Influence of Deterministic Attachments for Large Unifying Hybrid Network Model
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
Large unifying hybrid network model (LUHPM) introduced the deterministic mixing ratio fd on the basis of the harmonious unification hybrid preferential model, to describe the influence of deterministic attachment to the network topology characteristics,
Unified Model for Generation Complex Networks with Utility Preferential Attachment
Institute of Scientific and Technical Information of China (English)
WU Jian-Jun; GAO Zi-You; SUN Hui-Jun
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 ofthis new network are given.
Transcriptional Network growing Models using Motif-based Preferential Attachment
Directory of Open Access Journals (Sweden)
Ahmed Farouk Abdelzaher
2015-10-01
Full Text Available Understanding relationships between architectural properties of gene-regulatory networks (GRNs has been one of the major goals in systems biology and bioinformatics, as it can provide insights into, e.g., disease dynamics and drug development. Such GRNs are characterized by their scale-free degree distributions and existence of network motifs--i.e., small-node subgraphs that occur more abundantly in GRNs than expected from chance alone. Because these transcriptional modules represent ``building blocks'' of complex networks and exhibit a wide range of functional and dynamical properties, they may contribute to the remarkable robustness and dynamical stability associated with the whole of GRNs. Here we developed network-construction models to better understand this relationship, which produce randomized GRNs by using transcriptional motifs as the fundamental growth unit in contrast to other methods that construct similar networks on a node-by-node basis. Because this model produces networks with a prescribed lower bound on the number of choice transcriptional motifs (e.g., downlinks, feed-forward loops, its fidelity to the motif distributions observed in model organisms represents an improvement over existing methods, which we validated by contrasting their resultant motif and degree distributions against existing network-growth models and data from the model organism of the bacterium Escherichia coli. These models may therefore serve as novel testbeds for further elucidating relationships between the topology of transcriptional motifs and network-wide dynamical properties.
Transcriptional Network Growing Models Using Motif-Based Preferential Attachment.
Abdelzaher, Ahmed F; Al-Musawi, Ahmad F; Ghosh, Preetam; Mayo, Michael L; Perkins, Edward J
2015-01-01
Understanding relationships between architectural properties of gene-regulatory networks (GRNs) has been one of the major goals in systems biology and bioinformatics, as it can provide insights into, e.g., disease dynamics and drug development. Such GRNs are characterized by their scale-free degree distributions and existence of network motifs - i.e., small-node subgraphs that occur more abundantly in GRNs than expected from chance alone. Because these transcriptional modules represent "building blocks" of complex networks and exhibit a wide range of functional and dynamical properties, they may contribute to the remarkable robustness and dynamical stability associated with the whole of GRNs. Here, we developed network-construction models to better understand this relationship, which produce randomized GRNs by using transcriptional motifs as the fundamental growth unit in contrast to other methods that construct similar networks on a node-by-node basis. Because this model produces networks with a prescribed lower bound on the number of choice transcriptional motifs (e.g., downlinks, feed-forward loops), its fidelity to the motif distributions observed in model organisms represents an improvement over existing methods, which we validated by contrasting their resultant motif and degree distributions against existing network-growth models and data from the model organism of the bacterium Escherichia coli. These models may therefore serve as novel testbeds for further elucidating relationships between the topology of transcriptional motifs and network-wide dynamical properties.
Network growth models: A behavioural basis for attachment proportional to fitness
Bell, Michael; Perera, Supun; Piraveenan, Mahendrarajah; Bliemer, Michiel; Latty, Tanya; Reid, Chris
2017-01-01
Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relative merits of such models. This paper analyses an evolutionary mechanism that would give rise to a fitness-based attachment process. In particular, it is proven by analytical and numerical methods that in homogeneous networks, the minimisation of maximum exposure to node unfitness leads to attachment probabilities that are proportional to node fitness. This result is then extended to heterogeneous networks, with supply chain networks being used as an example. PMID:28205599
Coexistence in preferential attachment networks
Antunović, Tonći; Racz, Miklos Z
2013-01-01
Competition in markets is ubiquitous: cell-phone providers, computer manufacturers, and sport gear brands all vie for customers. Though several coexisting competitors are often observed in empirical data, many current theoretical models of competition on small-world networks predict a single winner taking over the majority of the network. We introduce a new model of product adoption that focuses on word-of-mouth recommendations to provide an explanation for this coexistence of competitors. The key property of our model is that customer choices evolve simultaneously with the network of customers. When a new node joins the network, it chooses neighbors according to preferential attachment, and then chooses its type based on the number of initial neighbors of each type. This can model a new cell-phone user choosing a cell-phone provider, a new student choosing a laptop, or a new athletic team member choosing a gear provider. We provide a detailed analysis of the new model; in particular, we determine the possibl...
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...... and competitive mentality towards others within SNSs. We further construct a theoretical model of members’ communal attachments within SNSs that is then empirically validated via an online survey of 787 active members of SNSs. Empirical findings suggest that members’ communal attachments play an instrumental role...
Complex cooperative networks from evolutionary preferential attachment.
Directory of Open Access Journals (Sweden)
Julia Poncela
Full Text Available In spite of its relevance to the origin of complex networks, the interplay between form and function and its role during network formation remains largely unexplored. While recent studies introduce dynamics by considering rewiring processes of a pre-existent network, we study network growth and formation by proposing an evolutionary preferential attachment model, its main feature being that the capacity of a node to attract new links depends on a dynamical variable governed in turn by the node interactions. As a specific example, we focus on the problem of the emergence of cooperation by analyzing the formation of a social network with interactions given by the Prisoner's Dilemma. The resulting networks show many features of real systems, such as scale-free degree distributions, cooperative behavior and hierarchical clustering. Interestingly, results such as the cooperators being located mostly on nodes of intermediate degree are very different from the observations of cooperative behavior on static networks. The evolutionary preferential attachment mechanism points to an evolutionary origin of scale-free networks and may help understand similar feedback problems in the dynamics of complex networks by appropriately choosing the game describing the interaction of nodes.
Characteristics of Preferentially Attached Network Grown from Small World
Lee, Seungyoung
2015-01-01
We introduce a model for a preferentially attached network which has grown from a small world network. Here, the average path length and the clustering coefficient are estimated, and the topological properties of modeled networks are compared as the initial conditions are changed. As a result, it is shown that the topological properties of the initial network remain even after the network growth. However, the vulnerability of each to preferentially attached nodes being added is not the same. It is found that the average path length rapidly decreases as the ratio of preferentially attached nodes increases and that the characteristics of the initial network can be easily disappeared. On the other hand, the clustering coefficient of the initial network slowly decreases with the ratio of preferentially attached nodes and its clustering characteristic remains much longer.
Network Evolution by Relevance and Importance Preferential Attachment
Zhang, Weituo
2014-01-01
Relevance and importance are the main factors when humans build network connections. We propose an evolutionary network model based on preferential attachment(PA) considering these factors. We analyze and compute several important features of the network class generated by this algorithm including scale free degree distribution, high clustering coefficient, small world property and core-periphery structure. We then compare this model with other network models and empirical data such as inter-city road transportation and air traffic networks.
Conflicting attachment and the growth of bipartite networks
Yin, Chung; Weitz, Joshua S
2015-01-01
Simple growth mechanisms have been proposed to explain the emergence of seemingly universal network structures. The widely-studied model of preferential attachment assumes that new nodes are more likely to connect to highly connected nodes. Preferential attachment explains the emergence of scale-free degree distributions within complex networks. Yet, it is incompatible with many network systems, particularly bipartite systems in which two distinct types of agents interact. For example, the addition of new links in a host-parasite system corresponds to the infection of hosts by parasites. Increasing connectivity is beneficial to a parasite and detrimental to a host. Therefore, the overall network connectivity is subject to conflicting pressures. Here, we propose a stochastic network growth model of conflicting attachment, inspired by a particular kind of parasite-host interactions: that of viruses interacting with microbial hosts. The mechanism of network growth includes conflicting preferences to network dens...
Link Prediction in Complex Networks by Multi Degree Preferential-Attachment Indices
Hu, Ke; Yang, Wanchun; Xu, Xiaoke; Tang, Yi
2012-01-01
In principle, the rules of links formation of a network model can be considered as a kind of link prediction algorithm. By revisiting the preferential attachment mechanism for generating a scale-free network, here we propose a class of preferential attachment indices which are different from the previous one. Traditionally, the preferential attachment index is defined by the product of the related nodes degrees, while the new indices will define the similarity score of a pair of nodes by either the maximum in the two nodes degrees or the summarization of their degrees. Extensive experiments are carried out on fourteen real-world networks. Compared with the traditional preferential attachment index, the new ones, especially the degree-summarization similarity index, can provide more accurate prediction on most of the networks. Due to the improved prediction accuracy and low computational complexity, these proposed preferential attachment indices may be of help to provide an instruction for mining unknown links...
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
Cascades with coupled map lattices in preferential attachment community networks
Institute of Scientific and Technical Information of China (English)
Cui Di; Gao Zi-You; Zhao Xiao-Mei
2008-01-01
In this paper,cascading failure is studied by coupled map lattice (CML) methods in preferential attachment community networks.It is found that external perturbation R is increasing with modularity Q growing by simulation.In particular,the large modularity Q can hold off the cascading failure dynamic process in community networks.Furthermore,different attack strategies also greatly affect the cascading failure dynamic process. It is particularly significant to control cascading failure process in real community networks.
Institute of Scientific and Technical Information of China (English)
LIU Xuan; JIA Hui-bo; CHENG Ming
2006-01-01
A new analytical method for improving the performance of a network attached optical jukebox is presented by means of artificial neural networks. Through analyzing operation (request) process in this system,the mathematics model and algorithm are built for this storage system,and then a classified method based on artificial neural networks for this system is proposed. Simulation results testified the feasibility and validity of the proposed method that it could overcome the drawbacks of the frequent I/O operation and provide an effective way for using the Network Attached Optical Jukebox.
Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion
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
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
Power-law weighted networks from local attachments
Moriano, P
2011-01-01
Large networks arise by the gradual addition of nodes attaching to an existing and evolving network component. There are a wide class of attachment strategies which lead to distinct structural features in growing networks. This paper introduces a mechanism for constructing, through a process of distributed decision-making, substrates for the study of collective dynamics on power-law weighted networks with both a desired scaling exponent and a fixed clustering coefficient. The analytical results show that the connectivity distribution converges to the scaling behavior often found in social and engineering systems. To illustrate the approach of the proposed framework we generate network substrates that resemble the empirical citation distributions of (i) publications indexed by the Institute for Scientific Information from 1981 to 1997; (ii) patents granted by the U.S. Patent and Trademark Office from 1975 to 1999; and (iii) opinions written by the Supreme Court and the cases they cite from 1754 to 2002.
Mediated attachment as a mechanism for growth of complex networks
Shekatkar, Snehal M
2014-01-01
Connection topologies of many networked systems like human brain, biological cell, world wide web, power grids, human society and ecological food webs markedly deviate from that of completely random networks indicating the presence of organizing principles behind their evolution. The five important features that characterize such networks are scale-free topology, small average path length, high clustering, hierarchical community structure and assortative mixing. Till now the generic mechanisms underlying the existence of these properties are not well understood. Here we show that potentially a single mechanism, which we call "mediated attachment", where two nodes get connected through a mediator or common neighbor, could be responsible for the emergence of all important properties of real networks. The mediated attachment naturally unifies scale-free topology, high clustering, small world nature, hierarchical community structure and dissortative nature of networks. Further, with additional mixing by age, this...
Dismissing Attachment Characteristics Dynamically Modulate Brain Networks Subserving Social Aversion
Krause, Anna Linda; Borchardt, Viola; Li, Meng; van Tol, Marie-José; Demenescu, L.R.; 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 reson
Assortativity in generalized preferential attachment models
Krot, Alexander
2016-01-01
In this paper, we analyze assortativity of preferential attachment models. We deal with a wide class of preferential attachment models (PA-class). It was previously shown that the degree distribution in all models of the PA-class follows a power law. Also, the global and the average local clustering coefficients were analyzed. We expand these results by analyzing the assortativity property of the PA-class of models. Namely, we analyze the behavior of $d_{nn}(d)$ which is the average degree of a neighbor of a vertex of degree $d$.
Network growth with preferential attachment and without “rich get richer” mechanism
Lachgar, A.; Achahbar, A.
2016-08-01
We propose a simple preferential attachment model of growing network using the complementary probability of Barabási-Albert (BA) model, i.e. Π(ki)∝1-ki∑jkj. In this network, new nodes are preferentially attached to not well connected nodes. Numerical simulations, in perfect agreement with the master equation solution, give an exponential degree distribution. This suggests that the power law degree distribution is a consequence of preferential attachment probability together with “rich get richer” phenomena. We also calculate the average degree of a target node at time t() and its fluctuations, to have a better view of the microscopic evolution of the network, and we also compare the results with BA model.
Reactive attachment disorder--a theoretical model beyond attachment.
Minnis, Helen; Marwick, Helen; Arthur, Julie; McLaughlin, Alexis
2006-09-01
Despite its importance in public health, reactive attachment disorder (RAD) is an under-researched and little used clinical category. Abnormalities of social relatedness have long been documented in children who have been abused, neglected or institutionalised, but there have been more recent efforts to define these behaviours within the psychiatric nosology. There has been an implicit assumption that the central deficit in RAD is in the attachment system, but this has caused controversy and may have blocked research. We propose that RAD is better construed within the framework of intersubjectivity, which has a central role in the development of core brain and social functions and may also have had an important role in the evolution of a key human characteristic-complex social functioning. This broader framework may potentially explain apparently diverse symptoms such as indiscriminate friendliness and negative or unpredictable reunion responses. Finally, we suggest that a change of name may be useful in progressing the field, but accept that this may be difficult until there is better agreement in the clinical and scientific communities about the core features and aetiology of this disorder.
Assortativity and leadership emerge from anti-preferential attachment in heterogeneous networks
Sendiña-Nadal, I.; Danziger, M. M.; Wang, Z.; Havlin, S.; Boccaletti, S.
2016-02-01
Real-world networks have distinct topologies, with marked deviations from purely random networks. Many of them exhibit degree-assortativity, with nodes of similar degree more likely to link to one another. Though microscopic mechanisms have been suggested for the emergence of other topological features, assortativity has proven elusive. Assortativity can be artificially implanted in a network via degree-preserving link permutations, however this destroys the graph’s hierarchical clustering and does not correspond to any microscopic mechanism. Here, we propose the first generative model which creates heterogeneous networks with scale-free-like properties in degree and clustering distributions and tunable realistic assortativity. Two distinct populations of nodes are incrementally added to an initial network by selecting a subgraph to connect to at random. One population (the followers) follows preferential attachment, while the other population (the potential leaders) connects via anti-preferential attachment: they link to lower degree nodes when added to the network. By selecting the lower degree nodes, the potential leader nodes maintain high visibility during the growth process, eventually growing into hubs. The evolution of links in Facebook empirically validates the connection between the initial anti-preferential attachment and long term high degree. In this way, our work sheds new light on the structure and evolution of social networks.
Coevolutionary modeling in network formation
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.
Directory of Open Access Journals (Sweden)
Lekso Budi Handoko
2015-05-01
Full Text Available Server yang melayani sebuah fungsi akan menyimpan data yang dimilikinya pada media penyimpanan secara lokal di tiap server itu sendiri. Namun dengan semakin meningkatnya penggunaan, cara ini menghadapi beberapa permasalahan, yaitu tidak efisien, tidak scalable, dan tidak dapat dikelola dengan mudah. Oleh karena itu, perlu mempergunakan sistem media penyimpanan external terpusat bagi seluruh layanan. Tujuan dari paper hasil penelitian dan analisis ini adalah memberikan perbandingan konsep penyimpanan data terpusat dengan Storage Area Network (SAN dan Network Attached Storage (NAS. Dimana yang dibandingkan adalah kecepatan baca dan tulis dari kedua konsep penyimpanan tersebut berkaitan dengan pemanfaatan network resource. Perbandingan ini akan memberikan referensi mengenai penyimpanan data terpusat mana yang paling efektif antara SAN dan NAS dalam menggunakan network resouce. Metode pengumpulan data yang digunakan yaitu menggunakan studi literatur dan studi kasus terhadap kedua konsep penyimpanan tersebut. Studi literatur dengan mencari referensi-referensi yang berkaitan dengan tema. Mengumpulkan data dan mencari kajian pustaka yang berkaitan. Dari hasil penelitian dan analisa maka dapat ditarik kesimpulan, ternyata setelah dilakukan pengujian dapat dikatakan bahwa terdapat perbandingan antara kecepatan baca dan tulis SAN dan NAS. Oleh karena itu didapatkan SAN adalah yang paling efektif dalam memanfaatkan network resource dan efisien dalam proses baca dan tulis pada storage server. Kata Kunci: Jaringan, Penyimpanan Data Terpusat, SAN, NAS, Storage Server.
Growing Scale-free Networks by a Mediation-Driven Attachment Rule
Hassan, Kamrul
2014-01-01
We propose a model that generates a new class of networks exhibiting power-law degree distribution with a spectrum of exponents depending on the number of links ($m$) with which incoming nodes join the existing network. Unlike the Barab\\'{a}si-Albert (BA) model, each new node first picks an existing node at random, and connects not with this but with $m$ of its neighbors also picked at random. Counterintuitively enough, such a mediation-driven attachment rule results not only in preferential but super-preferential attachment, albeit in disguise. We show that for small $m$, the dynamics of our model is governed by winners take all phenomenon, and for higher $m$ it is governed by winners take some. Besides, we show that the mean of the inverse harmonic mean of degrees of the neighborhood of all existing nodes is a measure that can well qualify how straight the degree distribution is.
Mining and modeling character networks
Bonato, Anthony; Elenberg, Ethan R; Gleich, David F; Hou, Yangyang
2016-01-01
We investigate social networks of characters found in cultural works such as novels and films. These character networks exhibit many of the properties of complex networks such as skewed degree distribution and community structure, but may be of relatively small order with a high multiplicity of edges. Building on recent work of beveridge, we consider graph extraction, visualization, and network statistics for three novels: Twilight by Stephanie Meyer, Steven King's The Stand, and J.K. Rowling's Harry Potter and the Goblet of Fire. Coupling with 800 character networks from films found in the http://moviegalaxies.com/ database, we compare the data sets to simulations from various stochastic complex networks models including random graphs with given expected degrees (also known as the Chung-Lu model), the configuration model, and the preferential attachment model. Using machine learning techniques based on motif (or small subgraph) counts, we determine that the Chung-Lu model best fits character networks and we ...
Assortativity and leadership emergence from anti-preferential attachment in heterogeneous networks
Sendiña-Nadal, I; Wang, Z; Havlin, S; Boccaletti, S
2015-01-01
Many real-world networks exhibit degree-assortativity, with nodes of similar degree more likely to link to one another. Particularly in social networks, the contribution to the total assortativity varies with degree, featuring a distinctive peak slightly past the average degree. The way traditional models imprint assortativity on top of pre-defined topologies is via degree-preserving link permutations, which however destroy the particular graph's hierarchical traits of clustering. Here, we propose the first generative model which creates heterogeneous networks with scale-free-like properties and tunable realistic assortativity. In our approach, two distinct populations of nodes are added to an initial network seed: one (the followers) that abides by usual preferential rules, and one (the potential leaders) connecting via anti-preferential attachments, i.e. selecting lower degree nodes for their initial links. The latter nodes come to develop a higher average degree, and convert eventually into the final hubs....
Granger Causality Stock Market Networks: Temporal Proximity and Preferential Attachment
Tom\\'a\\v{s} V\\'yrost; \\v{S}tefan Ly\\'ocsa; Eduard Baum\\"ohl
2014-01-01
The structure of return spillovers is examined by constructing Granger causality networks using daily closing prices of 20 developed markets from 2nd January 2006 to 31st December 2013. The data is properly aligned to take into account non-synchronous trading effects. The study of the resulting networks of over 94 sub-samples revealed three significant findings. First, after the recent financial crisis the impact of the US stock market has declined. Second, spatial probit models confirmed the...
An Attachment Model of University Connectedness
Wilson, Steffen; Gore, Jonathan
2013-01-01
Students with high levels of connectedness to the university have been found to be more likely to complete their college degree than are students with low levels of university connectedness. This study examined the role of parental and peer attachment as distal predictors of school connectedness. As predicted, it was found that attachment style to…
Preferential Attachment Model with Degree Bound and its Application to Key Predistribution in WSN
Ruj, Sushmita
2016-01-01
Preferential attachment models have been widely studied in complex networks, because they can explain the formation of many networks like social networks, citation networks, power grids, and biological networks, to name a few. Motivated by the application of key predistribution in wireless sensor networks (WSN), we initiate the study of preferential attachment with degree bound. Our paper has two important contributions to two different areas. The first is a contribution in the study of complex networks. We propose preferential attachment model with degree bound for the first time. In the normal preferential attachment model, the degree distribution follows a power law, with many nodes of low degree and a few nodes of high degree. In our scheme, the nodes can have a maximum degree $d_{\\max}$, where $d_{\\max}$ is an integer chosen according to the application. The second is in the security of wireless sensor networks. We propose a new key predistribution scheme based on the above model. The important features ...
Causadias, José M; Sroufe, L Alan; Herreros, Francisca
2011-03-01
In the face of a pressing need for expanded attachment research programs and attachment informed interventions in Latin America, a research network was established: Red Iberoamericana de Apego: RIA (Iberian-American Attachment Network). The purpose of RIA is to promote human development and well being, informed by attachment theory, centering on research, and with implications for public policies, education, and intervention. We report the proceedings of the second meeting of RIA held in Panama City, Panama, in February 2010. As part of this meeting, RIA sponsored the first Latin-American attachment conference. Proceedings of the conference are described, as are future goals of this new organization.
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.
Neurobiology of secure infant attachment and attachment despite adversity: a mouse model.
Roth, T L; Raineki, C; Salstein, L; Perry, R; Sullivan-Wilson, T A; Sloan, A; Lalji, B; Hammock, E; Wilson, D A; Levitt, P; Okutani, F; Kaba, H; Sullivan, R M
2013-10-01
Attachment to an abusive caregiver has wide phylogenetic representation, suggesting that animal models are useful in understanding the neural basis underlying this phenomenon and subsequent behavioral outcomes. We previously developed a rat model, in which we use classical conditioning to parallel learning processes evoked during secure attachment (odor-stroke, with stroke mimicking tactile stimulation from the caregiver) or attachment despite adversity (odor-shock, with shock mimicking maltreatment). Here we extend this model to mice. We conditioned infant mice (postnatal day (PN) 7-9 or 13-14) with presentations of peppermint odor and either stroking or shock. We used (14) C 2-deoxyglucose (2-DG) to assess olfactory bulb and amygdala metabolic changes following learning. PN7-9 mice learned to prefer an odor following either odor-stroke or shock conditioning, whereas odor-shock conditioning at PN13-14 resulted in aversion/fear learning. 2-DG data indicated enhanced bulbar activity in PN7-9 preference learning, whereas significant amygdala activity was present following aversion learning at PN13-14. Overall, the mouse results parallel behavioral and neural results in the rat model of attachment, and provide the foundation for the use of transgenic and knockout models to assess the impact of both genetic (biological vulnerabilities) and environmental factors (abusive) on attachment-related behaviors and behavioral development.
Attachment, Autonomy, and Emotional Reliance: A Multilevel Model
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…
The Relationship Between Attachment Styles, Self-Monitoring and Cybercrime in Social Network Users
Directory of Open Access Journals (Sweden)
Yaghoobi
2016-07-01
Full Text Available Background The anonymity in the cyberspace environment, as well as the rapid advent of and improvements to online activities has increased cybercrime. Objectives The aim of this paper was to survey the relationship between attachment styles, self-monitoring and cybercrime in social network users. Patients and Methods 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. Results 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. Conclusions Attachment styles have significant relationships with both self-monitoring and cybercrime. Self-monitoring and attachment styles are significant predictors of cybercrimes.
Extending the transdiagnostic model of attachment and psychopathology
Directory of Open Access Journals (Sweden)
Tsachi eEin-Dor
2016-03-01
Full Text Available Research has suggested that high levels of attachment insecurities that are formed through interactions with significant others are associated with a general vulnerability to mental disorders. In the present paper, we extend Ein-Dor and Doron's (2015 transdiagnostic model linking attachment orientations with internalizing and externalizing symptoms, to include thought disorder spectrum symptoms. Specifically, we speculate on the processes that mediate the linkage between attachment insecurities and psychosis and obsessive compulsive disorder (OCD symptoms, and indicate the different contexts that might set a trajectory of one individual to one set of symptoms while another individual to a different set of symptoms.
Wang, Xingyuan; Cao, Jianye; Li, Rui; Zhao, Tianfang
2017-10-01
Given the same two networks and only one-to-one interlinks are allowed, apparently interdependent networks coupled by these two networks has the optimal robustness when we connect every pair of the same nodes in these two networks. According to the structure of this interdependent network with the optimal robustness, we propose a preferential attachment strategy. And by applying this preferential attachment strategy to three existing connectivity link addition strategies RA (random addition strategy), LD (low degree addition strategy) and LIDD (low inter degree-degree difference addition strategy), we find that each improved strategy is obviously better than before in improving the robustness of interdependent networks. Our findings can provide guidance on connectivity link addition strategy to improve robustness of interdependent networks against cascading failures.
Joint estimation of preferential attachment and node fitness in growing complex networks
Pham, Thong; Sheridan, Paul; Shimodaira, Hidetoshi
2016-09-01
Complex network growth across diverse fields of science is hypothesized to be driven in the main by a combination of preferential attachment and node fitness processes. For measuring the respective influences of these processes, previous approaches make strong and untested assumptions on the functional forms of either the preferential attachment function or fitness function or both. We introduce a Bayesian statistical method called PAFit to estimate preferential attachment and node fitness without imposing such functional constraints that works by maximizing a log-likelihood function with suitably added regularization terms. We use PAFit to investigate the interplay between preferential attachment and node fitness processes in a Facebook wall-post network. While we uncover evidence for both preferential attachment and node fitness, thus validating the hypothesis that these processes together drive complex network evolution, we also find that node fitness plays the bigger role in determining the degree of a node. This is the first validation of its kind on real-world network data. But surprisingly the rate of preferential attachment is found to deviate from the conventional log-linear form when node fitness is taken into account. The proposed method is implemented in the R package PAFit.
Joint estimation of preferential attachment and node fitness in growing complex networks.
Pham, Thong; Sheridan, Paul; Shimodaira, Hidetoshi
2016-09-07
Complex network growth across diverse fields of science is hypothesized to be driven in the main by a combination of preferential attachment and node fitness processes. For measuring the respective influences of these processes, previous approaches make strong and untested assumptions on the functional forms of either the preferential attachment function or fitness function or both. We introduce a Bayesian statistical method called PAFit to estimate preferential attachment and node fitness without imposing such functional constraints that works by maximizing a log-likelihood function with suitably added regularization terms. We use PAFit to investigate the interplay between preferential attachment and node fitness processes in a Facebook wall-post network. While we uncover evidence for both preferential attachment and node fitness, thus validating the hypothesis that these processes together drive complex network evolution, we also find that node fitness plays the bigger role in determining the degree of a node. This is the first validation of its kind on real-world network data. But surprisingly the rate of preferential attachment is found to deviate from the conventional log-linear form when node fitness is taken into account. The proposed method is implemented in the R package PAFit.
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.
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.
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.
Preferential attachment in the growth of social networks: the internet encyclopedia Wikipedia.
Capocci, A; Servedio, V D P; Colaiori, F; Buriol, L S; Donato, D; Leonardi, S; Caldarelli, G
2006-09-01
We present an analysis of the statistical properties and growth of the free on-line encyclopedia Wikipedia. By describing topics by vertices and hyperlinks between them as edges, we can represent this encyclopedia as a directed graph. The topological properties of this graph are in close analogy with those of the World Wide Web, despite the very different growth mechanism. In particular, we measure a scale-invariant distribution of the in and out degree and we are able to reproduce these features by means of a simple statistical model. As a major consequence, Wikipedia growth can be described by local rules such as the preferential attachment mechanism, though users, who are responsible of its evolution, can act globally on the network.
Hadden, Benjamin W; Smith, C Veronica; Webster, Gregory D
2014-02-01
Although research has examined associations between attachment dimensions and relationship outcomes, theory has ignored how these associations change over time in adult romantic relationships. We proposed the Temporal Adult Romantic Attachment (TARA) model, which predicts that the negative associations between anxious and avoidant attachment on one hand and relationship satisfaction and commitment on the other will be more negative as relationship durations increase. Meta-analyses largely confirmed that negative associations between both insecure attachment dimensions and both relationship outcomes were more negative among longer relationship durations in cross-sectional samples. We also explored gender differences in these associations. The present review not only integrates the literature on adult attachment and romantic relationship satisfaction/commitment but also highlights the importance of relationship duration as a key moderator of the associations among these variables. We discuss the broad implications of these effects and our meta-analytic findings for the TARA model, attachment theory, and romantic relationships.
Neuroplasticity in dynamic neural networks comprised of neurons attached to adaptive base plate.
Joghataie, Abdolreza; Shafiei Dizaji, Mehrdad
2016-03-01
In this paper, a learning algorithm is developed for Dynamic Plastic Continuous Neural Networks (DPCNNs) to improve their learning of highly nonlinear time dependent problems. A DPCNN is comprised of a base medium, which is nonlinear and plastic, and a number of neurons that are attached to the base by wire-like connections similar to perceptrons. The information is distributed within DPCNNs gradually and through wave propagation mechanism. While a DPCNN is adaptive due to its connection weights, the material properties of its base medium can also be adjusted to improve its learning. The material of the medium is plastic and can contribute to memorizing the history of input-response similar to neuroplasticity in natural brain. The results obtained from numerical simulation of DPCNNs have been encouraging. Nonlinear plastic finite element modeling has been used for numerical simulation of dynamic behavior and wave propagation in the medium. Two significant differences of DPCNNs with other types of neural networks are that: (1) there is a medium to which the neurons are attached where the medium can contribute to the learning, (2) the input layer is not made of nodes but it is an edge terminal which is capable of receiving a continuous function over the input edge, though it is discretized in the finite element model. A DPCNN is reduced to a perceptron if the medium is removed and the neurons are connected to each other only by wires. Continuity of the input lets the discretization of data take place intrinsically within the DPCNN instead of being applied by the user.
Abbasi, A.; Hossain, L.; Leydesdorff, L.
2012-01-01
We analyze whether preferential attachment in scientific coauthorship networks is different for authors with different forms of centrality. Using a complete database for the scientific specialty of research about "steel structures," we show that betweenness centrality of an existing node is a signif
Armbruster, Benjamin
2011-01-01
We analyze random networks that change over time. First we analyze a dynamic Erdos-Renyi model, whose edges change over time. We describe its stationary distribution, its convergence thereto, and the SI contact process on the network, which has relevance for connectivity and the spread of infections. Second, we analyze the effect of node turnover, when nodes enter and leave the network, which has relevance for network models incorporating births, deaths, aging, and other demographic factors.
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.
A Generalized Preferential Attachment Model for Complex Systems
Yamasaki, K; Fu, D; Buldyrev, S V; Pammolli, F; Riccaboni, M; Stanley, H E; Yamasaki, Kazuko; Matia, Kaushik; Fu, Dongfeng; Buldyrev, Sergey V.; Pammolli, Fabio; Riccaboni, Massimo
2005-01-01
Complex systems can be characterized by classes of equivalency of their elements defined according to system specific rules. We propose a generalized preferential attachment model to describe the class size distribution. The model postulates preferential growth of the existing classes and the steady influx of new classes. We investigate how the distribution depends on the initial conditions and changes from a pure exponential form for zero influx of new classes to a power law with an exponential cutoff form when the influx of new classes is substantial. We apply the model to study the growth dynamics of pharmaceutical industry.
Modeling worldwide highway networks
Villas Boas, Paulino R.; Rodrigues, Francisco A.; da F. Costa, Luciano
2009-12-01
This Letter addresses the problem of modeling the highway systems of different countries by using complex networks formalism. More specifically, we compare two traditional geographical models with a modified geometrical network model where paths, rather than edges, are incorporated at each step between the origin and the destination vertices. Optimal configurations of parameters are obtained for each model and used for the comparison. The highway networks of Australia, Brazil, India, and Romania are considered and shown to be properly modeled by the modified geographical model.
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...
Modeling and Robustness of Knowledge Network in Supply Chain
Institute of Scientific and Technical Information of China (English)
王道平; 沈睿芳
2014-01-01
The growth and evolution of the knowledge network in supply chain can be characterized by dynamic growth clustering and non-homogeneous degree distribution. The networks with the above characteristics are also known as scale-free networks. In this paper, the knowledge network model in supply chain is established, in which the preferential attachment mechanism based on the node strength is adopted to simulate the growth and evolution of the network. The nodes in the network have a certain preference in the choice of a knowledge partner. On the basis of the network model, the robustness of the three network models based on different preferential attachment strategies is in-vestigated. The robustness is also referred to as tolerances when the nodes are subjected to random destruction and malicious damage. The simulation results of this study show that the improved network has higher connectivity and stability.
Application of an active attachment model as a high-throughput demineralization biofilm model
Silva, T.C.; Pereira, A.F.F.; Exterkate, R.A.M.; Bagnato, V.S.; Buzalaf, M.A.R.; de A.M. Machado, M.A.; ten Cate, J.M.; Crielaard, W.; Deng, D.M.
2012-01-01
Objectives To investigate the potential of an active attachment biofilm model as a high-throughput demineralization biofilm model for the evaluation of caries-preventive agents. Methods Streptococcus mutans UA159 biofilms were grown on bovine dentine discs in a high-throughput active attachment mode
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....
Artificial neural network modelling
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. .
Experience and Lessons learnt from running High Availability Databases on Network Attached Storage
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.
Filament networks attached to membranes: cytoskeletal pressure and local bilayer deformation
Auth, Thorsten; Safran, S. A.; Gov, Nir S.
2007-11-01
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.
Filament networks attached to membranes: cytoskeletal pressure and local bilayer deformation
Energy Technology Data Exchange (ETDEWEB)
Auth, Thorsten [Department of Materials and Interfaces, Weizmann Institute of Science, PO Box 26, Rehovot 76100 (Israel); Safran, S A [Department of Materials and Interfaces, Weizmann Institute of Science, PO Box 26, Rehovot 76100 (Israel); Gov, Nir S [Department of Chemical Physics, Weizmann Institute of Science, PO Box 26, Rehovot 76100 (Israel)
2007-11-15
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.
Modeling Network Interdiction Tasks
2015-09-17
minimize the operating costs for manufacturing 50 the item. This simple example illustrates the hierarchical structure that can be modeled using...fixed. The resulting model is linearized and the product of the dual variable and the (1−γij) term replaced with βij. This allows certain...the standard network interdiction model based on its tight linear programming relaxation. 2.3.3 Network Disruption. In practice, whenever an object is
Developing a neurobehavioral animal model of infant attachment to an abusive caregiver.
Raineki, Charlis; Moriceau, Stephanie; Sullivan, Regina M
2010-06-15
Both abused and well cared for infants show attachment to their caregivers, although the quality of that attachment differs. Moreover, the infant's attachment to the abusive caregiver is associated with compromised mental health, especially under stress. In an attempt to better understand how abuse by the caregiver can compromise mental health, we explore the neural basis of attachment in both typical and abusive environments using infant rats, which form attachments to the mother through learning her odor. Here, we hypothesize that the neural circuitry for infant attachment differs based on the quality of the attachment, which can be uncovered during stressful situations. We used infant rats to compare infant attachment social behaviors and supporting neurobiology using natural maternal odor, as well as two odor-learning attachment paradigms: odor-stroke (mimics typical attachment) and odor-.5 mA shock conditioning (mimics abusive attachment). Next, to uncover differences in behavior and brain, these pups were injected with systemic corticosterone. Finally, pups were reared with an abusive mother to determine ecological relevance. Our results suggest that the natural and learned attachment odors indistinguishably control social behavior in infancy (approach to the odor and interactions with the mother). However, with corticosterone injection, pups with an abusive attachment show disrupted infant social behavior with the mother and engagement of the amygdala. This animal model of attachment accommodates both abusive and typical attachment and suggests that pups' social behavior and underlying neural circuitry may provide clues to understanding attachment in children with various conditions of care.
Prepositional Phrase Attachment through a Backed-Off Model
Collins, M; Collins, Michael; Brooks, James
1995-01-01
Recent work has considered corpus-based or statistical approaches to the problem of prepositional phrase attachment ambiguity. Typically, ambiguous verb phrases of the form {v np1 p np2} are resolved through a model which considers values of the four head words (v, n1, p and n2). This paper shows that the problem is analogous to n-gram language models in speech recognition, and that one of the most common methods for language modeling, the backed-off estimate, is applicable. Results on Wall Street Journal data of 84.5% accuracy are obtained using this method. A surprising result is the importance of low-count events - ignoring events which occur less than 5 times in training data reduces performance to 81.6%.
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.
Modeling online social networks based on preferential linking
Institute of Scientific and Technical Information of China (English)
Hu Hai-Bo; Guo Jin-Li; Chen Jun
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.
Is Imprinting an Appropriate Model for Human Infant Attachment?
Reed, G. L.; Leiderman, P. H.
1983-01-01
Results of animal imprinting studies were generalized to attempt prediction of development of attachment in 28 polymatrically reared Kenyan Gusii infants, ages 6 to 30 months. While results provide evidence against a sensitive phase for attachment, an association was found between age of attachment and developmental level/caregiving history.…
Modeling Epidemic Network Failures
DEFF Research Database (Denmark)
Ruepp, Sarah Renée; Fagertun, Anna Manolova
2013-01-01
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......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...
Modeling Evolving Innovation Networks
Koenig, Michael D.; Battiston, Stefano; Schweitzer, Frank
2007-01-01
We develop a new framework for modeling innovation networks which evolve over time. The nodes in the network represent firms, whereas the directed links represent unilateral interactions between the firms. Both nodes and links evolve according to their own dynamics and on different time scales. The model assumes that firms produce knowledge based on the knowledge exchange with other firms, which involves both costs and benefits for the participating firms. In order to increase their knowledge...
Strategic games on a hierarchical network model
Institute of Scientific and Technical Information of China (English)
无
2008-01-01
Among complex network models, the hierarchical network model is the one most close to such real networks as world trade web, metabolic network, WWW, actor network, and so on. It has not only the property of power-law degree distribution, but growth based on growth and preferential attachment, showing the scale-free degree distribution property. In this paper, we study the evolution of cooperation on a hierarchical network model, adopting the prisoner's dilemma (PD) game and snowdrift game (SG) as metaphors of the interplay between connected nodes. BA model provides a unifying framework for the emergence of cooperation. But interestingly, we found that on hierarchical model, there is no sign of cooperation for PD game, while the frequency of cooperation decreases as the common benefit decreases for SG. By comparing the scaling clustering coefficient properties of the hierarchical network model with that of BA model, we found that the former amplifies the effect of hubs. Considering different performances of PD game and SG on complex network, we also found that common benefit leads to cooperation in the evolution. Thus our study may shed light on the emergence of cooperation in both natural and social environments.
Features and heterogeneities in growing network models
Ferretti, Luca; Cortelezzi, Michele; Yang, Bin; Marmorini, Giacomo; Bianconi, Ginestra
2012-06-01
Many complex networks from the World Wide Web to biological networks grow taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document such as personal page, thematic website, news, blog, search engine, social network, etc., or the classification of a gene in a functional module. Moreover the feature of a node can be a continuous variable such as the position of a node in the embedding space. In order to account for these properties, in this paper we provide a generalization of growing network models with preferential attachment that includes the effect of heterogeneous features of the nodes. The main effect of heterogeneity is the emergence of an “effective fitness” for each class of nodes, determining the rate at which nodes acquire new links. The degree distribution exhibits a multiscaling behavior analogous to the the fitness model. This property is robust with respect to variations in the model, as long as links are assigned through effective preferential attachment. Beyond the degree distribution, in this paper we give a full characterization of the other relevant properties of the model. We evaluate the clustering coefficient and show that it disappears for large network size, a property shared with the Barabási-Albert model. Negative degree correlations are also present in this class of models, along with nontrivial mixing patterns among features. We therefore conclude that both small clustering coefficients and disassortative mixing are outcomes of the preferential attachment mechanism in general growing networks.
Hassan, Md Kamrul; Haque, Syed Arefinul
2016-01-01
We investigate the growth of a class of networks in which a new node first picks a mediator at random and connects with $m$ randomly chosen neighbors of the mediator at each time step. We show that degree distribution in such a mediation-driven attachment (MDA) network exhibits power-law $P(k)\\sim k^{-\\gamma(m)}$ with a spectrum of exponents depending on $m$. To appreciate the contrast between MDA and Barab\\'{a}si-Albert (BA) networks, we then discuss their rank-size distribution. To quantify how long a leader, the node with the maximum degree, persists in its leadership as the network evolves, we investigate the leadership persistence probability $F(\\tau)$ i.e. the probability that a leader retains its leadership up to time $\\tau$. We find that it exhibits a power-law $F(\\tau)\\sim \\tau^{-\\theta(m)}$ with persistence exponent $\\theta(m) \\approx 1.51 \\ \\forall \\ m$ in the MDA networks and $\\theta(m) \\rightarrow 1.53$ exponentially with $m$ in the BA networks.
Hassan, Md. Kamrul; Islam, Liana; Haque, Syed Arefinul
2017-03-01
We investigate the growth of a class of networks in which a new node first picks a mediator at random and connects with m randomly chosen neighbors of the mediator at each time step. We show that the degree distribution in such a mediation-driven attachment (MDA) network exhibits power-law P(k) ∼k - γ(m) with a spectrum of exponents depending on m. To appreciate the contrast between MDA and Barabási-Albert (BA) networks, we then discuss their rank-size distribution. To quantify how long a leader, the node with the maximum degree, persists in its leadership as the network evolves, we investigate the leadership persistence probability F(τ) i.e. the probability that a leader retains its leadership up to time τ. We find that it exhibits a power-law F(τ) ∼τ - θ(m) with persistence exponent θ(m) ≈ 1.51 ∀ m in MDA networks and θ(m) → 1.53 exponentially with m in BA networks.
Evolution of Knowledge Networks (Ⅲ): Attachment Mechanism%知识网络的演化(Ⅲ):连接机制
Institute of Scientific and Technical Information of China (English)
马费成; 刘向
2011-01-01
Attachment mechanisms which construct connections from old knowledge vertex to new one is the mostimportant factor to form the topological structure of knowledge network. This paper constructed the evolution model by introducing preferential attachment of degree and time. The model considered the changing of edges and time effect to the attachment. By function analysis and simulation, it found that it had flatter degree distribution in liner growth edge attachment, and time effect made new knowledge more used, restraining the defect of Matthew effect.%新旧知识节点之间前承后继的连接机制是知识网络拓扑结构形成的最关键部分,通过引入度优先连接、时间优先连接,构造了知识网路的演化模型.模型考虑了知识节点出度的动态变化以及时间效应的作用,数理分析及仿真实验发现:出度线性增长形成更平坦的度分布,而出度对数增长对度分布影响不大,出度对数增长更加符合现实情况;时间效应使得新近加入知识节点也获得了较多的利用,自动平抑了马太效应的负面影响.
Institute of Scientific and Technical Information of China (English)
张济宇; 林诚; 林春深
2002-01-01
The axial concentration distribution of both particles with better wetting (forming non-attached system)and poorer wetting (forming attached system) was investigated in a vertical gas-liquid-solid fluidized bed of 4.2 cm indiameter and 130 cm in height with the solids holdup less than 0.05. The one-dimensional sedimentation-dispersionmodel could be used satisfactorily to describe the axial distribution of solids holdup by modifying only a modelparameter, i.e. by means of the terminal settling velocity minus a certain value, which is a function of gas velocityand considers the effect of an additional drag force resulted from attached rising bubbles. The axial profiles of solidconcentration predicted are in good agreement with experimental results. This model also explains reasonably thedifferent axial distributions of solid concentration, i.e. the solids holdup decreases as the axial height increases innon-attached system, but increases with the axial height in attached system at a given gas velocity.
Modeling Dynamic Evolution of Online Friendship Network
Institute of Scientific and Technical Information of China (English)
吴联仁; 闫强
2012-01-01
In this paper,we study the dynamic evolution of friendship network in SNS (Social Networking Site).Our analysis suggests that an individual joining a community depends not only on the number of friends he or she has within the community,but also on the friendship network generated by those friends.In addition,we propose a model which is based on two processes:first,connecting nearest neighbors;second,strength driven attachment mechanism.The model reflects two facts:first,in the social network it is a universal phenomenon that two nodes are connected when they have at least one common neighbor;second,new nodes connect more likely to nodes which have larger weights and interactions,a phenomenon called strength driven attachment (also called weight driven attachment).From the simulation results,we find that degree distribution P(k),strength distribution P(s),and degree-strength correlation are all consistent with empirical data.
Attachment, Working Models of Parenting, and Expectations for Using Television in Childrearing
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…
Attachment, Working Models of Parenting, and Expectations for Using Television in Childrearing
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…
HUSTserver： Implementation for Reliable and High—Performance Network Attached Storage System
Institute of Scientific and Technical Information of China (English)
郭辉; 周敬利; 余胜生
2003-01-01
Network-attached storage (NAS) with the properties of improved scalability, simplified management, low cost and balanced price-performance, is desirable for high performance storage systems applied to extensive areas. Unfortunately, it also has some dis-advantages such as increased network workload, and inconvenience in disaster recovery. To overcome these disadvantages, we pro-pose a channel-bonding technique and provide hot-backup functions in the designed NAS system, named HUSTserver. Channel bonding means merging multiple Ethernet channels into integrated one, and that the data packets can be transferred through any available net-work channels in a parallel mode. The hot-backup function provides automaticdata mirroring among servers. In this paper, we first describe the whole system prototype from a software and hardware architecture view. Then, multiple Ethernet and hot-backup tech-nologies that distinguish HUSTserver from others are discussed in detail. The findings presented demonstrate that network bandwidth can be scaled by the use of multiple commodity networks. Dual parallel channels of commodity 100 Mbps Ethernet are both necessary and sufficient to support the data rates of multiple concurrent file transfers. And the hot-backup function introduced in our system pro-vides high data accessibility.
Experience and Lessons learnt from running high availability databases on Network Attached Storage
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...
Raque-Bogdan, Trisha L; Piontkowski, Sarah; Hui, Kayi; Ziemer, Kathryn Schaefer; Garriott, Patton O
2016-12-01
Body appreciation has been found to be linked to interpersonal and intrapersonal factors, with attachment styles and self-compassion separately identified as important correlates. The present study examined these variables together in a model, and we hypothesized that maternal attachment anxiety was related to peer and romantic attachment anxiety, which, in turn, was associated with self-compassion and body appreciation. Using structural equation modeling, this cross-sectional study with a sample of 1306 incoming first year college women found that the proposed model explained 40% of the variance in body appreciation. Results further revealed that peer and romantic attachment anxiety mediated the relationships between maternal attachment anxiety and self-compassion, and that self-compassion mediated the associations between peer and romantic attachment anxiety and body appreciation. Self-compassion appears to hold a central role in explaining the relation between attachment anxiety and body appreciation.
Models of educational institutions' networking
Shilova Olga Nikolaevna
2015-01-01
The importance of educational institutions' networking in modern sociocultural conditions and a definition of networking in education are presented in the article. The results of research levels, methods and models of educational institutions' networking are presented and substantially disclosed.
Models of educational institutions' networking
Shilova Olga Nikolaevna
2015-01-01
The importance of educational institutions' networking in modern sociocultural conditions and a definition of networking in education are presented in the article. The results of research levels, methods and models of educational institutions' networking are presented and substantially disclosed.
Love, Keisha M.; Murdock, Tamera B.
2012-01-01
In an attempt to understand the cognitive mechanisms by which parental attachments predict depression among African American college students, the authors examined a mediational path model containing parental attachment, cognitive working models, and depression. The model demonstrated a close fit to the data, and several significant paths emerged.…
Parenting practices, parental attachment and aggressiveness in adolescence: a predictive model.
Gallarin, Miriam; Alonso-Arbiol, Itziar
2012-12-01
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' parenting practices, attachment to mother and to father, and aggressiveness. Acceptance/involvement of each parent positively predicted an adolescent's attachment to that parent, and coercion/imposition negatively predicted attachment to a lesser extent. Using structural equation modeling, a full mediation model provided the most parsimonious explanation for the data. With attachment in the model, the paths between the two parenting practices and aggressiveness were minor and statistically non-significant. Only attachment to the father, was predictive of adolescents' aggressiveness. Results are discussed in the light of the importance of the father-son/daughter relationship in adolescence.
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.
Degree distribution of a new model for evolving networks
Indian Academy of Sciences (India)
Xuan Zhang; Qinggui Zhao
2010-03-01
We propose and study an evolving network model with both preferential and random attachments of new links, incorporating the addition of new nodes, new links, and the removal of links. We first show that the degree evolution of a node follows a nonhomogeneous Markov chain. Based on the concept of Markov chain, we provide the exact solution of the degree distribution of this model and show that the model can generate scale-free evolving network.
Hamiltonian Dynamics of Preferential Attachment
Zuev, Konstantin; Krioukov, Dmitri
2015-01-01
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, 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 preferential attachment. 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 preferential attachment is nearly identical to the ensemble of random graphs with scale-free degree d...
Neural evidence for a multifaceted model of attachment security.
Canterberry, Melanie; Gillath, Omri
2013-06-01
The sense of attachment security has been linked with a host of beneficial outcomes related to personal and relational well-being. Moreover, research has demonstrated that the sense of attachment security can be enhanced via cognitive priming techniques. Studies using such techniques have shown that security priming results with similar outcomes as dispositional attachment security. The way security priming leads to these effects, however, is yet to be unveiled. Using fMRI we took one step in that direction and examined the neural mechanisms underlying enhanced attachment security. Participants were exposed to explicit and implicit security- and insecurity-related words. Security priming led to co-occurring activation in brain areas reflective of cognitive, affective, and behavioral processes (e.g., medial frontal cortex, parahippocampus, BA 6). There were activation differences based on attachment style. This research serves as an important step in mapping out the security process and supports a conceptualization of security as part of a behavioral system with multiple components. Copyright © 2012 Elsevier B.V. All rights reserved.
Directed network discovery with dynamic network modelling.
Anzellotti, Stefano; Kliemann, Dorit; Jacoby, Nir; Saxe, Rebecca
2017-05-01
Cognitive tasks recruit multiple brain regions. Understanding how these regions influence each other (the network structure) is an important step to characterize the neural basis of cognitive processes. Often, limited evidence is available to restrict the range of hypotheses a priori, and techniques that sift efficiently through a large number of possible network structures are needed (network discovery). This article introduces a novel modelling technique for network discovery (Dynamic Network Modelling or DNM) that builds on ideas from Granger Causality and Dynamic Causal Modelling introducing three key changes: (1) efficient network discovery is implemented with statistical tests on the consistency of model parameters across participants, (2) the tests take into account the magnitude and sign of each influence, and (3) variance explained in independent data is used as an absolute (rather than relative) measure of the quality of the network model. In this article, we outline the functioning of DNM, we validate DNM in simulated data for which the ground truth is known, and we report an example of its application to the investigation of influences between regions during emotion recognition, revealing top-down influences from brain regions encoding abstract representations of emotions (medial prefrontal cortex and superior temporal sulcus) onto regions engaged in the perceptual analysis of facial expressions (occipital face area and fusiform face area) when participants are asked to switch between reporting the emotional valence and the age of a face. Copyright © 2017 Elsevier Ltd. All rights reserved.
Revising Working Models Across Time: Relationship Situations That Enhance Attachment Security.
Arriaga, Ximena B; Kumashiro, Madoka; Simpson, Jeffry A; Overall, Nickola C
2017-06-01
We propose the Attachment Security Enhancement Model (ASEM) to suggest how romantic relationships can promote chronic attachment security. One part of the ASEM examines partner responses that protect relationships from the erosive effects of immediate insecurity, but such responses may not necessarily address underlying insecurities in a person's mental models. Therefore, a second part of the ASEM examines relationship situations that foster more secure mental models. Both parts may work in tandem. We posit that attachment anxiety should decline most in situations that foster greater personal confidence and more secure mental models of the self. In contrast, attachment avoidance should decline most in situations that involve positive dependence and foster more secure models of close others. The ASEM integrates research and theory, suggests novel directions for future research, and has practical implications, all of which center on the idea that adult attachment orientations are an emergent property of close relationships.
The paths leading from attachment to ageism: a structural equation model approach.
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.
Model Diagnostics for Bayesian Networks
Sinharay, Sandip
2006-01-01
Bayesian networks are frequently used in educational assessments primarily for learning about students' knowledge and skills. There is a lack of works on assessing fit of Bayesian networks. This article employs the posterior predictive model checking method, a popular Bayesian model checking tool, to assess fit of simple Bayesian networks. A…
Model of Effects of Adult Attachment on Emotional Empathy of Counseling Students
Trusty, Jerry; Ng, Kok-Mun; Watts, Richard E.
2005-01-01
The effects of adult attachment on emotional empathy were investigated using a sample of master's-degree level counseling students. Through structural equation modeling, the authors found that the latent attachment dimensions of avoidance and anxiety work in tandem in their effects on empathy. Lower avoidance and higher anxiety were associated…
A Study of Perfectionism, Attachment, and College Student Adjustment: Testing Mediational Models.
Hood, Camille A.; Kubal, Anne E.; Pfaller, Joan; Rice, Kenneth G.
Mediational models predicting college students' adjustment were tested using regression analyses. Contemporary adult attachment theory was employed to explore the cognitive/affective mechanisms by which adult attachment and perfectionism affect various aspects of psychological functioning. Consistent with theoretical expectations, results…
A dual modelling of evolving political opinion networks
Wang, Ru
2012-01-01
We present the result of a dual modeling of opinion network. The model complements the agent-based opinion models by attaching to the social agent (voters) network a political opinion (party) network having its own intrinsic mechanisms of evolution. These two sub-networks form a global network which can be either isolated from or dependent on the external influence. Basically, the evolution of the agent network includes link adding and deleting, the opinion changes influenced by social validation, the political climate, the attractivity of the parties and the interaction between them. The opinion network is initially composed of numerous nodes representing opinions or parties which are located on a one dimensional axis according to their political positions. The mechanism of evolution includes union, splitting, change of position and of attractivity, taken into account the pairwise node interaction decaying with node distance in power law. The global evolution ends in a stable distribution of the social agent...
Attachment Style and Chronic Pain: Toward an Interpersonal Model of Pain.
Romeo, Annunziata; Tesio, Valentina; Castelnuovo, Gianluca; Castelli, Lorys
2017-01-01
Chronic pain (CP) is a burdensome symptom. Different psychological models have been proposed to explain the role of psychological and social factors in developing and maintaining CP. Attachment, for example, is a psychological construct of possible relevance in CP. The first studies on the role of attachment in CP did not investigate the partner's psychological factors, thus neglecting the influence of the latter. The main aim of this mini-review was to examine the more recent literature investigating the relationship between CP and attachment style. In particular, whether or not more recent studies assessed the psychological variables of a patient's partner. The articles were selected from the Medline/PubMed database using the search terms "attachment" AND "pain"; "CP" AND "attachment style," which led to nine papers being identified. The results showed that, even though the key point was still the hypothesis that an insecure attachment style is associated with CP, in recent years researchers have focused on the possible psychological aspects mediating between attachment style and CP. In particular, worrying, coping strategies, catastrophizing and perceived spouse responses to pain behavior were taken into account. Only one study considered the role of the reciprocal influence of attachment style of both patient and partner, underlining the role of real significant others' responses to pain behaviors. In conclusion, the results of the present mini-review highlight how in recent years researchers have moved toward investigating those psychological aspects that could mediate the relationship between attachment and CP, while only partially evaluating the interpersonal perspective.
Cheryl C. Woolley; Dave Clarke; Karin du Plessis
2007-01-01
Attachment theory focuses on the cognitive models that underlie our interactions with attachment figures. Global or generalized mental models are thought to develop on the basis of attachment models with parents and might form the initial basis of internal working models in novel relationships. However, as discrepant information presents itself in a new relationship, it is thought that specific relational models develop. When conflict arises it can threaten the attachment bonds of the relatio...
An evolving model of online bipartite networks
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.
Modelling hierarchical and modular complex networks: division and independence
Kim, D.-H.; Rodgers, G. J.; Kahng, B.; Kim, D.
2005-06-01
We introduce a growing network model which generates both modular and hierarchical structure in a self-organized way. To this end, we modify the Barabási-Albert model into the one evolving under the principles of division and independence as well as growth and preferential attachment (PA). A newly added vertex chooses one of the modules composed of existing vertices, and attaches edges to vertices belonging to that module following the PA rule. When the module size reaches a proper size, the module is divided into two, and a new module is created. The karate club network studied by Zachary is a simple version of the current model. We find that the model can reproduce both modular and hierarchical properties, characterized by the hierarchical clustering function of a vertex with degree k, C(k), being in good agreement with empirical measurements for real-world networks.
Cantazaro, Amy; Wei, Meifen
2010-08-01
Attachment anxiety is expected to be positively associated with dependence and self-criticism. However, attachment avoidance is expected to be negatively associated with dependence but positively associated with self-criticism. Both dependence and self-criticism are expected to be related to depressive symptoms. Data were analyzed from 424 undergraduate participants at a large Midwestern university, using structural equation modeling. Results indicated that the relation between attachment anxiety and depressive symptoms was fully mediated by dependence and self-criticism, whereas the relation between attachment avoidance and depressive symptoms was partially mediated by dependence and self-criticism. Moreover, through a multiple-group comparison analysis, the results indicated that men with high levels of attachment avoidance are more likely than women to be self-critical.
Beebe, Beatrice; Lachmann, Frank; Markese, Sara; Bahrick, Lorraine
2012-01-01
Despite important recent progress in understanding disorganized attachment, we still lack a full understanding of the mechanisms of disorganized attachment formation and transmission prior to 12 months. In this paper we lay out our recommendations for the study of the 4-month origins of disorganized attachment. In our subsequent Paper II we report on the results of a large empirical study that was conducted along the lines we recommend in Paper I. Both Papers I and II are based on Beebe, Jaffe, Markese, Buck, Chen, Cohen, Bahrick, Andrews, Feldstein (2010). In Paper I we describe our proposal that a detailed microanalysis of 4-month mother-infant face-to-face communication would further inform our understanding of the process of disorganized attachment formation between mother and infant. Such a microanalysis would allow us to characterize the nature of the 4-month infant's procedural representations, or emerging "internal working models" of attachment.
Gay, Guillaume; Courtheoux, Thibault; Reyes, Céline; Tournier, Sylvie; Gachet, Yannick
2012-01-01
In fission yeast, erroneous attachments of spindle microtubules to kinetochores are frequent in early mitosis. Most are corrected before anaphase onset by a mechanism involving the protein kinase Aurora B, which destabilizes kinetochore microtubules (ktMTs) in the absence of tension between sister chromatids. In this paper, we describe a minimal mathematical model of fission yeast chromosome segregation based on the stochastic attachment and detachment of ktMTs. The model accurately reproduce...
Directory of Open Access Journals (Sweden)
Cheryl C. Woolley
2007-06-01
Full Text Available Attachment theory focuses on the cognitive models that underlie our interactions with attachment figures. Global or generalized mental models are thought to develop on the basis of attachment models with parents and might form the initial basis of internal working models in novel relationships. However, as discrepant information presents itself in a new relationship, it is thought that specific relational models develop. When conflict arises it can threaten the attachment bonds of the relationship. An Internet survey of 134 individuals in couple relationships was conducted to test the influence of secure parental and partner attachment conceptualizations on romantic relationship variables (conflict beliefs and conflict resolution styles. Results indicated that for the most part relationship variables were influenced by current secure romantic attachment conceptualizations. Analyses also indicated differential gender results for positive problem solving in terms of secure parental and partner attachment. Secure parental attachment was also found to impact on the report of compliant behavior during conflict resolution. Lastly, the belief that arguing is threatening was found to be impacted by an interaction effect between parental and partner attachment. In general secure partner attachment was more predictive of conflict resolution behavior and conflict beliefs, than a global attachment model. However, it would appear that the global attachment model can be activated in the context of the current relationship under certain conditions. This research lends support to the notion that generalized and specific attachment representations impacts differently on close relationship functioning, and encourages a further mapping of relationship functions in this regard.
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.
Gay, Guillaume; Courtheoux, Thibault; Reyes, Céline; Tournier, Sylvie; Gachet, Yannick
2012-03-19
In fission yeast, erroneous attachments of spindle microtubules to kinetochores are frequent in early mitosis. Most are corrected before anaphase onset by a mechanism involving the protein kinase Aurora B, which destabilizes kinetochore microtubules (ktMTs) in the absence of tension between sister chromatids. In this paper, we describe a minimal mathematical model of fission yeast chromosome segregation based on the stochastic attachment and detachment of ktMTs. The model accurately reproduces the timing of correct chromosome biorientation and segregation seen in fission yeast. Prevention of attachment defects requires both appropriate kinetochore orientation and an Aurora B-like activity. The model also reproduces abnormal chromosome segregation behavior (caused by, for example, inhibition of Aurora B). It predicts that, in metaphase, merotelic attachment is prevented by a kinetochore orientation effect and corrected by an Aurora B-like activity, whereas in anaphase, it is corrected through unbalanced forces applied to the kinetochore. These unbalanced forces are sufficient to prevent aneuploidy.
Attachment in medical care: A review of the interpersonal model in chronic disease management.
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.
Latency-aged children with attachment disturbances: a conjoint treatment model.
Shiller, Virginia M
2011-01-01
Psychoanalytic theory and practice has increasingly accepted the importance of attachment relationships in psychic development. However, there have been only very limited efforts to develop psychoanalytically informed interventions for older adopted and foster children who show significant disturbances in attachment. This paper reviews theory and research that lays groundwork for a framework for conceptualizing treatment needs for attachment disordered children. Two cases of conjoint work with parents and their latency age sons are presented. The treatment cases highlight the importance of work to increase parents' reflective functioning capacities and the need to challenge children's defensively excluded early internal working models of self and caregivers.
Internet Network Resource Information Model
Institute of Scientific and Technical Information of China (English)
陈传峰; 李增智; 唐亚哲; 刘康平
2002-01-01
The foundation of any network management systens is a database that con-tains information about the network resources relevant to the management tasks. A networkinformation model is an abstraction of network resources, including both managed resources andmanaging resources. In the SNMP-based management framework, management information isdefined almost exclusively from a "device" viewpoint, namely, managing a network is equiva-lent to managing a collection of individual nodes. Aiming at making use of recent advances indistributed computing and in object-oriented analysis and design, the Internet management ar-chitecture can also be based on the Open Distributed Processing Reference Model (RM-ODP).The purpose of this article is to provide an Internet Network Resource Information Model.First, a layered management information architecture will be discussed. Then the Internetnetwork resource information model is presented. The information model is specified usingObject-Z.
Complex Networks in Psychological Models
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.
Sturt, Patrick; Costa, Fabrizio; Lombardo, Vincenzo; Frasconi, Paolo
2003-06-01
One of the central problems in the study of human language processing is ambiguity resolution: how do people resolve the extremely pervasive ambiguity of the language they encounter? One possible answer to this question is suggested by experience-based models, which claim that people typically resolve ambiguities in a way which has been successful in the past. In order to determine the course of action that has been "successful in the past" when faced with some ambiguity, it is necessary to generalize over past experience. In this paper, we will present a computational experience-based model, which learns to generalize over linguistic experience from exposure to syntactic structures in a corpus. The model is a hybrid system, which uses symbolic grammars to build and represent syntactic structures, and neural networks to rank these structures on the basis of its experience. We use a dynamic grammar, which provides a very tight correspondence between grammatical derivations and incremental processing, and recursive neural networks, which are able to deal with the complex hierarchical structures produced by the grammar. We demonstrate that the model reproduces a number of the structural preferences found in the experimental psycholinguistics literature, and also performs well on unrestricted text.
Features and heterogeneities in growing network models
Ferretti, Luca; Yang, Bin; Marmorini, Giacomo; Bianconi, Ginestra
2011-01-01
Many complex networks from the World-Wide-Web to biological networks are growing taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document as personal page, thematic website, news, blog, search engine, social network, ect. or the classification of a gene in a functional module. Moreover the feature of a node can be a continuous variable such as the position of a node in the embedding space. In order to account for these properties, in this paper we provide a generalization of growing network models with preferential attachment that includes the effect of heterogeneous features of the nodes. The main effect of heterogeneity is the emergence of an "effective fitness" for each class of nodes, determining the rate at which nodes acquire new links. Beyond the degree distribution, in this paper we give a full characterization of the other relevant properties of the model. We evaluate the clustering coefficient and show ...
2008-12-01
well, then a Euclidean distance would be appropriate. The quadratic assignment procedure ( QAP ) (Krackhardt, 1987) could be used to compare the...Networks. Journal of Applied Psychology, 71(1): 50-55. Krackhardt, D. (1987). QAP Partialling as a Test of Spuriousness. Social Networks, 9, 171-186
Analysis of feedback loops and robustness in network evolution based on Boolean models
Directory of Open Access Journals (Sweden)
Cho Kwang-Hyun
2007-11-01
Full Text Available Abstract Background Many biological networks such as protein-protein interaction networks, signaling networks, and metabolic networks have topological characteristics of a scale-free degree distribution. Preferential attachment has been considered as the most plausible evolutionary growth model to explain this topological property. Although various studies have been undertaken to investigate the structural characteristics of a network obtained using this growth model, its dynamical characteristics have received relatively less attention. Results In this paper, we focus on the robustness of a network that is acquired during its evolutionary process. Through simulations using Boolean network models, we found that preferential attachment increases the number of coupled feedback loops in the course of network evolution. Whereas, if networks evolve to have more coupled feedback loops rather than following preferential attachment, the resulting networks are more robust than those obtained through preferential attachment, although both of them have similar degree distributions. Conclusion The presented analysis demonstrates that coupled feedback loops may play an important role in network evolution to acquire robustness. The result also provides a hint as to why various biological networks have evolved to contain a number of coupled feedback loops.
A mixing evolution model for bidirectional microblog user networks
Yuan, Wei-Guo; Liu, Yun
2015-08-01
Microblogs have been widely used as a new form of online social networking. Based on the user profile data collected from Sina Weibo, we find that the number of microblog user bidirectional friends approximately corresponds with the lognormal distribution. We then build two microblog user networks with real bidirectional relationships, both of which have not only small-world and scale-free but also some special properties, such as double power-law degree distribution, disassortative network, hierarchical and rich-club structure. Moreover, by detecting the community structures of the two real networks, we find both of their community scales follow an exponential distribution. Based on the empirical analysis, we present a novel evolution network model with mixed connection rules, including lognormal fitness preferential and random attachment, nearest neighbor interconnected in the same community, and global random associations in different communities. The simulation results show that our model is consistent with real network in many topology features.
Assortative model for social networks
Catanzaro, Michele; Caldarelli, Guido; Pietronero, Luciano
2004-09-01
In this Brief Report we present a version of a network growth model, generalized in order to describe the behavior of social networks. The case of study considered is the preprint archive at cul.arxiv.org. Each node corresponds to a scientist, and a link is present whenever two authors wrote a paper together. This graph is a nice example of degree-assortative network, that is, to say a network where sites with similar degree are connected to each other. The model presented is one of the few able to reproduce such behavior, giving some insight on the microscopic dynamics at the basis of the graph structure.
Developing Personal Network Business Models
DEFF Research Database (Denmark)
Saugstrup, Dan; Henten, Anders
2006-01-01
on the 'state of the art' in the field of business modeling. Furthermore, the paper suggests three generic business models for PNs: a service oriented model, a self-organized model, and a combination model. Finally, examples of relevant services and applications in relation to three different cases......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...... are presented and analyzed in light of business modeling of PN....
Ayoub, Catherine C; Fischer, Kurt W; O'Connor, Erin E
2003-06-01
This article offers a developmental model of attachment theory rooted in dynamic skill theory. Dynamic skill theory is based on the assumption that people do not have integrated, fundamentally logical minds, but instead develop along naturally fractionated strands of a web. Contrary to traditional interpretations of attachment theory, dynamic skill theory proposes that individuals continue to modify their working models of attachments throughout the lifespan. In particular, working models of close relationships develop systematically through a series of skill levels such that the skills vary across strands in the web and will not automatically form a unified whole. The continual modification of working models is particularly pertinent for the consequences of hidden family violence for individuals' development. Dynamic skill theory shows how trauma can produce not developmental delay or fixation, as has been proposed previously, but instead the construction of advanced, complex working models.
Network models in anatomical systems.
Esteve-Altava, Borja; Marugán-Lobón, Jesús; Botella, Héctor; Rasskin-Gutman, Diego
2011-01-01
Network theory has been extensively used to model the underlying structure of biological processes. From genetics to ecology, network thinking is changing our understanding of complex systems, specifically how their internal structure determines their overall behavior. Concepts such as hubs, scale-free or small-world networks, common in the complexity literature, are now used more and more in sociology, neurosciences, as well as other anthropological fields. Even though the use of network models is nowadays so widely applied, few attempts have been carried out to enrich our understanding in the classical morphological sciences such as in comparative anatomy or physical anthropology. The purpose of this article is to introduce the usage of network tools in morphology; specifically by building anatomical networks, dealing with the most common analyses and problems, and interpreting their outcome.
Telecommunications network modelling, planning and design
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.
Campus network security model study
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.
Briere, John; Runtz, Marsha; Eadie, Erin; Bigras, Noémie; Godbout, Natacha
2017-03-09
Based on attachment theory, we hypothesized that self-reported childhood experiences of disengaged parenting (DP) would predict adults' psychological symptoms even more than, on average, childhood sexual, physical, or psychological abuse. In a large (N=640) university sample, bootstrapped multiple regression analyses indicated that although various forms of child maltreatment were correlated with symptomatology at the univariate level, DP was the primary multivariate predictor. Structural equation modeling indicated significant direct paths from (a) DP to both nonsexual child maltreatment and sexual abuse, (b) DP and nonsexual child maltreatment to insecure attachment, and (c) sexual abuse and insecure attachment to symptomatology. There were significant indirect effects of DP on psychological symptoms through sexual and nonsexual abuse, as well as through attachment. These results suggest that although child abuse has direct and indirect impacts on psychological symptoms, exposure to DP may be especially detrimental, both by increasing the risk of child abuse and by virtue of its impacts on attachment insecurity. They also support the potential use of attachment-oriented intervention in the treatment of adults maltreated as children.
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.
Neural network modeling of emotion
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.
Nonequilibrium model on Apollonian networks.
Lima, F W S; Moreira, André A; Araújo, Ascânio D
2012-11-01
We investigate the majority-vote model with two states (-1,+1) and a noise parameter q on Apollonian networks. The main result found here is the presence of the phase transition as a function of the noise parameter q. Previous results on the Ising model in Apollonian networks have reported no presence of a phase transition. We also studied the effect of redirecting a fraction p of the links of the network. By means of Monte Carlo simulations, we obtained the exponent ratio γ/ν, β/ν, and 1/ν for several values of rewiring probability p. The critical noise q{c} and U were also calculated. Therefore, the results presented here demonstrate that the majority-vote model belongs to a different universality class than equilibrium Ising model on Apollonian network.
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.
A Tractable Complex Network Model based on the Stochastic Mean-field Model of Distance
Aldous, David J.
2003-01-01
Much recent research activity has been devoted to empirical study and theoretical models of complex networks (random graphs) with three qualitative features: power-law degree distribution, local clustering of edges, and small diameter. We point out a new (in this context) platform for such models -- the stochastic mean-field model of distance -- and within this platform study a simple two-parameter proportional attachment model. The model is mathematicallly natural, permits a wide variety of ...
Algebraic Statistics for Network Models
2014-02-19
AFRL-OSR-VA-TR-2014-0070 (DARPA) Algebraic Statistics for Network Models SONJA PETROVIC PENNSYLVANIA STATE UNIVERSITY 02/19/2014 Final Report...DARPA GRAPHS Phase I Algebraic Statistics for Network Models FA9550-12-1-0392 Sonja Petrović petrovic@psu.edu1 Department of Statistics Pennsylvania...Department of Statistics, Heinz College , Machine Learning Department, Cylab Carnegie Mellon University 1. Abstract This project focused on the family of
Attachment, mastery, and interdependence: a model of parenting processes.
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.
Attachment, social network size and patterns of social exchange in later life
Fiori, K.; Consedine, N.S.; Merz, E.-M.
2011-01-01
Dispositional styles of relating to significant others—adult attachment—are linked to social relatedness across the life span. Prior work has concentrated on the receipt of perceived social support and not examined links between attachment and patterns of exchange. Data from a sample of older adults
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…
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.
Advances in theoretical models of network science
Institute of Scientific and Technical Information of China (English)
FANG Jin-qing; BI Qiao; LI Yong
2007-01-01
In this review article, we will summarize the main advances in network science investigated by the CIAE Group of Complex Network in this field. Several theoretical models of network science were proposed and their topological and dynamical properties are reviewed and compared with the other models. Our models mainly include a harmonious unifying hybrid preferential model, a large unifying hybrid network model, a quantum interference network, a hexagonal nanowire network, and a small-world network with the same degree. The models above reveal some new phenomena and findings, which are useful for deeply understanding and investigating complex networks and their applications.
Structure learning for Bayesian networks as models of biological networks.
Larjo, Antti; Shmulevich, Ilya; Lähdesmäki, Harri
2013-01-01
Bayesian networks are probabilistic graphical models suitable for modeling several kinds of biological systems. In many cases, the structure of a Bayesian network represents causal molecular mechanisms or statistical associations of the underlying system. Bayesian networks have been applied, for example, for inferring the structure of many biological networks from experimental data. We present some recent progress in learning the structure of static and dynamic Bayesian networks from data.
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…
Simple One-Dimensional Quantum-Mechanical Model for a Particle Attached to a Surface
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…
Simple One-Dimensional Quantum-Mechanical Model for a Particle Attached to a Surface
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…
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.
Working models of attachment and reactions to different forms of caregiving from romantic partners.
Simpson, Jeffry A; Winterheld, Heike A; Rholes, W Steven; Oriña, M Minda
2007-09-01
Inspired by attachment theory, the authors tested a series of theoretically derived predictions about connections between attachment working models (attachment to one's parents assessed by the Adult Attachment Interview; M. Main & R. Goldwyn, 1994) and the effectiveness of specific types of caregiving spontaneously displayed by dating partners during a stressful conflict-resolution discussion. Each partner first completed the Adult Attachment Interview. One week later, each couple was videotaped while they tried to resolve a current problem in their relationship. Trained observers then rated each interaction for the degree to which (a) emotional, instrumental, and physical caregiving behaviors were displayed; (b) care recipients appeared calmed by their partners' caregiving attempts; and (c) each partner appeared distressed during the discussion. Individuals who had more secure representations of their parents were rated as being more calmed if/when their partners provided greater emotional care, especially if they were rated as more distressed. Conversely, individuals who had more insecure (dismissive) representations of their parents reacted more favorably to instrumental caregiving behaviors from their partners, especially if they were more distressed. The broader theoretical implications of these findings are discussed.
Theoretical modelling of a beam with attached spring-mass-damper system
Directory of Open Access Journals (Sweden)
Azmirul Mohd Rozlan Syaiful
2017-01-01
Full Text Available Vibrations are always undesirable, wasting energy besides producing noise. In this case, beams which are prominent component in most engineering having no exemption from the vibration effect when imposed by dynamic loading. One of the approach to attenuate vibration of a structure is by having a spring-mass-damper (SMD system or typically known as vibration neutralizer attached to the vibrating structure. This method is more promising as it does not contribute significant additional energy to the structure. The work presented in this paper describes the frequency response (FRF of a simply supported beam with an attached SMD system. A mathematical model of a beam was at first developed in the study which was further derived to include the attachment of SMD system. In order to transform the derived equations into a form of graph that can be analysed, Matlab® software was used. The outcome from Matlab® shows that the attachment of SMD onto beam attenuates its vibration significantly. The result also displays a good resemblance FRF when compared with numerical finite element analysis of Ansys®. It is expected that the theoretical derivation demonstrated in this paper provide a helpful reference to future researchers who endeavour to find equations of a simply supported beam with an attached SMD system as well as for a vibration control study.
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.
A new transient network model for associative polymer networks
Wientjes, R.H.W.; Jongschaap, R.J.J.; Duits, M.H.G.; Mellema, J.
1999-01-01
A new model for the linear viscoelastic behavior of polymer networks is developed. In this model the polymer system is described as a network of spring segments connected via sticky points (as in the Lodge model). [Lodge, A. S., “A network theory of flow birefringence and stress in concentrated poly
Community Attachment and Satisfaction: The Role of a Community's Social Network Structure
Crowe, Jessica
2010-01-01
This paper links the micro and macro levels of analysis by examining how different aspects of community sentiment are affected by one's personal ties to the community compared with the organizational network structure of the community. Using data collected from residents of six communities in Washington State, network analysis combined with…
A Stochastic Evolutionary Growth Model for Social Networks
Fenner, T; Loizou, G; Roussos, G; Fenner, Trevor; Levene, Mark; Loizou, George; Roussos, George
2006-01-01
We present a stochastic model for a social network, where new actors may join the network, existing actors may become inactive and, at a later stage, reactivate themselves. Our model captures the evolution of the network, assuming that actors attain new relations or become active according to the preferential attachment rule. We derive the mean-field equations for this stochastic model and show that, asymptotically, the distribution of actors obeys a power-law distribution. In particular, the model applies to social networks such as wireless local area networks, where users connect to access-points, and peer-to-peer networks where users connect to each other. As a proof of concept, we demonstrate the validity of our model empirically by analysing a public log containing traces from a wireless network at Dartmouth College over a period of three years. Analysing the data processed according to our model, we demonstrate that the distribution of user accesses is asymptotically a power-law distribution.
Modified DM Models for Aging Networks Based on Neighborhood Connectivity
Institute of Scientific and Technical Information of China (English)
WEI Du-Qu; LIN Min; LUO Xiao-Shu; WANG Gang; ZOU Yan-Li; CHEN Tian-Lun
2008-01-01
Two modified Dorogovtsev-Mendes (DM) models of aging networks based on the dynamics of connecting nearest-neighbors are introduced. One edge of the new site is connected to the old site with probabilityekt-αas in the DM's model, where the degree and age of the old site are k and t, respectively. We consider two eases, I.e. The other edges of the new site attaching to the nearest-neighbors of the old site with uniform and degree connectivity probability, respectively. The network structure changes with an increase of aging exponent α. It is found that the networks can produce scale-free degree distributions with small-world properties. And the different connectivity probabilities lead to the different properties of the networks.
Sigling, H.O.
2009-01-01
This thesis describes studies into the rat as an animal model for attachment, along the lines of Bowlby's attachment theory. First, the relation between attachment and human psychopathology is reviewed. The conclusion is that psychopathology is more frequent in insecure attached persons and that the
Uncertainty Modeling Based on Bayesian Network in Ontology Mapping
Institute of Scientific and Technical Information of China (English)
LI Yuhua; LIU Tao; SUN Xiaolin
2006-01-01
How to deal with uncertainty is crucial in exact concept mapping between ontologies. This paper presents a new framework on modeling uncertainty in ontologies based on bayesian networks (BN). In our approach, ontology Web language (OWL) is extended to add probabilistic markups for attaching probability information, the source and target ontologies (expressed by patulous OWL) are translated into bayesian networks (BNs), the mapping between the two ontologies can be digged out by constructing the conditional probability tables (CPTs) of the BN using a improved algorithm named I-IPFP based on iterative proportional fitting procedure (IPFP). The basic idea of this framework and algorithm are validated by positive results from computer experiments.
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 repor....... Working through these cases, students will learn to manage and evaluate realistic intelligence accounts.......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......, 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...
Persistence in a single species CSTR model with suspended flocs and wall attached biofilms.
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.
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.
CNEM: Cluster Based Network Evolution Model
Directory of Open Access Journals (Sweden)
Sarwat Nizamani
2015-01-01
Full Text Available This paper presents a network evolution model, which is based on the clustering approach. The proposed approach depicts the network evolution, which demonstrates the network formation from individual nodes to fully evolved network. An agglomerative hierarchical clustering method is applied for the evolution of network. In the paper, we present three case studies which show the evolution of the networks from the scratch. These case studies include: terrorist network of 9/11 incidents, terrorist network of WMD (Weapons Mass Destruction plot against France and a network of tweets discussing a topic. The network of 9/11 is also used for evaluation, using other social network analysis methods which show that the clusters created using the proposed model of network evolution are of good quality, thus the proposed method can be used by law enforcement agencies in order to further investigate the criminal networks
Radius model of convex vertical curve of freeway based on attachment coefficient
Institute of Scientific and Technical Information of China (English)
LI Song-ling; PEI Yu-long
2008-01-01
A longitudinal slope brake model was established for the radius calculation of vertical curve of free-way through analyzing the dynamics of brake-running of vehicles running on the longitudinal slope road section. To satisfy the requirement of sight distance, a relation model was established for the attachment coefficient and the convex vertical curve radius. Using MATLAB simulation technique, the convex vertical curve radius at different attachment conditions was calculated accurately and a three-dimensional figure was drawn to describe the relation between the adhesive coefficient, the driving velocity and the radius of vertical curve. The correlation between the convex vertical curve radius and the adhesive coefficient was further analyzed and compared with National Technical Standards. The suggested radius of vertical curve was then put forward to provide a theoretical platform for the security design of the convex vertical curve.
Biological transportation networks: Modeling and simulation
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.
Ising model for distribution networks
Hooyberghs, H; Giuraniuc, C; Van Schaeybroeck, B; Indekeu, J O
2012-01-01
An elementary Ising spin model is proposed for demonstrating cascading failures (break-downs, blackouts, collapses, avalanches, ...) that can occur in realistic networks for distribution and delivery by suppliers to consumers. A ferromagnetic Hamiltonian with quenched random fields results from policies that maximize the gap between demand and delivery. Such policies can arise in a competitive market where firms artificially create new demand, or in a solidary environment where too high a demand cannot reasonably be met. Network failure in the context of a policy of solidarity is possible when an initially active state becomes metastable and decays to a stable inactive state. We explore the characteristics of the demand and delivery, as well as the topological properties, which make the distribution network susceptible of failure. An effective temperature is defined, which governs the strength of the activity fluctuations which can induce a collapse. Numerical results, obtained by Monte Carlo simulations of t...
Thompson-Brenner, Heather
2014-06-01
Tasca and Balfour have done admirable work highlighting the importance of attachment security in the psychopathology of eating disorders (EDs), and their contributions are extremely valuable. For their points to be fully appreciated by the research and treatment-research communities, additional data are needed in key areas. Research is needed to help clarify the relative roles and cause-and-effect relationships between attachment insecurity, reflective functioning, and emotion regulation in the development and maintenance of EDs. Tasca and Balfour furthermore call their model "psychodynamic," and call for psychodynamically informed treatment for patients with attachment insecurity. For this call to be heeded, additional research is needed to examine whether the unique elements of psychodynamic psychotherapy have particular benefit for patients with insecure attachment styles. The unique psychodynamic elements considered in this comment include a therapeutic focus on reflective functioning, the patient's developmental history, the "unconscious," and the transference and countertransference. The utility of a non-directive (or patient-directed) therapeutic process is also considered. Investigation of these treatment issues could be extremely useful to practitioners and patients alike.
Nonparametric Bayesian Modeling of Complex Networks
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Mørup, Morten
2013-01-01
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...... for complex networks can be derived and point out relevant literature....
Simple one-dimensional quantum-mechanical model for a particle attached to a surface
Energy Technology Data Exchange (ETDEWEB)
Fernandez, Francisco M, E-mail: fernande@quimica.unlp.edu.a [INIFTA (UNLP, CCT La Plata-CONICET), Division Quimica Teorica, Blvd 113 S/N, Sucursal 4, Casilla de Correo 16, 1900 La Plata (Argentina)
2010-07-15
We present a simple one-dimensional quantum-mechanical model for a particle attached to a surface. It leads to the Schroedinger 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 as well as the asymptotic behaviour of the eigenvalues. We calculate the zero-point energy for model parameters corresponding to H adsorbed on Pd(1 0 0). The model is suitable for an advanced undergraduate or graduate course on quantum mechanics.
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.
Mathematical Modelling Plant Signalling Networks
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.
Bell, David C
2009-12-01
John Bowlby hypothesized an attachment system that interacts with caregiving, exploration, and fear systems in the brain, with a particular emphasis on fear. Neurobiological research confirms many of his hypotheses and also raises some new questions. A psychological model based on this neurobiological research is presented here. The model extends conventional attachment theory by describing additional attachment processes independent of fear. In this model, the attachment elements of trust, openness, and dependence interact with the caregiving elements of caring, empathy, and responsibility.
Bell, David C.
2009-01-01
John Bowlby hypothesized an attachment system that interacts with caregiving, exploration, and fear systems in the brain, with a particular emphasis on fear. Neurobiological research confirms many of his hypotheses and also raises some new questions. A psychological model based on this neurobiological research is presented here. The model extends conventional attachment theory by describing additional attachment processes independent of fear. In this model, the attachment elements of trust, o...
Random Boolean network models and the yeast transcriptional network
Kauffman, Stuart; Peterson, Carsten; Samuelsson, Björn; Troein, Carl
2003-12-01
The recently measured yeast transcriptional network is analyzed in terms of simplified Boolean network models, with the aim of determining feasible rule structures, given the requirement of stable solutions of the generated Boolean networks. We find that for ensembles of generated models, those with canalyzing Boolean rules are remarkably stable, whereas those with random Boolean rules are only marginally stable. Furthermore, substantial parts of the generated networks are frozen, in the sense that they reach the same state regardless of initial state. Thus, our ensemble approach suggests that the yeast network shows highly ordered dynamics.
Traxler, Matthew J
2007-07-01
An eye-movement-monitoring experiment tested readers' responses to sentences containing relative clauses that could be attached to one or both of two preceding nouns. Previous experiments with such sentences have indicated that globally ambiguous relative clauses are processed more quickly than are determinately attached relative clauses. Central to the present research, a recent study (Swets, Desmet, Hambrick, & Ferreira, 2007) showed that offline preferences for such sentences differ as a function of working memory capacity. Specifically, both English and Dutch participants' preference for the second of two nouns as the host for the relative clause increased as their working memory capacity increased. In the present study, readers' working memory capacity was measured, and eye movements were monitored. Hierarchical linear modeling was used to determine whether working memory capacity moderated readers' online processing performance. The modeling indicated that determinately attached sentences were harder to process than globally ambiguous sentences, that working memory did not affect processing of the relative clause itself, but that working memory did moderate how easy it was to integrate the relative clause with the preceding sentence context. Specifically, in contrast with the offline results from Swets and colleagues' study, readers with higher working memory capacity were more likely to prefer the first noun over the second noun as the host for the relative clause.
Heresi Milad, Eliana; Rivera Ottenberger, Diana; Huepe Artigas, David
2014-01-01
This study aimed to explore the associations among attachment system type, sexual satisfaction, and marital satisfaction in adult couples in stable relationships. Participants were 294 couples between the ages of 20 and 70 years who answered self-administered questionnaires. Hierarchical linear modeling revealed that the anxiety and avoidance, sexual satisfaction, and marital satisfaction dimensions were closely related. Specifically, the avoidance dimension, but not the anxiety dimension, corresponded to lower levels of sexual and marital satisfaction. Moreover, for the sexual satisfaction variable, an interaction effect was observed between the gender of the actor and avoidance of the partner, which was observed only in men. In the marital satisfaction dimension, effects were apparent only at the individual level; a positive relation was found between the number of years spent living together and greater contentment with the relationship. These results confirm the hypothetical association between attachment and sexual and marital satisfaction and demonstrate the relevance of methodologies when the unit of analysis is the couple.
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.
Plant Growth Models Using Artificial Neural Networks
Bubenheim, David
1997-01-01
In this paper, we descrive our motivation and approach to devloping models and the neural network architecture. Initial use of the artificial neural network for modeling the single plant process of transpiration is presented.
Generalization performance of regularized neural network models
DEFF Research Database (Denmark)
Larsen, Jan; Hansen, Lars Kai
1994-01-01
Architecture optimization is a fundamental problem of neural network modeling. The optimal architecture is defined as the one which minimizes the generalization error. This paper addresses estimation of the generalization performance of regularized, complete neural network models. Regularization...
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…
Scalable Capacity Bounding Models for Wireless Networks
Du, Jinfeng; Medard, Muriel; Xiao, Ming; Skoglund, Mikael
2014-01-01
The framework of network equivalence theory developed by Koetter et al. introduces a notion of channel emulation to construct noiseless networks as upper (resp. lower) bounding models, which can be used to calculate the outer (resp. inner) bounds for the capacity region of the original noisy network. Based on the network equivalence framework, this paper presents scalable upper and lower bounding models for wireless networks with potentially many nodes. A channel decoupling method is proposed...
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.
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.
Preferential survival in models of complex ad hoc networks
Kong, Joseph S.; Roychowdhury, Vwani P.
2008-05-01
There has been a rich interplay in recent years between (i) empirical investigations of real-world dynamic networks, (ii) analytical modeling of the microscopic mechanisms that drive the emergence of such networks, and (iii) harnessing of these mechanisms to either manipulate existing networks, or engineer new networks for specific tasks. We continue in this vein, and study the deletion phenomenon in the web by the following two different sets of websites (each comprising more than 150,000 pages) over a one-year period. Empirical data show that there is a significant deletion component in the underlying web networks, but the deletion process is not uniform. This motivates us to introduce a new mechanism of preferential survival (PS), where nodes are removed according to the degree-dependent deletion kernel, D(k)∝k, with α≥0. We use the mean-field rate equation approach to study a general dynamic model driven by Preferential Attachment (PA), Double PA (DPA), and a tunable PS (i.e., with any α>0), where c nodes ( cdynamics reported in this work can be used to design and engineer stable ad hoc networks and explain the stability of the power-law exponents observed in real-world networks.
A Tractable Complex Network Model Based onthe Stochastic Mean-Field Model of Distance
Aldous, David J.
Much recent research activity has been devoted to empirical study and theoretical models of complex networks (random graphs) possessing three qualitative features: power-law degree distributions, local clustering, and slowly-growing diameter. We point out a new (in this context) platform for such models - the stochastic mean-field model of distances - and within this platform study a simple two-parameter proportional attachment (or copying) model. The model is mathematically natural, permits a wide variety of explicit calculations, has the desired three qualitative features, and fits the complete range of degree scaling exponents and clustering parameters; in these respects it compares favorably with existing models.
Kinematic control model for light weighting mechanism of excavator attached to rotary working device
Lee, Choongho; Lee, Sangsik; Cho, Youngtae; Im, Kwanghee
2007-07-01
An excavator attached to a rotary working device is used principally in industrial work. In particular, they are used in the building industry and public works. This research concerns the rotary automatic control of an excavator attached to a rotary working device. The drilling excavator is used in the crushed stone industry and the dragline excavation system is employed in the construction industry. Cases of the excavator's use in agriculture have been the subject of a relatively few studies. However, several modified excavator designs have been released in recent years. Applied excavator products are primarily utilized under relatively severe environmental conditions. In this study, we focus on the uses of an excavator in agricultural work. The readjustment of arable land and the reduction of weeds in agricultural applications both require skilled hand-operation of the machines. As such workers have been shown to develop problems with regard to working posture and proper positioning while laboring, a more appropriate excavator design may prove useful in such applications. Therefore, this pilot study is focused primarily on the rotary automatic control of an excavator attached to a rotary working device, and will adapt smart materials to the excavator applications for developing redesigned excavator having a light weight. The excavator is attached to a rotary working device on a normal excavator's platform, and the position and orientation of the mechanism between the joints and the rotary working device was determined. Simulations were also conducted of the excavator attached to the rotary working device. With an eye toward the use of this mechanism in agricultural work, we also conducted a set of kinematic analyses. The rotary working device was assumed to have 3 DOF, and was comprised of 5 links. Computer simulations were also conducted using the developed excavator model. In order to adequately evaluate the possible performance of such a system, kinetic
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.
Ditching Tests of a 1/18-Scale Model of the Lockheed Constellation Airplane with Speedpak Attached
Fisher, Lloyd J.; Thompson, William C.
1949-01-01
Results of previous model ditching tests of the Lockheed Constellation airplane are reported. Further model tests have been made to determine the probable ditching characteristics and the proper ditching technique for the airplane with the Speedpak attached. This paper presents the results of these tests. Design information was furnished by the Lockheed Aircraft Corporation. A three-vies drawing of the airplane with the Speedpak attached is shown. The tests were made in calm water at the Langley tank no.2 monorail.
MODELS FOR NETWORK DYNAMICS - A MARKOVIAN FRAMEWORK
LEENDERS, RTAJ
1995-01-01
A question not very often addressed in social network analysis relates to network dynamics and focuses on how networks arise and change. It alludes to the idea that ties do not arise or vanish randomly, but (partly) as a consequence of human behavior and preferences. Statistical models for modeling
Modelling delay propagation within an airport network
Pyrgiotis, N.; Malone, K.M.; Odoni, A.
2013-01-01
We describe an analytical queuing and network decomposition model developed to study the complex phenomenon of the propagation of delays within a large network of major airports. The Approximate Network Delays (AND) model computes the delays due to local congestion at individual airports and capture
Modelling delay propagation within an airport network
Pyrgiotis, N.; Malone, K.M.; Odoni, A.
2013-01-01
We describe an analytical queuing and network decomposition model developed to study the complex phenomenon of the propagation of delays within a large network of major airports. The Approximate Network Delays (AND) model computes the delays due to local congestion at individual airports and
A system dynamics model for communications networks
Awcock, A. J.; King, T. E. G.
1985-09-01
An abstract model of a communications network in system dynamics terminology is developed as implementation of this model by a FORTRAN program package developed at RSRE is discussed. The result of this work is a high-level simulation package in which the performance of adaptive routing algorithms and other network controls may be assessed for a network of arbitrary topology.
Gene duplication models for directed networks with limits on growth
Enemark, Jakob; Sneppen, Kim
2007-11-01
Background: Duplication of genes is important for evolution of molecular networks. Many authors have therefore considered gene duplication as a driving force in shaping the topology of molecular networks. In particular it has been noted that growth via duplication would act as an implicit means of preferential attachment, and thereby provide the observed broad degree distributions of molecular networks. Results: We extend current models of gene duplication and rewiring by including directions and the fact that molecular networks are not a result of unidirectional growth. We introduce upstream sites and downstream shapes to quantify potential links during duplication and rewiring. We find that this in itself generates the observed scaling of transcription factors for genome sites in prokaryotes. The dynamical model can generate a scale-free degree distribution, p(k)\\propto 1/k^{\\gamma } , with exponent γ = 1 in the non-growing case, and with γ>1 when the network is growing. Conclusions: We find that duplication of genes followed by substantial recombination of upstream regions could generate features of genetic regulatory networks. Our steady state degree distribution is however too broad to be consistent with data, thereby suggesting that selective pruning acts as a main additional constraint on duplicated genes. Our analysis shows that gene duplication can only be a main cause for the observed broad degree distributions if there are also substantial recombinations between upstream regions of genes.
Network models in epidemiology: an overview
Lloyd, Alun L.; Valeika, Steve
In this chapter we shall discuss the development and use of network models in epidemiology. While network models have long been discussed in the theoretical epidemiology literature, they have recently received a large amount of attention amongst the statistical physics community. This has been fueled by the desire to better understand the structure of social and large-scale technological networks, and the increases in computational power that have made the simulation of reasonably-sized network models a feasible proposition. A main aim of this review is to bridge the epidemiologic and statistical physics approaches to network models for infectious diseases, highlighting the important contributions made by both research communities.
Modeling gene regulatory networks: A network simplification algorithm
Ferreira, Luiz Henrique O.; de Castro, Maria Clicia S.; da Silva, Fabricio A. B.
2016-12-01
Boolean networks have been used for some time to model Gene Regulatory Networks (GRNs), which describe cell functions. Those models can help biologists to make predictions, prognosis and even specialized treatment when some disturb on the GRN lead to a sick condition. However, the amount of information related to a GRN can be huge, making the task of inferring its boolean network representation quite a challenge. The method shown here takes into account information about the interactome to build a network, where each node represents a protein, and uses the entropy of each node as a key to reduce the size of the network, allowing the further inferring process to focus only on the main protein hubs, the ones with most potential to interfere in overall network behavior.
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.
An evolutionary model of social networks
Ludwig, M.; Abell, P.
2007-07-01
Social networks in communities, markets, and societies self-organise through the interactions of many individuals. In this paper we use a well-known mechanism of social interactions — the balance of sentiment in triadic relations — to describe the development of social networks. Our model contrasts with many existing network models, in that people not only establish but also break up relations whilst the network evolves. The procedure generates several interesting network features such as a variety of degree distributions and degree correlations. The resulting network converges under certain conditions to a steady critical state where temporal disruptions in triangles follow a power-law distribution.
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
Dakanalis, Antonios; Timko, C Alix; Zanetti, M Assunta; Rinaldi, Lucio; Prunas, Antonio; Carrà, Giuseppe; Riva, Giuseppe; Clerici, Massimo
2014-01-30
Although 96-100% of individuals with eating disorders (EDs) report insecure attachment, the specific mechanisms by which adult insecure attachment dimensions affect ED symptomatology remain to date largely unknown. This study examined maladaptive perfectionism as both a mediator and a moderator of the relationship between insecure attachment (anxiety and avoidance) and ED symptomatology in a clinical, treatment seeking, sample. Insecure anxious and avoidant attachment, maladaptive perfectionism, and ED symptomatology were assessed in 403 participants from three medium size specialized care centres for EDs in Italy. Structural equation modeling indicated that maladaptive perfectionism served as mediator between both insecure attachment patterns and ED symptomatology. It also interacted with insecure attachment to predict higher levels of ED symptoms - highlighting the importance of both insecure attachment patterns and maladaptive aspects of perfectionism as treatment targets. Multiple-group comparison analysis did not reveal differences across diagnostic groups (AN, BN, EDNOS) in mediating, main and interaction effects of perfectionism. These findings are consistent with recent discussions on the classification and treatment of EDs that have highlighted similarities between ED diagnostic groups and could be viewed through the lens of the Trans-theoretical Model of EDs. Implications for future research and intervention are discussed.
Random Graphs Associated to Some Discrete and Continuous Time Preferential Attachment Models
Pachon, Angelica; Polito, Federico; Sacerdote, Laura
2016-03-01
We give a common description of Simon, Barabási-Albert, II-PA and Price growth models, by introducing suitable random graph processes with preferential attachment mechanisms. Through the II-PA model, we prove the conditions for which the asymptotic degree distribution of the Barabási-Albert model coincides with the asymptotic in-degree distribution of the Simon model. Furthermore, we show that when the number of vertices in the Simon model (with parameter α ) goes to infinity, a portion of them behave as a Yule model with parameters (λ ,β ) = (1-α ,1), and through this relation we explain why asymptotic properties of a random vertex in Simon model, coincide with the asymptotic properties of a random genus in Yule model. As a by-product of our analysis, we prove the explicit expression of the in-degree distribution for the II-PA model, given without proof in Newman (Contemp Phys 46:323-351, 2005). References to traditional and recent applications of the these models are also discussed.
A dynamic network model for interbank market
Xu, Tao; He, Jianmin; Li, Shouwei
2016-12-01
In this paper, a dynamic network model based on agent behavior is introduced to explain the formation mechanism of interbank market network. We investigate the impact of credit lending preference on interbank market network topology, the evolution of interbank market network and stability of interbank market. Experimental results demonstrate that interbank market network is a small-world network and cumulative degree follows the power-law distribution. We find that the interbank network structure keeps dynamic stability in the network evolution process. With the increase of bank credit lending preference, network clustering coefficient increases and average shortest path length decreases monotonously, which improves the stability of the network structure. External shocks are main threats for the interbank market and the reduction of bank external investment yield rate and deposits fluctuations contribute to improve the resilience of the banking system.
Modeling Diagnostic Assessments with Bayesian Networks
Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego
2007-01-01
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Modeling Diagnostic Assessments with Bayesian Networks
Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego
2007-01-01
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Bayesian Network Webserver: a comprehensive tool for biological network modeling.
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.
What is preferential to preferential attachment?
Small, Michael; Stemler, Thomas
2013-01-01
Preferential attachment --- where new nodes are added and attached to existing nodes with probability proportional to the existing nodes' degree --- has become the standard growth model for scale-free networks, where the asymptotic probability of a node having degree $k$ is proportional to $k^{-\\gamma}$. However, the motivation for this model is entirely {\\em ad hoc}. We use exact likelihood arguments and show that the optimal way to build a scale-free network is to preferentially attach to low degree nodes. Asymptotically, the optimal strategy is to attach the new node to one of the nodes of degree $k$ (in a network with $N$ nodes) with probability proportional to $\\frac{1}{N+\\zeta(\\gamma)(k+1)^\\gamma}$. The algorithm we propose to do this can be employed to generate optimally scale-free networks (maximum likelihood realisations) as well as a random sampling of the space of all scale-free networks with a given degree exponent $\\gamma$. While we focus on scale free networks, these methods can be applied to a ...
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.
Bayesian estimation of the network autocorrelation model
Dittrich, D.; Leenders, R.T.A.J.; Mulder, J.
2017-01-01
The network autocorrelation model has been extensively used by researchers interested modeling social influence effects in social networks. The most common inferential method in the model is classical maximum likelihood estimation. This approach, however, has known problems such as negative bias of
Object Oriented Modeling Of Social Networks
Zeggelink, Evelien P.H.; Oosten, Reinier van; Stokman, Frans N.
1996-01-01
The aim of this paper is to explain principles of object oriented modeling in the scope of modeling dynamic social networks. As such, the approach of object oriented modeling is advocated within the field of organizational research that focuses on networks. We provide a brief introduction into the f
Agent-based modeling and network dynamics
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...
Tan, Michelle S. F.; White, Aaron P.; Rahman, Sadequr
2016-01-01
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. PMID:27355584
Edge exchangeable models for network data
Crane, Harry
2016-01-01
Exchangeable models for vertex labeled graphs cannot replicate the large sample behaviors of sparsity and power law degree distributions observed in many network datasets. Out of this mathematical impossibility emerges the question of how network data can be modeled in a way that reflects known empirical behaviors and respects basic statistical principles. We address this question by observing that edges, not vertices, act as the statistical units in most network datasets, making a theory of edge labeled networks more natural for most applications. Within this context we introduce the new invariance principle of {\\em edge exchangeability}, which unlike its vertex exchangeable counterpart can produce networks with sparse and/or power law structure. We characterize the class of all edge exchangeable network models and identify a particular two parameter family of models with suitable theoretical properties for statistical inference. We discuss issues of estimation from edge exchangeable models and compare our a...
Evolutionary Phylogenetic Networks: Models and Issues
Nakhleh, Luay
Phylogenetic networks are special graphs that generalize phylogenetic trees to allow for modeling of non-treelike evolutionary histories. The ability to sequence multiple genetic markers from a set of organisms and the conflicting evolutionary signals that these markers provide in many cases, have propelled research and interest in phylogenetic networks to the forefront in computational phylogenetics. Nonetheless, the term 'phylogenetic network' has been generically used to refer to a class of models whose core shared property is tree generalization. Several excellent surveys of the different flavors of phylogenetic networks and methods for their reconstruction have been written recently. However, unlike these surveys, this chapte focuses specifically on one type of phylogenetic networks, namely evolutionary phylogenetic networks, which explicitly model reticulate evolutionary events. Further, this chapter focuses less on surveying existing tools, and addresses in more detail issues that are central to the accurate reconstruction of phylogenetic networks.
Modeling Network Evolution Using Graph Motifs
Conway, Drew
2011-01-01
Network structures are extremely important to the study of political science. Much of the data in its subfields are naturally represented as networks. This includes trade, diplomatic and conflict relationships. The social structure of several organization is also of interest to many researchers, such as the affiliations of legislators or the relationships among terrorist. A key aspect of studying social networks is understanding the evolutionary dynamics and the mechanism by which these structures grow and change over time. While current methods are well suited to describe static features of networks, they are less capable of specifying models of change and simulating network evolution. In the following paper I present a new method for modeling network growth and evolution. This method relies on graph motifs to generate simulated network data with particular structural characteristic. This technique departs notably from current methods both in form and function. Rather than a closed-form model, or stochastic ...
Queuing theory models for computer networks
Galant, David C.
1989-01-01
A set of simple queuing theory models which can model the average response of a network of computers to a given traffic load has been implemented using a spreadsheet. The impact of variations in traffic patterns and intensities, channel capacities, and message protocols can be assessed using them because of the lack of fine detail in the network traffic rates, traffic patterns, and the hardware used to implement the networks. A sample use of the models applied to a realistic problem is included in appendix A. Appendix B provides a glossary of terms used in this paper. This Ames Research Center computer communication network is an evolving network of local area networks (LANs) connected via gateways and high-speed backbone communication channels. Intelligent planning of expansion and improvement requires understanding the behavior of the individual LANs as well as the collection of networks as a whole.
Starks, Tyrel J; Castro, Michael A; Castiblanco, Juan P; Millar, Brett M
2016-10-17
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.
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.
Quantum chemical calculations using the Floating Point Systems, Inc. Model 164 attached processor
Energy Technology Data Exchange (ETDEWEB)
Shepard, R.; Bair, R.A.; Eades, R.A.; Wagner, A.F.; Davis, M.J.; Harding, L.B.; Dunning, T.H. Jr.
1983-01-01
The Theoretical Chemistry Group at Argonne National Laboratory has had a Floating Point System, Inc., Model 164 Attached Processor (FPS-164) for several months. Actual production calculations, as well as benchmark calculations, indicate that the FPS-164 is capable of performance comparable to large mainframe computers, the groups experience with the FPS-164 includes the conversion of a complete system of electronic structure codes, including integral evaluation programs, generalized valence bond programs, integral transformation programs, and unitary group configuration interaction programs, and two classical trajectory codes. Timings of these programs at various levels of optimization along with estimates of the amount of effort required to make the necessary program modifications are discussed. 10 references, 2 figures, 2 tables.
Lee, Jeong-Hyun; Kim, Hye-Lee; Lee, Mi Hee; You, Kyung Eun; Kwon, Byeong-Ju; Seo, Hyok Jin; Park, Jong-Chul
2012-10-15
Wound healing proceeds through a complex collaborative process involving many types of cells. Keratinocytes and fibroblasts of epidermal and dermal layers of the skin play prominent roles in this process. Asiaticoside, an active component of Centella asiatica, is known for beneficial effects on keloid and hypertrophic scar. However, the effects of this compound on normal human skin cells are not well known. Using in vitro systems, we observed the effects of asiaticoside on normal human skin cell behaviors related to healing. In a wound closure seeding model, asiaticoside increased migration rates of skin cells. By observing the numbers of cells attached and the area occupied by the cells, we concluded that asiaticoside also enhanced the initial skin cell adhesion. In cell proliferation assays, asiaticoside induced an increase in the number of normal human dermal fibroblasts. In conclusion, asiaticoside promotes skin cell behaviors involved in wound healing; and as a bioactive component of an artificial skin, may have therapeutic value.
Stochastic dynamical model of a growing network based on self-exciting point process
Golosovsky, Michael; 10.1103/PhysRevLett.109.098701
2012-01-01
We perform experimental verification of the preferential attachment model that is commonly accepted as a generating mechanism of the scale-free complex networks. To this end we chose citation network of Physics papers and traced citation history of 40,195 papers published in one year. Contrary to common belief, we found that citation dynamics of the individual papers follows the \\emph{superlinear} preferential attachment, with the exponent $\\alpha= 1.25-1.3$. Moreover, we showed that the citation process cannot be described as a memoryless Markov chain since there is substantial correlation between the present and recent citation rates of a paper. Basing on our findings we constructed a stochastic growth model of the citation network, performed numerical simulations based on this model and achieved an excellent agreement with the measured citation distributions.
Random graph models for dynamic networks
Zhang, Xiao; Newman, M E J
2016-01-01
We propose generalizations of a number of standard network models, including the classic random graph, the configuration model, and the stochastic block model, to the case of time-varying networks. We assume that the presence and absence of edges are governed by continuous-time Markov processes with rate parameters that can depend on properties of the nodes. In addition to computing equilibrium properties of these models, we demonstrate their use in data analysis and statistical inference, giving efficient algorithms for fitting them to observed network data. This allows us, for instance, to estimate the time constants of network evolution or infer community structure from temporal network data using cues embedded both in the probabilities over time that node pairs are connected by edges and in the characteristic dynamics of edge appearance and disappearance. We illustrate our methods with a selection of applications, both to computer-generated test networks and real-world examples.
How do attachment dimensions affect bereavement adjustment? A mediation model of continuing bonds.
Yu, Wei; He, Li; Xu, Wei; Wang, Jianping; Prigerson, Holly G
2016-04-30
The current study aims to examine mechanisms underlying the impact of attachment dimensions on bereavement adjustment. Bereaved mainland Chinese participants (N=247) completed anonymous, retrospective, self-report surveys assessing attachment dimensions, continuing bonds (CB), grief symptoms and posttraumatic growth (PTG). Results demonstrated that attachment anxiety predicted grief symptoms via externalized CB and predicted PTG via internalized CB at the same time, whereas attachment avoidance positively predicted grief symptoms via externalized CB but negatively predicted PTG directly. Findings suggested that individuals with a high level of attachment anxiety could both suffer from grief and obtain posttraumatic growth after loss, but it depended on which kind of CB they used. By contrast, attachment avoidance was associated with a heightened risk of maladaptive bereavement adjustment. Future grief therapy may encourage the bereaved to establish CB with the deceased and gradually shift from externalized CB to internalized CB.
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...
Biodiversity: modelling angiosperms as networks.
Gottlieb, O R; Borin, M R
2000-11-01
In the neotropics, one of the last biological frontiers, the major ecological concern should not involve local strategies, but global effects often responsible for irreparable damage. For a holistic approach, angiosperms are ideal model systems dominating most land areas of the present world in an astonishing variety of form and function. Recognition of biogeographical patterns requires new methodologies and entails several questions, such as their nature, dynamics and mechanism. Demographical patterns of families, modelled via species dominance, reveal the existence of South American angiosperm networks converging at the central Brazilian plateau. Biodiversity of habitats, measured via taxonomic uniqueness, reveal higher creative power at this point of convergence than in more peripheral regions. Compositional affinities of habitats, measured via bioconnectivity, reveal the decisive role of ecotones in the exchange or redistribution of information, energy and organisms among the ecosystems. Forming dynamic boundaries, ecotones generate and relay evolutionary novelty, and integrate all neotropical ecosystems into a single vegetation net. Connectivity in such plant webs may depend on mycorrhizal links. If sufficiently general such means of metabolic transfer will require revision of the chemical composition of many plants.
A fractal growth model: Exploring the connection pattern of hubs in complex networks
Li, Dongyan; Wang, Xingyuan; Huang, Penghe
2017-04-01
Fractal is ubiquitous in many real-world networks. Previous researches showed that the strong disassortativity between the hub-nodes on all length scales was the key principle that gave rise to the fractal architecture of networks. Although fractal property emerged in some models, there were few researches about the fractal growth model and quantitative analyses about the strength of the disassortativity for fractal model. In this paper, we proposed a novel inverse renormalization method, named Box-based Preferential Attachment (BPA), to build the fractal growth models in which the Preferential Attachment was performed at box level. The proposed models provided a new framework that demonstrated small-world-fractal transition. Also, we firstly demonstrated the statistical characteristic of connection patterns of the hubs in fractal networks. The experimental results showed that, given proper growing scale and added edges, the proposed models could clearly show pure small-world or pure fractal or both of them. It also showed that the hub connection ratio showed normal distribution in many real-world networks. At last, the comparisons of connection pattern between the proposed models and the biological and technical networks were performed. The results gave useful reference for exploring the growth principle and for modeling the connection patterns for real-world networks.
Modeling of hysteresis in gene regulatory networks.
Hu, J; Qin, K R; Xiang, C; Lee, T H
2012-08-01
Hysteresis, observed in many gene regulatory networks, has a pivotal impact on biological systems, which enhances the robustness of cell functions. In this paper, a general model is proposed to describe the hysteretic gene regulatory network by combining the hysteresis component and the transient dynamics. The Bouc-Wen hysteresis model is modified to describe the hysteresis component in the mammalian gene regulatory networks. Rigorous mathematical analysis on the dynamical properties of the model is presented to ensure the bounded-input-bounded-output (BIBO) stability and demonstrates that the original Bouc-Wen model can only generate a clockwise hysteresis loop while the modified model can describe both clockwise and counter clockwise hysteresis loops. Simulation studies have shown that the hysteresis loops from our model are consistent with the experimental observations in three mammalian gene regulatory networks and two E.coli gene regulatory networks, which demonstrate the ability and accuracy of the mathematical model to emulate natural gene expression behavior with hysteresis. A comparison study has also been conducted to show that this model fits the experiment data significantly better than previous ones in the literature. The successful modeling of the hysteresis in all the five hysteretic gene regulatory networks suggests that the new model has the potential to be a unified framework for modeling hysteresis in gene regulatory networks and provide better understanding of the general mechanism that drives the hysteretic function.
Nonconsensus opinion model on directed networks
Qu, B.; Li, Q.; Havlin, S.; Stanley, E.; Wang, H.
2014-01-01
Dynamic social opinion models have been widely studied on undirected networks, and most of them are based on spin interaction models that produce a consensus. In reality, however, many networks such as Twitter and the World Wide Web are directed and are composed of both unidirectional and bidirectio
Radio channel modeling in body area networks
An, L.; Bentum, M.J.; Meijerink, A.; Scanlon, W.G.
2010-01-01
A body area network (BAN) is a network of bodyworn or implanted electronic devices, including wireless sensors which can monitor body parameters or to detect movements. One of the big challenges in BANs is the propagation channel modeling. Channel models can be used to understand wave propagation in
Radio channel modeling in body area networks
An, L.; Bentum, M.J.; Meijerink, A.; Scanlon, W.G.
2009-01-01
A body area network (BAN) is a network of bodyworn or implanted electronic devices, including wireless sensors which can monitor body parameters or to de- tect movements. One of the big challenges in BANs is the propagation channel modeling. Channel models can be used to understand wave propagation
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.
Network models in economics and finance
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.
Unified Hybrid Network Theoretical Model Trilogy
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
The first of the unified hybrid network theoretical model trilogy (UHNTF) is the harmonious unification hybrid preferential model (HUHPM), seen in the inner loop of Fig. 1, the unified hybrid ratio is defined.
A Network Formation Model Based on Subgraphs
Chandrasekhar, Arun
2016-01-01
We develop a new class of random-graph models for the statistical estimation of network formation that allow for substantial correlation in links. Various subgraphs (e.g., links, triangles, cliques, stars) are generated and their union results in a network. We provide estimation techniques for recovering the rates at which the underlying subgraphs were formed. We illustrate the models via a series of applications including testing for incentives to form cross-caste relationships in rural India, testing to see whether network structure is used to enforce risk-sharing, testing as to whether networks change in response to a community's exposure to microcredit, and show that these models significantly outperform stochastic block models in matching observed network characteristics. We also establish asymptotic properties of the models and various estimators, which requires proving a new Central Limit Theorem for correlated random variables.
Growing Networks with Positive and Negative Links
Dech, Corynne; Antwi, Shadrack; Shaw, Leah
Scale-free networks grown via preferential attachment have been used to model real-world networks such as the Internet, citation networks, and social networks. Here we investigate signed scale-free networks where an edge represents a positive or negative connection. We present analytic results and simulation for a growing signed network model. We compare the signed network to an unsigned scale-free network. We discuss several options for preferential attachment in a signed network that could be further adapted to model the accumulation of links over time in real-world signed networks.
Gossip spread in social network Models
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.
Inconsistencies within Attachment Teaching Practice in Zimbabwe: Call for a Participatory Model
Chikunda, Charles
2008-01-01
This article raises some inconsistencies observed in attachment teaching practice in Zimbabwe. The argument made is that these inconsistencies are caused by the different philosophical approaches informing attachment teaching practice and its delivery, which is largely visible in teaching practice supervision. The discussion shows that while…
Attachment Theory and Theory of Planned Behavior: An Integrative Model Predicting Underage Drinking
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…
Attachment Theory and Theory of Planned Behavior: An Integrative Model Predicting Underage Drinking
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…
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.
Symbolic regression of generative network models
Menezes, Telmo
2014-01-01
Networks are a powerful abstraction with applicability to a variety of scientific fields. Models explaining their morphology and growth processes permit a wide range of phenomena to be more systematically analysed and understood. At the same time, creating such models is often challenging and requires insights that may be counter-intuitive. Yet there currently exists no general method to arrive at better models. We have developed an approach to automatically detect realistic decentralised network growth models from empirical data, employing a machine learning technique inspired by natural selection and defining a unified formalism to describe such models as computer programs. As the proposed method is completely general and does not assume any pre-existing models, it can be applied "out of the box" to any given network. To validate our approach empirically, we systematically rediscover pre-defined growth laws underlying several canonical network generation models and credible laws for diverse real-world netwo...
Complex networks analysis in socioeconomic models
Varela, Luis M; Ausloos, Marcel; Carrete, Jesus
2014-01-01
This chapter aims at reviewing complex networks models and methods that were either developed for or applied to socioeconomic issues, and pertinent to the theme of New Economic Geography. After an introduction to the foundations of the field of complex networks, the present summary adds insights on the statistical mechanical approach, and on the most relevant computational aspects for the treatment of these systems. As the most frequently used model for interacting agent-based systems, a brief description of the statistical mechanics of the classical Ising model on regular lattices, together with recent extensions of the same model on small-world Watts-Strogatz and scale-free Albert-Barabasi complex networks is included. Other sections of the chapter are devoted to applications of complex networks to economics, finance, spreading of innovations, and regional trade and developments. The chapter also reviews results involving applications of complex networks to other relevant socioeconomic issues, including res...
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 sym
Boolean networks as modelling framework
Directory of Open Access Journals (Sweden)
Florian eGreil
2012-08-01
Full Text Available In a network, the components of a given system are represented as nodes, the interactions are abstracted as links between the nodes. Boolean networks refer to a class of dynamics on networks, in fact it is the simplest possible dynamics where each node has a value 0 or 1. This allows to investigate extensively the dynamics both analytically and by numerical experiments. The present article focuses on the theoretical concept of relevant components and the immediate application in plant biology, references for more in-depths treatment of the mathematical details are also given.
Gerlsma, Coby; Luteijn, Frans
By combining the Adult Attachment interview and the Autobiographical Memory Test, a structured interview was developed as a 'quick and dirty' measure for the assessment of attachment representations in clinical settings. The interview intends to assess valence, incongruence, and accessibility of the
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)
Modelling Microwave Devices Using Artificial Neural Networks
Directory of Open Access Journals (Sweden)
Andrius Katkevičius
2012-04-01
Full Text Available Artificial neural networks (ANN have recently gained attention as fast and flexible equipment for modelling and designing microwave devices. The paper reviews the opportunities to use them for undertaking the tasks on the analysis and synthesis. The article focuses on what tasks might be solved using neural networks, what challenges might rise when using artificial neural networks for carrying out tasks on microwave devices and discusses problem-solving techniques for microwave devices with intermittent characteristics.Article in Lithuanian
Delivery Time Reliability Model of Logistics Network
Liusan Wu; Qingmei Tan; Yuehui Zhang
2013-01-01
Natural disasters like earthquake and flood will surely destroy the existing traffic network, usually accompanied by delivery delay or even network collapse. A logistics-network-related delivery time reliability model defined by a shortest-time entropy is proposed as a means to estimate the actual delivery time reliability. The less the entropy is, the stronger the delivery time reliability remains, and vice versa. The shortest delivery time is computed separately based on two different assum...
Modeling Evolution of Weighted Clique Networks
Institute of Scientific and Technical Information of China (English)
杨旭华; 蒋峰岭; 陈胜勇; 王万良
2011-01-01
We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique （maximal complete sub-graph） at. each time step. And the cliques in the network overlap with each other. The structural expansion of the weighted clique network is combined with the edges＇ weight and vertices＇ strengths dynamical evolution. The model is based on a weight-driven dynamics and a weights＇ enhancement mechanism combining with the network growth. We study the network properties, which include the distribution of vertices＇ strength and the distribution o~ edges＇ weight, and find that both the distributions follow the scale-free distribution. At the same time, we also find that the relationship between strength and degree of a vertex are linear correlation during the growth of the network. On the basis of mean-field theory, we study the weighted network model and prove that both vertices＇ strength and edges＇ weight of this model follow the scale-free distribution. And we exploit an algorithm to forecast the network dynamics, which can be used to reckon the distributions and the corresponding scaling exponents. Furthermore, we observe that mean-field based theoretic results are consistent with the statistical data of the model, which denotes the theoretical result in this paper is effective.
Modeling Evolution of Weighted Clique Networks
Yang, Xu-Hua; Jiang, Feng-Ling; Chen, Sheng-Yong; Wang, Wan-Liang
2011-11-01
We propose a weighted clique network evolution model, which expands continuously by the addition of a new clique (maximal complete sub-graph) at each time step. And the cliques in the network overlap with each other. The structural expansion of the weighted clique network is combined with the edges' weight and vertices' strengths dynamical evolution. The model is based on a weight-driven dynamics and a weights' enhancement mechanism combining with the network growth. We study the network properties, which include the distribution of vertices' strength and the distribution of edges' weight, and find that both the distributions follow the scale-free distribution. At the same time, we also find that the relationship between strength and degree of a vertex are linear correlation during the growth of the network. On the basis of mean-field theory, we study the weighted network model and prove that both vertices' strength and edges' weight of this model follow the scale-free distribution. And we exploit an algorithm to forecast the network dynamics, which can be used to reckon the distributions and the corresponding scaling exponents. Furthermore, we observe that mean-field based theoretic results are consistent with the statistical data of the model, which denotes the theoretical result in this paper is effective.
Survey of propagation Model in wireless Network
Directory of Open Access Journals (Sweden)
Hemant Kumar Sharma
2011-05-01
Full Text Available To implementation of mobile ad hoc network wave propagation models are necessary to determine propagation characteristic through a medium. Wireless mobile ad hoc networks are self creating and self organizing entity. Propagation study provides an estimation of signal characteristics. Accurate prediction of radio propagation behaviour for MANET is becoming a difficult task. This paper presents investigation of propagation model. Radio wave propagation mechanisms are absorption, reflection, refraction, diffraction and scattering. This paper discuss free space model, two rays model, and cost 231 hata and its variants and fading model, and summarized the advantages and disadvantages of these model. This study would be helpful in choosing the correct propagation model.
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.
Modeling the interdependent network based on two-mode networks
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.
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.
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....... The suggested models are intended for incorporation into an existing analysis tool a.k.a. CyNC based on the MATLAB/SimuLink framework for graphical system analysis and design....
Neural network models of protein domain evolution
Sylvia Nagl
2000-01-01
Protein domains are complex adaptive systems, and here a novel procedure is presented that models the evolution of new functional sites within stable domain folds using neural networks. Neural networks, which were originally developed in cognitive science for the modeling of brain functions, can provide a fruitful methodology for the study of complex systems in general. Ethical implications of developing complex systems models of biomolecules are discussed, with particular reference to molecu...
Homophyly/Kinship Model: Naturally Evolving Networks
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.
A theoretical study on the unsteady aerothermodynamics for attached flow models
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The principle of the unsteady aerothermodynamics was theoretically investigated for the attached flow. Firstly, two simplified models with analytic solutions to the N-S equations were selected for the research, namely the compressible unsteady flows on the infinite flat plate with both time-varying wall velocity and time-varying wall temperature boundary conditions. The unsteady temperature field and the unsteady wall heat flux (heat flow) were analytically solved for the second model. Then, the interaction characteristic of the unsteady temperature field and the unsteady velocity field in the simplified models and the effects of the interaction on the transient wall heat transfer were studied by these two analytic solutions. The unsteady heat flux, which is governed by the energy equation, is directly related to the unsteady compression work and viscous dissipation which originates from the velocity field governed by the momentum equation. The main parameters and their roles in how the unsteady velocity field affects the unsteady heat flux were discussed for the simplified models. Lastly, the similarity criteria of the unsteady aerothermodynamics were derived based on the compressible boundary layer equations. Along with the Strouhal number Stu, the unsteadiness criterion of the velocity field, StT number, the unsteadiness criterion of the temperature field was proposed for the first time. Different from the traditional method used in unsteady aerodynamics which measures the flow unsteadiness only by the Stu number, present results show that the flow unsteadiness in unsteady aerothermodynamics should be comprehensively estimated by comparing the relative magnitudes of the temperature field unsteadiness criterion StT number with the coefficients of other terms in the dimensionless energy equation.
Simple model for river network evolution
Energy Technology Data Exchange (ETDEWEB)
Leheny, R.L. [The James Franck Institute and The Department of Physics, The University of Chicago, 5640 South Ellis Avenue, Chicago, Illinois 60637 (United States)
1995-11-01
We simulate the evolution of a drainage basin by erosion from precipitation and avalanching on hillslopes. The avalanches create a competition in growth between neighboring basins and play the central role in driving the evolution. The simulated landscapes form drainage systems that share many qualitative features with Glock`s model for natural network evolution and maintain statistical properties that characterize real river networks. We also present results from a second model with a modified, mass conserving avalanche scheme. Although the terrains from these two models are qualitatively dissimilar, their drainage networks share the same general evolution and statistical features.
Characterization and Modeling of Network Traffic
DEFF Research Database (Denmark)
Shawky, Ahmed; Bergheim, Hans; Ragnarsson, Olafur
2011-01-01
This paper attempts to characterize and model backbone network traffic, using a small number of statistics. In order to reduce cost and processing power associated with traffic analysis. The parameters affecting the behaviour of network traffic are investigated and the choice is that inter...
Modeling the hydrodynamics in tidal networks
Alebregtse, N.C.
2016-01-01
This thesis covers tidal propagation through networks of channels. Such networks are widespread and are often subject to discordant human and natural interests. First, the effect of a secondary channel on the tides in a main channel is explained with the use of an idealized model and the responsible
Simple models of human brain functional networks.
Vértes, Petra E; Alexander-Bloch, Aaron F; Gogtay, Nitin; Giedd, Jay N; Rapoport, Judith L; Bullmore, Edward T
2012-04-10
Human brain functional networks are embedded in anatomical space and have topological properties--small-worldness, modularity, fat-tailed degree distributions--that are comparable to many other complex networks. Although a sophisticated set of measures is available to describe the topology of brain networks, the selection pressures that drive their formation remain largely unknown. Here we consider generative models for the probability of a functional connection (an edge) between two cortical regions (nodes) separated by some Euclidean distance in anatomical space. In particular, we propose a model in which the embedded topology of brain networks emerges from two competing factors: a distance penalty based on the cost of maintaining long-range connections; and a topological term that favors links between regions sharing similar input. We show that, together, these two biologically plausible factors are sufficient to capture an impressive range of topological properties of functional brain networks. Model parameters estimated in one set of functional MRI (fMRI) data on normal volunteers provided a good fit to networks estimated in a second independent sample of fMRI data. Furthermore, slightly detuned model parameters also generated a reasonable simulation of the abnormal properties of brain functional networks in people with schizophrenia. We therefore anticipate that many aspects of brain network organization, in health and disease, may be parsimoniously explained by an economical clustering rule for the probability of functional connectivity between different brain areas.
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...
Cyber threat model for tactical radio networks
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.
Multiscaling in an YX model of networks.
Holme, Petter; Wu, Zhi-Xi; Minnhagen, Petter
2009-09-01
We investigate a Hamiltonian model of networks. The model is a mirror formulation of the XY model (hence the name)--instead of letting the XY spins vary, keeping the coupling topology static, we keep the spins conserved and sample different underlying networks. Our numerical simulations show complex scaling behaviors with various exponents as the system grows and temperature approaches zero, but no finite-temperature universal critical behavior. The ground-state and low-order excitations for sparse, finite graphs are a fragmented set of isolated network clusters. Configurations of higher energy are typically more connected. The connected networks of lowest energy are stretched out giving the network large average distances. For the finite sizes we investigate, there are three regions--a low-energy regime of fragmented networks, an intermediate regime of stretched-out networks, and a high-energy regime of compact, disordered topologies. Scaling up the system size, the borders between these regimes approach zero temperature algebraically, but different network-structural quantities approach their T=0 values with different exponents. We argue this is a, perhaps rare, example of a statistical-physics model where finite sizes show a more interesting behavior than the thermodynamic limit.
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....
Stochastic discrete model of karstic networks
Jaquet, O.; Siegel, P.; Klubertanz, G.; Benabderrhamane, H.
Karst aquifers are characterised by an extreme spatial heterogeneity that strongly influences their hydraulic behaviour and the transport of pollutants. These aquifers are particularly vulnerable to contamination because of their highly permeable networks of conduits. A stochastic model is proposed for the simulation of the geometry of karstic networks at a regional scale. The model integrates the relevant physical processes governing the formation of karstic networks. The discrete simulation of karstic networks is performed with a modified lattice-gas cellular automaton for a representative description of the karstic aquifer geometry. Consequently, more reliable modelling results can be obtained for the management and the protection of karst aquifers. The stochastic model was applied jointly with groundwater modelling techniques to a regional karst aquifer in France for the purpose of resolving surface pollution issues.
Viggiano, Albert A; Friedman, Jeffrey F; Shuman, Nicholas S; Miller, Thomas M; Schaffer, Linda C; Troe, Jürgen
2010-05-21
Thermal electron attachment to C(60) has been studied by relative rate measurements in a flowing afterglow Langmuir probe apparatus. The rate coefficients of the attachment k(1) are shown to be close to 10(-6) cm(3) s(-1) with a small negative temperature coefficient. These results supersede measurements from the 1990s which led to much smaller values of k(1) with a large positive temperature coefficient suggesting an activation barrier. Theoretical modeling of k(1) in terms of generalized Vogt-Wannier capture theory shows that k(1) now looks more consistent with measurements of absolute attachment cross sections sigma(at) than before. The comparison of capture theory and experimental rate or cross section data leads to empirical correction factors, accounting for "intramolecular vibrational relaxation" or "electron-phonon coupling," which reduce k(1) below the capture results and which, on a partial wave-selected level, decrease with increasing electron energy.
A Model for Telestrok Network Evaluation
DEFF Research Database (Denmark)
Storm, Anna; Günzel, Franziska; Theiss, Stephan
2011-01-01
Different telestroke network concepts have been implemented worldwide to enable fast and efficient treatment of stroke patients in underserved rural areas. Networks could demonstrate the improvement in clinical outcome, but have so far excluded a cost-effectiveness analysis. With health economic...... 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...
Energy Technology Data Exchange (ETDEWEB)
Davidson, R.N.
1996-10-01
By predicting the total life-cycle cost of owning and operating production equipment, it becomes possible for processors to make accurate and intelligent decisions regarding major capitol equipment investments as well as determining the most cost effective manufacturing processes and environments. Cost of Ownership (COO) is a decision making technique based on inputting the total costs of acquiring, operating and maintaining production equipment. All quantitative economic and production data can be modeled and processed using COO software programs such as the Cost of Ownership Luminator program TWO COOL{trademark}. This report investigated the Cost of Ownership differences between the current state-of-the-art solder ball attachment process and a prototype solder jetting process developed by Sandia National Laboratories. The prototype jetting process is a novel and unique approach to address the anticipated high rate ball grid array (BGA) production requirements currently forecasted for the next decade. The jetting process, which is both economically and environmentally attractive eliminates the solder sphere fabrication step, the solder flux application step as well as the furnace reflow and post cleaning operations.
Pitkin, Mark; Raykhtsaum, Grigory; Pilling, John; Shukeylo, Yuri; Moxson, Vladimir; Duz, Volodimir; Lewandowski, John; Connolly, Raymond; Kistenberg, Robert S.; Dalton, John F.; Prilutsky, Boris; Jacobson, Stewart
2010-01-01
This article presents recent results in the development of the skin and bone integrated pylon (SBIP) intended for direct skeletal attachment of limb prostheses. In our previous studies of the porous SBIP-1 and SBIP-2 prototypes, the bond site between the porous pylons and residuum bone and skin did not show the inflammation characteristically observed when solid pylons are used. At the same time, porosity diminished the strength of the pylon. To find a reasonable balance between the biological conductivity and the strength of the porous pylon, we developed a mathematical model of the composite permeable structure. A novel manufacturing process was implemented, and the new SBIP-3 prototype was tested mechanically. The minimal strength requirements established earlier for the SBIP were exceeded threefold. The first histopathological analysis of skin, bone, and the implanted SBIP-2 pylons was conducted on two rats and one cat. The histopathological analysis provided new evidence of inflammation-free, deep ingrowth of skin and bone cells throughout the SBIP structure. PMID:19675985
Marshall, Wallace F.; Fung, Jennifer C.
2016-04-01
The recognition and pairing of homologous chromosomes during meiosis is a complex physical and molecular process involving a combination of polymer dynamics and molecular recognition events. Two highly conserved features of meiotic chromosome behavior are the attachment of telomeres to the nuclear envelope and the active random motion of telomeres driven by their interaction with cytoskeletal motor proteins. Both of these features have been proposed to facilitate the process of homolog pairing, but exactly what role these features play in meiosis remains poorly understood. Here we investigate the roles of active motion and nuclear envelope tethering using a Brownian dynamics simulation in which meiotic chromosomes are represented by a Rouse polymer model subjected to tethering and active forces at the telomeres. We find that tethering telomeres to the nuclear envelope slows down pairing relative to the rates achieved by unattached chromosomes, but that randomly directed active forces applied to the telomeres speed up pairing dramatically in a manner that depends on the statistical properties of the telomere force fluctuations. The increased rate of initial pairing cannot be explained by stretching out of the chromosome conformation but instead seems to correlate with anomalous diffusion of sub-telomeric regions.
Model-based control of networked systems
Garcia, Eloy; Montestruque, Luis A
2014-01-01
This monograph introduces a class of networked control systems (NCS) called model-based networked control systems (MB-NCS) and presents various architectures and control strategies designed to improve the performance of NCS. The overall performance of NCS considers the appropriate use of network resources, particularly network bandwidth, in conjunction with the desired response of the system being controlled. The book begins with a detailed description of the basic MB-NCS architecture that provides stability conditions in terms of state feedback updates . It also covers typical problems in NCS such as network delays, network scheduling, and data quantization, as well as more general control problems such as output feedback control, nonlinear systems stabilization, and tracking control. Key features and topics include: Time-triggered and event-triggered feedback updates Stabilization of uncertain systems subject to time delays, quantization, and extended absence of feedback Optimal control analysis and ...
Complex networks repair strategies: Dynamic models
Fu, Chaoqi; Wang, Ying; Gao, Yangjun; Wang, Xiaoyang
2017-09-01
Network repair strategies are tactical methods that restore the efficiency of damaged networks; however, unreasonable repair strategies not only waste resources, they are also ineffective for network recovery. Most extant research on network repair focuses on static networks, but results and findings on static networks cannot be applied to evolutionary dynamic networks because, in dynamic models, complex network repair has completely different characteristics. For instance, repaired nodes face more severe challenges, and require strategic repair methods in order to have a significant effect. In this study, we propose the Shell Repair Strategy (SRS) to minimize the risk of secondary node failures due to the cascading effect. Our proposed method includes the identification of a set of vital nodes that have a significant impact on network repair and defense. Our identification of these vital nodes reduces the number of switching nodes that face the risk of secondary failures during the dynamic repair process. This is positively correlated with the size of the average degree and enhances network invulnerability.
Modeling trust context in networks
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
Graphical Model Theory for Wireless Sensor Networks
Energy Technology Data Exchange (ETDEWEB)
Davis, William B.
2002-12-08
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.
Modelling subtle growth of linguistic networks
Kulig, Andrzej; Kwapien, Jaroslaw; Oswiecimka, Pawel
2014-01-01
We investigate properties of evolving linguistic networks defined by the word-adjacency relation. Such networks belong to the category of networks with accelerated growth but their shortest path length appears to reveal the network size dependence of different functional form than the ones known so far. We thus compare the networks created from literary texts with their artificial substitutes based on different variants of the Dorogovtsev-Mendes model and observe that none of them is able to properly simulate the novel asymptotics of the shortest path length. Then, we identify grammar induced local chain-like linear growth as a missing element in this model and extend it by incorporating such effects. It is in this way that a satisfactory agreement with the empirical result is obtained.
Network models of dissolution of porous media
Budek, Agnieszka
2012-01-01
We investigate the chemical dissolution of porous media using a network model in which the system is represented as a series of interconnected pipes with the diameter of each segment increasing in proportion to the local reactant consumption. Moreover, the topology of the network is allowed to change dynamically during the simulation: as the diameters of the eroding pores become comparable with the interpore distances, the pores are joined together thus changing the interconnections within the network. With this model, we investigate different growth regimes in an evolving porous medium, identifying the mechanisms responsible for the emergence of specific patterns. We consider both the random and regular network and study the effect of the network geometry on the patterns. Finally, we consider practically important problem of finding an optimum flow rate that gives a maximum increase in permeability for a given amount of reactant.
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.
A minimal model for the emergence of cooperation in randomly growing networks
Miller, Steve
2016-01-01
Cooperation is observed widely in nature and is thought an essential component of many evolutionary processes, yet the mechanisms by which it arises and persists are still unclear. Among several theories, network reciprocity -- a model of inhomogeneous social interactions -- has been proposed as an enabling mechanism to explain the emergence of cooperation. Existing evolutionary models of this mechanism have tended to focus on highly heterogeneous (scale-free) networks, hence typically assume preferential attachment mechanisms, and consequently the prerequisite that individuals have global network knowledge. Within an evolutionary game theoretic context, using the weak prisoner's dilemma as a metaphor for cooperation, we present a minimal model which describes network growth by chronological random addition of new nodes, combined with regular attrition of less fit members of the population. Specifically our model does not require that agents have access to global information and does not assume scale-free net...
IP Network Management Model Based on NGOSS
Institute of Scientific and Technical Information of China (English)
ZHANG Jin-yu; LI Hong-hui; LIU Feng
2004-01-01
This paper addresses a management model for IP network based on Next Generation Operation Support System (NGOSS). It makes the network management on the base of all the operation actions of ISP, It provides QoS to user service through the whole path by providing end-to-end Service Level Agreements (SLA) management through whole path. Based on web and coordination technology, this paper gives an implement architecture of this model.
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.
Model-driven SOA for sensor networks
Ibbotson, John; Gibson, Christopher; Geyik, Sahin; Szymanski, Boleslaw K.; Mott, David; Braines, David; Klapiscak, Tom; Bergamaschi, Flavio
2011-06-01
Our previous work has explored the application of enterprise middleware techniques at the edge of the network to address the challenges of delivering complex sensor network solutions over heterogeneous communications infrastructures. In this paper, we develop this approach further into a practicable, semantically rich, model-based design and analysis approach that considers the sensor network and its contained services as a service-oriented architecture. The proposed model enables a systematic approach to service composition, analysis (using domain-specific techniques), and deployment. It also enables cross intelligence domain integration to simplify intelligence gathering, allowing users to express queries in structured natural language (Controlled English).
Effect of cathode model on arc attachment for short high-intensity arc on a refractory cathode
Javidi Shirvan, Alireza; Choquet, Isabelle; Nilsson, Håkan
2016-12-01
Various models coupling the refractory cathode, the cathode sheath and the arc at atmospheric pressure exist. They assume a homogeneous cathode with a uniform physical state, and differ by the cathode layer and the plasma arc model. However even the most advanced of these models still fail in predicting the extent of the arc attachment when applied to short high-intensity arcs such as gas tungsten arcs. Cathodes operating in these conditions present a non-uniform physical state. A model taking into account the first level of this non-homogeneity is proposed based on physical criteria. Calculations are done for 5 mm argon arcs with a thoriated tungsten cathode. The results obtained show that radiative heating and cooling of the cathode surface are of the same order. They also show that cathode inhomogeneity has a significant effect on the arc attachment, the arc temperature and pressure. When changing the arc current (100 A, 200 A) the proposed model allows predicting trends observed experimentally that cannot be captured by the homogeneous cathode model unless restricting a priori the size of the arc attachment. The cathode physics is thus an important element to include to obtain a comprehensive and predictive arc model.
Mugge, R.
2007-01-01
The topic of this doctoral research is the concept of product attachment for ordinary consumer durables. Product attachment is defined as the strength of the emotional bond a consumer experiences with a specific product. Specifically, the research investigated how this bond develops over time and th
Phenrat, Tanapon; Song, Jee Eun; Cisneros, Charlotte M; Schoenfelder, Daniel P; Tilton, Robert D; Lowry, Gregory V
2010-06-15
Assessing the environmental transport and fate of manufactured nanoparticles (NPs) and potential exposure risks requires models for predicting attachment of NPs coated with organic macromolecules in porous media. The objective of this study was to determine the properties of coated nanoparticles that control their attachment behavior. Deposition data for a variety of nanoparticles with different types of anionic organic coatings, including natural organic matter (NOM)-coated latex and hematite nanoparticles, and poly(styrenesulfonate)-, carboxymethylcellulose-, and polyaspartate-coated hematite and titanium dioxide nanoparticles (80 data points), were used to develop an empirical correlation between measurable NP properties and their sticking coefficient (alpha) under a variety of electrolyte conditions and flow velocities. Available semiempirical correlations used to predict the attachment efficiency of electrostatically stabilized (uncoated) NPs overestimate the attachment efficiency of nanoparticles coated with NOM or synthetic polyelectrolytes because the correlations neglect electrosteric repulsions and the decreased friction afforded by such coatings that can inhibit attachment to surfaces. Adding a dimensionless parameter (N(LEK)) representing steric repulsions and the decreased friction force afforded by adsorbed NOM or anionic polyelectrolytes in the correlation significantly improves the correlation. This establishes the importance of including the adsorbed NOM- or polyelectrolyte layer properties for estimating the attachment efficiency of NPs in the environment. The form of N(LEK) suggests that limiting unintended transport and exposure to NPs could be achieved by using coatings with the smallest adsorbed mass and polymer density, shortest extended layer thickness, and largest molecular weight that would still afford the desired functionality of the coating.
River Network Modeling Beyond Discharge at Gauges
David, C. H.; Famiglietti, J. S.; Salas, F. R.; Whiteaker, T. L.; Maidment, D. R.; Tolle, K.
2014-12-01
Over the past two decades, the estimation of water flow in river networks within hydro-meteorological models has mostly focused on simulations of natural processes and on their verification at available river gauges. Despite valuable existing skills in hydrologic modeling the accounting for anthropogenic actions in current models remains limited. The emerging availability of datasets containing measured dam outflows and reported irrigation withdrawals motivates their inclusion into simulations of flow in river networks. However, the development of advanced river network models accounting for such datasets of anthropogenic influences requires a detailed data model and a thorough handling of the various data types, sources and time scales. This contribution details the development of a consistent data model suitable for accounting some observations of anthropogenic modifications of the surface water cycle and presents the impact of such inclusion on simulations using the Routing Application for Parallel computatIon of Discharge (RAPID).
Posterior Predictive Model Checking in Bayesian Networks
Crawford, Aaron
2014-01-01
This simulation study compared the utility of various discrepancy measures within a posterior predictive model checking (PPMC) framework for detecting different types of data-model misfit in multidimensional Bayesian network (BN) models. The investigated conditions were motivated by an applied research program utilizing an operational complex…
Kitaev spin models from topological nanowire networks
Kells, G.; Lahtinen, V.; Vala, J.
2014-01-01
We show that networks of superconducting topological nanowires can realize the physics of exactly solvable Kitaev spin models on trivalent lattices. This connection arises from the low-energy theory of both systems being described by a tight-binding model of Majorana modes. In Kitaev spin models the
Inequalities in network structures
Whitmeyer, Joseph M.; Wittek, Rafael
We use a model of continuous attachments in networks to generate propositions concerning inequalities in network structures, and test the propositions on data from organizational settings. Our network model, inspired by that of [Gould, Roger 2002. The origins of status hierarchies: A formal theory
Inequalities in network structures
Whitmeyer, Joseph M.; Wittek, Rafael
2010-01-01
We use a model of continuous attachments in networks to generate propositions concerning inequalities in network structures, and test the propositions on data from organizational settings. Our network model, inspired by that of [Gould, Roger 2002. The origins of status hierarchies: A formal theory a
Fractal modeling of natural fracture networks
Energy Technology Data Exchange (ETDEWEB)
Ferer, M.; Dean, B.; Mick, C.
1995-06-01
West Virginia University will implement procedures for a fractal analysis of fractures in reservoirs. This procedure will be applied to fracture networks in outcrops and to fractures intersecting horizontal boreholes. The parameters resulting from this analysis will be used to generate synthetic fracture networks with the same fractal characteristics as the real networks. Recovery from naturally fractured, tight-gas reservoirs is controlled by the fracture network. Reliable characterization of the actual fracture network in the reservoir is severely limited. The location and orientation of fractures intersecting the borehole can be determined, but the length of these fractures cannot be unambiguously determined. Because of the lack of detailed information about the actual fracture network, modeling methods must represent the porosity and permeability associated with the fracture network, as accurately as possible with very little a priori information. In the sections following, the authors will (1) present fractal analysis of the MWX site, using the box-counting procedure; (2) review evidence testing the fractal nature of fracture distributions and discuss the advantages of using the fractal analysis over a stochastic analysis; and (3) present an efficient algorithm for producing a self-similar fracture networks which mimic the real MWX outcrop fracture network.
A simple model for studying interacting networks
Liu, Wenjia; Jolad, Shivakumar; Schmittmann, Beate; Zia, R. K. P.
2011-03-01
Many specific physical networks (e.g., internet, power grid, interstates), have been characterized in considerable detail, but in isolation from each other. Yet, each of these networks supports the functions of the others, and so far, little is known about how their interactions affect their structure and functionality. To address this issue, we consider two coupled model networks. Each network is relatively simple, with a fixed set of nodes, but dynamically generated set of links which has a preferred degree, κ . In the stationary state, the degree distribution has exponential tails (far from κ), an attribute which we can explain. Next, we consider two such networks with different κ 's, reminiscent of two social groups, e.g., extroverts and introverts. Finally, we let these networks interact by establishing a controllable fraction of cross links. The resulting distribution of links, both within and across the two model networks, is investigated and discussed, along with some potential consequences for real networks. Supported in part by NSF-DMR-0705152 and 1005417.
Automated modelling of signal transduction networks
Directory of Open Access Journals (Sweden)
Aach John
2002-11-01
Full Text Available Abstract Background Intracellular signal transduction is achieved by networks of proteins and small molecules that transmit information from the cell surface to the nucleus, where they ultimately effect transcriptional changes. Understanding the mechanisms cells use to accomplish this important process requires a detailed molecular description of the networks involved. Results We have developed a computational approach for generating static models of signal transduction networks which utilizes protein-interaction maps generated from large-scale two-hybrid screens and expression profiles from DNA microarrays. Networks are determined entirely by integrating protein-protein interaction data with microarray expression data, without prior knowledge of any pathway intermediates. In effect, this is equivalent to extracting subnetworks of the protein interaction dataset whose members have the most correlated expression profiles. Conclusion We show that our technique accurately reconstructs MAP Kinase signaling networks in Saccharomyces cerevisiae. This approach should enhance our ability to model signaling networks and to discover new components of known networks. More generally, it provides a method for synthesizing molecular data, either individual transcript abundance measurements or pairwise protein interactions, into higher level structures, such as pathways and networks.
A survey of statistical network models
Goldenberg, Anna; Fienberg, Stephen E; Airoldi, Edoardo M
2009-01-01
Networks are ubiquitous in science and have become a focal point for discussion in everyday life. Formal statistical models for the analysis of network data have emerged as a major topic of interest in diverse areas of study, and most of these involve a form of graphical representation. Probability models on graphs date back to 1959. Along with empirical studies in social psychology and sociology from the 1960s, these early works generated an active network community and a substantial literature in the 1970s. This effort moved into the statistical literature in the late 1970s and 1980s, and the past decade has seen a burgeoning network literature in statistical physics and computer science. The growth of the World Wide Web and the emergence of online networking communities such as Facebook, MySpace, and LinkedIn, and a host of more specialized professional network communities has intensified interest in the study of networks and network data. Our goal in this review is to provide the reader with an entry poin...
Coevolving complex networks in the model of social interactions
Raducha, Tomasz; Gubiec, Tomasz
2017-04-01
We analyze Axelrod's model of social interactions on coevolving complex networks. We introduce four extensions with different mechanisms of edge rewiring. The models are intended to catch two kinds of interactions-preferential attachment, which can be observed in scientists or actors collaborations, and local rewiring, which can be observed in friendship formation in everyday relations. Numerical simulations show that proposed dynamics can lead to the power-law distribution of nodes' degree and high value of the clustering coefficient, while still retaining the small-world effect in three models. All models are characterized by two phase transitions of a different nature. In case of local rewiring we obtain order-disorder discontinuous phase transition even in the thermodynamic limit, while in case of long-distance switching discontinuity disappears in the thermodynamic limit, leaving one continuous phase transition. In addition, we discover a new and universal characteristic of the second transition point-an abrupt increase of the clustering coefficient, due to formation of many small complete subgraphs inside the network.
A quantum-implementable neural network model
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.
Efficiency of attack strategies on complex model and real-world networks
Bellingeri, Michele; Vincenzi, Simone
2013-01-01
We investigated the efficiency of attack strategies to network nodes when targeting several complex model and real-world networks. We tested 5 attack strategies, 3 of which were introduced in this work for the first time, to attack 3 model (Erdos and Renyi, Barabasi and Albert preferential attachment network, and scale-free network configuration models) and 3 real networks (Gnutella peer-to-peer network, email network of the University of Rovira i Virgili, and immunoglobulin interaction network). Nodes were removed sequentially according to the importance criterion defined by the attack strategy. We used the size of the largest connected component (LCC) as a measure of network damage. We found that the efficiency of attack strategies (fraction of nodes to be deleted for a given reduction of LCC size) depends on the topology of the network, although attacks based on the number of connections of a node and betweenness centrality were often the most efficient strategies. Sequential deletion of nodes in decreasin...
Network Modeling and Simulation (NEMSE)
2013-07-01
Emulator (CORE) modules, hardware components, wireless cards with links modifiable using Radio Frequency (RF) cabling and variable attenuators, and GNU ...universal Network Interface Card (NIC) cards - Cardbus, PCI, or miniPCI. o GNU radio : Free & open-source software development toolkit that provides...Layer Emulator (FPLE), GNU Radio , CORE & EMANE, Tech Warrior, CASCON (CAS Connectivity), and Rate Adaptive Video Coding (RAVC). Also described is the
2016-11-09
standpoint remains more of an art than a science. Even when well executed, the ongoing evolution of the network may violate initial, security-critical design... Internet and compromises the LAN (this step compromises only the LAN). We describe this as a functional information flow between the Internet and the...vulnerabilities will stem from the delivery of email, access to the Internet , or access to an internal document or data repository. If any of these are
Telestroke network business model strategies.
Fanale, Christopher V; Demaerschalk, Bart M
2012-10-01
Our objective is to summarize the evidence that supports the reliability of telemedicine for diagnosis and efficacy in acute stroke treatment, identify strategies for funding the development of a telestroke network, and to present issues with respect to economic sustainability, cost effectiveness, and the status of reimbursement for telestroke. Copyright © 2012 National Stroke Association. Published by Elsevier Inc. All rights reserved.
Model Predictive Control of Sewer Networks
Pedersen, Einar B.; Herbertsson, Hannes R.; Niemann, Henrik; Poulsen, Niels K.; Falk, Anne K. V.
2017-01-01
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 controlled have thus become essential factors for effcient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona benchmark model. Due to the inherent constraints the applied approach is based on Model Predictive Control.
Performance modeling, stochastic networks, and statistical multiplexing
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
Network Modeling and Simulation A Practical Perspective
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
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
Distributed Bayesian Networks for User Modeling
DEFF Research Database (Denmark)
Tedesco, Roberto; Dolog, Peter; Nejdl, Wolfgang
2006-01-01
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...... efficiently combines distributed learner models without the need to exchange internal structure of local Bayesian networks, nor local evidence between the involved platforms....
Optimal transportation networks models and theory
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.
Modeling Emergence in Neuroprotective Regulatory Networks
Energy Technology Data Exchange (ETDEWEB)
Sanfilippo, Antonio P.; Haack, Jereme N.; McDermott, Jason E.; Stevens, S.L.; Stenzel-Poore, Mary
2013-01-05
The use of predictive modeling in the analysis of gene expression data can greatly accelerate the pace of scientific discovery in biomedical research by enabling in silico experimentation to test disease triggers and potential drug therapies. Techniques that focus on modeling emergence, such as agent-based modeling and multi-agent simulations, are of particular interest as they support the discovery of pathways that may have never been observed in the past. Thus far, these techniques have been primarily applied at the multi-cellular level, or have focused on signaling and metabolic networks. We present an approach where emergence modeling is extended to regulatory networks and demonstrate its application to the discovery of neuroprotective pathways. An initial evaluation of the approach indicates that emergence modeling provides novel insights for the analysis of regulatory networks that can advance the discovery of acute treatments for stroke and other diseases.
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.
International migration network: topology and modeling.
Fagiolo, Giorgio; Mastrorillo, Marina
2013-07-01
This paper studies international migration from a complex-network perspective. We define the international migration network (IMN) as the weighted-directed graph where nodes are world countries and links account for the stock of migrants originated in a given country and living in another country at a given point in time. We characterize the binary and weighted architecture of the network and its evolution over time in the period 1960-2000. We find that the IMN is organized around a modular structure with a small-world binary pattern displaying disassortativity and high clustering, with power-law distributed weighted-network statistics. We also show that a parsimonious gravity model of migration can account for most of observed IMN topological structure. Overall, our results suggest that socioeconomic, geographical, and political factors are more important than local-network properties in shaping the structure of the IMN.
Modeling, Optimization & Control of Hydraulic Networks
DEFF Research Database (Denmark)
Tahavori, Maryamsadat
2014-01-01
to check if the network is controllable. Afterward the pressure control problem in water supply systems is formulated as an optimal control problem. The goal is to minimize the power consumption in pumps and also to regulate the pressure drop at the end-users to a desired value. The formulated optimal...... 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...... systems. To have better understanding of water leakage, to control pressure and leakage effectively and for optimal design of water supply system, suitable modeling is an important prerequisite. Therefore a model with the main objective of pressure control and consequently leakage reduction is presented...
Spatial Models and Networks of Living Systems
DEFF Research Database (Denmark)
Juul, Jeppe Søgaard
. Such systems are known to be stabilized by spatial structure. Finally, I analyse data from a large mobile phone network and show that people who are topologically close in the network have similar communication patterns. This main part of the thesis is based on six different articles, which I have co...... 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...
Enhanced Gravity Model of trade: reconciling macroeconomic and network models
Almog, Assaf; Garlaschelli, Diego
2015-01-01
The bilateral trade relations between world countries form a complex network, the International Trade Network (ITN), which is involved in an increasing number of worldwide economic processes, including globalization, integration, industrial production, and the propagation of shocks and instabilities. Characterizing the ITN via a simple yet accurate model is an open problem. The classical Gravity Model of trade successfully reproduces the volume of trade between two connected countries using known macroeconomic properties such as GDP and geographic distance. However, it generates a network with an unrealistically homogeneous topology, thus failing to reproduce the highly heterogeneous structure of the real ITN. On the other hand, network models successfully reproduce the complex topology of the ITN, but provide no information about trade volumes. Therefore macroeconomic and network models of trade suffer from complementary limitations but are still largely incompatible. Here, we make an important step forward ...
Hybrid neural network models of transducers
Xie, Shilin; Zhang, Xinong; Chen, Shenglai; Zhu, Changchun
2011-10-01
A hybrid neural network (NN) approach is proposed and applied to modeling of transducers in the paper. The modeling procedures are also presented in detail. First, the simulated studies on the modeling of single input-single output and multi input-multi output transducers are conducted respectively by use of the developed hybrid NN scheme. Secondly, the hybrid NN modeling approach is utilized to characterize a six-axis force sensor prototype based on the measured data. The results show that the hybrid NN approach can significantly improve modeling precision in comparison with the conventional modeling method. In addition, the method is superior to NN black-box modeling because the former possesses smaller network scale, higher convergence speed, higher model precision and better generalization performance.
Preferential urn model and nongrowing complex networks.
Ohkubo, Jun; Yasuda, Muneki; Tanaka, Kazuyuki
2005-12-01
A preferential urn model, which is based on the concept "the rich get richer," is proposed. From a relationship between a nongrowing model for complex networks and the preferential urn model in regard to degree distributions, it is revealed that a fitness parameter in the nongrowing model is interpreted as an inverse local temperature in the preferential urn model. Furthermore, it is clarified that the preferential urn model with randomness generates a fat-tailed occupation distribution; the concept of the local temperature enables us to understand the fat-tailed occupation distribution intuitively. Since the preferential urn model is a simple stochastic model, it can be applied to research on not only the nongrowing complex networks, but also many other fields such as econophysics and social sciences.
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.
Spatial Models and Networks of Living Systems
DEFF Research Database (Denmark)
Juul, Jeppe Søgaard
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....... Such systems are known to be stabilized by spatial structure. Finally, I analyse data from a large mobile phone network and show that people who are topologically close in the network have similar communication patterns. This main part of the thesis is based on six different articles, which I have co...
Grid architecture model of network centric warfare
Institute of Scientific and Technical Information of China (English)
Yan Tihua; Wang Baoshu
2006-01-01
NCW(network centric warfare) is an information warfare concentrating on network. A global network-centric warfare architecture with OGSA grid technology is put forward, which is a four levels system including the user level, the application level, the grid middleware layer and the resource level. In grid middleware layer, based on virtual hosting environment, a BEPL4WS grid service composition method is introduced. In addition, the NCW grid service model is built with the help of Eclipse-SDK-3.0.1 and Bpws4j.
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.
Stochastic modeling and analysis of telecoms networks
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
Model Reduction for Complex Hyperbolic Networks
Himpe, Christian; Ohlberger, Mario
2013-01-01
We recently introduced the joint gramian for combined state and parameter reduction [C. Himpe and M. Ohlberger. Cross-Gramian Based Combined State and Parameter Reduction for Large-Scale Control Systems. arXiv:1302.0634, 2013], which is applied in this work to reduce a parametrized linear time-varying control system modeling a hyperbolic network. The reduction encompasses the dimension of nodes and parameters of the underlying control system. Networks with a hyperbolic structure have many app...
Parenting Practices, Parental Attachment and Aggressiveness in Adolescence: A Predictive Model
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'…
Parenting Practices, Parental Attachment and Aggressiveness in Adolescence: A Predictive Model
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'…
Continuum Modeling of Biological Network Formation
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.
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...
Implementation of a network model of hysteresis
Energy Technology Data Exchange (ETDEWEB)
Gruosso, G. [Dipartimento Elettronica e Informazione, Politecnico di Milano, P.za Leonardo da Vinci 32, I-20133 Milan (Italy); Repetto, M. [Dipartimento Ingegneria Elettrica, Politecnico di Torino, Corso Duca degli Abruzzi 24, I-10129 Turin (Italy)]. E-mail: maurizio.repetto@polito.it
2006-02-01
A network model of hysteresis based on elementary cells made up with piece-wise linear resistors and a linear capacitor has been presented in the literature and its theoretical properties have been investigated. This model allows to simulate hysteresis in a circuit solver without requiring any modification to its source code. Despite its appealing features, some cautions must be used for the treatment of the interface between the model and the rest of the circuit and for the handling of nonlinear resistors which can introduce some convergence problems in the network solution. These topics are investigated and some results on a simple test case are presented and discussed.
Evaluation of EOR Processes Using Network Models
DEFF Research Database (Denmark)
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)...
Spectral stability of unitary network models
Asch, Joachim; Bourget, Olivier; Joye, Alain
2015-08-01
We review various unitary network models used in quantum computing, spectral analysis or condensed matter physics and establish relationships between them. We show that symmetric one-dimensional quantum walks are universal, as are CMV matrices. We prove spectral stability and propagation properties for general asymptotically uniform models by means of unitary Mourre theory.
Modelling cooperative agents in infrastructure networks
Ligtvoet, A.; Chappin, E.J.L.; Stikkelman, R.M.
2010-01-01
This paper describes the translation of concepts of cooperation into an agent-based model of an industrial network. It first addresses the concept of cooperation and how this could be captured as heuristical rules within agents. Then it describes tests using these heuristics in an abstract model of
Delay and Disruption Tolerant Networking MACHETE Model
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
Adolescent attachment and psychopathology.
Rosenstein, D S; Horowitz, H A
1996-04-01
The relationships among attachment classification, psychopathology, and personality traits were examined in a group of 60 psychiatrically hospitalized adolescents. The concordance of attachment classification was examined in 27 adolescent-mother pairs. Both adolescent and maternal attachment status were overwhelmingly insecure and were highly concordant. Adolescents showing a dismissing attachment organization were more likely to have a conduct or substance abuse disorder, narcissistic or antisocial personality disorder, and self-reported narcissistic, antisocial, and paranoid personality traits. Adolescents showing a preoccupied attachment organization were more likely to have an affective disorder, obsessive-compulsive, histrionic, borderline or schizotypal personality disorder, and self-reported avoidant, anxious, and dysthymic personality traits. The results support a model of development of psychopathology based partially on relational experiences with parents.
Genetic network models: a comparative study
van Someren, Eugene P.; Wessels, Lodewyk F. A.; Reinders, Marcel J. T.
2001-06-01
Currently, the need arises for tools capable of unraveling the functionality of genes based on the analysis of microarray measurements. Modeling genetic interactions by means of genetic network models provides a methodology to infer functional relationships between genes. Although a wide variety of different models have been introduced so far, it remains, in general, unclear what the strengths and weaknesses of each of these approaches are and where these models overlap and differ. This paper compares different genetic modeling approaches that attempt to extract the gene regulation matrix from expression data. A taxonomy of continuous genetic network models is proposed and the following important characteristics are suggested and employed to compare the models: inferential power; predictive power; robustness; consistency; stability and computational cost. Where possible, synthetic time series data are employed to investigate some of these properties. The comparison shows that although genetic network modeling might provide valuable information regarding genetic interactions, current models show disappointing results on simple artificial problems. For now, the simplest models are favored because they generalize better, but more complex models will probably prevail once their bias is more thoroughly understood and their variance is better controlled.
An integrated network model of psychotic symptoms.
Looijestijn, Jasper; Blom, Jan Dirk; Aleman, André; Hoek, Hans W; Goekoop, Rutger
2015-12-01
The full body of research on the nature of psychosis and its determinants indicates that a considerable number of factors are relevant to the development of hallucinations, delusions, and other positive symptoms, ranging from neurodevelopmental parameters and altered connectivity of brain regions to impaired cognitive functioning and social factors. We aimed to integrate these factors in a single mathematical model based on network theory. At the microscopic level this model explains positive symptoms of psychosis in terms of experiential equivalents of robust, high-frequency attractor states of neural networks. At the mesoscopic level it explains them in relation to global brain states, and at the macroscopic level in relation to social-network structures and dynamics. Due to the scale-free nature of biological networks, all three levels are governed by the same general laws, thereby allowing for an integrated model of biological, psychological, and social phenomena involved in the mediation of positive symptoms of psychosis. This integrated network model of psychotic symptoms (INMOPS) is described together with various possibilities for application in clinical practice.
Research on Modeling of Genetic Networks Based on Information Measurement
Institute of Scientific and Technical Information of China (English)
ZHANG Guo-wei; SHAO Shi-huang; ZHANG Ying; LI Hai-ying
2006-01-01
As the basis of network of biology organism, the genetic network is concerned by many researchers.Current modeling methods to genetic network, especially the Boolean networks modeling method are analyzed. For modeling the genetic network, the information theory is proposed to mining the relations between elements in network. Through calculating the values of information entropy and mutual entropy in a case, the effectiveness of the method is verified.
Bayesian network modelling of upper gastrointestinal bleeding
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.
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.
Modeling epidemics dynamics on heterogenous networks.
Ben-Zion, Yossi; Cohen, Yahel; Shnerb, Nadav M
2010-05-21
The dynamics of the SIS process on heterogenous networks, where different local communities are connected by airlines, is studied. We suggest a new modeling technique for travelers movement, in which the movement does not affect the demographic parameters characterizing the metapopulation. A solution to the deterministic reaction-diffusion equations that emerges from this model on a general network is presented. A typical example of a heterogenous network, the star structure, is studied in detail both analytically and using agent-based simulations. The interplay between demographic stochasticity, spatial heterogeneity and the infection dynamics is shown to produce some counterintuitive effects. In particular it was found that, while movement always increases the chance of an outbreak, it may decrease the steady-state fraction of sick individuals. The importance of the modeling technique in estimating the outcomes of a vaccination campaign is demonstrated.
The Kuramoto model in complex networks
Rodrigues, Francisco A; 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 net...
A Random Growth Model for Power Grids and Other Spatially Embedded Infrastructure Networks
Schultz, Paul; Kurths, Jürgen
2016-01-01
We propose a model to create synthetic networks that may also serve as a narrative of a certain kind of infrastructure network evolution. It consists of an initialization phase with the network extending tree-like for minimum cost and a growth phase with an attachment rule giving a trade-off between cost-optimization and redundancy. Furthermore, we implement the feature of some lines being split during the grid's evolution. We show that the resulting degree distribution has an exponential tail and may show a maximum at degree two, suitable to observations of real-world power grid networks. In particular, the mean degree and the slope of the exponential decay can be controlled in partial independence. To verify to which extent the degree distribution is described by our analytic form, we conduct statistical tests, showing that the hypothesis of an exponential tail is well-accepted for our model data.
String networks with junctions in competition models
Avelino, P. P.; Bazeia, D.; Losano, L.; Menezes, J.; de Oliveira, B. F.
2017-03-01
In this work we give specific examples of competition models, with six and eight species, whose three-dimensional dynamics naturally leads to the formation of string networks with junctions, associated with regions that have a high concentration of enemy species. We study the two- and three-dimensional evolution of such networks, both using stochastic network and mean field theory simulations. If the predation, reproduction and mobility probabilities do not vary in space and time, we find that the networks attain scaling regimes with a characteristic length roughly proportional to t 1 / 2, where t is the physical time, thus showing that the presence of junctions, on its own, does not have a significant impact on their scaling properties.
String networks with junctions in competition models
Avelino, P P; Losano, L; Menezes, J; de Oliveira, B F
2016-01-01
In this work we give specific examples of competition models, with six and eight species, whose three-dimensional dynamics naturally leads to the formation of string networks with junctions, associated with regions that have a high concentration of enemy species. We study the two- and three-dimensional evolution of such networks, both using stochastic network and mean field theory simulations. If the predation, reproduction and mobility probabilities do not vary in space and time, we find that the networks attain scaling regimes with a characteristic length roughly proportional to $t^{1/2}$, where $t$ is the physical time, thus showing that the presence of junctions, on its own, does not have a significant impact on their scaling properties.
Mobility Models for Next Generation Wireless Networks Ad Hoc, Vehicular and Mesh Networks
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
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 controlled have thus become essential factors for efficient performance of waste water treatment plants. This paper examines methods for simplified modelling and controlling a sewer network. A practical approach to the problem is used by analysing simplified design model, which is based on the Barcelona...
Green Network Planning Model for Optical Backbones
DEFF Research Database (Denmark)
Gutierrez Lopez, Jose Manuel; Riaz, M. Tahir; Jensen, Michael
2010-01-01
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...... 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...
Osborne, Hannah; Stokes, Graham; Simpson, Jane
2010-11-01
This study replicates and extends research into the occurrence of parent fixation in people with dementia by exploring the relationship between demographic, cognitive and psychological factors. Fifty-one people with dementia, living both in the community and in residential/nursing home settings, were interviewed about their parents and a relative of each completed measures assessing the person with dementia's demographic details, level of cognitive impairment/executive functioning, behavioural consequences of parent fixation and pre-morbid personality and attachment style. Results indicated that parent fixation can be viewed as a psychosocial phenomenon arising from the environment, pre-morbid personality and attachment style and that the behavioural consequences of parent fixation are maintained by the individual's level of executive functioning and gender. Findings and clinical implications are discussed in relation to Miesen's (1992, 1993, 1999) theoretical assumption that dementia is a loss process that activates the experience of feeling unsafe and the emotional need for the security of an attachment figure.
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.
Gianturco, F A; Wester, R
2016-01-01
(abridged) The fairly recent detection of a variety of anions in the Interstellar Molecular Clouds have underlined the importance of realistically modeling the processes governing their abundance. To this aim, our earlier calculations for the radiative electron attachment (REA) rates for C4H-, C6H-, and C8H- are employed to generate the corresponding column density ratios of anion/neutral (A/N) relative abundances. The latter are then compared with those obtained from observational measurements. The calculations involved the time-dependent solutions of a large network of chemical processes over an extended time interval and included a series of runs in which the values of REA rates were repeatedly scaled. Macroscopic parameters for the clouds' modeling were also varied to cover a broad range of physical environments. It was found that, within the range and quality of the processes included in the present network,and selected from state-of-the-art astrophysical databases, the REA values required to match the o...
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.
Models and average properties of scale-free directed networks
Bernhardsson, Sebastian; Minnhagen, Petter
2006-08-01
We extend the merging model for undirected networks by Kim [Eur. Phys. J. B 43, 369 (2004)] to directed networks and investigate the emerging scale-free networks. Two versions of the directed merging model, friendly and hostile merging, give rise to two distinct network types. We uncover that some nontrivial features of these two network types resemble two levels of a certain randomization/nonspecificity in the link reshuffling during network evolution. Furthermore, the same features show up, respectively, in metabolic networks and transcriptional networks. We introduce measures that single out the distinguishing features between the two prototype networks, as well as point out features that are beyond the prototypes.
Delivery Time Reliability Model of Logistics Network
Directory of Open Access Journals (Sweden)
Liusan Wu
2013-01-01
Full Text Available Natural disasters like earthquake and flood will surely destroy the existing traffic network, usually accompanied by delivery delay or even network collapse. A logistics-network-related delivery time reliability model defined by a shortest-time entropy is proposed as a means to estimate the actual delivery time reliability. The less the entropy is, the stronger the delivery time reliability remains, and vice versa. The shortest delivery time is computed separately based on two different assumptions. If a path is concerned without capacity restriction, the shortest delivery time is positively related to the length of the shortest path, and if a path is concerned with capacity restriction, a minimax programming model is built to figure up the shortest delivery time. Finally, an example is utilized to confirm the validity and practicality of the proposed approach.
An improved network model for railway traffic
Li, Keping; Ma, Xin; Shao, Fubo
In railway traffic, safety analysis is a key issue for controlling train operation. Here, the identification and order of key factors are very important. In this paper, a new network model is constructed for analyzing the railway safety, in which nodes are regarded as causation factors and links represent possible relationships among those factors. Our aim is to give all these nodes an importance order, and to find the in-depth relationship among these nodes including how failures spread among them. Based on the constructed network model, we propose a control method to ensure the safe state by setting each node a threshold. As the results, by protecting the Hub node of the constructed network, the spreading of railway accident can be controlled well. The efficiency of such a method is further tested with the help of numerical example.
Methodically Modeling the Tor Network
2012-08-01
iPlane [7] and CAIDA [3]. Third, determining a better client model would further increase confidence in experimental results. Producing a more robust...Bandwidth Speed Test. http://speedtest.net/. [3] CAIDA Data. http://www.caida.org/data. [4] DETER Testbed. http://www.isi.edu/deter. [5] Emulab
Network Model Building (Process Mapping)
Blau, Gary; Yih, Yuehwern
2004-01-01
12 slides Provider Notes:See Project Planning Video (Windows Media) Posted at the bottom are Gary Blau's slides. Before watching, please note that "process mapping" and "modeling" are mentioned in the video and notes. Here they are meant to refer to the NSCORT "project plan"
Self-organized Collaboration Network Model Based on Module Emerging
Yang, Hongyong; Lu, Lan; Liu, Qiming
Recently, the studies of the complex network have gone deep into many scientific fields, such as computer science, physics, mathematics, sociology, etc. These researches enrich the realization for complex network, and increase understands for the new characteristic of complex network. Based on the evolvement characteristic of the author collaboration in the scientific thesis, a self-organized network model of the scientific cooperation network is presented by module emerging. By applying the theoretical analysis, it is shown that this network model is a scale-free network, and the strength degree distribution and the module degree distribution of the network nodes have the same power law. In order to make sure the validity of the theoretical analysis for the network model, we create the computer simulation and demonstration collaboration network. By analyzing the data of the network, the results of the demonstration network and the computer simulation are consistent with that of the theoretical analysis of the model.
Bayesian Network Based XP Process Modelling
Directory of Open Access Journals (Sweden)
Mohamed Abouelela
2010-07-01
Full Text Available A Bayesian Network based mathematical model has been used for modelling Extreme Programmingsoftware development process. The model is capable of predicting the expected finish time and theexpected defect rate for each XP release. Therefore, it can be used to determine the success/failure of anyXP Project. The model takes into account the effect of three XP practices, namely: Pair Programming,Test Driven Development and Onsite Customer practices. The model’s predictions were validated againsttwo case studies. Results show the precision of our model especially in predicting the project finish time.
Institute of Scientific and Technical Information of China (English)
门志梅
2012-01-01
There are 1264 university students who been selected to survey the relationship between network communication and interpersonal attachment by questionnaire investigation. The results showed that： the feature of network communication and interpersonal attachment had gender and grade difference; university students＇ interpersonal attachment has certain forecast on network communication.%以1264名大学生为被试,采用问卷调查法探讨大学生网络人际交往与人际依恋的关系。结果发现：大学生网络人际交往与人际依恋存在着性别和年级差异;大学生人际依恋在一定程度上对网络人际交往有一定的预测作用。
Modeling of Network Identification Capability.
1986-07-01
scalar moment is assumed to follow a Poisson distribution, as suggested by Lomnitz (1966). The A cumulative number of events occurring per year at or...Spectral Ratios from Point Sources in Plane-Layered Earth V Models," BSSA. 60, pp 1937-1987 Lomnitz . C. (1966). -Statistical Prediction of Earthquakes...Moment-Magritude Relations in Theory and Practice," J Geophy. Res., 89 (B7). pp. 6229-6235. Lomnitz , C. (1966), Statistical Prediction of Earthquakes
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.
Psychometric Measurement Models and Artificial Neural Networks
Sese, Albert; Palmer, Alfonso L.; Montano, Juan J.
2004-01-01
The study of measurement models in psychometrics by means of dimensionality reduction techniques such as Principal Components Analysis (PCA) is a very common practice. In recent times, an upsurge of interest in the study of artificial neural networks apt to computing a principal component extraction has been observed. Despite this interest, the…
A generalized network model for polymeric liquids
Jongschaap, R.J.J.; Kamphuis, H.; Doeksen, D.K.
1983-01-01
A kinetic model was developed for relating the molecular structure and the rheological behaviour of polymer-like materials in which bonds are being created and broken. In particular, the stress contribution of molecules that are not a part of the network was taken account of. In two limiting cases
The Kuramoto model in complex networks
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.
Modelling crime linkage with Bayesian networks
J. de Zoete; M. Sjerps; D. Lagnado; N. Fenton
2015-01-01
When two or more crimes show specific similarities, such as a very distinct modus operandi, the probability that they were committed by the same offender becomes of interest. This probability depends on the degree of similarity and distinctiveness. We show how Bayesian networks can be used to model
Dynamic Pathloss Model for Future Mobile Communication Networks
DEFF Research Database (Denmark)
Kumar, Ambuj; Mihovska, Albena Dimitrova; Prasad, Ramjee
2016-01-01
— 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...... that incorporates the environmental dynamics factor in the propagation model for intelligent and proactively iterative networks...
A Model of Mental State Transition Network
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.
Hybrid simulation models of production networks
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.
Model for the evolution of river networks
Energy Technology Data Exchange (ETDEWEB)
Leheny, R.L.; Nagel, S.R. (The James Franck Institute and the Department of Physics, The University of Chicago, 5640 South Ellis Avenue, Chicago, Illinois 60637 (United States))
1993-08-30
We have developed a model, which includes the effects of erosion both from precipitation and from avalanching of soil on steep slopes, to simulate the formation and evolution of river networks. The avalanches provide a mechanism for competition in growth between neighboring river basins. The changing morphology follows many of the characteristics of evolution set forth by Glock. We find that during evolution the model maintains the statistical characteristics measured in natural river systems.
Investigating complex networks with inverse models
Wens, Vincent
2014-01-01
Recent advances in neuroscience have motivated the study of network organization in spatially distributed dynamical systems from indirect measurements. However, the associated connectivity estimation, when combined with inverse modeling, is strongly affected by spatial leakage. We formulate this problem in a general framework and develop a new approach to model spatial leakage and limit its effects. It is analytically compared to existing regression-based methods used in electrophysiology, which are shown to yield biased estimates of amplitude and phase couplings.
Attachment-related psychodynamics.
Shaver, Phillip R; Mikulincer, Mario
2002-09-01
Because there has been relatively little communication and cross-fertilization between the two major lines of research on adult attachment, one based on coded narrative assessments of defensive processes, the other on simple self-reports of 'attachment style' in close relationships, we here explain and review recent work based on a combination of self-report and other kinds of method, including behavioral observations and unconscious priming techniques. The review indicates that considerable progress has been made in testing central hypotheses derived from attachment theory and in exploring unconscious, psychodynamic processes related to affect-regulation and attachment-system activation. The combination of self-report assessment of attachment style and experimental manipulation of other theoretically pertinent variables allows researchers to test causal hypotheses. We present a model of normative and individual-difference processes related to attachment and identify areas in which further research is needed and likely to be successful. One long-range goal is to create a more complete theory of personality built on attachment theory and other object relations theories.
Distance distribution in configuration-model networks
Nitzan, Mor; Katzav, Eytan; Kühn, Reimer; Biham, Ofer
2016-06-01
We present analytical results for the distribution of shortest path lengths between random pairs of nodes in configuration model networks. The results, which are based on recursion equations, are shown to be in good agreement with numerical simulations for networks with degenerate, binomial, and power-law degree distributions. The mean, mode, and variance of the distribution of shortest path lengths are also evaluated. These results provide expressions for central measures and dispersion measures of the distribution of shortest path lengths in terms of moments of the degree distribution, illuminating the connection between the two distributions.
Functional model of biological neural networks.
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.
Empirical generalization assessment of neural network models
DEFF Research Database (Denmark)
Larsen, Jan; Hansen, Lars Kai
1995-01-01
competing models. Since all models are trained on the same data, a key issue is to take this dependency into account. The optimal split of the data set of size N into a cross-validation set of size Nγ and a training set of size N(1-γ) is discussed. Asymptotically (large data sees), γopt→1......This paper addresses the assessment of generalization performance of neural network models by use of empirical techniques. We suggest to use the cross-validation scheme combined with a resampling technique to obtain an estimate of the generalization performance distribution of a specific model...
A Networks Approach to Modeling Enzymatic Reactions.
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.
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.
Network transmission model: A dynamic traffic model at network level (poster)
Knoop, V.L.; Hoogendoorn, S.P.
2014-01-01
New IT techniques allow communication and coordination between traffic measures. To best use this, one needs to coordinate over longer distances. Optimization of the measures is not possible using traditional microscopic or macroscopic simulation models. The Network Fundamental Diagram (NFD)
Characterizing Attention with Predictive Network Models.
Rosenberg, M D; Finn, E S; Scheinost, D; Constable, R T; Chun, M M
2017-04-01
Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals' attentional abilities. While being some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that: (i) attention is a network property of brain computation; (ii) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task; and (iii) this architecture supports a general attentional ability that is common to several laboratory-based tasks and is impaired in attention deficit hyperactivity disorder (ADHD). Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. Copyright © 2017 Elsevier Ltd. All rights reserved.
Higher-dimensional models of networks
Spivak, David I
2009-01-01
Networks are often studied as graphs, where the vertices stand for entities in the world and the edges stand for connections between them. While relatively easy to study, graphs are often inadequate for modeling real-world situations, especially those that include contexts of more than two entities. For these situations, one typically uses hypergraphs or simplicial complexes. In this paper, we provide a precise framework in which graphs, hypergraphs, simplicial complexes, and many other categories, all of which model higher graphs, can be studied side-by-side. We show how to transform a hypergraph into its nearest simplicial analogue, for example. Our framework includes many new categories as well, such as one that models broadcasting networks. We give several examples and applications of these ideas.
Threshold model of cascades in temporal networks
Karimi, Fariba
2012-01-01
Threshold models try to explain the consequences of social influence like the spread of fads and opinions. Along with models of epidemics, they constitute a major theoretical framework of social spreading processes. In threshold models on static networks, an individual changes her state if a certain fraction of her neighbors has done the same. When there are strong correlations in the temporal aspects of contact patterns, it is useful to represent the system as a temporal network. In such a system, not only contacts but also the time of the contacts are represented explicitly. There is a consensus that bursty temporal patterns slow down disease spreading. However, as we will see, this is not a universal truth for threshold models. In this work, we propose an extension of Watts' classic threshold model to temporal networks. We do this by assuming that an agent is influenced by contacts which lie a certain time into the past. I.e., the individuals are affected by contacts within a time window. In addition to th...
The noisy voter model on complex networks
Carro, Adrián; Miguel, Maxi San
2016-01-01
We propose a new analytical method to study stochastic, binary-state models on complex networks. Moving beyond the usual mean-field theories, this alternative approach is based on the introduction of an uncorrelated network approximation, allowing to deal with the network structure as parametric heterogeneity. As an illustration, we study the noisy voter model, a modification of the original voter model including random changes of state. The proposed method is able to unfold the dependence of the model not only on the mean degree (the mean-field prediction) but also on more complex averages over the degree distribution. In particular, we find that the degree heterogeneity ---variance of the underlying degree distribution--- has a strong influence on the location of the critical point of a noise-induced, finite-size transition occurring in the model, on the local ordering of the system, and on the functional form of its temporal correlations. Finally, we show how this latter point opens the possibility of infe...
Entanglement effects in model polymer networks
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
Network Strategies in the Voter Model
Javarone, Marco Alberto
2013-01-01
We study a simple voter model with two competing parties. In particular, we represent the case of political elections, where people can choose to support one of the two competitors or to remain neutral. People interact in a social network and their opinion depends on those of their neighbors. Therefore, people may change opinion over time, i.e., they can support one competitor or none. The two competitors try to gain the people's consensus by interacting with their neighbors and also with other people. In particular, competitors define temporal connections, following a strategy, to interact with people they do not know, i.e., with all the people that are not their neighbors. We analyze the proposed model to investigate which network strategies are more advantageous, for the competitors, in order to gain the popular consensus. As result, we found that the best network strategy depends on the topology of the social network. Finally, we investigate how the charisma of competitors affects the outcomes of the prop...
Models and Algorithm for Stochastic Network Designs
Institute of Scientific and Technical Information of China (English)
Anthony Chen; Juyoung Kim; Seungjae Lee; Jaisung Choi
2009-01-01
The network design problem (NDP) is one of the most difficult and challenging problems in trans-portation. Traditional NDP models are often posed as a deterministic bilevel program assuming that all rele-vant inputs are known with certainty. This paper presents three stochastic models for designing transporta-tion networks with demand uncertainty. These three stochastic NDP models were formulated as the ex-pected value model, chance-constrained model, and dependent-chance model in a bilevel programming framework using different criteria to hedge against demand uncertainty. Solution procedures based on the traffic assignment algorithm, genetic algorithm, and Monte-Cado simulations were developed to solve these stochastic NDP models. The nonlinear and nonconvex nature of the bilevel program was handled by the genetic algorithm and traffic assignment algorithm, whereas the stochastic nature was addressed through simulations. Numerical experiments were conducted to evaluate the applicability of the stochastic NDP models and the solution procedure. Results from the three experiments show that the solution procedures are quite robust to different parameter settings.
Microbial growth modelling with artificial neural networks.
Jeyamkonda, S; Jaya, D S; Holle, R A
2001-03-20
There is a growing interest in modelling microbial growth as an alternative to time-consuming, traditional, microbiological enumeration techniques. Several statistical models have been reported to describe the growth of different microorganisms, but there are accuracy problems. An alternate technique 'artificial neural networks' (ANN) for modelling microbial growth is explained and evaluated. Published data were used to build separate general regression neural network (GRNN) structures for modelling growth of Aeromonas hydrophila, Shigella flexneri, and Brochothrix thermosphacta. Both GRNN and published statistical model predictions were compared against the experimental data using six statistical indices. For training data sets, the GRNN predictions were far superior than the statistical model predictions, whereas the GRNN predictions were similar or slightly worse than statistical model predictions for test data sets for all the three data sets. GRNN predictions can be considered good, considering its performance for unseen data. Graphical plots, mean relative percentage residual, mean absolute relative residual, and root mean squared residual were identified as suitable indices for comparing competing models. ANN can now become a vehicle whereby predictive microbiology can be applied in food product development and food safety risk assessment.
Performance modeling, loss networks, and statistical multiplexing
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
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.
Miles, R N
2016-03-01
A mathematical model is presented to examine the propagation of bending waves on a plant stem that are induced by vibratory excitation from an attached insect. This idealized model represents the insect body as a mass and the legs as a linear spring along with a general time-varying force that is assumed to act in parallel with the spring. The spring connects the mass to a stem modeled as a beam having uniform geometric and material properties. The linearly elastic beam is assumed to undergo pure vibratory bending and to be infinitely long in each direction. The equations that govern the insect-induced, coupled motions of both the beam and the mass are solved for arbitrary time varying forces produced by the insect's legs. Solutions for the frequency response indicate that the response is dominated by frequency components near the natural resonant frequency of the attached insect while at higher frequencies the amplitude of the response is strongly influenced only by the properties of the stem.
Jeong, Sinwoo; Cho, Jae Yong; Sung, Tae Hyun; Yoo, Hong Hee
2017-03-01
Conventional vibration-based piezoelectric energy harvesters (PEHs) have advantages including the ubiquity of their energy source and their ease of manufacturing. However, they have a critical disadvantage as well: they can produce a reasonable amount of power only if the excitation frequency is concentrated near a natural frequency of the PEH. Because the excitation frequency is often spread and/or variable, it is very difficult to successfully design a conventional PEH. In this paper, we propose a new cantilevered PEH whose design includes an attached mass and a segmented piezoelectric layer. By choosing a proper size and location for the attached mass, the gap between the first and second natural frequencies of the PEH can be decreased in order to broaden the effective excitation frequency range and thus to allow reasonable power generation. Especially, the output power performance improves significantly around the second natural frequency of the PEH since the voltage cancellation effect can be made very weak by segmenting the piezoelectric layer at an appropriate location. To investigate the power performance of the new PEH, herein a reduced-order electromechanical analysis model is proposed and the accuracy of this model is validated experimentally. The effects of variable load resistance and piezoelectric layer segmentation location upon the power performance of the new PEH are investigated by means of the reduced-order analysis model.
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)
Network models of frequency modulated sweep detection.
Directory of Open Access Journals (Sweden)
Steven Skorheim
Full Text Available Frequency modulated (FM sweeps are common in species-specific vocalizations, including human speech. Auditory neurons selective for the direction and rate of frequency change in FM sweeps are present across species, but the synaptic mechanisms underlying such selectivity are only beginning to be understood. Even less is known about mechanisms of experience-dependent changes in FM sweep selectivity. We present three network models of synaptic mechanisms of FM sweep direction and rate selectivity that explains experimental data: (1 The 'facilitation' model contains frequency selective cells operating as coincidence detectors, summing up multiple excitatory inputs with different time delays. (2 The 'duration tuned' model depends on interactions between delayed excitation and early inhibition. The strength of delayed excitation determines the preferred duration. Inhibitory rebound can reinforce the delayed excitation. (3 The 'inhibitory sideband' model uses frequency selective inputs to a network of excitatory and inhibitory cells. The strength and asymmetry of these connections results in neurons responsive to sweeps in a single direction of sufficient sweep rate. Variations of these properties, can explain the diversity of rate-dependent direction selectivity seen across species. We show that the inhibitory sideband model can be trained using spike timing dependent plasticity (STDP to develop direction selectivity from a non-selective network. These models provide a means to compare the proposed synaptic and spectrotemporal mechanisms of FM sweep processing and can be utilized to explore cellular mechanisms underlying experience- or training-dependent changes in spectrotemporal processing across animal models. Given the analogy between FM sweeps and visual motion, these models can serve a broader function in studying stimulus movement across sensory epithelia.
Systems biology of plant molecular networks: from networks to models
Valentim, F.L.
2015-01-01
Developmental processes are controlled by regulatory networks (GRNs), which are tightly coordinated networks of transcription factors (TFs) that activate and repress gene expression within a spatial and temporal context. In Arabidopsis thaliana, the key components and network structures of the GRNs
Advances in dynamic network modeling in complex transportation systems
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.
New Federated Collaborative Networked Organization Model (FCNOM
Directory of Open Access Journals (Sweden)
Morcous M. Yassa
2012-01-01
Full Text Available Formation of Collaborative Networked Organization (CNO usually comes upon expected business opportunities and needs huge of negotiation during its lifecycle, especially to increase the Dynamic Virtual Organization (DVO configuration automation. Decision makers need more comprehensive information about CNO system to support their decisions. Unfortunately, there is no single formal modeling, tool, approach or any comprehensive methodology that covers all perspectives. In spite of there are some approaches to model CNO have been existed, these approaches model the CNO either with respect to the technology, or business without considering organizational behavior, federation modeling, and external environments. The aim of this paper is to propose an integrated framework that combines the existed modeling perspectives, as well as, proposes new ones. Also, it provides clear CNO boundaries. By using this approach the view of CNO environment becomes clear and unified. Also, it minimizes the negotiations within CNO components during its life cycle, supports DVO configuration automation, as well as, helps decision making for DVO, and achieves harmonization between CNO partners. The proposed FCNOM utilizes CommonKADS methodology organization model for describing CNO components. Insurance Collaborative Network has been used as an example to proof the proposed FCNOM model.
Antiferromagnetic Ising Model in Hierarchical Networks
Cheng, Xiang; Boettcher, Stefan
2015-03-01
The Ising antiferromagnet is a convenient model of glassy dynamics. It can introduce geometric frustrations and may give rise to a spin glass phase and glassy relaxation at low temperatures [ 1 ] . We apply the antiferromagnetic Ising model to 3 hierarchical networks which share features of both small world networks and regular lattices. Their recursive and fixed structures make them suitable for exact renormalization group analysis as well as numerical simulations. We first explore the dynamical behaviors using simulated annealing and discover an extremely slow relaxation at low temperatures. Then we employ the Wang-Landau algorithm to investigate the energy landscape and the corresponding equilibrium behaviors for different system sizes. Besides the Monte Carlo methods, renormalization group [ 2 ] is used to study the equilibrium properties in the thermodynamic limit and to compare with the results from simulated annealing and Wang-Landau sampling. Supported through NSF Grant DMR-1207431.
Gianturco, F. A.; Grassi, T.; Wester, R.
2016-10-01
The fairly recent detection of a variety of anions in the interstellar molecular clouds have underlined the importance of realistically modelling the processes governing their abundance. To pursue this task, our earlier calculations for the radiative electron attachment (REA) rates for C4H-, C6H-, and C8H- are employed in the present work, within a broad network of other concurrent reactions, to generate the corresponding column density ratios of anion/neutral (A/N) relative abundances. The latter are then compared with those obtained in recent years from observational measurements. The calculations involved the time-dependent solutions of a large network of chemical processes over an extended time interval and included a series of runs in which the values of REA rates were repeatedly scaled over several orders of magnitude. Macroscopic parameters for the Clouds’ modelling were also varied to cover a broad range of physical environments. It was found that, within the range and quality of the processes included in the present network,and selected from state-of-the-art astrophysical databases, the REA values required to match the observed A/N ratios needed to be reduced by orders of magnitude for C4H- case, while the same rates for C6H- and C8H- only needed to be scaled by much smaller factors. The results suggest that the generally proposed formation of interstellar anions by REA mechanism is overestimated by current models for the C4H- case, for which is likely to be an inefficient path to formation. This path is thus providing a rather marginal contribution to the observed abundances of C4H-, the latter being more likely to originate from other chemical processes in the network, as we discuss in some detail in the present work. Possible physical reasons for the much smaller differences against observations found instead for the values of the (A/N) ratios in two other, longer members of the series are put forward and analysed within the evolutionary modelling
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.
Electronic circuits modeling using artificial neural networks
Directory of Open Access Journals (Sweden)
Andrejević Miona V.
2003-01-01
Full Text Available In this paper artificial neural networks (ANN are applied to modeling of electronic circuits. ANNs are used for application of the black-box modeling concept in the time domain. Modeling process is described, so the topology of the ANN, the testing signal used for excitation, together with the complexity of ANN are considered. The procedure is first exemplified in modeling of resistive circuits. MOS transistor, as a four-terminal device, is modeled. Then nonlinear negative resistive characteristic is modeled in order to be used as a piece-wise linear resistor in Chua's circuit. Examples of modeling nonlinear dynamic circuits are given encompassing a variety of modeling problems. A nonlinear circuit containing quartz oscillator is considered for modeling. Verification of the concept is performed by verifying the ability of the model to generalize i.e. to create acceptable responses to excitations not used during training. Implementation of these models within a behavioral simulator is exemplified. Every model is implemented in realistic surrounding in order to show its interaction, and of course, its usage and purpose.
A study of the spreading scheme for viral marketing based on a complex network model
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.
Modeling social influence through network autocorrelation : constructing the weight matrix
Leenders, RTAJ
2002-01-01
Many physical and social phenomena are embedded within networks of interdependencies, the so-called 'context' of these phenomena. In network analysis, this type of process is typically modeled as a network autocorrelation model. Parameter estimates and inferences based on autocorrelation models, hin
A Universal Model of Commuting Networks
Lenormand, Maxime; Gargiulo, Floriana; Deffuant, Guillaume
2012-01-01
We test a recently proposed model of commuting networks on 80 case studies from different regions of the world (Europe and United-States) and with geographic units of different sizes (municipality, county, region). The model takes as input the number of commuters coming in and out of each geographic unit and generates the matrix of commuting flows betwen the geographic units. We show that the single parameter of the model, which rules the compromise between the influence of the distance and job opportunities, follows a universal law that depends only on the average surface of the geographic units. We verified that the law derived from a part of the case studies yields accurate results on other case studies. We also show that our model significantly outperforms the two other approaches proposing a universal commuting model (Balcan et al. (2009); Simini et al. (2012)), particularly when the geographic units are small (e.g. municipalities).
Dual random circuit breaker network model with equivalent thermal circuit network
Kim, Kwanyong; Yoon, Seong Jun; Choi, Woo Young
2014-02-01
A SPICE-based dual random circuit breaker (RCB) network model with an equivalent thermal circuit network has been proposed in order to emulate resistance switching (RS) of unipolar resistive random access memory (RRAM). The dual RCB network model consists of the electrical RCB network model for the forming and set operations and the equivalent thermal circuit network model for the reset operation. In addition, the proposed model can explain the effects of heat dissipation on the memory and threshold RS with the variation in electrode thickness.
A network model for Ebola spreading.
Rizzo, Alessandro; Pedalino, Biagio; Porfiri, Maurizio
2016-04-01
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.
Evolutionary algorithms in genetic regulatory networks model
Raza, Khalid
2012-01-01
Genetic Regulatory Networks (GRNs) plays a vital role in the understanding of complex biological processes. Modeling GRNs is significantly important in order to reveal fundamental cellular processes, examine gene functions and understanding their complex relationships. Understanding the interactions between genes gives rise to develop better method for drug discovery and diagnosis of the disease since many diseases are characterized by abnormal behaviour of the genes. In this paper we have reviewed various evolutionary algorithms-based approach for modeling GRNs and discussed various opportunities and challenges.
Lassri, Dana; Luyten, Patrick; Cohen, Guina; Shahar, Golan
2016-07-01
Despite growing recognition of the importance of childhood emotional maltreatment (CEM) on the development of psychopathology, very few studies have addressed its impact on adult romantic relationship functioning, particularly among otherwise relatively well-functioning individuals. In an attempt to further elucidate the mechanism underlying the negative impact of CEM on romantic relationships, we tested an integrative mediational model linking CEM to romantic relationships through the impact of CEM on the development of self-criticism and adult attachment. Recent work in this context suggests that while self-criticism concerns broad cognitive-affective schemas related to achievement and failure, attachment avoidance assesses the expression of these broad schemas in close relationships (Luyten & Blatt, 2011; Sibley & Overall, 2008, 2010). This hypothesized mediational model was examined in a sample of young adult undergraduates (N = 99, 85 female), using structural equation modeling. The mediational model was in large part supported. Attachment avoidance, but not attachment anxiety, fully accounted for the mediating role of self-criticism in the relationship between CEM and romantic relationship satisfaction, even when controlling for the potential role of concurrent levels of posttraumatic stress disorder severity. Understanding the long-term psychological dynamics related to CEM and identifying mediating vulnerability factors-self-criticism and attachment avoidance-might have implications for both the assessment and treatment of individuals with a history of CEM, particularly as effective interventions to address self-criticism and attachment issues are available. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
Lovejoy, Andrew E.; Jegley, Dawn C. (Technical Monitor)
2007-01-01
Structures often comprise smaller substructures that are connected to each other or attached to the ground by a set of finite connections. Under static loading one or more of these connections may exceed allowable limits and be deemed to fail. Of particular interest is the structural response when a connection is severed (failed) while the structure is under static load. A transient failure analysis procedure was developed by which it is possible to examine the dynamic effects that result from introducing a discrete failure while a structure is under static load. The failure is introduced by replacing a connection load history by a time-dependent load set that removes the connection load at the time of failure. The subsequent transient response is examined to determine the importance of the dynamic effects by comparing the structural response with the appropriate allowables. Additionally, this procedure utilizes a standard finite element transient analysis that is readily available in most commercial software, permitting the study of dynamic failures without the need to purchase software specifically for this purpose. The procedure is developed and explained, demonstrated on a simple cantilever box example, and finally demonstrated on a real-world example, the American Airlines Flight 587 (AA587) vertical tail plane (VTP).
Application of the Passionate Attachment Model to Recreational Use of MDMA/Ecstasy.
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.
Shtylla, Blerta
2013-01-01
Before cell division, two identical copies of chromosomes are pulled apart by microtubule (MT) filaments that approach the chromosomes from the opposite poles a mitotic spindle. Connection between the MTs and the chromosomes are mediated by a molecular complex called kinetochore. An externally applied tension can lead to detachment of the MTs from the kinetochore; the mean lifetime of such an attachment is essentially a mean first-passage time. In their in-vitro pioneering single-kinetochore experiments, Akiyoshi et al. (Nature 468, 576 (2010)), observed that the mean lifetimes of reconstituted MT-kinetochore attachments vary non-monotonically with increasing tension. The counter-intuitive stabilization of the attachments by small load forces was interpreted in terms of a catch-bond-like mechanism based on a phenomenological 2-state kinetic model. Here we develop the first detailed microscopic model for studying the dependence of the lifetime of the MT-kinetochore attachment on (a) the structure, (b) energeti...
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...... network....
Network Modeling of Crohn's Disease Incidence.
Directory of Open Access Journals (Sweden)
Jean-Marc Victor
Full Text Available Numerous genetic and environmental risk factors play a role in human complex genetic disorders (CGD. However, their complex interplay remains to be modelled and explained in terms of disease mechanisms.Crohn's Disease (CD was modeled as a modular network of patho-physiological functions, each summarizing multiple gene-gene and gene-environment interactions. The disease resulted from one or few specific combinations of module functional states. Network aging dynamics was able to reproduce age-specific CD incidence curves as well as their variations over the past century in Western countries. Within the model, we translated the odds ratios (OR associated to at-risk alleles in terms of disease propensities of the functional modules. Finally, the model was successfully applied to other CGD including ulcerative colitis, ankylosing spondylitis, multiple sclerosis and schizophrenia.Modeling disease incidence may help to understand disease causative chains, to delineate the potential of personalized medicine, and to monitor epidemiological changes in CGD.
A Packet Routing Model for Computer Networks
Directory of Open Access Journals (Sweden)
O. Osunade
2012-05-01
Full Text Available The quest for reliable data transmission in today’s computer networks and internetworks forms the basis for which routing schemes need be improved upon. The persistent increase in the size of internetwork leads to a dwindling performance of the present routing algorithms which are meant to provide optimal path for forwarding packets from one network to the other. A mathematical and analytical routing model framework is proposed to address the routing needs to a substantial extent. The model provides schemes typical of packet sources, queuing system within a buffer, links and bandwidth allocation and time-based bandwidth generator in routing chunks of packets to their destinations. Principal to the choice of link are such design considerations as least-congested link in a set of links, normalized throughput, mean delay and mean waiting time and the priority of packets in a set of prioritized packets. These performance metrics were targeted and the resultant outcome is a fair, load-balanced network.
Cecilia Serena ePace; Simona eDi Folco; Viviana eGuerriero; Alessandra eSantona; Grazia eTerrone
2015-01-01
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 rese...
Towards a Realistic Model for Failure Propagation in Interdependent Networks
Sturaro, Agostino; Conti, Mauro; Das, Sajal K
2015-01-01
Modern networks are becoming increasingly interdependent. As a prominent example, the smart grid is an electrical grid controlled through a communications network, which in turn is powered by the electrical grid. Such interdependencies create new vulnerabilities and make these networks more susceptible to failures. In particular, failures can easily spread across these networks due to their interdependencies, possibly causing cascade effects with a devastating impact on their functionalities. In this paper we focus on the interdependence between the power grid and the communications network, and propose a novel realistic model, HINT (Heterogeneous Interdependent NeTworks), to study the evolution of cascading failures. Our model takes into account the heterogeneity of such networks as well as their complex interdependencies. We compare HINT with previously proposed models both on synthetic and real network topologies. Experimental results show that existing models oversimplify the failure evolution and network...
Reflection and attachment of spirals at obstacles for the Fitzhugh-Nagumo and Beeler-Reuter models.
Olmos, Daniel
2010-04-01
In this paper, the Fitzhugh-Nagumo (FHN) equations and a modified FHN (MFHN) are considered. For the modified version, the recovery variable v has three different time scales. By considering different parameters in the local dynamics of the MFHN equations, it is observed that the phenomenon of reflection and annihilation at an impermeable boundary is observed just as in the Beeler-Reuter model. The interaction of spirals obtained with the FHN, MFHN, and Beeler-Reuter model, and an obstacle is also considered. The phenomenon of reflection of the spiral wave at a boundary changes when the boundary becomes an obstacle. Four properties for attachment of a spiral wave to an obstacle are presented in this work.
A hybrid neural network model for consciousness
Institute of Scientific and Technical Information of China (English)
蔺杰; 金小刚; 杨建刚
2004-01-01
A new framework for consciousness is introduced based upon traditional artificial neural network models. This framework reflects explicit connections between two parts of the brain: one global working memory and distributed modular cerebral networks relating to specific brain functions. Accordingly this framework is composed of three layers,physical mnemonic layer and abstract thinking layer,which cooperate together through a recognition layer to accomplish information storage and cognition using algorithms of how these interactions contribute to consciousness:(1)the reception process whereby cerebral subsystems group distributed signals into coherent object patterns;(2)the partial recognition process whereby patterns from particular subsystems are compared or stored as knowledge; and(3)the resonant learning process whereby global workspace stably adjusts its structure to adapt to patterns' changes. Using this framework,various sorts of human actions can be explained,leading to a general approach for analyzing brain functions.
A hybrid neural network model for consciousness
Institute of Scientific and Technical Information of China (English)
蔺杰; 金小刚; 杨建刚
2004-01-01
A new framework for consciousness is introduced based upon traditional artificial neural network models. This framework reflects explicit connections between two parts of the brain: one global working memory and distributed modular cerebral networks relating to specific brain functions. Accordingly this framework is composed of three layers, physical mnemonic layer and abstract thinking layer, which cooperate together through a recognition layer to accomplish information storage and cognition using algorithms of how these interactions contribute to consciousness: (l) the reception process whereby cerebral subsystems group distributed signals into coherent object patterns; (2) the partial recognition process whereby patterns from particular subsystems are compared or stored as knowledge; and (3) the resonant learning process whereby global workspace stably adjusts its structure to adapt to patterns' changes. Using this framework, various sorts of human actions can be explained, leading to a general approach for analyzing brain functions.
Neural Network Program Package for Prosody Modeling
Directory of Open Access Journals (Sweden)
J. Santarius
2004-04-01
Full Text Available This contribution describes the programme for one part of theautomatic Text-to-Speech (TTS synthesis. Some experiments (for example[14] documented the considerable improvement of the naturalness ofsynthetic speech, but this approach requires completing the inputfeature values by hand. This completing takes a lot of time for bigfiles. We need to improve the prosody by other approaches which useonly automatically classified features (input parameters. Theartificial neural network (ANN approach is used for the modeling ofprosody parameters. The program package contains all modules necessaryfor the text and speech signal pre-processing, neural network training,sensitivity analysis, result processing and a module for the creationof the input data protocol for Czech speech synthesizer ARTIC [1].
Modelling Traffic in IMS Network Nodes
Directory of Open Access Journals (Sweden)
BA Alassane
2013-07-01
Full Text Available IMS is well integrated with existing voice and data networks, while adopting many of their keycharacteristics.The Call Session Control Functions (CSCFs servers are the key part of the IMS structure. They are themain components responsible for processing and routing signalling messages.When CSCFs servers (P-CSCF, I-CSCF, S-CSCF are running on the same host, the SIP message can beinternally passed between SIP servers using a single operating system mechanism like a queue. It increasesthe reliability of the network [5], [6]. We have proposed in a last work for each type of service (between ICSCFand S-CSCF (call, data, multimedia.[23], to use less than two servers well dimensioned andrunning on the same operating system.Instead dimensioning servers, in order to increase performance, we try to model traffic on IMS nodes,particularly on entries nodes; it will provide results on separation of incoming flows, and then offer moresatisfactory service.
Aeronautical telecommunications network advances, challenges, and modeling
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...
Logic integer programming models for signaling networks.
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.
Quantifying robustness of biochemical network models
Directory of Open Access Journals (Sweden)
Iglesias Pablo A
2002-12-01
Full Text Available Abstract Background Robustness of mathematical models of biochemical networks is important for validation purposes and can be used as a means of selecting between different competing models. Tools for quantifying parametric robustness are needed. Results Two techniques for describing quantitatively the robustness of an oscillatory model were presented and contrasted. Single-parameter bifurcation analysis was used to evaluate the stability robustness of the limit cycle oscillation as well as the frequency and amplitude of oscillations. A tool from control engineering – the structural singular value (SSV – was used to quantify robust stability of the limit cycle. Using SSV analysis, we find very poor robustness when the model's parameters are allowed to vary. Conclusion The results show the usefulness of incorporating SSV analysis to single parameter sensitivity analysis to quantify robustness.
Combining logistic regression and neural networks to create predictive models.
Spackman, K. A.
1992-01-01
Neural networks are being used widely in medicine and other areas to create predictive models from data. The statistical method that most closely parallels neural networks is logistic regression. This paper outlines some ways in which neural networks and logistic regression are similar, shows how a small modification of logistic regression can be used in the training of neural network models, and illustrates the use of this modification for variable selection and predictive model building wit...
Optimizing neural network models: motivation and case studies
Harp, S A; T. Samad
2012-01-01
Practical successes have been achieved with neural network models in a variety of domains, including energy-related industry. The large, complex design space presented by neural networks is only minimally explored in current practice. The satisfactory results that nevertheless have been obtained testify that neural networks are a robust modeling technology; at the same time, however, the lack of a systematic design approach implies that the best neural network models generally rem...
TCP-IP Model in Data Communication and Networking
Pranab Bandhu Nath; Md.Mofiz Uddin
2015-01-01
The Internet protocol suite is the computer networking model and set of communications protocols used on the Internet and similar computer networks. It is commonly known as TCP/IP, because it’s most important protocols, the Transmission Control Protocol (TCP) and the Internet Protocol (IP), were the first networking protocols defined in this standard. Often also called the Internet model, it was originally also known as the DoD model, because the development of the networking mode...
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.
Synchronizability Analysis of Harmonious Unification Hybrid Preferential Model
Institute of Scientific and Technical Information of China (English)
无
2011-01-01
The harmonious unification hybrid preferential model uses the dr ratio to adjust the proportion of deterministic preferential attachment and random preferential attachment, enriched the only deterministic preferential network model,
Modeling of regional warehouse network generation
Directory of Open Access Journals (Sweden)
Popov Pavel Vladimirovich
2016-08-01
Full Text Available One of the factors that has a significant impact on the socio-economic development of the Russian Federation’s regions is the logistics infrastructure. It provides integrated transportation and distribution service of material flows. One of the main elements of logistics infrastructure is a storage infrastructure, which includes distribution center, distribution-and-sortout and sortout warehouses. It is the most expedient to place distribution center in the vicinity of the regional center. One of the tasks of the distribution network creation within the regions of the Russian Federation is to determine the location, capacity and number of stores. When determining regional network location of general purpose warehouses methodological approaches to solving the problems of location of production and non-production can be used which depend on various economic factors. The mathematical models for solving relevant problems are the deployment models. However, the existing models focus on the dimensionless power storage. The purpose of the given work is to develop a model to determine the optimal location of general-purpose warehouses on the Russian Federation area. At the first stage of the work, the authors assess the main economic indicators influencing the choice of the location of general purpose warehouses. An algorithm for solving the first stage, based on ABC, discriminant and cluster analysis were proposed by the authors in earlier papers. At the second stage the specific locations of general purpose warehouses and their power is chosen to provide the cost minimization for the construction and subsequent maintenance of warehouses and transportation heterogeneous products. In order to solve this problem the authors developed a mathematical model that takes into account the possibility of delivery in heterogeneous goods from suppliers and manufacturers in the distribution and storage sorting with specified set of capacities. The model allows
Epidemic model with isolation in multilayer networks
Zuzek, L G Alvarez; Braunstein, L A
2014-01-01
The Susceptible-Infected-Recovered (SIR) model has successfully mimicked the propagation of such airborne diseases as influenza A (H1N1). Although the SIR model has recently been studied in a multilayer networks configuration, in almost all the research the dynamic movement of infected individuals, e.g., how they are often kept in isolation, is disregarded. We study the SIR model in two multilayer networks and use an isolation parameter, indicating time period, to measure the effect of isolating infected individuals from both layers. This isolation reduces the transmission of the disease because the time in which infection can spread is reduced. In this scenario we find that the epidemic threshold increases with the isolation time and the isolation parameter and the impact of the propagation is reduced. We also find that when isolation is total there is a threshold for the isolation parameter above which the disease never becomes an epidemic. We also find that regular epidemic models always overestimate the e...
Parsimonious modeling with information filtering networks
Barfuss, Wolfram; Massara, Guido Previde; Di Matteo, T.; Aste, Tomaso
2016-12-01
We introduce a methodology to construct parsimonious probabilistic models. This method makes use of information filtering networks to produce a robust estimate of the global sparse inverse covariance from a simple sum of local inverse covariances computed on small subparts of the network. Being based on local and low-dimensional inversions, this method is computationally very efficient and statistically robust, even for the estimation of inverse covariance of high-dimensional, noisy, and short time series. Applied to financial data our method results are computationally more efficient than state-of-the-art methodologies such as Glasso producing, in a fraction of the computation time, models that can have equivalent or better performances but with a sparser inference structure. We also discuss performances with sparse factor models where we notice that relative performances decrease with the number of factors. The local nature of this approach allows us to perform computations in parallel and provides a tool for dynamical adaptation by partial updating when the properties of some variables change without the need of recomputing the whole model. This makes this approach particularly suitable to handle big data sets with large numbers of variables. Examples of practical application for forecasting, stress testing, and risk allocation in financial systems are also provided.
Bayesian Recurrent Neural Network for Language Modeling.
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.
Social network models predict movement and connectivity in ecological landscapes
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.
Inferring gene regression networks with model trees
Directory of Open Access Journals (Sweden)
Aguilar-Ruiz Jesus S
2010-10-01
Full Text Available Abstract Background Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities. Results We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods. Conclusions REGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear
Han, Seunghee; Kim, Ki Joon; Kim, Jang Hyun
2017-07-01
This study explicates nomophobia by developing a research model that identifies several determinants of smartphone separation anxiety and by conducting semantic network analyses on smartphone users' verbal descriptions of the meaning of their smartphones. Structural equation modeling of the proposed model indicates that personal memories evoked by smartphones encourage users to extend their identity onto their devices. When users perceive smartphones as their extended selves, they are more likely to get attached to the devices, which, in turn, leads to nomophobia by heightening the phone proximity-seeking tendency. This finding is also supplemented by the results of the semantic network analyses revealing that the words related to memory, self, and proximity-seeking are indeed more frequently used in the high, compared with low, nomophobia group.
Modeling of Bandwidth Aggregation over Heterogeneous Wireless Access Networks
DEFF Research Database (Denmark)
Popovska Avramova, Andrijana; Dittmann, Lars
2012-01-01
Motivated by the multihomming capability of the mobile devices and the fact that the heterogeneous wireless access networks overlap in coverage, mobile operators are looking for solutions that will benefit by simultaneous use of the available multiple access interfaces. Multipath or multilink...... transfer deals with the problem on how to effectively aggregate the bandwidth by simultaneous usage of heterogeneous networks that a host is attached to in order to improve the throughput. This paper deals with a simulation based analysis of bandwidth aggregation techniques and their impact on higher layer...
Neural Networks for Electrohydrodynamic Effect Modelling
Directory of Open Access Journals (Sweden)
Jolanta Gancarz
2004-01-01
Full Text Available This paper presents currently achieved results concerning methods of electrohydrodynamic effect used in geophysics simulated with feedforward networks trained with backpropagation algorithm, radial basis function networks and generalized regression networks.
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.
Assessment of distributed arterial network models.
Segers, P; Stergiopulos, N; Verdonck, P; Verhoeven, R
1997-11-01
The aim of this study is to evaluate the relative importance of elastic non-linearities, viscoelasticity and resistance vessel modelling on arterial pressure and flow wave contours computed with distributed arterial network models. The computational results of a non-linear (time-domain) and a linear (frequency-domain) mode were compared using the same geometrical configuration and identical upstream and downstream boundary conditions and mechanical properties. pressures were computed at the ascending aorta, brachial and femoral artery. In spite of the identical problem definition, computational differences were found in input impedance modulus (max. 15-20%), systolic pressure (max. 5%) and pulse pressure (max. 10%). For the brachial artery, the ratio of pulse pressure to aortic pulse pressure was practically identical for both models (3%), whereas for the femoral artery higher values are found for the linear model (+10%). The aortic/brachial pressure transfer function indicates that pressure harmonic amplification is somewhat higher in the linear model for frequencies lower than 6 Hz while the opposite is true for higher frequencies. These computational disparities were attributed to conceptual model differences, such as the treatment of geometric tapering, rather than to elastic or convective non-linearities. Compared to the effect of viscoelasticity, the discrepancy between the linear and non-linear model is of the same importance. At peripheral locations, the correct representation of terminal impedance outweight the computational differences between the linear and non-linear models.
Fundamentals of complex networks models, structures and dynamics
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
Stochastic simulation of HIV population dynamics through complex network modelling
Sloot, P.M.A.; Ivanov, S.V.; Boukhanovsky, A.V.; van de Vijver, D.A.M.C.; Boucher, C.A.B.
2008-01-01
We propose a new way to model HIV infection spreading through the use of dynamic complex networks. The heterogeneous population of HIV exposure groups is described through a unique network degree probability distribution. The time evolution of the network nodes is modelled by a Markov process and
Stochastic simulation of HIV population dynamics through complex network modelling
Sloot, P. M. A.; Ivanov, S. V.; Boukhanovsky, A. V.; van de Vijver, D. A. M. C.; Boucher, C. A. B.
We propose a new way to model HIV infection spreading through the use of dynamic complex networks. The heterogeneous population of HIV exposure groups is described through a unique network degree probability distribution. The time evolution of the network nodes is modelled by a Markov process and
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 c...
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...
A network-oriented business modeling environment
Bisconti, Cristian; Storelli, Davide; Totaro, Salvatore; Arigliano, Francesco; Savarino, Vincenzo; Vicari, Claudia
The development of formal models related to the organizational aspects of an enterprise is fundamental when these aspects must be re-engineered and digitalized, especially when the enterprise is involved in the dynamics and value flows of a business network. Business modeling provides an opportunity to synthesize and make business processes, business rules and the structural aspects of an organization explicit, allowing business managers to control their complexity and guide an enterprise through effective decisional and strategic activities. This chapter discusses the main results of the TEKNE project in terms of software components that enable enterprises to configure, store, search and share models of any aspects of their business while leveraging standard and business-oriented technologies and languages to bridge the gap between the world of business people and IT experts and to foster effective business-to-business collaborations.
Neural network models of categorical perception.
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.
Networks model of the East Turkistan terrorism
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.
Modeling Transmission Line Networks Using Quantum Graphs
Koch, Trystan; Antonsen, Thomas
Quantum graphs--one dimensional edges, connecting nodes, that support propagating Schrödinger wavefunctions--have been studied extensively as tractable models of wave chaotic behavior (Smilansky and Gnutzmann 2006, Berkolaiko and Kuchment 2013). Here we consider the electrical analog, in which the graph represents an electrical network where the edges are transmission lines (Hul et. al. 2004) and the nodes contain either discrete circuit elements or intricate circuit elements best represented by arbitrary scattering matrices. Including these extra degrees of freedom at the nodes leads to phenomena that do not arise in simpler graph models. We investigate the properties of eigenfrequencies and eigenfunctions on these graphs, and relate these to the statistical description of voltages on the transmission lines when driving the network externally. The study of electromagnetic compatibility, the effect of external radiation on complicated systems with numerous interconnected cables, motivates our research into this extension of the graph model. Work supported by the Office of Naval Research (N0014130474) and the Air Force Office of Scientific Research.
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.
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...
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.
Traffic chaotic dynamics modeling and analysis of deterministic network
Wu, Weiqiang; Huang, Ning; Wu, Zhitao
2016-07-01
Network traffic is an important and direct acting factor of network reliability and performance. To understand the behaviors of network traffic, chaotic dynamics models were proposed and helped to analyze nondeterministic network a lot. The previous research thought that the chaotic dynamics behavior was caused by random factors, and the deterministic networks would not exhibit chaotic dynamics behavior because of lacking of random factors. In this paper, we first adopted chaos theory to analyze traffic data collected from a typical deterministic network testbed — avionics full duplex switched Ethernet (AFDX, a typical deterministic network) testbed, and found that the chaotic dynamics behavior also existed in deterministic network. Then in order to explore the chaos generating mechanism, we applied the mean field theory to construct the traffic dynamics equation (TDE) for deterministic network traffic modeling without any network random factors. Through studying the derived TDE, we proposed that chaotic dynamics was one of the nature properties of network traffic, and it also could be looked as the action effect of TDE control parameters. A network simulation was performed and the results verified that the network congestion resulted in the chaotic dynamics for a deterministic network, which was identical with expectation of TDE. Our research will be helpful to analyze the traffic complicated dynamics behavior for deterministic network and contribute to network reliability designing and analysis.
Chow, Wei Zhen; Chan, Yoke Fun; Oong, Xiang Yong; Ng, Liang Jie; Nor’E, Siti Sarah; Ng, Kim Tien; Chan, Kok Gan; Hanafi, Nik Sherina; Pang, Yong Kek; Kamarulzaman, Adeeba; Tee, Kok Keng
2016-01-01
Human metapneumovirus (HMPV) is an important viral respiratory pathogen worldwide. Current knowledge regarding the genetic diversity, seasonality and transmission dynamics of HMPV among adults and children living in tropical climate remains limited. HMPV prevailed at 2.2% (n = 86/3,935) among individuals presented with acute respiratory tract infections in Kuala Lumpur, Malaysia between 2012 and 2014. Seasonal peaks were observed during the northeast monsoon season (November–April) and correlated with higher relative humidity and number of rainy days (P < 0.05). Phylogenetic analysis of the fusion and attachment genes identified the co-circulation of three known HMPV sub-lineages, A2b and B1 (30.2% each, 26/86) and B2 (20.9%, 18/86), with genotype shift from sub-lineage B1 to A2b observed in 2013. Interestingly, a previously unrecognized sub-lineage of A2 was identified in 18.6% (16/86) of the population. Using a custom script for network construction based on the TN93 pairwise genetic distance, we identified up to nine HMPV transmission clusters circulating as multiple sub-epidemics. Although no apparent major outbreak was observed, the increased frequency of transmission clusters (dyads) during seasonal peaks suggests the potential roles of transmission clusters in driving the spread of HMPV. Our findings provide essential information for therapeutic research, prevention strategies, and disease outbreak monitoring of HMPV. PMID:27279080
Christensen, Nynne; Tilsner, Jens; Bell, Karen; Hammann, Philippe; Parton, Richard; Lacomme, Christophe; Oparka, Karl
2009-05-01
Almost nothing is known of the earliest stages of plant virus infections. To address this, we microinjected Cy3 (UTP)-labelled tobacco mosaic virus (TMV) into living tobacco trichome cells. The Cy3-virions were infectious, and the viral genome trafficked from cell to cell. However, neither the fluorescent vRNA pool nor the co-injected green fluorescent protein (GFP) left the injected trichome, indicating that the synthesis of (unlabelled) progeny viral (v)RNA is required to initiate cell-to-cell movement, and that virus movement is not accompanied by passive plasmodesmatal gating. Cy3-vRNA formed granules that became anchored to the motile cortical actin/endoplasmic reticulum (ER) network within minutes of injection. Granule movement on actin/ER was arrested by actin inhibitors indicating actin-dependent RNA movement. The 5' methylguanosine cap was shown to be required for vRNA anchoring to the actin/ER. TMV vRNA lacking the 5' cap failed to form granules and was degraded in the cytoplasm. Removal of the 3' untranslated region or replicase both inhibited replication but did not prevent granule formation and movement. Dual-labelled TMV virions in which the vRNA and the coat protein were highlighted with different fluorophores showed that both fluorescent signals were initially located on the same ER-bound granules, indicating that TMV virions may become attached to the ER prior to uncoating of the viral genome.
Emergence of soft communities from geometric preferential attachment.
Zuev, Konstantin; Boguñá, Marián; Bianconi, Ginestra; Krioukov, Dmitri
2015-04-29
All real networks are different, but many have some structural properties in common. There seems to be no consensus on what the most common properties are, but scale-free degree distributions, strong clustering, and community structure are frequently mentioned without question. Surprisingly, there exists no simple generative mechanism explaining all the three properties at once in growing networks. Here we show how latent network geometry coupled with preferential attachment of nodes to this geometry fills this gap. We call this mechanism geometric preferential attachment (GPA), and validate it against the Internet. GPA gives rise to soft communities that provide a different perspective on the community structure in networks. The connections between GPA and cosmological models, including inflation, are also discussed.
Berrang, Mark E; Hofacre, Charles L; Frank, Joseph F
2014-12-01
Listeria monocytogenes can colonize a poultry processing plant as a resident in floor drains. Limiting growth and attachment to drain surfaces may help lessen the potential for cross-contamination of product. The objective of this study was to compare a hydrogen peroxide-peroxyacetic acid-based chemical to chitosan-arginine or heat to prevent attachment of or destroy existing L. monocytogenes on the inner surface of model floor drains. L. monocytogenes was introduced to result in about 10(9) planktonic and attached cells within untreated polyvinyl chloride model drain pipes. Treatments (0.13 % peroxide-based sanitizer, 0.1 % chitosan-arginine, or 15 s of hot water at 95 to 100°C) were applied immediately after inoculation or after 24 h of incubation. Following treatment, all pipes were incubated for an additional 24 h; planktonic and attached cells were enumerated by plate count. All treatments significantly (P < 0.05) lowered numbers of planktonic and attached cells recovered. Chitosan-arginine resulted in approximately a 6-log reduction in planktonic cells when applied prior to incubation and a 3-log reduction after the inoculum had a chance to grow. Both heat and peroxide significantly outperformed chitosan-arginine (8- to 9-log reduction) and were equally effective before and after incubation. Heat was the only treatment that eliminated planktonic L. monocytogenes. All treatments were less effective against attached cells. Chitosan-arginine provided about a 4.5-log decrease in attached cells when applied before incubation and no significant decrease when applied after growth. Like with planktonic cells, peroxide-peroxyacetic acid and heat were equally effective before or after incubation, causing decreases ranging from 7 to 8.5 log for attached L. monocytogenes. Applied at the most efficacious time, any of these techniques may lessen the potential for L. monocytogenes to remain as a long-term resident in processing plant floor drains.
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…
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…
Effect of mobility models on infrastructure based wireless networks ...
African Journals Online (AJOL)
Effect of mobility models on infrastructure based wireless networks. ... In this paper, the effect of handoff procedure on the performance of random mobile nodes in wireless networks was investigated. Mobility of node is defined ... Article Metrics.
An Optimal Design Model for New Water Distribution Networks in ...
African Journals Online (AJOL)
An Optimal Design Model for New Water Distribution Networks in Kigali City. ... a Linear Programming Problem (LPP) which involves the design of a new network of water distribution considering the cost in the form of unit price ... Article Metrics.
A Model of Genetic Variation in Human Social Networks
Fowler, James H; Christakis, Nicholas A
2008-01-01
Social networks influence the evolution of cooperation and they exhibit strikingly systematic patterns across a wide range of human contexts. Both of these facts suggest that variation in the topological attributes of human social networks might have a genetic basis. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a "mirror network" method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative "attract and introduce" model that generates significant heritability as well as other important network features, and we show that this model with two simple forms of heterogeneity is well suited to the modeling of real social networks in humans. These results suggest that natural selection ...
Bus transport network model with ideal n-depth clique network topology
Yang, Xu-Hua; Chen, Guang; Sun, Bao; Chen, Sheng-Yong; Wang, Wan-Liang
2011-11-01
We propose an ideal n-depth clique network model. In this model, the original network is composed of cliques (maximal complete subgraphs) that overlap with each other. The network expands continuously by the addition of new cliques. The final diameter of the network can be set in advance, namely, it is controllable. Assuming that the diameter of the network is n, the network exhibits a logistic structure with (n+1) layers. In this structure, the 0th layer represents the original network and each node of the (m)th layer (1≤m≤n) corresponds to a clique in the (m-1)th layer. In the growth process of the network, we ensure that any (m)th layer network is composed of overlapping cliques. Any node in an (m)th layer network corresponds to an m-depth community in the original network, and the diameter of an m-depth community is m. Therefore, the (n-1)th layer network will contain only one clique, the (n)th layer network will contain only one node, and the diameter of the corresponding original network is n. Then an ideal n-depth clique network will be obtained. Based on the ideal n-depth clique network model, we construct a bus transport network model with an ideal n-depth clique network topology (ICNBTN). Moreover, our study compares this model with the real bus transport network (RealBTN) of three major cities in China and a recently introduced bus transport network model (BTN) whose network properties correspond well with those of real BTNs. The network properties of the ICNBTN are much closer to those of the RealBTN than those of the BTN are. At the same time, the ICNBTN has higher clustering extent of bus routes, smaller network diameter, which corresponds to shorter maximum transfer times in a bus network, and lower average shortest path time coefficient than the BTN and the RealBTN. Therefore, the ICNBTN can achieve higher transfer efficiency for a bus transport system.
Sawyer, J. W.
1972-01-01
A wind-tunnel investigation was conducted at free-stream Mach numbers from 0.20 to 1.00 and corresponding Reynolds numbers, based on maximum afterbody diameter, from 2.25 x one million to 6.90 x one million on a solid model of an attached inflatable decelerator (AID) connected to the base of an ogive-cylinder. Tests were conducted to obtain ram-air and surface pressure distributions about the AID. AID shapes derived for subsonic deployment are dependent on the pressure distributions used in their derivation, and the different shapes obtained are dependent on the Mach number for which the design is made. The resulting pressure distributions were used in a design program to obtain new shapes which were compared with the original pressure-distribution shape.
Relay-Linking Models for Prominence and Obsolescence in Evolving Networks
Singh, Mayank; Goyal, Pawan; Mukherjee, Animesh; Chakrabarti, Soumen
2016-01-01
The rate at which nodes in evolving social networks acquire links (friends, citations) shows complex temporal dynamics. Elegant and simple models, such as preferential attachment and link copying, model only rich-gets-richer effects, not aging and decline. Recent aging models are complex and heavily parameterized; most involve estimating 1-3 parameters per node. These parameters are intrinsic: they explain decline in terms of events in the past of the same node, and do not explain, using the network, where the linking attention might go instead. We argue that traditional network characterization, or even per-node linking dynamics, are insufficient to judge the faithfulness of models. We propose a new temporal sketch of an evolving graph, and introduce three new characterizations of a network's temporal dynamics. Then we propose a new family of frugal aging models with no per-node parameters and only 2-3 global parameters. Our model is based on a surprising inversion or undoing of triangle completion, where an...
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.
A novel mathematical model for coverage in wireless sensor network
Institute of Scientific and Technical Information of China (English)
YAN Zhen-ya; ZHENG Bao-yu
2006-01-01
Coverage problem is one of the fundamental issues in the design of wireless sensor network, which has a great impact on the performance of sensor network. In this article,coverage problem was investigated using a mathematical model named Birth-death process. In this model, sensor nodes joining into networks at every period of time is considered as the rebirth of network and the quitting of sensor nodes from the networks is considered as the death of the network. In the end, an analytical solution is used to investigate the appropriate rate to meet the coverage requirement.
PageRank model of opinion formation on Ulam networks
Chakhmakhchyan, L
2013-01-01
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 have 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.
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 variab
Yang, X. I. A.; Baidya, R.; Johnson, P.; Marusic, I.; Meneveau, C.
2017-06-01
We investigate the scaling of the velocity structure function tensor Di j(r ,z ) in high Reynolds number wall-bounded turbulent flows, within the framework provided by the Townsend attached eddy hypothesis. Here i ,j =1 ,2 ,3 denote velocity components in the three Cartesian directions, and r is a general spatial displacement vector. We consider spatial homogeneous conditions in wall-parallel planes and dependence on wall-normal distance is denoted by z . At small scales (r =|r |≪z ) where turbulence approaches local isotropy, Di j(r ,z ) can be fully characterized as a function of r and the height-dependent dissipation rate ɛ (z ) , using the classical Kolmogorov scalings. At larger distances in the logarithmic range, existing previous studies have focused mostly on the scaling of Di j for r in the streamwise direction and for the streamwise velocity component (i =j =1 ) only. No complete description is available for Di j(r ,z ) for all i ,j , and r directions. In this paper we show that the hierarchical random additive process model for turbulent fluctuations in the logarithmic range (a model based on the Townsend's attached eddy hypothesis) may be used to make new predictions on the scaling of Di j(r ,z ) for all velocity components and in all two-point displacement directions. Some of the generalized scaling relations of Di j(r ,z ) in the logarithmic region are then compared to available data. Nevertheless, a number of predictions cannot yet be tested in detail, due to a lack of simultaneous two-point measurements with arbitrary cross-plane displacements, calling for further experiments to be conducted at high Reynolds numbers.
Directory of Open Access Journals (Sweden)
Lilach Golan
2011-01-01
Enterohemorrhagic Escherichia coli (EHEC O157:H7 is an important cause of diarrhea, hemorrhagic colitis and hemolytic uremic syndrome in humans worldwide. The two major virulence determinants of EHEC are the Shiga toxins (Stx and the type III secretion system (T3SS, including the injected effectors. Lack of a good model system hinders the study of EHEC virulence. Here, we investigated whether bovine and human intestinal xenografts in SCID mice can be useful for studying EHEC and host tissue interactions. Fully developed, germ-free human and bovine small intestine and colon were established by subcutaneous transplantation of human and bovine fetal gut into SCID mice. Xenografts were allowed to develop for 3–4 months and thereafter were infected by direct intraluminal inoculation of Stx-negative derivatives of EHEC O157:H7, strain EDL933. The small intestine and colon xenografts closely mimicked the respective native tissues. Upon infection, EHEC induced formation of typical attaching and effacing lesions and tissue damage that resembled hemorrhagic colitis in colon xenografts. By contrast, xenografts infected with an EHEC mutant deficient in T3SS remained undamaged. Furthermore, EHEC did not attach to or damage the epithelium of small intestinal tissue, and these xenografts remained intact. EHEC damaged the colon in a T3SS-dependent manner, and this model is therefore useful for studying the molecular details of EHEC interactions with live human and bovine intestinal tissue. Furthermore, we demonstrate that Stx and gut microflora are not essential for EHEC virulence in the human gut.
VEPCO network model reconciliation of LANL and MZA model data
Energy Technology Data Exchange (ETDEWEB)
NONE
1992-12-15
The LANL DC load flow model of the VEPCO transmission network shows 210 more substations than the AC load flow model produced by MZA utility Consultants. MZA was requested to determine the source of the difference. The AC load flow model used for this study utilizes 2 standard network algorithms (Decoupled or Newton). The solution time of each is affected by the number of substations. The more substations included, the longer the model will take to solve. In addition, the ability of the algorithms to converge to a solution is affected by line loadings and characteristics. Convergence is inhibited by numerous lightly loaded and electrically short lines. The MZA model reduces the total substations to 343 by creating equivalent loads and generation. Most of the omitted substations are lightly loaded and rated at 115 kV. The MZA model includes 16 substations not included in the LANL model. These represent new generation including Non-Utility Generator (NUG) sites, additional substations and an intertie (Wake, to CP and L). This report also contains data from the Italian State AC power flow model and the Duke Power Company AC flow model.
A scale-free neural network for modelling neurogenesis
Perotti, Juan I.; Tamarit, Francisco A.; Cannas, Sergio A.
2006-11-01
In this work we introduce a neural network model for associative memory based on a diluted Hopfield model, which grows through a neurogenesis algorithm that guarantees that the final network is a small-world and scale-free one. We also analyze the storage capacity of the network and prove that its performance is larger than that measured in a randomly dilute network with the same connectivity.
NSME: a framework for network worm modeling and simulation
Lin, Siming; Cheng, Xueqi
2006-01-01
Various worms have a devastating impact on Internet. Packet level network modeling and simulation has become an approach to find effective countermeasures against worm threat. However, current alternatives are not fit enough for this purpose. For instance, they mostly focus on the details of lower layers of the network so that the abstraction of application layer is very coarse. In our work, we propose a formal description of network and worm models, and define network virtualization level...
Spacing distribution functions for 1D point island model with irreversible attachment
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).
Modeling management of research and education networks
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 con
Formation of Modularity in a Model of Evolving Networks
Li, Menghui; Lai, Choy-Heng
2011-01-01
Modularity structures are common in various social and biological networks. However, its dynamical origin remains an open question. In this work, we set up a toy dynamical model describing the evolution of a social network. Based on the observations of real social networks, we introduced a strategy of link-creating/deleting according to the local dynamics in the model. Thus the coevolution of the dynamics and topology naturally determines the network properties. It is found that for a small coupling strength, the networked system cannot reach any synchronization and the network topology is homogeneous. Interestingly, when the coupling strength is large enough, the networked system spontaneously forms communities with different dynamical states. Meanwhile, the network topology becomes heterogeneous with modular structures. It is further shown that in certain parameter regime, both the degree and the community size in the formed network follow power-law distribution. These results are consistent with the charac...
Boolean network model predicts knockout mutant phenotypes of fission yeast.
Directory of Open Access Journals (Sweden)
Maria I Davidich
Full Text Available BOOLEAN NETWORKS (OR: networks of switches are extremely simple mathematical models of biochemical signaling networks. Under certain circumstances, Boolean networks, despite their simplicity, are capable of predicting dynamical activation patterns of gene regulatory networks in living cells. For example, the temporal sequence of cell cycle activation patterns in yeasts S. pombe and S. cerevisiae are faithfully reproduced by Boolean network models. An interesting question is whether this simple model class could also predict a more complex cellular phenomenology as, for example, the cell cycle dynamics under various knockout mutants instead of the wild type dynamics, only. Here we show that a Boolean network model for the cell cycle control network of yeast S. pombe correctly predicts viability of a large number of known mutants. So far this had been left to the more detailed differential equation models of the biochemical kinetics of the yeast cell cycle network and was commonly thought to be out of reach for models as simplistic as Boolean networks. The new results support our vision that Boolean networks may complement other mathematical models in systems biology to a larger extent than expected so far, and may fill a gap where simplicity of the model and a preference for an overall dynamical blueprint of cellular regulation, instead of biochemical details, are in the focus.
Boolean Network Model Predicts Knockout Mutant Phenotypes of Fission Yeast
Davidich, Maria I.; Bornholdt, Stefan
2013-01-01
Boolean networks (or: networks of switches) are extremely simple mathematical models of biochemical signaling networks. Under certain circumstances, Boolean networks, despite their simplicity, are capable of predicting dynamical activation patterns of gene regulatory networks in living cells. For example, the temporal sequence of cell cycle activation patterns in yeasts S. pombe and S. cerevisiae are faithfully reproduced by Boolean network models. An interesting question is whether this simple model class could also predict a more complex cellular phenomenology as, for example, the cell cycle dynamics under various knockout mutants instead of the wild type dynamics, only. Here we show that a Boolean network model for the cell cycle control network of yeast S. pombe correctly predicts viability of a large number of known mutants. So far this had been left to the more detailed differential equation models of the biochemical kinetics of the yeast cell cycle network and was commonly thought to be out of reach for models as simplistic as Boolean networks. The new results support our vision that Boolean networks may complement other mathematical models in systems biology to a larger extent than expected so far, and may fill a gap where simplicity of the model and a preference for an overall dynamical blueprint of cellular regulation, instead of biochemical details, are in the focus. PMID:24069138
A graph model for opportunistic network coding
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.
Determining Application Runtimes Using Queueing Network Modeling
Energy Technology Data Exchange (ETDEWEB)
Elliott, Michael L. [Univ. of San Francisco, CA (United States)
2006-12-14
Determination of application times-to-solution for large-scale clustered computers continues to be a difficult problem in high-end computing, which will only become more challenging as multi-core consumer machines become more prevalent in the market. Both researchers and consumers of these multi-core systems desire reasonable estimates of how long their programs will take to run (time-to-solution, or TTS), and how many resources will be consumed in the execution. Currently there are few methods of determining these values, and those that do exist are either overly simplistic in their assumptions or require great amounts of effort to parameterize and understand. One previously untried method is queuing network modeling (QNM), which is easy to parameterize and solve, and produces results that typically fall within 10 to 30% of the actual TTS for our test cases. Using characteristics of the computer network (bandwidth, latency) and communication patterns (number of messages, message length, time spent in communication), the QNM model of the NAS-PB CG application was applied to MCR and ALC, supercomputers at LLNL, and the Keck Cluster at USF, with average errors of 2.41%, 3.61%, and -10.73%, respectively, compared to the actual TTS observed. While additional work is necessary to improve the predictive capabilities of QNM, current results show that QNM has a great deal of promise for determining application TTS for multi-processor computer systems.
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.
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
Minzenberg, Michael J; Poole, John H; Vinogradov, Sophia
2008-01-01
Borderline personality disorder (BPD) is a paradigmatic disorder of adult attachment, with high rates of antecedent childhood maltreatment. The neurocognitive correlates of both attachment disturbance and maltreatment are both presently unknown in BPD. This study evaluated whether dimensional adult attachment disturbance in BPD is related to specific neurocognitive deficits, and whether childhood maltreatment is related to these dysfunctions. An outpatient BPD group (n=43) performed nearly 1 SD below a control group (n=26) on short-term recall, executive, and intelligence functions. These deficits were not affected by emotionally charged stimuli. In the BPD group, impaired recall was related to attachment-anxiety, whereas executive dysfunction was related to attachment-avoidance. Abuse history was correlated significantly with executive dysfunction and at a trend level with impaired recall. Neurocognitive deficits and abuse history exhibited both independent and interactive effects on adult attachment disturbance. These results suggest that (a) BPD patients' reactivity in attachment relationships is related to temporal-limbic dysfunction, irrespective of the emotional content of stimuli, (b) BPD patients' avoidance within attachment relationships may be a relational strategy to compensate for the emotional consequences of frontal-executive dysregulation, and (c) childhood abuse may contribute to these neurocognitive deficits but may also exert effects on adult attachment disturbance that is both independent and interacting with neurocognitive dysfunction.
Infinite multiple membership relational modeling for complex networks
DEFF Research Database (Denmark)
Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai
2011-01-01
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 multiple-membership latent feature model for networks. Contrary to exist......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 multiple-membership latent feature model for networks. Contrary...... to existing multiplemembership models that scale quadratically in the number of vertices the proposed model scales linearly in the number of links admitting multiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership...
Models of neural networks with fuzzy activation functions
Nguyen, A. T.; Korikov, A. M.
2017-02-01
This paper investigates the application of a new form of neuron activation functions that are based on the fuzzy membership functions derived from the theory of fuzzy systems. On the basis of the results regarding neuron models with fuzzy activation functions, we created the models of fuzzy-neural networks. These fuzzy-neural network models differ from conventional networks that employ the fuzzy inference systems using the methods of neural networks. While conventional fuzzy-neural networks belong to the first type, fuzzy-neural networks proposed here are defined as the second-type models. The simulation results show that the proposed second-type model can successfully solve the problem of the property prediction for time – dependent signals. Neural networks with fuzzy impulse activation functions can be widely applied in many fields of science, technology and mechanical engineering to solve the problems of classification, prediction, approximation, etc.
Topological evolution of virtual social networks by modeling social activities
Sun, Xin; Dong, Junyu; Tang, Ruichun; Xu, Mantao; Qi, Lin; Cai, Yang
2015-09-01
With the development of Internet and wireless communication, virtual social networks are becoming increasingly important in the formation of nowadays' social communities. Topological evolution model is foundational and critical for social network related researches. Up to present most of the related research experiments are carried out on artificial networks, however, a study of incorporating the actual social activities into the network topology model is ignored. This paper first formalizes two mathematical abstract concepts of hobbies search and friend recommendation to model the social actions people exhibit. Then a social activities based topology evolution simulation model is developed to satisfy some well-known properties that have been discovered in real-world social networks. Empirical results show that the proposed topology evolution model has embraced several key network topological properties of concern, which can be envisioned as signatures of real social networks.
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.
Modeling stochasticity in biochemical reaction networks
Constantino, P. H.; Vlysidis, M.; Smadbeck, P.; Kaznessis, Y. N.
2016-03-01
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.
Modelling transcriptional networks in leaf senescence.
Penfold, Christopher A; Buchanan-Wollaston, Vicky
2014-07-01
The process of leaf senescence is induced by an extensive range of developmental and environmental signals and controlled by multiple, cross-linking pathways, many of which overlap with plant stress-response signals. Elucidation of this complex regulation requires a step beyond a traditional one-gene-at-a-time analysis. Application of a more global analysis using statistical and mathematical tools of systems biology is an approach that is being applied to address this problem. A variety of modelling methods applicable to the analysis of current and future senescence data are reviewed and discussed using some senescence-specific examples. Network modelling with a senescence transcriptome time course followed by testing predictions with gene-expression data illustrates the application of systems biology tools.
Network transmission model: A dynamic traffic model at network level (poster)
Knoop, V.L.; Hoogendoorn, S.P.
2014-01-01
New IT techniques allow communication and coordination between traffic measures. To best use this, one needs to coordinate over longer distances. Optimization of the measures is not possible using traditional microscopic or macroscopic simulation models. The Network Fundamental Diagram (NFD) describ
Completely random measures for modelling block-structured sparse networks
DEFF Research Database (Denmark)
Herlau, Tue; Schmidt, Mikkel Nørgaard; Mørup, Morten
2016-01-01
Many statistical methods for network data parameterize the edge-probability by attributing latent traits to the vertices such as block structure and assume exchangeability in the sense of the Aldous-Hoover representation theorem. Empirical studies of networks indicate that many real-world network...... is not significantly more difficult to implement than existing approaches to block-modelling and performs well on real network datasets.......Many statistical methods for network data parameterize the edge-probability by attributing latent traits to the vertices such as block structure and assume exchangeability in the sense of the Aldous-Hoover representation theorem. Empirical studies of networks indicate that many real-world networks...... [2014] proposed the use of a different notion of exchangeability due to Kallenberg [2006] and obtained a network model which admits power-law behaviour while retaining desirable statistical properties, however this model does not capture latent vertex traits such as block-structure. In this work we re...
Road network safety evaluation using Bayesian hierarchical joint model.
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.
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
An Efficient Multitask Scheduling Model for Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Hongsheng Yin
2014-01-01
Full Text Available The sensor nodes of multitask wireless network are constrained in performance-driven computation. Theoretical studies on the data processing model of wireless sensor nodes suggest satisfying the requirements of high qualities of service (QoS of multiple application networks, thus improving the efficiency of network. In this paper, we present the priority based data processing model for multitask sensor nodes in the architecture of multitask wireless sensor network. The proposed model is deduced with the M/M/1 queuing model based on the queuing theory where the average delay of data packets passing by sensor nodes is estimated. The model is validated with the real data from the Huoerxinhe Coal Mine. By applying the proposed priority based data processing model in the multitask wireless sensor network, the average delay of data packets in a sensor nodes is reduced nearly to 50%. The simulation results show that the proposed model can improve the throughput of network efficiently.
Cagen:. a Modern, PC Based Computer Modeling Tool for Explosive MCG Generators and Attached Loads
Chase, J. B.; Chato, D.; Peterson, G.; Pincosy, P.; Kiuttu, G. F.
2004-11-01
We will describe the PC based computer program CAGEN. CAGEN models the performance of many varieties of Magneto-Cumulative-Generators (MCG) or Magnetic Flux Compression Generators (FCG) that are energized with High Explosive (HE). CAGEN models helical wound or coaxial types, which have HE on the interior. Any materials and any HE types may be used. The cylindrical radius of the windings (or outer conductor) and the radius of the armature may vary with axial position. Variable winding width, thickness, and pitch can be represented, and divided windings are allowed. The MHD equations are used to advance the diffusion of magnetic field into the conductors in order to compute resistance, melting, and contact effects. Magnetic pressure effects are included. The MCG model is treated as part of a lumped circuit, which includes the priming circuit, an opening fuse switch, an inline storage inductance, a transformer or a voltage dividing fuse, peaking-circuit, and several interesting load models. A typical problem will complete in a few seconds to a few minutes. Graphical input, run control, and analysis of results is provided by MathGraf, which is a CARE'N CO. application.
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
An information theoretic approach for combining neural network process models.
Sridhar, D V.; Bartlett, E B.; Seagrave, R C.
1999-07-01
Typically neural network modelers in chemical engineering focus on identifying and using a single, hopefully optimal, neural network model. Using a single optimal model implicitly assumes that one neural network model can extract all the information available in a given data set and that the other candidate models are redundant. In general, there is no assurance that any individual model has extracted all relevant information from the data set. Recently, Wolpert (Neural Networks, 5(2), 241 (1992)) proposed the idea of stacked generalization to combine multiple models. Sridhar, Seagrave and Barlett (AIChE J., 42, 2529 (1996)) implemented the stacked generalization for neural network models by integrating multiple neural networks into an architecture known as stacked neural networks (SNNs). SNNs consist of a combination of the candidate neural networks and were shown to provide improved modeling of chemical processes. However, in Sridhar's work SNNs were limited to using a linear combination of artificial neural networks. While a linear combination is simple and easy to use, it can utilize only those model outputs that have a high linear correlation to the output. Models that are useful in a nonlinear sense are wasted if a linear combination is used. In this work we propose an information theoretic stacking (ITS) algorithm for combining neural network models. The ITS algorithm identifies and combines useful models regardless of the nature of their relationship to the actual output. The power of the ITS algorithm is demonstrated through three examples including application to a dynamic process modeling problem. The results obtained demonstrate that the SNNs developed using the ITS algorithm can achieve highly improved performance as compared to selecting and using a single hopefully optimal network or using SNNs based on a linear combination of neural networks.
A last updating evolution model for online social networks
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.
Multi-agent Based Modeling of Manufacturing Network
Institute of Scientific and Technical Information of China (English)
GUO Yuming; SUN Yanming; ZHENG Shixiong
2006-01-01
An intelligent manufacturing system is modeled currently from the viewpoint of manufacturing applications, and the network platform's influence to manufacturing applications is not considered adequately. However any bottleneck in service oriented architecture (SOA) for the manufacturing network can affect the agility of the IT environment. In this paper, to achieve a trade-off between manufacturing resources and network resources, the manufacturing network is modeled with multi-agent, in which two kinds of basic elements, the manufacturing application unit and the network carrier of manufacturing information, are presented. And their main characters are described by colored petri net. The manufacturing application model drives the network platform that inversely provides this application model technology supports. The proposed multi-agent system is demonstrated through an example integration scenario involving production plan, resources management and execution subsystems. And the result suggests that analyzing and designing the system architecture of networked manufacturing should give due attention to the operation system as well as manufacturing applications.
A null model for Pearson coexpression networks.
Gobbi, Andrea; Jurman, Giuseppe
2015-01-01
Gene coexpression networks inferred by correlation from high-throughput profiling such as microarray data represent simple but effective structures for discovering and interpreting linear gene relationships. In recent years, several approaches have been proposed to tackle the problem of deciding when the resulting correlation values are statistically significant. This is most crucial when the number of samples is small, yielding a non-negligible chance that even high correlation values are due to random effects. Here we introduce a novel hard thresholding solution based on the assumption that a coexpression network inferred by randomly generated data is expected to be empty. The threshold is theoretically derived by means of an analytic approach and, as a deterministic independent null model, it depends only on the dimensions of the starting data matrix, with assumptions on the skewness of the data distribution compatible with the structure of gene expression levels data. We show, on synthetic and array datasets, that the proposed threshold is effective in eliminating all false positive links, with an offsetting cost in terms of false negative detected edges.
Natural Models for Evolution on Networks
Mertzios, George B; Raptopoulos, Christoforos; Spirakis, Paul G
2011-01-01
Evolutionary dynamics have been traditionally studied in the context of homogeneous populations, mainly described my the Moran process. Recently, this approach has been generalized in \\cite{LHN} by arranging individuals on the nodes of a network. Undirected networks seem to have a smoother behavior than directed ones, and thus it is more challenging to find suppressors/amplifiers of selection. In this paper we present the first class of undirected graphs which act as suppressors of selection, by achieving a fixation probability that is at most one half of that of the complete graph, as the number of vertices increases. Moreover, we provide some generic upper and lower bounds for the fixation probability of general undirected graphs. As our main contribution, we introduce the natural alternative of the model proposed in \\cite{LHN}, where all individuals interact simultaneously and the result is a compromise between aggressive and non-aggressive individuals. That is, the behavior of the individuals in our new m...
A null model for Pearson coexpression networks.
Directory of Open Access Journals (Sweden)
Andrea Gobbi
Full Text Available Gene coexpression networks inferred by correlation from high-throughput profiling such as microarray data represent simple but effective structures for discovering and interpreting linear gene relationships. In recent years, several approaches have been proposed to tackle the problem of deciding when the resulting correlation values are statistically significant. This is most crucial when the number of samples is small, yielding a non-negligible chance that even high correlation values are due to random effects. Here we introduce a novel hard thresholding solution based on the assumption that a coexpression network inferred by randomly generated data is expected to be empty. The threshold is theoretically derived by means of an analytic approach and, as a deterministic independent null model, it depends only on the dimensions of the starting data matrix, with assumptions on the skewness of the data distribution compatible with the structure of gene expression levels data. We show, on synthetic and array datasets, that the proposed threshold is effective in eliminating all false positive links, with an offsetting cost in terms of false negative detected edges.
Modeling sediment transport in river networks
Wang, Xu-Ming; Hao, Rui; Huo, Jie; Zhang, Jin-Feng
2008-11-01
A dynamical model is proposed to study sediment transport in river networks. A river can be divided into segments by the injection of branch streams of higher rank. The model is based on the fact that in a real river, the sediment-carrying capability of the stream in the ith segment may be modulated by the undergone state, which may be erosion or sedimentation, of the i-1th and ith segments, and also influenced by that of the ith injecting branch of higher rank. We select a database about the upper-middle reach of the Yellow River in the lower-water season to test the model. The result shows that the data, produced by averaging the erosion or sedimentation over the preceding transient process, are in good agreement with the observed average in a month. With this model, the steady state after transience can be predicted, and it indicates a scaling law that the quantity of erosion or sedimentation exponentially depends on the number of the segments along the reach of the channel. Our investigation suggests that fluctuation of the stream flow due to random rainfall will prevent this steady state from occurring. This is owing to the phenomenon that the varying trend of the quantity of erosion or sedimentation is opposite to that of sediment-carrying capability of the stream.
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.
Research on Remote Network Bidirectional Detect and Control Model
Directory of Open Access Journals (Sweden)
Hongyao Ju
2013-09-01
Full Text Available Remote network bidirectional detect and control technologies are the key factors to solve local network allopatry expansibility and management. With studying gateway integration technology, bidirectional VPN technology, identity authentication technology and dynamic host management technology can be integrated into gateway. Thus, bidirectional connect and control among allopatry local networks based on Internet can be solved. Whole area expansibility of local network is realized. With experiment, the model is proved to finish remote bidirectional interconnection of local network automatically and to obtain allopatry local users authority. The equipment detecting and controlling in remote local networks are realized.
Supplier Selection in Virtual Enterprise Model of Manufacturing Supply Network
Kaihara, Toshiya; Opadiji, Jayeola F.
The market-based approach to manufacturing supply network planning focuses on the competitive attitudes of various enterprises in the network to generate plans that seek to maximize the throughput of the network. It is this competitive behaviour of the member units that we explore in proposing a solution model for a supplier selection problem in convergent manufacturing supply networks. We present a formulation of autonomous units of the network as trading agents in a virtual enterprise network interacting to deliver value to market consumers and discuss the effect of internal and external trading parameters on the selection of suppliers by enterprise units.
Limkumnerd, Surachate
2014-03-01
Interest in thin-film fabrication for industrial applications have driven both theoretical and computational aspects of modeling its growth. One of the earliest attempts toward understanding the morphological structure of a film's surface is through a class of solid-on-solid limited-mobility growth models such as the Family, Wolf-Villain, or Das Sarma-Tamborenea models, which have produced fascinating surface roughening behaviors. These models, however, restrict the motion of an incidence atom to be within the neighborhood of its landing site, which renders them inept for simulating long-distance surface diffusion such as that observed in thin-film growth using a molecular-beam epitaxy technique. Naive extension of these models by repeatedly applying the local diffusion rules for each hop to simulate large diffusion length can be computationally very costly when certain statistical aspects are demanded. We present a graph-theoretic approach to simulating a long-range diffusion-attachment growth model. Using the Markovian assumption and given a local diffusion bias, we derive the transition probabilities for a random walker to traverse from one lattice site to the others after a large, possibly infinite, number of steps. Only computation with linear-time complexity is required for the surface morphology calculation without other probabilistic measures. The formalism is applied, as illustrations, to simulate surface growth on a two-dimensional flat substrate and around a screw dislocation under the modified Wolf-Villain diffusion rule. A rectangular spiral ridge is observed in the latter case with a smooth front feature similar to that obtained from simulations using the well-known multiple registration technique. An algorithm for computing the inverse of a class of substochastic matrices is derived as a corollary.
Precise Network Modeling of Systems Genetics Data Using the Bayesian Network Webserver.
Ziebarth, Jesse D; Cui, Yan
2017-01-01
The Bayesian Network Webserver (BNW, http://compbio.uthsc.edu/BNW ) is an integrated platform for Bayesian network modeling of biological datasets. It provides a web-based network modeling environment that seamlessly integrates advanced algorithms for probabilistic causal modeling and reasoning with Bayesian networks. BNW is designed for precise modeling of relatively small networks that contain less than 20 nodes. The structure learning algorithms used by BNW guarantee the discovery of the best (most probable) network structure given the data. To facilitate network modeling across multiple biological levels, BNW provides a very flexible interface that allows users to assign network nodes into different tiers and define the relationships between and within the tiers. This function is particularly useful for modeling systems genetics datasets that often consist of multiscalar heterogeneous genotype-to-phenotype data. BNW enables users to, within seconds or minutes, go from having a simply formatted input file containing a dataset to using a network model to make predictions about the interactions between variables and the potential effects of experimental interventions. In this chapter, we will introduce the functions of BNW and show how to model systems genetics datasets with BNW.
Neural networks in economic modelling : An empirical study
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 sta
Modeling community structure and topics in dynamic text networks
Henry, Teague; Chai, Christine; Owens-Oas, Derek
2016-01-01
The last decade has seen great progress in both dynamic network modeling and topic modeling. This paper draws upon both areas to create a Bayesian method that allows topic discovery to inform the latent network model and the network structure to facilitate topic identification. We apply this method to the 467 top political blogs of 2012. Our results find complex community structure within this set of blogs, where community membership depends strongly upon the set of topics in which the blogger is interested.
Model for the growth of the World Airline Network
Verma, T; Nagler, J; Andrade, J S; Herrmann, H J
2016-01-01
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 WAN, we observe that the difference between the two is minimized for $\\alpha\\approx 2$. 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.
Agent Based Modeling on Organizational Dynamics of Terrorist Network
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 ...
A dynamic epidemic control model on uncorrelated complex networks
Institute of Scientific and Technical Information of China (English)
Pei Wei-Dong; Chen Zeng-Qiang; Yuan Zhu-Zhi
2008-01-01
In this paper,a dynamic epidemic control model on the uncorrelated complex networks is proposed.By means of theoretical analysis,we found that the new model has a similar epidemic threshold as that of the susceptible-infectedrecovered (SIR) model on the above networks,but it can reduce the prevalence of the infected individuals remarkably.This result may help us understand epidemic spreading phenomena on real networks and design appropriate strategies to control infections.
Self-Organized Criticality in a Random Network Model
Nirei, Makoto
1998-01-01
A new model of self-organized criticality is defined by incorporating a random network model in order to explain endogenous complex fluctuations of economic aggregates. The model can feature many globally interactive systems such as economies or societies.
Shadow networks: Discovering hidden nodes with models of information flow
Bagrow, James P; Frank, Morgan R; Manukyan, Narine; Mitchell, Lewis; Reagan, Andrew; Bloedorn, Eric E; Booker, Lashon B; Branting, Luther K; Smith, Michael J; Tivnan, Brian F; Danforth, Christopher M; Dodds, Peter S; Bongard, Joshua C
2013-01-01
Complex, dynamic networks underlie many systems, and understanding these networks is the concern of a great span of important scientific and engineering problems. Quantitative description is crucial for this understanding yet, due to a range of measurement problems, many real network datasets are incomplete. Here we explore how accidentally missing or deliberately hidden nodes may be detected in networks by the effect of their absence on predictions of the speed with which information flows through the network. We use Symbolic Regression (SR) to learn models relating information flow to network topology. These models show localized, systematic, and non-random discrepancies when applied to test networks with intentionally masked nodes, demonstrating the ability to detect the presence of missing nodes and where in the network those nodes are likely to reside.
Adaptive Networks Theory, Models and Applications
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.
Modeling of polymer networks for application to solid propellant formulating
Marsh, H. E.
1979-01-01
Methods for predicting the network structural characteristics formed by the curing of pourable elastomers were presented; as well as the logic which was applied in the development of mathematical models. A universal approach for modeling was developed and verified by comparison with other methods in application to a complex system. Several applications of network models to practical problems are described.
A simulation model of a star computer network
Gomaa, H
1979-01-01
A simulation model of the CERN (European Organization for Nuclear Research) SPS star computer network is described. The model concentrates on simulating the message handling computer, through which all messages in the network pass. The implementation of the model and its calibration are also described. (6 refs).
Structural equation models from paths to networks
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...
Modelling crime linkage with Bayesian networks.
de Zoete, Jacob; Sjerps, Marjan; Lagnado, David; Fenton, Norman
2015-05-01
When two or more crimes show specific similarities, such as a very distinct modus operandi, the probability that they were committed by the same offender becomes of interest. This probability depends on the degree of similarity and distinctiveness. We show how Bayesian networks can be used to model different evidential structures that can occur when linking crimes, and how they assist in understanding the complex underlying dependencies. That is, how evidence that is obtained in one case can be used in another and vice versa. The flip side of this is that the intuitive decision to "unlink" a case in which exculpatory evidence is obtained leads to serious overestimation of the strength of the remaining cases.