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Sample records for attachment network model

  1. Unified Model for Generation Complex Networks with Utility Preferential Attachment

    International Nuclear Information System (INIS)

    Wu Jianjun; Gao Ziyou; Sun Huijun

    2006-01-01

    In this paper, based on the utility preferential attachment, we propose a new unified model to generate different network topologies such as scale-free, small-world and random networks. Moreover, a new network structure named super scale network is found, which has monopoly characteristic in our simulation experiments. Finally, the characteristics of this new network are given.

  2. Attachment and social networks.

    Science.gov (United States)

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

    2018-02-21

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

  3. Preferential Attachment in Online Networks: Measurement and Explanations

    NARCIS (Netherlands)

    Kunegis, J; Blattner, M; Moser, C.

    2013-01-01

    We perform an empirical study of the preferential attachment phenomenon in temporal networks and show that on the Web, networks follow a nonlinear preferential attachment model in which the exponent depends on the type of network considered. The classical preferential attachment model for networks

  4. Preferential attachment in evolutionary earthquake networks

    Science.gov (United States)

    Rezaei, Soghra; Moghaddasi, Hanieh; Darooneh, Amir Hossein

    2018-04-01

    Earthquakes as spatio-temporal complex systems have been recently studied using complex network theory. Seismic networks are dynamical networks due to addition of new seismic events over time leading to establishing new nodes and links to the network. Here we have constructed Iran and Italy seismic networks based on Hybrid Model and testified the preferential attachment hypothesis for the connection of new nodes which states that it is more probable for newly added nodes to join the highly connected nodes comparing to the less connected ones. We showed that the preferential attachment is present in the case of earthquakes network and the attachment rate has a linear relationship with node degree. We have also found the seismic passive points, the most probable points to be influenced by other seismic places, using their preferential attachment values.

  5. Networked Attached Devices at SNS

    CERN Document Server

    Blokland, W

    2003-01-01

    The Spallation Neutron Source (SNS) diagnostic instruments at Oak Ridge National Laboratory are based on the Network Attached Device (NAD) concept. Each pickup or sensor has its own resources such as timing, data acquisition and processing. NADs are individually connected to the network, thus reducing the brittleness inherent in tightly coupled systems. This architecture allows an individual device to fail or to be serviced or removed without disrupting other devices. This paper describes our implementation of the nearly 400 NADs to be deployed. The hardware consists of rack-mounted PCs with standard motherboards and PCI data-acquisition boards. The software environment is based on LabVIEW and EPICS. LabVIEW supports the agile development demanded by modern diagnostic systems. EPICS is the control system standard for the entire SNS facility. To achieve high performance, LabVIEW and EPICS communicate through shared memory. SNS diagnostics are developed by a multi-laboratory partnership including ORNL, BNL, LAN...

  6. Security for Network Attached Storage Devices

    National Research Council Canada - National Science Library

    Gobioff, Howard

    1997-01-01

    This paper presents a novel cryptographic capability system addressing the security and performance needs of network attached storage systems in which file management functions occur at a different...

  7. Distributed network generation based on preferential attachment in ABS

    NARCIS (Netherlands)

    K. Azadbakht (Keyvan); N. Bezirgiannis (Nikolaos); F.S. de Boer (Frank)

    2017-01-01

    textabstractGeneration of social networks using Preferential Attachment (PA) mechanism is proposed in the Barabasi-Albert model. In this mechanism, new nodes are introduced to the network sequentially and they attach to the existing nodes preferentially where the preference can be based on the

  8. Fitness networks for real world systems via modified preferential attachment

    Science.gov (United States)

    Shang, Ke-ke; Small, Michael; Yan, Wei-sheng

    2017-05-01

    Complex networks are virtually ubiquitous, and the Barabási and Albert model (BA model) has became an acknowledged standard for the modelling of these systems. The so-called BA model is a kind of preferential attachment growth model based on the intuitive premise that popularity is attractive. However, preferential attachment alone is insufficient to describe the diversity of complex networks observed in the real world. In this paper we first use the accuracy of a link prediction method, as a metric for network fitness. The link prediction method predicts the occurrence of links consistent with preferential attachment, the performance of this link prediction scheme is then a natural measure of the ;preferential-attachment-likeness; of a given network. We then propose several modification methods and modified BA models to construct networks which more accurately describe the fitness properties of real networks. We find that all features assortativity, degree distribution and rich-club formation can play significant roles for the network construction and eventual structure. Moreover, link sparsity and the size of a network are key factors for network reconstruction. In addition, we find that the structure of the network which is limited by geographic location (nodes are embedded in a Euclidean space and connectivity is correlated with distances) differs from other typical networks. In social networks, we observe that the high school contact network has similar structure as the friends network and so we speculate that the contact behaviours can reflect real friendships.

  9. A Weighted Evolving Network with Community Size Preferential Attachment

    International Nuclear Information System (INIS)

    Zhuo Zhiwei; Shan Erfang

    2010-01-01

    Community structure is an important characteristic in real complex network. It is a network consists of groups of nodes within which links are dense but among which links are sparse. In this paper, the evolving network include node, link and community growth and we apply the community size preferential attachment and strength preferential attachment to a growing weighted network model and utilize weight assigning mechanism from BBV model. The resulting network reflects the intrinsic community structure with generalized power-law distributions of nodes' degrees and strengths.

  10. Growing networks with mixed attachment mechanisms

    International Nuclear Information System (INIS)

    Shao Zhigang; Zou Xianwu; Tan Zhijie; Jin Zhunzhi

    2006-01-01

    Networks grow and evolve when new nodes and links are added in. There are two methods to add the links: uniform attachment and preferential attachment. We take account of the addition of links with mixed attachment between uniform attachment and preferential attachment in proportion. By using numerical simulations and analysis based on a continuum theory, we obtain that the degree distribution P(k) has an extended power-law form P(k) ∼ (k + k 0 ) -γ . When the number of edges k of a node is much larger than a certain value k 0 , the degree distribution reduces to the power-law form P(k) ∼ k -γ ; and when k is much smaller than k 0 , the degree distribution degenerates into the exponential form P(k)∼exp(-yk/k 0 ). It has been found that degree distribution possesses this extended power-law form for many real networks, such as the movie actor network, the citation network of scientific papers and diverse protein interaction networks

  11. Generating Billion-Edge Scale-Free Networks in Seconds: Performance Study of a Novel GPU-based Preferential Attachment Model

    Energy Technology Data Exchange (ETDEWEB)

    Perumalla, Kalyan S. [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Alam, Maksudul [Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

    2017-10-01

    A novel parallel algorithm is presented for generating random scale-free networks using the preferential-attachment model. The algorithm, named cuPPA, is custom-designed for single instruction multiple data (SIMD) style of parallel processing supported by modern processors such as graphical processing units (GPUs). To the best of our knowledge, our algorithm is the first to exploit GPUs, and also the fastest implementation available today, to generate scale free networks using the preferential attachment model. A detailed performance study is presented to understand the scalability and runtime characteristics of the cuPPA algorithm. In one of the best cases, when executed on an NVidia GeForce 1080 GPU, cuPPA generates a scale free network of a billion edges in less than 2 seconds.

  12. Understanding Members’ Attachment to Social Networking Sites

    DEFF Research Database (Denmark)

    Lim, Eric T. K.; Cyr, Dianne; Tan, Chee-Wee

    2014-01-01

    Social Networking Sites (SNSs) are pervasive phenomena in today’s society. With greater connectivity and interactivity enabled through emerging technologies, SNSs provide communication platforms for individuals to bridge spatial and temporal differences when making friends, sharing experiences......, socializing with others and much more. This study therefore endeavors to shed light on this growing trend by decomposing members’ motives for participating within SNSs into identity-based, bondbased and comparison-based attachments. Each of these forms of attachment in turn affects members’ cooperative...

  13. Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion.

    Science.gov (United States)

    Krause, Anna Linda; Borchardt, Viola; Li, Meng; van Tol, Marie-José; Demenescu, Liliana Ramona; Strauss, Bernhard; Kirchmann, Helmut; Buchheim, Anna; Metzger, Coraline D; Nolte, Tobias; Walter, Martin

    2016-01-01

    Attachment patterns influence actions, thoughts and feeling through a person's "inner working model". Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest functional magnetic resonance imaging (fMRI)-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants' attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC) analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described "social aversion network" including dorsal anterior cingulated cortex (dACC) and left anterior middle temporal gyrus (aMTG) specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants' avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the "social aversion network", namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule (IPL). Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by our observation of

  14. Maximum entropy networks are more controllable than preferential attachment networks

    International Nuclear Information System (INIS)

    Hou, Lvlin; Small, Michael; Lao, Songyang

    2014-01-01

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

  15. Complex networks as an emerging property of hierarchical preferential attachment

    Science.gov (United States)

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

    2015-12-01

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

  16. Preferential attachment in the evolution of metabolic networks

    Directory of Open Access Journals (Sweden)

    Elofsson Arne

    2005-11-01

    Full Text Available Abstract Background Many biological networks show some characteristics of scale-free networks. Scale-free networks can evolve through preferential attachment where new nodes are preferentially attached to well connected nodes. In networks which have evolved through preferential attachment older nodes should have a higher average connectivity than younger nodes. Here we have investigated preferential attachment in the context of metabolic networks. Results The connectivities of the enzymes in the metabolic network of Escherichia coli were determined and representatives for these enzymes were located in 11 eukaryotes, 17 archaea and 46 bacteria. E. coli enzymes which have representatives in eukaryotes have a higher average connectivity while enzymes which are represented only in the prokaryotes, and especially the enzymes only present in βγ-proteobacteria, have lower connectivities than expected by chance. Interestingly, the enzymes which have been proposed as candidates for horizontal gene transfer have a higher average connectivity than the other enzymes. Furthermore, It was found that new edges are added to the highly connected enzymes at a faster rate than to enzymes with low connectivities which is consistent with preferential attachment. Conclusion Here, we have found indications of preferential attachment in the metabolic network of E. coli. A possible biological explanation for preferential attachment growth of metabolic networks is that novel enzymes created through gene duplication maintain some of the compounds involved in the original reaction, throughout its future evolution. In addition, we found that enzymes which are candidates for horizontal gene transfer have a higher average connectivity than other enzymes. This indicates that while new enzymes are attached preferentially to highly connected enzymes, these highly connected enzymes have sometimes been introduced into the E. coli genome by horizontal gene transfer. We speculate

  17. Internal Representational Models of Attachment Relationships.

    Science.gov (United States)

    Crittenden, Patricia M.

    This paper outlines several properties of internal representational models (IRMs) and offers terminology that may help to differentiate the models. Properties of IRMs include focus, memory systems, content, cognitive function, "metastructure," quality of attachment, behavioral strategies, and attitude toward attachment. An IRM focuses on…

  18. The network perspective: an integration of attachment and family systems theories.

    Science.gov (United States)

    Kozlowska, Kasia; Hanney, Lesley

    2002-01-01

    In this article we discuss the network paradigm as a useful base from which to integrate attachment and family systems theories. The network perspective refers to the application of general systems theory to living systems, and provides a framework that conceptualizes the dyadic and family systems as simultaneously distinct and interconnected. Network thinking requires that the clinician holds multiple perspectives in mind, considers each system level as both a part and a whole, and shifts the focus of attention between levels as required. Key epistemological issues that have hindered the integration of the theories are discussed. These include inconsistencies within attachment theory itself and confusion surrounding the theoretical conceptualizations of the relationship between attachment and family systems theories. Detailed information about attachment categories is provided using the Dynamic Maturational model. Case vignettes illustrating work with young children and their families explore the clinical implications of integrating attachment data into family therapy practice.

  19. Dismissing attachment characteristics dynamically modulate brain networks subserving social aversion.

    Directory of Open Access Journals (Sweden)

    Anna Linda eKrause

    2016-03-01

    Full Text Available Attachment patterns influence actions, thoughts and feeling through a person’s ‘Inner Working Model’. Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest fMRI-experiment, presenting auditory narratives prototypical of dismissing attachment representations to investigate their effect on 23 healthy males. We then examined effects of participants’ attachment style and childhood trauma on brain state changes using seed-based functional connectivity (FC analyses, and finally tested whether subjective differences in responsivity to narratives could be predicted by baseline network states. In comparison to a baseline state, we observed increased FC in a previously described ‘social aversion network’ including dorsal anterior cingulated cortex (dACC and left anterior middle temporal gyrus (aMTG specifically after exposure to insecure-dismissing attachment narratives. Increased dACC-seeded FC within the social aversion network was positively related to the participants’ avoidant attachment style and presence of a history of childhood trauma. Anxious attachment style on the other hand was positively correlated with FC between the dACC and a region outside of the ‘social aversion network’, namely the dorsolateral prefrontal cortex, which suggests decreased network segregation as a function of anxious attachment. Finally, the extent of subjective experience of friendliness towards the dismissing narrative was predicted by low baseline FC-values between hippocampus and inferior parietal lobule. Taken together, our study demonstrates an activation of networks related to social aversion in terms of increased connectivity after listening to insecure-dismissing attachment narratives. A causal interrelation of brain state changes and subsequent changes in social reactivity was further supported by our observation of direct

  20. Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion

    NARCIS (Netherlands)

    Krause, Anna Linda; Borchardt, Viola; Li, Meng; van Tol, Marie-Jose; Demenescu, Liliana Ramona; Strauss, Bernhard; Kirchmanny, Helmut; Buchheim, Anna; Metzger, Coraline D.; Nolte, Tobias; Walter, Martin

    2016-01-01

    Attachment patterns influence actions, thoughts and feeling through a person's "inner working model". Speech charged with attachment-dependent content was proposed to modulate the activation of cognitive-emotional schemata in listeners. We performed a 7 Tesla rest-task-rest functional magnetic

  1. Social climber attachment in forming networks produces a phase transition in a measure of connectivity

    Science.gov (United States)

    Taylor, Dane; Larremore, Daniel B.

    2012-09-01

    The formation and fragmentation of networks are typically studied using percolation theory, but most previous research has been restricted to studying a phase transition in cluster size, examining the emergence of a giant component. This approach does not study the effects of evolving network structure on dynamics that occur at the nodes, such as the synchronization of oscillators and the spread of information, epidemics, and neuronal excitations. We introduce and analyze an alternative link-formation rule, called social climber (SC) attachment, that may be combined with arbitrary percolation models to produce a phase transition using the largest eigenvalue of the network adjacency matrix as the order parameter. This eigenvalue is significant in the analyses of many network-coupled dynamical systems in which it measures the quality of global coupling and is hence a natural measure of connectivity. We highlight the important self-organized properties of SC attachment and discuss implications for controlling dynamics on networks.

  2. Risk and resilience in military families experiencing deployment: the role of the family attachment network.

    Science.gov (United States)

    Riggs, Shelley A; Riggs, David S

    2011-10-01

    Deployment separation constitutes a significant stressor for U.S. military men and women and their families. Many military personnel return home struggling with physical and/or psychological injuries that challenge their ability to reintegrate and contribute to marital problems, family dysfunction, and emotional or behavioral disturbance in spouses and children. Yet research examining the psychological health and functioning of military families is scarce and rarely driven by developmental theory. The primary purpose of this theoretical paper is to describe a family attachment network model of military families during deployment and reintegration that is grounded in attachment theory and family systems theory. This integrative perspective provides a solid empirical foundation and a comprehensive account of individual and family risk and resilience during military-related separations and reunions. The proposed family attachment network model will inform future research and intervention efforts with service members and their families.

  3. A Net of Friends: Investigating Friendship by Integrating Attachment Theory and Social Network Analysis.

    Science.gov (United States)

    Gillath, Omri; Karantzas, Gery C; Selcuk, Emre

    2017-11-01

    The current article focuses on attachment style-an individual difference widely studied in the field of close relationships-and its application to the study of social networks. Specifically, we investigated whether attachment style predicts perception and management of social networks. In Study 1, we examined the associations of attachment style with perceptions of network tie strength and multiplexity. In Studies 2a and 2b, we investigated the association between attachment style and network management skills (initiating, maintaining, and dissolving ties) and whether network management skills mediated the associations of attachment style with network tie strength and multiplexity. In Study 3, experimentally enhancing attachment security made people more likely to initiate and less likely to dissolve social ties (for the latter, especially among those high on avoidance or anxiety). As for maintenance, security priming also increased maintenance; however, mainly among people high on attachment anxiety or low on attachment avoidance.

  4. Androgyny and Attachment Security: Two Related Models of Optimal Personality.

    Science.gov (United States)

    Shaver, Phillip R.; And Others

    1996-01-01

    Three studies explore similarities between attachment style typologies and sex role typologies. Both are defined by pairs of dimensions: self model and other model (attachment styles); masculinity, or agency, and femininity, or communion (sex role orientations). Discusses results. (KW)

  5. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim

    2014-12-03

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  6. Coevolutionary modeling in network formation

    KAUST Repository

    Al-Shyoukh, Ibrahim; Chasparis, Georgios; Shamma, Jeff S.

    2014-01-01

    Network coevolution, the process of network topology evolution in feedback with dynamical processes over the network nodes, is a common feature of many engineered and natural networks. In such settings, the change in network topology occurs at a comparable time scale to nodal dynamics. Coevolutionary modeling offers the possibility to better understand how and why network structures emerge. For example, social networks can exhibit a variety of structures, ranging from almost uniform to scale-free degree distributions. While current models of network formation can reproduce these structures, coevolutionary modeling can offer a better understanding of the underlying dynamics. This paper presents an overview of recent work on coevolutionary models of network formation, with an emphasis on the following three settings: (i) dynamic flow of benefits and costs, (ii) transient link establishment costs, and (iii) latent preferential attachment.

  7. An evolving network model with community structure

    International Nuclear Information System (INIS)

    Li Chunguang; Maini, Philip K

    2005-01-01

    Many social and biological networks consist of communities-groups of nodes within which connections are dense, but between which connections are sparser. Recently, there has been considerable interest in designing algorithms for detecting community structures in real-world complex networks. In this paper, we propose an evolving network model which exhibits community structure. The network model is based on the inner-community preferential attachment and inter-community preferential attachment mechanisms. The degree distributions of this network model are analysed based on a mean-field method. Theoretical results and numerical simulations indicate that this network model has community structure and scale-free properties

  8. Modeling online social signed networks

    Science.gov (United States)

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

    2018-04-01

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

  9. 'Adoption and attachment theory' the attachment models of adoptive mothers and the revision of attachment patterns of their late-adopted children.

    Science.gov (United States)

    Pace, C S; Zavattini, G C

    2011-01-01

    This study examined the attachment patterns of late-adopted children (aged 4-7) and their adoptive mothers during the first 7- to 8-month period after adoption and aimed to evaluate the effect of adoptive mothers' attachment security on the revision of the attachment patterns of their late-adopted children. We assessed attachment patterns in 20 adoptive dyads and 12 genetically related dyads at two different times: T1 (time 1) within 2 months of adoption and T2 (time 2) 6 months after T1. The children's behavioural attachment patterns were assessed using the Separation-Reunion Procedure and the children's representational (verbal) attachment patterns using the Manchester Child Attachment Story Task. The attachment models of the adoptive mothers were classified using the Adult Attachment Interview. We found that there was a significant enhancement of the late-adopted children's attachment security across the time period considered (P= 0.008). Moreover, all the late-adopted children who showed a change from insecurity to security had adoptive mothers with secure attachment models (P= 0.044). However, the matching between maternal attachment models and late-adopted children's attachment patterns (behaviours and representations) was not significant. Our data suggest that revision of the attachment patterns in the late-adopted children is possible but gradual, and that the adoptive mothers' attachment security makes it more likely to occur. © 2010 Blackwell Publishing Ltd.

  10. Statistical properties and attack tolerance of growing networks with algebraic preferential attachment

    International Nuclear Information System (INIS)

    Liu Zonghua; Lai Yingcheng; Ye Nong

    2002-01-01

    We consider growing networks with algebraic preferential attachment and address two questions: (1) what is the effect of temporal fluctuations in the number of new links acquired by the network? and (2) what is the network tolerance against random failures and intentional attacks? We find that the fluctuations generally have little effect on the network properties, although they lead to a plateau behavior for small degrees in the connectivity distribution. Formulas are derived for the evolution and distribution of the network connectivity, which are tested by numerical simulations. Numerical study of the effect of failures and attacks suggests that networks constructed under algebraic preferential attachment are more robust than scale-free networks

  11. The moderating role of attachment anxiety on social network site use intensity and social capital.

    Science.gov (United States)

    Liu, Haihua; Shi, Junqi; Liu, Yihao; Sheng, Zitong

    2013-02-01

    This study examined the moderating role of attachment anxiety on the relationship between intensity of social network site use and bridging, bonding, and maintained social capital. Data from 322 undergraduate Chinese students were collected. Hierarchical regression analyses showed positive relationships between online intensity of social network site use and the three types of social capital. Moreover, attachment anxiety moderated the effect of intensity of social network site use on social capital. Specifically, for students with lower attachment anxiety, the relationships between intensity of social network site use and bonding and bridging social capital were stronger than those with higher attachment anxiety. The result suggested that social network sites cannot improve highly anxiously attached individuals' social capital effectively; they may need more face-to-face communications.

  12. Topsector Energy. Innovation Officers Network; Topsector Energie. Innovatie Attache Netwerk

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2012-06-15

    The Top Sector policy of the Ministry of Economic Affairs, Agriculture and Innovation (ELI) has resulted in strongly worded plans with big ambitions for the various priority sectors. In this publication the Dutch Network of Innovation Officers gives an overview for the Top Sector Energy of developments taking place in the leading countries of the world in the field of Research, Development and Innovation. The information provides clues for the establishment and strengthening of international R and D strategy for the top sector and related options for cooperation with foreign parties [Dutch] Het topsectorenbeleid van onder meer het Ministerie van Economische zaken, Landbouw en Innovatie (ELI) heeft geresulteerd in scherp geformuleerde plannen met flinke ambities voor de diverse topsectoren. Het Netwerk van Innovatie Attachés geeft in deze publikatie een overzicht voor de Topsector Energie wat er in de meest toonaangevende landen van de wereld gebeurt op het terrein van Research and Development en Innovatie. De informatie biedt aanknopingspunten voor het opzetten en versterken van een internationale R and D strategie voor de topsector en daar toe behorende samenwerking met buitenlandse partijen.

  13. [Attachment theory and baby slings/carriers: technological network formation].

    Science.gov (United States)

    Lu, Zxy-Yann Jane; Lin, Wan-Shiuan

    2011-12-01

    Healthcare providers recognize the important role played by attachment theory in explaining the close relationship between mental health and social behavior in mothers and their children. This paper uses attachment theory in a socio-cultural context to ascertain the mechanism by which baby slings/carriers, a new technology, produced and reproduced the scientific motherhood. It further applies a social history of technology perspective to understand how baby carriers and attachment theory are socially constructed and historically contingent on three major transformations. These transformations include the use of attachment theory-based baby carriers to further scientific motherhood; the use of baby slings/carriers to further the medicalization of breastfeeding and enhance mother-infant attachment; and the use of baby slings/carriers to transform woman's identities by integrating scientific motherhood, independence and fashion. Implications for nursing clinical policy are suggested.

  14. Attachments

    International Nuclear Information System (INIS)

    2000-01-01

    In this attachment to the Annual report 1999 of the Nuclear Regulatory Authority of the Slovak Republic (UJD) the economic and personnel data of the UJD, used abbreviations, as well as the International nuclear event scales - INES are presented. Professional level of staff of the UJD is influenced by the education structure of its staff, when nearly 75% of the total number of staff has a university degree. A of 31.12.1999 there were 79 employees as average calculated number. Financing of the regulator in 1999 was mainly provided from the state budget, which represented 96% of all expenditures. The total volume of expenditures for UJD activity funded from the state budget achieved as of 31.12.1999 Slovak crowns (SK) 67 067 thousands. In the main category of expenditures an amount of SK 63 499 thous. was used for current activities, and the difference of SK 3 587 thous. was used for raising capital assets. Significant increase expenditures in the evaluated year compared to the 1998 was caused by a special purpose payment made by the Slovakia into the Fund for reconstruction of the Chernobyl cover (SK 19 996 thous.) funded through the budget chapter of the regulator. In the structure of current expenditures the highest share is taken by current transfers to abroad in total of SK 22 543 thous., i.e. contribution to reconstruction of Chernobyl cover made to the EBRD and contributions to the Fund of Technical Co-operation of the IAEA. For procurement of goods and services an amount of SK 19 814 thous. was spent, of which SK 7 054 thous. was used for funding science and technology tasks which were contracted out. The decision-making process in performing state supervision forced UJD to contact out various expert opinions and studies, for which UJD paid SK 2 058 thous. in total. Other expenditures in a volume of SK 10 702 thous. represent travel expenses, goods and services for UJD, rent for offices and other inevitable expenses. Salaries of staff represented SK 15 953

  15. Attachment, Autonomy, and Emotional Reliance: A Multilevel Model

    Science.gov (United States)

    Lynch, Martin F.

    2013-01-01

    This article reports a test of a multilevel model investigating how attachment security and autonomy contribute to emotional reliance, or the willingness to seek interpersonal support. Participants ("N" = 247) completed online measures of attachment, autonomy, emotional reliance, and vitality with respect to several everyday…

  16. Scale-free behavior of networks with the copresence of preferential and uniform attachment rules

    Science.gov (United States)

    Pachon, Angelica; Sacerdote, Laura; Yang, Shuyi

    2018-05-01

    Complex networks in different areas exhibit degree distributions with a heavy upper tail. A preferential attachment mechanism in a growth process produces a graph with this feature. We herein investigate a variant of the simple preferential attachment model, whose modifications are interesting for two main reasons: to analyze more realistic models and to study the robustness of the scale-free behavior of the degree distribution. We introduce and study a model which takes into account two different attachment rules: a preferential attachment mechanism (with probability 1 - p) that stresses the rich get richer system, and a uniform choice (with probability p) for the most recent nodes, i.e. the nodes belonging to a window of size w to the left of the last born node. The latter highlights a trend to select one of the last added nodes when no information is available. The recent nodes can be either a given fixed number or a proportion (αn) of the total number of existing nodes. In the first case, we prove that this model exhibits an asymptotically power-law degree distribution. The same result is then illustrated through simulations in the second case. When the window of recent nodes has a constant size, we herein prove that the presence of the uniform rule delays the starting time from which the asymptotic regime starts to hold. The mean number of nodes of degree k and the asymptotic degree distribution are also determined analytically. Finally, a sensitivity analysis on the parameters of the model is performed.

  17. Collaborative networks: Reference modeling

    NARCIS (Netherlands)

    Camarinha-Matos, L.M.; Afsarmanesh, H.

    2008-01-01

    Collaborative Networks: Reference Modeling works to establish a theoretical foundation for Collaborative Networks. Particular emphasis is put on modeling multiple facets of collaborative networks and establishing a comprehensive modeling framework that captures and structures diverse perspectives of

  18. A Cognitive Attachment Model of prolonged grief: integrating attachments, memory, and identity.

    Science.gov (United States)

    Maccallum, Fiona; Bryant, Richard A

    2013-08-01

    Prolonged grief (PG), otherwise known as complicated grief, has attracted much attention in recent years as a potentially debilitating condition that affects approximately 10% of bereaved people. We propose a model of PG that integrates processes of attachment, self-identity, and autobiographical memory. The paper commences with a discussion of the PG construct and reviews current evidence regarding the distinctiveness of PG from other bereavement related-outcomes. We then review the evidence regarding the dysfunctional attachments, appraisals, and coping styles that people with PG display. Recent evidence pertaining to the patterns of autobiographical memory in PG is described in the context of the self-memory system. This system provides a unifying framework to understand the roles of personal memories, identity, attachments, and coping responses in PG. The proposed model places emphasis on how one's sense of identity influences yearning, memories of the deceased, appraisals, and coping strategies, to maintain a focus on the loss. The model is discussed in relation to existing models of PG. The potential for shaping treatment strategies to shift perceptions of the self is then outlined. Finally, we outline future directions to test propositions stemming from the model and enhance our understanding of the mechanisms underlying PG. Copyright © 2013 Elsevier Ltd. All rights reserved.

  19. The Relationship Between Attachment Styles, Self-Monitoring and Cybercrime in Social Network Users.

    Science.gov (United States)

    Yaghoobi, Abolghasem; Mohammadzade, Serwa; Chegini, Ali Asghar; Yarmohammadi Vasel, Mosaeib; Zoghi Paidar, Mohammad Reza

    2016-09-01

    The anonymity in the cyberspace environment, as well as the rapid advent of and improvements to online activities has increased cybercrime. The aim of this paper was to survey the relationship between attachment styles, self-monitoring and cybercrime in social network users. The Collins and Read Adult Attachment Scale, and the Snyder self-monitoring and cybercrime scales were sent to 500 social network users. Of these, 203 users (103 men and 100 women) filled out the questionnaires. The results showed that women achieved higher scores in self-monitoring and the anxious attachment style, and men achieved higher scores in cybercrime and the anxious attachment style. There was a negative correlation between self-monitoring and cybercrime, and the anxious attachment style had a positive correlation with cybercrime and a negative correlation with self-monitoring. The secure attachment style had a positive correlation with self-monitoring and a negative correlation with cybercrime. The dependent attachment style had a positive correlation with self-monitoring and a negative correlation with cybercrime. All correlations were significant. Attachment styles have significant relationships with both self-monitoring and cybercrime. Self-monitoring and attachment styles are significant predictors of cybercrimes.

  20. Romantic Partner Monitoring After Breakups: Attachment, Dependence, Distress, and Post-Dissolution Online Surveillance via Social Networking Sites.

    Science.gov (United States)

    Fox, Jesse; Tokunaga, Robert S

    2015-09-01

    Romantic relationship dissolution can be stressful, and social networking sites make it difficult to separate from a romantic partner online as well as offline. An online survey (N = 431) tested a model synthesizing attachment, investment model variables, and post-dissolution emotional distress as predictors of interpersonal surveillance (i.e., "Facebook stalking") of one's ex-partner on Facebook after a breakup. Results indicated that anxious attachment predicted relational investment but also seeking relationship alternatives; avoidant attachment was negatively related to investment but positively related to seeking alternatives. Investment predicted commitment, whereas seeking alternatives was negatively related to commitment. Commitment predicted emotional distress after the breakup. Distress predicted partner monitoring immediately following the breakup, particularly for those who did not initiate the breakup, as well as current partner monitoring. Given their affordances, social media are discussed as potentially unhealthy enablers for online surveillance after relationship termination.

  1. PAFit: A Statistical Method for Measuring Preferential Attachment in Temporal Complex Networks.

    Directory of Open Access Journals (Sweden)

    Thong Pham

    Full Text Available Preferential attachment is a stochastic process that has been proposed to explain certain topological features characteristic of complex networks from diverse domains. The systematic investigation of preferential attachment is an important area of research in network science, not only for the theoretical matter of verifying whether this hypothesized process is operative in real-world networks, but also for the practical insights that follow from knowledge of its functional form. Here we describe a maximum likelihood based estimation method for the measurement of preferential attachment in temporal complex networks. We call the method PAFit, and implement it in an R package of the same name. PAFit constitutes an advance over previous methods primarily because we based it on a nonparametric statistical framework that enables attachment kernel estimation free of any assumptions about its functional form. We show this results in PAFit outperforming the popular methods of Jeong and Newman in Monte Carlo simulations. What is more, we found that the application of PAFit to a publically available Flickr social network dataset yielded clear evidence for a deviation of the attachment kernel from the popularly assumed log-linear form. Independent of our main work, we provide a correction to a consequential error in Newman's original method which had evidently gone unnoticed since its publication over a decade ago.

  2. Putting up emotional (Facebook) walls? Attachment status and emerging adults' experiences of social networking sites.

    Science.gov (United States)

    Nitzburg, George C; Farber, Barry A

    2013-11-01

    Social networking sites (SNS) like Facebook can increase interpersonal connections but also intensify jealousy, envy, and surveillance behaviors. Attachment styles may help explain differences in experiencing SNS. This study investigated the role of attachment in influencing emerging adults' perceptions and feelings about SNS and their disclosures on SNS. Disorganized and anxious attachment predicted subjects' use of SNS to avoid more personal face-to-face communication, suggesting individuals with these tendencies use SNS to hold relationships at a psychological arm's distance. Anxious attachment also predicted feelings of intimacy when using SNS, perhaps reflecting online needs for comfort from others. A case narrative is presented to show how those with insecure attachment patterns may struggle to avoid interpersonal conflict when being continuously presented with ambiguous social information. © 2013 Wiley Periodicals, Inc.

  3. Social networks, social satisfaction and place attachment in the neighborhood

    NARCIS (Netherlands)

    Weijs - Perrée, M.; van den Berg, P.E.W.; Arentze, T.A.; Kemperman, A.D.A.M.

    2017-01-01

    Feeling socially integrated and being satisfied with one’s social life are important indicators for happiness and well-being of individuals and for the strength of local communities. The effect of the living environment on social networks and the importance of local social contacts in the

  4. Modeling Network Interdiction Tasks

    Science.gov (United States)

    2015-09-17

    118 xiii Table Page 36 Computation times for weighted, 100-node random networks for GAND Approach testing in Python ...in Python . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 38 Accuracy measures for weighted, 100-node random networks for GAND...networks [15:p. 1]. A common approach to modeling network interdiction is to formulate the problem in terms of a two-stage strategic game between two

  5. Ecological Networks and Community Attachment and Support Among Recently Resettled Refugees.

    Science.gov (United States)

    Soller, Brian; Goodkind, Jessica R; Greene, R Neil; Browning, Christopher R; Shantzek, Cece

    2018-03-25

    Interventions aimed at enhancing mental health are increasingly centered around promoting community attachment and support. However, few have examined and tested the specific ecological factors that give rise to these key community processes. Drawing from insights from the ecological network perspective, we tested whether spatial and social overlap in routine activity settings (e.g., work, school, childcare) with fellow ethnic community members is associated with individuals' attachment to their ethnic communities and access to social resources embedded in their communities. Data on routine activity locations drawn from the Refugee Well-Being Project (based in a city in the Southwestern United States) were used to reconstruct the ecological networks of recently resettled refugee communities, which were two-mode networks that comprise individuals and their routine activity locations. Results indicated that respondents' community attachment and support increased with their ecological network extensity-which taps the extent to which respondents share routine activity locations with other community members. Our study highlights a key ecological process that potentially enhances individuals' ethnic community attachment that extends beyond residential neighborhoods. © Society for Community Research and Action 2018.

  6. Degree distribution of a new model for evolving networks

    Indian Academy of Sciences (India)

    on intuitive but realistic consideration that nodes are added to the network with both preferential and random attachments. The degree distribution of the model is between a power-law and an exponential decay. Motivated by the features of network evolution, we introduce a new model of evolving networks, incorporating the ...

  7. Social networking sites in romantic relationships: attachment, uncertainty, and partner surveillance on facebook.

    Science.gov (United States)

    Fox, Jesse; Warber, Katie M

    2014-01-01

    Social networking sites serve as both a source of information and a source of tension between romantic partners. Previous studies have investigated the use of Facebook for monitoring former and current romantic partners, but why certain individuals engage in this behavior has not been fully explained. College students (N=328) participated in an online survey that examined two potential explanatory variables for interpersonal electronic surveillance (IES) of romantic partners: attachment style and relational uncertainty. Attachment style predicted both uncertainty and IES, with preoccupieds and fearfuls reporting the highest levels. Uncertainty did not predict IES, however. Future directions for research on romantic relationships and online surveillance are explored.

  8. Modelling computer networks

    International Nuclear Information System (INIS)

    Max, G

    2011-01-01

    Traffic models in computer networks can be described as a complicated system. These systems show non-linear features and to simulate behaviours of these systems are also difficult. Before implementing network equipments users wants to know capability of their computer network. They do not want the servers to be overloaded during temporary traffic peaks when more requests arrive than the server is designed for. As a starting point for our study a non-linear system model of network traffic is established to exam behaviour of the network planned. The paper presents setting up a non-linear simulation model that helps us to observe dataflow problems of the networks. This simple model captures the relationship between the competing traffic and the input and output dataflow. In this paper, we also focus on measuring the bottleneck of the network, which was defined as the difference between the link capacity and the competing traffic volume on the link that limits end-to-end throughput. We validate the model using measurements on a working network. The results show that the initial model estimates well main behaviours and critical parameters of the network. Based on this study, we propose to develop a new algorithm, which experimentally determines and predict the available parameters of the network modelled.

  9. Identifying protein complex by integrating characteristic of core-attachment into dynamic PPI network.

    Directory of Open Access Journals (Sweden)

    Xianjun Shen

    Full Text Available How to identify protein complex is an important and challenging task in proteomics. It would make great contribution to our knowledge of molecular mechanism in cell life activities. However, the inherent organization and dynamic characteristic of cell system have rarely been incorporated into the existing algorithms for detecting protein complexes because of the limitation of protein-protein interaction (PPI data produced by high throughput techniques. The availability of time course gene expression profile enables us to uncover the dynamics of molecular networks and improve the detection of protein complexes. In order to achieve this goal, this paper proposes a novel algorithm DCA (Dynamic Core-Attachment. It detects protein-complex core comprising of continually expressed and highly connected proteins in dynamic PPI network, and then the protein complex is formed by including the attachments with high adhesion into the core. The integration of core-attachment feature into the dynamic PPI network is responsible for the superiority of our algorithm. DCA has been applied on two different yeast dynamic PPI networks and the experimental results show that it performs significantly better than the state-of-the-art techniques in terms of prediction accuracy, hF-measure and statistical significance in biology. In addition, the identified complexes with strong biological significance provide potential candidate complexes for biologists to validate.

  10. Modeling the citation network by network cosmology.

    Science.gov (United States)

    Xie, Zheng; Ouyang, Zhenzheng; Zhang, Pengyuan; Yi, Dongyun; Kong, Dexing

    2015-01-01

    Citation between papers can be treated as a causal relationship. In addition, some citation networks have a number of similarities to the causal networks in network cosmology, e.g., the similar in-and out-degree distributions. Hence, it is possible to model the citation network using network cosmology. The casual network models built on homogenous spacetimes have some restrictions when describing some phenomena in citation networks, e.g., the hot papers receive more citations than other simultaneously published papers. We propose an inhomogenous causal network model to model the citation network, the connection mechanism of which well expresses some features of citation. The node growth trend and degree distributions of the generated networks also fit those of some citation networks well.

  11. Brain Network Modelling

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther

    Three main topics are presented in this thesis. The first and largest topic concerns network modelling of functional Magnetic Resonance Imaging (fMRI) and Diffusion Weighted Imaging (DWI). In particular nonparametric Bayesian methods are used to model brain networks derived from resting state f...... for their ability to reproduce node clustering and predict unseen data. Comparing the models on whole brain networks, BCD and IRM showed better reproducibility and predictability than IDM, suggesting that resting state networks exhibit community structure. This also points to the importance of using models, which...... allow for complex interactions between all pairs of clusters. In addition, it is demonstrated how the IRM can be used for segmenting brain structures into functionally coherent clusters. A new nonparametric Bayesian network model is presented. The model builds upon the IRM and can be used to infer...

  12. Modeling Epidemic Network Failures

    DEFF Research Database (Denmark)

    Ruepp, Sarah Renée; Fagertun, Anna Manolova

    2013-01-01

    This paper presents the implementation of a failure propagation model for transport networks when multiple failures occur resulting in an epidemic. We model the Susceptible Infected Disabled (SID) epidemic model and validate it by comparing it to analytical solutions. Furthermore, we evaluate...... the SID model’s behavior and impact on the network performance, as well as the severity of the infection spreading. The simulations are carried out in OPNET Modeler. The model provides an important input to epidemic connection recovery mechanisms, and can due to its flexibility and versatility be used...... to evaluate multiple epidemic scenarios in various network types....

  13. Artificial neural network modelling

    CERN Document Server

    Samarasinghe, Sandhya

    2016-01-01

    This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling. .

  14. Experience and Lessons learnt from running High Availability Databases on Network Attached Storage

    CERN Document Server

    Guijarro, Manuel

    2008-01-01

    The Database and Engineering Services Group of CERN's Information Technology Department supplies the Oracle Central Database services used in many activities at CERN. In order to provide High Availability and ease management for those services, a NAS (Network Attached Storage) based infrastructure has been setup. It runs several instances of the Oracle RAC (Real Application Cluster) using NFS (Network File System) as shared disk space for RAC purposes and Data hosting. It is composed of two private LANs (Local Area Network), one to provide access to the NAS filers and a second to implement the Oracle RAC private interconnect, both using Network Bonding. NAS filers are configured in partnership to prevent having single points of failure and to provide automatic NAS filer fail-over.

  15. Filament networks attached to membranes: cytoskeletal pressure and local bilayer deformation

    International Nuclear Information System (INIS)

    Auth, Thorsten; Safran, S A; Gov, Nir S

    2007-01-01

    Several cell types, among them red blood cells, have a cortical, two-dimensional (2D) network of filaments sparsely attached to their lipid bilayer. In many mammalian cells, this 2D polymer network is connected to an underlying 3D, more rigid cytoskeleton. In this paper, we consider the pressure exerted by the thermally fluctuating, cortical network of filaments on the bilayer and predict the bilayer deformations that are induced by this pressure. We treat the filaments as flexible polymers and calculate the pressure that a network of such linear chains exerts on the bilayer; we then minimize the bilayer shape in order to predict the resulting local deformations. We compare our predictions with membrane deformations observed in electron micrographs of red blood cells. The polymer pressure along with the resulting membrane deformation can lead to compartmentalization, regulate in-plane diffusion and may influence protein sorting as well as transmit signals to the polymerization of the underlying 3D cytoskeleton

  16. Experience and lessons learnt from running high availability databases on network attached storage

    International Nuclear Information System (INIS)

    Guijarro, M; Gaspar, R

    2008-01-01

    The Database and Engineering Services Group of CERN's Information Technology Department supplies the Oracle Central Database services used in many activities at CERN. In order to provide High Availability and ease management for those services, a NAS (Network Attached Storage) based infrastructure has been setup. It runs several instances of the Oracle RAC (Real Application Cluster) using NFS (Network File System) as shared disk space for RAC purposes and Data hosting. It is composed of two private LANs (Local Area Network), one to provide access to the NAS filers and a second to implement the Oracle RAC private interconnect, both using Network Bonding. NAS filers are configured in partnership to prevent having single points of failure and to provide automatic NAS filer fail-over

  17. Social networking addiction, attachment style, and validation of the Italian version of the Bergen Social Media Addiction Scale.

    Science.gov (United States)

    Monacis, Lucia; de Palo, Valeria; Griffiths, Mark D; Sinatra, Maria

    2017-06-01

    Aim Research into social networking addiction has greatly increased over the last decade. However, the number of validated instruments assessing addiction to social networking sites (SNSs) remains few, and none have been validated in the Italian language. Consequently, this study tested the psychometric properties of the Italian version of the Bergen Social Media Addiction Scale (BSMAS), as well as providing empirical data concerning the relationship between attachment styles and SNS addiction. Methods A total of 769 participants were recruited to this study. Confirmatory factor analysis (CFA) and multigroup analyses were applied to assess construct validity of the Italian version of the BSMAS. Reliability analyses comprised the average variance extracted, the standard error of measurement, and the factor determinacy coefficient. Results Indices obtained from the CFA showed the Italian version of the BSMAS to have an excellent fit of the model to the data, thus confirming the single-factor structure of the instrument. Measurement invariance was established at configural, metric, and strict invariances across age groups, and at configural and metric levels across gender groups. Internal consistency was supported by several indicators. In addition, the theoretical associations between SNS addiction and attachment styles were generally supported. Conclusion This study provides evidence that the Italian version of the BSMAS is a psychometrically robust tool that can be used in future Italian research into social networking addiction.

  18. Modeling online social networks based on preferential linking

    International Nuclear Information System (INIS)

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

    2012-01-01

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

  19. A Binomial Modeling Approach for Upscaling Colloid Transport Under Unfavorable Attachment Conditions: Emergent Prediction of Nonmonotonic Retention Profiles

    Science.gov (United States)

    Hilpert, Markus; Johnson, William P.

    2018-01-01

    We used a recently developed simple mathematical network model to upscale pore-scale colloid transport information determined under unfavorable attachment conditions. Classical log-linear and nonmonotonic retention profiles, both well-reported under favorable and unfavorable attachment conditions, respectively, emerged from our upscaling. The primary attribute of the network is colloid transfer between bulk pore fluid, the near-surface fluid domain (NSFD), and attachment (treated as irreversible). The network model accounts for colloid transfer to the NSFD of downgradient grains and for reentrainment to bulk pore fluid via diffusion or via expulsion at rear flow stagnation zones (RFSZs). The model describes colloid transport by a sequence of random trials in a one-dimensional (1-D) network of Happel cells, which contain a grain and a pore. Using combinatorial analysis that capitalizes on the binomial coefficient, we derived from the pore-scale information the theoretical residence time distribution of colloids in the network. The transition from log-linear to nonmonotonic retention profiles occurs when the conditions underlying classical filtration theory are not fulfilled, i.e., when an NSFD colloid population is maintained. Then, nonmonotonic retention profiles result potentially both for attached and NSFD colloids. The concentration maxima shift downgradient depending on specific parameter choice. The concentration maxima were also shown to shift downgradient temporally (with continued elution) under conditions where attachment is negligible, explaining experimentally observed downgradient transport of retained concentration maxima of adhesion-deficient bacteria. For the case of zero reentrainment, we develop closed-form, analytical expressions for the shape, and the maximum of the colloid retention profile.

  20. Attachment, Working Models of Parenting, and Expectations for Using Television in Childrearing

    Science.gov (United States)

    Nathanson, Amy I.; Manohar, Uttara

    2012-01-01

    This study used attachment theory to understand college students' working models of parenting and expectations for how they would use television in parenting. We found that secure parent-child attachment histories were related to more positive expectations of parenting and that avoidant and anxious-ambivalent parent-child attachment histories were…

  1. Experience and Lessons learnt from running high availability databases on Network Attached Storage

    CERN Document Server

    Guijarro, Juan Manuel; Segura Chinchilla, Nilo

    2008-01-01

    The Database and Engineering Services Group of CERN's Information Technology Department provides the Oracle based Central Data Base services used in many activities at CERN. In order to provide High Availability and ease management for those services, a NAS (Network Attached Storage) based infrastructure has been set up. It runs several instances of the Oracle RAC (Real Application Cluster) using NFS as share disk space for RAC purposes and Data hosting. It is composed of two private LAN's to provide access to the NAS file servers and Oracle RAC interconnect, both using network bonding. NAS nodes are configured in partnership to prevent having single points of failure and to provide automatic NAS fail-over. This presentation describes that infrastructure and gives some advice on how to automate its management and setup using a Fabric Management framework such as Quattor. It also covers aspects related with NAS Performance and Monitoring as well Data Backup and Archive of such facility using already existing i...

  2. NAFFS: network attached flash file system for cloud storage on portable consumer electronics

    Science.gov (United States)

    Han, Lin; Huang, Hao; Xie, Changsheng

    Cloud storage technology has become a research hotspot in recent years, while the existing cloud storage services are mainly designed for data storage needs with stable high speed Internet connection. Mobile Internet connections are often unstable and the speed is relatively low. These native features of mobile Internet limit the use of cloud storage in portable consumer electronics. The Network Attached Flash File System (NAFFS) presented the idea of taking the portable device built-in NAND flash memory as the front-end cache of virtualized cloud storage device. Modern portable devices with Internet connection have built-in more than 1GB NAND Flash, which is quite enough for daily data storage. The data transfer rate of NAND flash device is much higher than mobile Internet connections[1], and its non-volatile feature makes it very suitable as the cache device of Internet cloud storage on portable device, which often have unstable power supply and intermittent Internet connection. In the present work, NAFFS is evaluated with several benchmarks, and its performance is compared with traditional network attached file systems, such as NFS. Our evaluation results indicate that the NAFFS achieves an average accessing speed of 3.38MB/s, which is about 3 times faster than directly accessing cloud storage by mobile Internet connection, and offers a more stable interface than that of directly using cloud storage API. Unstable Internet connection and sudden power off condition are tolerable, and no data in cache will be lost in such situation.

  3. Statistical Models for Social Networks

    NARCIS (Netherlands)

    Snijders, Tom A. B.; Cook, KS; Massey, DS

    2011-01-01

    Statistical models for social networks as dependent variables must represent the typical network dependencies between tie variables such as reciprocity, homophily, transitivity, etc. This review first treats models for single (cross-sectionally observed) networks and then for network dynamics. For

  4. A Network-Attached Storage System Supporting Guaranteed QoS

    Institute of Scientific and Technical Information of China (English)

    KONG Hua-feng; YU Sheng-sheng; LU Hong-wei

    2005-01-01

    We propose a network-attached storage system that can support guaranteed Quality of Service (QoS), called POPNet Storage. The special policy of date access and disk scheduling is enable users to access files quickly and directly with guaranteed QoS in the POPNet Storage. The POPNet Storage implements a measurement-based admission control algorithm (PSMBAC) to determine whether to admit a new data access request stream and admit as many requests as possible while meeting the QoS guarantees to its clients. The data reconstruction algorithms in the POPNet Storage also put more emphasis on data availability and guaranteed QoS, thus it is designed to complete the data recovery as soon as possible and at the same time provide the guaranteed QoS for high-priority data access. The experiment results show that the POPNet Storage can provide more significant performance, reliability, and guaranteed QoS than conventional storage systems.

  5. QNAP 1263U Network Attached Storage (NAS)/ Storage Area Network (SAN) Device Users Guide

    Science.gov (United States)

    2016-11-01

    position unless so designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an official endorsement or...Message Block, and newer standards such as Internet Small Computer Systems Interface. The differences in the protocols also play an important role in...Mapping the Network Drive 4 5.1 Windows 7 4 5.2 Windows 10 6 6. Connecting to the iSCSI on the NAS 6 7. Adding a New IQN to iSCSI ACL 7 8

  6. An evolving network model with modular growth

    International Nuclear Information System (INIS)

    Zou Zhi-Yun; Liu Peng; Lei Li; Gao Jian-Zhi

    2012-01-01

    In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner-module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module. (interdisciplinary physics and related areas of science and technology)

  7. The paths leading from attachment to ageism: a structural equation model approach.

    Science.gov (United States)

    Bodner, Ehud; Cohen-Fridel, Sara

    2014-01-01

    The study introduces a model in which attachment patterns serve as predictors, empathy and fear of death as mediators, and ageism as the predicted variable. Data were collected from young adults (N = 440). Anxious attachment was directly and positively correlated with ageism, and also indirectly and positively by the mediator "fear of death." Avoidant attachment was indirectly and negatively correlated with ageism by the mediator "empathy". It is suggested that interventions for reducing ageist attitudes among younger adults would focus on existential fears, as well as on empathic ability, according to the attachment tendencies of these individuals.

  8. A Model of Network Porosity

    Science.gov (United States)

    2016-11-09

    Figure 1. We generally express such networks in terms of the services running in each enclave as well as the routing and firewall rules between the...compromise a server, they can compromise other devices in the same subnet or protected enclave. They probe attached firewalls and routers for open ports and...spam and malware filter would prevent this content from reaching its destination. Content filtering provides another layer of defense to other controls

  9. Social networking addiction, attachment style, and validation of the Italian version of the Bergen Social Media Addiction Scale

    OpenAIRE

    Monacis, Lucia; de Palo, Valeria; Griffiths, Mark D.; Sinatra, Maria

    2017-01-01

    Aim: Research into social networking addiction has greatly increased over the last decade. However, the number of\\ud validated instruments assessing addiction to social networking sites (SNSs) remains few, and none have been\\ud validated in the Italian language. Consequently, this study tested the psychometric properties of the Italian version of\\ud the Bergen Social Media Addiction Scale (BSMAS), as well as providing empirical data concerning the relationship\\ud between attachment styles and...

  10. Parents' attachment histories and children's externalizing and internalizing behaviors: exploring family systems models of linkage.

    Science.gov (United States)

    Cowan, P A; Cowan, C P; Cohn, D A; Pearson, J L

    1996-02-01

    Twenty-seven mothers and 27 fathers were given the Adult Attachment Interview (M. Main & R. Goldwyn, in press) when their children were 3.5 years old. Continuous ratings of narrative coherence, probable experience quality (parents perceived as loving), and state of mind (current anger at parents) were entered as latent variables in partial least squares structural equation models that included observational measures of marital quality and parenting style. Models that include fathers' attachment histories predicted more variance in kindergarten teachers' descriptions of children's externalizing behavior, whereas models that include mothers' attachment histories predicted more variance in children's internalizing behavior. Marital data added predictive power to the equations. Discussion is focused on the importance of integrating attachment and family systems approaches, and of parents' gender and marital quality, in understanding specific links between parents' attachment histories and their young children's externalizing and internalizing behaviors.

  11. Testing an Attachment Model of Latina/o College Students' Psychological Adjustment

    Science.gov (United States)

    Garriott, Patton O.; Love, Keisha M.; Tyler, Kenneth M.; Thomas, Deneia M.; Roan-Belle, Clarissa R.; Brown, Carrie L.

    2010-01-01

    The present study examined the influence of attachment relationships on the psychological adjustment of Latina/o university students (N = 80) attending predominantly White institutions of higher education. A path analysis conducted to test a hypothesized model of parent and peer attachment, self-esteem, and psychological distress indicated that…

  12. Integrating attachment and depression in the confluence model of sexual assault perpetration.

    Science.gov (United States)

    Nguyen, David; Parkhill, Michele R

    2014-08-01

    This study sought to extend the confluence model of sexual assault perpetration by examining attachment insecurity and depression as additional predictors of sexual aggression. Male college students (N = 193) completed an online questionnaire assessing confluence model constructs in addition to attachment and history of depression. Overall, the model fit the data well, χ(2)(11, 193) = 19.43, p = ns; root mean square error of approximation = .063; comparative fit index = .94. Attachment and depression demonstrated both direct and indirect relationships with perpetration severity. The results contribute to elucidating the process by which certain men become susceptible to perpetrating sexual assault. Implications are discussed. © The Author(s) 2014.

  13. A neighbourhood evolving network model

    International Nuclear Information System (INIS)

    Cao, Y.J.; Wang, G.Z.; Jiang, Q.Y.; Han, Z.X.

    2006-01-01

    Many social, technological, biological and economical systems are best described by evolved network models. In this short Letter, we propose and study a new evolving network model. The model is based on the new concept of neighbourhood connectivity, which exists in many physical complex networks. The statistical properties and dynamics of the proposed model is analytically studied and compared with those of Barabasi-Albert scale-free model. Numerical simulations indicate that this network model yields a transition between power-law and exponential scaling, while the Barabasi-Albert scale-free model is only one of its special (limiting) cases. Particularly, this model can be used to enhance the evolving mechanism of complex networks in the real world, such as some social networks development

  14. Attachment of Salmonella strains to a plant cell wall model is modulated by surface characteristics and not by specific carbohydrate interactions.

    Science.gov (United States)

    Tan, Michelle Sze-Fan; Moore, Sean C; Tabor, Rico F; Fegan, Narelle; Rahman, Sadequr; Dykes, Gary A

    2016-09-15

    Processing of fresh produce exposes cut surfaces of plant cell walls that then become vulnerable to human foodborne pathogen attachment and contamination, particularly by Salmonella enterica. Plant cell walls are mainly composed of the polysaccharides cellulose, pectin and hemicelluloses (predominantly xyloglucan). Our previous work used bacterial cellulose-based plant cell wall models to study the interaction between Salmonella and the various plant cell wall components. We demonstrated that Salmonella attachment was favoured in the presence of pectin while xyloglucan had no effect on its attachment. Xyloglucan significantly increased the attachment of Salmonella cells to the plant cell wall model only when it was in association with pectin. In this study, we investigate whether the plant cell wall polysaccharides mediate Salmonella attachment to the bacterial cellulose-based plant cell wall models through specific carbohydrate interactions or through the effects of carbohydrates on the physical characteristics of the attachment surface. We found that none of the monosaccharides that make up the plant cell wall polysaccharides specifically inhibit Salmonella attachment to the bacterial cellulose-based plant cell wall models. Confocal laser scanning microscopy showed that Salmonella cells can penetrate and attach within the tightly arranged bacterial cellulose network. Analysis of images obtained from atomic force microscopy revealed that the bacterial cellulose-pectin-xyloglucan composite with 0.3 % (w/v) xyloglucan, previously shown to have the highest number of Salmonella cells attached to it, had significantly thicker cellulose fibrils compared to other composites. Scanning electron microscopy images also showed that the bacterial cellulose and bacterial cellulose-xyloglucan composites were more porous when compared to the other composites containing pectin. Our study found that the attachment of Salmonella cells to cut plant cell walls was not mediated by

  15. An evolving model of online bipartite networks

    Science.gov (United States)

    Zhang, Chu-Xu; Zhang, Zi-Ke; Liu, Chuang

    2013-12-01

    Understanding the structure and evolution of online bipartite networks is a significant task since they play a crucial role in various e-commerce services nowadays. Recently, various attempts have been tried to propose different models, resulting in either power-law or exponential degree distributions. However, many empirical results show that the user degree distribution actually follows a shifted power-law distribution, the so-called Mandelbrot’s law, which cannot be fully described by previous models. In this paper, we propose an evolving model, considering two different user behaviors: random and preferential attachment. Extensive empirical results on two real bipartite networks, Delicious and CiteULike, show that the theoretical model can well characterize the structure of real networks for both user and object degree distributions. In addition, we introduce a structural parameter p, to demonstrate that the hybrid user behavior leads to the shifted power-law degree distribution, and the region of power-law tail will increase with the increment of p. The proposed model might shed some lights in understanding the underlying laws governing the structure of real online bipartite networks.

  16. Negative childhood experiences and adult love relationships: the role of internal working models of attachment.

    Science.gov (United States)

    McCarthy, Gerard; Maughan, Barbara

    2010-09-01

    This study investigated links between internal working models of attachment and the quality of adult love relationships in a high risk sample of women (n = 34), all of whom reported negative parenting in childhood. Half of the sample was identified as having a history of satisfying adult love relationships, while the remainder had experienced ongoing adult relationship problems. Measures of internal working models of attachment were made using the Adult Attachment Interview (AAI). A strong association was found between attachment classifications and the quality of adult love relationships. In addition, women with satisfying love relationships demonstrated significantly higher coherence of mind ratings than those with poor relationship histories. Insecure working models of attachment were associated with problems in adult love relationships. Although secure/autonomous attachment status was linked to optimal adult relationship outcomes, some women with a history of satisfying love relationships had insecure working models of attachment. These results suggest that the ways that adults process early experiences may influence later psychosocial functioning.

  17. A Complex Network Approach to Distributional Semantic Models.

    Directory of Open Access Journals (Sweden)

    Akira Utsumi

    Full Text Available A number of studies on network analysis have focused on language networks based on free word association, which reflects human lexical knowledge, and have demonstrated the small-world and scale-free properties in the word association network. Nevertheless, there have been very few attempts at applying network analysis to distributional semantic models, despite the fact that these models have been studied extensively as computational or cognitive models of human lexical knowledge. In this paper, we analyze three network properties, namely, small-world, scale-free, and hierarchical properties, of semantic networks created by distributional semantic models. We demonstrate that the created networks generally exhibit the same properties as word association networks. In particular, we show that the distribution of the number of connections in these networks follows the truncated power law, which is also observed in an association network. This indicates that distributional semantic models can provide a plausible model of lexical knowledge. Additionally, the observed differences in the network properties of various implementations of distributional semantic models are consistently explained or predicted by considering the intrinsic semantic features of a word-context matrix and the functions of matrix weighting and smoothing. Furthermore, to simulate a semantic network with the observed network properties, we propose a new growing network model based on the model of Steyvers and Tenenbaum. The idea underlying the proposed model is that both preferential and random attachments are required to reflect different types of semantic relations in network growth process. We demonstrate that this model provides a better explanation of network behaviors generated by distributional semantic models.

  18. Emergence of global preferential attachment from local interaction

    International Nuclear Information System (INIS)

    Li Menghui; Fan Ying; Wu Jinshan; Di Zengru; Gao Liang

    2010-01-01

    Global degree/strength-based preferential attachment is widely used as an evolution mechanism of networks. But it is hard to believe that any individual can get global information and shape the network architecture based on it. In this paper, it is found that the global preferential attachment emerges from the local interaction models, including the distance-dependent preferential attachment (DDPA) evolving model of weighted networks (Li et al 2006 New J. Phys. 8 72), the acquaintance network model (Davidsen et al 2002 Phys. Rev. Lett. 88 128701) and the connecting nearest-neighbor (CNN) model (Vazquez 2003 Phys. Rev. E 67 056104). For the DDPA model and the CNN model, the attachment rate depends linearly on the degree or vertex strength, whereas for the acquaintance network model, the dependence follows a sublinear power law. It implies that for the evolution of social networks, local contact could be more fundamental than the presumed global preferential attachment.

  19. Attachment-based family therapy for depressed and suicidal adolescents: theory, clinical model and empirical support.

    Science.gov (United States)

    Ewing, E Stephanie Krauthamer; Diamond, Guy; Levy, Suzanne

    2015-01-01

    Attachment-Based Family Therapy (ABFT) is a manualized family-based intervention designed for working with depressed adolescents, including those at risk for suicide, and their families. It is an empirically informed and supported treatment. ABFT has its theoretical underpinnings in attachment theory and clinical roots in structural family therapy and emotion focused therapies. ABFT relies on a transactional model that aims to transform the quality of adolescent-parent attachment, as a means of providing the adolescent with a more secure relationship that can support them during challenging times generally, and the crises related to suicidal thinking and behavior, specifically. This article reviews: (1) the theoretical foundations of ABFT (attachment theory, models of emotional development); (2) the ABFT clinical model, including training and supervision factors; and (3) empirical support.

  20. Attachment in medical care: A review of the interpersonal model in chronic disease management.

    Science.gov (United States)

    Jimenez, Xavier F

    2017-03-01

    Objective Patient-physician interaction is continually examined in an era prioritizing patient-centered approaches, yet elaboration beyond aspects of communication and empathy is lacking. Major chronic conditions would benefit tremendously from understanding interpersonal aspects of patient-physician encounters. This review intends to provide a concise introduction to the interpersonal model of attachment theory and how it informs both the patient-physician interaction and medical outcomes in chronic care. Methods A narrative review of the theoretical, neurobiological, epidemiological, investigational, and clinical literature on attachment theory and its impact on medical outcomes was conducted, utilizing a variety of key words as searched on PubMed database. Studies and reviews included were of a variety of sources, including textbooks and peer-reviewed journals. Reports in languages other than English were excluded. Results Measurable, discrete attachment styles and behavioral patterns correlate with poor medical outcomes, including nonadherence in insecure dismissing attachment and care overutilization in insecure preoccupied attachment. Furthermore, insecure dismissing attachment is associated with significant mortality. These variables can be easily assessed, and their effects are reversible, as evidenced by collaborative care outcome data. Discussion Attachment theory is useful a model with application in clinical and investigational aspects of chronic illness care. Implications and guidelines are explored.

  1. Constraints and entropy in a model of network evolution

    Science.gov (United States)

    Tee, Philip; Wakeman, Ian; Parisis, George; Dawes, Jonathan; Kiss, István Z.

    2017-11-01

    Barabási-Albert's "Scale Free" model is the starting point for much of the accepted theory of the evolution of real world communication networks. Careful comparison of the theory with a wide range of real world networks, however, indicates that the model is in some cases, only a rough approximation to the dynamical evolution of real networks. In particular, the exponent γ of the power law distribution of degree is predicted by the model to be exactly 3, whereas in a number of real world networks it has values between 1.2 and 2.9. In addition, the degree distributions of real networks exhibit cut offs at high node degree, which indicates the existence of maximal node degrees for these networks. In this paper we propose a simple extension to the "Scale Free" model, which offers better agreement with the experimental data. This improvement is satisfying, but the model still does not explain why the attachment probabilities should favor high degree nodes, or indeed how constraints arrive in non-physical networks. Using recent advances in the analysis of the entropy of graphs at the node level we propose a first principles derivation for the "Scale Free" and "constraints" model from thermodynamic principles, and demonstrate that both preferential attachment and constraints could arise as a natural consequence of the second law of thermodynamics.

  2. A review of the evidence linking adult attachment theory and chronic pain: presenting a conceptual model.

    Science.gov (United States)

    Meredith, Pamela; Ownsworth, Tamara; Strong, Jenny

    2008-03-01

    It is now well established that pain is a multidimensional phenomenon, affected by a gamut of psychosocial and biological variables. According to diathesis-stress models of chronic pain, some individuals are more vulnerable to developing disability following acute pain because they possess particular psychosocial vulnerabilities which interact with physical pathology to impact negatively upon outcome. Attachment theory, a theory of social and personality development, has been proposed as a comprehensive developmental model of pain, implicating individual adult attachment pattern in the ontogenesis and maintenance of chronic pain. The present paper reviews and critically appraises studies which link adult attachment theory with chronic pain. Together, these papers offer support for the role of insecure attachment as a diathesis (or vulnerability) for problematic adjustment to pain. The Attachment-Diathesis Model of Chronic Pain developed from this body of literature, combines adult attachment theory with the diathesis-stress approach to chronic pain. The evidence presented in this review, and the associated model, advances our understanding of the developmental origins of chronic pain conditions, with potential application in guiding early pain intervention and prevention efforts, as well as tailoring interventions to suit specific patient needs.

  3. Developing Personal Network Business Models

    DEFF Research Database (Denmark)

    Saugstrup, Dan; Henten, Anders

    2006-01-01

    The aim of the paper is to examine the issue of business modeling in relation to personal networks, PNs. The paper builds on research performed on business models in the EU 1ST MAGNET1 project (My personal Adaptive Global NET). The paper presents the Personal Network concept and briefly reports...

  4. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.; Byrne, H.M.; King, J.R.; Bennett, M.J.

    2013-01-01

    methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more

  5. Complex Networks in Psychological Models

    Science.gov (United States)

    Wedemann, R. S.; Carvalho, L. S. A. V. D.; Donangelo, R.

    We develop schematic, self-organizing, neural-network models to describe mechanisms associated with mental processes, by a neurocomputational substrate. These models are examples of real world complex networks with interesting general topological structures. Considering dopaminergic signal-to-noise neuronal modulation in the central nervous system, we propose neural network models to explain development of cortical map structure and dynamics of memory access, and unify different mental processes into a single neurocomputational substrate. Based on our neural network models, neurotic behavior may be understood as an associative memory process in the brain, and the linguistic, symbolic associative process involved in psychoanalytic working-through can be mapped onto a corresponding process of reconfiguration of the neural network. The models are illustrated through computer simulations, where we varied dopaminergic modulation and observed the self-organizing emergent patterns at the resulting semantic map, interpreting them as different manifestations of mental functioning, from psychotic through to normal and neurotic behavior, and creativity.

  6. Interlinkages between attachment and the Five-Factor Model of personality in middle childhood and young adulthood: a longitudinal approach.

    Science.gov (United States)

    Fransson, Mari; Granqvist, Pehr; Bohlin, Gunilla; Hagekull, Berit

    2013-01-01

    In this paper, we examine concurrent and prospective links between attachment and the Five-Factor Model (FFM) of personality from middle childhood to young adulthood (n = 66). At age 8.5 years, attachment was measured with the Separation Anxiety Test and at 21 years with the Adult Attachment Interview, whereas the personality dimensions were assessed with questionnaires at both time points. The results showed that attachment and personality dimensions are meaningfully related, concurrently and longitudinally. Attachment security in middle childhood was positively related to extraversion and openness, both concurrently and prospectively. Unresolved/disorganized (U/d) attachment was negatively related to conscientiousness and positively related to openness in young adulthood. U/d attachment showed a unique contribution to openness above the observed temporal stability of openness. As attachment security was also associated with openness, the duality of this factor is discussed together with other theoretical considerations regarding attachment theory in relation to the FFM.

  7. Following the moving and changing attachments and assemblages of 'addiction': Applying the actor network approach to autobiographies.

    Science.gov (United States)

    Törrönen, Jukka; Tigerstedt, Christoffer

    2018-04-01

    The article applies actor network theory (ANT) to autobiographical data on alcohol dependence to explore what ANT can offer to the analysis of 'addiction stories'. By defining 'addiction' as a relational achievement, as the effect of elements acting together as a configuration of human and non-human actors, the article demonstrates how the moving and changing attachments of addiction can be dynamically analyzed with concepts of 'assemblage', 'mediator', 'tendency', 'translation', 'trajectory', 'immutable mobile', 'fluid' and 'bush fire'. The article shows how the reduction of alcohol dependence simply to genetic factors, neurobiological causes, personality disorders and self-medication constitutes an inadequate explanation. As 'meta theories', they illuminate addiction one-sidedly. Instead, as ANT pays attention to multiple heterogeneous mediators, it specifies in what way the causes identified in 'meta theories' may together with other actors participate in addiction assemblages. When following the development of addiction assemblages, we focus on situational sequences of action, in which human and non-human elements are linked to each other, and we trace how the relational shape of addiction changes from one sequence to another as a transforming assemblage of heterogeneous attachments that either maintain healthy subjectivities or destabilize them. The more attachments assemblages of addiction are able to make that are flexible and durable from one event to another, the stronger also the addiction-based subjectivities. Similarly, the fewer attachments that assemblages of addiction are able to keep in their various translations, the weaker the addiction-based subjectivities also become. An ANT-inspired analysis has a number of implications for the prevention and treatment of addiction: it suggests that in the prevention and treatment of addiction, the aim should hardly be to get rid of dependencies. Rather, the ambition should be the identification of attachments

  8. A model of coauthorship networks

    Science.gov (United States)

    Zhou, Guochang; Li, Jianping; Xie, Zonglin

    2017-10-01

    A natural way of representing the coauthorship of authors is to use a generalization of graphs known as hypergraphs. A random geometric hypergraph model is proposed here to model coauthorship networks, which is generated by placing nodes on a region of Euclidean space randomly and uniformly, and connecting some nodes if the nodes satisfy particular geometric conditions. Two kinds of geometric conditions are designed to model the collaboration patterns of academic authorities and basic researches respectively. The conditions give geometric expressions of two causes of coauthorship: the authority and similarity of authors. By simulation and calculus, we show that the forepart of the degree distribution of the network generated by the model is mixture Poissonian, and the tail is power-law, which are similar to these of some coauthorship networks. Further, we show more similarities between the generated network and real coauthorship networks: the distribution of cardinalities of hyperedges, high clustering coefficient, assortativity, and small-world property

  9. A network growth model based on the evolutionary ultimatum game

    International Nuclear Information System (INIS)

    Deng, L L; Zhou, G G; Cai, J H; Wang, C; Tang, W S

    2012-01-01

    In this paper, we provide a network growth model with incorporation into the ultimatum game dynamics. The network grows on the basis of the payoff-oriented preferential attachment mechanism, where a new node is added into the network and attached preferentially to nodes with higher payoffs. The interplay between the network growth and the game dynamics gives rise to quite interesting dynamical behaviors. Simulation results show the emergence of altruistic behaviors in the ultimatum game, which is affected by the growing network structure. Compared with the static counterpart case, the levels of altruistic behaviors are promoted. The corresponding strategy distributions and wealth distributions are also presented to further demonstrate the strategy evolutionary dynamics. Subsequently, we turn to the topological properties of the evolved network, by virtue of some statistics. The most studied characteristic path length and the clustering coefficient of the network are shown to indicate their small-world effect. Then the degree distributions are analyzed to clarify the interplay of structure and evolutionary dynamics. In particular, the difference between our growth network and the static counterpart is revealed. To explain clearly the evolved networks, the rich-club ordering and the assortative mixing coefficient are exploited to reveal the degree correlation. (paper)

  10. Telecommunications network modelling, planning and design

    CERN Document Server

    Evans, Sharon

    2003-01-01

    Telecommunication Network Modelling, Planning and Design addresses sophisticated modelling techniques from the perspective of the communications industry and covers some of the major issues facing telecommunications network engineers and managers today. Topics covered include network planning for transmission systems, modelling of SDH transport network structures and telecommunications network design and performance modelling, as well as network costs and ROI modelling and QoS in 3G networks.

  11. Campus network security model study

    Science.gov (United States)

    Zhang, Yong-ku; Song, Li-ren

    2011-12-01

    Campus network security is growing importance, Design a very effective defense hacker attacks, viruses, data theft, and internal defense system, is the focus of the study in this paper. This paper compared the firewall; IDS based on the integrated, then design of a campus network security model, and detail the specific implementation principle.

  12. Finger muscle attachments for an OpenSim upper-extremity model.

    Directory of Open Access Journals (Sweden)

    Jong Hwa Lee

    Full Text Available We determined muscle attachment points for the index, middle, ring and little fingers in an OpenSim upper-extremity model. Attachment points were selected to match both experimentally measured locations and mechanical function (moment arms. Although experimental measurements of finger muscle attachments have been made, models differ from specimens in many respects such as bone segment ratio, joint kinematics and coordinate system. Likewise, moment arms are not available for all intrinsic finger muscles. Therefore, it was necessary to scale and translate muscle attachments from one experimental or model environment to another while preserving mechanical function. We used a two-step process. First, we estimated muscle function by calculating moment arms for all intrinsic and extrinsic muscles using the partial velocity method. Second, optimization using Simulated Annealing and Hooke-Jeeves algorithms found muscle-tendon paths that minimized root mean square (RMS differences between experimental and modeled moment arms. The partial velocity method resulted in variance accounted for (VAF between measured and calculated moment arms of 75.5% on average (range from 48.5% to 99.5% for intrinsic and extrinsic index finger muscles where measured data were available. RMS error between experimental and optimized values was within one standard deviation (S.D of measured moment arm (mean RMS error = 1.5 mm < measured S.D = 2.5 mm. Validation of both steps of the technique allowed for estimation of muscle attachment points for muscles whose moment arms have not been measured. Differences between modeled and experimentally measured muscle attachments, averaged over all finger joints, were less than 4.9 mm (within 7.1% of the average length of the muscle-tendon paths. The resulting non-proprietary musculoskeletal model of the human fingers could be useful for many applications, including better understanding of complex multi-touch and gestural movements.

  13. Adult attachment, perceived social support, cultural orientation, and depressive symptoms: A moderated mediation model.

    Science.gov (United States)

    Zhu, Wenzhen; Wang, Chiachih Dc; Chong, Chu Chian

    2016-11-01

    In the current study, we tested a moderated mediation model in which cultural orientation moderated the mediation model of adult attachment-perceived social support-depressive symptoms, using 2 comparable cross-cultural samples of college students recruited from China and the U.S. (n = 363 for each group). Results indicated that perceived social support mediated the effect of attachment anxiety on depressive symptoms as well as the link between attachment avoidance and depression in both samples. Moderated mediation analyses using PROCESS revealed that interdependent self-construal significantly buffered the indirect effect of attachment avoidance (via perceived social support) on depressive symptoms. The findings indicated significant differences in the mediation models between the U.S. and China groups and interdependent self-construal accounted for the between-country differences. Limitations, implications of the findings, and future research directions are discussed from the perspectives of cross-cultural variation of adult attachment functioning. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

  14. The assessment of cyberstalking: an expanded examination including social networking, attachment, jealousy, and anger in relation to violence and abuse.

    Science.gov (United States)

    Strawhun, Jenna; Adams, Natasha; Huss, Matthew T

    2013-01-01

    Because the first antistalking statute was enacted in California in 1990, stalking research has been expanded immensely, yet been largely confined to exploring traditional pursuit tactics. This study instead examined the prevalence and correlates of cyberstalking behaviors while examining the phenomenon in a more inclusive manner than previous studies focusing on cyberstalking by including social networking avenues. In addition to a measure assessing cyberstalking-related behaviors, questionnaires assessing pathological aspects of personality, including attachment style, interpersonal jealousy, interpersonal violence, and anger were also provided to participants. Results indicate that, given preliminary evidence, cyberstalking-related behaviors are related to past measures of traditional stalking and cyberstalking, although prior attachment, jealousy, and violence issues within relationships are significant predictors of cyberstalking-related behaviors. In addition, unexpected gender differences emerged. For example, women admitted greater frequencies of cyberstalking perpetration than males, signaling that further research on frequency and motivation for cyberstalking among the sexes is necessary.

  15. Generalized Network Psychometrics : Combining Network and Latent Variable Models

    NARCIS (Netherlands)

    Epskamp, S.; Rhemtulla, M.; Borsboom, D.

    2017-01-01

    We introduce the network model as a formal psychometric model, conceptualizing the covariance between psychometric indicators as resulting from pairwise interactions between observable variables in a network structure. This contrasts with standard psychometric models, in which the covariance between

  16. Model of community emergence in weighted social networks

    Science.gov (United States)

    Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.

    2009-04-01

    Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.

  17. Neural network modeling of emotion

    Science.gov (United States)

    Levine, Daniel S.

    2007-03-01

    This article reviews the history and development of computational neural network modeling of cognitive and behavioral processes that involve emotion. The exposition starts with models of classical conditioning dating from the early 1970s. Then it proceeds toward models of interactions between emotion and attention. Then models of emotional influences on decision making are reviewed, including some speculative (not and not yet simulated) models of the evolution of decision rules. Through the late 1980s, the neural networks developed to model emotional processes were mainly embodiments of significant functional principles motivated by psychological data. In the last two decades, network models of these processes have become much more detailed in their incorporation of known physiological properties of specific brain regions, while preserving many of the psychological principles from the earlier models. Most network models of emotional processes so far have dealt with positive and negative emotion in general, rather than specific emotions such as fear, joy, sadness, and anger. But a later section of this article reviews a few models relevant to specific emotions: one family of models of auditory fear conditioning in rats, and one model of induced pleasure enhancing creativity in humans. Then models of emotional disorders are reviewed. The article concludes with philosophical statements about the essential contributions of emotion to intelligent behavior and the importance of quantitative theories and models to the interdisciplinary enterprise of understanding the interactions of emotion, cognition, and behavior.

  18. Modeling of fluctuating reaction networks

    International Nuclear Information System (INIS)

    Lipshtat, A.; Biham, O.

    2004-01-01

    Full Text:Various dynamical systems are organized as reaction networks, where the population size of one component affects the populations of all its neighbors. Such networks can be found in interstellar surface chemistry, cell biology, thin film growth and other systems. I cases where the populations of reactive species are large, the network can be modeled by rate equations which provide all reaction rates within mean field approximation. However, in small systems that are partitioned into sub-micron size, these populations strongly fluctuate. Under these conditions rate equations fail and the master equation is needed for modeling these reactions. However, the number of equations in the master equation grows exponentially with the number of reactive species, severely limiting its feasibility for complex networks. Here we present a method which dramatically reduces the number of equations, thus enabling the incorporation of the master equation in complex reaction networks. The method is examplified in the context of reaction network on dust grains. Its applicability for genetic networks will be discussed. 1. Efficient simulations of gas-grain chemistry in interstellar clouds. Azi Lipshtat and Ofer Biham, Phys. Rev. Lett. 93 (2004), 170601. 2. Modeling of negative autoregulated genetic networks in single cells. Azi Lipshtat, Hagai B. Perets, Nathalie Q. Balaban and Ofer Biham, Gene: evolutionary genomics (2004), In press

  19. Attachment, mastery, and interdependence: a model of parenting processes.

    Science.gov (United States)

    Edwards, Martha E

    2002-01-01

    A democratic nation needs an interdependent citizenry who are not only competent but who also can live together cooperatively with an eye toward what will benefit the whole as well as the self. In this article, the concept of interdependence is adopted as the central goal of parenting. The Parenting Processes Model is then presented, specifying how caregivers help children develop this interdependence. This work draws upon and integrates the work of a number of theoreticians, researchers, and clinicians, with the central focus on the work of John Bowlby, Alfred Adler, and Lev Vygotsky.

  20. Adolescent Mothers in a Transitional Living Facility: An Exploratory Study of Support Networks and Attachment Patterns

    Science.gov (United States)

    Schwartz, Ann E.; McRoy, Ruth G.; Downs, A. Chris

    2004-01-01

    Most of the research literature on attachment and adolescent transitions has addressed youth in family settings. This article explores these issues with a sample of 25 pregnant and parenting teens living in a transitional shelter. Using case records and interview data as well as results of standardized measures of depression, self-esteem, child…

  1. DNA-AuNP networks on cell membranes as a protective barrier to inhibit viral attachment, entry and budding.

    Science.gov (United States)

    Li, Chun Mei; Zheng, Lin Ling; Yang, Xiao Xi; Wan, Xiao Yan; Wu, Wen Bi; Zhen, Shu Jun; Li, Yuan Fang; Luo, Ling Fei; Huang, Cheng Zhi

    2016-01-01

    Viral infections have caused numerous diseases and deaths worldwide. Due to the emergence of new viruses and frequent virus variation, conventional antiviral strategies that directly target viral or cellular proteins are limited because of the specificity, drug resistance and rapid clearance from the human body. Therefore, developing safe and potent antiviral agents with activity against viral infection at multiple points in the viral life cycle remains a major challenge. In this report, we propose a new modality to inhibit viral infection by fabricating DNA conjugated gold nanoparticle (DNA-AuNP) networks on cell membranes as a protective barrier. The DNA-AuNPs networks were found, via a plaque formation assay and viral titers, to have potent antiviral ability and protect host cells from human respiratory syncytial virus (RSV). Confocal immunofluorescence image analysis showed 80 ± 3.8% of viral attachment, 91.1 ± 0.9% of viral entry and 87.9 ± 2.8% of viral budding were inhibited by the DNA-AuNP networks, which were further confirmed by real-time fluorescence imaging of the RSV infection process. The antiviral activity of the networks may be attributed to steric effects, the disruption of membrane glycoproteins and limited fusion of cell membrane bilayers, all of which play important roles in viral infection. Therefore, our results suggest that the DNA-AuNP networks have not only prophylactic effects to inhibit virus attachment and entry, but also therapeutic effects to inhibit viral budding and cell-to-cell spread. More importantly, this proof-of-principle study provides a pathway for the development of a universal, broad-spectrum antiviral therapy. Copyright © 2015 Elsevier Ltd. All rights reserved.

  2. Simple One-Dimensional Quantum-Mechanical Model for a Particle Attached to a Surface

    Science.gov (United States)

    Fernandez, Francisco M.

    2010-01-01

    We present a simple one-dimensional quantum-mechanical model for a particle attached to a surface. It leads to the Schrodinger equation for a harmonic oscillator bounded on one side that we solve in terms of Weber functions and discuss the behaviour of the eigenvalues and eigenfunctions. We derive the virial theorem and other exact relationships…

  3. Predicting Preschoolers' Attachment Security from Fathers' Involvement, Internal Working Models, and Use of Social Support

    Science.gov (United States)

    Newland, Lisa A.; Coyl, Diana D.; Freeman, Harry

    2008-01-01

    Associations between preschoolers' attachment security, fathers' involvement (i.e. parenting behaviors and consistency) and fathering context (i.e. fathers' internal working models (IWMs) and use of social support) were examined in a subsample of 102 fathers, taken from a larger sample of 235 culturally diverse US families. The authors predicted…

  4. Network model of security system

    Directory of Open Access Journals (Sweden)

    Adamczyk Piotr

    2016-01-01

    Full Text Available The article presents the concept of building a network security model and its application in the process of risk analysis. It indicates the possibility of a new definition of the role of the network models in the safety analysis. Special attention was paid to the development of the use of an algorithm describing the process of identifying the assets, vulnerability and threats in a given context. The aim of the article is to present how this algorithm reduced the complexity of the problem by eliminating from the base model these components that have no links with others component and as a result and it was possible to build a real network model corresponding to reality.

  5. Current approaches to gene regulatory network modelling

    Directory of Open Access Journals (Sweden)

    Brazma Alvis

    2007-09-01

    Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

  6. Structural Equation Model of Smartphone Addiction Based on Adult Attachment Theory: Mediating Effects of Loneliness and Depression.

    Science.gov (United States)

    Kim, EunYoung; Cho, Inhyo; Kim, Eun Joo

    2017-06-01

    This study investigated the mediating effects of loneliness and depression on the relationship between adult attachment and smartphone addiction in university students. A total of 200 university students participated in this study. The data was analysed using descriptive statistics, correlation analysis, and structural equation modeling. There were significant positive relationships between attachment anxiety, loneliness, depression, and smartphone addiction. However, attachment anxiety was not significantly correlated with smartphone addiction. The results also showed that loneliness did not directly mediate between attachment anxiety and smartphone addiction. In addition, loneliness and depression serially mediated between attachment anxiety and smartphone addiction. The results suggest there are mediating effects of loneliness and depression in the relationship between attachment anxiety and smartphone addiction. The hypothesized model was found to be a suitable model for predicting smartphone addiction among university students. Future study is required to find a causal path to prevent smartphone addiction among university students. Copyright © 2017. Published by Elsevier B.V.

  7. An Agent Model for a Human’s Social Support Network Tie Preference During Depression

    NARCIS (Netherlands)

    Aziz, A.A.; Klein, M.C.A.; Treur, J.; Baeza-Yates, R.; Lang, J.; Mitra, S.; Parsons, S.; Pasi, G.

    2009-01-01

    Seeking support from their environment is important for people suffering from a depression. People usually have different social networks to which they are attached with different ties. In this paper, a computational model is presented that describes the selection of network members for seeking

  8. Target-Centric Network Modeling

    DEFF Research Database (Denmark)

    Mitchell, Dr. William L.; Clark, Dr. Robert M.

    In Target-Centric Network Modeling: Case Studies in Analyzing Complex Intelligence Issues, authors Robert Clark and William Mitchell take an entirely new approach to teaching intelligence analysis. Unlike any other book on the market, it offers case study scenarios using actual intelligence...... reporting formats, along with a tested process that facilitates the production of a wide range of analytical products for civilian, military, and hybrid intelligence environments. Readers will learn how to perform the specific actions of problem definition modeling, target network modeling......, and collaborative sharing in the process of creating a high-quality, actionable intelligence product. The case studies reflect the complexity of twenty-first century intelligence issues by dealing with multi-layered target networks that cut across political, economic, social, technological, and military issues...

  9. Patterns and peculiarities of romatic attachment in adults from 62 cultural regions. Are "Model of Self" and "Model of Other" pancultural constructs?

    Directory of Open Access Journals (Sweden)

    David Schmitt

    2016-02-01

    Full Text Available As a part of the International Sexuality Description Project, a total of 17,804 participants from 62 cultural regions completed the Relationship Questionnaire (RQ, a self-report measure of adult romantic attachment. Correlational analyses within each culture suggested that the “Model of Self” and “Model of Other” scales of the RQ were psychometrically valid within the most cultures. Contrary to expectations, the Model of Self and Model of Other dimensions of the RQ did not underlie the four category model of attachment in the same way across all cultures. Analyses of specific attachment styles revealed that Secure romantic attachment was normative in 79% of cultures, and Preoccupied romantic attachment was particularly prevalent in East Asian cultures. Finally, the romantic attachment profiles of individual nations were correlated with sociocultural indicators in ways that supported evolutionary theories of romantic attachment and basic human mating strategies. 

  10. Persistence in a single species CSTR model with suspended flocs and wall attached biofilms.

    Science.gov (United States)

    Mašić, Alma; Eberl, Hermann J

    2012-04-01

    We consider a mathematical model for a bacterial population in a continuously stirred tank reactor (CSTR) with wall attachment. This is a modification of the Freter model, in which we model the sessile bacteria as a microbial biofilm. Our analysis indicates that the results of the algebraically simpler original Freter model largely carry over. In a computational simulation study, we find that the vast majority of bacteria in the reactor will eventually be sessile. However, we also find that suspended biomass is relatively more efficient in removing substrate from the reactor than biofilm bacteria.

  11. Constitutive and life modeling of single crystal blade alloys for root attachment analysis

    Science.gov (United States)

    Meyer, T. G.; Mccarthy, G. J.; Favrow, L. H.; Anton, D. L.; Bak, Joe

    1988-01-01

    Work to develop fatigue life prediction and constitutive models for uncoated attachment regions of single crystal gas turbine blades is described. At temperatures relevant to attachment regions, deformation is dominated by slip on crystallographic planes. However, fatigue crack initiation and early crack growth are not always observed to be crystallographic. The influence of natural occurring microporosity will be investigated by testing both hot isostatically pressed and conventionally cast PWA 1480 single crystal specimens. Several differnt specimen configurations and orientations relative to the natural crystal axes are being tested to investigate the influence of notch acuity and the material's anisotropy. Global and slip system stresses in the notched regions were determined from three dimensional stress analyses and will be used to develop fatigue life prediction models consistent with the observed lives and crack characteristics.

  12. Continuum Model for River Networks

    Science.gov (United States)

    Giacometti, Achille; Maritan, Amos; Banavar, Jayanth R.

    1995-07-01

    The effects of erosion, avalanching, and random precipitation are captured in a simple stochastic partial differential equation for modeling the evolution of river networks. Our model leads to a self-organized structured landscape and to abstraction and piracy of the smaller tributaries as the evolution proceeds. An algebraic distribution of the average basin areas and a power law relationship between the drainage basin area and the river length are found.

  13. No Pet or Their Person Left Behind: Increasing the Disaster Resilience of Vulnerable Groups through Animal Attachment, Activities and Networks

    Science.gov (United States)

    Thompson, Kirrilly; Every, Danielle; Rainbird, Sophia; Cornell, Victoria; Smith, Bradley; Trigg, Joshua

    2014-01-01

    Simple Summary The potential for reconfiguring pet ownership from a risk factor to a protective factor for natural disaster survival has been recently proposed. But how might this resilience-building proposition apply to members of the community who are already considered vulnerable? This article addresses this important question by synthesizing information about what makes seven particular groups vulnerable, the challenges to increasing their resilience and how animals figure in their lives. It concludes that animal attachment could provide a novel conduit for accessing, communicating with and motivating vulnerable people to engage in resilience building behaviors that promote survival and facilitate recovery. Abstract Increased vulnerability to natural disasters has been associated with particular groups in the community. This includes those who are considered de facto vulnerable (children, older people, those with disabilities etc.) and those who own pets (not to mention pets themselves). The potential for reconfiguring pet ownership from a risk factor to a protective factor for natural disaster survival has been recently proposed. But how might this resilience-building proposition apply to vulnerable members of the community who own pets or other animals? This article addresses this important question by synthesizing information about what makes particular groups vulnerable, the challenges to increasing their resilience and how animals figure in their lives. Despite different vulnerabilities, animals were found to be important to the disaster resilience of seven vulnerable groups in Australia. Animal attachment and animal-related activities and networks are identified as underexplored devices for disseminating or ‘piggybacking’ disaster-related information and engaging vulnerable people in resilience building behaviors (in addition to including animals in disaster planning initiatives in general). Animals may provide the kind of innovative approach required

  14. Comparison of kinetic and fluid neutral models for attached and detached state

    International Nuclear Information System (INIS)

    Furubayashi, M.; Hoshino, K.; Toma, M.; Hatayama, A.; Coster, D.; Schneider, R.; Bonnin, X.; Kawashima, H.; Asakura, N.; Suzuki, Y.

    2009-01-01

    Neutral behavior has an important role in the transport simulations of the edge plasma. Most of the edge plasma transport codes treat neutral particles by a simple fluid model or a kinetic model. The fluid model allows faster calculations. However, the applicability of the fluid model is limited. In this study, simulation results of JT-60U from kinetic neutral model and fluid neutral model are compared under the attached and detached state, using the 2D edge plasma code package, SOLPS5.0. In the SOL region, no significant differences are observed in the upstream plasma profiles between kinetic and fluid neutral models. However, in the divertor region, large differences are observed in plasma and neutral profiles. Therefore, further optimization of the fluid neutral model should be performed. Otherwise kinetic neutral model should be used to analyze the divertor region.

  15. No Pet or Their Person Left Behind: Increasing the Disaster Resilience of Vulnerable Groups through Animal Attachment, Activities and Networks.

    Science.gov (United States)

    Thompson, Kirrilly; Every, Danielle; Rainbird, Sophia; Cornell, Victoria; Smith, Bradley; Trigg, Joshua

    2014-05-07

    Increased vulnerability to natural disasters has been associated with particular groups in the community. This includes those who are considered de facto vulnerable (children, older people, those with disabilities etc.) and those who own pets (not to mention pets themselves). The potential for reconfiguring pet ownership from a risk factor to a protective factor for natural disaster survival has been recently proposed. But how might this resilience-building proposition apply to vulnerable members of the community who own pets or other animals? This article addresses this important question by synthesizing information about what makes particular groups vulnerable, the challenges to increasing their resilience and how animals figure in their lives. Despite different vulnerabilities, animals were found to be important to the disaster resilience of seven vulnerable groups in Australia. Animal attachment and animal-related activities and networks are identified as underexplored devices for disseminating or 'piggybacking' disaster-related information and engaging vulnerable people in resilience building behaviors (in addition to including animals in disaster planning initiatives in general). Animals may provide the kind of innovative approach required to overcome the challenges in accessing and engaging vulnerable groups. As the survival of humans and animals are so often intertwined, the benefits of increasing the resilience of vulnerable communities through animal attachment is twofold: human and animal lives can be saved together.

  16. No Pet or Their Person Left Behind: Increasing the Disaster Resilience of Vulnerable Groups through Animal Attachment, Activities and Networks

    Directory of Open Access Journals (Sweden)

    Kirrilly Thompson

    2014-05-01

    Full Text Available Increased vulnerability to natural disasters has been associated with particular groups in the community. This includes those who are considered de facto vulnerable (children, older people, those with disabilities etc. and those who own pets (not to mention pets themselves. The potential for reconfiguring pet ownership from a risk factor to a protective factor for natural disaster survival has been recently proposed. But how might this resilience-building proposition apply to vulnerable members of the community who own pets or other animals? This article addresses this important question by synthesizing information about what makes particular groups vulnerable, the challenges to increasing their resilience and how animals figure in their lives. Despite different vulnerabilities, animals were found to be important to the disaster resilience of seven vulnerable groups in Australia. Animal attachment and animal-related activities and networks are identified as underexplored devices for disseminating or ‘piggybacking’ disaster-related information and engaging vulnerable people in resilience building behaviors (in addition to including animals in disaster planning initiatives in general. Animals may provide the kind of innovative approach required to overcome the challenges in accessing and engaging vulnerable groups. As the survival of humans and animals are so often intertwined, the benefits of increasing the resilience of vulnerable communities through animal attachment is twofold: human and animal lives can be saved together.

  17. Attachment, Sexual Assertiveness, and Sexual Outcomes in Women with Provoked Vestibulodynia and Their Partners: A Mediation Model.

    Science.gov (United States)

    Leclerc, Bianca; Bergeron, Sophie; Brassard, Audrey; Bélanger, Claude; Steben, Marc; Lambert, Bernard

    2015-08-01

    Provoked vestibulodynia (PVD) is a prevalent women's sexual pain disorder, which is associated with sexual function difficulties. Attachment theory has been used to understand adult sexual outcomes, providing a useful framework for examining sexual adaptation in couples confronted with PVD. Research to date indicates that anxious and avoidant attachment dimensions correlate with worse sexual outcomes in community and clinical samples. The present study examined the association between attachment, pain, sexual function, and sexual satisfaction in a sample of 101 couples in which the women presented with PVD. The actor-partner interdependence model was used in order to investigate both actor and partner effects. This study also examined the role of sexual assertiveness as a mediator of these associations via structural equation modeling. Women completed measures of pain intensity and both members of the couple completed measures of romantic attachment, sexual assertiveness, sexual function, and satisfaction. Results indicated that attachment dimensions did not predict pain intensity. Both anxious and avoidant attachment were associated with lower sexual satisfaction. Only attachment avoidance predicted lower sexual function in women. Partner effects indicated that higher sexual assertiveness in women predicted higher sexual satisfaction in men. Finally, women's sexual assertiveness was found to be a significant mediator of the relationship between their attachment dimensions, sexual function, and satisfaction. Findings highlight the importance of examining how anxious and avoidant attachment may lead to difficulties in sexual assertiveness and to less satisfying sexual interactions in couples where women suffer from PVD.

  18. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo

    2015-09-15

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

  19. Network modelling methods for FMRI.

    Science.gov (United States)

    Smith, Stephen M; Miller, Karla L; Salimi-Khorshidi, Gholamreza; Webster, Matthew; Beckmann, Christian F; Nichols, Thomas E; Ramsey, Joseph D; Woolrich, Mark W

    2011-01-15

    There is great interest in estimating brain "networks" from FMRI data. This is often attempted by identifying a set of functional "nodes" (e.g., spatial ROIs or ICA maps) and then conducting a connectivity analysis between the nodes, based on the FMRI timeseries associated with the nodes. Analysis methods range from very simple measures that consider just two nodes at a time (e.g., correlation between two nodes' timeseries) to sophisticated approaches that consider all nodes simultaneously and estimate one global network model (e.g., Bayes net models). Many different methods are being used in the literature, but almost none has been carefully validated or compared for use on FMRI timeseries data. In this work we generate rich, realistic simulated FMRI data for a wide range of underlying networks, experimental protocols and problematic confounds in the data, in order to compare different connectivity estimation approaches. Our results show that in general correlation-based approaches can be quite successful, methods based on higher-order statistics are less sensitive, and lag-based approaches perform very poorly. More specifically: there are several methods that can give high sensitivity to network connection detection on good quality FMRI data, in particular, partial correlation, regularised inverse covariance estimation and several Bayes net methods; however, accurate estimation of connection directionality is more difficult to achieve, though Patel's τ can be reasonably successful. With respect to the various confounds added to the data, the most striking result was that the use of functionally inaccurate ROIs (when defining the network nodes and extracting their associated timeseries) is extremely damaging to network estimation; hence, results derived from inappropriate ROI definition (such as via structural atlases) should be regarded with great caution. Copyright © 2010 Elsevier Inc. All rights reserved.

  20. Structural Equation Model of Smartphone Addiction Based on Adult Attachment Theory: Mediating Effects of Loneliness and Depression

    OpenAIRE

    EunYoung Kim, PhD; Inhyo Cho, PhD; Eun Joo Kim, PhD

    2017-01-01

    Purpose: This study investigated the mediating effects of loneliness and depression on the relationship between adult attachment and smartphone addiction in university students. Methods: A total of 200 university students participated in this study. The data was analysed using descriptive statistics, correlation analysis, and structural equation modeling. Results: There were significant positive relationships between attachment anxiety, loneliness, depression, and smartphone addiction. ...

  1. American College Football Division I Team Attachment: A Model for Sponsorship Effectiveness

    Directory of Open Access Journals (Sweden)

    Hsin-Chung Chen

    2013-10-01

    Full Text Available The purpose of this study was to examine sponsorship effectiveness at the Division I level, including the relationship between fans and sponsors. To collect the necessary data, the 13-item questionnaire was disseminated at two college football games by volunteer sampling at three Division I universities in the United States. With a total of 407 respondents, LISREL 8.52 and SPSS 17.0 were used to analyze the data for descriptive statistics, CFA, and SEM. By utilizing SEM, the variables of team attachment, sponsor image, word of mouth, and purchase intentions fit the proposed model.  Pragmatically, the significance of team attachment can be understated in its role as an initial construct to begin the sponsorship process. Considering the construct of sponsor image as a mediating variable, sponsor image played an important role to anticipate an increase in positive word of mouth or an increase in consumer purchase intentions.

  2. Modelling Facebook Usage among University Students in Thailand: The Role of Emotional Attachment in an Extended Technology Acceptance Model

    Science.gov (United States)

    Teo, Timothy

    2016-01-01

    The aim of this study is to examine the factors that influenced the use of Facebook among university students. Using an extended technology acceptance model (TAM) with emotional attachment (EA) as an external variable, a sample of 498 students from a public-funded Thailand university were surveyed on their responses to five variables hypothesized…

  3. Research on the model of home networking

    Science.gov (United States)

    Yun, Xiang; Feng, Xiancheng

    2007-11-01

    It is the research hotspot of current broadband network to combine voice service, data service and broadband audio-video service by IP protocol to transport various real time and mutual services to terminal users (home). Home Networking is a new kind of network and application technology which can provide various services. Home networking is called as Digital Home Network. It means that PC, home entertainment equipment, home appliances, Home wirings, security, illumination system were communicated with each other by some composing network technology, constitute a networking internal home, and connect with WAN by home gateway. It is a new network technology and application technology, and can provide many kinds of services inside home or between homes. Currently, home networking can be divided into three kinds: Information equipment, Home appliances, Communication equipment. Equipment inside home networking can exchange information with outer networking by home gateway, this information communication is bidirectional, user can get information and service which provided by public networking by using home networking internal equipment through home gateway connecting public network, meantime, also can get information and resource to control the internal equipment which provided by home networking internal equipment. Based on the general network model of home networking, there are four functional entities inside home networking: HA, HB, HC, and HD. (1) HA (Home Access) - home networking connects function entity; (2) HB (Home Bridge) Home networking bridge connects function entity; (3) HC (Home Client) - Home networking client function entity; (4) HD (Home Device) - decoder function entity. There are many physical ways to implement four function entities. Based on theses four functional entities, there are reference model of physical layer, reference model of link layer, reference model of IP layer and application reference model of high layer. In the future home network

  4. Mathematical Modelling Plant Signalling Networks

    KAUST Repository

    Muraro, D.

    2013-01-01

    During the last two decades, molecular genetic studies and the completion of the sequencing of the Arabidopsis thaliana genome have increased knowledge of hormonal regulation in plants. These signal transduction pathways act in concert through gene regulatory and signalling networks whose main components have begun to be elucidated. Our understanding of the resulting cellular processes is hindered by the complex, and sometimes counter-intuitive, dynamics of the networks, which may be interconnected through feedback controls and cross-regulation. Mathematical modelling provides a valuable tool to investigate such dynamics and to perform in silico experiments that may not be easily carried out in a laboratory. In this article, we firstly review general methods for modelling gene and signalling networks and their application in plants. We then describe specific models of hormonal perception and cross-talk in plants. This mathematical analysis of sub-cellular molecular mechanisms paves the way for more comprehensive modelling studies of hormonal transport and signalling in a multi-scale setting. © EDP Sciences, 2013.

  5. EFL Learners' Home Culture Attachment and their Attitudes towards English Language Learning: A structural equation modeling approach

    Directory of Open Access Journals (Sweden)

    Zahra Sharifi Feriz

    2017-10-01

    Full Text Available The purpose of the present study is to examine home culture attachment construct and its underlying variables among Iranian English as Foreign Language learners as well as their attitudes towards English language learning. Pearson correlation is used with a sample of 411 English major university students from different provinces in Iran, mainly Khorasan Razavi, Khoran Jonoubi and Sistan Baluchestan participated in this study. As for the quantitative phase of data collection, the study employed home culture attachment and attitude towards English language learning questionnaires. The reliability and validity of these questionnaires are reported. A home culture attachment model and an attitude model are also developed and tested using structural equation modeling. The results suggest that all three subscales of attitudes (emotional, behavioral, and cognitive are positive and significant predictors of students' western attachment. From three subscales of attitude, only behavioral attitude is negative and significant predictors of students' religious attachment. In addition, Iranian attachment is influenced by cognitive attitudes and emotional attitudes. Besides, cognitive attitude is a positive and significant predictor of students' cultural attachment. It is also found that, artistic attachment is influenced by behavioral attitudes and emotional attitudes. Finally, the pedagogical implications are discussed in light of foreign language achievement.

  6. Energy modelling in sensor networks

    Science.gov (United States)

    Schmidt, D.; Krämer, M.; Kuhn, T.; Wehn, N.

    2007-06-01

    Wireless sensor networks are one of the key enabling technologies for the vision of ambient intelligence. Energy resources for sensor nodes are very scarce. A key challenge is the design of energy efficient communication protocols. Models of the energy consumption are needed to accurately simulate the efficiency of a protocol or application design, and can also be used for automatic energy optimizations in a model driven design process. We propose a novel methodology to create models for sensor nodes based on few simple measurements. In a case study the methodology was used to create models for MICAz nodes. The models were integrated in a simulation environment as well as in a SDL runtime framework of a model driven design process. Measurements on a test application that was created automatically from an SDL specification showed an 80% reduction in energy consumption compared to an implementation without power saving strategies.

  7. Modeling Aggregation Processes of Lennard-Jones particles Via Stochastic Networks

    Science.gov (United States)

    Forman, Yakir; Cameron, Maria

    2017-07-01

    We model an isothermal aggregation process of particles/atoms interacting according to the Lennard-Jones pair potential by mapping the energy landscapes of each cluster size N onto stochastic networks, computing transition probabilities from the network for an N-particle cluster to the one for N+1, and connecting these networks into a single joint network. The attachment rate is a control parameter. The resulting network representing the aggregation of up to 14 particles contains 6427 vertices. It is not only time-irreversible but also reducible. To analyze its transient dynamics, we introduce the sequence of the expected initial and pre-attachment distributions and compute them for a wide range of attachment rates and three values of temperature. As a result, we find the configurations most likely to be observed in the process of aggregation for each cluster size. We examine the attachment process and conduct a structural analysis of the sets of local energy minima for every cluster size. We show that both processes taking place in the network, attachment and relaxation, lead to the dominance of icosahedral packing in small (up to 14 atom) clusters.

  8. Exposure to family violence and attachment styles as predictors of dating violence perpetration among men and women: a mediational model.

    Science.gov (United States)

    Lee, Mary; Reese-Weber, Marla; Kahn, Jeffrey H

    2014-01-01

    This study examined a multiple mediator model explaining how sibling perpetration and one's attachment style mediate the relation between parent-to-child victimization and dating violence perpetration. A sample of undergraduate students (n = 392 women, n = 89 men) completed measures of the aforementioned variables on an Internet survey. For men, path analyses found no mediation; parent-to-child victimization had a direct association with dating violence perpetration, no association was found between sibling perpetration and dating violence perpetration, and attachment anxiety, but not attachment avoidance, was positively associated with dating violence perpetration for men. For women, the hypothesized mediation model was supported; parent-to-child victimization had a direct association with dating violence perpetration, and sibling perpetration and attachment anxiety served as mediating variables. Attachment avoidance was not associated with dating violence perpetration for women. Implications for future research and clinical practice are discussed.

  9. Parent-Child Attachment Working Models and Self-Esteem in Adolescence.

    Science.gov (United States)

    McCormick, Cynthia B.; Kennedy, Janice H.

    1994-01-01

    Continuity over time in parent-child attachments and the relationship between these attachments and current self-esteem were studied for 218 nonparent college students. Results indicate continuity over time of attachment. Self-esteem is related to childhood and adolescent styles of attachment and dimensions of independence encouragement and…

  10. Biological transportation networks: Modeling and simulation

    KAUST Repository

    Albi, Giacomo; Artina, Marco; Foransier, Massimo; Markowich, Peter A.

    2015-01-01

    We present a model for biological network formation originally introduced by Cai and Hu [Adaptation and optimization of biological transport networks, Phys. Rev. Lett. 111 (2013) 138701]. The modeling of fluid transportation (e.g., leaf venation

  11. N-doped graphene-carbon nanotube hybrid networks attaching with gold nanoparticles for glucose non-enzymatic sensor.

    Science.gov (United States)

    Jeong, Hun; Nguyen, Dang Mao; Lee, Min Sang; Kim, Hong Gun; Ko, Sang Cheol; Kwac, Lee Ku

    2018-09-01

    Herein, we successfully developed a novel three dimensional (3D) opened networks based on nitrogen doped graphene‑carbon nanotubes attaching with gold nanoparticles (N-GR-CNTs/AuNPs) to apply for non-enzymatic glucose determination. It was demonstrated that the N-GR-CNTs/AuNPs modified electrode exhibited good behavior for glucose detection with a long linear range of 2 μM to 19.6 mM, high sensitivity of 0.9824 μA·mM -1 ·cm -2 , low detection limit of 500 nM, and negligible interference effect. The high performance of the N-GR-CNTs/AuNPs based sensor was assumed due to the outstanding catalytic activity of AuNPs well dispersing on N-GR-CNTs networks, which exhibited as a perfect supporting scaffold due to the enhanced electrical conductivity and large surface area. The obtained results indicated that the N-GR-CNTs/AuNPs hybrid is highly promising for sensitive and selective detection of glucose in sensor application. Copyright © 2018 Elsevier B.V. All rights reserved.

  12. Brand Marketing Model on Social Networks

    Directory of Open Access Journals (Sweden)

    Jolita Jezukevičiūtė

    2014-04-01

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

  13. A novel Direct Small World network model

    Directory of Open Access Journals (Sweden)

    LIN Tao

    2016-10-01

    Full Text Available There is a certain degree of redundancy and low efficiency of existing computer networks.This paper presents a novel Direct Small World network model in order to optimize networks.In this model,several nodes construct a regular network.Then,randomly choose and replot some nodes to generate Direct Small World network iteratively.There is no change in average distance and clustering coefficient.However,the network performance,such as hops,is improved.The experiments prove that compared to traditional small world network,the degree,average of degree centrality and average of closeness centrality are lower in Direct Small World network.This illustrates that the nodes in Direct Small World networks are closer than Watts-Strogatz small world network model.The Direct Small World can be used not only in the communication of the community information,but also in the research of epidemics.

  14. RMBNToolbox: random models for biochemical networks

    Directory of Open Access Journals (Sweden)

    Niemi Jari

    2007-05-01

    Full Text Available Abstract Background There is an increasing interest to model biochemical and cell biological networks, as well as to the computational analysis of these models. The development of analysis methodologies and related software is rapid in the field. However, the number of available models is still relatively small and the model sizes remain limited. The lack of kinetic information is usually the limiting factor for the construction of detailed simulation models. Results We present a computational toolbox for generating random biochemical network models which mimic real biochemical networks. The toolbox is called Random Models for Biochemical Networks. The toolbox works in the Matlab environment, and it makes it possible to generate various network structures, stoichiometries, kinetic laws for reactions, and parameters therein. The generation can be based on statistical rules and distributions, and more detailed information of real biochemical networks can be used in situations where it is known. The toolbox can be easily extended. The resulting network models can be exported in the format of Systems Biology Markup Language. Conclusion While more information is accumulating on biochemical networks, random networks can be used as an intermediate step towards their better understanding. Random networks make it possible to study the effects of various network characteristics to the overall behavior of the network. Moreover, the construction of artificial network models provides the ground truth data needed in the validation of various computational methods in the fields of parameter estimation and data analysis.

  15. Attachments for fire modeling for Building 221-T, T Plant canyon deck and railroad tunnel

    International Nuclear Information System (INIS)

    Oar, D.L.

    1995-01-01

    The purpose of this attachment is to provide historical information and documentation for Document No. WHC-SD-CP-ANAL-008 Rev 0, ''Fire Modeling for Building 221-T--T Plant Canyon Deck and Railroad Tunnel'', dated September 29, 1994. This data compilation contains the following: Resumes of the Technical Director, Senior Engineer and Junior Engineer; Review and Comment Record; Software Files; CFAST Input and Output Files; Calculation Control Sheets; and Estimating Sprinkler Actuation Time in the Canyon and Railroad Tunnel. The T Plant was originally a fuel reprocessing facility. It was modified later to decontaminate and repair PuRex process equipment

  16. Brand Marketing Model on Social Networks

    OpenAIRE

    Jolita Jezukevičiūtė; Vida Davidavičienė

    2014-01-01

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

  17. Brand marketing model on social networks

    OpenAIRE

    Jezukevičiūtė, Jolita; Davidavičienė, Vida

    2014-01-01

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

  18. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  19. Network bandwidth utilization forecast model on high bandwidth networks

    Energy Technology Data Exchange (ETDEWEB)

    Yoo, Wuchert (William) [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Sim, Alex [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)

    2015-03-30

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2%. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  20. An acoustical model based monitoring network

    NARCIS (Netherlands)

    Wessels, P.W.; Basten, T.G.H.; Eerden, F.J.M. van der

    2010-01-01

    In this paper the approach for an acoustical model based monitoring network is demonstrated. This network is capable of reconstructing a noise map, based on the combination of measured sound levels and an acoustic model of the area. By pre-calculating the sound attenuation within the network the

  1. Spinal Cord Injury Model System Information Network

    Science.gov (United States)

    ... the UAB-SCIMS More The UAB-SCIMS Information Network The University of Alabama at Birmingham Spinal Cord Injury Model System (UAB-SCIMS) maintains this Information Network as a resource to promote knowledge in the ...

  2. Eight challenges for network epidemic models

    Directory of Open Access Journals (Sweden)

    Lorenzo Pellis

    2015-03-01

    Full Text Available Networks offer a fertile framework for studying the spread of infection in human and animal populations. However, owing to the inherent high-dimensionality of networks themselves, modelling transmission through networks is mathematically and computationally challenging. Even the simplest network epidemic models present unanswered questions. Attempts to improve the practical usefulness of network models by including realistic features of contact networks and of host–pathogen biology (e.g. waning immunity have made some progress, but robust analytical results remain scarce. A more general theory is needed to understand the impact of network structure on the dynamics and control of infection. Here we identify a set of challenges that provide scope for active research in the field of network epidemic models.

  3. Entropy Characterization of Random Network Models

    Directory of Open Access Journals (Sweden)

    Pedro J. Zufiria

    2017-06-01

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

  4. The model of social crypto-network

    Directory of Open Access Journals (Sweden)

    Марк Миколайович Орел

    2015-06-01

    Full Text Available The article presents the theoretical model of social network with the enhanced mechanism of privacy policy. It covers the problems arising in the process of implementing the mentioned type of network. There are presented the methods of solving problems arising in the process of building the social network with privacy policy. It was built a theoretical model of social networks with enhanced information protection methods based on information and communication blocks

  5. Introducing Synchronisation in Deterministic Network Models

    DEFF Research Database (Denmark)

    Schiøler, Henrik; Jessen, Jan Jakob; Nielsen, Jens Frederik D.

    2006-01-01

    The paper addresses performance analysis for distributed real time systems through deterministic network modelling. Its main contribution is the introduction and analysis of models for synchronisation between tasks and/or network elements. Typical patterns of synchronisation are presented leading...... to the suggestion of suitable network models. An existing model for flow control is presented and an inherent weakness is revealed and remedied. Examples are given and numerically analysed through deterministic network modelling. Results are presented to highlight the properties of the suggested models...

  6. Bayesian Network Webserver: a comprehensive tool for biological network modeling.

    Science.gov (United States)

    Ziebarth, Jesse D; Bhattacharya, Anindya; Cui, Yan

    2013-11-01

    The Bayesian Network Webserver (BNW) is a platform for comprehensive network modeling of systems genetics and other biological datasets. It allows users to quickly and seamlessly upload a dataset, learn the structure of the network model that best explains the data and use the model to understand relationships between network variables. Many datasets, including those used to create genetic network models, contain both discrete (e.g. genotype) and continuous (e.g. gene expression traits) variables, and BNW allows for modeling hybrid datasets. Users of BNW can incorporate prior knowledge during structure learning through an easy-to-use structural constraint interface. After structure learning, users are immediately presented with an interactive network model, which can be used to make testable hypotheses about network relationships. BNW, including a downloadable structure learning package, is available at http://compbio.uthsc.edu/BNW. (The BNW interface for adding structural constraints uses HTML5 features that are not supported by current version of Internet Explorer. We suggest using other browsers (e.g. Google Chrome or Mozilla Firefox) when accessing BNW). ycui2@uthsc.edu. Supplementary data are available at Bioinformatics online.

  7. The Structural Model in Parenting Style, Attachment Style, Self-regulation and Self-esteem for Smartphone Addiction

    Directory of Open Access Journals (Sweden)

    Kwan Hoi Ching

    2017-08-01

    Full Text Available Excessive smartphone usage has become a highly controversial and substantial worldwide issue. This paper explores the complexities and challenges of smartphone addiction with a particular focus on parenting styles, attachment, and self-regulation. Convenience sampling was used to gather data from 211 university students in Hong Kong (138 females/74 males through their responses to four questionnaires. One structural equation model was formed successfully which indicated that parenting style (authoritative or permissive could be a reasonable predictor of attachment style (secure or dismissive and self-regulation (impulse control or goal setting for smartphone addictions (positive anticipation, withdrawal, cyberspace relationship or overuse. Parenting style was a positive correlate to predict attachment, while the attachment positive correlated to predict self-regulation. Self-regulation was a negative correlate to smartphone addiction. It was revealed that a positive parenting style and positive attachment style could form a significant model with self-regulation and smartphone addiction. Furthermore, secure attachment had higher mediation effect, while impulse control and goal setting behavior had a fair mediation power over influencing addiction tendency. This model helped explore the relationships between smartphone addiction and other constructs in educational psychology. Based on findings, educators can gain insights into how parenting and self-regulation can influence the tendency towards excessive smartphone usage. More educational programs which aim at promoting adequate parenting skills, motivating children through self-regulation and goal setting, is proposed through this study.

  8. Self-assembly model, hepatocytes attachment and inflammatory response for silk fibroin/chitosan scaffolds

    International Nuclear Information System (INIS)

    She Zhending; Feng Qingling; Liu Weiqiang

    2009-01-01

    Silk fibroin is an attractive natural fibrous protein for biomedical application due to its good biocompatibility and high tensile strength. Silk fibroin is apt to form a sheet-like structure during the freeze-drying process, which is not suitable for the scaffold of tissue engineering. In our former study, the adding of chitosan promoted the self-assembly of silk fibroin/chitosan (SFCS) into a three-dimensional (3D) homogeneous porous structure. In this study, a model of the self-assembly is proposed; furthermore, hepatocytes attachment and inflammatory response for the SFCS scaffold were examined. The rigid chain of chitosan may be used as a template for β-sheet formation of silk fibroin, and this may break the sheet structure of the silk fibroin scaffold and promote the formation of a 3D porous structure of the SFCS scaffold. Compared with the polylactic glycolic acid scaffold, the SFCS scaffold further facilitates the attachment of hepatocytes. To investigate the inflammatory response, SFCS scaffolds were implanted into the greater omentum of rats. From the results of implantation, we could demonstrate in vivo that the implantation of SFCS scaffolds resulted in only slight inflammation. Keeping the good histocompatibility and combining the advantages of both fibroin and chitosan, the SFCS scaffold could be a prominent candidate for soft tissue engineering, for example, in the liver.

  9. Self-assembly model, hepatocytes attachment and inflammatory response for silk fibroin/chitosan scaffolds

    Energy Technology Data Exchange (ETDEWEB)

    She Zhending; Feng Qingling [State Key Laboratory of New Ceramics and Fine Processing, Department of Materials Science and Engineering, Tsinghua University, Beijing 100084 (China); Liu Weiqiang, E-mail: biomater@mail.tsinghua.edu.c [Center for Advanced Materials and Biotechnology, Research Institute of Tsinghua University in Shenzhen, Shenzhen 518057 (China)

    2009-08-15

    Silk fibroin is an attractive natural fibrous protein for biomedical application due to its good biocompatibility and high tensile strength. Silk fibroin is apt to form a sheet-like structure during the freeze-drying process, which is not suitable for the scaffold of tissue engineering. In our former study, the adding of chitosan promoted the self-assembly of silk fibroin/chitosan (SFCS) into a three-dimensional (3D) homogeneous porous structure. In this study, a model of the self-assembly is proposed; furthermore, hepatocytes attachment and inflammatory response for the SFCS scaffold were examined. The rigid chain of chitosan may be used as a template for beta-sheet formation of silk fibroin, and this may break the sheet structure of the silk fibroin scaffold and promote the formation of a 3D porous structure of the SFCS scaffold. Compared with the polylactic glycolic acid scaffold, the SFCS scaffold further facilitates the attachment of hepatocytes. To investigate the inflammatory response, SFCS scaffolds were implanted into the greater omentum of rats. From the results of implantation, we could demonstrate in vivo that the implantation of SFCS scaffolds resulted in only slight inflammation. Keeping the good histocompatibility and combining the advantages of both fibroin and chitosan, the SFCS scaffold could be a prominent candidate for soft tissue engineering, for example, in the liver.

  10. Hamiltonian dynamics of preferential attachment

    International Nuclear Information System (INIS)

    Zuev, Konstantin; Papadopoulos, Fragkiskos; Krioukov, Dmitri

    2016-01-01

    Prediction and control of network dynamics are grand-challenge problems in network science. The lack of understanding of fundamental laws driving the dynamics of networks is among the reasons why many practical problems of great significance remain unsolved for decades. Here we study the dynamics of networks evolving according to preferential attachment (PA), known to approximate well the large-scale growth dynamics of a variety of real networks. We show that this dynamics is Hamiltonian, thus casting the study of complex networks dynamics to the powerful canonical formalism, in which the time evolution of a dynamical system is described by Hamilton’s equations. We derive the explicit form of the Hamiltonian that governs network growth in PA. This Hamiltonian turns out to be nearly identical to graph energy in the configuration model, which shows that the ensemble of random graphs generated by PA is nearly identical to the ensemble of random graphs with scale-free degree distributions. In other words, PA generates nothing but random graphs with power-law degree distribution. The extension of the developed canonical formalism for network analysis to richer geometric network models with non-degenerate groups of symmetries may eventually lead to a system of equations describing network dynamics at small scales. (paper)

  11. Role of Fimbriae, Flagella and Cellulose on the Attachment of Salmonella Typhimurium ATCC 14028 to Plant Cell Wall Models.

    Directory of Open Access Journals (Sweden)

    Michelle S F Tan

    Full Text Available Cases of foodborne disease caused by Salmonella are frequently associated with the consumption of minimally processed produce. Bacterial cell surface components are known to be important for the attachment of bacterial pathogens to fresh produce. The role of these extracellular structures in Salmonella attachment to plant cell walls has not been investigated in detail. We investigated the role of flagella, fimbriae and cellulose on the attachment of Salmonella Typhimurium ATCC 14028 and a range of isogenic deletion mutants (ΔfliC fljB, ΔbcsA, ΔcsgA, ΔcsgA bcsA and ΔcsgD to bacterial cellulose (BC-based plant cell wall models [BC-Pectin (BCP, BC-Xyloglucan (BCX and BC-Pectin-Xyloglucan (BCPX] after growth at different temperatures (28°C and 37°C. We found that all three cell surface components were produced at 28°C but only the flagella was produced at 37°C. Flagella appeared to be most important for attachment (reduction of up to 1.5 log CFU/cm2 although both cellulose and fimbriae also aided in attachment. The csgD deletion mutant, which lacks both cellulose and fimbriae, showed significantly higher attachment as compared to wild type cells at 37°C. This may be due to the increased expression of flagella-related genes which are also indirectly regulated by the csgD gene. Our study suggests that bacterial attachment to plant cell walls is a complex process involving many factors. Although flagella, cellulose and fimbriae all aid in attachment, these structures are not the only mechanism as no strain was completely defective in its attachment.

  12. How to model wireless mesh networks topology

    International Nuclear Information System (INIS)

    Sanni, M L; Hashim, A A; Anwar, F; Ali, S; Ahmed, G S M

    2013-01-01

    The specification of network connectivity model or topology is the beginning of design and analysis in Computer Network researches. Wireless Mesh Networks is an autonomic network that is dynamically self-organised, self-configured while the mesh nodes establish automatic connectivity with the adjacent nodes in the relay network of wireless backbone routers. Researches in Wireless Mesh Networks range from node deployment to internetworking issues with sensor, Internet and cellular networks. These researches require modelling of relationships and interactions among nodes including technical characteristics of the links while satisfying the architectural requirements of the physical network. However, the existing topology generators model geographic topologies which constitute different architectures, thus may not be suitable in Wireless Mesh Networks scenarios. The existing methods of topology generation are explored, analysed and parameters for their characterisation are identified. Furthermore, an algorithm for the design of Wireless Mesh Networks topology based on square grid model is proposed in this paper. The performance of the topology generated is also evaluated. This research is particularly important in the generation of a close-to-real topology for ensuring relevance of design to the intended network and validity of results obtained in Wireless Mesh Networks researches

  13. Model checking mobile ad hoc networks

    NARCIS (Netherlands)

    Ghassemi, Fatemeh; Fokkink, Wan

    2016-01-01

    Modeling arbitrary connectivity changes within mobile ad hoc networks (MANETs) makes application of automated formal verification challenging. We use constrained labeled transition systems as a semantic model to represent mobility. To model check MANET protocols with respect to the underlying

  14. Modeling Interpersonal Correlates of Condomless Anal Sex among Gay and Bisexual Men: An Application of Attachment Theory.

    Science.gov (United States)

    Starks, Tyrel J; Castro, Michael A; Castiblanco, Juan P; Millar, Brett M

    2017-05-01

    The existing literature has identified that beliefs about the interpersonal meaning of condom use are a significant predictor of condomless anal sex (CAS). Some have suggested that condom use in this context may function as a form of nonverbal communication. This study utilized attachment theory as a framework and tested a hypothesized model linking adult attachment to CAS through communication skills and condom expectancies. An online survey was completed by 122 single, HIV-negative gay and bisexual (GB) men living in the U.S. They completed measures of adult attachment (anxious and avoidant), condom expectancies regarding intimacy and pleasure interference, communication skills, self-assessed mate value, and recent CAS with casual partners. There was a significant, positive bivariate association between anxious attachment and receptive CAS. In path model analyses, two over-arching pathways emerged. In the other-oriented pathway, anxious attachment, self-perceived mate value, and emotional communication predicted the belief that condoms interfere with intimacy. In turn, intimacy interference expectancies were positively associated with the odds of receptive CAS. In the self-oriented pathway, assertive communication skills mediated a link between avoidant attachment and the belief that condoms interfere with sexual pleasure. Pleasure interference expectancies were positively associated with the odds of insertive CAS. The findings highlight the importance of relational or interpersonal concerns in sexual risk-taking among single GB men. Attachment theory may serve as a framework for organizing these interpersonal correlates of CAS. Results are consistent with the conceptualization of condom use as a form of nonverbal attachment-related behavior. Implications for sexual health and risk-reduction interventions are explored in this context.

  15. Agent-based modeling and network dynamics

    CERN Document Server

    Namatame, Akira

    2016-01-01

    The book integrates agent-based modeling and network science. It is divided into three parts, namely, foundations, primary dynamics on and of social networks, and applications. The book begins with the network origin of agent-based models, known as cellular automata, and introduce a number of classic models, such as Schelling’s segregation model and Axelrod’s spatial game. The essence of the foundation part is the network-based agent-based models in which agents follow network-based decision rules. Under the influence of the substantial progress in network science in late 1990s, these models have been extended from using lattices into using small-world networks, scale-free networks, etc. The book also shows that the modern network science mainly driven by game-theorists and sociophysicists has inspired agent-based social scientists to develop alternative formation algorithms, known as agent-based social networks. The book reviews a number of pioneering and representative models in this family. Upon the gi...

  16. Attachment and Psychopathology

    Directory of Open Access Journals (Sweden)

    Mehmet Fatih Ustundag

    2011-06-01

    Full Text Available The type of attachment defined in the early stages of life and thought to be continuous, is a phenomenon that shapes the pattern of how a person makes contact with others. The clinical appearance of every type of attachment is different and each one has prospective and retrospective phenomenological reflections. In all stages of life and in close relationships, it can be observed if a person gets in close contact with someone else and if this relation bears supportive and protective qualities. According to attachment theorists, once it is defined as safe or unsafe during nursing period, it shows little change. Starting from Bowlby’s work, unsafe attachment type is considered as the determining factor of psychopathology in the later periods of life, while safe attachment is considered as in relation with healthy processes. The nature’s original model is safe attachment. Anxious/indecisive attachment, an unsafe attachment type, is associated with anxiety disorders and depressive disorder, while avoidant attachment is associated with behavior disorder and other extroverted pathologies. Disorganized/disoriented attachment is considered to be together with dissociative disorder. The aim of this paper is to review attachment theory and the relation between attachment and psychopathology.

  17. Nonparametric Bayesian Modeling of Complex Networks

    DEFF Research Database (Denmark)

    Schmidt, Mikkel Nørgaard; Mørup, Morten

    2013-01-01

    an infinite mixture model as running example, we go through the steps of deriving the model as an infinite limit of a finite parametric model, inferring the model parameters by Markov chain Monte Carlo, and checking the model?s fit and predictive performance. We explain how advanced nonparametric models......Modeling structure in complex networks using Bayesian nonparametrics makes it possible to specify flexible model structures and infer the adequate model complexity from the observed data. This article provides a gentle introduction to nonparametric Bayesian modeling of complex networks: Using...

  18. Influence of Bundle Diameter and Attachment Point on Kinematic Behavior in Double Bundle Anterior Cruciate Ligament Reconstruction Using Computational Model

    Directory of Open Access Journals (Sweden)

    Oh Soo Kwon

    2014-01-01

    Full Text Available A protocol to choose the graft diameter attachment point of each bundle has not yet been determined since they are usually dependent on a surgeon’s preference. Therefore, the influence of bundle diameters and attachment points on the kinematics of the knee joint needs to be quantitatively analyzed. A three-dimensional knee model was reconstructed with computed tomography images of a 26-year-old man. Based on the model, models of double bundle anterior cruciate ligament (ACL reconstruction were developed. The anterior tibial translations for the anterior drawer test and the internal tibial rotation for the pivot shift test were investigated according to variation of bundle diameters and attachment points. For the model in this study, the knee kinematics after the double bundle ACL reconstruction were dependent on the attachment point and not much influenced by the bundle diameter although larger sized anterior-medial bundles provided increased stability in the knee joint. Therefore, in the clinical setting, the bundle attachment point needs to be considered prior to the bundle diameter, and the current selection method of graft diameters for both bundles appears justified.

  19. Network structure exploration via Bayesian nonparametric models

    International Nuclear Information System (INIS)

    Chen, Y; Wang, X L; Xiang, X; Tang, B Z; Bu, J Z

    2015-01-01

    Complex networks provide a powerful mathematical representation of complex systems in nature and society. To understand complex networks, it is crucial to explore their internal structures, also called structural regularities. The task of network structure exploration is to determine how many groups there are in a complex network and how to group the nodes of the network. Most existing structure exploration methods need to specify either a group number or a certain type of structure when they are applied to a network. In the real world, however, the group number and also the certain type of structure that a network has are usually unknown in advance. To explore structural regularities in complex networks automatically, without any prior knowledge of the group number or the certain type of structure, we extend a probabilistic mixture model that can handle networks with any type of structure but needs to specify a group number using Bayesian nonparametric theory. We also propose a novel Bayesian nonparametric model, called the Bayesian nonparametric mixture (BNPM) model. Experiments conducted on a large number of networks with different structures show that the BNPM model is able to explore structural regularities in networks automatically with a stable, state-of-the-art performance. (paper)

  20. Stochastic dynamical model of a growing citation network based on a self-exciting point process.

    Science.gov (United States)

    Golosovsky, Michael; Solomon, Sorin

    2012-08-31

    We put under experimental scrutiny the preferential attachment model that is commonly accepted as a generating mechanism of the scale-free complex networks. To this end we chose a citation network of physics papers and traced the citation history of 40,195 papers published in one year. Contrary to common belief, we find that the citation dynamics of the individual papers follows the superlinear preferential attachment, with the exponent α=1.25-1.3. Moreover, we show that the citation process cannot be described as a memoryless Markov chain since there is a substantial correlation between the present and recent citation rates of a paper. Based on our findings we construct a stochastic growth model of the citation network, perform numerical simulations based on this model and achieve an excellent agreement with the measured citation distributions.

  1. Structural Equation Model of Smartphone Addiction Based on Adult Attachment Theory: Mediating Effects of Loneliness and Depression

    Directory of Open Access Journals (Sweden)

    EunYoung Kim, PhD

    2017-06-01

    Conclusion: The results suggest there are mediating effects of loneliness and depression in the relationship between attachment anxiety and smartphone addiction. The hypothesized model was found to be a suitable model for predicting smartphone addiction among university students. Future study is required to find a causal path to prevent smartphone addiction among university students.

  2. Modelling the structure of complex networks

    DEFF Research Database (Denmark)

    Herlau, Tue

    networks has been independently studied as mathematical objects in their own right. As such, there has been both an increased demand for statistical methods for complex networks as well as a quickly growing mathematical literature on the subject. In this dissertation we explore aspects of modelling complex....... The next chapters will treat some of the various symmetries, representer theorems and probabilistic structures often deployed in the modelling complex networks, the construction of sampling methods and various network models. The introductory chapters will serve to provide context for the included written...

  3. Building functional networks of spiking model neurons.

    Science.gov (United States)

    Abbott, L F; DePasquale, Brian; Memmesheimer, Raoul-Martin

    2016-03-01

    Most of the networks used by computer scientists and many of those studied by modelers in neuroscience represent unit activities as continuous variables. Neurons, however, communicate primarily through discontinuous spiking. We review methods for transferring our ability to construct interesting networks that perform relevant tasks from the artificial continuous domain to more realistic spiking network models. These methods raise a number of issues that warrant further theoretical and experimental study.

  4. Modeling, Optimization & Control of Hydraulic Networks

    DEFF Research Database (Denmark)

    Tahavori, Maryamsadat

    2014-01-01

    . The nonlinear network model is derived based on the circuit theory. A suitable projection is used to reduce the state vector and to express the model in standard state-space form. Then, the controllability of nonlinear nonaffine hydraulic networks is studied. The Lie algebra-based controllability matrix is used......Water supply systems consist of a number of pumping stations, which deliver water to the customers via pipeline networks and elevated reservoirs. A huge amount of drinking water is lost before it reaches to end-users due to the leakage in pipe networks. A cost effective solution to reduce leakage...... in water network is pressure management. By reducing the pressure in the water network, the leakage can be reduced significantly. Also it reduces the amount of energy consumption in water networks. The primary purpose of this work is to develop control algorithms for pressure control in water supply...

  5. Adolescent attachment, family functioning and depressive symptoms ...

    African Journals Online (AJOL)

    The Self-Report of Family Inventory (SFI), Experiences of Close Relationships Scale (ECR), Network of Relationships Inventory (NRI), Children's Depression Inventory (CDI) and Child Behavior Checklist (CBCL) were used to assess depression, parental support and attachment. Results. Two models were examined: one ...

  6. Attachment Theory and Theory of Planned Behavior: An Integrative Model Predicting Underage Drinking

    Science.gov (United States)

    Lac, Andrew; Crano, William D.; Berger, Dale E.; Alvaro, Eusebio M.

    2013-01-01

    Research indicates that peer and maternal bonds play important but sometimes contrasting roles in the outcomes of children. Less is known about attachment bonds to these 2 reference groups in young adults. Using a sample of 351 participants (18 to 20 years of age), the research integrated two theoretical traditions: attachment theory and theory of…

  7. Port Hamiltonian modeling of Power Networks

    NARCIS (Netherlands)

    van Schaik, F.; van der Schaft, Abraham; Scherpen, Jacquelien M.A.; Zonetti, Daniele; Ortega, R

    2012-01-01

    In this talk a full nonlinear model for the power network in port–Hamiltonian framework is derived to study its stability properties. For this we use the modularity approach i.e., we first derive the models of individual components in power network as port-Hamiltonian systems and then we combine all

  8. Modelling traffic congestion using queuing networks

    Indian Academy of Sciences (India)

    Flow-density curves; uninterrupted traffic; Jackson networks. ... ness - also suffer from a big handicap vis-a-vis the Indian scenario: most of these models do .... more well-known queuing network models and onsite data, a more exact Road Cell ...

  9. Settings in Social Networks : a Measurement Model

    NARCIS (Netherlands)

    Schweinberger, Michael; Snijders, Tom A.B.

    2003-01-01

    A class of statistical models is proposed that aims to recover latent settings structures in social networks. Settings may be regarded as clusters of vertices. The measurement model is based on two assumptions. (1) The observed network is generated by hierarchically nested latent transitive

  10. Network interconnections: an architectural reference model

    NARCIS (Netherlands)

    Butscher, B.; Lenzini, L.; Morling, R.; Vissers, C.A.; Popescu-Zeletin, R.; van Sinderen, Marten J.; Heger, D.; Krueger, G.; Spaniol, O.; Zorn, W.

    1985-01-01

    One of the major problems in understanding the different approaches in interconnecting networks of different technologies is the lack of reference to a general model. The paper develops the rationales for a reference model of network interconnection and focuses on the architectural implications for

  11. Performance modeling of network data services

    Energy Technology Data Exchange (ETDEWEB)

    Haynes, R.A.; Pierson, L.G.

    1997-01-01

    Networks at major computational organizations are becoming increasingly complex. The introduction of large massively parallel computers and supercomputers with gigabyte memories are requiring greater and greater bandwidth for network data transfers to widely dispersed clients. For networks to provide adequate data transfer services to high performance computers and remote users connected to them, the networking components must be optimized from a combination of internal and external performance criteria. This paper describes research done at Sandia National Laboratories to model network data services and to visualize the flow of data from source to sink when using the data services.

  12. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo; Burger, Martin; Haskovec, Jan; Markowich, Peter A.; Schlottbom, Matthias

    2017-01-01

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes

  13. Network models in economics and finance

    CERN Document Server

    Pardalos, Panos; Rassias, Themistocles

    2014-01-01

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

  14. Patterns and universals of adult romantic attachment across 62 cultural regions : are models of self and of other pancultural constructs?

    OpenAIRE

    Schmitt, David P.; Diniz, Glaucia; Alcalay, Lidia; Durkin, Kevin; Allensworth, Melissa; Echegaray, Marcela; Allik, Juri; Eremsoy, Ekin; Ault, Lara; Euler, Harald A.; Austers, Ivars; Falzon, Ruth; Bennett, Kevin L.; Fisher, Maryanne L.; Bianchi, Gabriel

    2004-01-01

    As part of the International Sexuality Description Project, a total of 17,804 participants from 62 cultural regions completed the Relationship Questionnaire (RQ), a self-report measure of adult romantic attachment. Correlational analyses within each culture suggested that the Model of Self and the Model of Other scales of the RQ were psychometrically valid within most cultures. Contrary to expectations, the Model of Self and Model of Other dimensions of the RQ did not underlie the four-cat...

  15. Synergistic effects in threshold models on networks

    Science.gov (United States)

    Juul, Jonas S.; Porter, Mason A.

    2018-01-01

    Network structure can have a significant impact on the propagation of diseases, memes, and information on social networks. Different types of spreading processes (and other dynamical processes) are affected by network architecture in different ways, and it is important to develop tractable models of spreading processes on networks to explore such issues. In this paper, we incorporate the idea of synergy into a two-state ("active" or "passive") threshold model of social influence on networks. Our model's update rule is deterministic, and the influence of each meme-carrying (i.e., active) neighbor can—depending on a parameter—either be enhanced or inhibited by an amount that depends on the number of active neighbors of a node. Such a synergistic system models social behavior in which the willingness to adopt either accelerates or saturates in a way that depends on the number of neighbors who have adopted that behavior. We illustrate that our model's synergy parameter has a crucial effect on system dynamics, as it determines whether degree-k nodes are possible or impossible to activate. We simulate synergistic meme spreading on both random-graph models and networks constructed from empirical data. Using a heterogeneous mean-field approximation, which we derive under the assumption that a network is locally tree-like, we are able to determine which synergy-parameter values allow degree-k nodes to be activated for many networks and for a broad family of synergistic models.

  16. Gossip spread in social network Models

    Science.gov (United States)

    Johansson, Tobias

    2017-04-01

    Gossip almost inevitably arises in real social networks. In this article we investigate the relationship between the number of friends of a person and limits on how far gossip about that person can spread in the network. How far gossip travels in a network depends on two sets of factors: (a) factors determining gossip transmission from one person to the next and (b) factors determining network topology. For a simple model where gossip is spread among people who know the victim it is known that a standard scale-free network model produces a non-monotonic relationship between number of friends and expected relative spread of gossip, a pattern that is also observed in real networks (Lind et al., 2007). Here, we study gossip spread in two social network models (Toivonen et al., 2006; Vázquez, 2003) by exploring the parameter space of both models and fitting them to a real Facebook data set. Both models can produce the non-monotonic relationship of real networks more accurately than a standard scale-free model while also exhibiting more realistic variability in gossip spread. Of the two models, the one given in Vázquez (2003) best captures both the expected values and variability of gossip spread.

  17. Evaluation of EOR Processes Using Network Models

    DEFF Research Database (Denmark)

    Winter, Anatol; Larsen, Jens Kjell; Krogsbøll, Anette

    1998-01-01

    The report consists of the following parts: 1) Studies of wetting properties of model fluids and fluid mixtures aimed at an optimal selection of candidates for micromodel experiments. 2) Experimental studies of multiphase transport properties using physical models of porous networks (micromodels......) including estimation of their "petrophysical" properties (e.g. absolute permeability). 3) Mathematical modelling and computer studies of multiphase transport through pore space using mathematical network models. 4) Investigation of link between pore-scale and macroscopic recovery mechanisms....

  18. Benchmarking Measures of Network Controllability on Canonical Graph Models

    Science.gov (United States)

    Wu-Yan, Elena; Betzel, Richard F.; Tang, Evelyn; Gu, Shi; Pasqualetti, Fabio; Bassett, Danielle S.

    2018-03-01

    The control of networked dynamical systems opens the possibility for new discoveries and therapies in systems biology and neuroscience. Recent theoretical advances provide candidate mechanisms by which a system can be driven from one pre-specified state to another, and computational approaches provide tools to test those mechanisms in real-world systems. Despite already having been applied to study network systems in biology and neuroscience, the practical performance of these tools and associated measures on simple networks with pre-specified structure has yet to be assessed. Here, we study the behavior of four control metrics (global, average, modal, and boundary controllability) on eight canonical graphs (including Erdős-Rényi, regular, small-world, random geometric, Barábasi-Albert preferential attachment, and several modular networks) with different edge weighting schemes (Gaussian, power-law, and two nonparametric distributions from brain networks, as examples of real-world systems). We observe that differences in global controllability across graph models are more salient when edge weight distributions are heavy-tailed as opposed to normal. In contrast, differences in average, modal, and boundary controllability across graph models (as well as across nodes in the graph) are more salient when edge weight distributions are less heavy-tailed. Across graph models and edge weighting schemes, average and modal controllability are negatively correlated with one another across nodes; yet, across graph instances, the relation between average and modal controllability can be positive, negative, or nonsignificant. Collectively, these findings demonstrate that controllability statistics (and their relations) differ across graphs with different topologies and that these differences can be muted or accentuated by differences in the edge weight distributions. More generally, our numerical studies motivate future analytical efforts to better understand the mathematical

  19. Attachment and psychosis

    NARCIS (Netherlands)

    Korver, N.

    2014-01-01

    The main goal of this thesis was to further our understanding of current psychosocial models by introducing attachment as a relevant developmental framework. Firstly, attachment theory provides a psychosocial model for a developmental pathway to psychosis. Secondly, after expression of psychotic

  20. Stability of attachment-related anxiety and avoidance and their relationships with the five-factor model and the psychobiological model of personality.

    Science.gov (United States)

    Picardi, Angelo; Caroppo, Emanuele; Toni, Alessandro; Bitetti, Daniela; Di Maria, Giuseppe

    2005-09-01

    The stability of attachment-related anxiety and avoidance and their relationship with influential personality models are issues worth further investigation. Studying discriminant validity with respect to aspects of personality deemed as prevalently heritable, such as temperament, is particularly important. Our aims were to examine the stability of attachment dimensions and to study their relationship with psychological distress, the Big Five factors, and temperament and character dimensions. The Experiences in Close Relationships (ECR) questionnaire, the State-Trait Anxiety Inventory (STAI), the Zung depression scale (ZDS), the Temperament and Character Inventory (TCI-125), and the Big Five Questionnaire (BFQ) were administered to 222 undergraduate and graduate students. After 1 month, 115 participants completed again the ECR, the STAI, and the ZDS. Attachment-related anxiety was modestly correlated with depression and anxiety, while attachment-related avoidance was modestly correlated with depression. The test-retest reliability of ECR scores was high. Changes in attachment-related anxiety were not related to changes in depression or anxiety, and changes in attachment-related avoidance were modestly correlated with changes in depression. In separate multiple regression models also including gender and age, attachment-related anxiety was correlated with harm avoidance, reward dependence, low novelty seeking, low self-directedness and low cooperativeness; low energy/extraversion and low emotional stability; attachment-related avoidance was correlated with low reward dependence and tended to be correlated with low self-directedness. These findings corroborate the reliability and the convergent and discriminant validity of the ECR, and support the notion that the attachment dimensions are only modestly related to psychological distress and are not redundant with constructs developed within influential personality models such as the five-factor model and the

  1. Towards reproducible descriptions of neuronal network models.

    Directory of Open Access Journals (Sweden)

    Eilen Nordlie

    2009-08-01

    Full Text Available Progress in science depends on the effective exchange of ideas among scientists. New ideas can be assessed and criticized in a meaningful manner only if they are formulated precisely. This applies to simulation studies as well as to experiments and theories. But after more than 50 years of neuronal network simulations, we still lack a clear and common understanding of the role of computational models in neuroscience as well as established practices for describing network models in publications. This hinders the critical evaluation of network models as well as their re-use. We analyze here 14 research papers proposing neuronal network models of different complexity and find widely varying approaches to model descriptions, with regard to both the means of description and the ordering and placement of material. We further observe great variation in the graphical representation of networks and the notation used in equations. Based on our observations, we propose a good model description practice, composed of guidelines for the organization of publications, a checklist for model descriptions, templates for tables presenting model structure, and guidelines for diagrams of networks. The main purpose of this good practice is to trigger a debate about the communication of neuronal network models in a manner comprehensible to humans, as opposed to machine-readable model description languages. We believe that the good model description practice proposed here, together with a number of other recent initiatives on data-, model-, and software-sharing, may lead to a deeper and more fruitful exchange of ideas among computational neuroscientists in years to come. We further hope that work on standardized ways of describing--and thinking about--complex neuronal networks will lead the scientific community to a clearer understanding of high-level concepts in network dynamics, and will thus lead to deeper insights into the function of the brain.

  2. Improved Maximum Parsimony Models for Phylogenetic Networks.

    Science.gov (United States)

    Van Iersel, Leo; Jones, Mark; Scornavacca, Celine

    2018-05-01

    Phylogenetic networks are well suited to represent evolutionary histories comprising reticulate evolution. Several methods aiming at reconstructing explicit phylogenetic networks have been developed in the last two decades. In this article, we propose a new definition of maximum parsimony for phylogenetic networks that permits to model biological scenarios that cannot be modeled by the definitions currently present in the literature (namely, the "hardwired" and "softwired" parsimony). Building on this new definition, we provide several algorithmic results that lay the foundations for new parsimony-based methods for phylogenetic network reconstruction.

  3. Modeling, robust and distributed model predictive control for freeway networks

    NARCIS (Netherlands)

    Liu, S.

    2016-01-01

    In Model Predictive Control (MPC) for traffic networks, traffic models are crucial since they are used as prediction models for determining the optimal control actions. In order to reduce the computational complexity of MPC for traffic networks, macroscopic traffic models are often used instead of

  4. Tool wear modeling using abductive networks

    Science.gov (United States)

    Masory, Oren

    1992-09-01

    A tool wear model based on Abductive Networks, which consists of a network of `polynomial' nodes, is described. The model relates the cutting parameters, components of the cutting force, and machining time to flank wear. Thus real time measurements of the cutting force can be used to monitor the machining process. The model is obtained by a training process in which the connectivity between the network's nodes and the polynomial coefficients of each node are determined by optimizing a performance criteria. Actual wear measurements of coated and uncoated carbide inserts were used for training and evaluating the established model.

  5. Representing Degree Distributions, Clustering, and Homophily in Social Networks With Latent Cluster Random Effects Models.

    Science.gov (United States)

    Krivitsky, Pavel N; Handcock, Mark S; Raftery, Adrian E; Hoff, Peter D

    2009-07-01

    Social network data often involve transitivity, homophily on observed attributes, clustering, and heterogeneity of actor degrees. We propose a latent cluster random effects model to represent all of these features, and we describe a Bayesian estimation method for it. The model is applicable to both binary and non-binary network data. We illustrate the model using two real datasets. We also apply it to two simulated network datasets with the same, highly skewed, degree distribution, but very different network behavior: one unstructured and the other with transitivity and clustering. Models based on degree distributions, such as scale-free, preferential attachment and power-law models, cannot distinguish between these very different situations, but our model does.

  6. Colloid transport in saturated porous media: Elimination of attachment efficiency in a new colloid transport model

    Science.gov (United States)

    Landkamer, Lee L.; Harvey, Ronald W.; Scheibe, Timothy D.; Ryan, Joseph N.

    2013-01-01

    A colloid transport model is introduced that is conceptually simple yet captures the essential features of colloid transport and retention in saturated porous media when colloid retention is dominated by the secondary minimum because an electrostatic barrier inhibits substantial deposition in the primary minimum. This model is based on conventional colloid filtration theory (CFT) but eliminates the empirical concept of attachment efficiency. The colloid deposition rate is computed directly from CFT by assuming all predicted interceptions of colloids by collectors result in at least temporary deposition in the secondary minimum. Also, a new paradigm for colloid re-entrainment based on colloid population heterogeneity is introduced. To accomplish this, the initial colloid population is divided into two fractions. One fraction, by virtue of physiochemical characteristics (e.g., size and charge), will always be re-entrained after capture in a secondary minimum. The remaining fraction of colloids, again as a result of physiochemical characteristics, will be retained “irreversibly” when captured by a secondary minimum. Assuming the dispersion coefficient can be estimated from tracer behavior, this model has only two fitting parameters: (1) the fraction of the initial colloid population that will be retained “irreversibly” upon interception by a secondary minimum, and (2) the rate at which reversibly retained colloids leave the secondary minimum. These two parameters were correlated to the depth of the Derjaguin-Landau-Verwey-Overbeek (DLVO) secondary energy minimum and pore-water velocity, two physical forces that influence colloid transport. Given this correlation, the model serves as a heuristic tool for exploring the influence of physical parameters such as surface potential and fluid velocity on colloid transport.

  7. Modelling of virtual production networks

    Directory of Open Access Journals (Sweden)

    2011-03-01

    Full Text Available Nowadays many companies, especially small and medium-sized enterprises (SMEs, specialize in a limited field of production. It requires forming virtual production networks of cooperating enterprises to manufacture better, faster and cheaper. Apart from that, some production orders cannot be realized, because there is not a company of sufficient production potential. In this case the virtual production networks of cooperating companies can realize these production orders. These networks have larger production capacity and many different resources. Therefore it can realize many more production orders together than each of them separately. Such organization allows for executing high quality product. The maintenance costs of production capacity and used resources are not so high. In this paper a methodology of rapid prototyping of virtual production networks is proposed. It allows to execute production orders on time considered existing logistic constraints.

  8. A Network Disruption Modeling Tool

    National Research Council Canada - National Science Library

    Leinart, James

    1998-01-01

    Given that network disruption has been identified as a military objective and C2-attack has been identified as the mechanism to accomplish this objective, a target set must be acquired and priorities...

  9. Modeling Epidemics Spreading on Social Contact Networks.

    Science.gov (United States)

    Zhang, Zhaoyang; Wang, Honggang; Wang, Chonggang; Fang, Hua

    2015-09-01

    Social contact networks and the way people interact with each other are the key factors that impact on epidemics spreading. However, it is challenging to model the behavior of epidemics based on social contact networks due to their high dynamics. Traditional models such as susceptible-infected-recovered (SIR) model ignore the crowding or protection effect and thus has some unrealistic assumption. In this paper, we consider the crowding or protection effect and develop a novel model called improved SIR model. Then, we use both deterministic and stochastic models to characterize the dynamics of epidemics on social contact networks. The results from both simulations and real data set conclude that the epidemics are more likely to outbreak on social contact networks with higher average degree. We also present some potential immunization strategies, such as random set immunization, dominating set immunization, and high degree set immunization to further prove the conclusion.

  10. Spatial Epidemic Modelling in Social Networks

    Science.gov (United States)

    Simoes, Joana Margarida

    2005-06-01

    The spread of infectious diseases is highly influenced by the structure of the underlying social network. The target of this study is not the network of acquaintances, but the social mobility network: the daily movement of people between locations, in regions. It was already shown that this kind of network exhibits small world characteristics. The model developed is agent based (ABM) and comprehends a movement model and a infection model. In the movement model, some assumptions are made about its structure and the daily movement is decomposed into four types: neighborhood, intra region, inter region and random. The model is Geographical Information Systems (GIS) based, and uses real data to define its geometry. Because it is a vector model, some optimization techniques were used to increase its efficiency.

  11. Implementing network constraints in the EMPS model

    Energy Technology Data Exchange (ETDEWEB)

    Helseth, Arild; Warland, Geir; Mo, Birger; Fosso, Olav B.

    2010-02-15

    This report concerns the coupling of detailed market and network models for long-term hydro-thermal scheduling. Currently, the EPF model (Samlast) is the only tool available for this task for actors in the Nordic market. A new prototype for solving the coupled market and network problem has been developed. The prototype is based on the EMPS model (Samkjoeringsmodellen). Results from the market model are distributed to a detailed network model, where a DC load flow detects if there are overloads on monitored lines or intersections. In case of overloads, network constraints are generated and added to the market problem. Theoretical and implementation details for the new prototype are elaborated in this report. The performance of the prototype is tested against the EPF model on a 20-area Nordic dataset. (Author)

  12. Role models for complex networks

    Science.gov (United States)

    Reichardt, J.; White, D. R.

    2007-11-01

    We present a framework for automatically decomposing (“block-modeling”) the functional classes of agents within a complex network. These classes are represented by the nodes of an image graph (“block model”) depicting the main patterns of connectivity and thus functional roles in the network. Using a first principles approach, we derive a measure for the fit of a network to any given image graph allowing objective hypothesis testing. From the properties of an optimal fit, we derive how to find the best fitting image graph directly from the network and present a criterion to avoid overfitting. The method can handle both two-mode and one-mode data, directed and undirected as well as weighted networks and allows for different types of links to be dealt with simultaneously. It is non-parametric and computationally efficient. The concepts of structural equivalence and modularity are found as special cases of our approach. We apply our method to the world trade network and analyze the roles individual countries play in the global economy.

  13. Efficacy of an Attachment-Based Intervention Model on Health Indices in Children with Chronic Disease and Their Mothers.

    Science.gov (United States)

    Dehghani-Arani, Fateme; Besharat, Mohammad Ali; Fitton, Victoria A; Aghamohammadi, Asghar

    2018-05-07

    Studies have shown significant relationship between health conditions and attachment. This study aimed to examine an attachment-based intervention model named mother-child-disease triangle (MCDT) on health indices in children with chronic disease and their mothers. This randomized trial study included 22 volunteer children aged 12-18 years undergoing medical treatment for a chronic disease and their mothers. After evaluation by 28-form General Health Questionnaire (GHQ-28), inventory of parent and peer attachment (IPPA), 28-form Child Health Questionnaire (CHQ-28) and Illness Perception Questionnaire (IPQ), the mother-child dyads were paired on the basis of IPPA scores. These pairs were then randomly assigned to an experimental or control group. The experimental group received ten 90-min sessions of MCDT over a 7-week period. Meanwhile, the control group received ten simple conversational sessions as a dummy intervention. In accordance with this study's pre-test/post-test design, both groups were evaluated once again after completing their respective treatment. Multivariate analysis of covariance (MANCOVA) showed members of the experimental group to have significantly stronger attachment and better physiological and psychosocial health than those in the control group. These findings suggest that attachment-based interventions can be used to improve the effectiveness of treatment among children with chronic disease and their mothers.

  14. Modeling the interdependent network based on two-mode networks

    Science.gov (United States)

    An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian

    2017-10-01

    Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.

  15. Latent variable models are network models.

    Science.gov (United States)

    Molenaar, Peter C M

    2010-06-01

    Cramer et al. present an original and interesting network perspective on comorbidity and contrast this perspective with a more traditional interpretation of comorbidity in terms of latent variable theory. My commentary focuses on the relationship between the two perspectives; that is, it aims to qualify the presumed contrast between interpretations in terms of networks and latent variables.

  16. [Effects of an implicit internal working model on attachment in information processing assessed using Go/No-Go Association Task].

    Science.gov (United States)

    Fujii, Tsutomu; Uebuchi, Hisashi; Yamada, Kotono; Saito, Masahiro; Ito, Eriko; Tonegawa, Akiko; Uebuchi, Marie

    2015-06-01

    The purposes of the present study were (a) to use both a relational-anxiety Go/No-Go Association Task (GNAT) and an avoidance-of-intimacy GNAT in order to assess an implicit Internal Working Model (IWM) of attachment; (b) to verify the effects of both measured implicit relational anxiety and implicit avoidance of intimacy on information processing. The implicit IWM measured by GNAT differed from the explicit IWM measured by questionnaires in terms of the effects on information processing. In particular, in subliminal priming tasks involving with others, implicit avoidance of intimacy predicted accelerated response times with negative stimulus words about attachment. Moreover, after subliminally priming stimulus words about self, implicit relational anxiety predicted delayed response times with negative stimulus words about attachment.

  17. Homophyly/Kinship Model: Naturally Evolving Networks

    Science.gov (United States)

    Li, Angsheng; Li, Jiankou; Pan, Yicheng; Yin, Xianchen; Yong, Xi

    2015-10-01

    It has been a challenge to understand the formation and roles of social groups or natural communities in the evolution of species, societies and real world networks. Here, we propose the hypothesis that homophyly/kinship is the intrinsic mechanism of natural communities, introduce the notion of the affinity exponent and propose the homophyly/kinship model of networks. We demonstrate that the networks of our model satisfy a number of topological, probabilistic and combinatorial properties and, in particular, that the robustness and stability of natural communities increase as the affinity exponent increases and that the reciprocity of the networks in our model decreases as the affinity exponent increases. We show that both homophyly/kinship and reciprocity are essential to the emergence of cooperation in evolutionary games and that the homophyly/kinship and reciprocity determined by the appropriate affinity exponent guarantee the emergence of cooperation in evolutionary games, verifying Darwin’s proposal that kinship and reciprocity are the means of individual fitness. We propose the new principle of structure entropy minimisation for detecting natural communities of networks and verify the functional module property and characteristic properties by a healthy tissue cell network, a citation network, some metabolic networks and a protein interaction network.

  18. Stochastic Boolean networks: An efficient approach to modeling gene regulatory networks

    Directory of Open Access Journals (Sweden)

    Liang Jinghang

    2012-08-01

    network inferred from a T cell immune response dataset. An SBN can also implement the function of an asynchronous PBN and is potentially useful in a hybrid approach in combination with a continuous or single-molecule level stochastic model. Conclusions Stochastic Boolean networks (SBNs are proposed as an efficient approach to modelling gene regulatory networks (GRNs. The SBN approach is able to recover biologically-proven regulatory behaviours, such as the oscillatory dynamics of the p53-Mdm2 network and the dynamic attractors in a T cell immune response network. The proposed approach can further predict the network dynamics when the genes are under perturbation, thus providing biologically meaningful insights for a better understanding of the dynamics of GRNs. The algorithms and methods described in this paper have been implemented in Matlab packages, which are attached as Additional files.

  19. A nonlocal, ab initio model of dissociative electron attachment and vibrational excitation of NO

    International Nuclear Information System (INIS)

    Trevisan, Cynthia S.; Houfek, Karel; Zhang, Zhiyong; Orel, Ann E.; McCurdy, C. William; Rescigno, Thomas N.

    2005-01-01

    We present the results of an ab initio study of elastic scattering and vibrational excitation of NO by electron impact in the loW--energy (0-2 eV) region where the cross sections are dominated by resonance contributions. The 3Sigma-, 1Delta and 1Sigma+ NO- resonance lifetimes are taken from our earlier study [Phys. Rev. A 69, 062711 (2004)], but the resonance energies used here are obtained from new configuration-interaction studies. Here we employ a more elaborate nonlocal treatment of the nuclear dynamics, which is found to remedy the principal deficiencies of the local complex potential model we employed in our earlier study, and gives cross sections in better agreement with the most recent experiments. We also present cross sections for dissociative electron attachment to NO leading to groundstate products. The calculations show that, while the peak cross sections starting from NO in its ground vibrational state are very small, the cross sections are extremely sensitive to vibrational excitation of the target and should be readily observable for target NO molecules excited to v = 10 and above

  20. Neural network tagging in a toy model

    International Nuclear Information System (INIS)

    Milek, Marko; Patel, Popat

    1999-01-01

    The purpose of this study is a comparison of Artificial Neural Network approach to HEP analysis against the traditional methods. A toy model used in this analysis consists of two types of particles defined by four generic properties. A number of 'events' was created according to the model using standard Monte Carlo techniques. Several fully connected, feed forward multi layered Artificial Neural Networks were trained to tag the model events. The performance of each network was compared to the standard analysis mechanisms and significant improvement was observed

  1. An endogenous model of the credit network

    Science.gov (United States)

    He, Jianmin; Sui, Xin; Li, Shouwei

    2016-01-01

    In this paper, an endogenous credit network model of firm-bank agents is constructed. The model describes the endogenous formation of firm-firm, firm-bank and bank-bank credit relationships. By means of simulations, the model is capable of showing some obvious similarities with empirical evidence found by other scholars: the upper-tail of firm size distribution can be well fitted with a power-law; the bank size distribution can be lognormally distributed with a power-law tail; the bank in-degrees of the interbank credit network as well as the firm-bank credit network fall into two-power-law distributions.

  2. Modelling and designing electric energy networks

    International Nuclear Information System (INIS)

    Retiere, N.

    2003-11-01

    The author gives an overview of his research works in the field of electric network modelling. After a brief overview of technological evolutions from the telegraph to the all-electric fly-by-wire aircraft, he reports and describes various works dealing with a simplified modelling of electric systems and with fractal simulation. Then, he outlines the challenges for the design of electric networks, proposes a design process, gives an overview of various design models, methods and tools, and reports an application in the design of electric networks for future jumbo jets

  3. Queueing Models for Mobile Ad Hoc Networks

    NARCIS (Netherlands)

    de Haan, Roland

    2009-01-01

    This thesis presents models for the performance analysis of a recent communication paradigm: \\emph{mobile ad hoc networking}. The objective of mobile ad hoc networking is to provide wireless connectivity between stations in a highly dynamic environment. These dynamics are driven by the mobility of

  4. Modeling GMPLS and Optical MPLS Networks

    DEFF Research Database (Denmark)

    Christiansen, Henrik Lehrmann; Wessing, Henrik

    2003-01-01

    . The MPLS concept is attractive because it can work as a unifying control structure. covering all technologies. This paper describes how a novel scheme for optical MPLS and circuit switched GMPLS based networks can incorporated in such multi-domain, MPLS-based scenarios and how it could be modeled. Network...

  5. Cyber threat model for tactical radio networks

    Science.gov (United States)

    Kurdziel, Michael T.

    2014-05-01

    The shift to a full information-centric paradigm in the battlefield has allowed ConOps to be developed that are only possible using modern network communications systems. Securing these Tactical Networks without impacting their capabilities has been a challenge. Tactical networks with fixed infrastructure have similar vulnerabilities to their commercial counterparts (although they need to be secure against adversaries with greater capabilities, resources and motivation). However, networks with mobile infrastructure components and Mobile Ad hoc Networks (MANets) have additional unique vulnerabilities that must be considered. It is useful to examine Tactical Network based ConOps and use them to construct a threat model and baseline cyber security requirements for Tactical Networks with fixed infrastructure, mobile infrastructure and/or ad hoc modes of operation. This paper will present an introduction to threat model assessment. A definition and detailed discussion of a Tactical Network threat model is also presented. Finally, the model is used to derive baseline requirements that can be used to design or evaluate a cyber security solution that can be scaled and adapted to the needs of specific deployments.

  6. Modeling documents with Generative Adversarial Networks

    OpenAIRE

    Glover, John

    2016-01-01

    This paper describes a method for using Generative Adversarial Networks to learn distributed representations of natural language documents. We propose a model that is based on the recently proposed Energy-Based GAN, but instead uses a Denoising Autoencoder as the discriminator network. Document representations are extracted from the hidden layer of the discriminator and evaluated both quantitatively and qualitatively.

  7. Designing Network-based Business Model Ontology

    DEFF Research Database (Denmark)

    Hashemi Nekoo, Ali Reza; Ashourizadeh, Shayegheh; Zarei, Behrouz

    2015-01-01

    Survival on dynamic environment is not achieved without a map. Scanning and monitoring of the market show business models as a fruitful tool. But scholars believe that old-fashioned business models are dead; as they are not included the effect of internet and network in themselves. This paper...... is going to propose e-business model ontology from the network point of view and its application in real world. The suggested ontology for network-based businesses is composed of individuals` characteristics and what kind of resources they own. also, their connections and pre-conceptions of connections...... such as shared-mental model and trust. However, it mostly covers previous business model elements. To confirm the applicability of this ontology, it has been implemented in business angel network and showed how it works....

  8. Modeling trust context in networks

    CERN Document Server

    Adali, Sibel

    2013-01-01

    We make complex decisions every day, requiring trust in many different entities for different reasons. These decisions are not made by combining many isolated trust evaluations. Many interlocking factors play a role, each dynamically impacting the others.? In this brief, 'trust context' is defined as the system level description of how the trust evaluation process unfolds.Networks today are part of almost all human activity, supporting and shaping it. Applications increasingly incorporate new interdependencies and new trust contexts. Social networks connect people and organizations throughout

  9. Mathematical model of highways network optimization

    Science.gov (United States)

    Sakhapov, R. L.; Nikolaeva, R. V.; Gatiyatullin, M. H.; Makhmutov, M. M.

    2017-12-01

    The article deals with the issue of highways network design. Studies show that the main requirement from road transport for the road network is to ensure the realization of all the transport links served by it, with the least possible cost. The goal of optimizing the network of highways is to increase the efficiency of transport. It is necessary to take into account a large number of factors that make it difficult to quantify and qualify their impact on the road network. In this paper, we propose building an optimal variant for locating the road network on the basis of a mathematical model. The article defines the criteria for optimality and objective functions that reflect the requirements for the road network. The most fully satisfying condition for optimality is the minimization of road and transport costs. We adopted this indicator as a criterion of optimality in the economic-mathematical model of a network of highways. Studies have shown that each offset point in the optimal binding road network is associated with all other corresponding points in the directions providing the least financial costs necessary to move passengers and cargo from this point to the other corresponding points. The article presents general principles for constructing an optimal network of roads.

  10. Ovarian tumor attachment, invasion and vascularization reflect unique microenvironments in the peritoneum:Insights from xenograft and mathematical models

    Directory of Open Access Journals (Sweden)

    Mara P. Steinkamp

    2013-05-01

    Full Text Available Ovarian cancer relapse is often characterized by metastatic spread throughout the peritoneal cavity with tumors attached to multiple organs. In this study, interaction of ovarian tumor cells with the peritoneal tumor microenvironment was evaluated in a xenograft model based on intraperitoneal injection of fluorescent SKOV3.ip1 ovarian cancer cells. Intra-vital microscopy of mixed GFP-RFP cell populations injected into the peritoneum demonstrated that tumor cells aggregate and attach as mixed spheroids, emphasizing the importance of homotypic adhesion in tumor formation. Electron microscopy provided high resolution structural information about local attachment sites. Experimental measurements from the mouse model were used to build a three-dimensional cellular Potts ovarian tumor model (OvTM that examines ovarian tumor cell attachment, chemotaxis, growth and vascularization. OvTM simulations provide insight into the relative influence of tumor cell-cell adhesion, oxygen availability, and local architecture on tumor growth and morphology. Notably, tumors on the mesentery, omentum or spleen readily invade the open architecture, while tumors attached to the gut encounter barriers that restrict invasion and instead rapidly expand into the peritoneal space. Simulations suggest that rapid neovascularization of SKOV3.ip1 tumors is triggered by constitutive release of angiogenic factors in the absence of hypoxia. This research highlights the importance of cellular adhesion and tumor microenvironment in the seeding of secondary ovarian tumors on diverse organs within the peritoneal cavity. Results of the OvTM simulations indicate that invasion is strongly influenced by features underlying the mesothelial lining at different sites, but is also affected by local production of chemotactic factors. The integrated in vivo mouse model and computer simulations provide a unique platform for evaluating targeted therapies for ovarian cancer relapse.

  11. Graphical Model Theory for Wireless Sensor Networks

    International Nuclear Information System (INIS)

    Davis, William B.

    2002-01-01

    Information processing in sensor networks, with many small processors, demands a theory of computation that allows the minimization of processing effort, and the distribution of this effort throughout the network. Graphical model theory provides a probabilistic theory of computation that explicitly addresses complexity and decentralization for optimizing network computation. The junction tree algorithm, for decentralized inference on graphical probability models, can be instantiated in a variety of applications useful for wireless sensor networks, including: sensor validation and fusion; data compression and channel coding; expert systems, with decentralized data structures, and efficient local queries; pattern classification, and machine learning. Graphical models for these applications are sketched, and a model of dynamic sensor validation and fusion is presented in more depth, to illustrate the junction tree algorithm

  12. Modeling Network Traffic in Wavelet Domain

    Directory of Open Access Journals (Sweden)

    Sheng Ma

    2004-12-01

    Full Text Available This work discovers that although network traffic has the complicated short- and long-range temporal dependence, the corresponding wavelet coefficients are no longer long-range dependent. Therefore, a "short-range" dependent process can be used to model network traffic in the wavelet domain. Both independent and Markov models are investigated. Theoretical analysis shows that the independent wavelet model is sufficiently accurate in terms of the buffer overflow probability for Fractional Gaussian Noise traffic. Any model, which captures additional correlations in the wavelet domain, only improves the performance marginally. The independent wavelet model is then used as a unified approach to model network traffic including VBR MPEG video and Ethernet data. The computational complexity is O(N for developing such wavelet models and generating synthesized traffic of length N, which is among the lowest attained.

  13. Sparsity in Model Gene Regulatory Networks

    International Nuclear Information System (INIS)

    Zagorski, M.

    2011-01-01

    We propose a gene regulatory network model which incorporates the microscopic interactions between genes and transcription factors. In particular the gene's expression level is determined by deterministic synchronous dynamics with contribution from excitatory interactions. We study the structure of networks that have a particular '' function '' and are subject to the natural selection pressure. The question of network robustness against point mutations is addressed, and we conclude that only a small part of connections defined as '' essential '' for cell's existence is fragile. Additionally, the obtained networks are sparse with narrow in-degree and broad out-degree, properties well known from experimental study of biological regulatory networks. Furthermore, during sampling procedure we observe that significantly different genotypes can emerge under mutation-selection balance. All the preceding features hold for the model parameters which lay in the experimentally relevant range. (author)

  14. Enriching practice of dialectic behaviour therapy with the dynamic maturational model of attachment and adaptation.

    Science.gov (United States)

    Wilkinson, Simon R

    2016-01-01

    The major challenge for a clinician is integration of the wisdom available in the wide range of therapeutic paradigms available. I have found the principles guiding dialectic behaviour therapy (DBT; see Miller, Rathus, & Linehan, 2007, for applying DBT to adolescents) extremely useful in my practice running a general adolescent unit; similarly, the understanding of the different information processing and learning principles associated with each of the Type A and C attachment strategies, as understood in dynamic maturational model (DMM), has guided me through the dark corners of treatment. Specifically, how does DMM inform practice of DBT? As a 'DBTer' might say, 'Where is the wisdom in both points of view?' Nevertheless, DMM is not primarily about treatment. It concerns how different ways of adapting to developmental contingencies bias perceptual propensities, and hence the information available for reflective brain function. Recognition of these twists to knowing what is going on can then be used to inform a variety of therapeutic approaches. The purpose of this article is to look for the signposts in DBT and DMM which together help navigate the comprehensive approach necessary in complicated therapy. In the process, hopefully some more general principles for addressing discomfited adolescents arise for informing future practice. Although many steer shy of using personality disorder diagnoses for adolescents, clinicians are nevertheless addressing, directly or indirectly, the personality development of all adolescents in treatment, regardless of their classical axis I diagnoses, including both those with developing emotional instability and a group of avoidant over-controlled adolescents, which in Norway is growing in prominence. © The Author(s) 2014.

  15. The QKD network: model and routing scheme

    Science.gov (United States)

    Yang, Chao; Zhang, Hongqi; Su, Jinhai

    2017-11-01

    Quantum key distribution (QKD) technology can establish unconditional secure keys between two communicating parties. Although this technology has some inherent constraints, such as the distance and point-to-point mode limits, building a QKD network with multiple point-to-point QKD devices can overcome these constraints. Considering the development level of current technology, the trust relaying QKD network is the first choice to build a practical QKD network. However, the previous research didn't address a routing method on the trust relaying QKD network in detail. This paper focuses on the routing issues, builds a model of the trust relaying QKD network for easily analysing and understanding this network, and proposes a dynamical routing scheme for this network. From the viewpoint of designing a dynamical routing scheme in classical network, the proposed scheme consists of three components: a Hello protocol helping share the network topology information, a routing algorithm to select a set of suitable paths and establish the routing table and a link state update mechanism helping keep the routing table newly. Experiments and evaluation demonstrates the validity and effectiveness of the proposed routing scheme.

  16. Thermal conductivity model for nanofiber networks

    Science.gov (United States)

    Zhao, Xinpeng; Huang, Congliang; Liu, Qingkun; Smalyukh, Ivan I.; Yang, Ronggui

    2018-02-01

    Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.

  17. Thermal conductivity model for nanofiber networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, Xinpeng [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Huang, Congliang [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; School of Electrical and Power Engineering, China University of Mining and Technology, Xuzhou 221116, China; Liu, Qingkun [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Smalyukh, Ivan I. [Department of Physics, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Yang, Ronggui [Department of Mechanical Engineering, University of Colorado, Boulder, Colorado 80309, USA; Materials Science and Engineering Program, University of Colorado, Boulder, Colorado 80309, USA; Buildings and Thermal Systems Center, National Renewable Energy Laboratory, Golden, Colorado 80401, USA

    2018-02-28

    Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.

  18. A quantum-implementable neural network model

    Science.gov (United States)

    Chen, Jialin; Wang, Lingli; Charbon, Edoardo

    2017-10-01

    A quantum-implementable neural network, namely quantum probability neural network (QPNN) model, is proposed in this paper. QPNN can use quantum parallelism to trace all possible network states to improve the result. Due to its unique quantum nature, this model is robust to several quantum noises under certain conditions, which can be efficiently implemented by the qubus quantum computer. Another advantage is that QPNN can be used as memory to retrieve the most relevant data and even to generate new data. The MATLAB experimental results of Iris data classification and MNIST handwriting recognition show that much less neuron resources are required in QPNN to obtain a good result than the classical feedforward neural network. The proposed QPNN model indicates that quantum effects are useful for real-life classification tasks.

  19. Combinatorial explosion in model gene networks

    Science.gov (United States)

    Edwards, R.; Glass, L.

    2000-09-01

    The explosive growth in knowledge of the genome of humans and other organisms leaves open the question of how the functioning of genes in interacting networks is coordinated for orderly activity. One approach to this problem is to study mathematical properties of abstract network models that capture the logical structures of gene networks. The principal issue is to understand how particular patterns of activity can result from particular network structures, and what types of behavior are possible. We study idealized models in which the logical structure of the network is explicitly represented by Boolean functions that can be represented by directed graphs on n-cubes, but which are continuous in time and described by differential equations, rather than being updated synchronously via a discrete clock. The equations are piecewise linear, which allows significant analysis and facilitates rapid integration along trajectories. We first give a combinatorial solution to the question of how many distinct logical structures exist for n-dimensional networks, showing that the number increases very rapidly with n. We then outline analytic methods that can be used to establish the existence, stability and periods of periodic orbits corresponding to particular cycles on the n-cube. We use these methods to confirm the existence of limit cycles discovered in a sample of a million randomly generated structures of networks of 4 genes. Even with only 4 genes, at least several hundred different patterns of stable periodic behavior are possible, many of them surprisingly complex. We discuss ways of further classifying these periodic behaviors, showing that small mutations (reversal of one or a few edges on the n-cube) need not destroy the stability of a limit cycle. Although these networks are very simple as models of gene networks, their mathematical transparency reveals relationships between structure and behavior, they suggest that the possibilities for orderly dynamics in such

  20. Analysis of the Attachment-Aversion Model of Consumer-brand Relationships in a Different Cultural Background

    Directory of Open Access Journals (Sweden)

    Veranika Novik

    2017-09-01

    Full Text Available Originally the Attachment-Aversion model of consumer-brand relationships, elaborated by Park, Eisingerich & Park in 2013, was analyzed with the help of the sample of English speaking respondents, living in Great Britain and the USA, and focused on two brands: Manchester United Football Club and Apple iPhone. The present study tries to validate the model regarding other type of brand and in conditions of another cultural background. The focal brand for the study was chosen from a high-end beauty category (Chanel. For the purposes of this research, a questionnaire was designed and spread online within the target population: the current students and alumni of Belarusian universities that are Russian/speaking, fluent in English and had a class in branding. A total of 273 responses was analysed using structural equation modelling. The outcomes of the research have shown that the Attachment-Aversion model of consumer-brand relationships has not proven to be totally versatile, while applied in the conditions of the other cultural background as some of the relationships of the model have shown to be insignificant. The enticing determinant has no effect on brand attachment relationship and the enabling determinant has no effect on the brand prominence. The implications of the findings are discussed.

  1. Complex networks under dynamic repair model

    Science.gov (United States)

    Chaoqi, Fu; Ying, Wang; Kun, Zhao; Yangjun, Gao

    2018-01-01

    Invulnerability is not the only factor of importance when considering complex networks' security. It is also critical to have an effective and reasonable repair strategy. Existing research on network repair is confined to the static model. The dynamic model makes better use of the redundant capacity of repaired nodes and repairs the damaged network more efficiently than the static model; however, the dynamic repair model is complex and polytropic. In this paper, we construct a dynamic repair model and systematically describe the energy-transfer relationships between nodes in the repair process of the failure network. Nodes are divided into three types, corresponding to three structures. We find that the strong coupling structure is responsible for secondary failure of the repaired nodes and propose an algorithm that can select the most suitable targets (nodes or links) to repair the failure network with minimal cost. Two types of repair strategies are identified, with different effects under the two energy-transfer rules. The research results enable a more flexible approach to network repair.

  2. On Mourning and Recovery: Integrating Stages of Grief and Change Toward a Neuroscience-Based Model of Attachment Adaptation in Addiction Treatment.

    Science.gov (United States)

    Chambers, R Andrew; Wallingford, Sue C

    2017-01-01

    Interpersonal attachment and drug addiction share many attributes across their behavioral and neurobiological domains. Understanding the overlapping brain circuitry of attachment formation and addiction illuminates a deeper understanding of the pathogenesis of trauma-related mental illnesses and comorbid substance use disorders, and the extent to which ending an addiction is complicated by being a sort of mourning process. Attention to the process of addiction recovery-as a form of grieving-in which Kubler-Ross's stages of grief and Prochaska's stages of change are ultimately describing complementary viewpoints on a general process of neural network and attachment remodeling, could lead to more effective and integrative psychotherapy and medication strategies.

  3. Performance modeling, stochastic networks, and statistical multiplexing

    CERN Document Server

    Mazumdar, Ravi R

    2013-01-01

    This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of introducing an appropriate mathematical framework for modeling and analysis as well as understanding the phenomenon of statistical multiplexing. The models, techniques, and results presented form the core of traffic engineering methods used to design, control and allocate resources in communication networks.The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the importan

  4. Network Modeling and Simulation A Practical Perspective

    CERN Document Server

    Guizani, Mohsen; Khan, Bilal

    2010-01-01

    Network Modeling and Simulation is a practical guide to using modeling and simulation to solve real-life problems. The authors give a comprehensive exposition of the core concepts in modeling and simulation, and then systematically address the many practical considerations faced by developers in modeling complex large-scale systems. The authors provide examples from computer and telecommunication networks and use these to illustrate the process of mapping generic simulation concepts to domain-specific problems in different industries and disciplines. Key features: Provides the tools and strate

  5. Modeling acquaintance networks based on balance theory

    Directory of Open Access Journals (Sweden)

    Vukašinović Vida

    2014-09-01

    Full Text Available An acquaintance network is a social structure made up of a set of actors and the ties between them. These ties change dynamically as a consequence of incessant interactions between the actors. In this paper we introduce a social network model called the Interaction-Based (IB model that involves well-known sociological principles. The connections between the actors and the strength of the connections are influenced by the continuous positive and negative interactions between the actors and, vice versa, the future interactions are more likely to happen between the actors that are connected with stronger ties. The model is also inspired by the social behavior of animal species, particularly that of ants in their colony. A model evaluation showed that the IB model turned out to be sparse. The model has a small diameter and an average path length that grows in proportion to the logarithm of the number of vertices. The clustering coefficient is relatively high, and its value stabilizes in larger networks. The degree distributions are slightly right-skewed. In the mature phase of the IB model, i.e., when the number of edges does not change significantly, most of the network properties do not change significantly either. The IB model was found to be the best of all the compared models in simulating the e-mail URV (University Rovira i Virgili of Tarragona network because the properties of the IB model more closely matched those of the e-mail URV network than the other models

  6. Optimal transportation networks models and theory

    CERN Document Server

    Bernot, Marc; Morel, Jean-Michel

    2009-01-01

    The transportation problem can be formalized as the problem of finding the optimal way to transport a given measure into another with the same mass. In contrast to the Monge-Kantorovitch problem, recent approaches model the branched structure of such supply networks as minima of an energy functional whose essential feature is to favour wide roads. Such a branched structure is observable in ground transportation networks, in draining and irrigation systems, in electrical power supply systems and in natural counterparts such as blood vessels or the branches of trees. These lectures provide mathematical proof of several existence, structure and regularity properties empirically observed in transportation networks. The link with previous discrete physical models of irrigation and erosion models in geomorphology and with discrete telecommunication and transportation models is discussed. It will be mathematically proven that the majority fit in the simple model sketched in this volume.

  7. Flood routing modelling with Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    R. Peters

    2006-01-01

    Full Text Available For the modelling of the flood routing in the lower reaches of the Freiberger Mulde river and its tributaries the one-dimensional hydrodynamic modelling system HEC-RAS has been applied. Furthermore, this model was used to generate a database to train multilayer feedforward networks. To guarantee numerical stability for the hydrodynamic modelling of some 60 km of streamcourse an adequate resolution in space requires very small calculation time steps, which are some two orders of magnitude smaller than the input data resolution. This leads to quite high computation requirements seriously restricting the application – especially when dealing with real time operations such as online flood forecasting. In order to solve this problem we tested the application of Artificial Neural Networks (ANN. First studies show the ability of adequately trained multilayer feedforward networks (MLFN to reproduce the model performance.

  8. Linear approximation model network and its formation via ...

    Indian Academy of Sciences (India)

    To overcome the deficiency of `local model network' (LMN) techniques, an alternative `linear approximation model' (LAM) network approach is proposed. Such a network models a nonlinear or practical system with multiple linear models fitted along operating trajectories, where individual models are simply networked ...

  9. Modeling Security Aspects of Network

    Science.gov (United States)

    Schoch, Elmar

    With more and more widespread usage of computer systems and networks, dependability becomes a paramount requirement. Dependability typically denotes tolerance or protection against all kinds of failures, errors and faults. Sources of failures can basically be accidental, e.g., in case of hardware errors or software bugs, or intentional due to some kind of malicious behavior. These intentional, malicious actions are subject of security. A more complete overview on the relations between dependability and security can be found in [31]. In parallel to the increased use of technology, misuse also has grown significantly, requiring measures to deal with it.

  10. Parenting Practices, Parental Attachment and Aggressiveness in Adolescence: A Predictive Model

    Science.gov (United States)

    Gallarin, Miriam; Alonso-Arbiol, Itziar

    2012-01-01

    The aim of this study was twofold: a) to test the mediation role of attachment between parenting practices and aggressiveness, and b) to clarify the differential role of mothers and fathers with regard to aggressiveness. A total of 554 adolescents (330 girls and 224 boys), ages ranging between 16 and 19, completed measures of mothers' and fathers'…

  11. A Managerial Perspective on Common Identity-based and Common Bond-based Groups in Non-governmental Organizations. Patterns of Interaction, Attachment and Social Network Configuration

    Directory of Open Access Journals (Sweden)

    Elena - Mădălina VĂTĂMĂNESCU

    2014-10-01

    Full Text Available The paper approaches the common identity and common bond theories in analyzing the group patterns of interaction, their causes, processes and outcomes from a managerial perspective. The distinction between identity and bond referred to people’s different reasons for being in a group, stressing out whether they like the group as a whole — identity-based attachment, or they like individuals in the group — bond-based attachment.  While members of the common identity groups reported feeling more attached to their group as a whole than to their fellow group members and tended to perceive others in the group as interchangeable, in bond-based attachment, people felt connected to each other and less to the group as a whole, loyalty or attraction to the group stemming from their attraction primarily to certain members in the group. At this level, the main question concerned with the particularities of common identity-based or common bond-based groups regarding social interaction, the participatory architecture of the group, the levels of personal and work engagement in acting like a cohesive group. In order to address pertinently this issue, the current work was focused on a qualitative research which comprised in-depth (semi-structured interviews with several project coordinators from non-governmental organizations (NGOs. Also, to make the investigation more complex and clear, the research relied on the social network analysis which was indicative of the group dynamics and configuration, highlighting the differences between common identity-based and common bond-based groups.

  12. Elastic Network Model of a Nuclear Transport Complex

    Science.gov (United States)

    Ryan, Patrick; Liu, Wing K.; Lee, Dockjin; Seo, Sangjae; Kim, Young-Jin; Kim, Moon K.

    2010-05-01

    The structure of Kap95p was obtained from the Protein Data Bank (www.pdb.org) and analyzed RanGTP plays an important role in both nuclear protein import and export cycles. In the nucleus, RanGTP releases macromolecular cargoes from importins and conversely facilitates cargo binding to exportins. Although the crystal structure of the nuclear import complex formed by importin Kap95p and RanGTP was recently identified, its molecular mechanism still remains unclear. To understand the relationship between structure and function of a nuclear transport complex, a structure-based mechanical model of Kap95p:RanGTP complex is introduced. In this model, a protein structure is simply modeled as an elastic network in which a set of coarse-grained point masses are connected by linear springs representing biochemical interactions at atomic level. Harmonic normal mode analysis (NMA) and anharmonic elastic network interpolation (ENI) are performed to predict the modes of vibrations and a feasible pathway between locked and unlocked conformations of Kap95p, respectively. Simulation results imply that the binding of RanGTP to Kap95p induces the release of the cargo in the nucleus as well as prevents any new cargo from attaching to the Kap95p:RanGTP complex.

  13. Modeling and optimization of an electric power distribution network ...

    African Journals Online (AJOL)

    Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...

  14. Modeling of contact tracing in social networks

    Science.gov (United States)

    Tsimring, Lev S.; Huerta, Ramón

    2003-07-01

    Spreading of certain infections in complex networks is effectively suppressed by using intelligent strategies for epidemic control. One such standard epidemiological strategy consists in tracing contacts of infected individuals. In this paper, we use a recently introduced generalization of the standard susceptible-infectious-removed stochastic model for epidemics in sparse random networks which incorporates an additional (traced) state. We describe a deterministic mean-field description which yields quantitative agreement with stochastic simulations on random graphs. We also discuss the role of contact tracing in epidemics control in small-world and scale-free networks. Effectiveness of contact tracing grows as the rewiring probability is reduced.

  15. A Network Model of Credit Risk Contagion

    Directory of Open Access Journals (Sweden)

    Ting-Qiang Chen

    2012-01-01

    Full Text Available A network model of credit risk contagion is presented, in which the effect of behaviors of credit risk holders and the financial market regulators and the network structure are considered. By introducing the stochastic dominance theory, we discussed, respectively, the effect mechanisms of the degree of individual relationship, individual attitude to credit risk contagion, the individual ability to resist credit risk contagion, the monitoring strength of the financial market regulators, and the network structure on credit risk contagion. Then some derived and proofed propositions were verified through numerical simulations.

  16. The Structural Model in Parenting Style, Attachment Style, Self-regulation and Self-esteem for Smartphone Addiction

    OpenAIRE

    Kwan Hoi Ching; Leung Man Tak

    2017-01-01

    Excessive smartphone usage has become a highly controversial and substantial worldwide issue. This paper explores the complexities and challenges of smartphone addiction with a particular focus on parenting styles, attachment, and self-regulation. Convenience sampling was used to gather data from 211 university students in Hong Kong (138 females/74 males) through their responses to four questionnaires. One structural equation model was formed successfully which indicated that parenting style ...

  17. The International Trade Network: weighted network analysis and modelling

    International Nuclear Information System (INIS)

    Bhattacharya, K; Mukherjee, G; Manna, S S; Saramäki, J; Kaski, K

    2008-01-01

    Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN

  18. Keystone Business Models for Network Security Processors

    OpenAIRE

    Arthur Low; Steven Muegge

    2013-01-01

    Network security processors are critical components of high-performance systems built for cybersecurity. Development of a network security processor requires multi-domain experience in semiconductors and complex software security applications, and multiple iterations of both software and hardware implementations. Limited by the business models in use today, such an arduous task can be undertaken only by large incumbent companies and government organizations. Neither the “fabless semiconductor...

  19. Stochastic modeling and analysis of telecoms networks

    CERN Document Server

    Decreusefond, Laurent

    2012-01-01

    This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an

  20. Decomposed Implicit Models of Piecewise - Linear Networks

    Directory of Open Access Journals (Sweden)

    J. Brzobohaty

    1992-05-01

    Full Text Available The general matrix form of the implicit description of a piecewise-linear (PWL network and the symbolic block diagram of the corresponding circuit model are proposed. Their decomposed forms enable us to determine quite separately the existence of the individual breakpoints of the resultant PWL characteristic and their coordinates using independent network parameters. For the two-diode and three-diode cases all the attainable types of the PWL characteristic are introduced.

  1. Artificial Immune Networks: Models and Applications

    Directory of Open Access Journals (Sweden)

    Xian Shen

    2008-06-01

    Full Text Available Artificial Immune Systems (AIS, which is inspired by the nature immune system, has been applied for solving complex computational problems in classification, pattern rec- ognition, and optimization. In this paper, the theory of the natural immune system is first briefly introduced. Next, we compare some well-known AIS and their applications. Several representative artificial immune networks models are also dis- cussed. Moreover, we demonstrate the applications of artificial immune networks in various engineering fields.

  2. Continuum Modeling of Biological Network Formation

    KAUST Repository

    Albi, Giacomo

    2017-04-10

    We present an overview of recent analytical and numerical results for the elliptic–parabolic system of partial differential equations proposed by Hu and Cai, which models the formation of biological transportation networks. The model describes the pressure field using a Darcy type equation and the dynamics of the conductance network under pressure force effects. Randomness in the material structure is represented by a linear diffusion term and conductance relaxation by an algebraic decay term. We first introduce micro- and mesoscopic models and show how they are connected to the macroscopic PDE system. Then, we provide an overview of analytical results for the PDE model, focusing mainly on the existence of weak and mild solutions and analysis of the steady states. The analytical part is complemented by extensive numerical simulations. We propose a discretization based on finite elements and study the qualitative properties of network structures for various parameter values.

  3. Adaptive-network models of collective dynamics

    Science.gov (United States)

    Zschaler, G.

    2012-09-01

    Complex systems can often be modelled as networks, in which their basic units are represented by abstract nodes and the interactions among them by abstract links. This network of interactions is the key to understanding emergent collective phenomena in such systems. In most cases, it is an adaptive network, which is defined by a feedback loop between the local dynamics of the individual units and the dynamical changes of the network structure itself. This feedback loop gives rise to many novel phenomena. Adaptive networks are a promising concept for the investigation of collective phenomena in different systems. However, they also present a challenge to existing modelling approaches and analytical descriptions due to the tight coupling between local and topological degrees of freedom. In this work, which is essentially my PhD thesis, I present a simple rule-based framework for the investigation of adaptive networks, using which a wide range of collective phenomena can be modelled and analysed from a common perspective. In this framework, a microscopic model is defined by the local interaction rules of small network motifs, which can be implemented in stochastic simulations straightforwardly. Moreover, an approximate emergent-level description in terms of macroscopic variables can be derived from the microscopic rules, which we use to analyse the system's collective and long-term behaviour by applying tools from dynamical systems theory. We discuss three adaptive-network models for different collective phenomena within our common framework. First, we propose a novel approach to collective motion in insect swarms, in which we consider the insects' adaptive interaction network instead of explicitly tracking their positions and velocities. We capture the experimentally observed onset of collective motion qualitatively in terms of a bifurcation in this non-spatial model. We find that three-body interactions are an essential ingredient for collective motion to emerge

  4. Network Design Models for Container Shipping

    DEFF Research Database (Denmark)

    Reinhardt, Line Blander; Kallehauge, Brian; Nielsen, Anders Nørrelund

    This paper presents a study of the network design problem in container shipping. The paper combines the network design and fleet assignment problem into a mixed integer linear programming model minimizing the overall cost. The major contributions of this paper is that the time of a vessel route...... is included in the calculation of the capacity and that a inhomogeneous fleet is modeled. The model also includes the cost of transshipment which is one of the major cost for the shipping companies. The concept of pseudo simple routes is introduced to expand the set of feasible routes. The linearization...

  5. Characterization and Modeling of Network Traffic

    DEFF Research Database (Denmark)

    Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur

    2011-01-01

    -arrival time, IP addresses, port numbers and transport protocol are the only necessary parameters to model network traffic behaviour. In order to recreate this behaviour, a complex model is needed which is able to recreate traffic behaviour based on a set of statistics calculated from the parameters values...

  6. Phenomenological network models: Lessons for epilepsy surgery.

    Science.gov (United States)

    Hebbink, Jurgen; Meijer, Hil; Huiskamp, Geertjan; van Gils, Stephan; Leijten, Frans

    2017-10-01

    The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational models offer a framework to investigate the influence of networks, as well as local tissue properties, and to explore alternative resection strategies. Here we study, using such a model, the influence of connections on seizures and how this might change our traditional views of epilepsy surgery. We use a simple network model consisting of four interconnected neuronal populations. One of these populations can be made hyperexcitable, modeling a pathological region of cortex. Using model simulations, the effect of surgery on the seizure rate is studied. We find that removal of the hyperexcitable population is, in most cases, not the best approach to reduce the seizure rate. Removal of normal populations located at a crucial spot in the network, the "driver," is typically more effective in reducing seizure rate. This work strengthens the idea that network structure and connections may be more important than localizing the pathological node. This can explain why lesionectomy may not always be sufficient. © 2017 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.

  7. Agent based modeling of energy networks

    International Nuclear Information System (INIS)

    Gonzalez de Durana, José María; Barambones, Oscar; Kremers, Enrique; Varga, Liz

    2014-01-01

    Highlights: • A new approach for energy network modeling is designed and tested. • The agent-based approach is general and no technology dependent. • The models can be easily extended. • The range of applications encompasses from small to large energy infrastructures. - Abstract: Attempts to model any present or future power grid face a huge challenge because a power grid is a complex system, with feedback and multi-agent behaviors, integrated by generation, distribution, storage and consumption systems, using various control and automation computing systems to manage electricity flows. Our approach to modeling is to build upon an established model of the low voltage electricity network which is tested and proven, by extending it to a generalized energy model. But, in order to address the crucial issues of energy efficiency, additional processes like energy conversion and storage, and further energy carriers, such as gas, heat, etc., besides the traditional electrical one, must be considered. Therefore a more powerful model, provided with enhanced nodes or conversion points, able to deal with multidimensional flows, is being required. This article addresses the issue of modeling a local multi-carrier energy network. This problem can be considered as an extension of modeling a low voltage distribution network located at some urban or rural geographic area. But instead of using an external power flow analysis package to do the power flow calculations, as used in electric networks, in this work we integrate a multiagent algorithm to perform the task, in a concurrent way to the other simulation tasks, and not only for the electric fluid but also for a number of additional energy carriers. As the model is mainly focused in system operation, generation and load models are not developed

  8. Delay and Disruption Tolerant Networking MACHETE Model

    Science.gov (United States)

    Segui, John S.; Jennings, Esther H.; Gao, Jay L.

    2011-01-01

    To verify satisfaction of communication requirements imposed by unique missions, as early as 2000, the Communications Networking Group at the Jet Propulsion Laboratory (JPL) saw the need for an environment to support interplanetary communication protocol design, validation, and characterization. JPL's Multi-mission Advanced Communications Hybrid Environment for Test and Evaluation (MACHETE), described in Simulator of Space Communication Networks (NPO-41373) NASA Tech Briefs, Vol. 29, No. 8 (August 2005), p. 44, combines various commercial, non-commercial, and in-house custom tools for simulation and performance analysis of space networks. The MACHETE environment supports orbital analysis, link budget analysis, communications network simulations, and hardware-in-the-loop testing. As NASA is expanding its Space Communications and Navigation (SCaN) capabilities to support planned and future missions, building infrastructure to maintain services and developing enabling technologies, an important and broader role is seen for MACHETE in design-phase evaluation of future SCaN architectures. To support evaluation of the developing Delay Tolerant Networking (DTN) field and its applicability for space networks, JPL developed MACHETE models for DTN Bundle Protocol (BP) and Licklider/Long-haul Transmission Protocol (LTP). DTN is an Internet Research Task Force (IRTF) architecture providing communication in and/or through highly stressed networking environments such as space exploration and battlefield networks. Stressed networking environments include those with intermittent (predictable and unknown) connectivity, large and/or variable delays, and high bit error rates. To provide its services over existing domain specific protocols, the DTN protocols reside at the application layer of the TCP/IP stack, forming a store-and-forward overlay network. The key capabilities of the Bundle Protocol include custody-based reliability, the ability to cope with intermittent connectivity

  9. A comprehensive Network Security Risk Model for process control networks.

    Science.gov (United States)

    Henry, Matthew H; Haimes, Yacov Y

    2009-02-01

    The risk of cyber attacks on process control networks (PCN) is receiving significant attention due to the potentially catastrophic extent to which PCN failures can damage the infrastructures and commodity flows that they support. Risk management addresses the coupled problems of (1) reducing the likelihood that cyber attacks would succeed in disrupting PCN operation and (2) reducing the severity of consequences in the event of PCN failure or manipulation. The Network Security Risk Model (NSRM) developed in this article provides a means of evaluating the efficacy of candidate risk management policies by modeling the baseline risk and assessing expectations of risk after the implementation of candidate measures. Where existing risk models fall short of providing adequate insight into the efficacy of candidate risk management policies due to shortcomings in their structure or formulation, the NSRM provides model structure and an associated modeling methodology that captures the relevant dynamics of cyber attacks on PCN for risk analysis. This article develops the NSRM in detail in the context of an illustrative example.

  10. Discrete dynamic modeling of cellular signaling networks.

    Science.gov (United States)

    Albert, Réka; Wang, Rui-Sheng

    2009-01-01

    Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

  11. Neural network modeling of associative memory: Beyond the Hopfield model

    Science.gov (United States)

    Dasgupta, Chandan

    1992-07-01

    A number of neural network models, in which fixed-point and limit-cycle attractors of the underlying dynamics are used to store and associatively recall information, are described. In the first class of models, a hierarchical structure is used to store an exponentially large number of strongly correlated memories. The second class of models uses limit cycles to store and retrieve individual memories. A neurobiologically plausible network that generates low-amplitude periodic variations of activity, similar to the oscillations observed in electroencephalographic recordings, is also described. Results obtained from analytic and numerical studies of the properties of these networks are discussed.

  12. Constitutive modelling of composite biopolymer networks.

    Science.gov (United States)

    Fallqvist, B; Kroon, M

    2016-04-21

    The mechanical behaviour of biopolymer networks is to a large extent determined at a microstructural level where the characteristics of individual filaments and the interactions between them determine the response at a macroscopic level. Phenomena such as viscoelasticity and strain-hardening followed by strain-softening are observed experimentally in these networks, often due to microstructural changes (such as filament sliding, rupture and cross-link debonding). Further, composite structures can also be formed with vastly different mechanical properties as compared to the individual networks. In this present paper, we present a constitutive model presented in a continuum framework aimed at capturing these effects. Special care is taken to formulate thermodynamically consistent evolution laws for dissipative effects. This model, incorporating possible anisotropic network properties, is based on a strain energy function, split into an isochoric and a volumetric part. Generalisation to three dimensions is performed by numerical integration over the unit sphere. Model predictions indicate that the constitutive model is well able to predict the elastic and viscoelastic response of biological networks, and to an extent also composite structures. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Modelling students' knowledge organisation: Genealogical conceptual networks

    Science.gov (United States)

    Koponen, Ismo T.; Nousiainen, Maija

    2018-04-01

    Learning scientific knowledge is largely based on understanding what are its key concepts and how they are related. The relational structure of concepts also affects how concepts are introduced in teaching scientific knowledge. We model here how students organise their knowledge when they represent their understanding of how physics concepts are related. The model is based on assumptions that students use simple basic linking-motifs in introducing new concepts and mostly relate them to concepts that were introduced a few steps earlier, i.e. following a genealogical ordering. The resulting genealogical networks have relatively high local clustering coefficients of nodes but otherwise resemble networks obtained with an identical degree distribution of nodes but with random linking between them (i.e. the configuration-model). However, a few key nodes having a special structural role emerge and these nodes have a higher than average communicability betweenness centralities. These features agree with the empirically found properties of students' concept networks.

  14. Modelling Users` Trust in Online Social Networks

    Directory of Open Access Journals (Sweden)

    Iacob Cătoiu

    2014-02-01

    Full Text Available Previous studies (McKnight, Lankton and Tripp, 2011; Liao, Lui and Chen, 2011 have shown the crucial role of trust when choosing to disclose sensitive information online. This is the case of online social networks users, who must disclose a certain amount of personal data in order to gain access to these online services. Taking into account privacy calculus model and the risk/benefit ratio, we propose a model of users’ trust in online social networks with four variables. We have adapted metrics for the purpose of our study and we have assessed their reliability and validity. We use a Partial Least Squares (PLS based structural equation modelling analysis, which validated all our initial assumptions, indicating that our three predictors (privacy concerns, perceived benefits and perceived risks explain 48% of the variation of users’ trust in online social networks, the resulting variable of our study. We also discuss the implications and further research opportunities of our study.

  15. Bayesian network modelling of upper gastrointestinal bleeding

    Science.gov (United States)

    Aisha, Nazziwa; Shohaimi, Shamarina; Adam, Mohd Bakri

    2013-09-01

    Bayesian networks are graphical probabilistic models that represent causal and other relationships between domain variables. In the context of medical decision making, these models have been explored to help in medical diagnosis and prognosis. In this paper, we discuss the Bayesian network formalism in building medical support systems and we learn a tree augmented naive Bayes Network (TAN) from gastrointestinal bleeding data. The accuracy of the TAN in classifying the source of gastrointestinal bleeding into upper or lower source is obtained. The TAN achieves a high classification accuracy of 86% and an area under curve of 92%. A sensitivity analysis of the model shows relatively high levels of entropy reduction for color of the stool, history of gastrointestinal bleeding, consistency and the ratio of blood urea nitrogen to creatinine. The TAN facilitates the identification of the source of GIB and requires further validation.

  16. Cy3 and Cy5 dyes attached to oligonucleotide terminus stabilize DNA duplexes: predictive thermodynamic model.

    Science.gov (United States)

    Moreira, Bernardo G; You, Yong; Owczarzy, Richard

    2015-03-01

    Cyanine dyes are important chemical modifications of oligonucleotides exhibiting intensive and stable fluorescence at visible light wavelengths. When Cy3 or Cy5 dye is attached to 5' end of a DNA duplex, the dye stacks on the terminal base pair and stabilizes the duplex. Using optical melting experiments, we have determined thermodynamic parameters that can predict the effects of the dyes on duplex stability quantitatively (ΔG°, Tm). Both Cy dyes enhance duplex formation by 1.2 kcal/mol on average, however, this Gibbs energy contribution is sequence-dependent. If the Cy5 is attached to a pyrimidine nucleotide of pyrimidine-purine base pair, the stabilization is larger compared to the attachment to a purine nucleotide. This is likely due to increased stacking interactions of the dye to the purine of the complementary strand. Dangling (unpaired) nucleotides at duplex terminus are also known to enhance duplex stability. Stabilization originated from the Cy dyes is significantly larger than the stabilization due to the presence of dangling nucleotides. If both the dangling base and Cy3 are present, their thermodynamic contributions are approximately additive. New thermodynamic parameters improve predictions of duplex folding, which will help design oligonucleotide sequences for biophysical, biological, engineering, and nanotechnology applications. Copyright © 2015. Published by Elsevier B.V.

  17. A Model of Network Porosity

    Science.gov (United States)

    2016-02-04

    of complex systems [1]. Although the ODD protocol was originally intended for individual-based or agent-based models ( ABM ), we adopt this protocol for...applies to information transfer between air-gapped systems . Trust relationships between devices (e.g. a trust relationship created by a domain controller...prevention systems , and data leakage protection systems . 2.2 ATTACKER The model specifies an attacker who gains access to internal enclaves by

  18. Modeling and optimization of potable water network

    Energy Technology Data Exchange (ETDEWEB)

    Djebedjian, B.; Rayan, M.A. [Mansoura Univ., El-Mansoura (Egypt); Herrick, A. [Suez Canal Authority, Ismailia (Egypt)

    2000-07-01

    Software was developed in order to optimize the design of water distribution systems and pipe networks. While satisfying all the constraints imposed such as pipe diameter and nodal pressure, it was based on a mathematical model treating looped networks. The optimum network configuration and cost are determined considering parameters like pipe diameter, flow rate, corresponding pressure and hydraulic losses. It must be understood that minimum cost is relative to the different objective functions selected. The determination of the proper objective function often depends on the operating policies of a particular company. The solution for the optimization technique was obtained by using a non-linear technique. To solve the optimal design of network, the model was derived using the sequential unconstrained minimization technique (SUMT) of Fiacco and McCormick, which decreased the number of iterations required. The pipe diameters initially assumed were successively adjusted to correspond to the existing commercial pipe diameters. The technique was then applied to a two-loop network without pumps or valves. Fed by gravity, it comprised eight pipes, 1000 m long each. The first evaluation of the method proved satisfactory. As with other methods, it failed to find the global optimum. In the future, research efforts will be directed to the optimization of networks with pumps and reservoirs. 24 refs., 3 tabs., 1 fig.

  19. Modelling dendritic ecological networks in space: An integrated network perspective

    Science.gov (United States)

    Erin E. Peterson; Jay M. Ver Hoef; Dan J. Isaak; Jeffrey A. Falke; Marie-Josee Fortin; Chris E. Jordan; Kristina McNyset; Pascal Monestiez; Aaron S. Ruesch; Aritra Sengupta; Nicholas Som; E. Ashley Steel; David M. Theobald; Christian E. Torgersen; Seth J. Wenger

    2013-01-01

    Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of...

  20. PREDIKSI FOREX MENGGUNAKAN MODEL NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    R. Hadapiningradja Kusumodestoni

    2015-11-01

    Full Text Available ABSTRAK Prediksi adalah salah satu teknik yang paling penting dalam menjalankan bisnis forex. Keputusan dalam memprediksi adalah sangatlah penting, karena dengan prediksi dapat membantu mengetahui nilai forex di waktu tertentu kedepan sehingga dapat mengurangi resiko kerugian. Tujuan dari penelitian ini dimaksudkan memprediksi bisnis fores menggunakan model neural network dengan data time series per 1 menit untuk mengetahui nilai akurasi prediksi sehingga dapat mengurangi resiko dalam menjalankan bisnis forex. Metode penelitian pada penelitian ini meliputi metode pengumpulan data kemudian dilanjutkan ke metode training, learning, testing menggunakan neural network. Setelah di evaluasi hasil penelitian ini menunjukan bahwa penerapan algoritma Neural Network mampu untuk memprediksi forex dengan tingkat akurasi prediksi 0.431 +/- 0.096 sehingga dengan prediksi ini dapat membantu mengurangi resiko dalam menjalankan bisnis forex. Kata kunci: prediksi, forex, neural network.

  1. Artificial neural network cardiopulmonary modeling and diagnosis

    Science.gov (United States)

    Kangas, Lars J.; Keller, Paul E.

    1997-01-01

    The present invention is a method of diagnosing a cardiopulmonary condition in an individual by comparing data from a progressive multi-stage test for the individual to a non-linear multi-variate model, preferably a recurrent artificial neural network having sensor fusion. The present invention relies on a cardiovascular model developed from physiological measurements of an individual. Any differences between the modeled parameters and the parameters of an individual at a given time are used for diagnosis.

  2. Green Network Planning Model for Optical Backbones

    DEFF Research Database (Denmark)

    Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Jensen, Michael

    2010-01-01

    on the environment in general. In network planning there are existing planning models focused on QoS provisioning, investment minimization or combinations of both and other parameters. But there is a lack of a model for designing green optical backbones. This paper presents novel ideas to be able to define......Communication networks are becoming more essential for our daily lives and critically important for industry and governments. The intense growth in the backbone traffic implies an increment of the power demands of the transmission systems. This power usage might have a significant negative effect...

  3. A Model for Telestrok Network Evaluation

    DEFF Research Database (Denmark)

    Storm, Anna; Günzel, Franziska; Theiss, Stephan

    2011-01-01

    analysis lacking, current telestroke reimbursement by third-party payers is limited to special contracts and not included in the regular billing system. Based on a systematic literature review and expert interviews with health care economists, third-party payers and neurologists, a Markov model...... was developed from the third-party payer perspective. In principle, it enables telestroke networks to conduct cost-effectiveness studies, because the majority of the required data can be extracted from health insurance companies’ databases and the telestroke network itself. The model presents a basis...

  4. PROJECT ACTIVITY ANALYSIS WITHOUT THE NETWORK MODEL

    Directory of Open Access Journals (Sweden)

    S. Munapo

    2012-01-01

    Full Text Available

    ENGLISH ABSTRACT: This paper presents a new procedure for analysing and managing activity sequences in projects. The new procedure determines critical activities, critical path, start times, free floats, crash limits, and other useful information without the use of the network model. Even though network models have been successfully used in project management so far, there are weaknesses associated with the use. A network is not easy to generate, and dummies that are usually associated with it make the network diagram complex – and dummy activities have no meaning in the original project management problem. The network model for projects can be avoided while still obtaining all the useful information that is required for project management. What are required are the activities, their accurate durations, and their predecessors.

    AFRIKAANSE OPSOMMING: Die navorsing beskryf ’n nuwerwetse metode vir die ontleding en bestuur van die sekwensiële aktiwiteite van projekte. Die voorgestelde metode bepaal kritiese aktiwiteite, die kritieke pad, aanvangstye, speling, verhasing, en ander groothede sonder die gebruik van ’n netwerkmodel. Die metode funksioneer bevredigend in die praktyk, en omseil die administratiewe rompslomp van die tradisionele netwerkmodelle.

  5. Mobility Models for Next Generation Wireless Networks Ad Hoc, Vehicular and Mesh Networks

    CERN Document Server

    Santi, Paolo

    2012-01-01

    Mobility Models for Next Generation Wireless Networks: Ad Hoc, Vehicular and Mesh Networks provides the reader with an overview of mobility modelling, encompassing both theoretical and practical aspects related to the challenging mobility modelling task. It also: Provides up-to-date coverage of mobility models for next generation wireless networksOffers an in-depth discussion of the most representative mobility models for major next generation wireless network application scenarios, including WLAN/mesh networks, vehicular networks, wireless sensor networks, and

  6. Modeling Renewable Penertration Using a Network Economic Model

    Science.gov (United States)

    Lamont, A.

    2001-03-01

    This paper evaluates the accuracy of a network economic modeling approach in designing energy systems having renewable and conventional generators. The network approach models the system as a network of processes such as demands, generators, markets, and resources. The model reaches a solution by exchanging prices and quantity information between the nodes of the system. This formulation is very flexible and takes very little time to build and modify models. This paper reports an experiment designing a system with photovoltaic and base and peak fossil generators. The level of PV penetration as a function of its price and the capacities of the fossil generators were determined using the network approach and using an exact, analytic approach. It is found that the two methods agree very closely in terms of the optimal capacities and are nearly identical in terms of annual system costs.

  7. Security Modeling on the Supply Chain Networks

    Directory of Open Access Journals (Sweden)

    Marn-Ling Shing

    2007-10-01

    Full Text Available In order to keep the price down, a purchaser sends out the request for quotation to a group of suppliers in a supply chain network. The purchaser will then choose a supplier with the best combination of price and quality. A potential supplier will try to collect the related information about other suppliers so he/she can offer the best bid to the purchaser. Therefore, confidentiality becomes an important consideration for the design of a supply chain network. Chen et al. have proposed the application of the Bell-LaPadula model in the design of a secured supply chain network. In the Bell-LaPadula model, a subject can be in one of different security clearances and an object can be in one of various security classifications. All the possible combinations of (Security Clearance, Classification pair in the Bell-LaPadula model can be thought as different states in the Markov Chain model. This paper extends the work done by Chen et al., provides more details on the Markov Chain model and illustrates how to use it to monitor the security state transition in the supply chain network.

  8. An autocatalytic network model for stock markets

    Science.gov (United States)

    Caetano, Marco Antonio Leonel; Yoneyama, Takashi

    2015-02-01

    The stock prices of companies with businesses that are closely related within a specific sector of economy might exhibit movement patterns and correlations in their dynamics. The idea in this work is to use the concept of autocatalytic network to model such correlations and patterns in the trends exhibited by the expected returns. The trends are expressed in terms of positive or negative returns within each fixed time interval. The time series derived from these trends is then used to represent the movement patterns by a probabilistic boolean network with transitions modeled as an autocatalytic network. The proposed method might be of value in short term forecasting and identification of dependencies. The method is illustrated with a case study based on four stocks of companies in the field of natural resource and technology.

  9. Keystone Business Models for Network Security Processors

    Directory of Open Access Journals (Sweden)

    Arthur Low

    2013-07-01

    Full Text Available Network security processors are critical components of high-performance systems built for cybersecurity. Development of a network security processor requires multi-domain experience in semiconductors and complex software security applications, and multiple iterations of both software and hardware implementations. Limited by the business models in use today, such an arduous task can be undertaken only by large incumbent companies and government organizations. Neither the “fabless semiconductor” models nor the silicon intellectual-property licensing (“IP-licensing” models allow small technology companies to successfully compete. This article describes an alternative approach that produces an ongoing stream of novel network security processors for niche markets through continuous innovation by both large and small companies. This approach, referred to here as the "business ecosystem model for network security processors", includes a flexible and reconfigurable technology platform, a “keystone” business model for the company that maintains the platform architecture, and an extended ecosystem of companies that both contribute and share in the value created by innovation. New opportunities for business model innovation by participating companies are made possible by the ecosystem model. This ecosystem model builds on: i the lessons learned from the experience of the first author as a senior integrated circuit architect for providers of public-key cryptography solutions and as the owner of a semiconductor startup, and ii the latest scholarly research on technology entrepreneurship, business models, platforms, and business ecosystems. This article will be of interest to all technology entrepreneurs, but it will be of particular interest to owners of small companies that provide security solutions and to specialized security professionals seeking to launch their own companies.

  10. Modeling and Simulation Network Data Standards

    Science.gov (United States)

    2011-09-30

    approaches . 2.3. JNAT. JNAT is a Web application that provides connectivity and network analysis capability. JNAT uses propagation models and low-fidelity...COMBATXXI Movement Logger Data Output Dictionary. Field # Geocentric Coordinates (GCC) Heading Geodetic Coordinates (GDC) Heading Universal...B-8 Field # Geocentric Coordinates (GCC) Heading Geodetic Coordinates (GDC) Heading Universal Transverse Mercator (UTM) Heading

  11. The Kuramoto model in complex networks

    Science.gov (United States)

    Rodrigues, Francisco A.; Peron, Thomas K. DM.; Ji, Peng; Kurths, Jürgen

    2016-01-01

    Synchronization of an ensemble of oscillators is an emergent phenomenon present in several complex systems, ranging from social and physical to biological and technological systems. The most successful approach to describe how coherent behavior emerges in these complex systems is given by the paradigmatic Kuramoto model. This model has been traditionally studied in complete graphs. However, besides being intrinsically dynamical, complex systems present very heterogeneous structure, which can be represented as complex networks. This report is dedicated to review main contributions in the field of synchronization in networks of Kuramoto oscillators. In particular, we provide an overview of the impact of network patterns on the local and global dynamics of coupled phase oscillators. We cover many relevant topics, which encompass a description of the most used analytical approaches and the analysis of several numerical results. Furthermore, we discuss recent developments on variations of the Kuramoto model in networks, including the presence of noise and inertia. The rich potential for applications is discussed for special fields in engineering, neuroscience, physics and Earth science. Finally, we conclude by discussing problems that remain open after the last decade of intensive research on the Kuramoto model and point out some promising directions for future research.

  12. An architectural model for network interconnection

    NARCIS (Netherlands)

    van Sinderen, Marten J.; Vissers, C.A.; Kalin, T.

    1983-01-01

    This paper presents a technique of successive decomposition of a common users' activity to illustrate the problems of network interconnection. The criteria derived from this approach offer a structuring principle which is used to develop an architectural model that embeds heterogeneous subnetworks

  13. Computational Modeling of Complex Protein Activity Networks

    NARCIS (Netherlands)

    Schivo, Stefano; Leijten, Jeroen; Karperien, Marcel; Post, Janine N.; Prignet, Claude

    2017-01-01

    Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a

  14. A Model of Mental State Transition Network

    Science.gov (United States)

    Xiang, Hua; Jiang, Peilin; Xiao, Shuang; Ren, Fuji; Kuroiwa, Shingo

    Emotion is one of the most essential and basic attributes of human intelligence. Current AI (Artificial Intelligence) research is concentrating on physical components of emotion, rarely is it carried out from the view of psychology directly(1). Study on the model of artificial psychology is the first step in the development of human-computer interaction. As affective computing remains unpredictable, creating a reasonable mental model becomes the primary task for building a hybrid system. A pragmatic mental model is also the fundament of some key topics such as recognition and synthesis of emotions. In this paper a Mental State Transition Network Model(2) is proposed to detect human emotions. By a series of psychological experiments, we present a new way to predict coming human's emotions depending on the various current emotional states under various stimuli. Besides, people in different genders and characters are taken into consideration in our investigation. According to the psychological experiments data derived from 200 questionnaires, a Mental State Transition Network Model for describing the transitions in distribution among the emotions and relationships between internal mental situations and external are concluded. Further more the coefficients of the mental transition network model were achieved. Comparing seven relative evaluating experiments, an average precision rate of 0.843 is achieved using a set of samples for the proposed model.

  15. UAV Trajectory Modeling Using Neural Networks

    Science.gov (United States)

    Xue, Min

    2017-01-01

    Massive small unmanned aerial vehicles are envisioned to operate in the near future. While there are lots of research problems need to be addressed before dense operations can happen, trajectory modeling remains as one of the keys to understand and develop policies, regulations, and requirements for safe and efficient unmanned aerial vehicle operations. The fidelity requirement of a small unmanned vehicle trajectory model is high because these vehicles are sensitive to winds due to their small size and low operational altitude. Both vehicle control systems and dynamic models are needed for trajectory modeling, which makes the modeling a great challenge, especially considering the fact that manufactures are not willing to share their control systems. This work proposed to use a neural network approach for modelling small unmanned vehicle's trajectory without knowing its control system and bypassing exhaustive efforts for aerodynamic parameter identification. As a proof of concept, instead of collecting data from flight tests, this work used the trajectory data generated by a mathematical vehicle model for training and testing the neural network. The results showed great promise because the trained neural network can predict 4D trajectories accurately, and prediction errors were less than 2:0 meters in both temporal and spatial dimensions.

  16. Modeling Insurgent Network Structure and Dynamics

    Science.gov (United States)

    Gabbay, Michael; Thirkill-Mackelprang, Ashley

    2010-03-01

    We present a methodology for mapping insurgent network structure based on their public rhetoric. Indicators of cooperative links between insurgent groups at both the leadership and rank-and-file levels are used, such as joint policy statements or joint operations claims. In addition, a targeting policy measure is constructed on the basis of insurgent targeting claims. Network diagrams which integrate these measures of insurgent cooperation and ideology are generated for different periods of the Iraqi and Afghan insurgencies. The network diagrams exhibit meaningful changes which track the evolution of the strategic environment faced by insurgent groups. Correlations between targeting policy and network structure indicate that insurgent targeting claims are aimed at establishing a group identity among the spectrum of rank-and-file insurgency supporters. A dynamical systems model of insurgent alliance formation and factionalism is presented which evolves the relationship between insurgent group dyads as a function of their ideological differences and their current relationships. The ability of the model to qualitatively and quantitatively capture insurgent network dynamics observed in the data is discussed.

  17. Influence of extracellular matrix proteins on human keratinocyte attachment, proliferation and transfer to a dermal wound model.

    Science.gov (United States)

    Dawson, R A; Goberdhan, N J; Freedlander, E; MacNeil, S

    1996-03-01

    The aim of this study was to investigate whether prior culture of cells on ECM proteins might positively influence the performance of keratinocytes when cells are transferred to a dermal in vitro wound bed model. Keratinocytes were cultured using a method for producing cultured epithelial autografts for severely burned patients (essentially using Green's medium, a mitogen-rich medium containing fetal calf serum, cholera toxin, EGF, insulin, transferrin and triiodothyronine). Cells were cultured either on irradiated 3T3 fibroblasts (as in the standard Rheinwald and Green technique) or, alternatively, on collagen I, collagen IV, matrigel, RGD, vitronectin or fibronectin. Under these conditions matrigel, collagen I and IV enhanced initial attachment, RGD, vitronectin, fibronectin and irradiated 3T3 fibroblasts did not. Proliferation of cells was positively influenced by matrigel, collagen I and IV and irradiated 3T3 fibroblasts; of these, however, only matrigel and 3T3 fibroblasts had sustained significant effects on keratinocyte proliferation over 4 days. Cells on fibronectin showed significantly reduced proliferation. An acellular non-viable dermis was then used to mimic the homograft allodermis onto which cultured epithelial autograft sheets are grafted clinically and cells cultured on the various ECM proteins for 96 h were transferred to this in vitro wound model. None of the substrates enhanced keratinocyte performance on this model. It was concluded that under these conditions some ECM proteins can significantly affect keratinocyte attachment and, to a lesser extent, proliferation but that the culture of keratinocytes on these ECM proteins does not appear to confer any lasting benefit to the attachment of these keratinocytes to an in vitro wound-bed model.

  18. Hybrid simulation models of production networks

    CERN Document Server

    Kouikoglou, Vassilis S

    2001-01-01

    This book is concerned with a most important area of industrial production, that of analysis and optimization of production lines and networks using discrete-event models and simulation. The book introduces a novel approach that combines analytic models and discrete-event simulation. Unlike conventional piece-by-piece simulation, this method observes a reduced number of events between which the evolution of the system is tracked analytically. Using this hybrid approach, several models are developed for the analysis of production lines and networks. The hybrid approach combines speed and accuracy for exceptional analysis of most practical situations. A number of optimization problems, involving buffer design, workforce planning, and production control, are solved through the use of hybrid models.

  19. Propagating semantic information in biochemical network models

    Directory of Open Access Journals (Sweden)

    Schulz Marvin

    2012-01-01

    Full Text Available Abstract Background To enable automatic searches, alignments, and model combination, the elements of systems biology models need to be compared and matched across models. Elements can be identified by machine-readable biological annotations, but assigning such annotations and matching non-annotated elements is tedious work and calls for automation. Results A new method called "semantic propagation" allows the comparison of model elements based not only on their own annotations, but also on annotations of surrounding elements in the network. One may either propagate feature vectors, describing the annotations of individual elements, or quantitative similarities between elements from different models. Based on semantic propagation, we align partially annotated models and find annotations for non-annotated model elements. Conclusions Semantic propagation and model alignment are included in the open-source library semanticSBML, available on sourceforge. Online services for model alignment and for annotation prediction can be used at http://www.semanticsbml.org.

  20. The 5’cap of Tobacco Mosaic Virus (TMV) is required for virion attachment to the actin/ER network during early infection

    DEFF Research Database (Denmark)

    Christensen, Nynne Meyn; Tilsner, Jens; Bell, Karen

    to the motile cortical actin/ER network within minutes of injection. Granule movement on actin/ER was arrested by actin inhibitors indicating actindependent RNA movement. The 5’ methylguanosine TMV cap was shown to be required for vRNA anchoring to the ER. TMV vRNA lacking the 5’cap failed to form granules...... the fluorescent vRNA pool nor co-injected GFP left the injected trichome, indicating that the synthesis of unlabelled progeny viral (v)RNA is required to initiate cell-cell movement, and that virus movement is not accompanied by passive plasmodesmatal gating. Cy3-vRNA formed granules that became anchored...... on the same ER-bound granules, indicating that TMV virions may become attached to the ER prior to uncoating of the viral genome....

  1. Model Predictive Control of Sewer Networks

    DEFF Research Database (Denmark)

    Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik

    2016-01-01

    The developments in solutions for management of urban drainage are of vital importance, as the amount of sewer water from urban areas continues to increase due to the increase of the world’s population and the change in the climate conditions. How a sewer network is structured, monitored and cont...... benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control....

  2. Modeling Multistandard Wireless Networks in OPNET

    DEFF Research Database (Denmark)

    Zakrzewska, Anna; Berger, Michael Stübert; Ruepp, Sarah Renée

    2011-01-01

    Future wireless communication is emerging towards one heterogeneous platform. In this new environment wireless access will be provided by multiple radio technologies that are cooperating and complementing one another. The paper investigates the possibilities of developing such a multistandard sys...... system using OPNET Modeler. A network model consisting of LTE interworking with WLAN and WiMAX is considered from the radio resource management perspective. In particular, implementing a joint packet scheduler across multiple systems is discussed more in detail....

  3. Modelling dendritic ecological networks in space: anintegrated network perspective

    Science.gov (United States)

    Peterson, Erin E.; Ver Hoef, Jay M.; Isaak, Dan J.; Falke, Jeffrey A.; Fortin, Marie-Josée; Jordon, Chris E.; McNyset, Kristina; Monestiez, Pascal; Ruesch, Aaron S.; Sengupta, Aritra; Som, Nicholas; Steel, E. Ashley; Theobald, David M.; Torgersen, Christian E.; Wenger, Seth J.

    2013-01-01

    Dendritic ecological networks (DENs) are a unique form of ecological networks that exhibit a dendritic network topology (e.g. stream and cave networks or plant architecture). DENs have a dual spatial representation; as points within the network and as points in geographical space. Consequently, some analytical methods used to quantify relationships in other types of ecological networks, or in 2-D space, may be inadequate for studying the influence of structure and connectivity on ecological processes within DENs. We propose a conceptual taxonomy of network analysis methods that account for DEN characteristics to varying degrees and provide a synthesis of the different approaches within

  4. Functional model of biological neural networks.

    Science.gov (United States)

    Lo, James Ting-Ho

    2010-12-01

    A functional model of biological neural networks, called temporal hierarchical probabilistic associative memory (THPAM), is proposed in this paper. THPAM comprises functional models of dendritic trees for encoding inputs to neurons, a first type of neuron for generating spike trains, a second type of neuron for generating graded signals to modulate neurons of the first type, supervised and unsupervised Hebbian learning mechanisms for easy learning and retrieving, an arrangement of dendritic trees for maximizing generalization, hardwiring for rotation-translation-scaling invariance, and feedback connections with different delay durations for neurons to make full use of present and past informations generated by neurons in the same and higher layers. These functional models and their processing operations have many functions of biological neural networks that have not been achieved by other models in the open literature and provide logically coherent answers to many long-standing neuroscientific questions. However, biological justifications of these functional models and their processing operations are required for THPAM to qualify as a macroscopic model (or low-order approximate) of biological neural networks.

  5. On traffic modelling in GPRS networks

    DEFF Research Database (Denmark)

    Madsen, Tatiana Kozlova; Schwefel, Hans-Peter; Prasad, Ramjee

    2005-01-01

    Optimal design and dimensioning of wireless data networks, such as GPRS, requires the knowledge of traffic characteristics of different data services. This paper presents an in-detail analysis of an IP-level traffic measurements taken in an operational GPRS network. The data measurements reported...... here are done at the Gi interface. The aim of this paper is to reveal some key statistics of GPRS data applications and to validate if the existing traffic models can adequately describe traffic volume and inter-arrival time distribution for different services. Additionally, we present a method of user...

  6. A Networks Approach to Modeling Enzymatic Reactions.

    Science.gov (United States)

    Imhof, P

    2016-01-01

    Modeling enzymatic reactions is a demanding task due to the complexity of the system, the many degrees of freedom involved and the complex, chemical, and conformational transitions associated with the reaction. Consequently, enzymatic reactions are not determined by precisely one reaction pathway. Hence, it is beneficial to obtain a comprehensive picture of possible reaction paths and competing mechanisms. By combining individually generated intermediate states and chemical transition steps a network of such pathways can be constructed. Transition networks are a discretized representation of a potential energy landscape consisting of a multitude of reaction pathways connecting the end states of the reaction. The graph structure of the network allows an easy identification of the energetically most favorable pathways as well as a number of alternative routes. © 2016 Elsevier Inc. All rights reserved.

  7. A improved Network Security Situation Awareness Model

    Directory of Open Access Journals (Sweden)

    Li Fangwei

    2015-08-01

    Full Text Available In order to reflect the situation of network security assessment performance fully and accurately, a new network security situation awareness model based on information fusion was proposed. Network security situation is the result of fusion three aspects evaluation. In terms of attack, to improve the accuracy of evaluation, a situation assessment method of DDoS attack based on the information of data packet was proposed. In terms of vulnerability, a improved Common Vulnerability Scoring System (CVSS was raised and maked the assessment more comprehensive. In terms of node weights, the method of calculating the combined weights and optimizing the result by Sequence Quadratic Program (SQP algorithm which reduced the uncertainty of fusion was raised. To verify the validity and necessity of the method, a testing platform was built and used to test through evaluating 2000 DAPRA data sets. Experiments show that the method can improve the accuracy of evaluation results.

  8. Exploring the role of experiential avoidance from the perspective of attachment theory and the dual process model.

    Science.gov (United States)

    Shear, M Katherine

    2010-01-01

    Avoidance can be adaptive and facilitate the healing process of acute grief or it can be maladaptive and hinder this same process. Maladaptive cognitive or behavioral avoidance comprises the central feature of the condition of complicated grief. This article explores the concept of experiential avoidance as it applies to bereavement, including when it is adaptive when it is problematic. Adaptive avoidance is framed using an attachment theory perspective and incorporates insights from the dual process model (DPM). An approach to clinical management of experiential avoidance in the syndrome of complicated grief is included.

  9. Spatial Models and Networks of Living Systems

    DEFF Research Database (Denmark)

    Juul, Jeppe Søgaard

    When studying the dynamics of living systems, insight can often be gained by developing a mathematical model that can predict future behaviour of the system or help classify system characteristics. However, in living cells, organisms, and especially groups of interacting individuals, a large number...... variables of the system. However, this approach disregards any spatial structure of the system, which may potentially change the behaviour drastically. An alternative approach is to construct a cellular automaton with nearest neighbour interactions, or even to model the system as a complex network...... with interactions defined by network topology. In this thesis I first describe three different biological models of ageing and cancer, in which spatial structure is important for the system dynamics. I then turn to describe characteristics of ecosystems consisting of three cyclically interacting species...

  10. Fractional virus epidemic model on financial networks

    Directory of Open Access Journals (Sweden)

    Balci Mehmet Ali

    2016-01-01

    Full Text Available In this study, we present an epidemic model that characterizes the behavior of a financial network of globally operating stock markets. Since the long time series have a global memory effect, we represent our model by using the fractional calculus. This model operates on a network, where vertices are the stock markets and edges are constructed by the correlation distances. Thereafter, we find an analytical solution to commensurate system and use the well-known differential transform method to obtain the solution of incommensurate system of fractional differential equations. Our findings are confirmed and complemented by the data set of the relevant stock markets between 2006 and 2016. Rather than the hypothetical values, we use the Hurst Exponent of each time series to approximate the fraction size and graph theoretical concepts to obtain the variables.

  11. Entanglement effects in model polymer networks

    Science.gov (United States)

    Everaers, R.; Kremer, K.

    The influence of topological constraints on the local dynamics in cross-linked polymer melts and their contribution to the elastic properties of rubber elastic systems are a long standing problem in statistical mechanics. Polymer networks with diamond lattice connectivity (Everaers and Kremer 1995, Everaers and Kremer 1996a) are idealized model systems which isolate the effect of topology conservation from other sources of quenched disorder. We study their behavior in molecular dynamics simulations under elongational strain. In our analysis we compare the measured, purely entropic shear moduli G to the predictions of statistical mechanical models of rubber elasticity, making extensive use of the microscopic structural and topological information available in computer simulations. We find (Everaers and Kremer 1995) that the classical models of rubber elasticity underestimate the true change in entropy in a deformed network significantly, because they neglect the tension along the contour of the strands which cannot relax due to entanglements (Everaers and Kremer (in preparation)). This contribution and the fluctuations in strained systems seem to be well described by the constrained mode model (Everaers 1998) which allows to treat the crossover from classical rubber elasticity to the tube model for polymer networks with increasing strand length within one transparant formalism. While this is important for the description of the effects we try to do a first quantitative step towards their explanation by topological considerations. We show (Everaers and Kremer 1996a) that for the comparatively short strand lengths of our diamond networks the topology contribution to the shear modulus is proportional to the density of entangled mesh pairs with non-zero Gauss linking number. Moreover, the prefactor can be estimated consistently within a rather simple model developed by Vologodskii et al. and by Graessley and Pearson, which is based on the definition of an entropic

  12. Vectorization of a classical trajectory code on a floating point systems, Inc. Model 164 attached processor.

    Science.gov (United States)

    Kraus, Wayne A; Wagner, Albert F

    1986-04-01

    A triatomic classical trajectory code has been modified by extensive vectorization of the algorithms to achieve much improved performance on an FPS 164 attached processor. Extensive timings on both the FPS 164 and a VAX 11/780 with floating point accelerator are presented as a function of the number of trajectories simultaneously run. The timing tests involve a potential energy surface of the LEPS variety and trajectories with 1000 time steps. The results indicate that vectorization results in timing improvements on both the VAX and the FPS. For larger numbers of trajectories run simultaneously, up to a factor of 25 improvement in speed occurs between VAX and FPS vectorized code. Copyright © 1986 John Wiley & Sons, Inc.

  13. Modelling fragmentations of amino-acids after resonant electron attachment: quantum evidence of possible direct -OH detachment

    Energy Technology Data Exchange (ETDEWEB)

    Panosetti, C.; Sebastianelli, F.; Gianturco, F.A. [Department of Chemistry and CNISM, University of Rome -La Sapienza-, Roma (Italy); Baccarelli, I. [CASPUR, Supercomputing Consortium for University and Research, Roma (Italy)

    2010-10-15

    We investigate some aspects of the radiation damage mechanisms in biomolecules, focusing on the modelling of resonant fragmentation caused by the attachment of low-energy electrons (LEEs) initially ejected by biological tissues when exposed to ionizing radiation. Scattering equations are formulated within a symmetry-adapted, single-center expansion of both continuum and bound electrons, and the interaction forces are obtained from a combination of ab initio calculations and a nonempirical model of exchange and correlation effects developed in our group. We present total elastic scattering cross-sections and resonance features obtained for the equilibrium geometries of glycine, alanine, proline and valine. Our results at those geometries of the target molecules are briefly shown to qualitatively explain some of the fragmentation patterns obtained in experiments. We further carry out a one-dimensional (1D) modeling for the dynamics of intramolecular energy transfers mediated by the vibrational activation of selected bonds: our calculations indicate that resonant electron attachment to glycine can trigger direct, dissociative evolution of the complex into (Gly-OH)- and -OH losses, while they also find that the same process does not occur via a direct, 1D dissociative path in the larger amino acids of the present study. (authors)

  14. Northern emporia and maritime networks. Modelling past communication using archaeological network analysis

    DEFF Research Database (Denmark)

    Sindbæk, Søren Michael

    2015-01-01

    preserve patterns of thisinteraction. Formal network analysis and modelling holds the potential to identify anddemonstrate such patterns, where traditional methods often prove inadequate. Thearchaeological study of communication networks in the past, however, calls for radically different analytical...... this is not a problem of network analysis, but network synthesis: theclassic problem of cracking codes or reconstructing black-box circuits. It is proposedthat archaeological approaches to network synthesis must involve a contextualreading of network data: observations arising from individual contexts, morphologies...

  15. Performance modeling, loss networks, and statistical multiplexing

    CERN Document Server

    Mazumdar, Ravi

    2009-01-01

    This monograph presents a concise mathematical approach for modeling and analyzing the performance of communication networks with the aim of understanding the phenomenon of statistical multiplexing. The novelty of the monograph is the fresh approach and insights provided by a sample-path methodology for queueing models that highlights the important ideas of Palm distributions associated with traffic models and their role in performance measures. Also presented are recent ideas of large buffer, and many sources asymptotics that play an important role in understanding statistical multiplexing. I

  16. Artificial Neural Network Model for Predicting Compressive

    Directory of Open Access Journals (Sweden)

    Salim T. Yousif

    2013-05-01

    Full Text Available   Compressive strength of concrete is a commonly used criterion in evaluating concrete. Although testing of the compressive strength of concrete specimens is done routinely, it is performed on the 28th day after concrete placement. Therefore, strength estimation of concrete at early time is highly desirable. This study presents the effort in applying neural network-based system identification techniques to predict the compressive strength of concrete based on concrete mix proportions, maximum aggregate size (MAS, and slump of fresh concrete. Back-propagation neural networks model is successively developed, trained, and tested using actual data sets of concrete mix proportions gathered from literature.    The test of the model by un-used data within the range of input parameters shows that the maximum absolute error for model is about 20% and 88% of the output results has absolute errors less than 10%. The parametric study shows that water/cement ratio (w/c is the most significant factor  affecting the output of the model.     The results showed that neural networks has strong potential as a feasible tool for predicting compressive strength of concrete.

  17. UAV Trajectory Modeling Using Neural Networks

    Science.gov (United States)

    Xue, Min

    2017-01-01

    Large amount of small Unmanned Aerial Vehicles (sUAVs) are projected to operate in the near future. Potential sUAV applications include, but not limited to, search and rescue, inspection and surveillance, aerial photography and video, precision agriculture, and parcel delivery. sUAVs are expected to operate in the uncontrolled Class G airspace, which is at or below 500 feet above ground level (AGL), where many static and dynamic constraints exist, such as ground properties and terrains, restricted areas, various winds, manned helicopters, and conflict avoidance among sUAVs. How to enable safe, efficient, and massive sUAV operations at the low altitude airspace remains a great challenge. NASA's Unmanned aircraft system Traffic Management (UTM) research initiative works on establishing infrastructure and developing policies, requirement, and rules to enable safe and efficient sUAVs' operations. To achieve this goal, it is important to gain insights of future UTM traffic operations through simulations, where the accurate trajectory model plays an extremely important role. On the other hand, like what happens in current aviation development, trajectory modeling should also serve as the foundation for any advanced concepts and tools in UTM. Accurate models of sUAV dynamics and control systems are very important considering the requirement of the meter level precision in UTM operations. The vehicle dynamics are relatively easy to derive and model, however, vehicle control systems remain unknown as they are usually kept by manufactures as a part of intellectual properties. That brings challenges to trajectory modeling for sUAVs. How to model the vehicle's trajectories with unknown control system? This work proposes to use a neural network to model a vehicle's trajectory. The neural network is first trained to learn the vehicle's responses at numerous conditions. Once being fully trained, given current vehicle states, winds, and desired future trajectory, the neural

  18. Mapping and modeling of physician collaboration network.

    Science.gov (United States)

    Uddin, Shahadat; Hamra, Jafar; Hossain, Liaquat

    2013-09-10

    Effective provisioning of healthcare services during patient hospitalization requires collaboration involving a set of interdependent complex tasks, which needs to be carried out in a synergistic manner. Improved patients' outcome during and after hospitalization has been attributed to how effective different health services provisioning groups carry out their tasks in a coordinated manner. Previous studies have documented the underlying relationships between collaboration among physicians on the effective outcome in delivering health services for improved patient outcomes. However, there are very few systematic empirical studies with a focus on the effect of collaboration networks among healthcare professionals and patients' medical condition. On the basis of the fact that collaboration evolves among physicians when they visit a common hospitalized patient, in this study, we first propose an approach to map collaboration network among physicians from their visiting information to patients. We termed this network as physician collaboration network (PCN). Then, we use exponential random graph (ERG) models to explore the microlevel network structures of PCNs and their impact on hospitalization cost and hospital readmission rate. ERG models are probabilistic models that are presented by locally determined explanatory variables and can effectively identify structural properties of networks such as PCN. It simplifies a complex structure down to a combination of basic parameters such as 2-star, 3-star, and triangle. By applying our proposed mapping approach and ERG modeling technique to the electronic health insurance claims dataset of a very large Australian health insurance organization, we construct and model PCNs. We notice that the 2-star (subset of 3 nodes in which 1 node is connected to each of the other 2 nodes) parameter of ERG has significant impact on hospitalization cost. Further, we identify that triangle (subset of 3 nodes in which each node is connected to

  19. Modeling In-Network Aggregation in VANETs

    NARCIS (Netherlands)

    Dietzel, Stefan; Kargl, Frank; Heijenk, Geert; Schaub, Florian

    2011-01-01

    The multitude of applications envisioned for vehicular ad hoc networks requires efficient communication and dissemination mechanisms to prevent network congestion. In-network data aggregation promises to reduce bandwidth requirements and enable scalability in large vehicular networks. However, most

  20. Different Epidemic Models on Complex Networks

    International Nuclear Information System (INIS)

    Zhang Haifeng; Small, Michael; Fu Xinchu

    2009-01-01

    Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals' relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each case. Finally, we present numerical simulations for each case to verify our results.

  1. Centralized Bayesian reliability modelling with sensor networks

    Czech Academy of Sciences Publication Activity Database

    Dedecius, Kamil; Sečkárová, Vladimíra

    2013-01-01

    Roč. 19, č. 5 (2013), s. 471-482 ISSN 1387-3954 R&D Projects: GA MŠk 7D12004 Grant - others:GA MŠk(CZ) SVV-265315 Keywords : Bayesian modelling * Sensor network * Reliability Subject RIV: BD - Theory of Information Impact factor: 0.984, year: 2013 http://library.utia.cas.cz/separaty/2013/AS/dedecius-0392551.pdf

  2. Modelling Pollutant Dispersion in a Street Network

    Science.gov (United States)

    Salem, N. Ben; Garbero, V.; Salizzoni, P.; Lamaison, G.; Soulhac, L.

    2015-04-01

    This study constitutes a further step in the analysis of the performances of a street network model to simulate atmospheric pollutant dispersion in urban areas. The model, named SIRANE, is based on the decomposition of the urban atmosphere into two sub-domains: the urban boundary layer, whose dynamics is assumed to be well established, and the urban canopy, represented as a series of interconnected boxes. Parametric laws govern the mass exchanges between the boxes under the assumption that the pollutant dispersion within the canopy can be fully simulated by modelling three main bulk transfer phenomena: channelling along street axes, transfers at street intersections, and vertical exchange between street canyons and the overlying atmosphere. Here, we aim to evaluate the reliability of the parametrizations adopted to simulate these phenomena, by focusing on their possible dependence on the external wind direction. To this end, we test the model against concentration measurements within an idealized urban district whose geometrical layout closely matches the street network represented in SIRANE. The analysis is performed for an urban array with a fixed geometry and a varying wind incidence angle. The results show that the model provides generally good results with the reference parametrizations adopted in SIRANE and that its performances are quite robust for a wide range of the model parameters. This proves the reliability of the street network approach in simulating pollutant dispersion in densely built city districts. The results also show that the model performances may be improved by considering a dependence of the wind fluctuations at street intersections and of the vertical exchange velocity on the direction of the incident wind. This opens the way for further investigations to clarify the dependence of these parameters on wind direction and street aspect ratios.

  3. The Channel Network model and field applications

    International Nuclear Information System (INIS)

    Khademi, B.; Moreno, L.; Neretnieks, I.

    1999-01-01

    The Channel Network model describes the fluid flow and solute transport in fractured media. The model is based on field observations, which indicate that flow and transport take place in a three-dimensional network of connected channels. The channels are generated in the model from observed stochastic distributions and solute transport is modeled taking into account advection and rock interactions, such as matrix diffusion and sorption within the rock. The most important site-specific data for the Channel Network model are the conductance distribution of the channels and the flow-wetted surface. The latter is the surface area of the rock in contact with the flowing water. These parameters may be estimated from hydraulic measurements. For the Aespoe site, several borehole data sets are available, where a packer distance of 3 meters was used. Numerical experiments were performed in order to study the uncertainties in the determination of the flow-wetted surface and conductance distribution. Synthetic data were generated along a borehole and hydraulic tests with different packer distances were simulated. The model has previously been used to study the Long-term Pumping and Tracer Test (LPT2) carried out in the Aespoe Hard Rock Laboratory (HRL) in Sweden, where the distance travelled by the tracers was of the order hundreds of meters. Recently, the model has been used to simulate the tracer tests performed in the TRUE experiment at HRL, with travel distance of the order of tens of meters. Several tracer tests with non-sorbing and sorbing species have been performed

  4. Advances in dynamic network modeling in complex transportation systems

    CERN Document Server

    Ukkusuri, Satish V

    2013-01-01

    This book focuses on the latest in dynamic network modeling, including route guidance and traffic control in transportation systems and other complex infrastructure networks. Covers dynamic traffic assignment, flow modeling, mobile sensor deployment and more.

  5. Distributed Bayesian Networks for User Modeling

    DEFF Research Database (Denmark)

    Tedesco, Roberto; Dolog, Peter; Nejdl, Wolfgang

    2006-01-01

    The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used by such ada......The World Wide Web is a popular platform for providing eLearning applications to a wide spectrum of users. However – as users differ in their preferences, background, requirements, and goals – applications should provide personalization mechanisms. In the Web context, user models used...... by such adaptive applications are often partial fragments of an overall user model. The fragments have then to be collected and merged into a global user profile. In this paper we investigate and present algorithms able to cope with distributed, fragmented user models – based on Bayesian Networks – in the context...... of Web-based eLearning platforms. The scenario we are tackling assumes learners who use several systems over time, which are able to create partial Bayesian Networks for user models based on the local system context. In particular, we focus on how to merge these partial user models. Our merge mechanism...

  6. Application of the Passionate Attachment Model to Recreational Use of MDMA/Ecstasy.

    Science.gov (United States)

    Davis, Alan K; Rosenberg, Harold

    2015-01-01

    Those who are not addicted to ecstasy, but who use it persistently over time, could be viewed as having a "passionate attachment" to a highly valued activity. To evaluate the associations of obsessive and harmonious passion with psychological and behavioral aspects of ecstasy consumption, we recruited a community sample of ecstasy users to complete a modified version of the Passion Scale (Vallerand et al. 2003) and other questionnaires assessing their substance use history, self-efficacy to refuse ecstasy, and use of ecstasy to cope with worries and problems. Both Obsessive and Harmonious passion scores were negatively correlated with self-efficacy to refuse ecstasy and positively correlated with using ecstasy to cope with worries and problems. The findings also provided partial support for our hypotheses that scores on the Obsessive Passion subscale would be associated with number of times participants had used ecstasy, the frequency of use, and the typical number of pills consumed. Participants agreed more strongly with statements indicative of Harmonious Passion to consume ecstasy, but Harmonious subscale scores were not associated with several measures of consumption. As a supplemental measure, the modified questionnaire could provide a more comprehensive picture of the psychology of one's ecstasy use.

  7. Adolescent attachment, family functioning and depressive symptoms

    Directory of Open Access Journals (Sweden)

    Nishola Rawatlal

    2015-08-01

    Full Text Available Background. Adolescence represents a challenging transitional period where changes in biological, emotional, cognitive and social domains can increase the risk of developing internalised problems including subthreshold depression. Adolescent-parent attachment style, perceived support and family functioning may increase risk for depressive symptoms or may reduce such risk. Adolescent-parent attachment, adolescent-perceived support from parents and family functioning were examined as correlates of depressive symptom presentation within this age group. Methods. Participants included a maternal parent and an adolescent (65.5% female from each family. Adolescents were in Grade 7 (n=175 or Grade 10 (n=31. Data were collected through home interviews. The Self-Report of Family Inventory (SFI, Experiences of Close Relationships Scale (ECR, Network of Relationships Inventory (NRI, Children’s Depression Inventory (CDI and Child Behavior Checklist (CBCL were used to assess depression, parental support and attachment.  Results. Two models were examined: one with adolescent report of depressive symptoms as the outcome and a second with parent report of adolescent internalising symptoms as the outcome. The model predicting adolescent-reported depressive symptoms was significant with older age, higher levels of avoidant attachment, and higher levels of youth-reported dysfunctional family interaction associated with more depressive symptomatology. In the model predicting parent report of adolescent internalising symptoms only higher levels of dysfunctional family interaction, as reported by the parent, were associated with higher levels of internalising symptoms. Conclusion. Positive family communication, cohesion and support predictive of a secure parent-adolescent attachment relationship reduced the risk of a depressive symptom outcome. Secure adolescents were able to regulate their emotions, knowing that they could seek out secure base attachment relations

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

    Science.gov (United States)

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

    2005-01-01

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

  9. A network model for Ebola spreading.

    Science.gov (United States)

    Rizzo, Alessandro; Pedalino, Biagio; Porfiri, Maurizio

    2016-04-07

    The availability of accurate models for the spreading of infectious diseases has opened a new era in management and containment of epidemics. Models are extensively used to plan for and execute vaccination campaigns, to evaluate the risk of international spreadings and the feasibility of travel bans, and to inform prophylaxis campaigns. Even when no specific therapeutical protocol is available, as for the Ebola Virus Disease (EVD), models of epidemic spreading can provide useful insight to steer interventions in the field and to forecast the trend of the epidemic. Here, we propose a novel mathematical model to describe EVD spreading based on activity driven networks (ADNs). Our approach overcomes the simplifying assumption of homogeneous mixing, which is central to most of the mathematically tractable models of EVD spreading. In our ADN-based model, each individual is not bound to contact every other, and its network of contacts varies in time as a function of an activity potential. Our model contemplates the possibility of non-ideal and time-varying intervention policies, which are critical to accurately describe EVD spreading in afflicted countries. The model is calibrated from field data of the 2014 April-to-December spreading in Liberia. We use the model as a predictive tool, to emulate the dynamics of EVD in Liberia and offer a one-year projection, until December 2015. Our predictions agree with the current vision expressed by professionals in the field, who consider EVD in Liberia at its final stage. The model is also used to perform a what-if analysis to assess the efficacy of timely intervention policies. In particular, we show that an earlier application of the same intervention policy would have greatly reduced the number of EVD cases, the duration of the outbreak, and the infrastructures needed for the implementation of the intervention. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. A study of the spreading scheme for viral marketing based on a complex network model

    Science.gov (United States)

    Yang, Jianmei; Yao, Canzhong; Ma, Weicheng; Chen, Guanrong

    2010-02-01

    Buzzword-based viral marketing, known also as digital word-of-mouth marketing, is a marketing mode attached to some carriers on the Internet, which can rapidly copy marketing information at a low cost. Viral marketing actually uses a pre-existing social network where, however, the scale of the pre-existing network is believed to be so large and so random, so that its theoretical analysis is intractable and unmanageable. There are very few reports in the literature on how to design a spreading scheme for viral marketing on real social networks according to the traditional marketing theory or the relatively new network marketing theory. Complex network theory provides a new model for the study of large-scale complex systems, using the latest developments of graph theory and computing techniques. From this perspective, the present paper extends the complex network theory and modeling into the research of general viral marketing and develops a specific spreading scheme for viral marking and an approach to design the scheme based on a real complex network on the QQ instant messaging system. This approach is shown to be rather universal and can be further extended to the design of various spreading schemes for viral marketing based on different instant messaging systems.

  11. Modeling Network Transition Constraints with Hypergraphs

    DEFF Research Database (Denmark)

    Harrod, Steven

    2011-01-01

    Discrete time dynamic graphs are frequently used to model multicommodity flows or activity paths through constrained resources, but simple graphs fail to capture the interaction effects of resource transitions. The resulting schedules are not operationally feasible, and return inflated objective...... values. A directed hypergraph formulation is derived to address railway network sequencing constraints, and an experimental problem sample solved to estimate the magnitude of objective inflation when interaction effects are ignored. The model is used to demonstrate the value of advance scheduling...... of train paths on a busy North American railway....

  12. Mathematical model for spreading dynamics of social network worms

    International Nuclear Information System (INIS)

    Sun, Xin; Liu, Yan-Heng; Han, Jia-Wei; Liu, Xue-Jie; Li, Bin; Li, Jin

    2012-01-01

    In this paper, a mathematical model for social network worm spreading is presented from the viewpoint of social engineering. This model consists of two submodels. Firstly, a human behavior model based on game theory is suggested for modeling and predicting the expected behaviors of a network user encountering malicious messages. The game situation models the actions of a user under the condition that the system may be infected at the time of opening a malicious message. Secondly, a social network accessing model is proposed to characterize the dynamics of network users, by which the number of online susceptible users can be determined at each time step. Several simulation experiments are carried out on artificial social networks. The results show that (1) the proposed mathematical model can well describe the spreading dynamics of social network worms; (2) weighted network topology greatly affects the spread of worms; (3) worms spread even faster on hybrid social networks

  13. Model parameter updating using Bayesian networks

    International Nuclear Information System (INIS)

    Treml, C.A.; Ross, Timothy J.

    2004-01-01

    This paper outlines a model parameter updating technique for a new method of model validation using a modified model reference adaptive control (MRAC) framework with Bayesian Networks (BNs). The model parameter updating within this method is generic in the sense that the model/simulation to be validated is treated as a black box. It must have updateable parameters to which its outputs are sensitive, and those outputs must have metrics that can be compared to that of the model reference, i.e., experimental data. Furthermore, no assumptions are made about the statistics of the model parameter uncertainty, only upper and lower bounds need to be specified. This method is designed for situations where a model is not intended to predict a complete point-by-point time domain description of the item/system behavior; rather, there are specific points, features, or events of interest that need to be predicted. These specific points are compared to the model reference derived from actual experimental data. The logic for updating the model parameters to match the model reference is formed via a BN. The nodes of this BN consist of updateable model input parameters and the specific output values or features of interest. Each time the model is executed, the input/output pairs are used to adapt the conditional probabilities of the BN. Each iteration further refines the inferred model parameters to produce the desired model output. After parameter updating is complete and model inputs are inferred, reliabilities for the model output are supplied. Finally, this method is applied to a simulation of a resonance control cooling system for a prototype coupled cavity linac. The results are compared to experimental data.

  14. Stigma models: Testing hypotheses of how images of Nevada are acquired and values are attached to them

    Energy Technology Data Exchange (ETDEWEB)

    Jenkins-Smith, H.C. [New Mexico Univ., Albuquerque, NM (United States)

    1994-12-01

    This report analyzes data from surveys on the effects that images associated with nuclear power and waste (i.e., nuclear images) have on people`s preference to vacation in Nevada. The analysis was stimulated by a model of imagery and stigma which assumes that information about a potentially hazardous facility generates signals that elicit negative images about the place in which it is located. Individuals give these images negative values (valences) that lessen their desire to vacation, relocate, or retire in that place. The model has been used to argue that the proposed Yucca Mountain high-level nuclear waste repository could elicit images of nuclear waste that would stigmatize Nevada and thus impose substantial economic losses there. This report proposes a revised model that assumes that the acquisition and valuation of images depend on individuals` ideological and cultural predispositions and that the ways in which new images will affect their preferences and behavior partly depend on these predispositions. The report tests these hypotheses: (1) individuals with distinct cultural and ideological predispositions have different propensities for acquiring nuclear images, (2) these people attach different valences to these images, (3) the variations in these valences are important, and (4) the valences of the different categories of images within an individual`s image sets for a place correlate very well. The analysis largely confirms these hypotheses, indicating that the stigma model should be revised to (1) consider the relevant ideological and cultural predispositions of the people who will potentially acquire and attach value to the image, (2) specify the kinds of images that previously attracted people to the host state, and (3) consider interactions between the old and potential new images of the place. 37 refs., 18 figs., 17 tabs.

  15. Stigma models: Testing hypotheses of how images of Nevada are acquired and values are attached to them

    International Nuclear Information System (INIS)

    Jenkins-Smith, H.C.

    1994-12-01

    This report analyzes data from surveys on the effects that images associated with nuclear power and waste (i.e., nuclear images) have on people's preference to vacation in Nevada. The analysis was stimulated by a model of imagery and stigma which assumes that information about a potentially hazardous facility generates signals that elicit negative images about the place in which it is located. Individuals give these images negative values (valences) that lessen their desire to vacation, relocate, or retire in that place. The model has been used to argue that the proposed Yucca Mountain high-level nuclear waste repository could elicit images of nuclear waste that would stigmatize Nevada and thus impose substantial economic losses there. This report proposes a revised model that assumes that the acquisition and valuation of images depend on individuals' ideological and cultural predispositions and that the ways in which new images will affect their preferences and behavior partly depend on these predispositions. The report tests these hypotheses: (1) individuals with distinct cultural and ideological predispositions have different propensities for acquiring nuclear images, (2) these people attach different valences to these images, (3) the variations in these valences are important, and (4) the valences of the different categories of images within an individual's image sets for a place correlate very well. The analysis largely confirms these hypotheses, indicating that the stigma model should be revised to (1) consider the relevant ideological and cultural predispositions of the people who will potentially acquire and attach value to the image, (2) specify the kinds of images that previously attracted people to the host state, and (3) consider interactions between the old and potential new images of the place. 37 refs., 18 figs., 17 tabs

  16. Complex networks-based energy-efficient evolution model for wireless sensor networks

    Energy Technology Data Exchange (ETDEWEB)

    Zhu Hailin [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China)], E-mail: zhuhailin19@gmail.com; Luo Hong [Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, P.O. Box 106, Beijing 100876 (China); Peng Haipeng; Li Lixiang; Luo Qun [Information Secure Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, P.O. Box 145, Beijing 100876 (China)

    2009-08-30

    Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.

  17. Complex networks-based energy-efficient evolution model for wireless sensor networks

    International Nuclear Information System (INIS)

    Zhu Hailin; Luo Hong; Peng Haipeng; Li Lixiang; Luo Qun

    2009-01-01

    Based on complex networks theory, we present two self-organized energy-efficient models for wireless sensor networks in this paper. The first model constructs the wireless sensor networks according to the connectivity and remaining energy of each sensor node, thus it can produce scale-free networks which have a performance of random error tolerance. In the second model, we not only consider the remaining energy, but also introduce the constraint of links to each node. This model can make the energy consumption of the whole network more balanced. Finally, we present the numerical experiments of the two models.

  18. Modeling the Effect of Bandwidth Allocation on Network Performance

    African Journals Online (AJOL)

    ... The proposed model showed improved performance for CDMA networks, but further increase in the bandwidth did not benefit the network; (iii) A reliability measure such as the spectral efficiency is therefore useful to redeem the limitation in (ii). Keywords: Coverage Capacity, CDMA, Mobile Network, Network Throughput ...

  19. Aeronautical telecommunications network advances, challenges, and modeling

    CERN Document Server

    Musa, Sarhan M

    2015-01-01

    Addresses the Challenges of Modern-Day Air Traffic Air traffic control (ATC) directs aircraft in the sky and on the ground to safety, while the Aeronautical Telecommunications Network (ATN) comprises all systems and phases that assist in aircraft departure and landing. The Aeronautical Telecommunications Network: Advances, Challenges, and Modeling focuses on the development of ATN and examines the role of the various systems that link aircraft with the ground. The book places special emphasis on ATC-introducing the modern ATC system from the perspective of the user and the developer-and provides a thorough understanding of the operating mechanism of the ATC system. It discusses the evolution of ATC, explaining its structure and how it works; includes design examples; and describes all subsystems of the ATC system. In addition, the book covers relevant tools, techniques, protocols, and architectures in ATN, including MIPv6, air traffic control (ATC), security of air traffic management (ATM), very-high-frequenc...

  20. Modelling dependable systems using hybrid Bayesian networks

    International Nuclear Information System (INIS)

    Neil, Martin; Tailor, Manesh; Marquez, David; Fenton, Norman; Hearty, Peter

    2008-01-01

    A hybrid Bayesian network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment, the models are invariably hybrid and the need for efficient and accurate computation is paramount. We apply a new iterative algorithm that efficiently combines dynamic discretisation with robust propagation algorithms on junction tree structures to perform inference in hybrid BNs. We illustrate its use in the field of dependability with two example of reliability estimation. Firstly we estimate the reliability of a simple single system and next we implement a hierarchical Bayesian model. In the hierarchical model we compute the reliability of two unknown subsystems from data collected on historically similar subsystems and then input the result into a reliability block model to compute system level reliability. We conclude that dynamic discretisation can be used as an alternative to analytical or Monte Carlo methods with high precision and can be applied to a wide range of dependability problems

  1. Logic integer programming models for signaling networks.

    Science.gov (United States)

    Haus, Utz-Uwe; Niermann, Kathrin; Truemper, Klaus; Weismantel, Robert

    2009-05-01

    We propose a static and a dynamic approach to model biological signaling networks, and show how each can be used to answer relevant biological questions. For this, we use the two different mathematical tools of Propositional Logic and Integer Programming. The power of discrete mathematics for handling qualitative as well as quantitative data has so far not been exploited in molecular biology, which is mostly driven by experimental research, relying on first-order or statistical models. The arising logic statements and integer programs are analyzed and can be solved with standard software. For a restricted class of problems the logic models reduce to a polynomial-time solvable satisfiability algorithm. Additionally, a more dynamic model enables enumeration of possible time resolutions in poly-logarithmic time. Computational experiments are included.

  2. Adoptive parenting and attachment: association of the internal working models between adoptive mothers and their late-adopted children during adolescence.

    Science.gov (United States)

    Pace, Cecilia S; Di Folco, Simona; Guerriero, Viviana; Santona, Alessandra; Terrone, Grazia

    2015-01-01

    Recent literature has shown that the good outcome of adoption would mostly depend on the quality of adoptive parenting, which is strongly associated with the security of parental internal working models (IWMs) of attachment. Specifically, attachment states-of-mind of adoptive mothers classified as free and autonomous and without lack of resolution of loss or trauma could represent a good protective factor for adopted children, previously maltreated and neglected. While most research on adoptive families focused on pre-school and school-aged children, the aim of this study was to assess the concordance of IWMs of attachment in adoptive dyads during adolescence. Our pilot-study involved 76 participants: 30 adoptive mothers (mean age = 51.5 ± 4.3), and their 46 late-adopted adolescents (mean age = 13.9 ± 1.6), who were all aged 4-9 years old at time of adoption (mean age = 6.3 ± 1.5). Attachment representations of adopted adolescents were assessed by the Friend and Family Interview (FFI), while adoptive mothers' state-of-mind with respect to attachment was classified by the Adult Attachment Interview (AAI). Adolescents' verbal intelligence was controlled for. Late-adopted adolescents were classified as follows: 67% secure, 26% dismissing, and 7% preoccupied in the FFI, while their adoptive mothers' AAI classifications were 70% free-autonomous, 7% dismissing, and 23% unresolved. We found a significant concordance of 70% (32 dyads) between the secure-insecure FFI and AAI classifications. Specifically adoptive mothers with high coherence of transcript and low unresolved loss tend to have late-adopted children with high secure attachment, even if the adolescents' verbal intelligence made a significant contribution to this prediction. Our results provides an empirical contribution to the literature concerning the concordance of attachment in adoptive dyads, highlighting the beneficial impact of highly coherent states-of-mind of adoptive mothers on the attachment

  3. Bayesian Recurrent Neural Network for Language Modeling.

    Science.gov (United States)

    Chien, Jen-Tzung; Ku, Yuan-Chu

    2016-02-01

    A language model (LM) is calculated as the probability of a word sequence that provides the solution to word prediction for a variety of information systems. A recurrent neural network (RNN) is powerful to learn the large-span dynamics of a word sequence in the continuous space. However, the training of the RNN-LM is an ill-posed problem because of too many parameters from a large dictionary size and a high-dimensional hidden layer. This paper presents a Bayesian approach to regularize the RNN-LM and apply it for continuous speech recognition. We aim to penalize the too complicated RNN-LM by compensating for the uncertainty of the estimated model parameters, which is represented by a Gaussian prior. The objective function in a Bayesian classification network is formed as the regularized cross-entropy error function. The regularized model is constructed not only by calculating the regularized parameters according to the maximum a posteriori criterion but also by estimating the Gaussian hyperparameter by maximizing the marginal likelihood. A rapid approximation to a Hessian matrix is developed to implement the Bayesian RNN-LM (BRNN-LM) by selecting a small set of salient outer-products. The proposed BRNN-LM achieves a sparser model than the RNN-LM. Experiments on different corpora show the robustness of system performance by applying the rapid BRNN-LM under different conditions.

  4. Studying the Amount, Motivations and Perception of Consequences of Using the Social Networks Based on Quality of the Relationship between Attachment Styles with Perception of Parental Rejection and Control in Adolescents

    Directory of Open Access Journals (Sweden)

    پریسا سادات سیدموسوی

    2018-03-01

    Full Text Available Due to the importance of user behavior in social networks especially in adolescents, the purpose of this study was investigating the amount, motivations and perception of consequences of using the social networks based on the quality of the relationship between attachment styles with perception of parental rejection and control in adole-scents. The population of the research included all of the 15-18 years old adolescents of Tehran from which 146 students (77 girls and 69 boys were chosen by cluster sampling and completed the Inventory of Parent & Peer Attachment, Parental Acceptance-Rejection and Control, and Social Network Using Checklist. The results showed that the quality of the relationship with parents has a key role in prediction of the amount and the way of using the social networks and in addition could affect the consequences of using these networks. In addition, increasing of the parental control unexpectedly could not decrease the using of social networks. According to the results, it seems that although most of the adolescents are using the social networks, the relationship with parents can be critical in predicting the motives of using these networks.

  5. Research on network information security model and system construction

    OpenAIRE

    Wang Haijun

    2016-01-01

    It briefly describes the impact of large data era on China’s network policy, but also brings more opportunities and challenges to the network information security. This paper reviews for the internationally accepted basic model and characteristics of network information security, and analyses the characteristics of network information security and their relationship. On the basis of the NIST security model, this paper describes three security control schemes in safety management model and the...

  6. Two stage neural network modelling for robust model predictive control.

    Science.gov (United States)

    Patan, Krzysztof

    2018-01-01

    The paper proposes a novel robust model predictive control scheme realized by means of artificial neural networks. The neural networks are used twofold: to design the so-called fundamental model of a plant and to catch uncertainty associated with the plant model. In order to simplify the optimization process carried out within the framework of predictive control an instantaneous linearization is applied which renders it possible to define the optimization problem in the form of constrained quadratic programming. Stability of the proposed control system is also investigated by showing that a cost function is monotonically decreasing with respect to time. Derived robust model predictive control is tested and validated on the example of a pneumatic servomechanism working at different operating regimes. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

  7. Attachment, hope, and participation: Testing an expanded model of Snyder's hope theory for prediction of participation for individuals with spinal cord injury.

    Science.gov (United States)

    Blake, John; Yaghmaian, Rana; Brooks, Jessica; Fais, Connor; Chan, Fong

    2018-05-01

    The aim of the study was to test an expanded model of Snyder's hope theory for prediction of participation for individuals with spinal cord injury (SCI). Statistical model testing focused on evaluation of hope theory constructs (i.e., agency thoughts and pathways thoughts) as serial mediators of relationships between attachment and community participation. Quantitative, cross-sectional, descriptive design using multiple regression and correlational techniques. The sample comprised 108 persons with SCI recruited from spinal cord injury advocacy organizations in the United States, the United Kingdom, and Canada. Secure attachment, avoidant attachment, anxious attachment, and the hope constructs were significantly related to participation. Significant mediational effects were observed when agency thoughts and pathways thoughts were specified as mediators in series between attachment and community participation for people with SCI (i.e., agency specified as M1 and pathways specified as M2). Results provide support for Snyder's theoretical conceptualization and the use of hope-based interventions by rehabilitation practitioners for improving global participation outcomes for people with SCI who experience attachment-related difficulties. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

  8. Reduced order dynamic model for polysaccharides molecule attached to an atomic force microscope

    International Nuclear Information System (INIS)

    Tang Deman; Li Aiqin; Attar, Peter; Dowell, Earl H.

    2004-01-01

    A dynamic analysis and numerical simulation has been conducted of a polysaccharides molecular structure (a ten (10) single-α-D-glucose molecule chain) connected to a moving atomic force microscope (AFM). Sinusoidal base excitation of the AFM cantilevered beam is considered. First a linearized perturbation model is constructed for the complex polysaccharides molecular structure. Then reduced order (dynamic) models based upon a proper orthogonal decomposition (POD) technique are constructed using global modes for both the linearized perturbation model and for the full nonlinear model. The agreement between the original and reduced order models (ROM/POD) is very good even when only a few global modes are included in the ROM for either the linear case or for the nonlinear case. The computational advantage of the reduced order model is clear from the results presented

  9. Spacing distribution functions for the one-dimensional point-island model with irreversible attachment

    Science.gov (United States)

    González, Diego Luis; Pimpinelli, Alberto; Einstein, T. L.

    2011-07-01

    We study the configurational structure of the point-island model for epitaxial growth in one dimension. In particular, we calculate the island gap and capture zone distributions. Our model is based on an approximate description of nucleation inside the gaps. Nucleation is described by the joint probability density pnXY(x,y), which represents the probability density to have nucleation at position x within a gap of size y. Our proposed functional form for pnXY(x,y) describes excellently the statistical behavior of the system. We compare our analytical model with extensive numerical simulations. Our model retains the most relevant physical properties of the system.

  10. Exact model reduction of combinatorial reaction networks

    Directory of Open Access Journals (Sweden)

    Fey Dirk

    2008-08-01

    Full Text Available Abstract Background Receptors and scaffold proteins usually possess a high number of distinct binding domains inducing the formation of large multiprotein signaling complexes. Due to combinatorial reasons the number of distinguishable species grows exponentially with the number of binding domains and can easily reach several millions. Even by including only a limited number of components and binding domains the resulting models are very large and hardly manageable. A novel model reduction technique allows the significant reduction and modularization of these models. Results We introduce methods that extend and complete the already introduced approach. For instance, we provide techniques to handle the formation of multi-scaffold complexes as well as receptor dimerization. Furthermore, we discuss a new modeling approach that allows the direct generation of exactly reduced model structures. The developed methods are used to reduce a model of EGF and insulin receptor crosstalk comprising 5,182 ordinary differential equations (ODEs to a model with 87 ODEs. Conclusion The methods, presented in this contribution, significantly enhance the available methods to exactly reduce models of combinatorial reaction networks.

  11. Neural Networks For Electrohydrodynamic Effect Modelling

    Directory of Open Access Journals (Sweden)

    Wiesław Wajs

    2004-01-01

    Full Text Available This paper presents currently achieved results concerning methods of electrohydrodynamiceffect used in geophysics simulated with feedforward networks trained with backpropagation algorithm, radial basis function networks and generalized regression networks.

  12. Social network models predict movement and connectivity in ecological landscapes

    Science.gov (United States)

    Fletcher, Robert J.; Acevedo, M.A.; Reichert, Brian E.; Pias, Kyle E.; Kitchens, Wiley M.

    2011-01-01

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  13. Social network models predict movement and connectivity in ecological landscapes.

    Science.gov (United States)

    Fletcher, Robert J; Acevedo, Miguel A; Reichert, Brian E; Pias, Kyle E; Kitchens, Wiley M

    2011-11-29

    Network analysis is on the rise across scientific disciplines because of its ability to reveal complex, and often emergent, patterns and dynamics. Nonetheless, a growing concern in network analysis is the use of limited data for constructing networks. This concern is strikingly relevant to ecology and conservation biology, where network analysis is used to infer connectivity across landscapes. In this context, movement among patches is the crucial parameter for interpreting connectivity but because of the difficulty of collecting reliable movement data, most network analysis proceeds with only indirect information on movement across landscapes rather than using observed movement to construct networks. Statistical models developed for social networks provide promising alternatives for landscape network construction because they can leverage limited movement information to predict linkages. Using two mark-recapture datasets on individual movement and connectivity across landscapes, we test whether commonly used network constructions for interpreting connectivity can predict actual linkages and network structure, and we contrast these approaches to social network models. We find that currently applied network constructions for assessing connectivity consistently, and substantially, overpredict actual connectivity, resulting in considerable overestimation of metapopulation lifetime. Furthermore, social network models provide accurate predictions of network structure, and can do so with remarkably limited data on movement. Social network models offer a flexible and powerful way for not only understanding the factors influencing connectivity but also for providing more reliable estimates of connectivity and metapopulation persistence in the face of limited data.

  14. Neural network models of categorical perception.

    Science.gov (United States)

    Damper, R I; Harnad, S R

    2000-05-01

    Studies of the categorical perception (CP) of sensory continua have a long and rich history in psychophysics. In 1977, Macmillan, Kaplan, and Creelman introduced the use of signal detection theory to CP studies. Anderson and colleagues simultaneously proposed the first neural model for CP, yet this line of research has been less well explored. In this paper, we assess the ability of neural-network models of CP to predict the psychophysical performance of real observers with speech sounds and artificial/novel stimuli. We show that a variety of neural mechanisms are capable of generating the characteristics of CP. Hence, CP may not be a special model of perception but an emergent property of any sufficiently powerful general learning system.

  15. Combination of Bayesian Network and Overlay Model in User Modeling

    Directory of Open Access Journals (Sweden)

    Loc Nguyen

    2009-12-01

    Full Text Available The core of adaptive system is user model containing personal information such as knowledge, learning styles, goals… which is requisite for learning personalized process. There are many modeling approaches, for example: stereotype, overlay, plan recognition… but they don’t bring out the solid method for reasoning from user model. This paper introduces the statistical method that combines Bayesian network and overlay modeling so that it is able to infer user’s knowledge from evidences collected during user’s learning process.

  16. Parental Bonds, Attachment Anxiety, Media Susceptibility, and Body Dissatisfaction: A Mediation Model

    Science.gov (United States)

    Patton, Sarah C.; Beaujean, A. Alexander; Benedict, Helen E.

    2014-01-01

    The developmental trajectory of body image dissatisfaction is unclear. Researchers have investigated sociocultural and developmental risk factors; however, the literature needs an integrative etiological model. In 2009, Cheng and Mallinckrodt proposed a dual mediation model, positing that poor-quality parental bonds, via the mechanisms of…

  17. Networks model of the East Turkistan terrorism

    Science.gov (United States)

    Li, Ben-xian; Zhu, Jun-fang; Wang, Shun-guo

    2015-02-01

    The presence of the East Turkistan terrorist network in China can be traced back to the rebellions on the BAREN region in Xinjiang in April 1990. This article intends to research the East Turkistan networks in China and offer a panoramic view. The events, terrorists and their relationship are described using matrices. Then social network analysis is adopted to reveal the network type and the network structure characteristics. We also find the crucial terrorist leader. Ultimately, some results show that the East Turkistan network has big hub nodes and small shortest path, and that the network follows a pattern of small world network with hierarchical structure.

  18. Pruning Boltzmann networks and hidden Markov models

    DEFF Research Database (Denmark)

    Pedersen, Morten With; Stork, D.

    1996-01-01

    We present sensitivity-based pruning algorithms for general Boltzmann networks. Central to our methods is the efficient calculation of a second-order approximation to the true weight saliencies in a cross-entropy error. Building upon previous work which shows a formal correspondence between linear...... Boltzmann chains and hidden Markov models (HMMs), we argue that our method can be applied to HMMs as well. We illustrate pruning on Boltzmann zippers, which are equivalent to two HMMs with cross-connection links. We verify that our second-order approximation preserves the rank ordering of weight saliencies...

  19. Compartmentalization analysis using discrete fracture network models

    Energy Technology Data Exchange (ETDEWEB)

    La Pointe, P.R.; Eiben, T.; Dershowitz, W. [Golder Associates, Redmond, VA (United States); Wadleigh, E. [Marathon Oil Co., Midland, TX (United States)

    1997-08-01

    This paper illustrates how Discrete Fracture Network (DFN) technology can serve as a basis for the calculation of reservoir engineering parameters for the development of fractured reservoirs. It describes the development of quantitative techniques for defining the geometry and volume of structurally controlled compartments. These techniques are based on a combination of stochastic geometry, computational geometry, and graph the theory. The parameters addressed are compartment size, matrix block size and tributary drainage volume. The concept of DFN models is explained and methodologies to compute these parameters are demonstrated.

  20. Analysis and Comparison of Typical Models within Distribution Network Design

    DEFF Research Database (Denmark)

    Jørgensen, Hans Jacob; Larsen, Allan; Madsen, Oli B.G.

    This paper investigates the characteristics of typical optimisation models within Distribution Network Design. During the paper fourteen models known from the literature will be thoroughly analysed. Through this analysis a schematic approach to categorisation of distribution network design models...... for educational purposes. Furthermore, the paper can be seen as a practical introduction to network design modelling as well as a being an art manual or recipe when constructing such a model....

  1. Fundamentals of complex networks models, structures and dynamics

    CERN Document Server

    Chen, Guanrong; Li, Xiang

    2014-01-01

    Complex networks such as the Internet, WWW, transportationnetworks, power grids, biological neural networks, and scientificcooperation networks of all kinds provide challenges for futuretechnological development. In particular, advanced societies havebecome dependent on large infrastructural networks to an extentbeyond our capability to plan (modeling) and to operate (control).The recent spate of collapses in power grids and ongoing virusattacks on the Internet illustrate the need for knowledge aboutmodeling, analysis of behaviors, optimized planning and performancecontrol in such networks. F

  2. A Search Model with a Quasi-Network

    DEFF Research Database (Denmark)

    Ejarque, Joao Miguel

    This paper adds a quasi-network to a search model of the labor market. Fitting the model to an average unemployment rate and to other moments in the data implies the presence of the network is not noticeable in the basic properties of the unemployment and job finding rates. However, the network...

  3. Joint Modelling of Structural and Functional Brain Networks

    DEFF Research Database (Denmark)

    Andersen, Kasper Winther; Herlau, Tue; Mørup, Morten

    -parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish...

  4. Artificial Neural Network Modeling of an Inverse Fluidized Bed ...

    African Journals Online (AJOL)

    A Radial Basis Function neural network has been successfully employed for the modeling of the inverse fluidized bed reactor. In the proposed model, the trained neural network represents the kinetics of biological decomposition of pollutants in the reactor. The neural network has been trained with experimental data ...

  5. Superego: an attachment perspective.

    Science.gov (United States)

    Holmes, Jeremy

    2011-10-01

    With the help of attachment theory and research, the paper attempts to broaden and build on classical and current views on the superego. Attachment theory's epigenetic approach and the concept of the subliminal superego are described. The superego, it is argued, is as much concerned with safety as sex. The superego is 'heir', not just to the Oedipus complex or Klein's pre-oedipal constellation, but also to the attachment relationship. Under favourable developmental conditions a 'mature superego' emerges, facilitating, in the presence of an internal secure base, maturational boundary crossings towards adult sexuality. In the light of the above, the paper reviews Lear's updating of Strachey's model of psychic change and explores the concept of transgression in relation to the 'professional superego', its development and maturation. Theoretical arguments are illustrated with clinical examples. Copyright © 2011 Institute of Psychoanalysis.

  6. Neural Network Based Models for Fusion Applications

    Science.gov (United States)

    Meneghini, Orso; Tema Biwole, Arsene; Luda, Teobaldo; Zywicki, Bailey; Rea, Cristina; Smith, Sterling; Snyder, Phil; Belli, Emily; Staebler, Gary; Canty, Jeff

    2017-10-01

    Whole device modeling, engineering design, experimental planning and control applications demand models that are simultaneously physically accurate and fast. This poster reports on the ongoing effort towards the development and validation of a series of models that leverage neural-­network (NN) multidimensional regression techniques to accelerate some of the most mission critical first principle models for the fusion community, such as: the EPED workflow for prediction of the H-Mode and Super H-Mode pedestal structure the TGLF and NEO models for the prediction of the turbulent and neoclassical particle, energy and momentum fluxes; and the NEO model for the drift-kinetic solution of the bootstrap current. We also applied NNs on DIII-D experimental data for disruption prediction and quantifying the effect of RMPs on the pedestal and ELMs. All of these projects were supported by the infrastructure provided by the OMFIT integrated modeling framework. Work supported by US DOE under DE-SC0012656, DE-FG02-95ER54309, DE-FC02-04ER54698.

  7. A Topology Evolution Model Based on Revised PageRank Algorithm and Node Importance for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xiaogang Qi

    2015-01-01

    Full Text Available Wireless sensor network (WSN is a classical self-organizing communication network, and its topology evolution currently becomes one of the attractive issues in this research field. Accordingly, the problem is divided into two subproblems: one is to design a new preferential attachment method and the other is to analyze the dynamics of the network topology evolution. To solve the first subproblem, a revised PageRank algorithm, called Con-rank, is proposed to evaluate the node importance upon the existing node contraction, and then a novel preferential attachment is designed based on the node importance calculated by the proposed Con-rank algorithm. To solve the second one, we firstly analyze the network topology evolution dynamics in a theoretical way and then simulate the evolution process. Theoretical analysis proves that the network topology evolution of our model agrees with power-law distribution, and simulation results are well consistent with our conclusions obtained from the theoretical analysis and simultaneously show that our topology evolution model is superior to the classic BA model in the average path length and the clustering coefficient, and the network topology is more robust and can tolerate the random attacks.

  8. A generalized preferential attachment model for business firms growth rates. I. Empirical evidence

    Science.gov (United States)

    Pammolli, F.; Fu, D.; Buldyrev, S. V.; Riccaboni, M.; Matia, K.; Yamasaki, K.; Stanley, H. E.

    2007-05-01

    We introduce a model of proportional growth to explain the distribution P(g) of business firm growth rates. The model predicts that P(g) is Laplace in the central part and depicts an asymptotic power-law behavior in the tails with an exponent ζ = 3. Because of data limitations, previous studies in this field have been focusing exclusively on the Laplace shape of the body of the distribution. We test the model at different levels of aggregation in the economy, from products, to firms, to countries, and we find that the predictions are in good agreement with empirical evidence on both growth distributions and size-variance relationships.

  9. Spacing distribution functions for 1D point island model with irreversible attachment

    Science.gov (United States)

    Gonzalez, Diego; Einstein, Theodore; Pimpinelli, Alberto

    2011-03-01

    We study the configurational structure of the point island model for epitaxial growth in one dimension. In particular, we calculate the island gap and capture zone distributions. Our model is based on an approximate description of nucleation inside the gaps. Nucleation is described by the joint probability density p xy n (x,y), which represents the probability density to have nucleation at position x within a gap of size y. Our proposed functional form for p xy n (x,y) describes excellently the statistical behavior of the system. We compare our analytical model with extensive numerical simulations. Our model retains the most relevant physical properties of the system. This work was supported by the NSF-MRSEC at the University of Maryland, Grant No. DMR 05-20471, with ancillary support from the Center for Nanophysics and Advanced Materials (CNAM).

  10. A network of networks model to study phase synchronization using structural connection matrix of human brain

    Science.gov (United States)

    Ferrari, F. A. S.; Viana, R. L.; Reis, A. S.; Iarosz, K. C.; Caldas, I. L.; Batista, A. M.

    2018-04-01

    The cerebral cortex plays a key role in complex cortical functions. It can be divided into areas according to their function (motor, sensory and association areas). In this paper, the cerebral cortex is described as a network of networks (cortex network), we consider that each cortical area is composed of a network with small-world property (cortical network). The neurons are assumed to have bursting properties with the dynamics described by the Rulkov model. We study the phase synchronization of the cortex network and the cortical networks. In our simulations, we verify that synchronization in cortex network is not homogeneous. Besides, we focus on the suppression of neural phase synchronization. Synchronization can be related to undesired and pathological abnormal rhythms in the brain. For this reason, we consider the delayed feedback control to suppress the synchronization. We show that delayed feedback control is efficient to suppress synchronous behavior in our network model when an appropriate signal intensity and time delay are defined.

  11. QSAR modelling using combined simple competitive learning networks and RBF neural networks.

    Science.gov (United States)

    Sheikhpour, R; Sarram, M A; Rezaeian, M; Sheikhpour, E

    2018-04-01

    The aim of this study was to propose a QSAR modelling approach based on the combination of simple competitive learning (SCL) networks with radial basis function (RBF) neural networks for predicting the biological activity of chemical compounds. The proposed QSAR method consisted of two phases. In the first phase, an SCL network was applied to determine the centres of an RBF neural network. In the second phase, the RBF neural network was used to predict the biological activity of various phenols and Rho kinase (ROCK) inhibitors. The predictive ability of the proposed QSAR models was evaluated and compared with other QSAR models using external validation. The results of this study showed that the proposed QSAR modelling approach leads to better performances than other models in predicting the biological activity of chemical compounds. This indicated the efficiency of simple competitive learning networks in determining the centres of RBF neural networks.

  12. Linear approximation model network and its formation via ...

    Indian Academy of Sciences (India)

    niques, an alternative `linear approximation model' (LAM) network approach is .... network is LPV, existing LTI theory is difficult to apply (Kailath 1980). ..... Beck J V, Arnold K J 1977 Parameter estimation in engineering and science (New York: ...

  13. Equity venture capital platform model based on complex network

    Science.gov (United States)

    Guo, Dongwei; Zhang, Lanshu; Liu, Miao

    2018-05-01

    This paper uses the small-world network and the random-network to simulate the relationship among the investors, construct the network model of the equity venture capital platform to explore the impact of the fraud rate and the bankruptcy rate on the robustness of the network model while observing the impact of the average path length and the average agglomeration coefficient of the investor relationship network on the income of the network model. The study found that the fraud rate and bankruptcy rate exceeded a certain threshold will lead to network collapse; The bankruptcy rate has a great influence on the income of the platform; The risk premium exists, and the average return is better under a certain range of bankruptcy risk; The structure of the investor relationship network has no effect on the income of the investment model.

  14. Feature network models for proximity data : statistical inference, model selection, network representations and links with related models

    NARCIS (Netherlands)

    Frank, Laurence Emmanuelle

    2006-01-01

    Feature Network Models (FNM) are graphical structures that represent proximity data in a discrete space with the use of features. A statistical inference theory is introduced, based on the additivity properties of networks and the linear regression framework. Considering features as predictor

  15. Related work on reference modeling for collaborative networks

    NARCIS (Netherlands)

    Afsarmanesh, H.; Camarinha-Matos, L.M.; Camarinha-Matos, L.M.; Afsarmanesh, H.

    2008-01-01

    Several international research and development initiatives have led to development of models for organizations and organization interactions. These models and their approaches constitute a background for development of reference models for collaborative networks. A brief survey of work on modeling

  16. A random spatial network model based on elementary postulates

    Science.gov (United States)

    Karlinger, Michael R.; Troutman, Brent M.

    1989-01-01

    A model for generating random spatial networks that is based on elementary postulates comparable to those of the random topology model is proposed. In contrast to the random topology model, this model ascribes a unique spatial specification to generated drainage networks, a distinguishing property of some network growth models. The simplicity of the postulates creates an opportunity for potential analytic investigations of the probabilistic structure of the drainage networks, while the spatial specification enables analyses of spatially dependent network properties. In the random topology model all drainage networks, conditioned on magnitude (number of first-order streams), are equally likely, whereas in this model all spanning trees of a grid, conditioned on area and drainage density, are equally likely. As a result, link lengths in the generated networks are not independent, as usually assumed in the random topology model. For a preliminary model evaluation, scale-dependent network characteristics, such as geometric diameter and link length properties, and topologic characteristics, such as bifurcation ratio, are computed for sets of drainage networks generated on square and rectangular grids. Statistics of the bifurcation and length ratios fall within the range of values reported for natural drainage networks, but geometric diameters tend to be relatively longer than those for natural networks.

  17. Adoptive parenting and attachment: association of the Internal Working Models between adoptive mothers and their late-adopted children during adolescence

    Directory of Open Access Journals (Sweden)

    Cecilia Serena ePace

    2015-09-01

    Full Text Available Introduction. Recent literature has shown that the good outcome of adoption would mostly depend on the quality of adoptive parenting, which is strongly associated with the security of parental internal working models (IWMs of attachment. Specifically, attachment states-of-mind of adoptive mothers classified as free and autonomous and without lack of resolution of loss or trauma could represent a good protective factor for adopted children previously maltreated and neglected. While most research on adoptive families has focused on pre-school and school-aged children, the aim of this study was to assess the concordance of IWMs of attachment in adoptive dyads during adolescence.Method. Our pilot-study involved 76 participants: 30 adoptive mothers (mean age=51.5±4.3, and their 46 late-adopted adolescents (mean age = 13.9 ± 1.6, who were all aged four to nine years old at time of adoption (M = 6.3 ± 1.5. Attachment representations of adopted adolescents were assessed by the Friend and Family Interview (FFI, while adoptive mothers’ state-of-mind with respect to attachment was classified by the Adult Attachment Interview (AAI. Adolescents’ verbal intelligence was controlled.Results. Late-adopted adolescents were classified as follows: 67% secure, 26% dismissing and 7% preoccupied in the FFI, while their adoptive mothers’ AAI classifications were 70% free-autonomous, 7% dismissing, and 23% unresolved. We found a significant concordance of 70% (32 dyads between the secure-insecure FFI and AAI classifications. Specifically adoptive mothers with high coherence of transcript and low unresolved loss tend to have late-adopted children with high secure attachment, even if the adolescents’ verbal intelligence made a significant contribution to this prediction.Discussion. Our results provides an empirical contribution to the literature concerning the concordance of attachment in adoptive dyads, highlighting the beneficial impact of highly coherent

  18. PageRank model of opinion formation on Ulam networks

    Science.gov (United States)

    Chakhmakhchyan, L.; Shepelyansky, D.

    2013-12-01

    We consider a PageRank model of opinion formation on Ulam networks, generated by the intermittency map and the typical Chirikov map. The Ulam networks generated by these maps have certain similarities with such scale-free networks as the World Wide Web (WWW), showing an algebraic decay of the PageRank probability. We find that the opinion formation process on Ulam networks has certain similarities but also distinct features comparing to the WWW. We attribute these distinctions to internal differences in network structure of the Ulam and WWW networks. We also analyze the process of opinion formation in the frame of generalized Sznajd model which protects opinion of small communities.

  19. An Improved Car-Following Model in Vehicle Networking Based on Network Control

    Directory of Open Access Journals (Sweden)

    D. Y. Kong

    2014-01-01

    Full Text Available Vehicle networking is a system to realize information interoperability between vehicles and people, vehicles and roads, vehicles and vehicles, and cars and transport facilities, through the network information exchange, in order to achieve the effective monitoring of the vehicle and traffic flow. Realizing information interoperability between vehicles and vehicles, which can affect the traffic flow, is an important application of network control system (NCS. In this paper, a car-following model using vehicle networking theory is established, based on network control principle. The car-following model, which is an improvement of the traditional traffic model, describes the traffic in vehicle networking condition. The impact that vehicle networking has on the traffic flow is quantitatively assessed in a particular scene of one-way, no lane changing highway. The examples show that the capacity of the road is effectively enhanced by using vehicle networking.

  20. Modeling management of research and education networks

    NARCIS (Netherlands)

    Galagan, D.V.

    2004-01-01

    Computer networks and their services have become an essential part of research and education. Nowadays every modern R&E institution must have a computer network and provide network services to its students and staff. In addition to its internal computer network, every R&E institution must have a

  1. Marketing communications model for innovation networks

    Directory of Open Access Journals (Sweden)

    Tiago João Freitas Correia

    2015-10-01

    Full Text Available Innovation is an increasingly relevant concept for the success of any organization, but it also represents a set of internal and external considerations, barriers and challenges to overcome. Along the concept of innovation, new paradigms emerge such as open innovation and co-creation that are simultaneously innovation modifiers and intensifiers in organizations, promoting organizational openness and stakeholder integration within the value creation process. Innovation networks composed by a multiplicity of agents in co-creative work perform as innovation mechanisms to face the increasingly complexity of products, services and markets. Technology, especially the Internet, is an enabler of all process among organizations supported by co-creative platforms for innovation. The definition of marketing communication strategies that promote motivation and involvement of all stakeholders in synergic creation and external promotion is the central aspect of this research. The implementation of the projects is performed by participative workshops with stakeholders from Madan Parque through IDEAS(REVOLUTION methodology and the operational model LinkUp parameterized for the project. The project is divided into the first part, the theoretical framework, and the second part where a model is developed for the marketing communication strategies that appeal to the Madan Parque case study. Keywords: Marketing Communication; Open Innovation, Technology; Innovation Networks; Incubator; Co-Creation.

  2. A graph model for opportunistic network coding

    KAUST Repository

    Sorour, Sameh

    2015-08-12

    © 2015 IEEE. Recent advancements in graph-based analysis and solutions of instantly decodable network coding (IDNC) trigger the interest to extend them to more complicated opportunistic network coding (ONC) scenarios, with limited increase in complexity. In this paper, we design a simple IDNC-like graph model for a specific subclass of ONC, by introducing a more generalized definition of its vertices and the notion of vertex aggregation in order to represent the storage of non-instantly-decodable packets in ONC. Based on this representation, we determine the set of pairwise vertex adjacency conditions that can populate this graph with edges so as to guarantee decodability or aggregation for the vertices of each clique in this graph. We then develop the algorithmic procedures that can be applied on the designed graph model to optimize any performance metric for this ONC subclass. A case study on reducing the completion time shows that the proposed framework improves on the performance of IDNC and gets very close to the optimal performance.

  3. Efficient Bayesian network modeling of systems

    International Nuclear Information System (INIS)

    Bensi, Michelle; Kiureghian, Armen Der; Straub, Daniel

    2013-01-01

    The Bayesian network (BN) is a convenient tool for probabilistic modeling of system performance, particularly when it is of interest to update the reliability of the system or its components in light of observed information. In this paper, BN structures for modeling the performance of systems that are defined in terms of their minimum link or cut sets are investigated. Standard BN structures that define the system node as a child of its constituent components or its minimum link/cut sets lead to converging structures, which are computationally disadvantageous and could severely hamper application of the BN to real systems. A systematic approach to defining an alternative formulation is developed that creates chain-like BN structures that are orders of magnitude more efficient, particularly in terms of computational memory demand. The formulation uses an integer optimization algorithm to identify the most efficient BN structure. Example applications demonstrate the proposed methodology and quantify the gained computational advantage

  4. Modeling stochasticity in biochemical reaction networks

    International Nuclear Information System (INIS)

    Constantino, P H; Vlysidis, M; Smadbeck, P; Kaznessis, Y N

    2016-01-01

    Small biomolecular systems are inherently stochastic. Indeed, fluctuations of molecular species are substantial in living organisms and may result in significant variation in cellular phenotypes. The chemical master equation (CME) is the most detailed mathematical model that can describe stochastic behaviors. However, because of its complexity the CME has been solved for only few, very small reaction networks. As a result, the contribution of CME-based approaches to biology has been very limited. In this review we discuss the approach of solving CME by a set of differential equations of probability moments, called moment equations. We present different approaches to produce and to solve these equations, emphasizing the use of factorial moments and the zero information entropy closure scheme. We also provide information on the stability analysis of stochastic systems. Finally, we speculate on the utility of CME-based modeling formalisms, especially in the context of synthetic biology efforts. (topical review)

  5. SUSTAIN: a network model of category learning.

    Science.gov (United States)

    Love, Bradley C; Medin, Douglas L; Gureckis, Todd M

    2004-04-01

    SUSTAIN (Supervised and Unsupervised STratified Adaptive Incremental Network) is a model of how humans learn categories from examples. SUSTAIN initially assumes a simple category structure. If simple solutions prove inadequate and SUSTAIN is confronted with a surprising event (e.g., it is told that a bat is a mammal instead of a bird), SUSTAIN recruits an additional cluster to represent the surprising event. Newly recruited clusters are available to explain future events and can themselves evolve into prototypes-attractors-rules. SUSTAIN's discovery of category substructure is affected not only by the structure of the world but by the nature of the learning task and the learner's goals. SUSTAIN successfully extends category learning models to studies of inference learning, unsupervised learning, category construction, and contexts in which identification learning is faster than classification learning.

  6. Multiplicative Attribute Graph Model of Real-World Networks

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)

    2010-10-20

    Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.

  7. Multilevel method for modeling large-scale networks.

    Energy Technology Data Exchange (ETDEWEB)

    Safro, I. M. (Mathematics and Computer Science)

    2012-02-24

    Understanding the behavior of real complex networks is of great theoretical and practical significance. It includes developing accurate artificial models whose topological properties are similar to the real networks, generating the artificial networks at different scales under special conditions, investigating a network dynamics, reconstructing missing data, predicting network response, detecting anomalies and other tasks. Network generation, reconstruction, and prediction of its future topology are central issues of this field. In this project, we address the questions related to the understanding of the network modeling, investigating its structure and properties, and generating artificial networks. Most of the modern network generation methods are based either on various random graph models (reinforced by a set of properties such as power law distribution of node degrees, graph diameter, and number of triangles) or on the principle of replicating an existing model with elements of randomization such as R-MAT generator and Kronecker product modeling. Hierarchical models operate at different levels of network hierarchy but with the same finest elements of the network. However, in many cases the methods that include randomization and replication elements on the finest relationships between network nodes and modeling that addresses the problem of preserving a set of simplified properties do not fit accurately enough the real networks. Among the unsatisfactory features are numerically inadequate results, non-stability of algorithms on real (artificial) data, that have been tested on artificial (real) data, and incorrect behavior at different scales. One reason is that randomization and replication of existing structures can create conflicts between fine and coarse scales of the real network geometry. Moreover, the randomization and satisfying of some attribute at the same time can abolish those topological attributes that have been undefined or hidden from

  8. A comprehensive probabilistic analysis model of oil pipelines network based on Bayesian network

    Science.gov (United States)

    Zhang, C.; Qin, T. X.; Jiang, B.; Huang, C.

    2018-02-01

    Oil pipelines network is one of the most important facilities of energy transportation. But oil pipelines network accident may result in serious disasters. Some analysis models for these accidents have been established mainly based on three methods, including event-tree, accident simulation and Bayesian network. Among these methods, Bayesian network is suitable for probabilistic analysis. But not all the important influencing factors are considered and the deployment rule of the factors has not been established. This paper proposed a probabilistic analysis model of oil pipelines network based on Bayesian network. Most of the important influencing factors, including the key environment condition and emergency response are considered in this model. Moreover, the paper also introduces a deployment rule for these factors. The model can be used in probabilistic analysis and sensitive analysis of oil pipelines network accident.

  9. An improved mounting device for attaching intracranial probes in large animal models.

    Science.gov (United States)

    Dunster, Kimble R

    2015-12-01

    The rigid support of intracranial probes can be difficult when using animal models, as mounting devices suitable for the probes are either not available, or designed for human use and not suitable in animal skulls. A cheap and reliable mounting device for securing intracranial probes in large animal models is described. Using commonly available clinical consumables, a universal mounting device for securing intracranial probes to the skull of large animals was developed and tested. A simply made mounting device to hold a variety of probes from 500 μm to 1.3 mm in diameter to the skull was developed. The device was used to hold probes to the skulls of sheep for up to 18 h. No adhesives or cements were used. The described device provides a reliable method of securing probes to the skull of animals.

  10. A fusion networking model for smart grid power distribution backbone communication network based on PTN

    Directory of Open Access Journals (Sweden)

    Wang Hao

    2016-01-01

    Full Text Available In current communication network for distribution in Chinese power grid systems, the fiber communication backbone network for distribution and TD-LTE power private wireless backhaul network of power grid are both bearing by the SDH optical transmission network, which also carries the communication network of transformer substation and main electric. As the data traffic of the distribution communication and TD-LTE power private wireless network grow rapidly in recent years, it will have a big impact with the SDH network’s bearing capacity which is mainly used for main electric communication in high security level. This paper presents a fusion networking model which use a multiple-layer PTN network as the unified bearing of the TD-LTE power private wireless backhaul network and fiber communication backbone network for distribution. Network dataflow analysis shows that this model can greatly reduce the capacity pressure of the traditional SDH network as well as ensure the reliability of the transmission of the communication network for distribution and TD-LTE power private wireless network.

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

    Science.gov (United States)

    Wang, Jie; Huang, Helai

    2016-05-01

    Safety and efficiency are commonly regarded as two significant performance indicators of transportation systems. In practice, road network planning has focused on road capacity and transport efficiency whereas the safety level of a road network has received little attention in the planning stage. This study develops a Bayesian hierarchical joint model for road network safety evaluation to help planners take traffic safety into account when planning a road network. The proposed model establishes relationships between road network risk and micro-level variables related to road entities and traffic volume, as well as socioeconomic, trip generation and network density variables at macro level which are generally used for long term transportation plans. In addition, network spatial correlation between intersections and their connected road segments is also considered in the model. A road network is elaborately selected in order to compare the proposed hierarchical joint model with a previous joint model and a negative binomial model. According to the results of the model comparison, the hierarchical joint model outperforms the joint model and negative binomial model in terms of the goodness-of-fit and predictive performance, which indicates the reasonableness of considering the hierarchical data structure in crash prediction and analysis. Moreover, both random effects at the TAZ level and the spatial correlation between intersections and their adjacent segments are found to be significant, supporting the employment of the hierarchical joint model as an alternative in road-network-level safety modeling as well. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Models as Tools of Analysis of a Network Organisation

    Directory of Open Access Journals (Sweden)

    Wojciech Pająk

    2013-06-01

    Full Text Available The paper presents models which may be applied as tools of analysis of a network organisation. The starting point of the discussion is defining the following terms: supply chain and network organisation. Further parts of the paper present basic assumptions analysis of a network organisation. Then the study characterises the best known models utilised in analysis of a network organisation. The purpose of the article is to define the notion and the essence of network organizations and to present the models used for their analysis.

  13. Resolving structural variability in network models and the brain.

    Directory of Open Access Journals (Sweden)

    Florian Klimm

    2014-03-01

    Full Text Available Large-scale white matter pathways crisscrossing the cortex create a complex pattern of connectivity that underlies human cognitive function. Generative mechanisms for this architecture have been difficult to identify in part because little is known in general about mechanistic drivers of structured networks. Here we contrast network properties derived from diffusion spectrum imaging data of the human brain with 13 synthetic network models chosen to probe the roles of physical network embedding and temporal network growth. We characterize both the empirical and synthetic networks using familiar graph metrics, but presented here in a more complete statistical form, as scatter plots and distributions, to reveal the full range of variability of each measure across scales in the network. We focus specifically on the degree distribution, degree assortativity, hierarchy, topological Rentian scaling, and topological fractal scaling--in addition to several summary statistics, including the mean clustering coefficient, the shortest path-length, and the network diameter. The models are investigated in a progressive, branching sequence, aimed at capturing different elements thought to be important in the brain, and range from simple random and regular networks, to models that incorporate specific growth rules and constraints. We find that synthetic models that constrain the network nodes to be physically embedded in anatomical brain regions tend to produce distributions that are most similar to the corresponding measurements for the brain. We also find that network models hardcoded to display one network property (e.g., assortativity do not in general simultaneously display a second (e.g., hierarchy. This relative independence of network properties suggests that multiple neurobiological mechanisms might be at play in the development of human brain network architecture. Together, the network models that we develop and employ provide a potentially useful

  14. Sonication reduces the attachment of Salmonella Typhimurium ATCC 14028 cells to bacterial cellulose-based plant cell wall models and cut plant material.

    Science.gov (United States)

    Tan, Michelle S F; Rahman, Sadequr; Dykes, Gary A

    2017-04-01

    This study investigated the removal of bacterial surface structures, particularly flagella, using sonication, and examined its effect on the attachment of Salmonella Typhimurium ATCC 14028 cells to plant cell walls. S. Typhimurium ATCC 14028 cells were subjected to sonication at 20 kHz to remove surface structures without affecting cell viability. Effective removal of flagella was determined by staining flagella of sonicated cells with Ryu's stain and enumerating the flagella remaining by direct microscopic counting. The attachment of sonicated S. Typhimurium cells to bacterial cellulose-based plant cell wall models and cut plant material (potato, apple, lettuce) was then evaluated. Varying concentrations of pectin and/or xyloglucan were used to produce a range of bacterial cellulose-based plant cell wall models. As compared to the non-sonicated controls, sonicated S. Typhimurium cells attached in significantly lower numbers (between 0.5 and 1.0 log CFU/cm 2 ) to all surfaces except to the bacterial cellulose-only composite without pectin and xyloglucan. Since attachment of S. Typhimurium to the bacterial cellulose-only composite was not affected by sonication, this suggests that bacterial surface structures, particularly flagella, could have specific interactions with pectin and xyloglucan. This study indicates that sonication may have potential applications for reducing Salmonella attachment during the processing of fresh produce. Copyright © 2016 Elsevier Ltd. All rights reserved.

  15. Women’s Social Networks and Birth Attendant Decisions: Application of the Network-Episode Model

    OpenAIRE

    Edmonds, Joyce K.; Hruschka, Daniel; Bernard, H. Russell; Sibley, Lynn

    2011-01-01

    This paper examines the association of women's social networks with the use of skilled birth attendants in uncomplicated pregnancy and childbirth in Matlab, Bangladesh. The Network-Episode Model was applied to determine if network structure variables (density / kinship homogeneity / strength of ties) together with network content (endorsement for or against a particular type of birth attendant) explain the type of birth attendant used by women above and beyond the variance explained by women'...

  16. A last updating evolution model for online social networks

    Science.gov (United States)

    Bu, Zhan; Xia, Zhengyou; Wang, Jiandong; Zhang, Chengcui

    2013-05-01

    As information technology has advanced, people are turning to electronic media more frequently for communication, and social relationships are increasingly found on online channels. However, there is very limited knowledge about the actual evolution of the online social networks. In this paper, we propose and study a novel evolution network model with the new concept of “last updating time”, which exists in many real-life online social networks. The last updating evolution network model can maintain the robustness of scale-free networks and can improve the network reliance against intentional attacks. What is more, we also found that it has the “small-world effect”, which is the inherent property of most social networks. Simulation experiment based on this model show that the results and the real-life data are consistent, which means that our model is valid.

  17. Adaptive Networks Theory, Models and Applications

    CERN Document Server

    Gross, Thilo

    2009-01-01

    With adaptive, complex networks, the evolution of the network topology and the dynamical processes on the network are equally important and often fundamentally entangled. Recent research has shown that such networks can exhibit a plethora of new phenomena which are ultimately required to describe many real-world networks. Some of those phenomena include robust self-organization towards dynamical criticality, formation of complex global topologies based on simple, local rules, and the spontaneous division of "labor" in which an initially homogenous population of network nodes self-organizes into functionally distinct classes. These are just a few. This book is a state-of-the-art survey of those unique networks. In it, leading researchers set out to define the future scope and direction of some of the most advanced developments in the vast field of complex network science and its applications.

  18. A graph model for opportunistic network coding

    KAUST Repository

    Sorour, Sameh; Aboutoraby, Neda; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim

    2015-01-01

    © 2015 IEEE. Recent advancements in graph-based analysis and solutions of instantly decodable network coding (IDNC) trigger the interest to extend them to more complicated opportunistic network coding (ONC) scenarios, with limited increase

  19. Modeling and control of magnetorheological fluid dampers using neural networks

    Science.gov (United States)

    Wang, D. H.; Liao, W. H.

    2005-02-01

    Due to the inherent nonlinear nature of magnetorheological (MR) fluid dampers, one of the challenging aspects for utilizing these devices to achieve high system performance is the development of accurate models and control algorithms that can take advantage of their unique characteristics. In this paper, the direct identification and inverse dynamic modeling for MR fluid dampers using feedforward and recurrent neural networks are studied. The trained direct identification neural network model can be used to predict the damping force of the MR fluid damper on line, on the basis of the dynamic responses across the MR fluid damper and the command voltage, and the inverse dynamic neural network model can be used to generate the command voltage according to the desired damping force through supervised learning. The architectures and the learning methods of the dynamic neural network models and inverse neural network models for MR fluid dampers are presented, and some simulation results are discussed. Finally, the trained neural network models are applied to predict and control the damping force of the MR fluid damper. Moreover, validation methods for the neural network models developed are proposed and used to evaluate their performance. Validation results with different data sets indicate that the proposed direct identification dynamic model using the recurrent neural network can be used to predict the damping force accurately and the inverse identification dynamic model using the recurrent neural network can act as a damper controller to generate the command voltage when the MR fluid damper is used in a semi-active mode.

  20. Structural equation models from paths to networks

    CERN Document Server

    Westland, J Christopher

    2015-01-01

    This compact reference surveys the full range of available structural equation modeling (SEM) methodologies.  It reviews applications in a broad range of disciplines, particularly in the social sciences where many key concepts are not directly observable.  This is the first book to present SEM’s development in its proper historical context–essential to understanding the application, strengths and weaknesses of each particular method.  This book also surveys the emerging path and network approaches that complement and enhance SEM, and that will grow in importance in the near future.  SEM’s ability to accommodate unobservable theory constructs through latent variables is of significant importance to social scientists.  Latent variable theory and application are comprehensively explained, and methods are presented for extending their power, including guidelines for data preparation, sample size calculation, and the special treatment of Likert scale data.  Tables of software, methodologies and fit st...

  1. Modeling bacterial attachment to surfaces as an early stage of biofilm development.

    Science.gov (United States)

    El Moustaid, Fadoua; Eladdadi, Amina; Uys, Lafras

    2013-06-01

    Biofilms are present in all natural, medical and industrial surroundings where bacteria live. Biofilm formation is a key factor in the growth and transport of both beneficial and harmful bacteria. While much is known about the later stages of biofilm formation, less is known about its initiation which is an important first step in the biofilm formation. In this paper, we develop a non-linear system of partial differential equations of Keller-Segel type model in one-dimensional space, which couples the dynamics of bacterial movement to that of the sensing molecules. In this case, bacteria perform a biased random walk towards the sensing molecules. We derive the boundary conditions of the adhesion of bacteria to a surface using zero-Dirichlet boundary conditions, while the equation describing sensing molecules at the interface needed particular conditions to be set. The numerical results show the profile of bacteria within the space and the time evolution of the density within the free-space and on the surface. Testing different parameter values indicate that significant amount of sensing molecules present on the surface leads to a faster bacterial movement toward the surface which is the first step of biofilm initiation. Our work gives rise to results that agree with the biological description of the early stages of biofilm formation.

  2. Network formation under heterogeneous costs: The multiple group model

    NARCIS (Netherlands)

    Kamphorst, J.J.A.; van der Laan, G.

    2007-01-01

    It is widely recognized that the shape of networks influences both individual and aggregate behavior. This raises the question which types of networks are likely to arise. In this paper we investigate a model of network formation, where players are divided into groups and the costs of a link between

  3. Neural networks in economic modelling : An empirical study

    NARCIS (Netherlands)

    Verkooijen, W.J.H.

    1996-01-01

    This dissertation addresses the statistical aspects of neural networks and their usability for solving problems in economics and finance. Neural networks are discussed in a framework of modelling which is generally accepted in econometrics. Within this framework a neural network is regarded as a

  4. Multiple Social Networks, Data Models and Measures for

    DEFF Research Database (Denmark)

    Magnani, Matteo; Rossi, Luca

    2017-01-01

    Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

  5. Agent Based Modeling on Organizational Dynamics of Terrorist Network

    OpenAIRE

    Bo Li; Duoyong Sun; Renqi Zhu; Ze Li

    2015-01-01

    Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model ...

  6. Learning Analytics for Networked Learning Models

    Science.gov (United States)

    Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

    2014-01-01

    Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

  7. Network model for fine coal dewatering. Part I. The model

    Energy Technology Data Exchange (ETDEWEB)

    Qamar, I.; Tierney, J.W.; Chiang, S.H.

    1985-08-01

    There is a body of well established research in filtration and related subjects, but much of it has been empirical - based on correlations from experimental data. This approach has the disadvantage that it lacks generality, and it is difficult to predict the behavior of new or different systems. A more general method for studying dewatering is needed-one which will include the microscopic characteristics of the filter cake, which, like other porous media, contains a complicated network of interconnected pores through which the fluid must flow. These pores play an important role in dewatering because they give rise to capillary forces when one fluid is displacing another. In this report, we describe a network model which we believe satisfies these requirements. In the main body of this report, the model is described in detail. Background information is given where appropriate, and a brief description is given of the experimental work being done in our laboratories to verify the model. A detailed description of the experimental procedures and results is given in other DOE reports. The computer programs which are needed to solve the model are described in detail in the Appendices and are accompanied by flow charts, sample problems, and sample outputs. Sufficient detail is given in order to use the model programs on other computer systems. 32 refs., 7 figs., 5 tabs.

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

    Directory of Open Access Journals (Sweden)

    Lan Liu

    2017-01-01

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

  9. Stochastic actor-oriented models for network change

    NARCIS (Netherlands)

    Snijders, T.A.B.

    1996-01-01

    A class of models is proposed for longitudinal network data. These models are along the lines of methodological individualism: actors use heuristics to try to achieve their individual goals, subject to constraints. The current network structure is among these constraints. The models are continuous

  10. Modeling the reemergence of information diffusion in social network

    Science.gov (United States)

    Yang, Dingda; Liao, Xiangwen; Shen, Huawei; Cheng, Xueqi; Chen, Guolong

    2018-01-01

    Information diffusion in networks is an important research topic in various fields. Existing studies either focus on modeling the process of information diffusion, e.g., independent cascade model and linear threshold model, or investigate information diffusion in networks with certain structural characteristics such as scale-free networks and small world networks. However, there are still several phenomena that have not been captured by existing information diffusion models. One of the prominent phenomena is the reemergence of information diffusion, i.e., a piece of information reemerges after the completion of its initial diffusion process. In this paper, we propose an optimized information diffusion model by introducing a new informed state into traditional susceptible-infected-removed model. We verify the proposed model via simulations in real-world social networks, and the results indicate that the model can reproduce the reemergence of information during the diffusion process.

  11. An Improved Walk Model for Train Movement on Railway Network

    International Nuclear Information System (INIS)

    Li Keping; Mao Bohua; Gao Ziyou

    2009-01-01

    In this paper, we propose an improved walk model for simulating the train movement on railway network. In the proposed method, walkers represent trains. The improved walk model is a kind of the network-based simulation analysis model. Using some management rules for walker movement, walker can dynamically determine its departure and arrival times at stations. In order to test the proposed method, we simulate the train movement on a part of railway network. The numerical simulation and analytical results demonstrate that the improved model is an effective tool for simulating the train movement on railway network. Moreover, it can well capture the characteristic behaviors of train scheduling in railway traffic. (general)

  12. Infinite Multiple Membership Relational Modeling for Complex Networks

    DEFF Research Database (Denmark)

    Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai

    Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...

  13. Stabilization of model-based networked control systems

    Energy Technology Data Exchange (ETDEWEB)

    Miranda, Francisco [CIDMA, Universidade de Aveiro, Aveiro (Portugal); Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); Abreu, Carlos [Instituto Politécnico de Viana do Castelo, Viana do Castelo (Portugal); CMEMS-UMINHO, Universidade do Minho, Braga (Portugal); Mendes, Paulo M. [CMEMS-UMINHO, Universidade do Minho, Braga (Portugal)

    2016-06-08

    A class of networked control systems called Model-Based Networked Control Systems (MB-NCSs) is considered. Stabilization of MB-NCSs is studied using feedback controls and simulation of stabilization for different feedbacks is made with the purpose to reduce the network trafic. The feedback control input is applied in a compensated model of the plant that approximates the plant dynamics and stabilizes the plant even under slow network conditions. Conditions for global exponential stabilizability and for the choosing of a feedback control input for a given constant time between the information moments of the network are derived. An optimal control problem to obtain an optimal feedback control is also presented.

  14. Mixture models with entropy regularization for community detection in networks

    Science.gov (United States)

    Chang, Zhenhai; Yin, Xianjun; Jia, Caiyan; Wang, Xiaoyang

    2018-04-01

    Community detection is a key exploratory tool in network analysis and has received much attention in recent years. NMM (Newman's mixture model) is one of the best models for exploring a range of network structures including community structure, bipartite and core-periphery structures, etc. However, NMM needs to know the number of communities in advance. Therefore, in this study, we have proposed an entropy regularized mixture model (called EMM), which is capable of inferring the number of communities and identifying network structure contained in a network, simultaneously. In the model, by minimizing the entropy of mixing coefficients of NMM using EM (expectation-maximization) solution, the small clusters contained little information can be discarded step by step. The empirical study on both synthetic networks and real networks has shown that the proposed model EMM is superior to the state-of-the-art methods.

  15. Conceptual and methodological biases in network models.

    Science.gov (United States)

    Lamm, Ehud

    2009-10-01

    Many natural and biological phenomena can be depicted as networks. Theoretical and empirical analyses of networks have become prevalent. I discuss theoretical biases involved in the delineation of biological networks. The network perspective is shown to dissolve the distinction between regulatory architecture and regulatory state, consistent with the theoretical impossibility of distinguishing a priori between "program" and "data." The evolutionary significance of the dynamics of trans-generational and interorganism regulatory networks is explored and implications are presented for understanding the evolution of the biological categories development-heredity, plasticity-evolvability, and epigenetic-genetic.

  16. Transmission network expansion planning based on hybridization model of neural networks and harmony search algorithm

    Directory of Open Access Journals (Sweden)

    Mohammad Taghi Ameli

    2012-01-01

    Full Text Available Transmission Network Expansion Planning (TNEP is a basic part of power network planning that determines where, when and how many new transmission lines should be added to the network. So, the TNEP is an optimization problem in which the expansion purposes are optimized. Artificial Intelligence (AI tools such as Genetic Algorithm (GA, Simulated Annealing (SA, Tabu Search (TS and Artificial Neural Networks (ANNs are methods used for solving the TNEP problem. Today, by using the hybridization models of AI tools, we can solve the TNEP problem for large-scale systems, which shows the effectiveness of utilizing such models. In this paper, a new approach to the hybridization model of Probabilistic Neural Networks (PNNs and Harmony Search Algorithm (HSA was used to solve the TNEP problem. Finally, by considering the uncertain role of the load based on a scenario technique, this proposed model was tested on the Garver’s 6-bus network.

  17. An effective fractal-tree closure model for simulating blood flow in large arterial networks.

    Science.gov (United States)

    Perdikaris, Paris; Grinberg, Leopold; Karniadakis, George Em

    2015-06-01

    The aim of the present work is to address the closure problem for hemodynamic simulations by developing a flexible and effective model that accurately distributes flow in the downstream vasculature and can stably provide a physiological pressure outflow boundary condition. To achieve this goal, we model blood flow in the sub-pixel vasculature by using a non-linear 1D model in self-similar networks of compliant arteries that mimic the structure and hierarchy of vessels in the meso-vascular regime (radii [Formula: see text]). We introduce a variable vessel length-to-radius ratio for small arteries and arterioles, while also addressing non-Newtonian blood rheology and arterial wall viscoelasticity effects in small arteries and arterioles. This methodology aims to overcome substantial cut-off radius sensitivities, typically arising in structured tree and linearized impedance models. The proposed model is not sensitive to outflow boundary conditions applied at the end points of the fractal network, and thus does not require calibration of resistance/capacitance parameters typically required for outflow conditions. The proposed model convergences to a periodic state in two cardiac cycles even when started from zero-flow initial conditions. The resulting fractal-trees typically consist of thousands to millions of arteries, posing the need for efficient parallel algorithms. To this end, we have scaled up a Discontinuous Galerkin solver that utilizes the MPI/OpenMP hybrid programming paradigm to thousands of computer cores, and can simulate blood flow in networks of millions of arterial segments at the rate of one cycle per 5 min. The proposed model has been extensively tested on a large and complex cranial network with 50 parent, patient-specific arteries and 21 outlets to which fractal trees where attached, resulting to a network of up to 4,392,484 vessels in total, and a detailed network of the arm with 276 parent arteries and 103 outlets (a total of 702,188 vessels

  18. Switching performance of OBS network model under prefetched real traffic

    Science.gov (United States)

    Huang, Zhenhua; Xu, Du; Lei, Wen

    2005-11-01

    Optical Burst Switching (OBS) [1] is now widely considered as an efficient switching technique in building the next generation optical Internet .So it's very important to precisely evaluate the performance of the OBS network model. The performance of the OBS network model is variable in different condition, but the most important thing is that how it works under real traffic load. In the traditional simulation models, uniform traffics are usually generated by simulation software to imitate the data source of the edge node in the OBS network model, and through which the performance of the OBS network is evaluated. Unfortunately, without being simulated by real traffic, the traditional simulation models have several problems and their results are doubtable. To deal with this problem, we present a new simulation model for analysis and performance evaluation of the OBS network, which uses prefetched IP traffic to be data source of the OBS network model. The prefetched IP traffic can be considered as real IP source of the OBS edge node and the OBS network model has the same clock rate with a real OBS system. So it's easy to conclude that this model is closer to the real OBS system than the traditional ones. The simulation results also indicate that this model is more accurate to evaluate the performance of the OBS network system and the results of this model are closer to the actual situation.

  19. Attachment as a Moderating Factor Between Social Support, Physical Health, and Psychological Symptoms

    Directory of Open Access Journals (Sweden)

    Kimberly A. Rapoza

    2016-12-01

    Full Text Available This study investigated the extent to which perceived social support functioned as a protective factors, and dimensions of insecure attachment (i.e., avoidant and anxious functioned as risks factors for physical and psychological health. We explored whether insecure attachment was a mechanism that modified the relationship (i.e., protect against or increases risk between social support and adult health. Participants were 155 non-traditional adult college students from demographically diverse backgrounds. Students were approached in common areas on campus or in classrooms during break and were asked to complete the questionnaire. Bartholomew and Horowitz’s Attachment Questionnaire assessed avoidant and anxious attachment dimensions, the Brief Social Support Questionnaire assessed perceived social support, and the Memorial Symptom Assessment Scale measured physical and psychological symptoms. Model results indicated that the anxious dimension of insecure attachment was more directly and positively associated with poorer general physical health and psychological symptoms, whereas greater perceived social support was linked with better reported health. However, an interesting pattern emerged with avoidant attachment through a moderated relationship with social support. The absence of a satisfying supportive network was significantly related to poorer physical and psychological health outcomes for those low in avoidant attachment, but not for those high in avoidant attachment. Results from this work suggest that insecure attachment plays a detrimental role in adult health. Perceived social support does not necessarily function as a blanket protective factor for health, as it seemed to offer less benefit to those high in attachment avoidance.

  20. Modeling MAC layer for powerline communications networks

    Science.gov (United States)

    Hrasnica, Halid; Haidine, Abdelfatteh

    2001-02-01

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

  1. Paternal Attachment, Parenting Beliefs and Children's Attachment

    Science.gov (United States)

    Howard, Kimberly S.

    2010-01-01

    Relationships between fathers' romantic attachment style, parenting beliefs and father-child attachment security and dependence were examined in a diverse sample of 72 fathers of young children. Paternal romantic attachment style was coded based on fathers' endorsement of a particular style represented in the Hazan and Shaver Three-Category…

  2. Ripple-Spreading Network Model Optimization by Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Xiao-Bing Hu

    2013-01-01

    Full Text Available Small-world and scale-free properties are widely acknowledged in many real-world complex network systems, and many network models have been developed to capture these network properties. The ripple-spreading network model (RSNM is a newly reported complex network model, which is inspired by the natural ripple-spreading phenomenon on clam water surface. The RSNM exhibits good potential for describing both spatial and temporal features in the development of many real-world networks where the influence of a few local events spreads out through nodes and then largely determines the final network topology. However, the relationships between ripple-spreading related parameters (RSRPs of RSNM and small-world and scale-free topologies are not as obvious or straightforward as in many other network models. This paper attempts to apply genetic algorithm (GA to tune the values of RSRPs, so that the RSNM may generate these two most important network topologies. The study demonstrates that, once RSRPs are properly tuned by GA, the RSNM is capable of generating both network topologies and therefore has a great flexibility to study many real-world complex network systems.

  3. Modelling the impact of social network on energy savings

    International Nuclear Information System (INIS)

    Du, Feng; Zhang, Jiangfeng; Li, Hailong; Yan, Jinyue; Galloway, Stuart; Lo, Kwok L.

    2016-01-01

    Highlights: • Energy saving propagation along a social network is modelled. • This model consists of a time evolving weighted directed network. • Network weights and information decay are applied in savings calculation. - Abstract: It is noted that human behaviour changes can have a significant impact on energy consumption, however, qualitative study on such an impact is still very limited, and it is necessary to develop the corresponding mathematical models to describe how much energy savings can be achieved through human engagement. In this paper a mathematical model of human behavioural dynamic interactions on a social network is derived to calculate energy savings. This model consists of a weighted directed network with time evolving information on each node. Energy savings from the whole network is expressed as mathematical expectation from probability theory. This expected energy savings model includes both direct and indirect energy savings of individuals in the network. The savings model is obtained by network weights and modified by the decay of information. Expected energy savings are calculated for cases where individuals in the social network are treated as a single information source or multiple sources. This model is tested on a social network consisting of 40 people. The results show that the strength of relations between individuals is more important to information diffusion than the number of connections individuals have. The expected energy savings of optimally chosen node can be 25.32% more than randomly chosen nodes at the end of the second month for the case of single information source in the network, and 16.96% more than random nodes for the case of multiple information sources. This illustrates that the model presented in this paper can be used to determine which individuals will have the most influence on the social network, which in turn provides a useful guide to identify targeted customers in energy efficiency technology rollout

  4. Hybrid neural network bushing model for vehicle dynamics simulation

    International Nuclear Information System (INIS)

    Sohn, Jeong Hyun; Lee, Seung Kyu; Yoo, Wan Suk

    2008-01-01

    Although the linear model was widely used for the bushing model in vehicle suspension systems, it could not express the nonlinear characteristics of bushing in terms of the amplitude and the frequency. An artificial neural network model was suggested to consider the hysteretic responses of bushings. This model, however, often diverges due to the uncertainties of the neural network under the unexpected excitation inputs. In this paper, a hybrid neural network bushing model combining linear and neural network is suggested. A linear model was employed to represent linear stiffness and damping effects, and the artificial neural network algorithm was adopted to take into account the hysteretic responses. A rubber test was performed to capture bushing characteristics, where sine excitation with different frequencies and amplitudes is applied. Random test results were used to update the weighting factors of the neural network model. It is proven that the proposed model has more robust characteristics than a simple neural network model under step excitation input. A full car simulation was carried out to verify the proposed bushing models. It was shown that the hybrid model results are almost identical to the linear model under several maneuvers

  5. Model for the growth of the world airline network

    Science.gov (United States)

    Verma, T.; Araújo, N. A. M.; Nagler, J.; Andrade, J. S.; Herrmann, H. J.

    2016-06-01

    We propose a probabilistic growth model for transport networks which employs a balance between popularity of nodes and the physical distance between nodes. By comparing the degree of each node in the model network and the World Airline Network (WAN), we observe that the difference between the two is minimized for α≈2. Interestingly, this is the value obtained for the node-node correlation function in the WAN. This suggests that our model explains quite well the growth of airline networks.

  6. Modelling the dependability in Network Function Virtualisation

    OpenAIRE

    Lin, Wenqi

    2017-01-01

    Network Function Virtualization has been brought up to allow the TSPs to have more possibilities and flexibilities to provision services with better load optimizing, energy utilizing and dynamic scaling. Network functions will be decoupled from the underlying dedicated hardware into software instances that run on commercial off-the-shelf servers. However, the development is still at an early stage and the dependability concerns raise by the virtualization of the network functions are touched ...

  7. Mode Choice Modeling Using Artificial Neural Networks

    OpenAIRE

    Edara, Praveen Kumar

    2003-01-01

    Artificial intelligence techniques have produced excellent results in many diverse fields of engineering. Techniques such as neural networks and fuzzy systems have found their way into transportation engineering. In recent years, neural networks are being used instead of regression techniques for travel demand forecasting purposes. The basic reason lies in the fact that neural networks are able to capture complex relationships and learn from examples and also able to adapt when new data becom...

  8. Bayesian Networks for Modeling Dredging Decisions

    Science.gov (United States)

    2011-10-01

    years, that algorithms have been developed to solve these problems efficiently. Most modern Bayesian network software uses junction tree (a.k.a. join... software was used to develop the network . This is by no means an exhaustive list of Bayesian network applications, but it is representative of recent...characteristic node (SCN), state- defining node ( SDN ), effect node (EFN), or value node. The five types of nodes can be described as follows: ERDC/EL TR-11

  9. A genetic algorithm for solving supply chain network design model

    Science.gov (United States)

    Firoozi, Z.; Ismail, N.; Ariafar, S. H.; Tang, S. H.; Ariffin, M. K. M. A.

    2013-09-01

    Network design is by nature costly and optimization models play significant role in reducing the unnecessary cost components of a distribution network. This study proposes a genetic algorithm to solve a distribution network design model. The structure of the chromosome in the proposed algorithm is defined in a novel way that in addition to producing feasible solutions, it also reduces the computational complexity of the algorithm. Computational results are presented to show the algorithm performance.

  10. Runoff Modelling in Urban Storm Drainage by Neural Networks

    DEFF Research Database (Denmark)

    Rasmussen, Michael R.; Brorsen, Michael; Schaarup-Jensen, Kjeld

    1995-01-01

    A neural network is used to simulate folw and water levels in a sewer system. The calibration of th neural network is based on a few measured events and the network is validated against measureed events as well as flow simulated with the MOUSE model (Lindberg and Joergensen, 1986). The neural...... network is used to compute flow or water level at selected points in the sewer system, and to forecast the flow from a small residential area. The main advantages of the neural network are the build-in self calibration procedure and high speed performance, but the neural network cannot be used to extract...... knowledge of the runoff process. The neural network was found to simulate 150 times faster than e.g. the MOUSE model....

  11. A control model for district heating networks with storage

    NARCIS (Netherlands)

    Scholten, Tjeert; De Persis, Claudio; Tesi, Pietro

    2014-01-01

    In [1] pressure control of hydraulic networks is investigated. We extend this work to district heating systems with storage capabilities and derive a model taking the topology of the network into account. The goal for the derived model is that it should allow for control of the storage level and

  12. Travel Time Reliability for Urban Networks : Modelling and Empirics

    NARCIS (Netherlands)

    Zheng, F.; Liu, Xiaobo; van Zuylen, H.J.; Li, Jie; Lu, Chao

    2017-01-01

    The importance of travel time reliability in traffic management, control, and network design has received a lot of attention in the past decade. In this paper, a network travel time distribution model based on the Johnson curve system is proposed. The model is applied to field travel time data

  13. Deterministic ripple-spreading model for complex networks.

    Science.gov (United States)

    Hu, Xiao-Bing; Wang, Ming; Leeson, Mark S; Hines, Evor L; Di Paolo, Ezequiel

    2011-04-01

    This paper proposes a deterministic complex network model, which is inspired by the natural ripple-spreading phenomenon. The motivations and main advantages of the model are the following: (i) The establishment of many real-world networks is a dynamic process, where it is often observed that the influence of a few local events spreads out through nodes, and then largely determines the final network topology. Obviously, this dynamic process involves many spatial and temporal factors. By simulating the natural ripple-spreading process, this paper reports a very natural way to set up a spatial and temporal model for such complex networks. (ii) Existing relevant network models are all stochastic models, i.e., with a given input, they cannot output a unique topology. Differently, the proposed ripple-spreading model can uniquely determine the final network topology, and at the same time, the stochastic feature of complex networks is captured by randomly initializing ripple-spreading related parameters. (iii) The proposed model can use an easily manageable number of ripple-spreading related parameters to precisely describe a network topology, which is more memory efficient when compared with traditional adjacency matrix or similar memory-expensive data structures. (iv) The ripple-spreading model has a very good potential for both extensions and applications.

  14. Scaffold Attachment Factor B1: A Novel Chromatin Regulator of Prostate Cancer Metabolism

    Science.gov (United States)

    2016-10-01

    AWARD NUMBER: W81XWH-14-1-0152 TITLE: Scaffold Attachment Factor B1: A Novel Chromatin Regulator of Prostate Cancer Metabolism PRINCIPAL...TITLE AND SUBTITLE 5a. CONTRACT NUMBER W81XWH-14-1-0152 Scaffold Attachment Factor B1: A Novel Chromatin Regulator of Prostate Cancer Metabolism... chromatin immunoprecipitation-next generation DNA sequencing (ChIP-seq) and integrative network modeling to identify the SAFB1 cistrome and the extent of

  15. Mathematical modelling of complex contagion on clustered networks

    Science.gov (United States)

    O'sullivan, David J.; O'Keeffe, Gary; Fennell, Peter; Gleeson, James

    2015-09-01

    The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010), adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the “complex contagion” effects of social reinforcement are important in such diffusion, in contrast to “simple” contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory) regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010), to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.

  16. Mathematical modelling of complex contagion on clustered networks

    Directory of Open Access Journals (Sweden)

    David J. P. O'Sullivan

    2015-09-01

    Full Text Available The spreading of behavior, such as the adoption of a new innovation, is influenced bythe structure of social networks that interconnect the population. In the experiments of Centola (Science, 2010, adoption of new behavior was shown to spread further and faster across clustered-lattice networks than across corresponding random networks. This implies that the complex contagion effects of social reinforcement are important in such diffusion, in contrast to simple contagion models of disease-spread which predict that epidemics would grow more efficiently on random networks than on clustered networks. To accurately model complex contagion on clustered networks remains a challenge because the usual assumptions (e.g. of mean-field theory regarding tree-like networks are invalidated by the presence of triangles in the network; the triangles are, however, crucial to the social reinforcement mechanism, which posits an increased probability of a person adopting behavior that has been adopted by two or more neighbors. In this paper we modify the analytical approach that was introduced by Hebert-Dufresne et al. (Phys. Rev. E, 2010, to study disease-spread on clustered networks. We show how the approximation method can be adapted to a complex contagion model, and confirm the accuracy of the method with numerical simulations. The analytical results of the model enable us to quantify the level of social reinforcement that is required to observe—as in Centola’s experiments—faster diffusion on clustered topologies than on random networks.

  17. A small-world network model of facial emotion recognition.

    Science.gov (United States)

    Takehara, Takuma; Ochiai, Fumio; Suzuki, Naoto

    2016-01-01

    Various models have been proposed to increase understanding of the cognitive basis of facial emotions. Despite those efforts, interactions between facial emotions have received minimal attention. If collective behaviours relating to each facial emotion in the comprehensive cognitive system could be assumed, specific facial emotion relationship patterns might emerge. In this study, we demonstrate that the frameworks of complex networks can effectively capture those patterns. We generate 81 facial emotion images (6 prototypes and 75 morphs) and then ask participants to rate degrees of similarity in 3240 facial emotion pairs in a paired comparison task. A facial emotion network constructed on the basis of similarity clearly forms a small-world network, which features an extremely short average network distance and close connectivity. Further, even if two facial emotions have opposing valences, they are connected within only two steps. In addition, we show that intermediary morphs are crucial for maintaining full network integration, whereas prototypes are not at all important. These results suggest the existence of collective behaviours in the cognitive systems of facial emotions and also describe why people can efficiently recognize facial emotions in terms of information transmission and propagation. For comparison, we construct three simulated networks--one based on the categorical model, one based on the dimensional model, and one random network. The results reveal that small-world connectivity in facial emotion networks is apparently different from those networks, suggesting that a small-world network is the most suitable model for capturing the cognitive basis of facial emotions.

  18. A general evolving model for growing bipartite networks

    International Nuclear Information System (INIS)

    Tian, Lixin; He, Yinghuan; Liu, Haijun; Du, Ruijin

    2012-01-01

    In this Letter, we propose and study an inner evolving bipartite network model. Significantly, we prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. Furthermore, the joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks. Numerical simulations and empirical results are given to verify the theoretical results. -- Highlights: ► We proposed a general evolving bipartite network model which was based on priority connection, reconnection and breaking edges. ► We prove that the degree distribution of two different kinds of nodes both obey power-law form with adjustable exponents. ► The joint degree distribution of any two nodes for bipartite networks model is calculated analytically by the mean-field method. ► The result displays that such bipartite networks are nearly uncorrelated networks, which is different from one-mode networks.

  19. Modeling geomagnetic induced currents in Australian power networks

    Science.gov (United States)

    Marshall, R. A.; Kelly, A.; Van Der Walt, T.; Honecker, A.; Ong, C.; Mikkelsen, D.; Spierings, A.; Ivanovich, G.; Yoshikawa, A.

    2017-07-01

    Geomagnetic induced currents (GICs) have been considered an issue for high-latitude power networks for some decades. More recently, GICs have been observed and studied in power networks located in lower latitude regions. This paper presents the results of a model aimed at predicting and understanding the impact of geomagnetic storms on power networks in Australia, with particular focus on the Queensland and Tasmanian networks. The model incorporates a "geoelectric field" determined using a plane wave magnetic field incident on a uniform conducting Earth, and the network model developed by Lehtinen and Pirjola (1985). Model results for two intense geomagnetic storms of solar cycle 24 are compared with transformer neutral monitors at three locations within the Queensland network and one location within the Tasmanian network. The model is then used to assess the impacts of the superintense geomagnetic storm of 29-31 October 2003 on the flow of GICs within these networks. The model results show good correlation with the observations with coefficients ranging from 0.73 to 0.96 across the observing sites. For Queensland, modeled GIC magnitudes during the superstorm of 29-31 October 2003 exceed 40 A with the larger GICs occurring in the south-east section of the network. Modeled GICs in Tasmania for the same storm do not exceed 30 A. The larger distance spans and general east-west alignment of the southern section of the Queensland network, in conjunction with some relatively low branch resistance values, result in larger modeled GICs despite Queensland being a lower latitude network than Tasmania.

  20. Systems and methods for modeling and analyzing networks

    Science.gov (United States)

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

    2013-10-29

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

  1. Ocean wave prediction using numerical and neural network models

    Digital Repository Service at National Institute of Oceanography (India)

    Mandal, S.; Prabaharan, N.

    This paper presents an overview of the development of the numerical wave prediction models and recently used neural networks for ocean wave hindcasting and forecasting. The numerical wave models express the physical concepts of the phenomena...

  2. Dynamic thermo-hydraulic model of district cooling networks

    International Nuclear Information System (INIS)

    Oppelt, Thomas; Urbaneck, Thorsten; Gross, Ulrich; Platzer, Bernd

    2016-01-01

    Highlights: • A dynamic thermo-hydraulic model for district cooling networks is presented. • The thermal modelling is based on water segment tracking (Lagrangian approach). • Thus, numerical errors and balance inaccuracies are avoided. • Verification and validation studies proved the reliability of the model. - Abstract: In the present paper, the dynamic thermo-hydraulic model ISENA is presented which can be applied for answering different questions occurring in design and operation of district cooling networks—e.g. related to economic and energy efficiency. The network model consists of a quasistatic hydraulic model and a transient thermal model based on tracking water segments through the whole network (Lagrangian method). Applying this approach, numerical errors and balance inaccuracies can be avoided which leads to a higher quality of results compared to other network models. Verification and validation calculations are presented in order to show that ISENA provides reliable results and is suitable for practical application.

  3. Investigation of the single layer model of GPS ionospheric data processing using IRI-90 and the attached diffusive equilibrium model of plasmaspheric electron density

    Directory of Open Access Journals (Sweden)

    L. Bànyai

    1997-06-01

    Full Text Available The single layer model of GPS ionospheric data processing is compared with the International Reference Ionosphere í 1990 and the attached Diffusive Equilibrium model of Plasmasphere (IRI-90+DEP which proved to be a good supplement to GPS data processing. These models can be used to estimate the single layer height and to improve the mapping function in day-time. The code delays estimated from IRI-90+DEP models are compared with GPS measurements carried out by TurboRogue receiver. These models can be used to estimate the preliminary receiver biases especially in the case of cross-correlation tracking mode. The practical drawback of the IRI-90 model is the sharp discontinuity of the ion components during sunset and sunrise at an elevation of 1000 km, because it also causes a sharp discontinuity in the TEC values computed from the DEP model. The GPS data may be a good source to improve the topside region of the IRI model estimating smooth TEC transition before and after sunrise in the plasmasphere.

  4. Dynamic Pathloss Model for Future Mobile Communication Networks

    DEFF Research Database (Denmark)

    Kumar, Ambuj; Mihovska, Albena Dimitrova; Prasad, Ramjee

    2016-01-01

    that are essentially static. Therefore, once the signal level drops beyond the predicted values due to any variance in the environmental conditions, very crowded areas may not be catered well enough by the deployed network that had been designed with the static path loss model. This paper proposes an approach......— Future mobile communication networks (MCNs) are expected to be more intelligent and proactive based on new capabilities that increase agility and performance. However, for any successful mobile network service, the dexterity in network deployment is a key factor. The efficiency of the network...... planning depends on how congruent the chosen path loss model and real propagation are. Various path loss models have been developed that predict the signal propagation in various morphological and climatic environments; however they consider only those physical parameters of the network environment...

  5. Dynamic Pathloss Model for Place and Time Itinerant Networks

    DEFF Research Database (Denmark)

    Kumar, Ambuj; Mihovska, Albena; Prasad, Ramjee

    2018-01-01

    that are essentially static. Therefore, once the signal level drops beyond the predicted values due to any variance in the environmental conditions, very crowded areas may not be catered well enough by the deployed network that had been designed with the static path loss model. This paper proposes an approach......t Future mobile communication networks are expected to be more intelligent and proactive based on new capabilities that increase agility and performance. However, for any successful mobile network service, the dexterity in network deployment is a key factor. The efficiency of the network planning...... depends on how congruent the chosen path loss model and real propagation are. Various path loss models have been developed that predict the signal propagation in various morphological and climatic environments; however they consider only those physical parameters of the network environment...

  6. An information spreading model based on online social networks

    Science.gov (United States)

    Wang, Tao; He, Juanjuan; Wang, Xiaoxia

    2018-01-01

    Online social platforms are very popular in recent years. In addition to spreading information, users could review or collect information on online social platforms. According to the information spreading rules of online social network, a new information spreading model, namely IRCSS model, is proposed in this paper. It includes sharing mechanism, reviewing mechanism, collecting mechanism and stifling mechanism. Mean-field equations are derived to describe the dynamics of the IRCSS model. Moreover, the steady states of reviewers, collectors and stiflers and the effects of parameters on the peak values of reviewers, collectors and sharers are analyzed. Finally, numerical simulations are performed on different networks. Results show that collecting mechanism and reviewing mechanism, as well as the connectivity of the network, make information travel wider and faster, and compared to WS network and ER network, the speed of reviewing, sharing and collecting information is fastest on BA network.

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

    Science.gov (United States)

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

    2018-02-01

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

  8. A Mathematical Model to Improve the Performance of Logistics Network

    Directory of Open Access Journals (Sweden)

    Muhammad Izman Herdiansyah

    2012-01-01

    Full Text Available The role of logistics nowadays is expanding from just providing transportation and warehousing to offering total integrated logistics. To remain competitive in the global market environment, business enterprises need to improve their logistics operations performance. The improvement will be achieved when we can provide a comprehensive analysis and optimize its network performances. In this paper, a mixed integer linier model for optimizing logistics network performance is developed. It provides a single-product multi-period multi-facilities model, as well as the multi-product concept. The problem is modeled in form of a network flow problem with the main objective to minimize total logistics cost. The problem can be solved using commercial linear programming package like CPLEX or LINDO. Even in small case, the solver in Excel may also be used to solve such model.Keywords: logistics network, integrated model, mathematical programming, network optimization

  9. A Network Contention Model for the Extreme-scale Simulator

    Energy Technology Data Exchange (ETDEWEB)

    Engelmann, Christian [ORNL; Naughton III, Thomas J [ORNL

    2015-01-01

    The Extreme-scale Simulator (xSim) is a performance investigation toolkit for high-performance computing (HPC) hardware/software co-design. It permits running a HPC application with millions of concurrent execution threads, while observing its performance in a simulated extreme-scale system. This paper details a newly developed network modeling feature for xSim, eliminating the shortcomings of the existing network modeling capabilities. The approach takes a different path for implementing network contention and bandwidth capacity modeling using a less synchronous and accurate enough model design. With the new network modeling feature, xSim is able to simulate on-chip and on-node networks with reasonable accuracy and overheads.

  10. Efficient Neural Network Modeling for Flight and Space Dynamics Simulation

    Directory of Open Access Journals (Sweden)

    Ayman Hamdy Kassem

    2011-01-01

    Full Text Available This paper represents an efficient technique for neural network modeling of flight and space dynamics simulation. The technique will free the neural network designer from guessing the size and structure for the required neural network model and will help to minimize the number of neurons. For linear flight/space dynamics systems, the technique can find the network weights and biases directly by solving a system of linear equations without the need for training. Nonlinear flight dynamic systems can be easily modeled by training its linearized models keeping the same network structure. The training is fast, as it uses the linear system knowledge to speed up the training process. The technique is tested on different flight/space dynamic models and showed promising results.

  11. Mathematical model on malicious attacks in a mobile wireless network with clustering

    International Nuclear Information System (INIS)

    Haldar, Kaushik; Mishra, Bimal Kumar

    2015-01-01

    A mathematical model has been formulated for the analysis of a wireless epidemic on a clustered heterogeneous network. The model introduces mobility into the epidemic framework assuming that the component nodes have a tendency to be attached with a frequently visited home cluster. This underlines the inherent regularity in the mobility pattern of mobile nodes in a wireless network. The analysis focuses primarily on features that arise because of the mobility considerations compared in the larger scenario formed by the epidemic aspects. A result on the invariance of the home cluster populations with respect to time provides an important view-point of the long-term behavior of the system. The analysis also focuses on obtaining a basic threshold condition that guides the epidemic behavior of the system. Analytical as well as numerical results have also been obtained to establish the asymptotic behavior of the connected components of the network, and that of the whole network when the underlying graph turns out to be irreducible. Applications to proximity based attacks and to scenarios with high cluster density have also been outlined

  12. Experimental findings on God as an attachment figure: normative processes and moderating effects of internal working models.

    Science.gov (United States)

    Granqvist, Pehr; Mikulincer, Mario; Gewirtz, Vered; Shaver, Phillip R

    2012-11-01

    Four studies examined implications of attachment theory for psychological aspects of religion among Israeli Jews. Study 1 replicated previous correlational findings indicating correspondence among interpersonal attachment orientations, attachment to God, and image of God. Studies 2-4 were subliminal priming experiments, which documented both normative and individual-difference effects. Regarding normative effects, findings indicated that threat priming heightened cognitive access to God-related concepts in a lexical decision task (Study 2); priming with "God" heightened cognitive access to positive, secure base-related concepts in the same task (Study 3); and priming with a religious symbol caused neutral material to be better liked (Study 4). Regarding individual differences, interpersonal attachment-related avoidance reduced the normative effects (i.e., avoidant participants had lower implicit access to God as a safe haven and secure base). Findings were mostly independent of level of religiousness. The present experiments considerably extend the psychological literature on connections between attachment constructs and aspects of religion. (c) 2012 APA, all rights reserved.

  13. Statistics of leaders and lead changes in growing networks

    International Nuclear Information System (INIS)

    Godrèche, C; Grandclaude, H; Luck, J M

    2010-01-01

    We investigate various aspects of the statistics of leaders in growing network models defined by stochastic attachment rules. The leader is the node with highest degree at a given time (or the node which reached that degree first if there are co-leaders). This comprehensive study includes the full distribution of the degree of the leader, its identity, the number of co-leaders, as well as several observables characterizing the whole history of lead changes: number of lead changes, number of distinct leaders, lead persistence probability. We successively consider the following network models: uniform attachment, linear attachment (the Barabási–Albert model), and generalized preferential attachment with initial attractiveness

  14. Model and simulation of Krause model in dynamic open network

    Science.gov (United States)

    Zhu, Meixia; Xie, Guangqiang

    2017-08-01

    The construction of the concept of evolution is an effective way to reveal the formation of group consensus. This study is based on the modeling paradigm of the HK model (Hegsekmann-Krause). This paper analyzes the evolution of multi - agent opinion in dynamic open networks with member mobility. The results of the simulation show that when the number of agents is constant, the interval distribution of the initial distribution will affect the number of the final view, The greater the distribution of opinions, the more the number of views formed eventually; The trust threshold has a decisive effect on the number of views, and there is a negative correlation between the trust threshold and the number of opinions clusters. The higher the connectivity of the initial activity group, the more easily the subjective opinion in the evolution of opinion to achieve rapid convergence. The more open the network is more conducive to the unity of view, increase and reduce the number of agents will not affect the consistency of the group effect, but not conducive to stability.

  15. A comprehensive multi-local-world model for complex networks

    International Nuclear Information System (INIS)

    Fan Zhengping; Chen Guanrong; Zhang Yunong

    2009-01-01

    The nodes in a community within a network are much more connected to each other than to the others outside the community in the same network. This phenomenon has been commonly observed from many real-world networks, ranging from social to biological even to technical networks. Meanwhile, the number of communities in some real-world networks, such as the Internet and most social networks, are evolving with time. To model this kind of networks, the present Letter proposes a multi-local-world (MLW) model to capture and describe their essential topological properties. Based on the mean-field theory, the degree distribution of this model is obtained analytically, showing that the generated network has a novel topological feature as being not completely random nor completely scale-free but behaving somewhere between them. As a typical application, the MLW model is applied to characterize the Internet against some other models such as the BA, GBA, Fitness and HOT models, demonstrating the superiority of the new model.

  16. Hydrometeorological network for flood monitoring and modeling

    Science.gov (United States)

    Efstratiadis, Andreas; Koussis, Antonis D.; Lykoudis, Spyros; Koukouvinos, Antonis; Christofides, Antonis; Karavokiros, George; Kappos, Nikos; Mamassis, Nikos; Koutsoyiannis, Demetris

    2013-08-01

    Due to its highly fragmented geomorphology, Greece comprises hundreds of small- to medium-size hydrological basins, in which often the terrain is fairly steep and the streamflow regime ephemeral. These are typically affected by flash floods, occasionally causing severe damages. Yet, the vast majority of them lack flow-gauging infrastructure providing systematic hydrometric data at fine time scales. This has obvious impacts on the quality and reliability of flood studies, which typically use simplistic approaches for ungauged basins that do not consider local peculiarities in sufficient detail. In order to provide a consistent framework for flood design and to ensure realistic predictions of the flood risk -a key issue of the 2007/60/EC Directive- it is essential to improve the monitoring infrastructures by taking advantage of modern technologies for remote control and data management. In this context and in the research project DEUCALION, we have recently installed and are operating, in four pilot river basins, a telemetry-based hydro-meteorological network that comprises automatic stations and is linked to and supported by relevant software. The hydrometric stations measure stage, using 50-kHz ultrasonic pulses or piezometric sensors, or both stage (piezometric) and velocity via acoustic Doppler radar; all measurements are being temperature-corrected. The meteorological stations record air temperature, pressure, relative humidity, wind speed and direction, and precipitation. Data transfer is made via GPRS or mobile telephony modems. The monitoring network is supported by a web-based application for storage, visualization and management of geographical and hydro-meteorological data (ENHYDRIS), a software tool for data analysis and processing (HYDROGNOMON), as well as an advanced model for flood simulation (HYDROGEIOS). The recorded hydro-meteorological observations are accessible over the Internet through the www-application. The system is operational and its

  17. Hidden long evolutionary memory in a model biochemical network

    Science.gov (United States)

    Ali, Md. Zulfikar; Wingreen, Ned S.; Mukhopadhyay, Ranjan

    2018-04-01

    We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

  18. Linear control theory for gene network modeling.

    Science.gov (United States)

    Shin, Yong-Jun; Bleris, Leonidas

    2010-09-16

    Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain) and linear state-space (time domain) can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

  19. Modeling Temporal Evolution and Multiscale Structure in Networks

    DEFF Research Database (Denmark)

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

    2013-01-01

    Many real-world networks exhibit both temporal evolution and multiscale structure. We propose a model for temporally correlated multifurcating hierarchies in complex networks which jointly capture both effects. We use the Gibbs fragmentation tree as prior over multifurcating trees and a change......-point model to account for the temporal evolution of each vertex. We demonstrate that our model is able to infer time-varying multiscale structure in synthetic as well as three real world time-evolving complex networks. Our modeling of the temporal evolution of hierarchies brings new insights...

  20. Growth of cortical neuronal network in vitro: Modeling and analysis

    International Nuclear Information System (INIS)

    Lai, P.-Y.; Jia, L. C.; Chan, C. K.

    2006-01-01

    We present a detailed analysis and theoretical growth models to account for recent experimental data on the growth of cortical neuronal networks in vitro [Phys. Rev. Lett. 93, 088101 (2004)]. The experimentally observed synchronized firing frequency of a well-connected neuronal network is shown to be proportional to the mean network connectivity. The growth of the network is consistent with the model of an early enhanced growth of connection, but followed by a retarded growth once the synchronized cluster is formed. Microscopic models with dominant excluded volume interactions are consistent with the observed exponential decay of the mean connection probability as a function of the mean network connectivity. The biological implications of the growth model are also discussed

  1. SPLAI: Computational Finite Element Model for Sensor Networks

    Directory of Open Access Journals (Sweden)

    Ruzana Ishak

    2006-01-01

    Full Text Available Wireless sensor network refers to a group of sensors, linked by a wireless medium to perform distributed sensing task. The primary interest is their capability in monitoring the physical environment through the deployment of numerous tiny, intelligent, wireless networked sensor nodes. Our interest consists of a sensor network, which includes a few specialized nodes called processing elements that can perform some limited computational capabilities. In this paper, we propose a model called SPLAI that allows the network to compute a finite element problem where the processing elements are modeled as the nodes in the linear triangular approximation problem. Our model also considers the case of some failures of the sensors. A simulation model to visualize this network has been developed using C++ on the Windows environment.

  2. Modeling the propagation of mobile malware on complex networks

    Science.gov (United States)

    Liu, Wanping; Liu, Chao; Yang, Zheng; Liu, Xiaoyang; Zhang, Yihao; Wei, Zuxue

    2016-08-01

    In this paper, the spreading behavior of malware across mobile devices is addressed. By introducing complex networks to model mobile networks, which follows the power-law degree distribution, a novel epidemic model for mobile malware propagation is proposed. The spreading threshold that guarantees the dynamics of the model is calculated. Theoretically, the asymptotic stability of the malware-free equilibrium is confirmed when the threshold is below the unity, and the global stability is further proved under some sufficient conditions. The influences of different model parameters as well as the network topology on malware propagation are also analyzed. Our theoretical studies and numerical simulations show that networks with higher heterogeneity conduce to the diffusion of malware, and complex networks with lower power-law exponents benefit malware spreading.

  3. Analysis and logical modeling of biological signaling transduction networks

    Science.gov (United States)

    Sun, Zhongyao

    The study of network theory and its application span across a multitude of seemingly disparate fields of science and technology: computer science, biology, social science, linguistics, etc. It is the intrinsic similarities embedded in the entities and the way they interact with one another in these systems that link them together. In this dissertation, I present from both the aspect of theoretical analysis and the aspect of application three projects, which primarily focus on signal transduction networks in biology. In these projects, I assembled a network model through extensively perusing literature, performed model-based simulations and validation, analyzed network topology, and proposed a novel network measure. The application of network modeling to the system of stomatal opening in plants revealed a fundamental question about the process that has been left unanswered in decades. The novel measure of the redundancy of signal transduction networks with Boolean dynamics by calculating its maximum node-independent elementary signaling mode set accurately predicts the effect of single node knockout in such signaling processes. The three projects as an organic whole advance the understanding of a real system as well as the behavior of such network models, giving me an opportunity to take a glimpse at the dazzling facets of the immense world of network science.

  4. UML modelling of network warfare examples

    CSIR Research Space (South Africa)

    Veerasamy, N

    2011-08-01

    Full Text Available ] Affects both civilian and military domains [8] [9] Related to the concepts of infowar, information operations, hacking, hackivism, cyberterrorism and cybotage depending on motivations and techniques [10] Encompasses both technological solutions...]. In addition, Williers as well as Qingbao and Anwar discuss more offensive aspects of information security and Network Warfare like Hacking, Vulnerability Injection, Network Attacks, Denial of Capability, Interception and Blockage [6] [18] [19]. Various...

  5. Neural Network Models for Time Series Forecasts

    OpenAIRE

    Tim Hill; Marcus O'Connor; William Remus

    1996-01-01

    Neural networks have been advocated as an alternative to traditional statistical forecasting methods. In the present experiment, time series forecasts produced by neural networks are compared with forecasts from six statistical time series methods generated in a major forecasting competition (Makridakis et al. [Makridakis, S., A. Anderson, R. Carbone, R. Fildes, M. Hibon, R. Lewandowski, J. Newton, E. Parzen, R. Winkler. 1982. The accuracy of extrapolation (time series) methods: Results of a ...

  6. Stochastic model and method of zoning water networks

    OpenAIRE

    Тевяшев, Андрей Дмитриевич; Матвиенко, Ольга Ивановна

    2014-01-01

    Water consumption at different time of the day is uneven. The model of steady flow distribution in water-supply networks is calculated for maximum consumption and effectively used in the network design and reconstruction. Quasi-stationary modes, in which the parameters are random variables and vary relative to their mean values are more suitable for operational management and planning of rational network operation modes.Leaks, which sometimes exceed 50 % of the volume of water supplied, are o...

  7. A three-dimensional computational model of collagen network mechanics.

    Directory of Open Access Journals (Sweden)

    Byoungkoo Lee

    Full Text Available Extracellular matrix (ECM strongly influences cellular behaviors, including cell proliferation, adhesion, and particularly migration. In cancer, the rigidity of the stromal collagen environment is thought to control tumor aggressiveness, and collagen alignment has been linked to tumor cell invasion. While the mechanical properties of collagen at both the single fiber scale and the bulk gel scale are quite well studied, how the fiber network responds to local stress or deformation, both structurally and mechanically, is poorly understood. This intermediate scale knowledge is important to understanding cell-ECM interactions and is the focus of this study. We have developed a three-dimensional elastic collagen fiber network model (bead-and-spring model and studied fiber network behaviors for various biophysical conditions: collagen density, crosslinker strength, crosslinker density, and fiber orientation (random vs. prealigned. We found the best-fit crosslinker parameter values using shear simulation tests in a small strain region. Using this calibrated collagen model, we simulated both shear and tensile tests in a large linear strain region for different network geometry conditions. The results suggest that network geometry is a key determinant of the mechanical properties of the fiber network. We further demonstrated how the fiber network structure and mechanics evolves with a local formation, mimicking the effect of pulling by a pseudopod during cell migration. Our computational fiber network model is a step toward a full biomechanical model of cellular behaviors in various ECM conditions.

  8. Hybrid network defense model based on fuzzy evaluation.

    Science.gov (United States)

    Cho, Ying-Chiang; Pan, Jen-Yi

    2014-01-01

    With sustained and rapid developments in the field of information technology, the issue of network security has become increasingly prominent. The theme of this study is network data security, with the test subject being a classified and sensitive network laboratory that belongs to the academic network. The analysis is based on the deficiencies and potential risks of the network's existing defense technology, characteristics of cyber attacks, and network security technologies. Subsequently, a distributed network security architecture using the technology of an intrusion prevention system is designed and implemented. In this paper, first, the overall design approach is presented. This design is used as the basis to establish a network defense model, an improvement over the traditional single-technology model that addresses the latter's inadequacies. Next, a distributed network security architecture is implemented, comprising a hybrid firewall, intrusion detection, virtual honeynet projects, and connectivity and interactivity between these three components. Finally, the proposed security system is tested. A statistical analysis of the test results verifies the feasibility and reliability of the proposed architecture. The findings of this study will potentially provide new ideas and stimuli for future designs of network security architecture.

  9. A Secure Network Coding-based Data Gathering Model and Its Protocol in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Qian Xiao

    2012-09-01

    Full Text Available To provide security for data gathering based on network coding in wireless sensor networks (WSNs, a secure network coding-based data gathering model is proposed, and a data-privacy preserving and pollution preventing (DPPaamp;PP protocol using network coding is designed. DPPaamp;PP makes use of a new proposed pollution symbol selection and pollution (PSSP scheme based on a new obfuscation idea to pollute existing symbols. Analyses of DPPaamp;PP show that it not only requires low overhead on computation and communication, but also provides high security on resisting brute-force attacks.

  10. An evolving model for the lodging-service network in a tourism destination

    Science.gov (United States)

    Hernández, Juan M.; González-Martel, Christian

    2017-09-01

    Tourism is a complex dynamic system including multiple actors which are related each other composing an evolving social network. This paper presents a growing model that explains how part of the supply components in a tourism system forms a social network. Specifically, the lodgings and services in a destination are the network nodes and a link between them appears if a representative tourist hosted in the lodging visits/consumes the service during his/her stay. The specific link between both categories are determined by a random and preferential attachment rule. The analytic results show that the long-term degree distribution of services follows a shifted power-law distribution. The numerical simulations show slight disagreements with the theoretical results in the case of the one-mode degree distribution of services, due to the low order of convergence to zero of X-motifs. The model predictions are compared with real data coming from a popular tourist destination in Gran Canaria, Spain, showing a good agreement between analytical and empirical data for the degree distribution of services. The theoretical model was validated assuming four type of perturbations in the real data.

  11. Generating finite element models of the knee: How accurately can we determine ligament attachment sites from MRI scans?

    NARCIS (Netherlands)

    Rachmat, H.H.; Janssen, D.; Zevenbergen, W.J.; Verkerke, Gijsbertus Jacob; Diercks, R.L.; Verdonschot, Nicolaas Jacobus Joseph

    2014-01-01

    In this study, we evaluated the intra- and inter-observer variability when determining the insertion and origin sites of knee ligaments on MRI scan images. We collected data of five observers with different backgrounds, who determined the ligament attachment sites in an MRI scan of a right knee of a

  12. Hydrolysis of protein and model dipeptide substrated by attached and nonattached marine Pseudomonas sp. strain NCIMB 2021

    International Nuclear Information System (INIS)

    Griffith, P.C.; Fletcher, M.

    1991-01-01

    Rates of substrate hydrolysis by nonattached bacteria and by bacteria attached to particles derived from marine diatom frustules were estimated by using two substrates, a dipeptide analog and a protein. Adsorption of the two substrates onto the particles was also evaluated. Methyl-coumarinyl-amide-leucine (MCA-leucine) was used to estimate hydrolysis of dipeptides by measuring an increase in fluorescence as MCA-leucine was hydrolyzed to leucine and the fluorochrome methylcoumarin. To examine hydrolysis of a larger molecule, was prepared a radiolabeled protein by 14 C-methylation of bovine serum albumin. The rate of protein hydrolysis in samples of particle-attached or nonattached bacteria was estimated by precipitating all nonhydrolyzed protein with cold trichloroacetic acid and then determining the trichloroacetic acid-soluble radiolabeled material, which represented methyl- 14 C-peptides and -amino acids. About 25% of the MCA-leucine adsorbed to the particles. MCA-leucine was hydrolyzed faster by nonattached than attached bacteria, which was probably related to its tendency to remain dissolved in the liquid phase. In contrast, almost 100% of the labeled protein adsorbed to the particles. Accordingly, protein was much less available to nonattached bacteria but was rapidly hydrolyzed by attached bacteria

  13. Generalized Tavis-Cummings models and quantum networks

    Science.gov (United States)

    Gorokhov, A. V.

    2018-04-01

    The properties of quantum networks based on generalized Tavis-Cummings models are theoretically investigated. We have calculated the information transfer success rate from one node to another in a simple model of a quantum network realized with two-level atoms placed in the cavities and interacting with an external laser field and cavity photons. The method of dynamical group of the Hamiltonian and technique of corresponding coherent states were used for investigation of the temporal dynamics of the two nodes model.

  14. Analysis of organizational culture with social network models

    OpenAIRE

    Titov, S.

    2015-01-01

    Organizational culture is nowadays an object of numerous scientific papers. However, only marginal part of existing research attempts to use the formal models of organizational cultures. The lack of organizational culture models significantly limits the further research in this area and restricts the application of the theory to practice of organizational culture change projects. The article consists of general views on potential application of network models and social network analysis to th...

  15. Mathematics of epidemics on networks from exact to approximate models

    CERN Document Server

    Kiss, István Z; Simon, Péter L

    2017-01-01

    This textbook provides an exciting new addition to the area of network science featuring a stronger and more methodical link of models to their mathematical origin and explains how these relate to each other with special focus on epidemic spread on networks. The content of the book is at the interface of graph theory, stochastic processes and dynamical systems. The authors set out to make a significant contribution to closing the gap between model development and the supporting mathematics. This is done by: Summarising and presenting the state-of-the-art in modeling epidemics on networks with results and readily usable models signposted throughout the book; Presenting different mathematical approaches to formulate exact and solvable models; Identifying the concrete links between approximate models and their rigorous mathematical representation; Presenting a model hierarchy and clearly highlighting the links between model assumptions and model complexity; Providing a reference source for advanced undergraduate...

  16. Emerging trends in evolving networks: Recent behaviour dominant and non-dominant model

    Science.gov (United States)

    Abbas, Khushnood; Shang, Mingsheng; Luo, Xin; Abbasi, Alireza

    2017-10-01

    Novel phenomenon receives similar attention as popular one. Therefore predicting novelty is as important as popularity. Emergence is the side effect of competition and ageing in evolving systems. Recent behaviour or recent link gain in networks plays an important role in emergence. We exploited this wisdom and came up with two models considering different scenarios and systems. Where recent behaviour dominates over total behaviour (total link gain) in the first one, and recent behaviour is as important as total behaviour for future link gain in the second one. It supposes that random walker walks on a network and can jump to any node, the probability of jumping or making a connection to other node is based on which node is recently more active or receiving more links. In our assumption, the random walker can also jump to the node which is already popular but recently not popular. We are able to predict emerging nodes which are generally suppressed under preferential attachment effect. To show the performance of our model we have conducted experiments on four real data sets namely, MovieLens, Netflix, Facebook and Arxiv High Energy Physics paper citation. For testing our model we used four information retrieval indices namely Precision, Novelty, Area Under Receiving Operating Characteristic (AUC) and Kendal's rank correlation coefficient. We have used four benchmark models for validating our proposed models. Although our model does not perform better in all the cases but, it has theoretical significance in working better for recent behaviour dominated systems.

  17. Exponential random graph models for networks with community structure.

    Science.gov (United States)

    Fronczak, Piotr; Fronczak, Agata; Bujok, Maksymilian

    2013-09-01

    Although the community structure organization is an important characteristic of real-world networks, most of the traditional network models fail to reproduce the feature. Therefore, the models are useless as benchmark graphs for testing community detection algorithms. They are also inadequate to predict various properties of real networks. With this paper we intend to fill the gap. We develop an exponential random graph approach to networks with community structure. To this end we mainly built upon the idea of blockmodels. We consider both the classical blockmodel and its degree-corrected counterpart and study many of their properties analytically. We show that in the degree-corrected blockmodel, node degrees display an interesting scaling property, which is reminiscent of what is observed in real-world fractal networks. A short description of Monte Carlo simulations of the models is also given in the hope of being useful to others working in the field.

  18. Dynamic Evolution Model Based on Social Network Services

    Science.gov (United States)

    Xiong, Xi; Gou, Zhi-Jian; Zhang, Shi-Bin; Zhao, Wen

    2013-11-01

    Based on the analysis of evolutionary characteristics of public opinion in social networking services (SNS), in the paper we propose a dynamic evolution model, in which opinions are coupled with topology. This model shows the clustering phenomenon of opinions in dynamic network evolution. The simulation results show that the model can fit the data from a social network site. The dynamic evolution of networks accelerates the opinion, separation and aggregation. The scale and the number of clusters are influenced by confidence limit and rewiring probability. Dynamic changes of the topology reduce the number of isolated nodes, while the increased confidence limit allows nodes to communicate more sufficiently. The two effects make the distribution of opinion more neutral. The dynamic evolution of networks generates central clusters with high connectivity and high betweenness, which make it difficult to control public opinions in SNS.

  19. Nonlinear adaptive inverse control via the unified model neural network

    Science.gov (United States)

    Jeng, Jin-Tsong; Lee, Tsu-Tian

    1999-03-01

    In this paper, we propose a new nonlinear adaptive inverse control via a unified model neural network. In order to overcome nonsystematic design and long training time in nonlinear adaptive inverse control, we propose the approximate transformable technique to obtain a Chebyshev Polynomials Based Unified Model (CPBUM) neural network for the feedforward/recurrent neural networks. It turns out that the proposed method can use less training time to get an inverse model. Finally, we apply this proposed method to control magnetic bearing system. The experimental results show that the proposed nonlinear adaptive inverse control architecture provides a greater flexibility and better performance in controlling magnetic bearing systems.

  20. Literature Review on Modeling Cyber Networks and Evaluating Cyber Risks.

    Energy Technology Data Exchange (ETDEWEB)

    Kelic, Andjelka; Campbell, Philip L

    2018-04-01

    The National Infrastructure Simulations and Analysis Center (NISAC) conducted a literature review on modeling cyber networks and evaluating cyber risks. The literature review explores where modeling is used in the cyber regime and ways that consequence and risk are evaluated. The relevant literature clusters in three different spaces: network security, cyber-physical, and mission assurance. In all approaches, some form of modeling is utilized at varying levels of detail, while the ability to understand consequence varies, as do interpretations of risk. This document summarizes the different literature viewpoints and explores their applicability to securing enterprise networks.

  1. A large deformation viscoelastic model for double-network hydrogels

    Science.gov (United States)

    Mao, Yunwei; Lin, Shaoting; Zhao, Xuanhe; Anand, Lallit

    2017-03-01

    We present a large deformation viscoelasticity model for recently synthesized double network hydrogels which consist of a covalently-crosslinked polyacrylamide network with long chains, and an ionically-crosslinked alginate network with short chains. Such double-network gels are highly stretchable and at the same time tough, because when stretched the crosslinks in the ionically-crosslinked alginate network rupture which results in distributed internal microdamage which dissipates a substantial amount of energy, while the configurational entropy of the covalently-crosslinked polyacrylamide network allows the gel to return to its original configuration after deformation. In addition to the large hysteresis during loading and unloading, these double network hydrogels also exhibit a substantial rate-sensitive response during loading, but exhibit almost no rate-sensitivity during unloading. These features of large hysteresis and asymmetric rate-sensitivity are quite different from the response of conventional hydrogels. We limit our attention to modeling the complex viscoelastic response of such hydrogels under isothermal conditions. Our model is restricted in the sense that we have limited our attention to conditions under which one might neglect any diffusion of the water in the hydrogel - as might occur when the gel has a uniform initial value of the concentration of water, and the mobility of the water molecules in the gel is low relative to the time scale of the mechanical deformation. We also do not attempt to model the final fracture of such double-network hydrogels.

  2. Constructive Lower Bounds on Model Complexity of Shallow Perceptron Networks

    Czech Academy of Sciences Publication Activity Database

    Kůrková, Věra

    2018-01-01

    Roč. 29, č. 7 (2018), s. 305-315 ISSN 0941-0643 R&D Projects: GA ČR GA15-18108S Institutional support: RVO:67985807 Keywords : shallow and deep networks * model complexity and sparsity * signum perceptron networks * finite mappings * variational norms * Hadamard matrices Subject RIV: IN - Informatics, Computer Science Impact factor: 2.505, year: 2016

  3. Line and lattice networks under deterministic interference models

    NARCIS (Netherlands)

    Goseling, Jasper; Gastpar, Michael; Weber, Jos H.

    Capacity bounds are compared for four different deterministic models of wireless networks, representing four different ways of handling broadcast and superposition in the physical layer. In particular, the transport capacity under a multiple unicast traffic pattern is studied for a 1-D network of

  4. Radio Channel Modelling for UAV Communication over Cellular Networks

    DEFF Research Database (Denmark)

    Amorim, Rafhael Medeiros de; Nguyen, Huan Cong; Mogensen, Preben Elgaard

    2017-01-01

    The main goal of this paper is to obtain models for path loss exponents and shadowing for the radio channel between airborne Unmanned Aerial Vehicles (UAVs) and cellular networks. In this pursuit, field measurements were conducted in live LTE networks at the 800 MHz frequency band, using a commer...

  5. Modelling aspects of distributed processing in telecommunication networks

    NARCIS (Netherlands)

    Tomasgard, A; Audestad, JA; Dye, S; Stougie, L; van der Vlerk, MH; Wallace, SW

    1998-01-01

    The purpose of this paper is to formally describe new optimization models for telecommunication networks with distributed processing. Modem distributed networks put more focus on the processing of information and less on the actual transportation of data than we are traditionally used to in

  6. Oxygen diffusion in a network model of the myocardial microcirculation

    NARCIS (Netherlands)

    Wieringa, P. A.; Stassen, H. G.; van Kan, J. J.; Spaan, J. A.

    1993-01-01

    Oxygen supply was studied in a three-dimensional capillary network model of the myocardial microcirculation. Capillary networks were generated using one common strategy to locate the capillary branchings and segments, arterioles and venules. Flow paths developed with different capillary flow

  7. Modelling flow dynamics in water distribution networks using ...

    African Journals Online (AJOL)

    One such approach is the Artificial Neural Networks (ANNs) technique. The advantage of ANNs is that they are robust and can be used to model complex linear and non-linear systems without making implicit assumptions. ANNs can be trained to forecast flow dynamics in a water distribution network. Such flow dynamics ...

  8. Modelling the permeability of polymers: a neural network approach

    NARCIS (Netherlands)

    Wessling, Matthias; Mulder, M.H.V.; Bos, A.; Bos, A.; van der Linden, M.K.T.; Bos, M.; van der Linden, W.E.

    1994-01-01

    In this short communication, the prediction of the permeability of carbon dioxide through different polymers using a neural network is studied. A neural network is a numeric-mathematical construction that can model complex non-linear relationships. Here it is used to correlate the IR spectrum of a

  9. Towards a Social Networks Model for Online Learning & Performance

    Science.gov (United States)

    Chung, Kon Shing Kenneth; Paredes, Walter Christian

    2015-01-01

    In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…

  10. Capacity allocation in wireless communication networks - models and analyses

    NARCIS (Netherlands)

    Litjens, Remco

    2003-01-01

    This monograph has concentrated on capacity allocation in cellular and Wireless Local Area Networks, primarily with a network operator’s perspective. In the introduc- tory chapter, a reference model has been proposed for the extensive suite of capacity allocation mechanisms that can be applied at

  11. DAILY RAINFALL-RUNOFF MODELLING BY NEURAL NETWORKS ...

    African Journals Online (AJOL)

    K. Benzineb, M. Remaoun

    2016-09-01

    Sep 1, 2016 ... The hydrologic behaviour modelling of w. Journal of ... i Ouahrane's basin from rainfall-runoff relation which is non-linea networks ... will allow checking efficiency of formal neural networks for flows simulation in semi-arid zone.

  12. Energy Model of Networks-on-Chip and a Bus

    NARCIS (Netherlands)

    Wolkotte, P.T.; Smit, Gerardus Johannes Maria; Kavaldjiev, N.K.; Becker, Jens E.; Becker, Jürgen; Nurmi, J.; Takala, J.; Hamalainen, T.D.

    2005-01-01

    A Network-on-Chip (NoC) is an energy-efficient onchip communication architecture for Multi-Processor Systemon-Chip (MPSoC) architectures. In earlier papers we proposed two Network-on-Chip architectures based on packet-switching and circuit-switching. In this paper we derive an energy model for both

  13. modeling and optimization of an electric power distribution network

    African Journals Online (AJOL)

    user

    EDNEPP) was solved by a mixed binary integer programming (MBIP) formulation of the network, where the steady-state operation of the network was modelled with non-linear mathematical expressions. The non-linear terms are linearized, using ...

  14. Agent Based Modeling on Organizational Dynamics of Terrorist Network

    Directory of Open Access Journals (Sweden)

    Bo Li

    2015-01-01

    Full Text Available Modeling organizational dynamics of terrorist network is a critical issue in computational analysis of terrorism research. The first step for effective counterterrorism and strategic intervention is to investigate how the terrorists operate with the relational network and what affects the performance. In this paper, we investigate the organizational dynamics by employing a computational experimentation methodology. The hierarchical cellular network model and the organizational dynamics model are developed for modeling the hybrid relational structure and complex operational processes, respectively. To intuitively elucidate this method, the agent based modeling is used to simulate the terrorist network and test the performance in diverse scenarios. Based on the experimental results, we show how the changes of operational environments affect the development of terrorist organization in terms of its recovery and capacity to perform future tasks. The potential strategies are also discussed, which can be used to restrain the activities of terrorists.

  15. System-level Modeling of Wireless Integrated Sensor Networks

    DEFF Research Database (Denmark)

    Virk, Kashif M.; Hansen, Knud; Madsen, Jan

    2005-01-01

    Wireless integrated sensor networks have emerged as a promising infrastructure for a new generation of monitoring and tracking applications. In order to efficiently utilize the extremely limited resources of wireless sensor nodes, accurate modeling of the key aspects of wireless sensor networks...... is necessary so that system-level design decisions can be made about the hardware and the software (applications and real-time operating system) architecture of sensor nodes. In this paper, we present a SystemC-based abstract modeling framework that enables system-level modeling of sensor network behavior...... by modeling the applications, real-time operating system, sensors, processor, and radio transceiver at the sensor node level and environmental phenomena, including radio signal propagation, at the sensor network level. We demonstrate the potential of our modeling framework by simulating and analyzing a small...

  16. A continuous-time control model on production planning network ...

    African Journals Online (AJOL)

    A continuous-time control model on production planning network. DEA Omorogbe, MIU Okunsebor. Abstract. In this paper, we give a slightly detailed review of Graves and Hollywood model on constant inventory tactical planning model for a job shop. The limitations of this model are pointed out and a continuous time ...

  17. Non-consensus Opinion Models on Complex Networks

    Science.gov (United States)

    Li, Qian; Braunstein, Lidia A.; Wang, Huijuan; Shao, Jia; Stanley, H. Eugene; Havlin, Shlomo

    2013-04-01

    Social dynamic opinion models have been widely studied to understand how interactions among individuals cause opinions to evolve. Most opinion models that utilize spin interaction models usually produce a consensus steady state in which only one opinion exists. Because in reality different opinions usually coexist, we focus on non-consensus opinion models in which above a certain threshold two opinions coexist in a stable relationship. We revisit and extend the non-consensus opinion (NCO) model introduced by Shao et al. (Phys. Rev. Lett. 103:01870, 2009). The NCO model in random networks displays a second order phase transition that belongs to regular mean field percolation and is characterized by the appearance (above a certain threshold) of a large spanning cluster of the minority opinion. We generalize the NCO model by adding a weight factor W to each individual's original opinion when determining their future opinion (NCO W model). We find that as W increases the minority opinion holders tend to form stable clusters with a smaller initial minority fraction than in the NCO model. We also revisit another non-consensus opinion model based on the NCO model, the inflexible contrarian opinion (ICO) model (Li et al. in Phys. Rev. E 84:066101, 2011), which introduces inflexible contrarians to model the competition between two opinions in a steady state. Inflexible contrarians are individuals that never change their original opinion but may influence the opinions of others. To place the inflexible contrarians in the ICO model we use two different strategies, random placement and one in which high-degree nodes are targeted. The inflexible contrarians effectively decrease the size of the largest rival-opinion cluster in both strategies, but the effect is more pronounced under the targeted method. All of the above models have previously been explored in terms of a single network, but human communities are usually interconnected, not isolated. Because opinions propagate not

  18. Linear control theory for gene network modeling.

    Directory of Open Access Journals (Sweden)

    Yong-Jun Shin

    Full Text Available Systems biology is an interdisciplinary field that aims at understanding complex interactions in cells. Here we demonstrate that linear control theory can provide valuable insight and practical tools for the characterization of complex biological networks. We provide the foundation for such analyses through the study of several case studies including cascade and parallel forms, feedback and feedforward loops. We reproduce experimental results and provide rational analysis of the observed behavior. We demonstrate that methods such as the transfer function (frequency domain and linear state-space (time domain can be used to predict reliably the properties and transient behavior of complex network topologies and point to specific design strategies for synthetic networks.

  19. Modelling, synthesis and analysis of biorefinery networks

    DEFF Research Database (Denmark)

    Bertran, Maria-Ona

    for the conversion of biomass into chemicals, fuels and energy, because they have the potential to maximize biomass value while reducing emissions. The design of biorefinery networks is a complex decisionmaking problem that involves the selection of feedstocks, processing technologies, products, geographical...... locations, and operating conditions, among others. Unlike petroleumbased processing networks, biorefineries rely on feedstocks that are nonhomogeneous across geographical areas in terms of their availability, type and properties. For this reason, the performance of biorefinery networks depends...... of reactions to convert available biomassbased feedstocks into desired products, the selection of processing routes and technologies from a large set of alternatives, or the generation of hybrid technologies through process intensification. Systematic process synthesis and design methods have been developed...

  20. Phase-synchronisation in continuous flow models of production networks

    Science.gov (United States)

    Scholz-Reiter, Bernd; Tervo, Jan Topi; Freitag, Michael

    2006-04-01

    To improve their position at the market, many companies concentrate on their core competences and hence cooperate with suppliers and distributors. Thus, between many independent companies strong linkages develop and production and logistics networks emerge. These networks are characterised by permanently increasing complexity, and are nowadays forced to adapt to dynamically changing markets. This factor complicates an enterprise-spreading production planning and control enormously. Therefore, a continuous flow model for production networks will be derived regarding these special logistic problems. Furthermore, phase-synchronisation effects will be presented and their dependencies to the set of network parameters will be investigated.

  1. Hybrid modeling and empirical analysis of automobile supply chain network

    Science.gov (United States)

    Sun, Jun-yan; Tang, Jian-ming; Fu, Wei-ping; Wu, Bing-ying

    2017-05-01

    Based on the connection mechanism of nodes which automatically select upstream and downstream agents, a simulation model for dynamic evolutionary process of consumer-driven automobile supply chain is established by integrating ABM and discrete modeling in the GIS-based map. Firstly, the rationality is proved by analyzing the consistency of sales and changes in various agent parameters between the simulation model and a real automobile supply chain. Second, through complex network theory, hierarchical structures of the model and relationships of networks at different levels are analyzed to calculate various characteristic parameters such as mean distance, mean clustering coefficients, and degree distributions. By doing so, it verifies that the model is a typical scale-free network and small-world network. Finally, the motion law of this model is analyzed from the perspective of complex self-adaptive systems. The chaotic state of the simulation system is verified, which suggests that this system has typical nonlinear characteristics. This model not only macroscopically illustrates the dynamic evolution of complex networks of automobile supply chain but also microcosmically reflects the business process of each agent. Moreover, the model construction and simulation of the system by means of combining CAS theory and complex networks supplies a novel method for supply chain analysis, as well as theory bases and experience for supply chain analysis of auto companies.

  2. A DUAL NETWORK MODEL OF INTERLOCKING DIRECTORATES

    Directory of Open Access Journals (Sweden)

    Humphry Hung

    2003-01-01

    Full Text Available The article proposes an integrative framework for the study of interlocking directorates by using an approach that encompasses the concepts of multiple networks and resource endowment. This serves to integrate the traditional views of interorganizational linkages and intra-class cohesion. Through appropriate strategic analysis of relevant resource endowment of internal environment and external networks of organizations and corporate elites, this article argues that the selection of directors, if used effectively, can be adopted as a strategic device to enhance the corporation's overall performance.

  3. A Simplified Network Model for Travel Time Reliability Analysis in a Road Network

    Directory of Open Access Journals (Sweden)

    Kenetsu Uchida

    2017-01-01

    Full Text Available This paper proposes a simplified network model which analyzes travel time reliability in a road network. A risk-averse driver is assumed in the simplified model. The risk-averse driver chooses a path by taking into account both a path travel time variance and a mean path travel time. The uncertainty addressed in this model is that of traffic flows (i.e., stochastic demand flows. In the simplified network model, the path travel time variance is not calculated by considering all travel time covariance between two links in the network. The path travel time variance is calculated by considering all travel time covariance between two adjacent links in the network. Numerical experiments are carried out to illustrate the applicability and validity of the proposed model. The experiments introduce the path choice behavior of a risk-neutral driver and several types of risk-averse drivers. It is shown that the mean link flows calculated by introducing the risk-neutral driver differ as a whole from those calculated by introducing several types of risk-averse drivers. It is also shown that the mean link flows calculated by the simplified network model are almost the same as the flows calculated by using the exact path travel time variance.

  4. Copula-based modeling of degree-correlated networks

    International Nuclear Information System (INIS)

    Raschke, Mathias; Schläpfer, Markus; Trantopoulos, Konstantinos

    2014-01-01

    Dynamical processes on complex networks such as information exchange, innovation diffusion, cascades in financial networks or epidemic spreading are highly affected by their underlying topologies as characterized by, for instance, degree–degree correlations. Here, we introduce the concept of copulas in order to generate random networks with an arbitrary degree distribution and a rich a priori degree–degree correlation (or ‘association’) structure. The accuracy of the proposed formalism and corresponding algorithm is numerically confirmed, while the method is tested on a real-world network of yeast protein–protein interactions. The derived network ensembles can be systematically deployed as proper null models, in order to unfold the complex interplay between the topology of real-world networks and the dynamics on top of them. (paper)

  5. neural network based model o work based model of an industrial oil

    African Journals Online (AJOL)

    eobe

    technique. g, Neural Network Model, Regression, Mean Square Error, PID controller. ... during the training processes. An additio ... used to carry out simulation studies of the mode .... A two-layer feed-forward neural network with Matlab.

  6. A Gaussian graphical model approach to climate networks

    Energy Technology Data Exchange (ETDEWEB)

    Zerenner, Tanja, E-mail: tanjaz@uni-bonn.de [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Friederichs, Petra; Hense, Andreas [Meteorological Institute, University of Bonn, Auf dem Hügel 20, 53121 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany); Lehnertz, Klaus [Department of Epileptology, University of Bonn, Sigmund-Freud-Straße 25, 53105 Bonn (Germany); Helmholtz Institute for Radiation and Nuclear Physics, University of Bonn, Nussallee 14-16, 53115 Bonn (Germany); Interdisciplinary Center for Complex Systems, University of Bonn, Brühler Straße 7, 53119 Bonn (Germany)

    2014-06-15

    Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately.

  7. A Gaussian graphical model approach to climate networks

    International Nuclear Information System (INIS)

    Zerenner, Tanja; Friederichs, Petra; Hense, Andreas; Lehnertz, Klaus

    2014-01-01

    Distinguishing between direct and indirect connections is essential when interpreting network structures in terms of dynamical interactions and stability. When constructing networks from climate data the nodes are usually defined on a spatial grid. The edges are usually derived from a bivariate dependency measure, such as Pearson correlation coefficients or mutual information. Thus, the edges indistinguishably represent direct and indirect dependencies. Interpreting climate data fields as realizations of Gaussian Random Fields (GRFs), we have constructed networks according to the Gaussian Graphical Model (GGM) approach. In contrast to the widely used method, the edges of GGM networks are based on partial correlations denoting direct dependencies. Furthermore, GRFs can be represented not only on points in space, but also by expansion coefficients of orthogonal basis functions, such as spherical harmonics. This leads to a modified definition of network nodes and edges in spectral space, which is motivated from an atmospheric dynamics perspective. We construct and analyze networks from climate data in grid point space as well as in spectral space, and derive the edges from both Pearson and partial correlations. Network characteristics, such as mean degree, average shortest path length, and clustering coefficient, reveal that the networks posses an ordered and strongly locally interconnected structure rather than small-world properties. Despite this, the network structures differ strongly depending on the construction method. Straightforward approaches to infer networks from climate data while not regarding any physical processes may contain too strong simplifications to describe the dynamics of the climate system appropriately

  8. Quebec mental health services networks: models and implementation

    Directory of Open Access Journals (Sweden)

    Marie-Josée Fleury

    2005-06-01

    Full Text Available Purpose: In the transformation of health care systems, the introduction of integrated service networks is considered to be one of the main solutions for enhancing efficiency. In the last few years, a wealth of literature has emerged on the topic of services integration. However, the question of how integrated service networks should be modelled to suit different implementation contexts has barely been touched. To fill that gap, this article presents four models for the organization of mental health integrated networks. Data sources: The proposed models are drawn from three recently published studies on mental health integrated services in the province of Quebec (Canada with the author as principal investigator. Description: Following an explanation of the concept of integrated service network and a description of the Quebec context for mental health networks, the models, applicable in all settings: rural, urban or semi-urban, and metropolitan, and summarized in four figures, are presented. Discussion and conclusion: To apply the models successfully, the necessity of rallying all the actors of a system, from the strategic, tactical and operational levels, according to the type of integration involved: functional/administrative, clinical and physician-system is highlighted. The importance of formalizing activities among organizations and actors in a network and reinforcing the governing mechanisms at the local level is also underlined. Finally, a number of integration strategies and key conditions of success to operationalize integrated service networks are suggested.

  9. A ternary logic model for recurrent neuromime networks with delay.

    Science.gov (United States)

    Hangartner, R D; Cull, P

    1995-07-01

    In contrast to popular recurrent artificial neural network (RANN) models, biological neural networks have unsymmetric structures and incorporate significant delays as a result of axonal propagation. Consequently, biologically inspired neural network models are more accurately described by nonlinear differential-delay equations rather than nonlinear ordinary differential equations (ODEs), and the standard techniques for studying the dynamics of RANNs are wholly inadequate for these models. This paper develops a ternary-logic based method for analyzing these networks. Key to the technique is the realization that a nonzero delay produces a bounded stability region. This result significantly simplifies the construction of sufficient conditions for characterizing the network equilibria. If the network gain is large enough, each equilibrium can be classified as either asymptotically stable or unstable. To illustrate the analysis technique, the swim central pattern generator (CPG) of the sea slug Tritonia diomedea is examined. For wide range of reasonable parameter values, the ternary analysis shows that none of the network equilibria are stable, and thus the network must oscillate. The results show that complex synaptic dynamics are not necessary for pattern generation.

  10. Business Process Modeling Languages Supporting Collaborative Networks

    NARCIS (Netherlands)

    Soleimani Malekan, H.; Afsarmanesh, H.; Hammoudi, S.; Maciaszek, L.A.; Cordeiro, J.; Dietz, J.L.G.

    2013-01-01

    Formalizing the definition of Business Processes (BPs) performed within each enterprise is fundamental for effective deployment of their competencies and capabilities within Collaborative Networks (CN). In our approach, every enterprise in the CN is represented by its set of BPs, so that other

  11. Message Integrity Model for Wireless Sensor Networks

    Science.gov (United States)

    Qleibo, Haider W.

    2009-01-01

    WSNs are susceptible to a variety of attacks. These attacks vary in the way they are performed and executed; they include but not limited to node capture, physical tampering, denial of service, and message alteration. It is of paramount importance to protect gathered data by WSNs and defend the network against illegal access and malicious…

  12. Modeling urbanization patterns with generative adversarial networks

    OpenAIRE

    Albert, Adrian; Strano, Emanuele; Kaur, Jasleen; Gonzalez, Marta

    2018-01-01

    In this study we propose a new method to simulate hyper-realistic urban patterns using Generative Adversarial Networks trained with a global urban land-use inventory. We generated a synthetic urban "universe" that qualitatively reproduces the complex spatial organization observed in global urban patterns, while being able to quantitatively recover certain key high-level urban spatial metrics.

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

    International Nuclear Information System (INIS)

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

    2009-01-01

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

  14. SCYNet. Testing supersymmetric models at the LHC with neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Bechtle, Philip; Belkner, Sebastian; Hamer, Matthias [Universitaet Bonn, Bonn (Germany); Dercks, Daniel [Universitaet Hamburg, Hamburg (Germany); Keller, Tim; Kraemer, Michael; Sarrazin, Bjoern; Schuette-Engel, Jan; Tattersall, Jamie [RWTH Aachen University, Institute for Theoretical Particle Physics and Cosmology, Aachen (Germany)

    2017-10-15

    SCYNet (SUSY Calculating Yield Net) is a tool for testing supersymmetric models against LHC data. It uses neural network regression for a fast evaluation of the profile likelihood ratio. Two neural network approaches have been developed: one network has been trained using the parameters of the 11-dimensional phenomenological Minimal Supersymmetric Standard Model (pMSSM-11) as an input and evaluates the corresponding profile likelihood ratio within milliseconds. It can thus be used in global pMSSM-11 fits without time penalty. In the second approach, the neural network has been trained using model-independent signature-related objects, such as energies and particle multiplicities, which were estimated from the parameters of a given new physics model. (orig.)

  15. Numeral eddy current sensor modelling based on genetic neural network

    International Nuclear Information System (INIS)

    Yu Along

    2008-01-01

    This paper presents a method used to the numeral eddy current sensor modelling based on the genetic neural network to settle its nonlinear problem. The principle and algorithms of genetic neural network are introduced. In this method, the nonlinear model parameters of the numeral eddy current sensor are optimized by genetic neural network (GNN) according to measurement data. So the method remains both the global searching ability of genetic algorithm and the good local searching ability of neural network. The nonlinear model has the advantages of strong robustness, on-line modelling and high precision. The maximum nonlinearity error can be reduced to 0.037% by using GNN. However, the maximum nonlinearity error is 0.075% using the least square method

  16. Modelling and predicting biogeographical patterns in river networks

    Directory of Open Access Journals (Sweden)

    Sabela Lois

    2016-04-01

    Full Text Available Statistical analysis and interpretation of biogeographical phenomena in rivers is now possible using a spatially explicit modelling framework, which has seen significant developments in the past decade. I used this approach to identify a spatial extent (geostatistical range in which the abundance of the parasitic freshwater pearl mussel (Margaritifera margaritifera L. is spatially autocorrelated in river networks. I show that biomass and abundance of host fish are a likely explanation for the autocorrelation in mussel abundance within a 15-km spatial extent. The application of universal kriging with the empirical model enabled precise prediction of mussel abundance within segments of river networks, something that has the potential to inform conservation biogeography. Although I used a variety of modelling approaches in my thesis, I focus here on the details of this relatively new spatial stream network model, thus advancing the study of biogeographical patterns in river networks.

  17. Particle swarm optimization of a neural network model in a ...

    Indian Academy of Sciences (India)

    . Since tool life is critically affected by the tool wear, accurate prediction of this wear ... In their work, they established an improvement in the quality ... objective optimization of hard turning using neural network modelling and swarm intelligence ...

  18. Modelling the self-organization and collapse of complex networks

    Indian Academy of Sciences (India)

    Modelling the self-organization and collapse of complex networks. Sanjay Jain Department of Physics and Astrophysics, University of Delhi Jawaharlal Nehru Centre for Advanced Scientific Research, Bangalore Santa Fe Institute, Santa Fe, New Mexico.

  19. Numerical Analysis of Modeling Based on Improved Elman Neural Network

    Directory of Open Access Journals (Sweden)

    Shao Jie

    2014-01-01

    Full Text Available A modeling based on the improved Elman neural network (IENN is proposed to analyze the nonlinear circuits with the memory effect. The hidden layer neurons are activated by a group of Chebyshev orthogonal basis functions instead of sigmoid functions in this model. The error curves of the sum of squared error (SSE varying with the number of hidden neurons and the iteration step are studied to determine the number of the hidden layer neurons. Simulation results of the half-bridge class-D power amplifier (CDPA with two-tone signal and broadband signals as input have shown that the proposed behavioral modeling can reconstruct the system of CDPAs accurately and depict the memory effect of CDPAs well. Compared with Volterra-Laguerre (VL model, Chebyshev neural network (CNN model, and basic Elman neural network (BENN model, the proposed model has better performance.

  20. Feed forward neural networks modeling for K-P interactions

    International Nuclear Information System (INIS)

    El-Bakry, M.Y.

    2003-01-01

    Artificial intelligence techniques involving neural networks became vital modeling tools where model dynamics are difficult to track with conventional techniques. The paper make use of the feed forward neural networks (FFNN) to model the charged multiplicity distribution of K-P interactions at high energies. The FFNN was trained using experimental data for the multiplicity distributions at different lab momenta. Results of the FFNN model were compared to that generated using the parton two fireball model and the experimental data. The proposed FFNN model results showed good fitting to the experimental data. The neural network model performance was also tested at non-trained space and was found to be in good agreement with the experimental data