities. In today’s scenario, Internet is acting as an interface for the people who spread across the globe to exchange their ideas. Social network analysis is a Web 2.0 application, which facilitates the users tointeract, response and express their views. Social network analysis has greatest attention as a research area in computer science in the recent past. Blogs or weblogs are like catalogs that are maintained by individuals related to a particular topic of interest. In this problem, we analyze the blog responses as social networks that are posted by AIDS patients over a period of time.
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...
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Andras Jakab
Full Text Available Attempts to explicate the neural abnormalities behind autism spectrum disorders frequently revealed impaired brain connectivity, yet our knowledge is limited about the alterations linked with autistic traits in the non-clinical population. In our study, we aimed at exploring the neural correlates of dimensional autistic traits using a dual approach of diffusion tensor imaging (DTI and graph theoretical analysis of resting state functional MRI data. Subjects were sampled from a public neuroimaging dataset of healthy volunteers. Inclusion criteria were adult age (age: 18-65, availability of DTI and resting state functional acquisitions and psychological evaluation including the Social Responsiveness Scale (SRS and Autistic Spectrum Screening Questionnaire (ASSQ. The final subject cohort consisted of 127 neurotypicals. Global brain network structure was described by graph theoretical parameters: global and average local efficiency. Regional topology was characterized by degree and efficiency. We provided measurements for diffusion anisotropy. The association between autistic traits and the neuroimaging findings was studied using a general linear model analysis, controlling for the effects of age, gender and IQ profile. Significant negative correlation was found between the degree and efficiency of the right posterior cingulate cortex and autistic traits, measured by the combination of ASSQ and SRS scores. Autistic phenotype was associated with the decrease of whole-brain local efficiency. Reduction of diffusion anisotropy was found bilaterally in the temporal fusiform and parahippocampal gyri. Numerous models describe the autistic brain connectome to be dominated by reduced long-range connections and excessive short-range fibers. Our finding of decreased efficiency supports this hypothesis although the only prominent effect was seen in the posterior limbic lobe, which is known to act as a connector hub. The neural correlates of the autistic trait
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.
Benchmark analysis of railway networks and undertakings
Hansen, I.A.; Wiggenraad, P.B.L.; Wolff, J.W.
2013-01-01
Benchmark analysis of railway networks and companies has been stimulated by the European policy of deregulation of transport markets, the opening of national railway networks and markets to new entrants and separation of infrastructure and train operation. Recent international railway benchmarking s
Consistency Analysis of Network Traffic Repositories
Lastdrager, Elmer; Pras, Aiko
2009-01-01
Traffic repositories with TCP/IP header information are very important for network analysis. Researchers often assume that such repositories reliably represent all traffic that has been flowing over the network; little thoughts are made regarding the consistency of these repositories. Still, for var
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…
Information- Theoretic Analysis for the Difficulty of Extracting Hidden Information
Institute of Scientific and Technical Information of China (English)
ZHANG Wei-ming; LI Shi-qu; CAO Jia; LIU Jiu-fen
2005-01-01
The difficulty of extracting hidden information,which is essentially a kind of secrecy, is analyzed by information-theoretic method. The relations between key rate, message rate, hiding capacity and difficulty of extraction are studied in the terms of unicity distance of stego-key, and the theoretic conclusion is used to analyze the actual extracting attack on Least Significant Bit(LSB) steganographic algorithms.
Game Theoretical Approaches for Transport-Aware Channel Selection in Cognitive Radio Networks
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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.
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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.
Karmonik, Christof; Brandt, Anthony K; Fung, Steve H; Grossman, Robert G; Frazier, J Todd
2013-01-01
Benefits of listening to music with emotional attachment while recovering from a cerebral ischemic event have been reported. To develop a better understanding of the effects of music listening on the human brain, an algorithm for the graph-theoretical analysis of functional magnetic resonance imaging (fMRI) data was developed. From BOLD data of two paradigms (block-design, first piece: music without emotional attachment, additional visual guidance by a moving cursor in the score sheet; second piece: music with emotional attachment), network graphs were constructed with correlations between signal time courses as edge weights. Functional subunits in these graphs were identified with the MCODE clustering algorithm and mapped back into anatomical space using AFNI. Emotional centers including the right amygdala and bilateral insula were activated by the second piece (emotional attachment) but not by the first piece. Network clustering analysis revealed two separate networks of small-world property corresponding to task-oriented and resting state conditions, respectively. Functional subunits with highest interactions were bilateral precuneus for the first piece and left middle frontal gyrus and right amygdala, bilateral insula, left middle temporal gyrus for the second piece. Our results indicate that fMRI in connection with graph theoretical network analysis is capable of identifying and differentiating functional subunits in the human brain when listening to music with and without emotional attachment.
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...
Rakkiyappan, R; Cao, Jinde; Velmurugan, G
2015-01-01
This paper deals with the problem of existence and uniform stability analysis of fractional-order complex-valued neural networks with constant time delays. Complex-valued recurrent neural networks is an extension of real-valued recurrent neural networks that includes complex-valued states, connection weights, or activation functions. This paper explains sufficient condition for the existence and uniform stability analysis of such networks. Three numerical simulations are delineated to substantiate the effectiveness of the theoretical results.
Extending Stochastic Network Calculus to Loss Analysis
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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.
Extending stochastic network calculus to loss analysis.
Luo, Chao; Yu, Li; Zheng, Jun
2013-01-01
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.
Constructing an Intelligent Patent Network Analysis Method
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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.
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.
Statistical Analysis of Bus Networks in India
2016-01-01
In this paper, we model the bus networks of six major Indian cities as graphs in L-space, and evaluate their various statistical properties. While airline and railway networks have been extensively studied, a comprehensive study on the structure and growth of bus networks is lacking. In India, where bus transport plays an important role in day-to-day commutation, it is of significant interest to analyze its topological structure and answer basic questions on its evolution, growth, robustness and resiliency. Although the common feature of small-world property is observed, our analysis reveals a wide spectrum of network topologies arising due to significant variation in the degree-distribution patterns in the networks. We also observe that these networks although, robust and resilient to random attacks are particularly degree-sensitive. Unlike real-world networks, such as Internet, WWW and airline, that are virtual, bus networks are physically constrained. Our findings therefore, throw light on the evolution of such geographically and constrained networks that will help us in designing more efficient bus networks in the future. PMID:27992590
Equilibrium Analysis for Anycast in WDM Networks
Institute of Scientific and Technical Information of China (English)
唐矛宁; 王汉兴
2005-01-01
In this paper, the wavelength-routed WDM network, was analyzed for the dynamic case where the arrival of anycast requests was modeled by a state-dependent Poisson process. The equilibrium analysis was also given with the UWNC algorithm.
Graph theoretical analysis of the energy landscape of model polymers.
Baiesi, Marco; Bongini, Lorenzo; Casetti, Lapo; Tattini, Lorenzo
2009-07-01
In systems characterized by a rough potential-energy landscape, local energetic minima and saddles define a network of metastable states whose topology strongly influences the dynamics. Changes in temperature, causing the merging and splitting of metastable states, have nontrivial effects on such networks and must be taken into account. We do this by means of a recently proposed renormalization procedure. This method is applied to analyze the topology of the network of metastable states for different polypeptidic sequences in a minimalistic polymer model. A smaller spectral dimension emerges as a hallmark of stability of the global energy minimum and highlights a nonobvious link between dynamic and thermodynamic properties.
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
Behavioral analysis of network flow traffic
Heller, Mark D.
2010-01-01
Approved for public release, distribution unlimited Network Behavior Analysis (NBA) is a technique to enhance network security by passively monitoring aggregate traffic patterns and noting unusual action or departures from normal operations. The analysis is typically performed offline, due to the huge volume of input data, in contrast to conventional intrusion prevention solutions based on deep packet inspection, signature detection, and real-time blocking. After establishing a benchmar...
Spectral derivative analysis of solar spectroradiometric measurements: Theoretical basis
Hansell, R. A.; Tsay, S.-C.; Pantina, P.; Lewis, J. R.; Ji, Q.; Herman, J. R.
2014-07-01
Spectral derivative analysis, a commonly used tool in analytical spectroscopy, is described for studying cirrus clouds and aerosols using hyperspectral, remote sensing data. The methodology employs spectral measurements from the 2006 Biomass-burning Aerosols in Southeast Asia field study to demonstrate the approach. Spectral peaks associated with the first two derivatives of measured/modeled transmitted spectral fluxes are examined in terms of their shapes, magnitudes, and positions from 350 to 750 nm, where variability is largest. Differences in spectral features between media are mainly associated with particle size and imaginary term of the complex refractive index. Differences in derivative spectra permit cirrus to be conservatively detected at optical depths near the optical thin limit of ~0.03 and yield valuable insight into the composition and hygroscopic nature of aerosols. Biomass-burning smoke aerosols/cirrus generally exhibit positive/negative slopes, respectively, across the 500-700 nm spectral band. The effect of cirrus in combined media is to increase/decrease the slope as cloud optical thickness decreases/increases. For thick cirrus, the slope tends to 0. An algorithm is also presented which employs a two model fit of derivative spectra for determining relative contributions of aerosols/clouds to measured data, thus enabling the optical thickness of the media to be partitioned. For the cases examined, aerosols/clouds explain ~83%/17% of the spectral signatures, respectively, yielding a mean cirrus cloud optical thickness of 0.08 ± 0.03, which compared reasonably well with those retrieved from a collocated Micropulse Lidar Network Instrument (0.09 ± 0.04). This method permits extracting the maximum informational content from hyperspectral data for atmospheric remote sensing applications.
A quantum information theoretic analysis of three flavor neutrino oscillations
Banerjee, Subhashish; Srikanth, R; Hiesmayr, Beatrix C
2015-01-01
Correlations exhibited by neutrino oscillations are studied via quantum information theoretic quantities. We show that the strongest type of entanglement, genuine multipartite entanglement, is persistent in the flavour changing states. We prove the existence of Bell-type nonlocal features, in both its absolute and genuine avatars. Finally, we show that a measure of nonclassicality, dissension, which is a generalization of quantum discord to the tripartite case, is nonzero for almost the entire range of time in the evolution of an initial electron-neutrino. Via these quantum information theoretic quantities capturing different aspects of quantum correlations, we elucidate the differences between the flavour types, shedding light on the quantum-information theoretic aspects of the weak force.
Theoretical analysis and experimental verification on optical rotational Doppler effect
Zhou, Hailong; Dong, Jianji; Zhang, Pei; Zhang, Xinliang
2016-01-01
We present a theoretical model to sufficiently investigate the optical rotational Doppler effect based on modal expansion method. We find that the frequency shift content is only determined by the surface of spinning object and the reduced Doppler shift is linear to the difference of mode index between input and output orbital angular momentum (OAM) light, and linear to the rotating speed of spinning object as well. An experiment is carried out to verify the theoretical model. We explicitly suggest that the spatial spiral phase distribution of spinning object determines the frequency content. The theoretical model makes us better understand the physical processes of rotational Doppler effect, and thus has many related application fields, such as detection of rotating bodies, imaging of surface and measurement of OAM light.
Theoretical analysis and experimental verification on optical rotational Doppler effect
Zhou, Hailong; Fu, Dongzhi; Dong, Jianji; Zhang, Pei; Zhang, Xinliang
2016-05-01
We present a theoretical model to sufficiently investigate the optical rotational Doppler effect based on modal expansion method. We find that the frequency shift content is only determined by the surface of spinning object and the reduced Doppler shift is linear to the difference of mode index between input and output orbital angular momentum (OAM) light, and linear to the rotating speed of spinning object as well. An experiment is carried out to verify the theoretical model. We explicitly suggest that the spatial spiral phase distribution of spinning object determines the frequency content. The theoretical model makes us better understand the physical processes of rotational Doppler effect, and thus has many related application fields, such as detection of rotating bodies, imaging of surface and measurement of OAM light.
Pathogenic Network Analysis Predicts Candidate Genes for Cervical Cancer
Directory of Open Access Journals (Sweden)
Yun-Xia Zhang
2016-01-01
Full Text Available Purpose. The objective of our study was to predicate candidate genes in cervical cancer (CC using a network-based strategy and to understand the pathogenic process of CC. Methods. A pathogenic network of CC was extracted based on known pathogenic genes (seed genes and differentially expressed genes (DEGs between CC and normal controls. Subsequently, cluster analysis was performed to identify the subnetworks in the pathogenic network using ClusterONE. Each gene in the pathogenic network was assigned a weight value, and then candidate genes were obtained based on the weight distribution. Eventually, pathway enrichment analysis for candidate genes was performed. Results. In this work, a total of 330 DEGs were identified between CC and normal controls. From the pathogenic network, 2 intensely connected clusters were extracted, and a total of 52 candidate genes were detected under the weight values greater than 0.10. Among these candidate genes, VIM had the highest weight value. Moreover, candidate genes MMP1, CDC45, and CAT were, respectively, enriched in pathway in cancer, cell cycle, and methane metabolism. Conclusion. Candidate pathogenic genes including MMP1, CDC45, CAT, and VIM might be involved in the pathogenesis of CC. We believe that our results can provide theoretical guidelines for future clinical application.
Modelling Opinion Dynamics: Theoretical analysis and continuous approximation
Pinasco, Juan Pablo; Balenzuela, Pablo
2016-01-01
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. In this case, the agreement is reached because the new arguments are incorporated. In this paper we deal with a simple model of opinion formation with such persuasion dynamics, and we find the exact analytical solutions for both, long and short range interactions. A novel theoretical approach has been used in order to solve the master equations of the model with non-local kernels. Simulation results demonstrate an excellent agreement with results obtained by the theoretical estimation.
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
Differential network analysis reveals dysfunctional regulatory networks in gastric carcinogenesis.
Cao, Mu-Shui; Liu, Bing-Ya; Dai, Wen-Tao; Zhou, Wei-Xin; Li, Yi-Xue; Li, Yuan-Yuan
2015-01-01
Gastric Carcinoma is one of the most common cancers in the world. A large number of differentially expressed genes have been identified as being associated with gastric cancer progression, however, little is known about the underlying regulatory mechanisms. To address this problem, we developed a differential networking approach that is characterized by including a nascent methodology, differential coexpression analysis (DCEA), and two novel quantitative methods for differential regulation analysis. We first applied DCEA to a gene expression dataset of gastric normal mucosa, adenoma and carcinoma samples to identify gene interconnection changes during cancer progression, based on which we inferred normal, adenoma, and carcinoma-specific gene regulation networks by using linear regression model. It was observed that cancer genes and drug targets were enriched in each network. To investigate the dynamic changes of gene regulation during carcinogenesis, we then designed two quantitative methods to prioritize differentially regulated genes (DRGs) and gene pairs or links (DRLs) between adjacent stages. It was found that known cancer genes and drug targets are significantly higher ranked. The top 4% normal vs. adenoma DRGs (36 genes) and top 6% adenoma vs. carcinoma DRGs (56 genes) proved to be worthy of further investigation to explore their association with gastric cancer. Out of the 16 DRGs involved in two top-10 DRG lists of normal vs. adenoma and adenoma vs. carcinoma comparisons, 15 have been reported to be gastric cancer or cancer related. Based on our inferred differential networking information and known signaling pathways, we generated testable hypotheses on the roles of GATA6, ESRRG and their signaling pathways in gastric carcinogenesis. Compared with established approaches which build genome-scale GRNs, or sub-networks around differentially expressed genes, the present one proved to be better at enriching cancer genes and drug targets, and prioritizing
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...
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...
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....
A theoretical analysis of NADPH production and consumption in yeasts
Bruinenberg, P.M.; Van Dijken, J.P.; Scheffers, W.A.
1983-01-01
Theoretical calculations of the NADPH requirement for yeast biomass formation reveal that this parameter is strongly dependent on the carbon and nitrogen source. The data obtained have been used to estimate the carbon flow over the NADPH-producing pathways in these organisms, namely the hexose monop
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.
Advantages and limitations of transition voltage spectroscopy: A theoretical analysis
Mirjani, F.; Thijssen, J.M.; Van der Molen, S.J.
2011-01-01
In molecular charge transport, transition voltage spectroscopy (TVS) holds the promise that molecular energy levels can be explored at bias voltages lower than required for resonant tunneling. We investigate the theoretical basis of this tool using a generic model. In particular, we study the length
Theoretical bases analysis of scientific prediction on marketing principles
Directory of Open Access Journals (Sweden)
A.S. Rosohata
2012-06-01
Full Text Available 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.
The US-China Trade Conflict: A Game Theoretical Analysis
Hebatallah Ghoneim; Yasmine Reda
2008-01-01
Game Theory has been gaining great importance in Economics, encouraging research in many theoretical and applied fields. This paper relies on simple game theory tools to set up a major international trade dispute. Using the backward deduction approach, the strategies of the United States and China in their recent trade conflict are analyzed.
Theoretical Analysis and Derivation of Combustion Wave Parameters
Institute of Scientific and Technical Information of China (English)
CHEN Jun
2006-01-01
Theoretical relations of pressure, density, velocity, temperature and Mach number of combustion waves are built. The parameters' curves with different combustion energy are illustrated in which four zones are pointed out to represent different combustion states. The expressions and curves of parameters are important to analyze the trends of combustion waves, and to determine conditions on which detonation waves or deflagration waves occur.
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.
Analytical framework for recurrence network analysis of time series.
Donges, Jonathan F; Heitzig, Jobst; Donner, Reik V; Kurths, Jürgen
2012-04-01
Recurrence networks are a powerful nonlinear tool for time series analysis of complex dynamical systems. While there are already many successful applications ranging from medicine to paleoclimatology, a solid theoretical foundation of the method has still been missing so far. Here, we interpret an ɛ-recurrence network as a discrete subnetwork of a "continuous" graph with uncountably many vertices and edges corresponding to the system's attractor. This step allows us to show that various statistical measures commonly used in complex network analysis can be seen as discrete estimators of newly defined continuous measures of certain complex geometric properties of the attractor on the scale given by ɛ. In particular, we introduce local measures such as the ɛ-clustering coefficient, mesoscopic measures such as ɛ-motif density, path-based measures such as ɛ-betweennesses, and global measures such as ɛ-efficiency. This new analytical basis for the so far heuristically motivated network measures also provides an objective criterion for the choice of ɛ via a percolation threshold, and it shows that estimation can be improved by so-called node splitting invariant versions of the measures. We finally illustrate the framework for a number of archetypical chaotic attractors such as those of the Bernoulli and logistic maps, periodic and two-dimensional quasiperiodic motions, and for hyperballs and hypercubes by deriving analytical expressions for the novel measures and comparing them with data from numerical experiments. More generally, the theoretical framework put forward in this work describes random geometric graphs and other networks with spatial constraints, which appear frequently in disciplines ranging from biology to climate science.
Theoretical Investigation of Optical WDM Network Performance in the Presence of FWM and ASE Noise
Iyer, Sridhar; Joy, Ambily
2017-03-01
In this article, for an optical star wavelength division multiplexing (WDM) network, with quality factor (Q-factor) as performance metric, we investigate the performance degradation due to the combined effects of four-wave mixing (FWM) and amplified spontaneous emission (ASE) noise. A mathematical model is developed, and the simulations are performed based on the optical frequency grid defined by the ITU-T Recommendation G.692. Further, the analysis is conducted for the optical fibers that are ITU-T compliant viz. G.652, G. 652D, G. 653, G. 654 and G.655. The simulation results show that, compared to the other fiber types, performance of the G. 652D and G.652 fibers is the "best", thus justifying the preferred use of fibers with high dispersion and effective area values. The simulation results also highlight that with the use of a fiber having low dispersion and effective area value, it may not be possible to obtain the desired performance.
Network Analysis: A Novel Approach to Understand Suicidal Behaviour
de Beurs, Derek
2017-01-01
Although suicide is a major public health issue worldwide, we understand little of the onset and development of suicidal behaviour. Suicidal behaviour is argued to be the end result of the complex interaction between psychological, social and biological factors. Epidemiological studies resulted in a range of risk factors for suicidal behaviour, but we do not yet understand how their interaction increases the risk for suicidal behaviour. A new approach called network analysis can help us better understand this process as it allows us to visualize and quantify the complex association between many different symptoms or risk factors. A network analysis of data containing information on suicidal patients can help us understand how risk factors interact and how their interaction is related to suicidal thoughts and behaviour. A network perspective has been successfully applied to the field of depression and psychosis, but not yet to the field of suicidology. In this theoretical article, I will introduce the concept of network analysis to the field of suicide prevention, and offer directions for future applications and studies.
Network Anomaly Detection Based on Wavelet Analysis
Directory of Open Access Journals (Sweden)
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.
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.
Intrinsic functional brain architecture derived from graph theoretical analysis in the human fetus.
Thomason, Moriah E; Brown, Jesse A; Dassanayake, Maya T; Shastri, Rupal; Marusak, Hilary A; Hernandez-Andrade, Edgar; Yeo, Lami; Mody, Swati; Berman, Susan; Hassan, Sonia S; Romero, Roberto
2014-01-01
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 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.
Volkov, Alexey N.; Salaway, Richard N.; Zhigilei, Leonid V.
2013-09-01
The propensity of carbon nanotubes (CNTs) to self-organize into continuous networks of bundles has direct implications for thermal transport properties of CNT network materials and defines the importance of clear understanding of the mechanisms and scaling laws governing the heat transfer within the primary building blocks of the network structures—close-packed bundles of CNTs. A comprehensive study of the thermal conductivity of CNT bundles is performed with a combination of non-equilibrium molecular dynamics (MD) simulations of heat transfer between adjacent CNTs and the intrinsic conductivity of CNTs in a bundle with a theoretical analysis that reveals the connections between the structure and thermal transport properties of CNT bundles. The results of MD simulations of heat transfer in CNT bundles consisting of up to 7 CNTs suggest that, contrary to the widespread notion of strongly reduced conductivity of CNTs in bundles, van der Waals interactions between defect-free well-aligned CNTs in a bundle have negligible effect on the intrinsic conductivity of the CNTs. The simulations of inter-tube heat conduction performed for partially overlapping parallel CNTs indicate that the conductance through the overlap region is proportional to the length of the overlap for CNTs and CNT-CNT overlaps longer than several tens of nm. Based on the predictions of the MD simulations, a mesoscopic-level model is developed and applied for theoretical analysis and numerical modeling of heat transfer in bundles consisting of CNTs with infinitely large and finite intrinsic thermal conductivities. The general scaling laws predicting the quadratic dependence of the bundle conductivity on the length of individual CNTs in the case when the thermal transport is controlled by the inter-tube conductance and the independence of the CNT length in another limiting case when the intrinsic conductivity of CNTs plays the dominant role are derived. An application of the scaling laws to bundles of
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.
Self-selection into teamwork: A theoretical and experimental analysis
Stribeck, Agnes; Pull, Kerstin
2010-01-01
We analyze self-selection decisions regarding teamwork both theoretically and empirically. While we focus on individual talent, we also investigate the effects of team tasks, individual teamwork skills, and expectations concerning the talent and teamwork skills of potential teammates as further determinants in the self-selection process. Putting our hypotheses derived from a basic self-selection model in dialogue with original data from a real-task laboratory experiment, we are able to show t...
Theoretical analysis of radiation-balanced double clad fiber laser
Institute of Scientific and Technical Information of China (English)
CHEN Ji-xin; SUI Zhan; CHEN Fu-shen; LI Ming-zhong; WANG Jian-jun
2005-01-01
In this letter,a theoretical model of radiation-balanced double clad fiber laser is presented.The characteristic of the laser with Yb doped double clad fiber is analyzed numerically.It is concluded that high output laser power can be obtained by selecting output coupling mirror with lower reflectivity,improving Yb doped concentration and choosing fiber length. This result can help us to design radiation balanced fiber laser.
Microgenetic Analysis of Moral Development: Theoretical and Methodological Issues
Barrios, Alia; Barbato,Silviane; Branco,Angela
2012-01-01
New ideas and methodologies need to be developed to advance our knowledge in the understanding of moral development. The intertwined nature of human activities, communication processes, and the numerous aspects of morality pose a challenge to researchers to construct a methodology that takes into account cognition, affect, sociocultural processes and characteristics, as well as the active role of individuals in their own development. In this paper we aim at suggesting fresh theoretical ideas ...
Medical image analysis with artificial neural networks.
Jiang, J; Trundle, P; Ren, J
2010-12-01
Given that neural networks have been widely reported in the research community of medical imaging, we provide a focused literature survey on recent neural network developments in computer-aided diagnosis, medical image segmentation and edge detection towards visual content analysis, and medical image registration for its pre-processing and post-processing, with the aims of increasing awareness of how neural networks can be applied to these areas and to provide a foundation for further research and practical development. Representative techniques and algorithms are explained in detail to provide inspiring examples illustrating: (i) how a known neural network with fixed structure and training procedure could be applied to resolve a medical imaging problem; (ii) how medical images could be analysed, processed, and characterised by neural networks; and (iii) how neural networks could be expanded further to resolve problems relevant to medical imaging. In the concluding section, a highlight of comparisons among many neural network applications is included to provide a global view on computational intelligence with neural networks in medical imaging. Copyright © 2010 Elsevier Ltd. All rights reserved.
Kinetic analysis of complex metabolic networks
Energy Technology Data Exchange (ETDEWEB)
Stephanopoulos, G. [MIT, Cambridge, MA (United States)
1996-12-31
A new methodology is presented for the analysis of complex metabolic networks with the goal of metabolite overproduction. The objective is to locate a small number of reaction steps in a network that have maximum impact on network flux amplification and whose rate can also be increased without functional network derangement. This method extends the concepts of Metabolic Control Analysis to groups of reactions and offers the means for calculating group control coefficients as measures of the control exercised by groups of reactions on the overall network fluxes and intracellular metabolite pools. It is further demonstrated that the optimal strategy for the effective increase of network fluxes, while maintaining an uninterrupted supply of intermediate metabolites, is through the coordinated amplification of multiple (as opposed to a single) reaction steps. Satisfying this requirement invokes the concept of the concentration control to coefficient, which emerges as a critical parameter in the identification of feasible enzymatic modifications with maximal impact on the network flux. A case study of aromatic aminoacid production is provided to illustrate these concepts.
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/.
Sympatry inference and network analysis in biogeography.
Dos Santos, Daniel A; Fernández, Hugo R; Cuezzo, María Gabriela; Domínguez, Eduardo
2008-06-01
A new approach for biogeography to find patterns of sympatry, based on network analysis, is proposed. Biogeographic analysis focuses basically on sympatry patterns of species. Sympatry is a network (= relational) datum, but it has never been analyzed before using relational tools such as Network Analysis. Our approach to biogeographic analysis consists of two parts: first the sympatry inference and second the network analysis method (NAM). The sympatry inference method was designed to propose sympatry hypothesis, constructing a basal sympatry network based on punctual data, independent of a priori distributional area determination. In this way, two or more species are considered sympatric when there is interpenetration and relative proximity among their records of occurrence. In nature, groups of species presenting within-group sympatry and between-group allopatry constitute natural units (units of co-occurrence). These allopatric units are usually connected by intermediary species. The network analysis method (NAM) that we propose here is based on the identification and removal of intermediary species to segregate units of co-occurrence, using the betweenness measure and the clustering coefficient. The species ranges of the units of co-occurrence obtained are transferred to a map, being considered as candidates to areas of endemism. The new approach was implemented on three different real complex data sets (one of them a classic example previously used in biogeography) resulting in (1) independence of predefined spatial units; (2) definition of co-occurrence patterns from the sympatry network structure, not from species range similarities; (3) higher stability in results despite scale changes; (4) identification of candidates to areas of endemism supported by strictly endemic species; (5) identification of intermediary species with particular biological attributes.
PIT Overload Analysis in Content Centric Networks
Virgilio, Matteo; Marchetto, Guido; Sisto, Riccardo
2013-01-01
Content Centric Networking represents a paradigm shift in the evolution and definition of modern network protocols. Many research efforts have been made with the purpose of proving the feasibility and the scalability of this proposal. Our main contribution is to provide an analysis of the Pending Interest Table memory requirements in real deployment scenarios, especially considering the impact of distributed denial of service attacks. In fact, the state that the protocol maintains for each re...
Multilayer Analysis and Visualization of Networks
De Domenico, Manlio; Arenas, Alex
2014-01-01
Multilayer relationships among and information about biological entities must be accompanied by the means to analyze, visualize, and obtain insights from such data. We report a methodology and a collection of algorithms for the analysis of multilayer networks in our new open-source software (muxViz). We demonstrate the ability of muxViz to analyze and interactively visualize multilayer data using empirical genetic and neuronal networks.
Applying centrality measures to impact analysis: A coauthorship network analysis
Yan, Erjia
2010-01-01
Many studies on coauthorship networks focus on network topology and network statistical mechanics. This article takes a different approach by studying micro-level network properties, with the aim to apply centrality measures to impact analysis. Using coauthorship data from 16 journals in the field of library and information science (LIS) with a time span of twenty years (1988-2007), we construct an evolving coauthorship network and calculate four centrality measures (closeness, betweenness, degree and PageRank) for authors in this network. We find out that the four centrality measures are significantly correlated with citation counts. We also discuss the usability of centrality measures in author ranking, and suggest that centrality measures can be useful indicators for impact analysis.
Probabilistic analysis on fault tolerance of 3-Dimensional mesh networks
Institute of Scientific and Technical Information of China (English)
王高才; 陈建二; 王国军; 陈松乔
2003-01-01
The probability model is used to analyze the fault tolerance of mesh. To simplify its analysis, it is as-sumed that the failure probability of each node is independent. A 3-D mesh is partitioned into smaller submeshes,and then the probability with which each submesh satisfies the defined condition is computed. If each submesh satis-fies the condition, then the whole mesh is connected. Consequently, the probability that a 3-D mesh is connected iscomputed assuming each node has a failure probability. Mathematical methods are used to derive a relationship be-tween network node failure probability and network connectivity probability. The calculated results show that the 3-D mesh networks can remain connected with very high probability in practice. It is formally proved that when thenetwork node failure probability is boutded by 0.45 %, the 3-D mesh networks of more than three hundred thousandnodes remain connected with probability larger than 99 %. The theoretical results show that the method is a power-ful technique to calculate the lower bound of the connectivity probability of mesh networks.
Percolation centrality: quantifying graph-theoretic impact of nodes during percolation in networks.
Directory of Open Access Journals (Sweden)
Mahendra Piraveenan
Full Text Available A number of centrality measures are available to determine the relative importance of a node in a complex network, and betweenness is prominent among them. However, the existing centrality measures are not adequate in network percolation scenarios (such as during infection transmission in a social network of individuals, spreading of computer viruses on computer networks, or transmission of disease over a network of towns because they do not account for the changing percolation states of individual nodes. We propose a new measure, percolation centrality, that quantifies relative impact of nodes based on their topological connectivity, as well as their percolation states. The measure can be extended to include random walk based definitions, and its computational complexity is shown to be of the same order as that of betweenness centrality. We demonstrate the usage of percolation centrality by applying it to a canonical network as well as simulated and real world scale-free and random networks.
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.
Directory of Open Access Journals (Sweden)
Marcus H Heitger
Full Text Available In bimanual coordination, older and younger adults activate a common cerebral network but the elderly also have additional activation in a secondary network of brain areas to master task performance. It remains unclear whether the functional connectivity within these primary and secondary motor networks differs between the old and the young and whether task difficulty modulates connectivity. We applied graph-theoretical network analysis (GTNA to task-driven fMRI data in 16 elderly and 16 young participants using a bimanual coordination task including in-phase and anti-phase flexion/extension wrist movements. Network nodes for the GTNA comprised task-relevant brain areas as defined by fMRI activation foci. The elderly matched the motor performance of the young but showed an increased functional connectivity in both networks across a wide range of connectivity metrics, i.e., higher mean connectivity degree, connection strength, network density and efficiency, together with shorter mean communication path length between the network nodes and also a lower betweenness centrality. More difficult movements showed an increased connectivity in both groups. The network connectivity of both groups had "small world" character. The present findings indicate (a that bimanual coordination in the aging brain is associated with a higher functional connectivity even between areas also activated in young adults, independently from task difficulty, and (b that adequate motor coordination in the context of task-driven bimanual control in older adults may not be solely due to additional neural recruitment but also to aging-related changes of functional relationships between brain regions.
Analysis of Theoretical Basis of Direct Subsidies for Grain Production
Institute of Scientific and Technical Information of China (English)
Shengping; SHI; Xiaorong; LUO; Hongjing; LI
2014-01-01
Financial distribution to compensate grain production reflects governmental macro-control on grain production and supply. With the reference of agricultural basic theory,agricultural multi-function theory,economic externality theory,public finance and other theories,this article points out that direct subsidies for grain production is reasonable and necessary with six main theoretical basis,namely fundamentality,multi-function,positive externality of grain production,particularity of grain supply and demand,grain safety being closely linked with national security and basic function of service-oriented government.
Information-theoretic analysis of electronic and printed document authentication
Voloshynovskiy, Sviatoslav; Koval, Oleksiy; Villan, Renato; Topak, Emre; Vila Forcén, José Emilio; Deguillaume, Frederic; Rytsar, Yuriy; Pun, Thierry
2006-02-01
In this paper we consider the problem of document authentication in electronic and printed forms. We formulate this problem from the information-theoretic perspectives and present the joint source-channel coding theorems showing the performance limits in such protocols. We analyze the security of document authentication methods and present the optimal attacking strategies with corresponding complexity estimates that, contrarily to the existing studies, crucially rely on the information leaked by the authentication protocol. Finally, we present the results of experimental validation of the developed concept that justifies the practical efficiency of the elaborated framework.
A theoretical analysis of global characteristics of spread-F
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
Spread-F is an important ionosphere pheonome non and it has much effect on radio wave propogation. Tak ing magnetic inclination and declination into consideration, a theoretical model is deduced for the linear growth-rate of spread-F. It is a generalization of the earlier equatorial model and a relatively complete description o f the spread-F pheonomenon. This theory shows that the magnetic configu ration, i.e. the magnetic strength, inclination and declination,affects the occurrence rate greatly, which forms some re gional distribution characteristics of the spread-F.
A game-theoretic perspective on rough set analysis
Institute of Scientific and Technical Information of China (English)
YAO Jing-tao; HERBERT Joseph P
2008-01-01
Determining the correct threshold values for the probabilistic rough set approaches has been a heated issue among the community. Existing techniques offer no way in guaranteeing that the calculated values optimize the classification ability of the decision rules derived from this configuration. This article will formulate a game theoretic approach to calculating these thresholds to ensure correct approximation region size. Using payoff tables created from approximation measures and modified conditional risk strategies, we provide the user with tolerance levels for their loss functions. Using the tolerance values, new thresholds are calculated to provide correct classification regions. This will aid in determining a set of optimal region threshold values for decision making.
Theoretical Analysis of Magnetorheological Damper Characteristics in Squeeze Mode
Directory of Open Access Journals (Sweden)
Sapiński Bogdan
2015-06-01
Full Text Available The paper summarises the theoretical study of a magnetorheological (MR damper operated in squeeze mode, intended to be used as an actuator in a semi-active mount system in a car motor. The structural design and operating principle of the damper are described and a simplified model of the MR fluid flow in the gap is presented. The plots of the damper force generated by the MR damper are obtained for monoharmonic piston motion with respect to the centre point of the gap height and in the conditions of the control coil being supplied with direct current.
Pino-Fan, Luis R.; Guzmán, Ismenia; Font, Vicenç; Duval, Raymond
2017-01-01
This paper presents a study of networking of theories between the theory of registers of semiotic representation (TRSR) and the onto-semiotic approach of mathematical cognition and instruction (OSA). The results obtained show complementarities between these two theoretical perspectives, which might allow more detailed analysis of the students'…
Sparsity analysis of DS spread spectrum signals via theoretical analysis and dictionary learning
Wang, Kai; Wu, Bin; Wang, Bo
2017-04-01
For the purpose of solving the problem of high sampling rate and massive data processing brought by high bandwidth in the field of Aerospace Communication, researchers applied CS theory to spread spectrum signal processing. Sparsity analysis is the prerequisite for the application of CS theory. This paper studies the sparsity of the DS spread spectrum signals, which is the most common kind of signal in the current TT&C systems. Based on the theoretical analysis we get the sparse dictionary, then the dictionary is optimized by K-SVD dictionary learning algorithm. The simulation results show that the two signals have strong sparsity in the constructed sparse base dictionary, which lays a theoretical foundation for the TT&C spread spectrum signal processing based on CS theory.
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.
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.
Exploring triad-rich substructures by graph-theoretic characterizations in complex networks
Jia, Songwei; Gao, Lin; Gao, Yong; Nastos, James; Wen, Xiao; Zhang, Xindong; Wang, Haiyang
2017-02-01
One of the most important problems in complex networks is how to detect communities accurately. The main challenge lies in the fact that traditional definition about communities does not always capture the intrinsic features of communities. Motivated by the observation that communities in PPI networks tend to consist of an abundance of interacting triad motifs, we define a 2-club substructure with diameter 2 possessing triad-rich property to describe a community. Based on the triad-rich substructure, we design a DIVision Algorithm using our proposed edge Niche Centrality DIVANC to detect communities effectively in complex networks. We also extend DIVANC to detect overlapping communities by proposing a simple 2-hop overlapping strategy. To verify the effectiveness of triad-rich substructures, we compare DIVANC with existing algorithms on PPI networks, LFR synthetic networks and football networks. The experimental results show that DIVANC outperforms most other algorithms significantly and, in particular, can detect sparse communities.
Exploring triad-rich substructures by graph-theoretic characterizations in complex networks
Jia, Songwei; Gao, Yong; Nastos, James; Wen, Xiao; Zhang, Xindong; Wang, Haiyang
2016-01-01
One of the most important problems in complex networks is how to detect metadata groups accurately. The main challenge lies in the fact that traditional structural communities do not always capture the intrinsic features of metadata groups. Motivated by the observation that metadata groups in PPI networks tend to consist of an abundance of interacting triad motifs, we define a 2-club substructure with diameter 2 which possessing triad-rich property to describe a metadata group. Based on the triad-rich substructure, we design a DIVision Algorithm using our proposed edge Niche Centrality DIVANC to detect metadata groups effectively in complex networks. We also extend DIVANC to detect overlapping metadata groups by proposing a simple 2-hop overlapping strategy. To verify the effectiveness of triad-rich substructures, we compare DIVANC with existing algorithms on PPI networks, LFR synthetic networks and football networks. The experimental results show that DIVANC outperforms most other algorithms significantly an...
Anion order in perovskites: a group-theoretical analysis.
Talanov, M V; Shirokov, V B; Talanov, V M
2016-03-01
Anion ordering in the structure of cubic perovskite has been investigated by the group-theoretical method. The possibility of the existence of 261 ordered low-symmetry structures, each with a unique space-group symmetry, is established. These results include five binary and 14 ternary anion superstructures. The 261 idealized anion-ordered perovskite structures are considered as aristotypes, giving rise to different derivatives. The structures of these derivatives are formed by tilting of BO6 octahedra, distortions caused by the cooperative Jahn-Teller effect and other physical effects. Some derivatives of aristotypes exist as real substances, and some as virtual ones. A classification of aristotypes of anion superstructures in perovskite is proposed: the AX class (the simultaneous ordering of A cations and anions in cubic perovskite structure), the BX class (the simultaneous ordering of B cations and anions) and the X class (the ordering of anions only in cubic perovskite structure). In most perovskites anion ordering is accompanied by cation ordering. Therefore, the main classes of anion order in perovskites are the AX and BX classes. The calculated structures of some anion superstructures are reported. Comparison of predictions and experimentally investigated anion superstructures shows coherency of theoretical and experimental results.
Network analysis of eight industrial symbiosis systems
Zhang, Yan; Zheng, Hongmei; Shi, Han; Yu, Xiangyi; Liu, Gengyuan; Su, Meirong; Li, Yating; Chai, Yingying
2016-06-01
Industrial symbiosis is the quintessential characteristic of an eco-industrial park. To divide parks into different types, previous studies mostly focused on qualitative judgments, and failed to use metrics to conduct quantitative research on the internal structural or functional characteristics of a park. To analyze a park's structural attributes, a range of metrics from network analysis have been applied, but few researchers have compared two or more symbioses using multiple metrics. In this study, we used two metrics (density and network degree centralization) to compare the degrees of completeness and dependence of eight diverse but representative industrial symbiosis networks. Through the combination of the two metrics, we divided the networks into three types: weak completeness, and two forms of strong completeness, namely "anchor tenant" mutualism and "equality-oriented" mutualism. The results showed that the networks with a weak degree of completeness were sparse and had few connections among nodes; for "anchor tenant" mutualism, the degree of completeness was relatively high, but the affiliated members were too dependent on core members; and the members in "equality-oriented" mutualism had equal roles, with diverse and flexible symbiotic paths. These results revealed some of the systems' internal structure and how different structures influenced the exchanges of materials, energy, and knowledge among members of a system, thereby providing insights into threats that may destabilize the network. Based on this analysis, we provide examples of the advantages and effectiveness of recent improvement projects in a typical Chinese eco-industrial park (Shandong Lubei).
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
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…
Complex networks analysis of language complexity
Amancio, Diego R; Oliveira, Osvaldo N; Costa, Luciano da F; 10.1209/0295-5075/100/58002
2013-01-01
Methods from statistical physics, such as those involving complex networks, have been increasingly used in quantitative analysis of linguistic phenomena. In this paper, we represented pieces of text with different levels of simplification in co-occurrence networks and found that topological regularity correlated negatively with textual complexity. Furthermore, in less complex texts the distance between concepts, represented as nodes, tended to decrease. The complex networks metrics were treated with multivariate pattern recognition techniques, which allowed us to distinguish between original texts and their simplified versions. For each original text, two simplified versions were generated manually with increasing number of simplification operations. As expected, distinction was easier for the strongly simplified versions, where the most relevant metrics were node strength, shortest paths and diversity. Also, the discrimination of complex texts was improved with higher hierarchical network metrics, thus point...
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.
Shattering and Compressing Networks for Centrality Analysis
Sarıyüce, Ahmet Erdem; Kaya, Kamer; Çatalyürek, Ümit V
2012-01-01
Who is more important in a network? Who controls the flow between the nodes or whose contribution is significant for connections? Centrality metrics play an important role while answering these questions. The betweenness metric is useful for network analysis and implemented in various tools. Since it is one of the most computationally expensive kernels in graph mining, several techniques have been proposed for fast computation of betweenness centrality. In this work, we propose and investigate techniques which compress a network and shatter it into pieces so that the rest of the computation can be handled independently for each piece. Although we designed and tuned the shattering process for betweenness, it can be adapted for other centrality metrics in a straightforward manner. Experimental results show that the proposed techniques can be a great arsenal to reduce the centrality computation time for various types of networks.
Domino effect analysis using Bayesian networks.
Khakzad, Nima; Khan, Faisal; Amyotte, Paul; Cozzani, Valerio
2013-02-01
A new methodology is introduced based on Bayesian network both to model domino effect propagation patterns and to estimate the domino effect probability at different levels. The flexible structure and the unique modeling techniques offered by Bayesian network make it possible to analyze domino effects through a probabilistic framework, considering synergistic effects, noisy probabilities, and common cause failures. Further, the uncertainties and the complex interactions among the domino effect components are captured using Bayesian network. The probabilities of events are updated in the light of new information, and the most probable path of the domino effect is determined on the basis of the new data gathered. This study shows how probability updating helps to update the domino effect model either qualitatively or quantitatively. The methodology is applied to a hypothetical example and also to an earlier-studied case study. These examples accentuate the effectiveness of Bayesian network in modeling domino effects in processing facility. © 2012 Society for Risk Analysis.
Automated Analysis of Security in Networking Systems
DEFF Research Database (Denmark)
Buchholtz, Mikael
2004-01-01
It has for a long time been a challenge to built secure networking systems. One way to counter this problem is to provide developers of software applications for networking systems with easy-to-use tools that can check security properties before the applications ever reach the marked. These tools...... will both help raise the general level of awareness of the problems and prevent the most basic flaws from occurring. This thesis contributes to the development of such tools. Networking systems typically try to attain secure communication by applying standard cryptographic techniques. In this thesis...... attacks, and attacks launched by insiders. Finally, the perspectives for the application of the analysis techniques are discussed, thereby, coming a small step closer to providing developers with easy- to-use tools for validating the security of networking applications....
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.
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.
Design of Intelligent Network Performance Analysis Forecast Support System
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A system designed for supporting the network performance analysis and forecast effort is pre sented, based on the combination of offline network analysis and online real-time performance forecast. The off-line analysis will perform analysis of specific network node performance, correlation analysis of relative network nodes performance and evolutionary mathematical modeling of long-term network performance mea surements. The online real-time network performance forecast will be based on one so-called hybrid predic tion modeling approach for short-term network performance prediction and trend analysis. Based on the module design, the system proposed has good intelligence, scalability and self-adaptability, which will offer highly effective network performance analysis and forecast tools for network managers, and is one ideal sup port platform for network performance analysis and forecast effort.
The creep experiment and theoretical model analysis of gascontaining coal
Institute of Scientific and Technical Information of China (English)
YIN Guang-zhi; ZHANG Dong-ming; WANG Wei-zhong
2007-01-01
A creep experiment of preformed molding coal under different confining pressures were carried out using self-developed 3-triaxial creep loading device for gas-containing coal, which loaded by Shimadzu AGI-250 kN electrical servo-controlled stiffness testing machine. Based on the experimental results, the variation trend of axial deformation under different stress states was studied, and creep failure characteristics of gascontaining coal under different confining pressures were analyzed. The experimental results were identified with seven-component nonlinear viscoelasto-plastic creep model (Hohai model), and the creep material parameters were obtained. The experimental result complies well with the theoretical value of this model. It indicates that creep constitutive relation of gas-containing coal can be expressed by nonlinear viscoelasto-plastic creep model correctly.
Income Distribution Dependence of Poverty Measure: A Theoretical Analysis
Chattopadhyay, A K; Chattopadhyay, Amit K; Mallick, Sushanta K
2005-01-01
With a new deprivation (or poverty) function, in this paper, we theoretically study the changes in poverty with respect to the `global' mean and variance of the income distribution using Indian survey data. We show that when the income obeys a log-normal distribution, a rising mean income generally indicates a reduction in poverty while an increase in the variance of the income distribution increases poverty. This altruistic view for a developing economy, however, is not tenable anymore once the poverty index is found to follow a pareto distribution. Here although a rising mean income indicates a reduction in poverty, due to the presence of an inflexion point in the poverty function, there is a critical value of the variance below which poverty decreases with increasing variance while beyond this value, poverty undergoes a steep increase followed by a decrease with respect to higher variance. Following these results, we make quantitative predictions to correlate a developing with a developed economy.
An Information Theoretic Analysis of Decision in Computer Chess
Godescu, Alexandru
2011-01-01
The basis of the method proposed in this article is the idea that information is one of the most important factors in strategic decisions, including decisions in computer chess and other strategy games. The model proposed in this article and the algorithm described are based on the idea of a information theoretic basis of decision in strategy games . The model generalizes and provides a mathematical justification for one of the most popular search algorithms used in leading computer chess programs, the fractional ply scheme. However, despite its success in leading computer chess applications, until now few has been published about this method. The article creates a fundamental basis for this method in the axioms of information theory, then derives the principles used in programming the search and describes mathematically the form of the coefficients. One of the most important parameters of the fractional ply search is derived from fundamental principles. Until now this coefficient has been usually handcrafted...
Differential network analysis in human cancer research.
Gill, Ryan; Datta, Somnath; Datta, Susmita
2014-01-01
A complex disease like cancer is hardly caused by one gene or one protein singly. It is usually caused by the perturbation of the network formed by several genes or proteins. In the last decade several research teams have attempted to construct interaction maps of genes and proteins either experimentally or reverse engineer interaction maps using computational techniques. These networks were usually created under a certain condition such as an environmental condition, a particular disease, or a specific tissue type. Lately, however, there has been greater emphasis on finding the differential structure of the existing network topology under a novel condition or disease status to elucidate the perturbation in a biological system. In this review/tutorial article we briefly mention some of the research done in this area; we mainly illustrate the computational/statistical methods developed by our team in recent years for differential network analysis using publicly available gene expression data collected from a well known cancer study. This data includes a group of patients with acute lymphoblastic leukemia and a group with acute myeloid leukemia. In particular, we describe the statistical tests to detect the change in the network topology based on connectivity scores which measure the association or interaction between pairs of genes. The tests under various scores are applied to this data set to perform a differential network analysis on gene expression for human leukemia. We believe that, in the future, differential network analysis will be a standard way to view the changes in gene expression and protein expression data globally and these types of tests could be useful in analyzing the complex differential signatures.
Theoretical and software considerations for nonlinear dynamic analysis
Schmidt, R. J.; Dodds, R. H., Jr.
1983-01-01
In the finite element method for structural analysis, it is generally necessary to discretize the structural model into a very large number of elements to accurately evaluate displacements, strains, and stresses. As the complexity of the model increases, the number of degrees of freedom can easily exceed the capacity of present-day software system. Improvements of structural analysis software including more efficient use of existing hardware and improved structural modeling techniques are discussed. One modeling technique that is used successfully in static linear and nonlinear analysis is multilevel substructuring. This research extends the use of multilevel substructure modeling to include dynamic analysis and defines the requirements for a general purpose software system capable of efficient nonlinear dynamic analysis. The multilevel substructuring technique is presented, the analytical formulations and computational procedures for dynamic analysis and nonlinear mechanics are reviewed, and an approach to the design and implementation of a general purpose structural software system is presented.
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.
Institute of Scientific and Technical Information of China (English)
YANG Jun; YUAN Li-bo
2006-01-01
A white-light interferometric fiber-optic sensing network based on the double-ring topology is demonstrated,which can be applied to the measurements of quasidistributed strain and temperature in a smart structure.In order to increase the multiplexing capacity,decrease the measurement cost of each sensor,and improve the ability of reliability of the sensor network,a double-port interrogating technology was used.The double- ring fiber optical sensing network based on the space division multiplexing (SDM) is further developed,The low coherent multiplexing principle in the double-ring network structure is analyzed.Based on the optical path matching condition of SDM,the intensity characteristic of the interference signal in the sensor is deduced.The characteristics of the double-ring sensing network connecting 9 sensors and its property of robust resisting destruction are verified by experiments,and the results are analyzed and discussed.
Liu, Wenjia; Schmittmann, Beate; Zia, R. K. P.
2012-02-01
Network studies have played a central role for understanding many systems in nature - e.g., physical, biological, and social. So far, much of the focus has been the statistics of networks in isolation. Yet, many networks in the world are coupled to each other. Recently, we considered this issue, in the context of two interacting social networks. In particular, We studied networks with two different preferred degrees, modeling, say, introverts vs. extroverts, with a variety of ``rules for engagement.'' As a first step towards an analytically accessible theory, we restrict our attention to an ``extreme scenario'': The introverts prefer zero contacts while the extroverts like to befriend everyone in the society. In this ``maximally frustrated'' system, the degree distributions, as well as the statistics of cross-links (between the two groups), can depend sensitively on how a node (individual) creates/breaks its connections. The simulation results can be reasonably well understood in terms of an approximate theory.
On Distributed Localization for Road Sensor Networks: A Game Theoretic Approach
Directory of Open Access Journals (Sweden)
Jie Jia
2013-01-01
Full Text Available Road sensor network is an important part of vehicle networks system and is critical for many intelligent automobile scenarios, such as vehicle safety monitoring and transportation efficiency supporting. Localization of sensors is an active and crucial issue to most applications of road sensor network. Generally, given some anchor nodes’ positions and certain pairwise distance measurements, estimating the positions of all nonanchor nodes embodies a nonconvex optimization problem. However, due to the small number of anchor nodes and low sensor node connectivity degree in road sensor networks, the existing localization solutions are ineffective. In order to tackle this problem, a novel distributed localization method based on game theory for road sensor networks is proposed in this paper. Formally, we demonstrate that our proposed localization game is a potential game. Furthermore, we present several techniques to accelerate the convergence to the optimal solution. Simulation results demonstrate the effectiveness of our proposed algorithm.
Complex network analysis of time series
Gao, Zhong-Ke; Small, Michael; Kurths, Jürgen
2016-12-01
Revealing complicated behaviors from time series constitutes a fundamental problem of continuing interest and it has attracted a great deal of attention from a wide variety of fields on account of its significant importance. The past decade has witnessed a rapid development of complex network studies, which allow to characterize many types of systems in nature and technology that contain a large number of components interacting with each other in a complicated manner. Recently, the complex network theory has been incorporated into the analysis of time series and fruitful achievements have been obtained. Complex network analysis of time series opens up new venues to address interdisciplinary challenges in climate dynamics, multiphase flow, brain functions, ECG dynamics, economics and traffic systems.
Complex Network Characteristics and Invulnerability Simulating Analysis of Supply Chain
Hui-Huang Chen; Ai-Min Lin
2012-01-01
To study the characteristics of the complex supply chain, a invulnerability analysis method based on the complex network theory is proposed. The topological structure and dynamic characteristics of the complex supply chain network were analyzed. The fact was found that the network is with general characteristics of the complex network, and with the characteristics of small-world network and scale-free network. A simulation experiment was made on the invulnerability of the supply chain network...
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.
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.
Link-space formalism for network analysis.
Smith, David M D; Lee, Chiu Fan; Onnela, Jukka-Pekka; Johnson, Neil F
2008-03-01
We introduce the link-space formalism for analyzing network models with degree-degree correlations. The formalism is based on a statistical description of the fraction of links l(i,j) connecting nodes of degrees i and j. To demonstrate its use, we apply the framework to some pedagogical network models, namely, random attachment, Barabási-Albert preferential attachment, and the classical Erdos and Rényi random graph. For these three models the link-space matrix can be solved analytically. We apply the formalism to a simple one-parameter growing network model whose numerical solution exemplifies the effect of degree-degree correlations for the resulting degree distribution. We also employ the formalism to derive the degree distributions of two very simple network decay models, more specifically, that of random link deletion and random node deletion. The formalism allows detailed analysis of the correlations within networks and we also employ it to derive the form of a perfectly nonassortative network for arbitrary degree distribution.
Theoretical analysis of single molecule spectroscopy lineshapes of conjugated polymers
Devi, Murali
Conjugated Polymers(CPs) exhibit a wide range of highly tunable optical properties. Quantitative and detailed understanding of the nature of excitons responsible for such a rich optical behavior has significant implications for better utilization of CPs for more efficient plastic solar cells and other novel optoelectronic devices. In general, samples of CPs are plagued with substantial inhomogeneous broadening due to various sources of disorder. Single molecule emission spectroscopy (SMES) offers a unique opportunity to investigate the energetics and dynamics of excitons and their interactions with phonon modes. The major subject of the present thesis is to analyze and understand room temperature SMES lineshapes for a particular CP, called poly(2,5-di-(2'-ethylhexyloxy)-1,4-phenylenevinylene) (DEH-PPV). A minimal quantum mechanical model of a two-level system coupled to a Brownian oscillator bath is utilized. The main objective is to identify the set of model parameters best fitting a SMES lineshape for each of about 200 samples of DEH-PPV, from which new insight into the nature of exciton-bath coupling can be gained. This project also entails developing a reliable computational methodology for quantum mechanical modeling of spectral lineshapes in general. Well-known optimization techniques such as gradient descent, genetic algorithms, and heuristic searches have been tested, employing an L2 measure between theoretical and experimental lineshapes for guiding the optimization. However, all of these tend to result in theoretical lineshapes qualitatively different from experimental ones. This is attributed to the ruggedness of the parameter space and inadequateness of the L2 measure. On the other hand, when the dynamic reduction of the original parameter space to a 2-parameter space through feature searching and visualization of the search space paths using directed acyclic graphs(DAGs), the qualitative nature of the fitting improved significantly. For a more
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.
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...
Bistability Analysis of Excitatory-Inhibitory Neural Networks in Limited-Sustained-Activity Regime
Institute of Scientific and Technical Information of China (English)
倪赟; 吴亮; 吴丹; 朱士群
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.
Graph theory and stability analysis of protein complex interaction networks.
Huang, Chien-Hung; Chen, Teng-Hung; Ng, Ka-Lok
2016-04-01
Protein complexes play an essential role in many biological processes. Complexes can interact with other complexes to form protein complex interaction network (PCIN) that involves in important cellular processes. There are relatively few studies on examining the interaction topology among protein complexes; and little is known about the stability of PCIN under perturbations. We employed graph theoretical approach to reveal hidden properties and features of four species PCINs. Two main issues are addressed, (i) the global and local network topological properties, and (ii) the stability of the networks under 12 types of perturbations. According to the topological parameter classification, we identified some critical protein complexes and validated that the topological analysis approach could provide meaningful biological interpretations of the protein complex systems. Through the Kolmogorov-Smimov test, we showed that local topological parameters are good indicators to characterise the structure of PCINs. We further demonstrated the effectiveness of the current approach by performing the scalability and data normalization tests. To measure the robustness of PCINs, we proposed to consider eight topological-based perturbations, which are specifically applicable in scenarios of targeted, sustained attacks. We found that the degree-based, betweenness-based and brokering-coefficient-based perturbations have the largest effect on network stability.
Theoretical analysis of high-resolution digital mammography.
Suryanarayanan, Sankararaman; Karellas, Andrew; Vedantham, Srinivasan; Sechopoulos, Ioannis
2006-06-21
The performance of a high-resolution charge coupled device-based full-field digital mammography imager was analysed using a mathematical framework based on an adaptation of cascaded linear systems theory described by other investigators. This work has been conducted in order to understand the impact of various design parameters on the physical performance characteristics of the imager. Specifically, the effect of pixel size, scintillator thickness and packing density, x-ray spectra, air kerma, dark current, charge integration time, and pixel fill-factor on the frequency dependent detective quantum efficiency was studied using a charge-coupled device as a reference platform. The imaging system was modelled as a series of physical processes with gain and spatial spreading. For each stage, the signal and noise power spectra were computed and propagated through the imaging chain as inputs to subsequent stages. Good agreement between experimental and theoretical predictions was obtained for various x-ray spectral conditions that were investigated. The modulation transfer function, MTF(f) and detective quantum efficiency DQE(f) characteristics obtained in this study are encouraging and comparable to other digital mammography systems. The results of this study strongly suggest the feasibility of large area scintillator-based digital mammography imagers with pixel sizes below 100 microm.
THEORETICAL ANALYSIS OF THE STABILITY OF A DEEP ROADWAY
Institute of Scientific and Technical Information of China (English)
付国彬
1995-01-01
In this paper the thickness of a broken zone, a state parameter of roadway surrounding rock, is used as the index to evaluate the stability of surrounding rock of a deep roadway. The paper gives a theoretic formula for calculating the thickness of the broken zone. The author points out that not only the ultimate strength of rockmass but its residual strength and strain-softening level all have a great influence on the stability of surrounding rock of a deep roadway. The peper′s results show that to reinforce surrounding rock, raise its residual strength and lower its strain-softening level should be taken as a basic requirement for supports of a deep roadway. In addition, the research also indicates that it is impossible for roadway supports to change surrounding rock states of a deep roadway, so it is certain for them to work in a broken state. For this reason, a sufficient yieldable quantity is necessary for roadway supports used in deep mining.
Theoretical limits on detection and analysis of small earthquakes
Kwiatek, Grzegorz; Ben-Zion, Yehuda
2016-08-01
We investigate theoretical limits on detection and reliable estimates of source characteristics of small earthquakes using synthetic seismograms for shear/tensile dislocations on kinematic circular ruptures and observed seismic noise and properties of several acquisition systems (instrument response, sampling rate). Simulated source time functions for shear/tensile dislocation events with different magnitudes, static stress drops, and rupture velocities provide estimates for the amplitude and frequency content of P and S phases at various observation angles. The source time functions are convolved with a Green's function for a homogenous solid assuming given P, S wave velocities and attenuation coefficients and a given instrument response. The synthetic waveforms are superposed with average levels of the observed ambient seismic noise up to 1 kHz. The combined seismograms are used to calculate signal-to-noise ratios and expected frequency content of P and S phases at various locations. The synthetic simulations of signal-to-noise ratio reproduce observed ratios extracted from several well-recorded data sets. The results provide guidelines on detection of small events in various geological environments, along with information relevant to reliable analyses of earthquake source properties.
Income distribution dependence of poverty measure: A theoretical analysis
Chattopadhyay, Amit K.; Mallick, Sushanta K.
2007-04-01
Using a modified deprivation (or poverty) function, in this paper, we theoretically study the changes in poverty with respect to the ‘global’ mean and variance of the income distribution using Indian survey data. We show that when the income obeys a log-normal distribution, a rising mean income generally indicates a reduction in poverty while an increase in the variance of the income distribution increases poverty. This altruistic view for a developing economy, however, is not tenable anymore once the poverty index is found to follow a pareto distribution. Here although a rising mean income indicates a reduction in poverty, due to the presence of an inflexion point in the poverty function, there is a critical value of the variance below which poverty decreases with increasing variance while beyond this value, poverty undergoes a steep increase followed by a decrease with respect to higher variance. Identifying this inflexion point as the poverty line, we show that the pareto poverty function satisfies all three standard axioms of a poverty index [N.C. Kakwani, Econometrica 43 (1980) 437; A.K. Sen, Econometrica 44 (1976) 219] whereas the log-normal distribution falls short of this requisite. Following these results, we make quantitative predictions to correlate a developing with a developed economy.
Fuzzy set theoretic approach to fault tree analysis
African Journals Online (AJOL)
user
Research in conventional fault tree analysis (FTA) is based mainly on failure ... Thus for a very complex system having large number of components, the ..... Smaller, the triangular fuzzy number B-Ai, will result in the best approximation for B.
Theoretical and methodological analysis of personality theories of leadership
Directory of Open Access Journals (Sweden)
Оксана Григорівна Гуменюк
2016-10-01
Full Text Available 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
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....
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....
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.
Graph theoretical analysis of brain connectivity in phantom sound perception.
Mohan, Anusha; De Ridder, Dirk; Vanneste, Sven
2016-02-02
Tinnitus is a phantom sound commonly thought of to be produced by the brain related to auditory deafferentation. The current study applies concepts from graph theory to investigate the differences in lagged phase functional connectivity using the average resting state EEG of 311 tinnitus patients and 256 healthy controls. The primary finding of the study was a significant increase in connectivity in beta and gamma oscillations and a significant reduction in connectivity in the lower frequencies for the tinnitus group. There also seems to be parallel processing of long-distance information between delta, theta, alpha1 and gamma frequency bands that is significantly stronger in the tinnitus group. While the network reorganizes into a more regular topology in the low frequency carrier oscillations, development of a more random topology is witnessed in the high frequency oscillations. In summary, tinnitus can be regarded as a maladaptive 'disconnection' syndrome, which tries to both stabilize into a regular topology and broadcast the presence of a deafferentation-based bottom-up prediction error as a result of a top-down prediction.
2016-12-22
self-organized industrial symbiosis networks: an agent- based simulation study," Journal of Cleaner Production , vol. 112, pp. 4353- 4366, 2016. 104...networks: a complex adaptive systems perspective," International Journal of Production Research 43.20, pp. 4235-4265, 2005. [4] P. Anderson...34 International Journal of Production Economics 124.2, pp. 310-330, 2010. [24] S. D. Pathak, J. M. Day, A. Nair, W. J. Sawaya and M. M. Kristal
Calculation and Analysis of Destination Buffer for Multimedia Service in Mobile Ad Hoc Network
Institute of Scientific and Technical Information of China (English)
ZHOU Zhong; MAO Yu-ming; JIANG Zhi-qong
2005-01-01
Jitter is one of the most important issues for multimedia real time services in future mobile ad hoc networks(MANET). A thorough theoretical analysis of the destination buffer for smoothing the jitter of the real time service in MANET is given. The theoretical results are applied in moderate populated ad hoc networks in our simulation, the simulation results show that by predicting and adjusting destination buffer in our way, Jitter will be alleviated in large part and this will contribute much to the quality of service (QOS) in MANET.
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
Historical Network Analysis of the Web
DEFF Research Database (Denmark)
Brügger, Niels
2013-01-01
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...... at the Danish parliamentary elections in 2011, 2007, and 2001. As the Internet grows older historical studies of networks on the web will probably become more widespread and therefore it may be about time to begin debating the methodological challenges within this emerging field....
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.
Theoretical performance analysis for CMOS based high resolution detectors.
Jain, Amit; Bednarek, Daniel R; Rudin, Stephen
2013-03-06
High resolution imaging capabilities are essential for accurately guiding successful endovascular interventional procedures. Present x-ray imaging detectors are not always adequate due to their inherent limitations. The newly-developed high-resolution micro-angiographic fluoroscope (MAF-CCD) detector has demonstrated excellent clinical image quality; however, further improvement in performance and physical design may be possible using CMOS sensors. We have thus calculated the theoretical performance of two proposed CMOS detectors which may be used as a successor to the MAF. The proposed detectors have a 300 μm thick HL-type CsI phosphor, a 50 μm-pixel CMOS sensor with and without a variable gain light image intensifier (LII), and are designated MAF-CMOS-LII and MAF-CMOS, respectively. For the performance evaluation, linear cascade modeling was used. The detector imaging chains were divided into individual stages characterized by one of the basic processes (quantum gain, binomial selection, stochastic and deterministic blurring, additive noise). Ranges of readout noise and exposure were used to calculate the detectors' MTF and DQE. The MAF-CMOS showed slightly better MTF than the MAF-CMOS-LII, but the MAF-CMOS-LII showed far better DQE, especially for lower exposures. The proposed detectors can have improved MTF and DQE compared with the present high resolution MAF detector. The performance of the MAF-CMOS is excellent for the angiography exposure range; however it is limited at fluoroscopic levels due to additive instrumentation noise. The MAF-CMOS-LII, having the advantage of the variable LII gain, can overcome the noise limitation and hence may perform exceptionally for the full range of required exposures; however, it is more complex and hence more expensive.
Theoretical performance analysis of multislice channelized Hotelling observers
Goossens, Bart; Platiša, Ljiljana; Philips, Wilfried
2012-02-01
Quality assessment of 3D medical images is becoming increasingly important, because of clinical practice rapidly moving in the direction of volumetric imaging. In a recent publication, three multi-slice channelized Hotelling observer (msCHO) models are presented for the task of detecting 3D signals in multi-slice images, where each multi-slice image is inspected in a so called stack-browsing mode. The observer models are based on the assumption that humans observe multi-slice images in a simple two stage process, and each of the models implement this principle in a different way. In this paper, we investigate the theoretical performance, in terms of detection signal-to-noise-ratio (SNR) of msCHO models, for the task of detecting a separable signal in a Gaussian background with separable covariance matrix. We find that, despite the differences in architecture of the three models, they all have the same asymptotical performance in this task (i.e., when the number of training images tends to infinity). On the other hand, when backgrounds with nonseparable covariance matrices are considered, the third model, msCHOc, is expected to perform slightly better than the other msCHO models (msCHOa and msCHOb), but only when sufficient training images are provided. These findings suggest that the choice between the msCHO models mainly depends on the experiment setup (e.g., the number of available training samples), while the relation to human observers depends on the particular choice of the "temporal" channels that the msCHO models use.
Information Theoretic Measures to Infer Feedback Dynamics in Coupled Logistic Networks
Directory of Open Access Journals (Sweden)
Allison Goodwell
2015-10-01
Full Text Available A process network is a collection of interacting time series nodes, in which interactions can range from weak dependencies to complete synchronization. Between these extremes, nodes may respond to each other or external forcing at certain time scales and strengths. Identification of such dependencies from time series can reveal the complex behavior of the system as a whole. Since observed time series datasets are often limited in length, robust measures are needed to quantify strengths and time scales of interactions and their unique contributions to the whole system behavior. We generate coupled chaotic logistic networks with a range of connectivity structures, time scales, noise, and forcing mechanisms, and compute variance and lagged mutual information measures to evaluate how detected time dependencies reveal system behavior. When a target node is detected to receive information from multiple sources, we compute conditional mutual information and total shared information between each source node pair to identify unique or redundant sources. While variance measures capture synchronization trends, combinations of information measures provide further distinctions regarding drivers, redundancies, and time dependencies within the network. We find that imposed network connectivity often leads to induced feedback that is identified as redundant links, and cannot be distinguished from imposed causal linkages. We find that random or external driving nodes are more likely to provide unique information than mutually dependent nodes in a highly connected network. In process networks constructed from observed data, the methods presented can be used to infer connectivity, dominant interactions, and systemic behavioral shift.
A Game-Theoretic Response Strategy for Coordinator Attack in Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Jianhua Liu
2014-01-01
Full Text Available 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.
A game-theoretic response strategy for coordinator attack in wireless sensor networks.
Liu, Jianhua; Yue, Guangxue; Shen, Shigen; 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.
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
Discriminating topology in galaxy distributions using network analysis
Hong, Sungryong; Coutinho, Bruno C.; Dey, Arjun; Barabási, Albert-L.; Vogelsberger, Mark; Hernquist, Lars; Gebhardt, Karl
2016-07-01
The large-scale distribution of galaxies is generally analysed using the two-point correlation function. However, this statistic does not capture the topology of the distribution, and it is necessary to resort to higher order correlations to break degeneracies. We demonstrate that an alternate approach using network analysis can discriminate between topologically different distributions that have similar two-point correlations. We investigate two galaxy point distributions, one produced by a cosmological simulation and the other by a Lévy walk. For the cosmological simulation, we adopt the redshift z = 0.58 slice from Illustris and select galaxies with stellar masses greater than 108 M⊙. The two-point correlation function of these simulated galaxies follows a single power law, ξ(r) ˜ r-1.5. Then, we generate Lévy walks matching the correlation function and abundance with the simulated galaxies. We find that, while the two simulated galaxy point distributions have the same abundance and two-point correlation function, their spatial distributions are very different; most prominently, filamentary structures, absent in Lévy fractals. To quantify these missing topologies, we adopt network analysis tools and measure diameter, giant component, and transitivity from networks built by a conventional friends-of-friends recipe with various linking lengths. Unlike the abundance and two-point correlation function, these network quantities reveal a clear separation between the two simulated distributions; therefore, the galaxy distribution simulated by Illustris is not a Lévy fractal quantitatively. We find that the described network quantities offer an efficient tool for discriminating topologies and for comparing observed and theoretical distributions.
Kolleck, Nina
2016-01-01
This paper examines the implementation of Education for Sustainable Development (ESD) in Germany and explores the possibilities of Social Network Analysis (SNA) for uncovering influential actors in educational policy innovation processes. From the theoretical perspective, an actor's influence is inferred from its relative position within…
Finite-time analysis of global projective synchronization on coloured networks
Indian Academy of Sciences (India)
Cai Guoliang; Jiang Shengqin; Cai Shuiming; Tian Lixin
2016-03-01
A novel finite-time analysis is given to investigate the global projective synchronization on coloured networks. Some less conservative conditions are derived by utilizing finite-time control techniques and Lyapunov stability theorem. In addition, two illustrative numerical simulations are provided to verify the effectiveness of the proposed theoretical results.
Directory of Open Access Journals (Sweden)
Borkowski Andrzej
2015-12-01
Full Text Available The paper presents a summary of research activities concerning theoretical geodesy performed in Poland in the period of 2011-2014. It contains the results of research on new methods of the parameter estimation, a study on robustness properties of the M-estimation, control network and deformation analysis, and geodetic time series analysis. The main achievements in the geodetic parameter estimation involve a new model of the M-estimation with probabilistic models of geodetic observations, a new Shift-Msplit estimation, which allows to estimate a vector of parameter differences and the Shift-Msplit(+ that is a generalisation of Shift-Msplit estimation if the design matrix A of a functional model has not a full column rank. The new algorithms of the coordinates conversion between the Cartesian and geodetic coordinates, both on the rotational and triaxial ellipsoid can be mentioned as a highlights of the research of the last four years. New parameter estimation models developed have been adopted and successfully applied to the control network and deformation analysis.
Borkowski, Andrzej; Kosek, Wiesław
2015-12-01
The paper presents a summary of research activities concerning theoretical geodesy performed in Poland in the period of 2011-2014. It contains the results of research on new methods of the parameter estimation, a study on robustness properties of the M-estimation, control network and deformation analysis, and geodetic time series analysis. The main achievements in the geodetic parameter estimation involve a new model of the M-estimation with probabilistic models of geodetic observations, a new Shift-Msplit estimation, which allows to estimate a vector of parameter differences and the Shift-Msplit(+) that is a generalisation of Shift-Msplit estimation if the design matrix A of a functional model has not a full column rank. The new algorithms of the coordinates conversion between the Cartesian and geodetic coordinates, both on the rotational and triaxial ellipsoid can be mentioned as a highlights of the research of the last four years. New parameter estimation models developed have been adopted and successfully applied to the control network and deformation analysis. New algorithms based on the wavelet, Fourier and Hilbert transforms were applied to find time-frequency characteristics of geodetic and geophysical time series as well as time-frequency relations between them. Statistical properties of these time series are also presented using different statistical tests as well as 2nd, 3rd and 4th moments about the mean. The new forecasts methods are presented which enable prediction of the considered time series in different frequency bands.
Nonlinear Analysis of Experimental Measurements 7.6. Theoretical Chemistry
2015-01-26
manuscript under consideration in Biophysical Journal. d) Coherent energy transfer in photosynthetic light -harvesting systems In photosynthesis ...Menten equation for enzymatic reactions ; (b) counting statistics of single molecule reaction trajectories and single cell microarray data (c) analysis...of cytoadhesion and binding kinetics experiments; and (d) optimization of coherent energy transfer in photosynthetic light -harvesting systems. The
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…
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…
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...
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
Micro-macro analysis of complex networks.
Marchiori, Massimo; Possamai, Lino
2015-01-01
Complex systems have attracted considerable interest because of their wide range of applications, and are often studied via a "classic" approach: study a specific system, find a complex network behind it, and analyze the corresponding properties. This simple methodology has produced a great deal of interesting results, but relies on an often implicit underlying assumption: the level of detail on which the system is observed. However, in many situations, physical or abstract, the level of detail can be one out of many, and might also depend on intrinsic limitations in viewing the data with a different level of abstraction or precision. So, a fundamental question arises: do properties of a network depend on its level of observability, or are they invariant? If there is a dependence, then an apparently correct network modeling could in fact just be a bad approximation of the true behavior of a complex system. In order to answer this question, we propose a novel micro-macro analysis of complex systems that quantitatively describes how the structure of complex networks varies as a function of the detail level. To this extent, we have developed a new telescopic algorithm that abstracts from the local properties of a system and reconstructs the original structure according to a fuzziness level. This way we can study what happens when passing from a fine level of detail ("micro") to a different scale level ("macro"), and analyze the corresponding behavior in this transition, obtaining a deeper spectrum analysis. The obtained results show that many important properties are not universally invariant with respect to the level of detail, but instead strongly depend on the specific level on which a network is observed. Therefore, caution should be taken in every situation where a complex network is considered, if its context allows for different levels of observability.
Experiment and Theoretical Analysis Study of ETFE Inflatable Tubes
Directory of Open Access Journals (Sweden)
YanLi He
2014-01-01
Full Text Available The load bearing capacity of an ETFE (ethylene-tetra-fluoro-ethylene inflatable tube is tested in this paper, and a comparative study of two wrinkling theories, the bifurcation theory and the tension field theory, is carried out for wrinkling analysis of the ETFE inflatable tube. Results obtained from the bifurcation theory and experiment reveal the limitations of tension field theory on the wrinkling analysis. The load-displacement curves of inflatable beams under bending load are obtained and compared with the experimental results; curves obtained using the bifurcation theory show coincidence with experimental curves, but the curves obtained using the tension field theory have noticeable deviations between calculated and experimental results.
O'Danleyman, Grastivia; Seebens, Hanno; Blasius, Bernd; Brockmann, Dirk
2011-01-01
We present a comparative network theoretic analysis of the two largest global transportation networks: The worldwide air-transportation network (WAN) and the global cargoship network (GCSN). We show that both networks exhibit striking statistical similarities despite significant differences in topology and connectivity. Both networks exhibit a discontinuity in node and link betweenness distributions which implies that these networks naturally segragate in two different classes of nodes and links. We introduce a technique based on effective distances, shortest paths and shortest-path trees for strongly weighted symmetric networks and show that in a shortest-path-tree representation the most significant features of both networks can be readily seen. We show that effective shortest-path distance, unlike conventional geographic distance measures, strongly correlates with node centrality measures. Using the new technique we show that network resilience can be investigated more precisely than with contemporary tech...
Directory of Open Access Journals (Sweden)
Hui-Jing Li
2014-03-01
Full Text Available Electrophilic aromatic bromination is the most common synthetic method used to prepare aryl bromides, which are very useful intermediates in organic synthesis. To understand the experimental results in electrophilic aromatic brominations, ab initio calculations are used here for a tentative analysis of the positional selectivity. The calculated results agree well with the corresponding experimental data, and the reliability of the resulting positional selectivity was verified by the corresponding experimental data.
THEORETICAL ANALYSIS OF THE CONCEPT OF INSURANCE PORTFOLIO OF INSURER
Kondratenko, D.
2014-01-01
The article is devoted to the analysis of the different interpretations of the concept of "portfolio insurance". The examples of the essence understanding of the “portfolio insurance'' concept from the different scholars point of view was examined from the perspective of the aggregate insurance risks and the number of contracts or assets incepted for the insurance. The functions and principles of the insurance portfoli were designated. It has been established that the current legislation does...
Dissecting Situational Strength: Theoretical Analysis and Empirical Tests
2012-09-01
approaches such as difference scores and profile similarity indices (see Edwards , 2007; Shanock, Baran, Gentry, Pattison, & Heggestad, 2010). In addition...and (2) via analysis of indirect, actual measures of fit through polynomial regression and response surfaces ( Edwards , 2007; Shanock et al., 2010...Thoresen, Bono , & Patton, 2001; see also Herman, 1973; Smith, 1977) suggests that job attitudes are related to job performance more strongly in situations
Game-Theoretic Approach for Solving Multiobjective Flow Problems on Networks
Directory of Open Access Journals (Sweden)
Maria A. Fonoberova
2005-10-01
Full Text Available The game-theoretic formulation of the multiobjective multicommodity flow problem is considered. The dynamic version of this problem is studied and an algorithm for its solving, based on the concept of multiobjective games, is proposed. Mathematics Subject Classification 2000: 90B10, 90C35, 90C27, 90C47.
Mukherjee, Amitav
2010-01-01
It is unrealistic to assume that all nodes in an ad hoc wireless network would be willing to participate in cooperative communication, especially if their desired Quality-of- Service (QoS) is achievable via direct transmission. An incentivebased auction mechanism is presented to induce cooperative behavior in wireless networks with emphasis on users with asymmetrical channel fading conditions. A single-object secondprice auction is studied for cooperative partner selection in singlecarrier networks. In addition, a multiple-object bundled auction is analyzed for the selection of multiple simultaneous partners in a cooperative orthogonal frequency-division multiplexing (OFDM) setting. For both cases, we characterize equilibrium outage probability performance, seller revenue, and feedback bounds. The auction-based partner selection allows winning bidders to achieve their desired QoS while compensating the seller who assists them. At the local level sellers aim for revenue maximization, while connections are draw...
Hydraulically interconnected vehicle suspension: theoretical and experimental ride analysis
Smith, Wade A.; Zhang, Nong; Jeyakumaran, Jeku
2010-01-01
In this paper, a previously derived model for the frequency-domain analysis of vehicles with hydraulically interconnected suspension (HIS) systems is applied to the ride analysis of a four-degrees of freedom roll-plane, half-car under a rough road input. The entire road surface is assumed to be a realisation of a two-dimensional Gaussian homogenous and isotropic random process. The frequency responses of the half-car, in terms of bounce and roll acceleration, suspension deflection and dynamic tyre forces, are obtained under the road input of a single profile represented by its power spectral density function. Simulation results obtained for the roll-plane half-car fitted with an HIS and those with conventional suspensions are compared in detail. In addition, sensitivity analysis of key parameters of the HIS to the ride performance is carried out through simulations. The paper also presents the experimental validation of the analytical results of the free and forced vibrations of the roll-plane half-car. The hydraulic and mechanical system layouts, data acquisition system and the external force actuation mechanism of the test set-up are described in detail. The methodology for free and forced vibration tests and the application of mathematical models to account for the effective damper valve pressure loss are explained. Results are provided for the free and forced vibration testing of the half-car with different mean operating pressures. Comparisons are also given between the test results and those obtained from the system model with estimated damper valve loss coefficients. Furthermore, discussions on the deficiencies and practical implications of the proposed model and suggestions for future investigation are provided. Finally, the key findings of the investigation on the ride performance of the roll-plane half-car are summarised.
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...
A network analysis of developing brain cultures
Christopoulos, V. N.; Boeff, D. V.; Evans, C. D.; Crowe, D. A.; Amirikian, B.; Georgopoulos, A.; Georgopoulos, A. P.
2012-08-01
We recorded electrical activity from four developing embryonic brain cultures (4-40 days in vitro) using multielectrode arrays (MEAs) with 60 embedded electrodes. Data were filtered for local field potentials (LFPs) and downsampled to 1 ms to yield a matrix of time series consisting of 60 electrode × 60 000 time samples per electrode per day per MEA. Each electrode time series was rendered stationary and nonautocorrelated by applying an ARIMA (25, 1, 1) model and taking the residuals (i.e. innovations). Two kinds of analyses were then performed. First, a pairwise crosscorrelation (CC) analysis (±25 1 ms lags) revealed systematic changes in CC with lag, day in vitro (DIV), and inter-electrode distance. Specifically, (i) positive CCs were 1.76× more prevalent and 1.44× stronger (absolute value) than negative ones, and (ii) the strength of CC increased with DIV and decreased with lag and inter-electrode distance. Second, a network equilibrium analysis was based on the instantaneous (1 ms resolution) logratio of the number of electrodes that were above or below their mean, called simultaneous departure from equilibrium, SDE. This measure possesses a major computational advantage over the pairwise crosscorrelation approach because it is very simple and fast to calculate, an important factor for the analysis of large networks. The results obtained with SDE covaried highly with CC over DIV, which further validates the usefulness of this measure as a computationally effective tool for large scale network analysis.
A user’s guide to network analysis in R
Luke, Douglas
2015-01-01
Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.
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.
Theoretical analysis of BLM system for HLS II
Yukai, Chen; Lijuan, He; Weimin, Li
2014-01-01
Hefei Light Source (HLS) is being upgraded to HLS II. Its emittance will be much lower than before, therefore the Touschek scattering will increase significantly and become the dominant factor of beam loss. So it is necessary to build a new beam loss monitoring (BLM) system differed from the old one to obtain the quantity and position information of lost electrons. This information is useful in the commissioning, troubleshooting and beam lifetime studying for HLS II. This paper analyzes the distribution features of different kinds of lost electrons, introduces the new machine's operation parameters and discusses the way to choose proper monitoring positions. Base on these comprehensive analysis, a new BLM system for HLS II is proposed.
Theoretical analysis and simulation of thermoelastic deformation of bimorph microbeams
Institute of Scientific and Technical Information of China (English)
SHANG; YuanFang; YE; XiongYing; FENG; JinYang
2013-01-01
In this paper, a purely mechanical model for the thermoelastic behavior of a bimorph microbeam is presented. The thermoelastic coupling problem of the microbeam is converted to a mechanical problem by simply replacing the thermal stress in the beam with a bulk force and a surface force. Thermoelastic deformation of the bimorph microbeams with constraints frequently used in micro-electro-mechanical systems (MEMS) devices has been derived based on this model and is characterized by FEA simulation. Coincidence of the results from theory and simulation demonstrates the validity of the model. The analysis shows that a bimorph microbeam with a soft constraint and a uniform temperature field has a larger thermoelastic deformation than that with a hard constraint and a linear temperature field. In addition to the adoption of materials with large CTE mismatch,thickness ratio and length ratio of the two layers need to be optimized to get a large thermoelastic deformation.
Motility of a model bristle-bot: A theoretical analysis
Cicconofri, Giancarlo; DeSimone, Antonio
2015-11-01
Bristle-bots are legged robots that can be easily made out of a toothbrush head and a small vibrating engine. Despite their simple appearance, the mechanism enabling them to propel themselves by exploiting friction with the substrate is far from trivial. Numerical experiments on a model bristle-bot have been able to reproduce such a mechanism revealing, in addition, the ability to switch direction of motion by varying the vibration frequency. This paper provides a detailed account of these phenomena through a fully analytical treatment of the model. The equations of motion are solved through an expansion in terms of a properly chosen small parameter. The convergence of the expansion is rigorously proven. In addition, the analysis delivers formulas for the average velocity of the robot and for the frequency at which the direction switch takes place. A quantitative description of the mechanism for the friction modulation underlying the motility of the bristle-bot is also provided.
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.
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 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. PMID:23569288
A Game Theoretical Interest Forwarding for Cached Data in Content-Centric Networking
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Chengming Li
Full Text Available Content-Centric Networking (CCN has recently emerged as a clean slate approach to rethink Internet foundations, which changes from host-centric communication model to contentcentric. It is common that the current router does not have all the information ...
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.
Corten, R.
2009-01-01
Social networks play an important role in explanations of outcomes of social dilemmas; situations in which goal-directed individual action can lead to a collectively suboptimal outcome. Among these dilemmas are the cooperation- and coordination problems that underlie many social phenomena. In most r
Introduction to stream network habitat analysis
Bartholow, John M.; Waddle, Terry J.
1986-01-01
Increasing demands on stream resources by a variety of users have resulted in an increased emphasis on studies that evaluate the cumulative effects of basinwide water management programs. Network habitat analysis refers to the evaluation of an entire river basin (or network) by predicting its habitat response to alternative management regimes. The analysis principally focuses on the biological and hydrological components of the riv er basin, which include both micro- and macrohabitat. (The terms micro- and macrohabitat are further defined and discussed later in this document.) Both conceptual and analytic models are frequently used for simplifying and integrating the various components of the basin. The model predictions can be used in developing management recommendations to preserve, restore, or enhance instream fish habitat. A network habitat analysis should begin with a clear and concise statement of the study objectives and a thorough understanding of the institutional setting in which the study results will be applied. This includes the legal, social, and political considerations inherent in any water management setting. The institutional environment may dictate the focus and level of detail required of the study to a far greater extent than the technical considerations. After the study objectives, including species on interest, and institutional setting are collectively defined, the technical aspects should be scoped to determine the spatial and temporal requirements of the analysis. A macro level approach should be taken first to identify critical biological elements and requirements. Next, habitat availability is quantified much as in a "standard" river segment analysis, with the likely incorporation of some macrohabitat components, such as stream temperature. Individual river segments may be aggregated to represent the networkwide habitat response of alternative water management schemes. Things learned about problems caused or opportunities generated may
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.
Inference and contradictory analysis for binary neural networks
Institute of Scientific and Technical Information of China (English)
郭宝龙; 郭雷
1996-01-01
A weak-inference theory and a contradictory analysis for binary neural networks (BNNs).are presented.The analysis indicates that the essential reason why a neural network is changing its slates is the existence of superior contradiction inside the network,and that the process by which a neural network seeks a solution corresponds to eliminating the superior contradiction.Different from general constraint satisfaction networks,the solutions found by BNNs may contain inferior contradiction but not superior contradiction.
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.
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 of Cell Load Coupling for LTE Network Planning and Optimization
Siomina, Iana
2012-01-01
System-centric modeling and analysis are of key significance in planning and optimizing cellular networks. In this paper, we provide a mathematical analysis of performance modeling for LTE networks. The system model characterizes the coupling relation between the cell load factors, taking into account non-uniform traffic demand and interference between the cells with arbitrary network topology. Solving the model enables a network-wide performance evaluation in resource consumption. We develop and prove both sufficient and necessary conditions for the feasibility of the load-coupling system, and provide results related to computational aspects for numerically approaching the solution. The theoretical findings are accompanied with experimental results to instructively illustrate the application in optimizing LTE network configuration.
Analysis of single-hop traffic grooming in mesh WDM optical networks
Xin, Chunsheng; Qiao, Chunming; Dixit, Sudhir
2003-10-01
Traffic grooming is a significant task in internetworking between an optical wavelength-routed core network that supplies "pipes" at the wavelength-granularity, and the attached client (e.g., IP) networks that usually require connections of sub-wavelength granularity. The focus of this study is to develop a theoretical performance analysis model for online traffic grooming in mesh optical networks. This paper first briefly discusses the difficulty in applying the analytic models developed for circuit-switched networks (including wavelength-routed optical networks) to the traffic grooming problem. It then develops a link blocking model based on the continuous time Markov chain and queueing theory, and finally conducts end-to-end performance analysis based on the Erlang fixed-point approximation. The results obtained from the analytic model are shown to match well with numerical results obtained from simulations.
Information-theoretic analysis of MIMO channel sounding
Baum, Daniel S
2007-01-01
The large majority of commercially available multiple-input multiple-output (MIMO) radio channel measurement devices (sounders) is based on time-division multiplexed switching (TDMS) of a single transmit/receive radio-frequency chain into the elements of a transmit/receive antenna array. While being cost-effective, such a solution can cause significant measurement errors due to phase noise and frequency offset in the local oscillators. In this paper, we systematically analyze the resulting errors and show that, in practice, overestimation of channel capacity by several hundred percent can occur. Overestimation is caused by phase noise (and to a lesser extent frequency offset) leading to an increase of the MIMO channel rank. Our analysis furthermore reveals that the impact of phase errors is, in general, most pronounced if the physical channel has low rank (typical for line-of-sight or poor scattering scenarios). The extreme case of a rank-1 physical channel is analyzed in detail. Finally, we present measureme...
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.
Multi-Objective Optimization and Analysis Model of Sintering Process Based on BP Neural Network
Institute of Scientific and Technical Information of China (English)
ZHANG Jun-hong; XIE An-guo; SHEN Feng-man
2007-01-01
A multi-objective optimization and analysis model of the sintering process based on BP neural network is presented. Genetic algorithms are combined to simplify the BP neural network, which can reduce the learning time and increase the forecasting accuracy of the network model. This model has been experimented in the sintering process, and the production cost, the energy consumption, the quality (revolving intensity), and the output are considered at the same time. Moreover, the relation between some factors and the multi-objectives has been analyzed, and the results are consistent with the process. Different objectives are emphasized at different practical periods, and this can provide a theoretical basis for the manager.
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.
Theoretical analysis of droplet transition from Cassie to Wenzel state
Institute of Scientific and Technical Information of China (English)
刘天庆; 李艳杰; 李香琴; 孙玮
2015-01-01
Whether droplets transit from the Cassie to the Wenzel state (C–W) on a textured surface is the touchstone that the superhydrophobicity of the surface is still maintained. However, the C–W transition mechanism, especially the spontaneous transition of small droplets, is still not very clear to date. The interface free energy gradient of a small droplet is firstly proposed and derived as the driving force for its C–W evolution in this study based on the energy and gradient analysis. Then the physical and mathematical model of the C–W transition is found after the C–W driving force or transition pressure, the resistance, and the parameters of the meniscus beneath the droplet are formulated. The results show that the micro/nano structural parameters significantly affect the C–W driving force and resistance. The smaller the pillar diameter and pitch, the minor the C–W transition pressure, and the larger the resistance. Consequently, the C–W transition is difficult to be completed for the droplets on nano-textured surfaces. Meanwhile if the posts are too short, the front of the curved liquid–air interface below the droplet will touch the structural substrate easily even though the three phase contact line (TPCL) has not depinned. When the posts are high enough, the TPCL beneath the drop must move firstly before the meniscus can reach the substrate. As a result, the droplet on a textured surface with short pillars is easy to complete its C–W evolution. On the other hand, the smaller the droplet, the easier the C–W shift, since the transition pressure becomes larger, which well explains why an evaporating drop will collapse spontaneously from composite to Wenzel state. Besides, both intrinsic and advancing contact angles affect the C–W transition as well. The greater the two angles, the harder the C–W transition. In the end, the C–W transition parameters and the critical conditions measured in literatures are calculated and compared, and the
Theoretical analysis of oxygen supply to contracted skeletal muscle.
Groebe, K; Thews, G
1986-01-01
Honig and collaborators reported striking contradictions in current understanding of O2 supply to working skeletal muscle. Therefore we re-examined the problem by means of a new composite computer simulation. As inclusion of erythrocytic O2 desaturation and oxygen transport and consumption inside the muscle cell into a single model would entail immense numerical difficulties, we broke up the whole process into its several components: O2 desaturation of erythrocytes O2 transport and consumption in muscle fiber capillary transit time characterizing the period of contact between red cell and muscle fiber. "Erythrocyte model" as well as "muscle fiber model" both consist of a central core cylinder surrounded by a concentric diffusion layer representing the extracellular resistance to O2 diffusion (Fig. 1). Resistance layers in both models are to be conceived of as one and the same anatomical structure--even though in each model their shape is adapted to the respective geometry. By means of this overlap region a spatial connexion between both is given, whereas temporal coherence governing O2 fluxes and red cell spacing is derived from capillary transit time. Analysis of individual components is outlined as follows: Assuming axial symmetry of the problem a numerical algorithm was employed to solve the parabolic system of partial differential equations describing red cell O2 desaturation. Hb-O2 reaction kinetics, free and facilitated O2 diffusion in axial and radial directions, and red cell movement in capillary were considered. Resulting time courses of desaturation, which are considerably faster than the ones computed by Honig et al., are given in the following table (see also Fig. 3). (Formula: see text) Furthermore, we studied the respective importance of the several processes included in our model: Omission of longitudinal diffusion increased desaturation time by 15% to 23%, whereas effects of reaction kinetics and axial movement were 5% and 2% respectively. For time
Kattan, Michael W.; Hess, Kenneth R.; Kattan, Michael W.
1998-01-01
New computationally intensive tools for medical survival analyses include recursive partitioning (also called CART) and artificial neural networks. A challenge that remains is to better understand the behavior of these techniques in effort to know when they will be effective tools. Theoretically they may overcome limitations of the traditional multivariable survival technique, the Cox proportional hazards regression model. Experiments were designed to test whether the new tools would, in practice, overcome these limitations. Two datasets in which theory suggests CART and the neural network should outperform the Cox model were selected. The first was a published leukemia dataset manipulated to have a strong interaction that CART should detect. The second was a published cirrhosis dataset with pronounced nonlinear effects that a neural network should fit. Repeated sampling of 50 training and testing subsets was applied to each technique. The concordance index C was calculated as a measure of predictive accuracy by each technique on the testing dataset. In the interaction dataset, CART outperformed Cox (P less than 0.05) with a C improvement of 0.1 (95% Cl, 0.08 to 0.12). In the nonlinear dataset, the neural network outperformed the Cox model (P less than 0.05), but by a very slight amount (0.015). As predicted by theory, CART and the neural network were able to overcome limitations of the Cox model. Experiments like these are important to increase our understanding of when one of these new techniques will outperform the standard Cox model. Further research is necessary to predict which technique will do best a priori and to assess the magnitude of superiority.
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.
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.
Physical Layer Security Jamming: Theoretical Limits and Practical Designs in Wireless Networks
Cumanan, Kanapathippillai; Xing, Hong; Xu, Peng; Zheng, Gan; Dai, Xuchu; Nallanathan, Arumugam; Ding, Zhiguo; Karagiannidis, George K.
2016-01-01
Physical layer security has been recently recognizedas a promising new design paradigm to provide security inwireless networks. In addition to the existing conventional cryp-tographic methods, physical layer security exploits the dynamicsof fading channels to enhance secured wireless links. In thisapproach, jamming plays a key role by generating noise signalsto confuse the potential eavesdroppers, and significantly improvesquality and reliability of secure communications between legitimate te...
Physical Layer Security Jamming: Theoretical Limits and Practical Designs in Wireless Networks
Cumanan, Kanapathippillai; Xing, Hong; Xu, Peng; Zheng, Gan; Dai, Xuchu; Nallanathan, Arumugam; Ding, Zhiguo; Karagiannidis, George K.
2017-01-01
Physical layer security has been recently recognized as a promising new design paradigm to provide security in wireless networks. In addition to the existing conventional cryptographic methods, physical layer security exploits the dynamics of fading channels to enhance secured wireless links. In this approach, jamming plays a key role by generating noise signals to confuse the potential eavesdroppers, and significantly improves quality and reliability of secure communications between legitima...
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.
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 CO
Communicating oscillatory networks: frequency domain analysis
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Ihekwaba Adaoha EC
2011-12-01
Full Text Available Abstract Background Constructing predictive dynamic models of interacting signalling networks remains one of the great challenges facing systems biology. While detailed dynamical data exists about individual pathways, the task of combining such data without further lengthy experimentation is highly nontrivial. The communicating links between pathways, implicitly assumed to be unimportant and thus excluded, are precisely what become important in the larger system and must be reinstated. To maintain the delicate phase relationships between signals, signalling networks demand accurate dynamical parameters, but parameters optimised in isolation and under varying conditions are unlikely to remain optimal when combined. The computational burden of estimating parameters increases exponentially with increasing system size, so it is crucial to find precise and efficient ways of measuring the behaviour of systems, in order to re-use existing work. Results Motivated by the above, we present a new frequency domain-based systematic analysis technique that attempts to address the challenge of network assembly by defining a rigorous means to quantify the behaviour of stochastic systems. As our focus we construct a novel coupled oscillatory model of p53, NF-kB and the mammalian cell cycle, based on recent experimentally verified mathematical models. Informed by online databases of protein networks and interactions, we distilled their key elements into simplified models containing the most significant parts. Having coupled these systems, we constructed stochastic models for use in our frequency domain analysis. We used our new technique to investigate the crosstalk between the components of our model and measure the efficacy of certain network-based heuristic measures. Conclusions We find that the interactions between the networks we study are highly complex and not intuitive: (i points of maximum perturbation do not necessarily correspond to points of maximum
Integrated Adaptive Analysis and Visualization of Satellite Network Data Project
National Aeronautics and Space Administration — We propose to develop a system that enables integrated and adaptive analysis and visualization of satellite network management data. Integrated analysis and...
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 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
From 1D chain to 3D network: A theoretical study on TiO{sub 2} low dimensional structures
Energy Technology Data Exchange (ETDEWEB)
Guo, Ling-ju; He, Tao, E-mail: het@nanoctr.cn [CAS Laboratory of Nanosystem and Hierarchical Fabrication, National Center for Nanoscience and Technology, Beijing 100190 (China); Zeng, Zhi [Chinese Academy of Sciences, Institute of Solid State Physics, Hefei 230031 (China)
2015-06-14
We have performed a systematic study on a series of low dimensional TiO{sub 2} nanostructures under density functional theory methods. The geometries, stabilities, growth mechanism, and electronic structures of 1D chain, 2D ring, 2D ring array, and 3D network of TiO{sub 2} nanostructures are analyzed. Based on the Ti{sub 2}O{sub 4} building unit, a series of 1D TiO{sub 2} nano chains and rings can be built. Furthermore, 2D ring array and 3D network nanostructures can be constructed from 1D chains and rings. Among non-periodic TiO{sub 2} chain and ring structures, one series of ring structures is found to be more stable. The geometry model of the 2D ring arrays and 3D network structures in this work has provided a theoretical understanding on the structure information in experiments. Based on these semiconductive low dimensional structures, moreover, it can help to understand and design new hierarchical TiO{sub 2} nanostructure in the future.
Design Criteria For Networked Image Analysis System
Reader, Cliff; Nitteberg, Alan
1982-01-01
Image systems design is currently undergoing a metamorphosis from the conventional computing systems of the past into a new generation of special purpose designs. This change is motivated by several factors, notably among which is the increased opportunity for high performance with low cost offered by advances in semiconductor technology. Another key issue is a maturing in understanding of problems and the applicability of digital processing techniques. These factors allow the design of cost-effective systems that are functionally dedicated to specific applications and used in a utilitarian fashion. Following an overview of the above stated issues, the paper presents a top-down approach to the design of networked image analysis systems. The requirements for such a system are presented, with orientation toward the hospital environment. The three main areas are image data base management, viewing of image data and image data processing. This is followed by a survey of the current state of the art, covering image display systems, data base techniques, communications networks and software systems control. The paper concludes with a description of the functional subystems and architectural framework for networked image analysis in a production environment.
Simultaneity Analysis In A Wireless Sensor Network
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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.
A Theoretical Analysis of Potential Extinction Properties of Behavior-Specific Manual Restraint
Cipani, Ennio; Thomas, Melvin; Martin, Daniel
2007-01-01
This paper will examine possible extinction properties of behavior-specific manual restraint. It will analyze the possibility of extinction being produced via restraint with respect to the target behavior's possible environmental functions. The theoretical analysis will involve the analysis of behavioral properties of restraint during two temporal…
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…
Brain network analysis of EEG functional connectivity during imagery hand movements.
Demuru, Matteo; Fara, Francesca; Fraschini, Matteo
2013-12-01
The characterization of human neural activity during imaginary movement tasks represent an important challenge in order to develop effective applications that allow the control of a machine. Yet methods based on brain network analysis of functional connectivity have been scarcely investigated. As a result we use graph theoretic methods to investigate the functional connectivity and brain network measures in order to characterize imagery hand movements in a set of healthy subjects. The results of the present study show that functional connectivity analysis and minimum spanning tree (MST) parameters allow to successfully discriminate between imagery hand movements (both right and left) and resting state conditions. In conclusion, this paper shows that brain network analysis of EEG functional connectivity could represent an efficient alternative to more classical local activation based approaches. Furthermore, it also suggests the shift toward methods based on the characterization of a limited set of fundamental functional connections that disclose salient network topological features.
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.
Expert Network for Die Casing Defect Analysis
Institute of Scientific and Technical Information of China (English)
Jiadi WANG; Yongfeng JIANG; Chen LU; Wenjiang DING
2003-01-01
Due to the competition and high cost associated with die casting defects, it is urgent to adopt a rapid and effective method for defect analysis. In this research, a novel expert network approach was proposed to avoid some disadvantages of rulebased expert system. The main objective of the system is to assist die casting engineer in identifying defect, determining the probable causes of defect and proposing remedies to eliminate the defect. 14 common die casting defects could be identified quickly by expert system on the basis of their characteristics. BP neural network in combination with expert system was applied to map the complex relationship between causes and defects, and further explained the cause determination process.Cause determination gives due consideration to practical process conditions. Finally, corrective measures were recommended to eliminate the defect and implemented in the sequence of difficulty.
Integrative bayesian network analysis of genomic data.
Ni, Yang; Stingo, Francesco C; Baladandayuthapani, Veerabhadran
2014-01-01
Rapid development of genome-wide profiling technologies has made it possible to conduct integrative analysis on genomic data from multiple platforms. In this study, we develop a novel integrative Bayesian network approach to investigate the relationships between genetic and epigenetic alterations as well as how these mutations affect a patient's clinical outcome. We take a Bayesian network approach that admits a convenient decomposition of the joint distribution into local distributions. Exploiting the prior biological knowledge about regulatory mechanisms, we model each local distribution as linear regressions. This allows us to analyze multi-platform genome-wide data in a computationally efficient manner. We illustrate the performance of our approach through simulation studies. Our methods are motivated by and applied to a multi-platform glioblastoma dataset, from which we reveal several biologically relevant relationships that have been validated in the literature as well as new genes that could potentially be novel biomarkers for cancer progression.
Network analysis of online bidding activity
Yang, I.; Oh, E.; Kahng, B.
2006-07-01
With the advent of digital media, people are increasingly resorting to online channels for commercial transactions. The online auction is a prototypical example. In such online transactions, the pattern of bidding activity is more complex than traditional offline transactions; this is because the number of bidders participating in a given transaction is not bounded and the bidders can also easily respond to the bidding instantaneously. By using the recently developed network theory, we study the interaction patterns between bidders (items) who (that) are connected when they bid for the same item (if the item is bid by the same bidder). The resulting network is analyzed by using the hierarchical clustering algorithm, which is used for clustering analysis for expression data from DNA microarrays. A dendrogram is constructed for the item subcategories; this dendrogram is compared to a traditional classification scheme. The implication of the difference between the two is discussed.
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.
Network meta-analysis: an introduction for clinicians.
Rouse, Benjamin; Chaimani, Anna; Li, Tianjing
2017-02-01
Network meta-analysis is a technique for comparing multiple treatments simultaneously in a single analysis by combining direct and indirect evidence within a network of randomized controlled trials. Network meta-analysis may assist assessing the comparative effectiveness of different treatments regularly used in clinical practice and, therefore, has become attractive among clinicians. However, if proper caution is not taken in conducting and interpreting network meta-analysis, inferences might be biased. The aim of this paper is to illustrate the process of network meta-analysis with the aid of a working example on first-line medical treatment for primary open-angle glaucoma. We discuss the key assumption of network meta-analysis, as well as the unique considerations for developing appropriate research questions, conducting the literature search, abstracting data, performing qualitative and quantitative synthesis, presenting results, drawing conclusions, and reporting the findings in a network meta-analysis.
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.
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
Game Theoretical Power Control for Open-Loop Overlaid Network MIMO Systems with Partial Cooperation
Yu, Hao; Lau, Vincent K N
2010-01-01
Network MIMO is considered to be a key solution for the next generation wireless systems in breaking the interference bottleneck in cellular systems. In the MIMO systems, open-loop transmission scheme is used to support mobile stations (MSs) with high mobilities because the base stations (BSs) do not need to track the fast varying channel fading. In this paper, we consider an open-loop network MIMO system with $K$ BSs serving K private MSs and $M^c$ common MS based on a novel partial cooperation overlaying scheme. Exploiting the heterogeneous path gains between the private MSs and the common MSs, each of the $K$ BSs serves a private MS non-cooperatively and the $K$ BSs also serve the $M^c$ common MSs cooperatively. The proposed scheme does not require closed loop instantaneous channel state information feedback, which is highly desirable for high mobility users. Furthermore, we formulate the long-term distributive power allocation problem between the private MSs and the common MSs at each of the $K$ BSs using...
An Information-Theoretical View of Network-Aware Malware Attacks
Chen, Zesheng
2008-01-01
This work investigates three aspects: (a) a network vulnerability as the non-uniform vulnerable-host distribution, (b) threats, i.e., intelligent malwares that exploit such a vulnerability, and (c) defense, i.e., challenges for fighting the threats. We first study five large data sets and observe consistent clustered vulnerable-host distributions. We then present a new metric, referred to as the non-uniformity factor, which quantifies the unevenness of a vulnerable-host distribution. This metric is essentially the Renyi information entropy and better characterizes the non-uniformity of a distribution than the Shannon entropy. Next, we analyze the propagation speed of network-aware malwares in view of information theory. In particular, we draw a relationship between Renyi entropies and randomized epidemic malware-scanning algorithms. We find that the infection rates of malware-scanning methods are characterized by the Renyi entropies that relate to the information bits in a non-unform vulnerable-host distribut...
Schlüter, M; Kerschhaggl, O; Wagner, F
1999-08-01
We present a general performance measure (information loss) for associative memories based on information theoretical concepts. This performance measure can be estimated, provided that mean values of observables have been determined for the associative memory. Then the estimation guarantees a minimal association quality. The formalism allows the application of the performance measure to complex systems where the relation between input and output of the associative memory is not explicitly known. Here we apply our formalism to the Hopfield model and estimate the storage capacity alpha(c) from the numerically determined information loss. In contrast to other numerical methods the whole overlap distribution is taken into account. Our numerical value alpha(c)=0.1379(4) for the storage capacity in the Hopfield model is below numerical values obtained previously. This indicates that the consideration of small remnant overlaps lowers the storage capacity of the Hopfield model.
Indian Academy of Sciences (India)
Alfred Gierer
2002-06-01
The topic of this article is the relation between bottom-up and top-down, reductionist and ``holistic” approaches to the solution of basic biological problems. While there is no doubt that the laws of physics apply to all events in space and time, including the domains of life, understanding biology depends not only on elucidating the role of the molecules involved, but, to an increasing extent, on systems theoretical approaches in diverse fields of the life sciences. Examples discussed in this article are the generation of spatial patterns in development by the interplay of autocatalysis and lateral inhibition; the evolution of integrating capabilities of the human brain, such as cognition-based empathy; and both neurobiological and epistemological aspects of scientific theories of consciousness and the mind.
Pang, Y. F.
2016-08-01
The traditional limiting conditions have the biggest refrigeration quantity condition and the biggest refrigeration coefficient condition, there is a special operating mode during these conditions, enabling to both have the big refrigeration quantity and the small power loss, this operating mode is “Optimum condition”. This article first carried on the theoretical analysis to the semiconductor's optimum condition, inferred optimum electric current's theoretical formula; Carried on the experiment again to a semiconductor refrigeration box by regulating current changing operating mode, which had analyzed performance parameter's change situation under 8 kinds of condition experiments, carried on the regression analysis to the experimental data, obtained the regression equation thus discovered optimum electric current corresponding optimum condition. Carried on working under this condition, and then obtained the big refrigeration quantity and small power, which enhanced the refrigeration performance of semiconductor refrigerator. The experimental result and the theoretical analysis result tallied basically.
Tao, Fei; Guo, Hua; Zhang, Lin; Cheng, Ying
2012-11-01
Existing works on service composition are primarily based on the requirements of service composition, such as describing language supporting service composition, service composition framework, mechanism and method for service composition, and service composition validation. Few works have been carried out from the perspective of combinable relationship among composite services and composition service network. This article emphasises on combinable relationship-based composition service network, i.e. CoRCS-Net. The principles for establishing and modelling CoRCS-Net were studied, and nine combinable relationships among services in CoRCS-Net were investigated and 14 elementary evolving operators for CoRCS-Net dynamic evolution were designed. According to the definition of scale-free network (SFN) and the investigations on its related research achievements, it is supposed that 'CoRCS-Net is a scale-free network' in this study. In order to prove the theoretical hypothesis, the concepts of combinable strength and variation of combinable strength were introduced, and combinable strength is used to describe the invoking times of a service being invoked for service composition. First we calculate the real time variation of combinable strength of an arbitrary service in CoRCS-Net, and then obtain the corresponding real time combinable strength and investigate its distribution for all services in CoRCS-Net. It is discovered that 'like many nature and social phenomenon, CoRCS-Net is "scale-free", and it is constructed by few "active services" and a great deal of "silent services". In the process of service composition, the invoking times for majority services are very small, while only few services are invoked frequently, and the probability (or invoking times) for the services in a CoRCS-Net to be invoked for service composition decays as a power-law'.
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.
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.
Community-enhanced Network Representation Learning for Network Analysis
Tu, Cunchao; Zeng, Xiangkai; Liu, Zhiyuan; Sun, Maosong
2016-01-01
Network representation learning (NRL) aims to build low-dimensional vectors for vertices in a network. Most existing NRL methods focus on learning representations from local context of vertices (such as their neighbors). Nevertheless, vertices in many complex networks also exhibit significant global patterns widely known as communities. It's a common sense that vertices in the same community tend to connect densely, and usually share common attributes. These patterns are expected to improve NRL and benefit relevant evaluation tasks, such as link prediction and vertex classification. In this work, we propose a novel NRL model by introducing community information of vertices to learn more discriminative network representations, named as Community-enhanced Network Representation Learning (CNRL). CNRL simultaneously detects community distribution of each vertex and learns embeddings of both vertices and communities. In this way, we can obtain more informative representation of a vertex accompanying with its commu...
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.
Directory of Open Access Journals (Sweden)
Wei Zhang
2015-11-01
Full Text Available 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.
Theoretical analysis and experimental research on port/starboard discrimination in towed line array
Institute of Scientific and Technical Information of China (English)
DU Xuanmin; ZHU Daizhu; ZHAO Rongrong; YAO Lan
2001-01-01
The theoretical analysis and experimental research on Port/Starboard (P/S) discrimination in towed line array are proposed. Two methods resolving the P/S ambiguity with hydrophone triplets are introduced. By processing experimental data, the theoretical analysis is verified. The processing algorithm is extended to broadband signal. The research results show that the method based on optimum beamforming with triplets can be used to remove the port/starboard ambiguity. Also because of the simplicity of the method, it is expected to be implemented in practical towed line array sonar.
China ASON Network Migration Scenarios and Their Quantitative Analysis
Institute of Scientific and Technical Information of China (English)
Soichiro; Araki; Itaru; Nishioka; Yoshihiko; Suemura
2003-01-01
This paper proposes two migration scenarios from China ring networks to ASON mesh networks. In our quantitative analysis with ASON/GMPLS simulator, a subnetwork protection scheme achieved best balanced performance in resource utilization and restoration time.
China ASON Network Migration Scenarios and Their Quantitative Analysis
Institute of Scientific and Technical Information of China (English)
Guoying Zhang; Soichiro Araki; Itaru Nishioka; Yoshihiko Suemura
2003-01-01
This paper proposes two migration scenarios from China rin g networks to ASON mesh networks . In our quantitative analysis with ASON/GMPLS simulator, a subnetwork protection scheme achieved best balanced performance in resource utilization and restoration time.
Automated Analysis of Security in Networking Systems
DEFF Research Database (Denmark)
Buchholtz, Mikael
2004-01-01
will both help raise the general level of awareness of the problems and prevent the most basic flaws from occurring. This thesis contributes to the development of such tools. Networking systems typically try to attain secure communication by applying standard cryptographic techniques. In this thesis......-experts users. The feasibility of the techiques is illustrated by a proof-of-concept implementation of a control ow analysis developed for LySa. From a techincal point of view, this implementation also interesting because it encodes in nite sets of algebraic terms, which denote encryption, as a nite number...
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
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.
Economic analysis of spider web airline networks
Institute of Scientific and Technical Information of China (English)
无
2009-01-01
The distinct network organization, management, service and operating characteristics of US Southwest Airlines are key elements of its success compared with other airlines. As a network organization type, the spider web airline network has received more attention. In this paper, we analyzed the relation between the spider web airline network and spider web, and the structure of spider web airline network, built the assignment model of the spider web airline network,and investigated the economics concerned.
Advantages of Social Network Analysis in Educational Research
Ushakov, K. M.; Kukso, K. N.
2015-01-01
Currently one of the main tools for the large scale studies of schools is statistical analysis. Although it is the most common method and it offers greatest opportunities for analysis, there are other quantitative methods for studying schools, such as network analysis. We discuss the potential advantages that network analysis has for educational…
Analysis and perturbation of degree correlation in complex networks
Xiang, Ju; Hu, Tao; Zhang, Yan
2015-01-01
Degree correlation is an important topological property common to many real-world networks. In this paper, the statistical measures for characterizing the degree correlation in networks are investigated analytically. We give an exact proof of the consistency for the statistical measures, reveal the general linear relation in the degree correlation, which provide a simple and interesting perspective on the analysis of the degree correlation in complex networks. By using the general linear analysis, we investigate the perturbation of the degree correlation in complex networks caused by the addition of few nodes and the rich club. The results show that the assortativity of homogeneous networks such as the ER graphs is easily to be affected strongly by the simple structural changes, while it has only slight variation for heterogeneous networks with broad degree distribution such as the scale-free networks. Clearly, the homogeneous networks are more sensitive for the perturbation than the heterogeneous networks.
Packet flow analysis in IP networks via abstract interpretation
Komondoor, Raghavan; Seetharam, Deva P; Balodia, Sudha
2011-01-01
Static analysis (aka offline analysis) of a model of an IP network is useful for understanding, debugging, and verifying packet flow properties of the network. There have been static analysis approaches proposed in the literature for networks based on model checking as well as graph reachability. Abstract interpretation is a method that has typically been applied to static analysis of programs. We propose a new, abstract-interpretation based approach for analysis of networks. We formalize our approach, mention its correctness guarantee, and demonstrate its flexibility in addressing multiple network-analysis problems that have been previously solved via tailor-made approaches. Finally, we investigate an application of our analysis to a novel problem -- inferring a high-level policy for the network -- which has been addressed in the past only in the restricted single-router setting.
A Game-Theoretic Approach to Energy-Efficient Modulation in CDMA Networks with Delay QoS Constraints
Meshkati, Farhad; Poor, H Vincent; Schwartz, Stuart C
2007-01-01
A game-theoretic framework is used to study the effect of constellation size on the energy efficiency of wireless networks for M-QAM modulation. A non-cooperative game is proposed in which each user seeks to choose its transmit power (and possibly transmit symbol rate) as well as the constellation size in order to maximize its own utility while satisfying its delay quality-of-service (QoS) constraint. The utility function used here measures the number of reliable bits transmitted per joule of energy consumed, and is particularly suitable for energy-constrained networks. The best-response strategies and Nash equilibrium solution for the proposed game are derived. It is shown that in order to maximize its utility (in bits per joule), a user must choose the lowest constellation size that can accommodate the user's delay constraint. This strategy is different from one that would maximize spectral efficiency. Using this framework, the tradeoffs among energy efficiency, delay, throughput and constellation size are ...
Co-occurrence network analysis of Chinese and English poems
Liang, Wei; Wang, Yanli; Shi, Yuming; Chen, Guanrong
2015-02-01
A total of 572 co-occurrence networks of Chinese characters and words as well as English words are constructed from both Chinese and English poems. It is found that most of the networks have small-world features; more Chinese networks have scale-free properties and hierarchical structures as compared with the English networks; all the networks are disassortative, and the disassortativeness of the Chinese word networks is more prominent than those of the English networks; the spectral densities of the Chinese word networks and English networks are similar, but they are different from those of the ER, BA, and WS networks. For the above observed phenomena, analysis is provided with interpretation from a linguistic perspective.
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)…
Analysis of High Degree Nodes in a Social Network
Directory of Open Access Journals (Sweden)
Nadeem Akhtar
2013-05-01
Full Text Available Online Social Network platforms(e.g. Facebook, LinkedIn, Flickr, Instant Messenger etc provide a deeper comprehension of social networks and hence render the basis for social network analysis. The huge amount of data from these sites has given a boost to the researchers who examine a network from different perspectives through various SNA methods. The development of network analysis tools have further helped to extract actionable patterns which are useful for business, consumers, and users. This study is a part of the growing body of research on Social Network Analysis and make use of a Facebook network to analyze the attributes of high degree nodes (users having greater number of friends and to uncover the hidden relationships of that network. Results show that there is little association among high degree nodes
Capacity Analysis for Dynamic Space Networks
Institute of Scientific and Technical Information of China (English)
Yang Lu; Bo Li; Wenjing Kang; Gongliang Liu; Xueting Li
2015-01-01
To evaluate transmission rate of highly dynamic space networks, a new method for studying space network capacity is proposed in this paper. Using graph theory, network capacity is defined as the maximum amount of flows ground stations can receive per unit time. Combined with a hybrid constellation model, network capacity is calculated and further analyzed for practical cases. Simulation results show that network capacity will increase to different extents as link capacity, minimum ground elevation constraint and satellite onboard processing capability change. Considering the efficiency and reliability of communication networks, how to scientifically design satellite networks is also discussed.
Institute of Scientific and Technical Information of China (English)
无
2002-01-01
Time domain ABCD matrix formalism is a useful model for analyzing the characteristics of actively modelocked fiber laser. Based on this model and given more consideration on the influences of optical fiber dispersion and optical fiber nonlinearity, the laser characteristic of actively modelocked fiber laser is analyzed, and the comparision of the theoretical analysis results with experimental ones is given.
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...
Metaphor Analysis as an Approach for Exploring Theoretical Concepts: The Case of Social Capital
Andriessen, Daniel; Gubbins, Claire
2009-01-01
In many fields within management and organizational literature there is considerable debate and controversy about key theoretical concepts and their definitions and meanings. Systematic metaphor analysis can be a useful approach to study the underlying conceptualizations that give rise to these cont
Traffic chaotic dynamics modeling and analysis of deterministic network
Wu, Weiqiang; Huang, Ning; Wu, Zhitao
2016-07-01
Network traffic is an important and direct acting factor of network reliability and performance. To understand the behaviors of network traffic, chaotic dynamics models were proposed and helped to analyze nondeterministic network a lot. The previous research thought that the chaotic dynamics behavior was caused by random factors, and the deterministic networks would not exhibit chaotic dynamics behavior because of lacking of random factors. In this paper, we first adopted chaos theory to analyze traffic data collected from a typical deterministic network testbed — avionics full duplex switched Ethernet (AFDX, a typical deterministic network) testbed, and found that the chaotic dynamics behavior also existed in deterministic network. Then in order to explore the chaos generating mechanism, we applied the mean field theory to construct the traffic dynamics equation (TDE) for deterministic network traffic modeling without any network random factors. Through studying the derived TDE, we proposed that chaotic dynamics was one of the nature properties of network traffic, and it also could be looked as the action effect of TDE control parameters. A network simulation was performed and the results verified that the network congestion resulted in the chaotic dynamics for a deterministic network, which was identical with expectation of TDE. Our research will be helpful to analyze the traffic complicated dynamics behavior for deterministic network and contribute to network reliability designing and analysis.
DEFF Research Database (Denmark)
Sindbæk, Søren Michael
2015-01-01
Long-distance communication has emerged as a particular focus for archaeologicalexploration using network theory, analysis, and modelling. The promise is apparentlyobvious: communication in the past doubtlessly had properties of complex, dynamicnetworks, and archaeological datasets almost certainly...... 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...
Theoretical Analysis of TCS with a Comparison to HGS in Characteristics
Institute of Scientific and Technical Information of China (English)
侯培民
2001-01-01
A theoretical analysis of TCS is provided to explain the structure evolution along the filament during processing.This analysis based on the spinning process kinematics incorporates the constitutive equation of PET polymer, a convection and radiation combining procedure in the thermal channel, and takinginto account the nonisothermal crystallization kinetics. The characteristics of the fiber so-produced are compared with those produced by HGS.
Theoretical analysis of the acoustical characteristics of suspended micro-perforated panel absorbers
Institute of Scientific and Technical Information of China (English)
SHENG Shengwo; SONG Yongmin; WANG Jiqing
2005-01-01
Sound absorption characteristics of suspended micro-perforated panel absorbers were investigated theoretically. The method of half thickness model of such panel absorber with quadripole analysis was used for predicting its acoustic performance. The analysis results show that the predictions agree well with the measurements of absorption in the reverberation chamber. The factors affecting the absorption characteristics for such absorbers were discussed,and some rules as design guidelines were given.
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.
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 shipp
[Assessment of ultraviolet radiation penetration into human skin. I. Theoretical analysis].
Cader, A; Jankowski, J
1995-01-01
This is one of the two articles under the same title "Assessment of ultraviolet radiation penetrating into human skin" which are aimed at presenting a part of broader studies in this area. They drive at identifying biophysical aspects of the effects of ultraviolet radiation on human skin. In order to characterise such parameters as UV reflectance from the skin surface of UV absorption and dispersion coefficients, it is necessary to develop appropriate methods. In Part I--"Theoretical analysis", theoretical principles for interpreting measurements of radiation dispersed in different geometrical configurations are presented. They can serve as a basis for estimating the values of UV linear absorption and dispersion coefficients in skin tissues.
BRIEF ANALYSIS ON THEORETIC EVIDENCE OF FOUR-GATE POINTS IN TREATMENT OF DISEASE
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
In the present paper, the authors expound the approaches of four-gate points on treatment of diseases and the relevant theoretic evidence. The analysis and discussion were carried on in the aspects of the origins of four-gate points and the relationships of four-gate points with primary qi, running course of meridian, qi and blood and biaoben qijie of meridian and collateral. Being the major points in clinic, fourgate points provide extensive indications and good therapeutic effects, which are supported thoroughly by the theoretic evidence.
THEORETICAL ANALYSIS OF COORDINATES MEASUREMENT BY FLEXIBLE 3D MEASURING SYSTEM
Institute of Scientific and Technical Information of China (English)
ZHANG Guoyu; SUN Tianxiang; WANG Lingyun; XU Xiping
2007-01-01
The system mathematical model of flexible 3D measuring system is built by theoretical analysis, and the theoretical formula for measuring space point coordinate is also derived.Frog-jumping based coordinate transform method is put forward in order to solve measuring problem for large size parts. The flog-jumping method is discussed, and the coordinate transform mathematical model is method of the space point coordinate compared to original value, and an advanced method is provided. Form the space point coordinate transform formula can derive the calculation measuring method for measuring large size parts.
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...
Social Network Analysis: A case study of the Islamist terrorist network
Energy Technology Data Exchange (ETDEWEB)
Medina, Richard M [ORNL
2012-01-01
Social Network Analysis is a compilation of methods used to identify and analyze patterns in social network systems. This article serves as a primer on foundational social network concepts and analyses and builds a case study on the global Islamist terrorist network to illustrate the use and usefulness of these methods. The Islamist terrorist network is a system composed of multiple terrorist organizations that are socially connected and work toward the same goals. This research utilizes traditional social network, as well as small-world, and scale-free analyses to characterize this system on individual, network and systemic levels. Leaders in the network are identified based on their positions in the social network and the network structure is categorized. Finally, two vital nodes in the network are removed and this version of the network is compared with the previous version to make implications of strengths, weaknesses and vulnerabilities. The Islamist terrorist network structure is found to be a resilient and efficient structure, even with important social nodes removed. Implications for counterterrorism are given from the results of each analysis.
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...
Node Exchange Network and its Statistical Analysis
Toyota, N
2005-01-01
In considering a social network, there are cases where people is transferred to another place. Then the physical (direct) relations among nodes are lost by the movement. In terms of a network theory, some nodes break the present connections with neighboring nodes, move and there build new connections of nodes. For simplicity we here consider only that two nodes exchange the place each other on a network. Such exchange is assumed to be constantly carried out. We study this dynamic network (node exchange network NEN) and uncover some new features which usual networks do not contain. We mainly consider average path length and the diameter. Lastly we consider a propagation of one virus on the network by a computer simulation. They are compared to other networks investigated hitherto. The relation to a scale free network is also discussed.
An asymptotic analysis of closed queueing networks with branching populations
Bayer, N.; Coffman, E.G.; Kogan, Y.A.
1995-01-01
Closed 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 cu
Traffic Driven Analysis of Cellular and WiFi Networks
Paul, Utpal Kumar
2012-01-01
Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…
A Network Text Analysis of David Ayer's "Fury"
Hunter, Starling David; Smith, Susan
2015-01-01
Network Text Analysis (NTA) involves the creation of networks of words and/or concepts from linguistic data. Its key insight is that the position of words and concepts in a text network provides vital clues to the central and underlying themes of the text as a whole. Recent research has relied on inductive approaches to identify these themes. In…
Traffic Driven Analysis of Cellular and WiFi Networks
Paul, Utpal Kumar
2012-01-01
Since the days Internet traffic proliferated, measurement, monitoring and analysis of network traffic have been critical to not only the basic understanding of large networks, but also to seek improvements in resource management, traffic engineering and security. At the current times traffic in wireless local and wide area networks are facing…
Network Analysis of Cosmic Structures : Network Centrality and Topological Environment
Hong, Sungryong
2015-01-01
We apply simple analyses techniques developed for the study of complex networks to the study of the cosmic web, the large scale galaxy distribution. In this paper, we measure three network centralities (ranks of topological importance), Degree Centrality (DC), Closeness Centrality (CL), and Betweenness Centrality (BC) from a network built from the Cosmological Evolution Survey (COSMOS) catalog. We define 8 galaxy populations according to the centrality measures; Void, Wall, and Cluster by DC, Main Branch and Dangling Leaf by BC, and Kernel, Backbone, and Fracture by CL. We also define three populations by voronoi tessellation density to compare these with the DC selection. We apply the topological selections to galaxies in the (photometric) redshift range $0.91