WorldWideScience

Sample records for network evolution based

  1. 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

  2. A random network based, node attraction facilitated network evolution method

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2016-03-01

    Full Text Available In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999 of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor Lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor Lamda can reflect various effects of the node degree on connection mechanism. Even the changes of Lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.

  3. Evolution based on chromosome affinity from a network perspective

    Science.gov (United States)

    Monteiro, R. L. S.; Fontoura, J. R. A.; Carneiro, T. K. G.; Moret, M. A.; Pereira, H. B. B.

    2014-06-01

    Recent studies have focused on models to simulate the complex phenomenon of evolution of species. Several studies have been performed with theoretical models based on Darwin's theories to associate them with the actual evolution of species. However, none of the existing models include the affinity between individuals using network properties. In this paper, we present a new model based on the concept of affinity. The model is used to simulate the evolution of species in an ecosystem composed of individuals and their relationships. We propose an evolutive algorithm that incorporates the degree centrality and efficiency network properties to perform the crossover process and to obtain the network topology objective, respectively. Using a real network as a starting point, we simulate its evolution and compare its results with the results of 5788 computer-generated networks.

  4. A Novel Software Evolution Model Based on Software Networks

    Science.gov (United States)

    Pan, Weifeng; Li, Bing; Ma, Yutao; Liu, Jing

    Many published papers analyzed the forming mechanisms and evolution laws of OO software systems from software reuse, software pattern, etc. There, however, have been fewer models so far merely built on the software components such as methods, classes, etc. and their interactions. In this paper, a novel Software Evolution Model based on Software Networks (called SEM-SN) is proposed. It uses software network at class level to represent software systems, and uses software network’s dynamical generating process to simulate activities in real software development process such as new classes’ dynamical creations and their dynamical interactions with already existing classes. It also introduces the concept of node/edge ageing to describe the decaying of classes with time. Empirical results on eight open-source Object-Oriented (OO) software systems demonstrate that SCM-SN roughly describes the evolution process of software systems and the emergence of their complex network characteristics.

  5. River Network Evolution Based on Fluid-Erosion Model

    OpenAIRE

    2010-01-01

    A new landscape evolution model is proposed which is composed of the shallow water equations for the fluid above the sediment and the mass conservation equation of the sediment. Numerical simulations of the formation of landscape and river network are carried out based on these equations. It is shown that steady patterns of river network are formed for the initial inclinations of slopes within 0.00005 and 0.005. The fractal dimensions of the river network and the exponent of Hack's law are ob...

  6. The Evolution of Reputation-Based Cooperation in Regular Networks

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    Tatsuya Sasaki

    2017-01-01

    Full Text Available Despite recent advances in reputation technologies, it is not clear how reputation systems can affect human cooperation in social networks. Although it is known that two of the major mechanisms in the evolution of cooperation are spatial selection and reputation-based reciprocity, theoretical study of the interplay between both mechanisms remains almost uncharted. Here, we present a new individual-based model for the evolution of reciprocal cooperation between reputation and networks. We comparatively analyze four of the leading moral assessment rules—shunning, image scoring, stern judging, and simple standing—and base the model on the giving game in regular networks for Cooperators, Defectors, and Discriminators. Discriminators rely on a proper moral assessment rule. By using individual-based models, we show that the four assessment rules are differently characterized in terms of how cooperation evolves, depending on the benefit-to-cost ratio, the network-node degree, and the observation and error conditions. Our findings show that the most tolerant rule—simple standing—is the most robust among the four assessment rules in promoting cooperation in regular networks.

  7. Network Generation Model Based on Evolution Dynamics To Generate Benchmark Graphs

    CERN Document Server

    Pasta, Muhammad Qasim

    2016-01-01

    Network generation models provide an understanding of the dynamics behind the formation and evolution of different networks including social networks, technological networks and biological networks. Two important applications of these models are to study the evolution dynamics of network formation and to generate benchmark networks with known community structures. Research has been conducted in both these directions relatively independent of the other application area. This creates a disjunct between real world networks and the networks generated to study community detection algorithms. In this paper, we propose to study both these application areas together i.e.\\ introduce a network generation model based on evolution dynamics of real world networks and generate networks with community structures that can be used as benchmark graphs to study community detection algorithms. The generated networks possess tunable modular structures which can be used to generate networks with known community structures. We stud...

  8. Research on social communication network evolution based on topology potential distribution

    Science.gov (United States)

    Zhao, Dongjie; Jiang, Jian; Li, Deyi; Zhang, Haisu; Chen, Guisheng

    2011-12-01

    Aiming at the problem of social communication network evolution, first, topology potential is introduced to measure the local influence among nodes in networks. Second, from the perspective of topology potential distribution the method of network evolution description based on topology potential distribution is presented, which takes the artificial intelligence with uncertainty as basic theory and local influence among nodes as essentiality. Then, a social communication network is constructed by enron email dataset, the method presented is used to analyze the characteristic of the social communication network evolution and some useful conclusions are got, implying that the method is effective, which shows that topology potential distribution can effectively describe the characteristic of sociology and detect the local changes in social communication network.

  9. Manufacturing network evolution

    DEFF Research Database (Denmark)

    Yang, Cheng; Farooq, Sami; Johansen, John

    2011-01-01

    Purpose – This paper examines the effect of changes at the manufacturing plant level on other plants in the manufacturing network and also investigates the role of manufacturing plants on the evolution of a manufacturing network. Design/methodology/approach –The research questions are developed...... by identifying the gaps in the reviewed literature. The paper is based on three case studies undertaken in Danish manufacturing companies to explore in detail their manufacturing plants and networks. The cases provide a sound basis for developing the research questions and explaining the interaction between...... different manufacturing plants in the network and their impact on network transformation. Findings – The paper highlights the dominant role of manufacturing plants in the continuously changing shape of a manufacturing network. The paper demonstrates that a product or process change at one manufacturing...

  10. The Evolution of ICT Markets: An Agent-Based Model on Complex Networks

    Science.gov (United States)

    Zhao, Liangjie; Wu, Bangtao; Chen, Zhong; Li, Li

    Information and communication technology (ICT) products exhibit positive network effects.The dynamic process of ICT markets evolution has two intrinsic characteristics: (1) customers are influenced by each others’ purchasing decision; (2) customers are intelligent agents with bounded rationality.Guided by complex systems theory, we construct an agent-based model and simulate on complex networks to examine how the evolution can arise from the interaction of customers, which occur when they make expectations about the future installed base of a product by the fraction of neighbors who are using the same product in his personal network.We demonstrate that network effects play an important role in the evolution of markets share, which make even an inferior product can dominate the whole market.We also find that the intensity of customers’ communication can influence whether the best initial strategy for firms is to improve product quality or expand their installed base.

  11. DESIGN METHODOLOGY OF NETWORKED SOFTWARE EVOLUTION GROWTH BASED ON SOFTWARE PATTERNS

    Institute of Scientific and Technical Information of China (English)

    Keqing HE; Rong PENG; Jing LIU; Fei HE; Peng LIANG; Bing LI

    2006-01-01

    Recently, some new characteristics of complex networks attract the attentions of scientists in different fields, and lead to many kinds of emerging research directions. So far, most of the research work has been limited in discovery of complex network characteristics by structure analysis in large-scale software systems. This paper presents the theoretical basis, design method, algorithms and experiment results of the research. It firstly emphasizes the significance of design method of evolution growth for network topology of Object Oriented (OO) software systems, and argues that the selection and modulation of network models with various topology characteristics will bring un-ignorable effect on the process of design and implementation of OO software systems. Then we analyze the similar discipline of "negation of negation and compromise" between the evolution of network models with different topology characteristics and the development of software modelling methods. According to the analysis of the growth features of software patterns, we propose an object-oriented software network evolution growth method and its algorithms in succession. In addition, we also propose the parameter systems for Oosoftware system metrics based on complex network theory. Based on these parameter systems, it can analyze the features of various nodes, links and local-world, modulate the network topology and guide the software metrics. All these can be helpful to the detailed design, implementation and performance analysis. Finally, we focus on the application of the evolution algorithms and demonstrate it by a case study.Comparing the results from our early experiments with methodologies in empirical software engineering, we believe that the proposed software engineering design method is a computational software engineering approach based on complex network theory. We argue that this method should be greatly beneficial for the design, implementation, modulation and metrics of

  12. Differential Evolution Algorithm Based Solution Approaches for Solving Transportation Network Design Problems

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    Özgür Başkan

    2014-09-01

    Full Text Available Differential Evolution algorithm has effectively been used to solve engineering optimization problems recently. The Differential Evolution algorithm, which uses similar principles with Genetic Algorithms, is more robust on obtaining optimal solution than many other heuristic algorithms with its simpler structure. In this study, Differential Evolution algorithm is applied to the transportation network design problems and its effectiveness on the solution is investigated. In this context, Differential Evolution based models are developed using bi-level programming approach for the solution of the transportation network design problem and determination of the on-street parking places in urban road networks. In these models, optimal investment and parking strategies are investigated on the upper level. On the lower level, deterministic traffic assignment problem, which represents drivers' responses, is solved using Frank-Wolfe algorithm and VISUM traffic modeling software. In order to determine the effectiveness of the proposed models, numerical applications are carried out on Sioux-Falls test network. Results showed that the Differential Evolution algorithm may effectively been used for the solution of transportation network design problems.

  13. An approach of community evolution based on gravitational relationship refactoring in dynamic networks

    Energy Technology Data Exchange (ETDEWEB)

    Yin, Guisheng; Chi, Kuo, E-mail: chik89769@hrbeu.edu.cn; Dong, Yuxin; Dong, Hongbin

    2017-04-25

    In this paper, an approach of community evolution based on gravitational relationship refactoring between the nodes in a dynamic network is proposed, and it can be used to simulate the process of community evolution. A static community detection algorithm and a dynamic community evolution algorithm are included in the approach. At first, communities are initialized by constructing the core nodes chains, the nodes can be iteratively searched and divided into corresponding communities via the static community detection algorithm. For a dynamic network, an evolutionary process is divided into three phases, and behaviors of community evolution can be judged according to the changing situation of the core nodes chain in each community. Experiments show that the proposed approach can achieve accuracy and availability in the synthetic and real world networks. - Highlights: • The proposed approach considers both the static community detection and dynamic community evolution. • The approach of community evolution can identify the whole 6 common evolution events. • The proposed approach can judge the evolutionary events according to the variations of the core nodes chains.

  14. On cooperative and efficient overlay network evolution based on a group selection pattern.

    Science.gov (United States)

    Wang, Yufeng; Nakao, Akihiro

    2010-06-01

    In overlay networks, the interplay between network structure and dynamics remains largely unexplored. In this paper, we study dynamic coevolution between individual rational strategies (cooperative or defect) and the overlay network structure, that is, the interaction between peer's local rational behaviors and the emergence of the whole network structure. We propose an evolutionary game theory (EGT)-based overlay topology evolution scheme to drive a given overlay into the small-world structure (high global network efficiency and average clustering coefficient). Our contributions are the following threefold: From the viewpoint of peers' local interactions, we explicitly consider the peer's rational behavior and introduce a link-formation game to characterize the social dilemma of forming links in an overlay network. Furthermore, in the evolutionary link-formation phase, we adopt a simple economic process: Each peer keeps one link to a cooperative neighbor in its neighborhood, which can slightly speed up the convergence of cooperation and increase network efficiency; from the viewpoint of the whole network structure, our simulation results show that the EGT-based scheme can drive an arbitrary overlay network into a fully cooperative and efficient small-world structure. Moreover, we compare our scheme with a search-based economic model of network formation and illustrate that our scheme can achieve the experimental and analytical results in the latter model. In addition, we also graphically illustrate the final overlay network structure; finally, based on the group selection model and evolutionary set theory, we theoretically obtain the approximate threshold of cost and draw the conclusion that the small value of the average degree and the large number of the total peers in an overlay network facilitate the evolution of cooperation.

  15. An Evolution Model of Trading Behavior Based on Peer Effect in Networks

    Directory of Open Access Journals (Sweden)

    Yue-Tang Bian

    2012-01-01

    Full Text Available This work concerns the modeling of evolvement of trading behavior in stock markets which can cause significant impact on the movements of prices and volatilities. Based on the assumption of the investors' limited rationality, the evolution mechanism of trading behavior is modeled according to peer effect in network, that investors are prone to imitate their neighbors' activity through comprehensive analysis on the neighboring preferred degree, self-psychological preference, and the network topology of the relationship among them. We investigate by mean-field analysis and extensive simulations the evolution of investors' trading behavior in various typical networks under different characteristics of peer effect. Our results indicate that the evolution of investors' behavior is affected by the network structure of stock market and the effect of neighboring preferred degree; the stability of equilibrium states of investors' behavior dynamics is directly related with the concavity and convexity of the peer effect function; connectivity and heterogeneity of the network play an important role in the evolution of the investment behavior in stock market.

  16. Manufacturing network evolution

    DEFF Research Database (Denmark)

    Yang, Cheng; Farooq, Sami; Johansen, John

    2011-01-01

    Purpose – This paper examines the effect of changes at the manufacturing plant level on other plants in the manufacturing network and also investigates the role of manufacturing plants on the evolution of a manufacturing network. Design/methodology/approach –The research questions are developed......, the complex phenomenon of a manufacturing network evolution is observed by combining the analysis of a manufacturing plant and network level. The historical trajectories of manufacturing networks that are presented in the case studies are examined in order to understand and determine the future shape...

  17. Nonlinear Dynamical Behavior in BS Evolution Model Based on Small-World Network Added with Mechanism of Preferential Connection

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In this paper, we introduce a modified small-world network added with new links with preferential connection instead of adding randomly, then we apply Bak-Sneppen (BS) evolution model on this network. Several dynamical character of the model such as the evolution graph, fo avalanche, the critical exponent D and τ, and the distribution of mutation times of all the nodes, show particular behaviors different from those of the model based on the regular network and the small-world network.

  18. Neural Networks Based Physical Cell Identity Assignment for Self Organized 3GPP Long Term Evolution

    Directory of Open Access Journals (Sweden)

    Muhammad Basit Shahab

    2013-10-01

    Full Text Available This paper proposes neural networks based graph coloring technique to assign Physical Cell Identities throughout the self-organized 3GPP Long Term Evolution Networks. PCIs are allocated such that no two cells in the vicinity of each other or with a common neighbor get the same identity. Efficiency of proposed methodology resides in the fact that minimum number of identities is utilized in the network wise assignment. Simulations are performed on a very large scale network, where initially all the cells are without any PCIs assigned. Results of simulations are demonstrated to analyze the performance of the proposed technique. Discussions about the presence of femto cells and PCI assignment in them are also presented at the end.

  19. Evolution of Social networks

    OpenAIRE

    Hellmann, Tim; Staudigl, Mathias

    2012-01-01

    Modeling the evolution of networks is central to our understanding of modern large communication systems, such as theWorld-Wide-Web, as well as economic and social networks. The research on social and economic networks is truly interdisciplinary and the number of modeling strategies and concepts is enormous. In this survey we present some modeling approaches, covering classical random graph models and game-theoretic models, which may be used to provide a unified framework to model and analyze...

  20. Spatial and Temporal Behaviors in a Modified Evolution Model Based on Small World Network

    Institute of Scientific and Technical Information of China (English)

    ZHAO Xiao-Wei; ZHOU Li-Ming; CHEN Tian-Lun

    2004-01-01

    In this paper, we introduce a new modified evolution model on a small world network. In our model,the spatial and temporal correlations and the spatial-temporal evolve pattern of mutating nodes exhibit some particular behaviors different from those of the original BS evolution model. More importantly, these behaviors will change with φ, the density of short paths in our network.

  1. Active networks: an evolution of the internet

    OpenAIRE

    Di Fatta, Giuseppe; Lo Re, Giuseppe

    2001-01-01

    Active Networks can be seen as an evolution of the classical model of packet-switched networks. The traditional and ”passive” network model is based on a static definition of the network node behaviour. Active Networks propose an “active” model where the intermediate nodes (switches and routers) can load and execute user code contained in the data units (packets). Active Networks are a programmable network model, where bandwidth and computation are both considered shared network resources. Th...

  2. A contribution to the study of plant development evolution based on gene co-expression networks

    Directory of Open Access Journals (Sweden)

    Francisco J. Romero-Campero

    2013-08-01

    Full Text Available Phototrophic eukaryotes are among the most successful organisms on Earth due to their unparalleled efficiency at capturing light energy and fixing carbon dioxide to produce organic molecules. A conserved and efficient network of light-dependent regulatory modules could be at the bases of this success. This regulatory system conferred early advantages to phototrophic eukaryotes that allowed for specialization, complex developmental processes and modern plant characteristics. We have studied light-dependent gene regulatory modules from algae to plants employing integrative-omics approaches based on gene co-expression networks. Our study reveals some remarkably conserved ways in which eukaryotic phototrophs deal with day length and light signaling. Here we describe how a family of Arabidopsis transcription factors involved in photoperiod response has evolved from a single algal gene according to the innovation, amplification and divergence theory of gene evolution by duplication. These modifications of the gene co-expression networks from the ancient unicellular green algae Chlamydomonas reinhardtii to the modern brassica Arabidopsis thaliana may hint on the evolution and specialization of plants and other organisms.

  3. Transient and sustained elementary flux mode networks on a catalytic string-based chemical evolution model.

    Science.gov (United States)

    Pereira, José A

    2014-08-01

    Theoretical models designed to test the metabolism-first hypothesis for prebiotic evolution have yield strong indications about the hypothesis validity but could sometimes use a more extensive identification between model objects and real objects towards a more meaningful interpretation of results. In an attempt to go in that direction, the string-based model SSE ("steady state evolution") was developed, where abstract molecules (strings) and catalytic interaction rules are based on some of the most important features of carbon compounds in biological chemistry. The system is open with a random inflow and outflow of strings but also with a permanent string food source. Although specific catalysis is a key aspect of the model, used to define reaction rules, the focus is on energetics rather than kinetics. Standard energy change tables were constructed and used with standard formation reactions to track energy flows through the interpretation of equilibrium constant values. Detection of metabolic networks on the reaction system was done with elementary flux mode (EFM) analysis. The combination of these model design and analysis options enabled obtaining metabolic and catalytic networks showing several central features of biological metabolism, some more clearly than in previous models: metabolic networks with stepwise synthesis, energy coupling, catalysts regulation, SN2 coupling, redox coupling, intermediate cycling, coupled inverse pathways (metabolic cycling), autocatalytic cycles and catalytic cascades. The results strongly suggest that the main biological metabolism features, including the genotype-phenotype interpretation, are caused by the principles of catalytic systems and are prior to modern genetic systems principles. It also gives further theoretical support to the thesis that the basic features of biologic metabolism are a consequence of the time evolution of a random catalyst search working on an open system with a permanent food source. The importance

  4. 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.

  5. Route strategy of satellite network in GNSS based on topology evolution law

    Institute of Scientific and Technical Information of China (English)

    Xianqing Yi; Zhenwei Hou; Tao Zhong; Yaohong Zhang; Zhili Sun

    2014-01-01

    As each type of satel ite network has different link features, its data transmission must be designed based on its link features to improve the efficiency of data transferring. The transmission of navigation integrated services information (NISI) in a global navigation satel ite system (GNSS) with inter-satel ite links (ISLs) is studied by taking the real situation of inter-satel ite communication links into account. An on-demand computing and buffering centralized route strategy is proposed based on dynamic grouping and the topology evolution law of the GNSS network within which the satel ite nodes are operated in the manner of dynamic grouping. Dynamic grouping is based on satel ites spatial relationships and the group role of the satel ite node changes by turns due to its spatial relationships. The route strategy provides significant advantages of high efficiency, low complexity, and flexi-ble configuration, by which the established GNSS can possess the features and capabilities of feasible deployment, efficient trans-mission, convenient management, structural invulnerability and flexible expansion.

  6. Optimization of the Distribution and Localization of Wireless Sensor Networks Based on Differential Evolution Approach

    Directory of Open Access Journals (Sweden)

    Armando Céspedes-Mota

    2016-01-01

    Full Text Available Location information for wireless sensor nodes is needed in most of the routing protocols for distributed sensor networks to determine the distance between two particular nodes in order to estimate the energy consumption. Differential evolution obtains a suboptimal solution based on three features included in the objective function: area, energy, and redundancy. The use of obstacles is considered to check how these barriers affect the behavior of the whole solution. The obstacles are considered like new restrictions aside of the typical restrictions of area boundaries and the overlap minimization. At each generation, the best element is tested to check whether the node distribution is able to create a minimum spanning tree and then to arrange the nodes using the smallest distance from the initial position to the suboptimal end position based on the Hungarian algorithm. This work presents results for different scenarios delimited by walls and testing whether it is possible to obtain a suboptimal solution with inner obstacles. Also, a case with an area delimited by a star shape is presented showing that the algorithm is able to fill the whole area, even if such area is delimited for the peaks of the star.

  7. Plant Evolution: A Manufacturing Network Perspective

    DEFF Research Database (Denmark)

    Yang, Cheng; Johansen, John; Boer, Harry

    2009-01-01

    Viewing them as portfolios of products and processes, we aim to address how plants evolve in the context of a manufacturing network and how the evolution of one plant impacts other plants in the same manufacturing network. Based on discussions of ten plants from three Danish companies, we identify...

  8. Measuring multiple evolution mechanisms of complex networks.

    Science.gov (United States)

    Zhang, Qian-Ming; Xu, Xiao-Ke; Zhu, Yu-Xiao; Zhou, Tao

    2015-01-01

    Numerous concise models such as preferential attachment have been put forward to reveal the evolution mechanisms of real-world networks, which show that real-world networks are usually jointly driven by a hybrid mechanism of multiplex features instead of a single pure mechanism. To get an accurate simulation for real networks, some researchers proposed a few hybrid models by mixing multiple evolution mechanisms. Nevertheless, how a hybrid mechanism of multiplex features jointly influence the network evolution is not very clear. In this study, we introduce two methods (link prediction and likelihood analysis) to measure multiple evolution mechanisms of complex networks. Through tremendous experiments on artificial networks, which can be controlled to follow multiple mechanisms with different weights, we find the method based on likelihood analysis performs much better and gives very accurate estimations. At last, we apply this method to some real-world networks which are from different domains (including technology networks and social networks) and different countries (e.g., USA and China), to see how popularity and clustering co-evolve. We find most of them are affected by both popularity and clustering, but with quite different weights.

  9. An evolution analysis of executive-based listed company relationships using complex networks

    Science.gov (United States)

    An, Feng; Gao, Xiangyun; Guan, Jianhe; Li, Huajiao; Liu, Qian

    2016-04-01

    This paper addresses the problem of relationship analysis of listed companies. It mainly focuses on the analysis of affiliation relationship network among listed companies based on the co-attendance behavior of senior executives. In order to solve this problem we propose a two-stage method. In stage 1, we propose a method of network construction which can change the two-mode affiliation network to one-mode network using model-descending process, and in stage 2, we analyze the networks from stage 1 in four aspects includes analysis of topological characteristic, influence distribution, information control ability distribution and small world phenomenon. We then took a case of Chinese listed companies' executive-based network as an example of the method and the results of the case study showed that the co-attendance behaviors of executives became more widespread (the number and percentage of related listed companies increased 624% and 322%) and that more companies preferred to relate to others on this level, improving the stability of the massive company structures.

  10. Differential evolution based on the node degree of its complex network: Initial study

    Science.gov (United States)

    Skanderova, Lenka; Zelinka, Ivan

    2016-06-01

    In this paper is reported our progress in the synthesis of two partially different areas of research: complex networks and evolutionary computation. Ideas and results reported and mentioned here are based on our previous results and experiments. The main core of our participation is an evolutionary algorithm performance improvement by means of complex network use. Complex network is related to the evolutionary dynamics and reflect it. We report here our latest results as well as propositions on further research that is in process in our group (http://navy.cs.vsb.cz/). Only the main ideas and results are reported here, for more details it is recommended to read related literature of our previous research and results.

  11. Energy Efficient Evolution of Mobile Broadband Networks

    DEFF Research Database (Denmark)

    Micallef, Gilbert

    costs, which, based on increasing energy prices and necessary network upgrades are likely to increase. Since base station sites make up for about 75% of the power consumption in mobile networks, studies are focused on this specific network element. A number of factors believed to play a role...... the v impact of replacing old equipment. Results show that an aggressive replacement strategy and the upgrade of sites to remote radio head can restrain the increase in power consumption of the network to just 17%. In addition to upgrading equipment, mobile network operators can further reduce power...... network capacity evolution path, replacing old and less efficient equipment, and enabling power saving features, can all considerably reduce the power consumption of future mobile broadband networks. Studies and recommendations presented within this thesis demonstrate that it is realistic for mobile...

  12. Measuring multiple evolution mechanisms of complex networks

    CERN Document Server

    Zhang, Qian-Ming; Zhu, Yu-Xiao; Zhou, Tao

    2014-01-01

    Traditionally, numerous simple models such as preferential attachment have been put forward to reveal the evolution mechanisms of real networks. However, previous simulations show that real networks usually are driven by various features instead of single pure mechanism. To solve this problem, some pioneers proposed a few hybrid models of mixing multiple evolution mechanisms and tried to uncover the contributions of different mechanisms. In this paper, we introduce two methods which can tackle this problem: one is based on link prediction model, and the other is based on likelihood analysis. To examine the effectiveness, we generate plenty of artificial networks which can be controlled to follow multiple mechanisms with different weights, so that we can compare the estimated weights with the true values. The experimental results show the method based on likelihood analysis performs much better and gives very accurate estimations. At last, we apply this method to real networks to see how popularity and cluster...

  13. Evolution of Chinese airport network

    CERN Document Server

    Zhang, Jun; Du, Wen-Bo; Cai, Kai-Quan

    2011-01-01

    With the rapid development of economy and the accelerated globalization process, the aviation industry plays more and more critical role in today's world, in both developed and developing countries. As the infrastructure of aviation industry, the airport network is one of the most important indicators of economic growth. In this paper, we investigate the evolution of Chinese airport network (CAN) via complex network theory. It is found that although the topology of CAN remains steady during the past several years, there are many dynamic switchings inside the network, which changes the relative relevance of airports and airlines. Moreover, we investigate the evolution of traffic flow (passengers and cargoes) on CAN. It is found that the traffic keeps growing in an exponential form and it has evident seasonal fluctuations. We also found that cargo traffic and passenger traffic are positively related but the correlations are quite different for different kinds of cities.

  14. Evolution of Ideas: A Novel Memetic Algorithm Based on Semantic Networks

    CERN Document Server

    Baydin, Atilim Gunes

    2012-01-01

    This paper presents a new type of evolutionary algorithm (EA) based on the concept of "meme", where the individuals forming the population are represented by semantic networks and the fitness measure is defined as a function of the represented knowledge. Our work can be classified as a novel memetic algorithm (MA), given that (1) it is the units of culture, or information, that are undergoing variation, transmission, and selection, very close to the original sense of memetics as it was introduced by Dawkins; and (2) this is different from existing MA, where the idea of memetics has been utilized as a means of local refinement by individual learning after classical global sampling of EA. The individual pieces of information are represented as simple semantic networks that are directed graphs of concepts and binary relations, going through variation by memetic versions of operators such as crossover and mutation, which utilize knowledge from commonsense knowledge bases. In evaluating this introductory work, as ...

  15. Energy efficient evolution of mobile broadband networks

    Energy Technology Data Exchange (ETDEWEB)

    Micallef, G.

    2013-04-15

    Over the last decade, the mobile communications industry has broken through some remarkable barriers, pushing further and transforming the way people communicate and access information. As the volume of traffic carried by mobile networks maintains an insatiable growth, mobile network operators are required to ensure that networks can scale accordingly. In addition to upgrading existing networks, a number of operators have already started to rollout a further radio access technology layer, Long Term Evolution, or LTE. In addition to enhancing network capacity, operators are also required to adhere to public commitments for reducing their energy and carbon footprint. In 2008 Vodafone stated that by the year 2020, efforts for reducing emissions are expected to halve emissions registered in the year 2006/7. In addition to presenting a more environmentally conscious brand, this is also hoped to reduce costs, which, based on increasing energy prices and necessary network upgrades are likely to increase. Since base station sites make up for about 75% of the power consumption in mobile networks, studies are focused on this specific network element. A number of factors believed to play a role in the power consumption of mobile networks are separately investigated and later combined, providing a realistic indication of how the consumption is expected to evolve. This is also used as an indication to determine how likely it is for operators to achieve power consumption and emission targets. In order for mobile network operators to upgrade existing infrastructure different options are available. Irrespective of the selected option, capacity upgrades are bound to increase the power consumption of the network. Carried through case studies, a first analysis compares a number of network evolution strategies, determining which provides the necessary performance while limiting the increase in power consumption. Overall, it is noted that a hybrid solution involving the upgrade of

  16. Simulation Research of Space-Time Evolution of Emergency Logistics Network Reliability Based on Complex Network Theory

    Directory of Open Access Journals (Sweden)

    Li Huang

    2013-01-01

    Full Text Available We propose the conception and evaluation indexes of emergency logistics network connecting reliability to construct evaluation index system of complex network reliability, and describe these indexes quantitatively to evaluate the network connecting reliability. Moreover, the network topological model and the simulation methods of reliability measurement when the network is under attack are present. Finally, we take three classical emergency logistics networks as examples, and through emulation analysis we obtain the connecting reliability changing situation of these three networks under random attack, the changing curve of the ratio of effective demand nodes and emergence supply mileage of emergency logistics network with same network density but different forms, and then evaluate the emergency logistics network connecting reliability. This can provide references for the designing of emergency logistics network with high reliability and analysis means for research in other fields.

  17. 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.

  18. Modeling Evolution of Weighted Clique Networks

    Science.gov (United States)

    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.

  19. Internet-based social networking and its role in the evolution of chronic cerebrospinal venous insufficiency.

    Science.gov (United States)

    Vera, Chido; Herr, Allen; Mandato, Kenneth; Englander, Meridith; Ginsburg, Lauren; Siskin, Gary P

    2012-06-01

    The Internet is being seen as a growing resource for health-related information for a large number of patients. It is undeniable that its widespread presence has led to the growth of awareness that chronic cerebrospinal venous insufficiency (CCSVI) as an entity that may contribute to the symptoms experienced by patients with multiple sclerosis (MS). Social networking and file-sharing Web sites have brought patients with MS together from all over the world and have facilitated the distribution of personal experiences and information derived from medical research as it relates to CCSVI. As a result, there has been an accelerated growth in the number of patients seeking treatment for this syndrome in light of the possibility that it may improve their present condition. This article will review this phenomenon, the Internet-based resources available to MS patients seeking information about CCSVI, and the responsibilities of physicians as they participate in these online discussions.

  20. Evolution model of online social networks based on complex networks%复杂网络中的在线社交网络演化模型

    Institute of Scientific and Technical Information of China (English)

    王景丽; 许立波; 庞超逸

    2015-01-01

    在线社交网络是一种广泛存在的社会网络,其节点度遵循幂率分布规律,但对于其结构演化模型方面的相关研究还不多. 基于复杂网络理论研究在线社交网络内部结构特征,提出一种结合内增长、外增长及内部边更替的演化模型,借助平均场理论分析该模型的拓扑特性,实验和理论分析表明由该模型生成的网络,其度分布服从幂率分布,且通过调整参数,幂率指数在1~3,能较好地反映不同类型的真实在线社交网络的度分布特征,因此具有广泛适用性.%As a widespread social network , the node degree of online social networks has been proven by many re-searchers to follow the power-law distribution .However , there are few studies modeling the evolution of its struc-ture.In this paper , we propose an evolution model that combines the inside growth , outside growth , and edge re-placement based on those of complex networks .The topology properties of this model are analyzed using the mean-field theory .Experiment and theoretical analyses show that the degree of a node in a network generated by the new evolution model follows the power-law distribution and that the power-law index ranges between 1 and 3.Therefore , the proposed model can better reflect the node degree distribution characteristics of different types of real online so -cial networks and will have wide applicability .

  1. Evolution of Terrorist Network using Clustered approach: A Case study

    DEFF Research Database (Denmark)

    2011-01-01

    In the paper we present a cluster based approach for terrorist network evolution. We have applied hierarchical agglomerative clustering approach to 9/11 case study. We show that, how individual actors who are initially isolated from each other are converted in small clusters and result in a fully...... evolved network. This method of network evolution can help intelligence security analysts to understand the structure of the network....

  2. Evolution of metabolic network organization

    Directory of Open Access Journals (Sweden)

    Bonchev Danail

    2010-05-01

    Full Text Available Abstract Background Comparison of metabolic networks across species is a key to understanding how evolutionary pressures shape these networks. By selecting taxa representative of different lineages or lifestyles and using a comprehensive set of descriptors of the structure and complexity of their metabolic networks, one can highlight both qualitative and quantitative differences in the metabolic organization of species subject to distinct evolutionary paths or environmental constraints. Results We used a novel representation of metabolic networks, termed network of interacting pathways or NIP, to focus on the modular, high-level organization of the metabolic capabilities of the cell. Using machine learning techniques we identified the most relevant aspects of cellular organization that change under evolutionary pressures. We considered the transitions from prokarya to eukarya (with a focus on the transitions among the archaea, bacteria and eukarya, from unicellular to multicellular eukarya, from free living to host-associated bacteria, from anaerobic to aerobic, as well as the acquisition of cell motility or growth in an environment of various levels of salinity or temperature. Intuitively, we expect organisms with more complex lifestyles to have more complex and robust metabolic networks. Here we demonstrate for the first time that such organisms are not only characterized by larger, denser networks of metabolic pathways but also have more efficiently organized cross communications, as revealed by subtle changes in network topology. These changes are unevenly distributed among metabolic pathways, with specific categories of pathways being promoted to more central locations as an answer to environmental constraints. Conclusions Combining methods from graph theory and machine learning, we have shown here that evolutionary pressures not only affects gene and protein sequences, but also specific details of the complex wiring of functional modules

  3. Predicting Community Evolution in Social Networks

    Directory of Open Access Journals (Sweden)

    Stanisław Saganowski

    2015-05-01

    Full Text Available Nowadays, sustained development of different social media can be observed worldwide. One of the relevant research domains intensively explored recently is analysis of social communities existing in social media as well as prediction of their future evolution taking into account collected historical evolution chains. These evolution chains proposed in the paper contain group states in the previous time frames and its historical transitions that were identified using one out of two methods: Stable Group Changes Identification (SGCI and Group Evolution Discovery (GED. Based on the observed evolution chains of various length, structural network features are extracted, validated and selected as well as used to learn classification models. The experimental studies were performed on three real datasets with different profile: DBLP, Facebook and Polish blogosphere. The process of group prediction was analysed with respect to different classifiers as well as various descriptive feature sets extracted from evolution chains of different length. The results revealed that, in general, the longer evolution chains the better predictive abilities of the classification models. However, chains of length 3 to 7 enabled the GED-based method to almost reach its maximum possible prediction quality. For SGCI, this value was at the level of 3–5 last periods.

  4. On the Evolution of Complex Network Topology Under Network Churn

    OpenAIRE

    Karyotis, Vasileios; Stai, Eleni; Papavassiliou, Symeon

    2016-01-01

    Part 6: Network Modeling; International audience; The future Internet is becoming more diverse, incorporating heterogeneous access networks. The latter are characterized by numerous devices that join/leave the network dynamically, creating intense churn patterns. New approaches to analyze and quantify churn-induced network evolution are required. In this paper, we address such need by introducing a new analysis framework that maps network evolution into trajectories in multi-dimensional vecto...

  5. Nonlinear Dynamical Behavior in BS Evolution Model Based on Small-World Network Added with Nonlinear Preference

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ying-Yue; YANG Qiu-Ying; CHEN Tian-Lun

    2007-01-01

    We introduce a modified small-world network adding new links with nonlinearly preferential connection instead of adding randomly, then we apply Bak-Sneppen (BS) evolution model on this network. We study several important structural properties of our network such as the distribution of link-degree, the maximum link-degree, and the length of the shortest path. We further argue several dynamical characteristics of the model such as the important critical value fc, the f0 avalanche, and the mutating condition, and find that those characteristics show particular behaviors.

  6. Group Evolution Discovery in Social Networks

    OpenAIRE

    Bródka, Piotr; Saganowski, Stanisław; Kazienko, Przemysław

    2013-01-01

    Group extraction and their evolution are among the topics which arouse the greatest interest in the domain of social network analysis. However, while the grouping methods in social networks are developed very dynamically, the methods of group evolution discovery and analysis are still uncharted territory on the social network analysis map. Therefore the new method for the group evolution discovery called GED is proposed in this paper. Additionally, the results of the first experiments on the ...

  7. Predicting Group Evolution in the Social Network

    OpenAIRE

    Bródka, Piotr; Kazienko, Przemysław; Kołoszczyk, Bartosz

    2012-01-01

    Groups - social communities are important components of entire societies, analysed by means of the social network concept. Their immanent feature is continuous evolution over time. If we know how groups in the social network has evolved we can use this information and try to predict the next step in the given group evolution. In the paper, a new aproach for group evolution prediction is presented and examined. Experimental studies on four evolving social networks revealed that (i) the predict...

  8. The evolution analysis of listed companies co-holding non-listed financial companies based on two-mode heterogeneous networks

    Science.gov (United States)

    An, Pengli; Li, Huajiao; Zhou, Jinsheng; Chen, Fan

    2017-10-01

    Complex network theory is a widely used tool in the empirical research of financial markets. Two-mode and multi-mode networks are new trends and represent new directions in that they can more accurately simulate relationships between entities. In this paper, we use data for Chinese listed companies holding non-listed financial companies over a ten-year period to construct two networks: a two-mode primitive network in which listed companies and non-listed financial companies are considered actors and events, respectively, and a one-mode network that is constructed based on the decreasing-mode method in which listed companies are considered nodes. We analyze the evolution of the listed company co-holding network from several perspectives, including that of the whole network, of information control ability, of implicit relationships, of community division and of small-world characteristics. The results of the analysis indicate that (1) China's developing stock market affects the share-holding condition of listed companies holding non-listed financial companies; (2) the information control ability of co-holding networks is focused on a few listed companies and the implicit relationship of investment preference between listed companies is determined by the co-holding behavior; (3) the community division of the co-holding network is increasingly obvious, as determined by the investment preferences among listed companies; and (4) the small-world characteristics of the co-holding network are increasingly obvious, resulting in reduced communication costs. In this paper, we conduct an evolution analysis and develop an understanding of the factors that influence the listed companies co-holding network. This study will help illuminate research on evolution analysis.

  9. Evolution of a Modular Software Network

    CERN Document Server

    Fortuna, Miguel A; Levin, Simon A

    2011-01-01

    "Evolution behaves like a tinkerer" (Francois Jacob, Science, 1977). Software systems provide a unique opportunity to understand biological processes using concepts from network theory. The Debian GNU/Linux operating system allows us to explore the evolution of a complex network in a novel way. The modular design detected during its growth is based on the reuse of existing code in order to minimize costs during programming. The increase of modularity experienced by the system over time has not counterbalanced the increase in incompatibilities between software packages within modules. This negative effect is far from being a failure of design. A random process of package installation shows that the higher the modularity the larger the fraction of packages working properly in a local computer. The decrease in the relative number of conflicts between packages from different modules avoids a failure in the functionality of one package spreading throughout the entire system. Some potential analogies with the evolu...

  10. Energy efficient evolution of mobile broadband networks

    Energy Technology Data Exchange (ETDEWEB)

    Micallef, G.

    2013-04-15

    Over the last decade, the mobile communications industry has broken through some remarkable barriers, pushing further and transforming the way people communicate and access information. As the volume of traffic carried by mobile networks maintains an insatiable growth, mobile network operators are required to ensure that networks can scale accordingly. In addition to upgrading existing networks, a number of operators have already started to rollout a further radio access technology layer, Long Term Evolution, or LTE. In addition to enhancing network capacity, operators are also required to adhere to public commitments for reducing their energy and carbon footprint. In 2008 Vodafone stated that by the year 2020, efforts for reducing emissions are expected to halve emissions registered in the year 2006/7. In addition to presenting a more environmentally conscious brand, this is also hoped to reduce costs, which, based on increasing energy prices and necessary network upgrades are likely to increase. Since base station sites make up for about 75% of the power consumption in mobile networks, studies are focused on this specific network element. A number of factors believed to play a role in the power consumption of mobile networks are separately investigated and later combined, providing a realistic indication of how the consumption is expected to evolve. This is also used as an indication to determine how likely it is for operators to achieve power consumption and emission targets. In order for mobile network operators to upgrade existing infrastructure different options are available. Irrespective of the selected option, capacity upgrades are bound to increase the power consumption of the network. Carried through case studies, a first analysis compares a number of network evolution strategies, determining which provides the necessary performance while limiting the increase in power consumption. Overall, it is noted that a hybrid solution involving the upgrade of

  11. Evolution Properties of Modules in Complex Networks

    Institute of Scientific and Technical Information of China (English)

    LI Ke-Ping; GAO Zi-You

    2008-01-01

    In complex networks, network modules play a center role, which carry out a key function. In this paper, we introduce the spatial correlation function to describe the relationships among the network modules. Our focus is to investigate how the network modules evolve, and what the evolution properties of the modules are. In order to test the proposed method, as the examples, we use our method to analyze and discuss the ER random network and scale-free network. Rigorous analysis of the existing data shows that the introduced correlation function is suitable for describing the evolution properties of network modules. Remarkably, the numerical simulations indicate that the ER random network and scale-free network have different evolution properties.

  12. A paradigm for viewing biologic systems as scale-free networks based on energy efficiency: implications for present therapies and the future of evolution.

    Science.gov (United States)

    Yun, Anthony J; Lee, Patrick Y; Doux, John D

    2006-01-01

    A network constitutes an abstract description of the relationships among entities, respectively termed links and nodes. If a power law describes the probability distribution of the number of links per node, the network is said to be scale-free. Scale-free networks feature link clustering around certain hubs based on preferential attachments that emerge due either to merit or legacy. Biologic systems ranging from sub-atomic to ecosystems represent scale-free networks in which energy efficiency forms the basis of preferential attachments. This paradigm engenders a novel scale-free network theory of evolution based on energy efficiency. As environmental flux induces fitness dislocations and compels a new meritocracy, new merit-based hubs emerge, previously merit-based hubs become legacy hubs, and network recalibration occurs to achieve system optimization. To date, Darwinian evolution, characterized by innovation sampling, variation, and selection through filtered termination, has enabled biologic progress through optimization of energy efficiency. However, as humans remodel their environment, increasing the level of unanticipated fitness dislocations and inducing evolutionary stress, the tendency of networks to exhibit inertia and retain legacy hubs engender maladaptations. Many modern diseases may fundamentally derive from these evolutionary displacements. Death itself may constitute a programmed adaptation, terminating individuals who represent legacy hubs and recalibrating the network. As memes replace genes as the basis of innovation, death itself has become a legacy hub. Post-Darwinian evolution may favor indefinite persistence to optimize energy efficiency. We describe strategies to reprogram or decommission legacy hubs that participate in human disease and death.

  13. Perception Evolution Network Based on Cognition Deepening Model--Adapting to the Emergence of New Sensory Receptor.

    Science.gov (United States)

    Xing, Youlu; Shen, Furao; Zhao, Jinxi

    2016-03-01

    The proposed perception evolution network (PEN) is a biologically inspired neural network model for unsupervised learning and online incremental learning. It is able to automatically learn suitable prototypes from learning data in an incremental way, and it does not require the predefined prototype number or the predefined similarity threshold. Meanwhile, being more advanced than the existing unsupervised neural network model, PEN permits the emergence of a new dimension of perception in the perception field of the network. When a new dimension of perception is introduced, PEN is able to integrate the new dimensional sensory inputs with the learned prototypes, i.e., the prototypes are mapped to a high-dimensional space, which consists of both the original dimension and the new dimension of the sensory inputs. In the experiment, artificial data and real-world data are used to test the proposed PEN, and the results show that PEN can work effectively.

  14. 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.

  15. A last updating evolution model for online social networks

    Science.gov (United States)

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

    2013-05-01

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

  16. Topological evolution of virtual social networks by modeling social activities

    Science.gov (United States)

    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.

  17. Cloud networking understanding cloud-based data center networks

    CERN Document Server

    Lee, Gary

    2014-01-01

    Cloud Networking: Understanding Cloud-Based Data Center Networks explains the evolution of established networking technologies into distributed, cloud-based networks. Starting with an overview of cloud technologies, the book explains how cloud data center networks leverage distributed systems for network virtualization, storage networking, and software-defined networking. The author offers insider perspective to key components that make a cloud network possible such as switch fabric technology and data center networking standards. The final chapters look ahead to developments in architectures

  18. Evolution of Cooperation in Adaptive Social Networks

    Science.gov (United States)

    Segbroeck, Sven Van; Santos, Francisco C.; Traulsen, Arne; Lenaerts, Tom; Pacheco, Jorge M.

    Humans are organized in societies, a phenomenon that would never have been possible without the evolution of cooperative behavior. Several mechanisms that foster this evolution have been unraveled over the years, with population structure as a prominent promoter of cooperation. Modern networks of exchange and cooperation are, however, becoming increasingly volatile, and less and less based on long-term stable structure. Here, we address how this change of paradigm aspects the evolution of cooperation. We discuss analytical and numerical models in which individuals can break social ties and create new ones. Interactions are modeled as two-player dilemmas of cooperation. Once a link between two individuals has formed, the productivity of this link is evaluated. Links can be broken off at different rates. This individual capacity of forming new links or severing inconvenient ones can effectively change the nature of the game. We address random formation of new links and local linking rules as well as different individual capacities to maintain social interactions. We conclude by discussing how adaptive social networks can become an important step towards more realistic models of cultural dynamics.

  19. The evolution of network-based business models illustrated through the case study of an entrepreneurship project

    DEFF Research Database (Denmark)

    Lund, Morten; Nielsen, Christian

    2014-01-01

    : This paper illustrates how a network-based business model arises and evolves and how the forces of a network structure impact the development of its partner relationships. The contribution of this article is to understanding how partners positioned around a business model can be organized into a network......-based business model that generates additional value for the core business model and for both the partners and the customers. Research limitations/implications: The results should be taken with caution as they are based on the case study of a single network-based business model. Practical implications: Managers......’s strategic partners and how a how a business model can evolve in a series of distinct phases...

  20. Evolution of cooperation on stochastic dynamical networks.

    Directory of Open Access Journals (Sweden)

    Bin Wu

    Full Text Available Cooperative behavior that increases the fitness of others at a cost to oneself can be promoted by natural selection only in the presence of an additional mechanism. One such mechanism is based on population structure, which can lead to clustering of cooperating agents. Recently, the focus has turned to complex dynamical population structures such as social networks, where the nodes represent individuals and links represent social relationships. We investigate how the dynamics of a social network can change the level of cooperation in the network. Individuals either update their strategies by imitating their partners or adjust their social ties. For the dynamics of the network structure, a random link is selected and breaks with a probability determined by the adjacent individuals. Once it is broken, a new one is established. This linking dynamics can be conveniently characterized by a Markov chain in the configuration space of an ever-changing network of interacting agents. Our model can be analytically solved provided the dynamics of links proceeds much faster than the dynamics of strategies. This leads to a simple rule for the evolution of cooperation: The more fragile links between cooperating players and non-cooperating players are (or the more robust links between cooperators are, the more likely cooperation prevails. Our approach may pave the way for analytically investigating coevolution of strategy and structure.

  1. Evolution of a modular software network.

    Science.gov (United States)

    Fortuna, Miguel A; Bonachela, Juan A; Levin, Simon A

    2011-12-13

    "Evolution behaves like a tinkerer" (François Jacob, Science, 1977). Software systems provide a singular opportunity to understand biological processes using concepts from network theory. The Debian GNU/Linux operating system allows us to explore the evolution of a complex network in a unique way. The modular design detected during its growth is based on the reuse of existing code in order to minimize costs during programming. The increase of modularity experienced by the system over time has not counterbalanced the increase in incompatibilities between software packages within modules. This negative effect is far from being a failure of design. A random process of package installation shows that the higher the modularity, the larger the fraction of packages working properly in a local computer. The decrease in the relative number of conflicts between packages from different modules avoids a failure in the functionality of one package spreading throughout the entire system. Some potential analogies with the evolutionary and ecological processes determining the structure of ecological networks of interacting species are discussed.

  2. Cross-linked structure of network evolution

    Science.gov (United States)

    Bassett, Danielle S.; Wymbs, Nicholas F.; Porter, Mason A.; Mucha, Peter J.; Grafton, Scott T.

    2014-03-01

    We study the temporal co-variation of network co-evolution via the cross-link structure of networks, for which we take advantage of the formalism of hypergraphs to map cross-link structures back to network nodes. We investigate two sets of temporal network data in detail. In a network of coupled nonlinear oscillators, hyperedges that consist of network edges with temporally co-varying weights uncover the driving co-evolution patterns of edge weight dynamics both within and between oscillator communities. In the human brain, networks that represent temporal changes in brain activity during learning exhibit early co-evolution that then settles down with practice. Subsequent decreases in hyperedge size are consistent with emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. Our results on real and synthetic networks give a poignant demonstration of the ability of cross-link structure to uncover unexpected co-evolution attributes in both real and synthetic dynamical systems. This, in turn, illustrates the utility of analyzing cross-links for investigating the structure of temporal networks.

  3. Cross-linked structure of network evolution

    Energy Technology Data Exchange (ETDEWEB)

    Bassett, Danielle S., E-mail: dsb@seas.upenn.edu [Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States); Department of Physics, University of California, Santa Barbara, California 93106 (United States); Sage Center for the Study of the Mind, University of California, Santa Barbara, California 93106 (United States); Wymbs, Nicholas F.; Grafton, Scott T. [Department of Psychology and UCSB Brain Imaging Center, University of California, Santa Barbara, California 93106 (United States); Porter, Mason A. [Oxford Centre for Industrial and Applied Mathematics, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); CABDyN Complexity Centre, University of Oxford, Oxford, OX1 1HP (United Kingdom); Mucha, Peter J. [Carolina Center for Interdisciplinary Applied Mathematics, Department of Mathematics, University of North Carolina, Chapel Hill, North Carolina 27599 (United States); Department of Applied Physical Sciences, University of North Carolina, Chapel Hill, North Carolina 27599 (United States)

    2014-03-15

    We study the temporal co-variation of network co-evolution via the cross-link structure of networks, for which we take advantage of the formalism of hypergraphs to map cross-link structures back to network nodes. We investigate two sets of temporal network data in detail. In a network of coupled nonlinear oscillators, hyperedges that consist of network edges with temporally co-varying weights uncover the driving co-evolution patterns of edge weight dynamics both within and between oscillator communities. In the human brain, networks that represent temporal changes in brain activity during learning exhibit early co-evolution that then settles down with practice. Subsequent decreases in hyperedge size are consistent with emergence of an autonomous subgraph whose dynamics no longer depends on other parts of the network. Our results on real and synthetic networks give a poignant demonstration of the ability of cross-link structure to uncover unexpected co-evolution attributes in both real and synthetic dynamical systems. This, in turn, illustrates the utility of analyzing cross-links for investigating the structure of temporal networks.

  4. Modeling Network Evolution Using Graph Motifs

    CERN Document Server

    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 ...

  5. Community evolution mining and analysis in social network

    Science.gov (United States)

    Liu, Hongtao; Tian, Yuan; Liu, Xueyan; Jian, Jie

    2017-03-01

    With the development of digital and network technology, various social platforms emerge. These social platforms have greatly facilitated access to information, attracting more and more users. They use these social platforms every day to work, study and communicate, so every moment social platforms are generating massive amounts of data. These data can often be modeled as complex networks, making large-scale social network analysis possible. In this paper, the existing evolution classification model of community has been improved based on community evolution relationship over time in dynamic social network, and the Evolution-Tree structure is proposed which can show the whole life cycle of the community more clearly. The comparative test result shows that the improved model can excavate the evolution relationship of the community well.

  6. 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.

  7. Evolution of Heterogeneous Wireless Networks

    DEFF Research Database (Denmark)

    Zhang, Q.; Fitzek, Frank; Katz, Marcos

    2006-01-01

    Mobile and wireless content, services and networks - Short-term and long-term development trends......Mobile and wireless content, services and networks - Short-term and long-term development trends...

  8. 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.

  9. Social network analysis community detection and evolution

    CERN Document Server

    Missaoui, Rokia

    2015-01-01

    This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edit

  10. Nation-Wide Mobile Network Energy Evolution Analysis

    DEFF Research Database (Denmark)

    Perez, Eva; Frank, Philipp; Micallef, Gilbert

    2013-01-01

    Mobile network operators are facing a challenging dilemma. While on the one hand they are committed to reducing their carbon emissions, and energy consumption, they are also required to continuously upgrade existing networks, ensuring that the relentless growth in data traffic can still be suppor...... is expected to evolve from 2012 until 2020. The study also considers an efficient network capacity evolution path, including base station equipment improvement forecasts....

  11. Evolution of Cooperation on Temporal Networks

    CERN Document Server

    Li, Aming; Su, Qi; Cornelius, Sean P; Liu, Yang-Yu; Wang, Long

    2016-01-01

    The structure of social networks is a key determinant in fostering cooperation and other altruistic behavior among naturally selfish individuals. However, most real social interactions are temporal, being both finite in duration and spread out over time. This raises the question of whether stable cooperation can form despite an intrinsically fragmented social fabric. Here we develop a framework to study the evolution of cooperation on temporal networks in the setting of the classic Prisoner's Dilemma. By analyzing both real and synthetic datasets, we find that temporal networks generally facilitate the evolution of cooperation compared to their static counterparts. More interestingly, we find that the intrinsic human interactive pattern like bursty behavior impedes the evolution of cooperation. Finally, we introduce a measure to quantify the temporality present in networks and demonstrate that there is an intermediate level of temporality that boosts cooperation most. Our results open a new avenue for investi...

  12. Genetic Regulatory Networks in Embryogenesis and Evolution

    Science.gov (United States)

    1998-01-01

    The article introduces a series of papers that were originally presented at a workshop titled Genetic Regulatory Network in Embryogenesis and Evaluation. Contents include the following: evolution of cleavage programs in relationship to axial specification and body plan evolution, changes in cell lineage specification elucidate evolutionary relations in spiralia, axial patterning in the leech: developmental mechanisms and evolutionary implications, hox genes in arthropod development and evolution, heterochronic genes in development and evolution, a common theme for LIM homeobox gene function across phylogeny, and mechanisms of specification in ascidian embryos.

  13. The Evolution of Network-based Business Models Illustrated Through the Case Study of an Entrepreneurship Project

    Directory of Open Access Journals (Sweden)

    Morten Lund

    2014-08-01

    Full Text Available Purpose: Existing frameworks for understanding and analyzing the value configuration and structuring of partnerships in relation such network-based business models are found to be inferior. The purpose of this paper is therefore to broaden our understanding of how business models may change over time and how the role of strategic partners may differ over time too. Design/methodology/approach: A longitudinal case study spanning over years and mobilising multiple qualitative methods such as interviews, observation and participative observation forms the basis of the data collection. Findings: This paper illustrates how a network-based business model arises and evolves and how the forces of a network structure impact the development of its partner relationships. The contribution of this article is to understanding how partners positioned around a business model can be organized into a network-based business model that generates additional value for the core business model and for both the partners and the customers. Research limitations/implications: The results should be taken with caution as they are based on the case study of a single network-based business model. Practical implications: Managers can gain insight into barriers and enablers relating to different types of loose organisations and how to best manage such relationships and interactions Originality/value: This study adds value to the existing literature by reflecting the dynamics created in the interactions between a business model’s strategic partners and how a how a business model can evolve in a series of distinct phases

  14. Study on Reverse Reconstruction Method of Vehicle Group Situation in Urban Road Network Based on Driver-Vehicle Feature Evolution

    Directory of Open Access Journals (Sweden)

    Xiaoyuan Wang

    2017-01-01

    Full Text Available Vehicle group situation is the status and situation of dynamic permutation which is composed of target vehicle and neighboring traffic entities. It is a concept which is frequently involved in the research of traffic flow theory, especially the active vehicle security. Studying vehicle group situation in depth is of great significance for traffic safety. Three-lane condition was taken as an example; the characteristics of target vehicle and its neighboring vehicles were synthetically considered to restructure the vehicle group situation in this paper. The Gamma distribution theory was used to identify the vehicle group situation when target vehicle arrived at the end of the study area. From the perspective of driver-vehicle feature evolution, the reverse reconstruction method of vehicle group situation in the urban road network was proposed. Results of actual driving, virtual driving, and simulation experiments showed that the model established in this paper was reasonable and feasible.

  15. Semigroup methods for evolution equations on networks

    CERN Document Server

    Mugnolo, Delio

    2014-01-01

    This concise text is based on a series of lectures held only a few years ago and originally intended as an introduction to known results on linear hyperbolic and parabolic equations.  Yet the topic of differential equations on graphs, ramified spaces, and more general network-like objects has recently gained significant momentum and, well beyond the confines of mathematics, there is a lively interdisciplinary discourse on all aspects of so-called complex networks. Such network-like structures can be found in virtually all branches of science, engineering and the humanities, and future research thus calls for solid theoretical foundations.      This book is specifically devoted to the study of evolution equations – i.e., of time-dependent differential equations such as the heat equation, the wave equation, or the Schrödinger equation (quantum graphs) – bearing in mind that the majority of the literature in the last ten years on the subject of differential equations of graphs has been devoted to ellip...

  16. Evolution of Linux operating system network

    Science.gov (United States)

    Xiao, Guanping; Zheng, Zheng; Wang, Haoqin

    2017-01-01

    Linux operating system (LOS) is a sophisticated man-made system and one of the most ubiquitous operating systems. However, there is little research on the structure and functionality evolution of LOS from the prospective of networks. In this paper, we investigate the evolution of the LOS network. 62 major releases of LOS ranging from versions 1.0 to 4.1 are modeled as directed networks in which functions are denoted by nodes and function calls are denoted by edges. It is found that the size of the LOS network grows almost linearly, while clustering coefficient monotonically decays. The degree distributions are almost the same: the out-degree follows an exponential distribution while both in-degree and undirected degree follow power-law distributions. We further explore the functionality evolution of the LOS network. It is observed that the evolution of functional modules is shown as a sequence of seven events (changes) succeeding each other, including continuing, growth, contraction, birth, splitting, death and merging events. By means of a statistical analysis of these events in the top 4 largest components (i.e., arch, drivers, fs and net), it is shown that continuing, growth and contraction events occupy more than 95% events. Our work exemplifies a better understanding and describing of the dynamics of LOS evolution.

  17. Network evolution of body plans.

    Directory of Open Access Journals (Sweden)

    Koichi Fujimoto

    Full Text Available One of the major goals in evolutionary developmental biology is to understand the relationship between gene regulatory networks and the diverse morphologies and their functionalities. Are the diversities solely triggered by random events, or are they inevitable outcomes of an interplay between evolving gene networks and natural selection? Segmentation in arthropod embryogenesis represents a well-known example of body plan diversity. Striped patterns of gene expression that lead to the future body segments appear simultaneously or sequentially in long and short germ-band development, respectively. Moreover, a combination of both is found in intermediate germ-band development. Regulatory genes relevant for stripe formation are evolutionarily conserved among arthropods, therefore the differences in the observed traits are thought to have originated from how the genes are wired. To reveal the basic differences in the network structure, we have numerically evolved hundreds of gene regulatory networks that produce striped patterns of gene expression. By analyzing the topologies of the generated networks, we show that the characteristics of stripe formation in long and short germ-band development are determined by Feed-Forward Loops (FFLs and negative Feed-Back Loops (FBLs respectively, and those of intermediate germ-band development are determined by the interconnections between FFL and negative FBL. Network architectures, gene expression patterns and knockout responses exhibited by the artificially evolved networks agree with those reported in the fly Drosophila melanogaster and the beetle Tribolium castaneum. For other arthropod species, principal network architectures that remain largely unknown are predicted. Our results suggest that the emergence of the three modes of body segmentation in arthropods is an inherent property of the evolving networks.

  18. Evolution of evolvability in gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Anton Crombach

    Full Text Available Gene regulatory networks are perhaps the most important organizational level in the cell where signals from the cell state and the outside environment are integrated in terms of activation and inhibition of genes. For the last decade, the study of such networks has been fueled by large-scale experiments and renewed attention from the theoretical field. Different models have been proposed to, for instance, investigate expression dynamics, explain the network topology we observe in bacteria and yeast, and for the analysis of evolvability and robustness of such networks. Yet how these gene regulatory networks evolve and become evolvable remains an open question. An individual-oriented evolutionary model is used to shed light on this matter. Each individual has a genome from which its gene regulatory network is derived. Mutations, such as gene duplications and deletions, alter the genome, while the resulting network determines the gene expression pattern and hence fitness. With this protocol we let a population of individuals evolve under Darwinian selection in an environment that changes through time. Our work demonstrates that long-term evolution of complex gene regulatory networks in a changing environment can lead to a striking increase in the efficiency of generating beneficial mutations. We show that the population evolves towards genotype-phenotype mappings that allow for an orchestrated network-wide change in the gene expression pattern, requiring only a few specific gene indels. The genes involved are hubs of the networks, or directly influencing the hubs. Moreover, throughout the evolutionary trajectory the networks maintain their mutational robustness. In other words, evolution in an alternating environment leads to a network that is sensitive to a small class of beneficial mutations, while the majority of mutations remain neutral: an example of evolution of evolvability.

  19. Artificial Neural Networks, Symmetries and Differential Evolution

    CERN Document Server

    Urfalioglu, Onay

    2010-01-01

    Neuroevolution is an active and growing research field, especially in times of increasingly parallel computing architectures. Learning methods for Artificial Neural Networks (ANN) can be divided into two groups. Neuroevolution is mainly based on Monte-Carlo techniques and belongs to the group of global search methods, whereas other methods such as backpropagation belong to the group of local search methods. ANN's comprise important symmetry properties, which can influence Monte-Carlo methods. On the other hand, local search methods are generally unaffected by these symmetries. In the literature, dealing with the symmetries is generally reported as being not effective or even yielding inferior results. In this paper, we introduce the so called Minimum Global Optimum Proximity principle derived from theoretical considerations for effective symmetry breaking, applied to offline supervised learning. Using Differential Evolution (DE), which is a popular and robust evolutionary global optimization method, we experi...

  20. Evolution of Force Networks in Dense Particulate Media

    CERN Document Server

    Kramar, Miroslav; Kondic, Lou; Mischaikow, Konstantin

    2014-01-01

    We introduce novel sets of measures with the goal of describing dynamical properties of force networks in dense particulate systems. The presented approach is based on persistent homology and allows for extracting precise, quantitative measures that describe the evolution of geometric features of the interparticle forces, without necessarily considering the details related to individual contacts between particles. The networks considered emerge from discrete element simulations of two dimensional particulate systems consisting of compressible frictional circular disks. We quantify the evolution of the networks for slowly compressed systems undergoing jamming transition. The main findings include uncovering significant but localized changes of force networks for unjammed systems, global (system-wide) changes as the systems evolve through jamming, to be followed by significantly less dramatic evolution for the jammed states. We consider both connected components, related in loose sense to force chains, and loop...

  1. Evolution of Scientific Collaboration Network Driven by Homophily and Heterophily

    CERN Document Server

    Liu, Peng; Xia, Haoxiang

    2015-01-01

    Many scientific collaboration networks exhibit clear community and small world structures. However, the studies on the underlying mechanisms for the formation and evolution of community and small world structures are still insufficient. The mechanisms of homophily and heterophily based on scholars' traits are two important factors for the formation of community and inter-communal links, which may deserve further exploration. In this paper, a multi-agent model, which is based on combinatorial effects of homophily and heterophily, is developed to investigate the evolution of scientific collaboration networks. The simulation results indicate that agents with similar traits aggregate to form community by homophily, while heterophily plays a major role in the formation of inter-communal links. The pattern of network evolution revealed in simulations is essentially consistent with what is observed in empirical analyses, as in both cases the giant component evolves from a small cluster to a structure of chained-comm...

  2. Neural network models of protein domain evolution

    OpenAIRE

    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...

  3. Radical Innovation and Network Evolution

    NARCIS (Netherlands)

    S.M.W. Phlippen (Sandra); M. Riccaboni

    2007-01-01

    textabstractThis paper examines how a radical technological innovation affects alliance formation of firms and subsequent network structures. We use longitudinal data of interfirm R&D collaborations in the biopharmaceutical industry in which a new technological regime is established. Our findings su

  4. A mixing evolution model for bidirectional microblog user networks

    Science.gov (United States)

    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.

  5. Energy Efficient Evolution of Mobile Networks

    DEFF Research Database (Denmark)

    Micallef, Gilbert; Mogensen, Preben

    2011-01-01

    in understanding the impact that different options can have on the energy consumption of their networks. This paper investigates the possible energy gains of evolving a mobile network through a joint pico deployment and macro upgrade solution over a period of 8 years. Besides the network energy consumption, energy...... efficiency in Mbps/kWh is also analyzed. Furthermore, a cost analysis is carried out, to give a more complete picture of the different options being considered. Focusing on the last year of the evolution analysis, results show that deploying more pico sites reduces the energy consumption of the network......, by a maximum of 30%. With regards to the energy efficiency, high deployment of pico sites allowed the network to carry 16% more traffic for the same amount of energy. This, however, results in an increase in cost, specifically operational costs....

  6. ATHENA: A knowledge-based hybrid backpropagation-grammatical evolution neural network algorithm for discovering epistasis among quantitative trait Loci

    Directory of Open Access Journals (Sweden)

    Turner Stephen D

    2010-09-01

    Full Text Available Abstract Background Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritability in highly studied complex traits has been explained by genetic variation. Non-additive gene-gene interactions, which are not often explored, are thought to be one source of this "missing" heritability. Methods Stochastic methods employing evolutionary algorithms have demonstrated promise in being able to detect and model gene-gene and gene-environment interactions that influence human traits. Here we demonstrate modifications to a neural network algorithm in ATHENA (the Analysis Tool for Heritable and Environmental Network Associations resulting in clear performance improvements for discovering gene-gene interactions that influence human traits. We employed an alternative tree-based crossover, backpropagation for locally fitting neural network weights, and incorporation of domain knowledge obtainable from publicly accessible biological databases for initializing the search for gene-gene interactions. We tested these modifications in silico using simulated datasets. Results We show that the alternative tree-based crossover modification resulted in a modest increase in the sensitivity of the ATHENA algorithm for discovering gene-gene interactions. The performance increase was highly statistically significant when backpropagation was used to locally fit NN weights. We also demonstrate that using domain knowledge to initialize the search for gene-gene interactions results in a large performance increase, especially when the search space is larger than the search coverage. Conclusions We show that a hybrid optimization procedure, alternative crossover strategies, and incorporation of domain knowledge from publicly available biological databases can result in marked increases in sensitivity and performance of the ATHENA

  7. Analyzing complex networks evolution through Information Theory quantifiers

    Energy Technology Data Exchange (ETDEWEB)

    Carpi, Laura C., E-mail: Laura.Carpi@studentmail.newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Rosso, Osvaldo A., E-mail: rosso@fisica.ufmg.b [Departamento de Fisica, Instituto de Ciencias Exatas, Universidade Federal de Minas Gerais, Av. Antonio Carlos 6627, Belo Horizonte (31270-901), MG (Brazil); Chaos and Biology Group, Instituto de Calculo, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellon II, Ciudad Universitaria, 1428 Ciudad de Buenos Aires (Argentina); Saco, Patricia M., E-mail: Patricia.Saco@newcastle.edu.a [Civil, Surveying and Environmental Engineering, University of Newcastle, University Drive, Callaghan NSW 2308 (Australia); Departamento de Hidraulica, Facultad de Ciencias Exactas, Ingenieria y Agrimensura, Universidad Nacional de Rosario, Avenida Pellegrini 250, Rosario (Argentina); Ravetti, Martin Gomez, E-mail: martin.ravetti@dep.ufmg.b [Departamento de Engenharia de Producao, Universidade Federal de Minas Gerais, Av. Antonio Carlos, 6627, Belo Horizonte (31270-901), MG (Brazil)

    2011-01-24

    A methodology to analyze dynamical changes in complex networks based on Information Theory quantifiers is proposed. The square root of the Jensen-Shannon divergence, a measure of dissimilarity between two probability distributions, and the MPR Statistical Complexity are used to quantify states in the network evolution process. Three cases are analyzed, the Watts-Strogatz model, a gene network during the progression of Alzheimer's disease and a climate network for the Tropical Pacific region to study the El Nino/Southern Oscillation (ENSO) dynamic. We find that the proposed quantifiers are able not only to capture changes in the dynamics of the processes but also to quantify and compare states in their evolution.

  8. Discriminating micropathogen lineages and their reticulate evolution through graph theory-based network analysis: the case of Trypanosoma cruzi, the agent of Chagas disease.

    Science.gov (United States)

    Arnaud-Haond, Sophie; Moalic, Yann; Barnabé, Christian; Ayala, Francisco José; Tibayrenc, Michel

    2014-01-01

    Micropathogens (viruses, bacteria, fungi, parasitic protozoa) share a common trait, which is partial clonality, with wide variance in the respective influence of clonality and sexual recombination on the dynamics and evolution of taxa. The discrimination of distinct lineages and the reconstruction of their phylogenetic history are key information to infer their biomedical properties. However, the phylogenetic picture is often clouded by occasional events of recombination across divergent lineages, limiting the relevance of classical phylogenetic analysis and dichotomic trees. We have applied a network analysis based on graph theory to illustrate the relationships among genotypes of Trypanosoma cruzi, the parasitic protozoan responsible for Chagas disease, to identify major lineages and to unravel their past history of divergence and possible recombination events. At the scale of T. cruzi subspecific diversity, graph theory-based networks applied to 22 isoenzyme loci (262 distinct Multi-Locus-Enzyme-Electrophoresis -MLEE) and 19 microsatellite loci (66 Multi-Locus-Genotypes -MLG) fully confirms the high clustering of genotypes into major lineages or "near-clades". The release of the dichotomic constraint associated with phylogenetic reconstruction usually applied to Multilocus data allows identifying putative hybrids and their parental lineages. Reticulate topology suggests a slightly different history for some of the main "near-clades", and a possibly more complex origin for the putative hybrids than hitherto proposed. Finally the sub-network of the near-clade T. cruzi I (28 MLG) shows a clustering subdivision into three differentiated lesser near-clades ("Russian doll pattern"), which confirms the hypothesis recently proposed by other investigators. The present study broadens and clarifies the hypotheses previously obtained from classical markers on the same sets of data, which demonstrates the added value of this approach. This underlines the potential of graph

  9. 基于网络演化方法的城市群城际铁路线网规划模型研究%Network Evolution-based Planning Model for Intercity Railway Network within Urban Agglomeration

    Institute of Scientific and Technical Information of China (English)

    黄超; 刘苏; 吕颖

    2016-01-01

    Intercity railway network plays an important role in the integration of urban agglomeration, and reasonable planning is of great significance on the basis of urban agglomeration spatial structure. This paper, based on network evolution, takes node importance and economic contact intensity as major parameters of network evolution, and a planning model of the intercity railway network of urban agglomeration is constructed, under the comprehensive consideration of social economy of the specific urban agglomeration. With the analysis of technical performance and constraints of the intercity railway network, evolution mechanism and evolution algorithm are present. At last, the Chengdu-Chongqing urban agglomeration is taken as a case to validate the planning model. The result shows that this model is reasonable and efficient, and provides an important guidance on the intercity railway network planning.%城际铁路网络在城市群一体化发展中发挥着重要作用,在城市群空间结构的基础上进行合理规划意义重大。本文基于网络演化思想,将节点重要度和城市经济联系强度指标作为重要参数,在综合考虑城市群社会经济影响的基础上,构建城市群城际铁路线网布局规划模型,并对城际铁路线网的技术性能和约束条件进行分析,提出节点成长、线路连接、边权演化规则,设计网络演化机制和城际铁路网络演化算法。以成渝城市群为对象进行实证分析,得到不同参数组合下的演化结果和城际铁路线网规划方案,验证了模型的合理性和适用性,对实际城市群城际铁路线网规划工作有一定的参考价值。

  10. Spectral properties of the temporal evolution of brain network structure

    Science.gov (United States)

    Wang, Rong; Zhang, Zhen-Zhen; Ma, Jun; Yang, Yong; Lin, Pan; Wu, Ying

    2015-12-01

    The temporal evolution properties of the brain network are crucial for complex brain processes. In this paper, we investigate the differences in the dynamic brain network during resting and visual stimulation states in a task-positive subnetwork, task-negative subnetwork, and whole-brain network. The dynamic brain network is first constructed from human functional magnetic resonance imaging data based on the sliding window method, and then the eigenvalues corresponding to the network are calculated. We use eigenvalue analysis to analyze the global properties of eigenvalues and the random matrix theory (RMT) method to measure the local properties. For global properties, the shifting of the eigenvalue distribution and the decrease in the largest eigenvalue are linked to visual stimulation in all networks. For local properties, the short-range correlation in eigenvalues as measured by the nearest neighbor spacing distribution is not always sensitive to visual stimulation. However, the long-range correlation in eigenvalues as evaluated by spectral rigidity and number variance not only predicts the universal behavior of the dynamic brain network but also suggests non-consistent changes in different networks. These results demonstrate that the dynamic brain network is more random for the task-positive subnetwork and whole-brain network under visual stimulation but is more regular for the task-negative subnetwork. Our findings provide deeper insight into the importance of spectral properties in the functional brain network, especially the incomparable role of RMT in revealing the intrinsic properties of complex systems.

  11. A model for evolution of overlapping community networks

    Science.gov (United States)

    Karan, Rituraj; Biswal, Bibhu

    2017-05-01

    A model is proposed for the evolution of network topology in social networks with overlapping community structure. Starting from an initial community structure that is defined in terms of group affiliations, the model postulates that the subsequent growth and loss of connections is similar to the Hebbian learning and unlearning in the brain and is governed by two dominant factors: the strength and frequency of interaction between the members, and the degree of overlap between different communities. The temporal evolution from an initial community structure to the current network topology can be described based on these two parameters. It is possible to quantify the growth occurred so far and predict the final stationary state to which the network is likely to evolve. Applications in epidemiology or the spread of email virus in a computer network as well as finding specific target nodes to control it are envisaged. While facing the challenge of collecting and analyzing large-scale time-resolved data on social groups and communities one faces the most basic questions: how do communities evolve in time? This work aims to address this issue by developing a mathematical model for the evolution of community networks and studying it through computer simulation.

  12. 基于复杂网络演化模型的三元闭环合著网络研究%A Research of Triadic Closure in Coauthorship Network Based on Evolution Model of Complex Network

    Institute of Scientific and Technical Information of China (English)

    张洋; 麦江萌

    2015-01-01

    The concepts of Strictly Triadic Closure and Expanding Coefficient were proposed in the research of Coauthership network expansion,based on the analysis of current Library & information science Coauthership network and an optimized evolution model of Complex Network. It is proven that the expansion of a scholar’ s coauthorship clique is positively correlated with the homogeneous degree of his/her coauthoring with other scholars. Expanding Coefficient is considered as a useful supplementary index to the evaluation of Coauthorship network.%本文通过构建和分析国外图书情报领域的三元闭环合著网络,改进已有的复杂网络演化模型,提出严格三元闭环概念和扩张系数用以研究影响合著网络扩张速度的关键因素。研究表明,学者合著集群的扩张速度,与他跟集群成员合著的均匀程度成正相关关系。扩张系数是对目前合著网络测度指标的一个有效补充。

  13. Evolution of Wireless Sensor Networks for Industrial Control

    Directory of Open Access Journals (Sweden)

    Arthur Low

    2013-05-01

    Full Text Available Technologies evolve in a process of gradual scientific change, but the commercial application of technologies is discontinuous. Managers interested in technology evolution can integrate these contrasting ideas using a powerful theoretical framework, based on the concept of punctuated equilibrium from evolutionary biology. The framework, which enables the differentiation of the technical evolution of a technology from its market application, is used in this article to compare the two standards for wireless sensor networks (WSN for industrial instrumentation and control: WirelessHART and ISA100.11a. The two WSN standards are the product of two different market contexts, which have selected different minimum viable technologies for evolution in their respective niches. Network security issues present some important selection criteria. Both WSN standards implement security countermeasures against localized wireless network attacks based on the application of the AES encryption standard, but some specific security threats – some local, others remotely launched – are only well-defended by the adoption of public-key cryptographic (PKC protocols, which only ISA100.11a supports. This article concludes that the mainstream market potential of the Internet has influenced the evolution of ISA100.11a and will continue to demand that each WSN standard evolve in ways that are difficult to predict.

  14. Swarm-Evolution-based Reputation Model for Peer-to-Peer Networks%对等网中基于种群进化的信誉模型

    Institute of Scientific and Technical Information of China (English)

    鲍翊平; 姚莉; 张维明; 唐九阳

    2011-01-01

    信誉系统是应对对等网信任危机的关键途径.提出了一种新的基于种群进化的信誉模型.该模型将对等网视为社会生态系统,将节点的信誉评估过程模型化为一种进化过程,通过引入交叉和变异,节点能快速有效地评估潜在交易对象的信任度,从而最终提高其网络适应能力.通过仿真对模型进行了验证.%Reputation system is the key approach to fight against the trust crisis of Peer-to-Peer networks. A novel reputation model based on swarm evolution was proposed in this article. In the model, the Peer-to-Peer network is viewed as social ecosystem, the process of reputation evaluation is modeled as an evolutionary process for peers. By using the strategy of crossover and selection, the peers can rapidly and efficiently evaluate the trust value of potential partners,and finally improve the ability of their fitness. In order for verifying its performance, a simulation experiment for this model was also provided.

  15. The evolution of communities in the international oil trade network

    Science.gov (United States)

    Zhong, Weiqiong; An, Haizhong; Gao, Xiangyun; Sun, Xiaoqi

    2014-11-01

    International oil trade is a subset of global trade and there exist oil trade communities. These communities evolve over time and provide clues of international oil trade patterns. A better understanding of the international oil trade patterns is necessary for governments in policy making. To study the evolution of trade communities in the international oil trade network, we set up unweighted and weighted oil trade network models based on complex network theory using data from 2002 to 2011. We detected the communities in the oil trade networks and analyzed their evolutionary properties and stabilities over time. We found that the unweighted and weighted international oil trade networks show many different features in terms of community number, community scale, distribution of countries, quality of partitions, and stability of communities. Two turning points occurred in the evolution of community stability in the international oil trade network. One is the year 2004-2005 which correlates with changes in demand and supply in the world oil market after the Iraq War, and the other is the year 2008-2009 which is connected to the 2008 financial crisis. Different causations of instability show different features and this should be considered by policy makers.

  16. Bursty egocentric network evolution in Skype

    CERN Document Server

    Kikas, Riivo; Karsai, Márton

    2013-01-01

    In this study we analyze the dynamics of the contact list evolution of millions of users of the Skype communication network. We find that egocentric networks evolve heterogeneously in time as events of edge additions and deletions of individuals are grouped in long bursty clusters, which are separated by long inactive periods. We classify users by their link creation dynamics and show that bursty peaks of contact additions are likely to appear shortly after user account creation. We also study possible relations between bursty contact addition activity and other user-initiated actions like free and paid service adoption events. We show that bursts of contact additions are associated with increases in activity and adoption - an observation that can inform the design of targeted marketing tactics.

  17. The Asymptotic Mandelbrot Law of Some Evolution Networks

    CERN Document Server

    Li, Li

    2011-01-01

    In this letter, we study some evolution networks that grow with linear preferential attachment. Based upon some recent results on the quotient Gamma function, we give a rigorous proof of the asymptotic Mandelbrot law for the degree distribution $p_k \\propto (k + c)^{-\\gamma}$ in certain conditions. We also analytically derive the best fitting values for the scaling exponent $\\gamma$ and the shifting coefficient $c$.

  18. Functional organization and its implication in evolution of the human protein-protein interaction network

    Directory of Open Access Journals (Sweden)

    Zhao Yiqiang

    2012-04-01

    Full Text Available Abstract Background Based on the distinguishing properties of protein-protein interaction networks such as power-law degree distribution and modularity structure, several stochastic models for the evolution of these networks have been purposed, motivated by the idea that a validated model should reproduce similar topological properties of the empirical network. However, being able to capture topological properties does not necessarily mean it correctly reproduces how networks emerge and evolve. More importantly, there is already evidence suggesting functional organization and significance of these networks. The current stochastic models of evolution, however, grow the network without consideration for biological function and natural selection. Results To test whether protein interaction networks are functionally organized and their impacts on the evolution of these networks, we analyzed their evolution at both the topological and functional level. We find that the human network is shown to be functionally organized, and its function evolves with the topological properties of the network. Our analysis suggests that function most likely affects local modularity of the network. Consistently, we further found that the topological unit is also the functional unit of the network. Conclusion We have demonstrated functional organization of a protein interaction network. Given our observations, we suggest that its significance should not be overlooked when studying network evolution.

  19. Exploring the evolution of node neighborhoods in Dynamic Networks

    Science.gov (United States)

    Orman, Günce Keziban; Labatut, Vincent; Naskali, Ahmet Teoman

    2017-09-01

    Dynamic Networks are a popular way of modeling and studying the behavior of evolving systems. However, their analysis constitutes a relatively recent subfield of Network Science, and the number of available tools is consequently much smaller than for static networks. In this work, we propose a method specifically designed to take advantage of the longitudinal nature of dynamic networks. It characterizes each individual node by studying the evolution of its direct neighborhood, based on the assumption that the way this neighborhood changes reflects the role and position of the node in the whole network. For this purpose, we define the concept of neighborhood event, which corresponds to the various transformations such groups of nodes can undergo, and describe an algorithm for detecting such events. We demonstrate the interest of our method on three real-world networks: DBLP, LastFM and Enron. We apply frequent pattern mining to extract meaningful information from temporal sequences of neighborhood events. This results in the identification of behavioral trends emerging in the whole network, as well as the individual characterization of specific nodes. We also perform a cluster analysis, which reveals that, in all three networks, one can distinguish two types of nodes exhibiting different behaviors: a very small group of active nodes, whose neighborhood undergo diverse and frequent events, and a very large group of stable nodes.

  20. Pareto evolution of gene networks: an algorithm to optimize multiple fitness objectives.

    Science.gov (United States)

    Warmflash, Aryeh; Francois, Paul; Siggia, Eric D

    2012-10-01

    The computational evolution of gene networks functions like a forward genetic screen to generate, without preconceptions, all networks that can be assembled from a defined list of parts to implement a given function. Frequently networks are subject to multiple design criteria that cannot all be optimized simultaneously. To explore how these tradeoffs interact with evolution, we implement Pareto optimization in the context of gene network evolution. In response to a temporal pulse of a signal, we evolve networks whose output turns on slowly after the pulse begins, and shuts down rapidly when the pulse terminates. The best performing networks under our conditions do not fall into categories such as feed forward and negative feedback that also encode the input-output relation we used for selection. Pareto evolution can more efficiently search the space of networks than optimization based on a single ad hoc combination of the design criteria.

  1. Optimal evolution on random networks: from social to airports networks

    CERN Document Server

    Curty, P

    2005-01-01

    Social movements, neurons in the brain or even industrial suppliers are best described by agents evolving on networks with basic interaction rules. In these real systems, the connectivity between agents corresponds to the most efficient state of the system. The new idea is that connectivity adjusts itself because of two opposite tendencies: information percolation, decision making or coordination are better when the network connectivity is small. When agents have many connections, the opinion of a person or the state of a neuron tend to freeze: agents find always a minority among their advisors to support their opinion. A general and new model reproduces these features showing a clear transition between the two tendencies at some critical connectivity. Depending on the noise, the evolution of the system is optimal at a precise critical connectivity since, away from this critical point, the system always ends up in a static phase. When the error tolerance is very small, the optimal connectivity becomes very la...

  2. Study on the topology evolution modeling of wireless sensor networks based on scale-free network%基于无标度网络的无线传感器网络拓扑演化模型研究

    Institute of Scientific and Technical Information of China (English)

    郑耿忠; 刘三阳; 齐小刚; 郑巍

    2011-01-01

    针对无线传感器网络抗毁性的问题,从复杂网络的视角提出了两个基于无标度网络的无线传感器网络拓扑演化模型.这两个演化模型先借助分簇算法实现传感器簇头的均匀分布,然后按照一定的连接策略,进行簇间的拓扑演化.根据提出的拓扑演化模型,设计了相应的拓扑演化算法,并对拓扑演化模型的动态特性进行了分析.仿真结果表明,由于新模型设计考虑了节点剩余能量、节点饱和度等问题,因此演化而成的网络拓扑更加符合无线传感器网络的实际应用,并且具有很好的抗毁性,进一步提高了网络的鲁棒性.%In view of the survivability of wireless sensor networks ( WSNs) , two topology evolution models for WSNs based on a scale-free network are proposed from the angle of complex networks. The models firstly use a clustering algorithm to achieve the cluster heads, uniform distribution, and then make the topology evolution among cluster heads according to a certain connection strategy. The corresponding topology evolution algorithms are given according to the proposed models, and the dynamic characteristics of the models are analyzed. The simulation results show that the network topologies formed by the new models are more fit for the practical applications of WSNs and have a good survivability, a further improved robustness due to the consideration of the node residual energy and the node saturation when designing the models.

  3. Theory of interface: category theory, directed networks and evolution of biological networks.

    Science.gov (United States)

    Haruna, Taichi

    2013-11-01

    Biological networks have two modes. The first mode is static: a network is a passage on which something flows. The second mode is dynamic: a network is a pattern constructed by gluing functions of entities constituting the network. In this paper, first we discuss that these two modes can be associated with the category theoretic duality (adjunction) and derive a natural network structure (a path notion) for each mode by appealing to the category theoretic universality. The path notion corresponding to the static mode is just the usual directed path. The path notion for the dynamic mode is called lateral path which is the alternating path considered on the set of arcs. Their general functionalities in a network are transport and coherence, respectively. Second, we introduce a betweenness centrality of arcs for each mode and see how the two modes are embedded in various real biological network data. We find that there is a trade-off relationship between the two centralities: if the value of one is large then the value of the other is small. This can be seen as a kind of division of labor in a network into transport on the network and coherence of the network. Finally, we propose an optimization model of networks based on a quality function involving intensities of the two modes in order to see how networks with the above trade-off relationship can emerge through evolution. We show that the trade-off relationship can be observed in the evolved networks only when the dynamic mode is dominant in the quality function by numerical simulations. We also show that the evolved networks have features qualitatively similar to real biological networks by standard complex network analysis.

  4. Gossip Consensus Algorithm Based on Time-Varying Influence Factors and Weakly Connected Graph for Opinion Evolution in Social Networks

    Directory of Open Access Journals (Sweden)

    Lingyun Li

    2013-01-01

    Full Text Available We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. What is more, we discuss not only the effect of the time-varying factors and the randomized topological structure but also the spread of misinformation and communication constrains described by probabilistic quantized communication in the social network. Under the underlying weakly connected graph, we first denote that all opinion states converge to a stochastic consensus almost surely; that is, our algorithm indeed achieves the consensus with probability one. Furthermore, our results show that the mean of all the opinion states converges to the average of the initial states when time-varying influence factors satisfy some conditions. Finally, we give a result about the square mean error between the dynamic opinion states and the benchmark without quantized communication.

  5. Energy Efficient Evolution of Mobile Networks

    DEFF Research Database (Denmark)

    Micallef, Gilbert; Mogensen, Preben

    2011-01-01

    options for how to evolve their networks, allowing them to carry the expected increase in traffic. The best solution is generally selected based on two main criteria, performance and cost. However, pushed by a variety of environmental and energy challenges, MNOs are now also showing interest...

  6. Time evolution of Wikipedia network ranking

    CERN Document Server

    Eom, Young-Ho; Benczúr, András; Shepelyansky, Dima L

    2013-01-01

    We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003 - 2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007 - 2011. A special emphasis is done on ranking of Wikipedia personalities and universities. We show that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts. The Wikipedia PageRank of universities recovers 80 percents of top universities of Shanghai ranking during the considered time period.

  7. Time evolution of Wikipedia network ranking

    Science.gov (United States)

    Eom, Young-Ho; Frahm, Klaus M.; Benczúr, András; Shepelyansky, Dima L.

    2013-12-01

    We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003-2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007-2011. A special emphasis is done on ranking of Wikipedia personalities and universities. We show that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts. The Wikipedia PageRank of universities recovers 80% of top universities of Shanghai ranking during the considered time period.

  8. Evolution of semilocal string networks. II. Velocity estimators

    Science.gov (United States)

    Lopez-Eiguren, A.; Urrestilla, J.; Achúcarro, A.; Avgoustidis, A.; Martins, C. J. A. P.

    2017-07-01

    We continue a comprehensive numerical study of semilocal string networks and their cosmological evolution. These can be thought of as hybrid networks comprised of (nontopological) string segments, whose core structure is similar to that of Abelian Higgs vortices, and whose ends have long-range interactions and behavior similar to that of global monopoles. Our study provides further evidence of a linear scaling regime, already reported in previous studies, for the typical length scale and velocity of the network. We introduce a new algorithm to identify the position of the segment cores. This allows us to determine the length and velocity of each individual segment and follow their evolution in time. We study the statistical distribution of segment lengths and velocities for radiation- and matter-dominated evolution in the regime where the strings are stable. Our segment detection algorithm gives higher length values than previous studies based on indirect detection methods. The statistical distribution shows no evidence of (anti)correlation between the speed and the length of the segments.

  9. Evolution of Cooperation in Social Dilemmas on Complex Networks.

    Science.gov (United States)

    Iyer, Swami; Killingback, Timothy

    2016-02-01

    Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoner's dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games.

  10. Evolution of Cooperation in Social Dilemmas on Complex Networks.

    Directory of Open Access Journals (Sweden)

    Swami Iyer

    2016-02-01

    Full Text Available Cooperation in social dilemmas is essential for the functioning of systems at multiple levels of complexity, from the simplest biological organisms to the most sophisticated human societies. Cooperation, although widespread, is fundamentally challenging to explain evolutionarily, since natural selection typically favors selfish behavior which is not socially optimal. Here we study the evolution of cooperation in three exemplars of key social dilemmas, representing the prisoner's dilemma, hawk-dove and coordination classes of games, in structured populations defined by complex networks. Using individual-based simulations of the games on model and empirical networks, we give a detailed comparative study of the effects of the structural properties of a network, such as its average degree, variance in degree distribution, clustering coefficient, and assortativity coefficient, on the promotion of cooperative behavior in all three classes of games.

  11. An Overview on Wireless Sensor Networks Technology and Evolution

    Directory of Open Access Journals (Sweden)

    Chiara Buratti

    2009-08-01

    Full Text Available Wireless sensor networks (WSNs enable new applications and require non-conventional paradigms for protocol design due to several constraints. Owing to the requirement for low device complexity together with low energy consumption (i.e., long network lifetime, a proper balance between communication and signal/data processing capabilities must be found. This motivates a huge effort in research activities, standardization process, and industrial investments on this field since the last decade. This survey paper aims at reporting an overview of WSNs technologies, main applications and standards, features in WSNs design, and evolutions. In particular, some peculiar applications, such as those based on environmental monitoring, are discussed and design strategies highlighted; a case study based on a real implementation is also reported. Trends and possible evolutions are traced. Emphasis is given to the IEEE 802.15.4 technology, which enables many applications of WSNs. Some example of performance characteristics of 802.15.4-based networks are shown and discussed as a function of the size of the WSN and the data type to be exchanged among nodes.

  12. OLDA-based method for online topic evolution in network public opinion analysis%网络舆情中一种基于OLDA的在线话题演化方法

    Institute of Scientific and Technical Information of China (English)

    胡艳丽; 白亮; 张维明

    2012-01-01

    研究网络舆情分析中话题演化方法.首先分析网络舆情信息的特点;在此基础上,建立网络舆情信息模型,基于话题模型抽象描述文本内容的隐含语义,进而建立文本流在时间序列上的关联模型;进一步,提出基于OLDA的话题演化方法,针对舆情信息的特点,建立不同时间片话题间的关联.实验结果表明,该方法能够有效检测话题演化,为网络舆情分析提供了有效途径.%The topic evolution was investigated for network public opinion analysis. The properties of network public opinion information were analyzed firstly. Based on the properties, the latent semantics of textual data for network public opinion was described by using the topic model, and the text streams are modeled with a consideration of time for online analysis. Furthermore, a topic evolution method based on OLDA was proposed by incorporating the correlation of topics among time slices. The proposed method was experimentally verified to be efficient for detecting topic evolution of network public opinion.

  13. 基于SDN/NFV的核心网演进关键技术研究%Research on Key Technologies of Core Network Evolution Based on SDN/NFV

    Institute of Scientific and Technical Information of China (English)

    薛淼; 符刚; 朱斌; 李勇辉

    2014-01-01

    在NFV和SDN的基础上研究核心网架构的演进及应用领域;通过将NFV和SDN技术引入核心网,在核心网虚拟化,分组域网关控制转发分离及基于Service Chaining的即插即用的增值业务及复杂流处理平台进行研究,建议了基于SDN/NFV的核心网长期演进架构。%It studies the mobile core network evolution and the application based on SDN/NFV. Through bring SDN/NFV to the mobile core network, it researches the core network virtualization, control and forward decouple architecture of mobile core network gate-way and plug and play platform for added value services and complex processing based service chaining. Final y it gives sug-gestions on a long-term evolution architecture of core network based on SDN/NFV.

  14. Dynamic structure evolution of time-dependent network

    Science.gov (United States)

    Zhang, Beibei; Zhou, Yadong; Xu, Xiaoyan; Wang, Dai; Guan, Xiaohong

    2016-08-01

    In this paper, we research the long-voided problem of formulating the time-dependent network structure evolution scheme, it focus not only on finding new emerging vertices in evolving communities and new emerging communities over the specified time range but also formulating the complex network structure evolution schematic. Previous approaches basically applied to community detection on time static networks and thus failed to consider the potentially crucial and useful information latently embedded in the dynamic structure evolution process of time-dependent network. To address these problems and to tackle the network non-scalability dilemma, we propose the dynamic hierarchical method for detecting and revealing structure evolution schematic of the time-dependent network. In practice and specificity, we propose an explicit hierarchical network evolution uncovering algorithm framework originated from and widely expanded from time-dependent and dynamic spectral optimization theory. Our method yields preferable results compared with previous approaches on a vast variety of test network data, including both real on-line networks and computer generated complex networks.

  15. Exploring mitochondrial evolution and metabolism organization principles by comparative analysis of metabolic networks.

    Science.gov (United States)

    Chang, Xiao; Wang, Zhuo; Hao, Pei; Li, Yuan-Yuan; Li, Yi-Xue

    2010-06-01

    The endosymbiotic theory proposed that mitochondrial genomes are derived from an alpha-proteobacterium-like endosymbiont, which was concluded from sequence analysis. We rebuilt the metabolic networks of mitochondria and 22 relative species, and studied the evolution of mitochondrial metabolism at the level of enzyme content and network topology. Our phylogenetic results based on network alignment and motif identification supported the endosymbiotic theory from the point of view of systems biology for the first time. It was found that the mitochondrial metabolic network were much more compact than the relative species, probably related to the higher efficiency of oxidative phosphorylation of the specialized organelle, and the network is highly clustered around the TCA cycle. Moreover, the mitochondrial metabolic network exhibited high functional specificity to the modules. This work provided insight to the understanding of mitochondria evolution, and the organization principle of mitochondrial metabolic network at the network level.

  16. Modeling Temporal Evolution and Multiscale Structure in Networks

    DEFF Research Database (Denmark)

    Herlau, Tue; Mørup, Morten; Schmidt, Mikkel Nørgaard

    2013-01-01

    Many real-world networks exhibit both temporal evolution and multiscale structure. We propose a model for temporally correlated multifurcating hierarchies in complex networks which jointly capture both effects. We use the Gibbs fragmentation tree as prior over multifurcating trees and a change......-point model to account for the temporal evolution of each vertex. We demonstrate that our model is able to infer time-varying multiscale structure in synthetic as well as three real world time-evolving complex networks. Our modeling of the temporal evolution of hierarchies brings new insights...

  17. Predicting the evolution of complex networks via similarity dynamics

    Science.gov (United States)

    Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping

    2017-01-01

    Almost all real-world networks are subject to constant evolution, and plenty of them have been investigated empirically to uncover the underlying evolution mechanism. However, the evolution prediction of dynamic networks still remains a challenging problem. The crux of this matter is to estimate the future network links of dynamic networks. This paper studies the evolution prediction of dynamic networks with link prediction paradigm. To estimate the likelihood of the existence of links more accurate, an effective and robust similarity index is presented by exploiting network structure adaptively. Moreover, most of the existing link prediction methods do not make a clear distinction between future links and missing links. In order to predict the future links, the networks are regarded as dynamic systems in this paper, and a similarity updating method, spatial-temporal position drift model, is developed to simulate the evolutionary dynamics of node similarity. Then the updated similarities are used as input information for the future links' likelihood estimation. Extensive experiments on real-world networks suggest that the proposed similarity index performs better than baseline methods and the position drift model performs well for evolution prediction in real-world evolving networks.

  18. Social Network Analysis Based on Network Motifs

    OpenAIRE

    2014-01-01

    Based on the community structure characteristics, theory, and methods of frequent subgraph mining, network motifs findings are firstly introduced into social network analysis; the tendentiousness evaluation function and the importance evaluation function are proposed for effectiveness assessment. Compared with the traditional way based on nodes centrality degree, the new approach can be used to analyze the properties of social network more fully and judge the roles of the nodes effectively. I...

  19. Evolution of cooperative imitators in social networks

    Science.gov (United States)

    Li, Yixiao

    2017-02-01

    Many evolutionary game models for network reciprocity are based on an imitation dynamics, yet how semirational imitators prevail has seldom been explained. Here we use a model to investigate the coevolutionary dynamics of cooperation and partnership adjustment in a polygenic population of semirational imitators and rational payoff maximizers. A rational individual chooses a strategy best responding to its neighbors when updating strategy and switches to a new partner who can bring it the maximal payoff from all candidates when adjusting the partnership. In contrast, a semirational individual imitates its neighbor's strategy directly and adjusts its partnership based upon a simple reputation rule. Individual-based simulations show that cooperation cannot evolve in a population of all best responders even if they can switch their partners to somebody who can reward them best in game playing. However, when imitators exist, a stable community that consists of cooperative imitators emerges. Further, we show that a birth-death selection mechanism can eliminate all best responders, cultivating a social regime of all cooperative imitators. Compared with parallel simulations that assume fixed networks, cooperative imitators are evolutionarily favored, provided they are able to adjust their partners.

  20. Graph spectral analysis of protein interaction network evolution

    OpenAIRE

    Thorne, Thomas; Stumpf, Michael P. H.

    2012-01-01

    We present an analysis of protein interaction network data via the comparison of models of network evolution to the observed data. We take a Bayesian approach and perform posterior density estimation using an approximate Bayesian computation with sequential Monte Carlo method. Our approach allows us to perform model selection over a selection of potential network growth models. The methodology we apply uses a distance defined in terms of graph spectra which captures the network data more natu...

  1. Predicting the evolution of social networks with life cycle events

    OpenAIRE

    Sharmeen, F Fariya; Arentze, TA Theo; Timmermans, HJP Harry

    2015-01-01

    This paper presents a model of social network evolution, to predict and simulate changes in social networks induced by lifecycle events. We argue that social networks change with lifecycle events, and we extend a model of friendship selection to incorporate these dynamics of personal social networks. The model uses theories of homophily and reciprocity and is formulated in a random utility maximization framework to predict the formation of social ties between individuals in the population. It...

  2. Millimeter-Wave Evolution for 5G Cellular Networks

    Science.gov (United States)

    Sakaguchi, Kei; Tran, Gia Khanh; Shimodaira, Hidekazu; Nanba, Shinobu; Sakurai, Toshiaki; Takinami, Koji; Siaud, Isabelle; Strinati, Emilio Calvanese; Capone, Antonio; Karls, Ingolf; Arefi, Reza; Haustein, Thomas

    Triggered by the explosion of mobile traffic, 5G (5th Generation) cellular network requires evolution to increase the system rate 1000 times higher than the current systems in 10 years. Motivated by this common problem, there are several studies to integrate mm-wave access into current cellular networks as multi-band heterogeneous networks to exploit the ultra-wideband aspect of the mm-wave band. The authors of this paper have proposed comprehensive architecture of cellular networks with mm-wave access, where mm-wave small cell basestations and a conventional macro basestation are connected to Centralized-RAN (C-RAN) to effectively operate the system by enabling power efficient seamless handover as well as centralized resource control including dynamic cell structuring to match the limited coverage of mm-wave access with high traffic user locations via user-plane/control-plane splitting. In this paper, to prove the effectiveness of the proposed 5G cellular networks with mm-wave access, system level simulation is conducted by introducing an expected future traffic model, a measurement based mm-wave propagation model, and a centralized cell association algorithm by exploiting the C-RAN architecture. The numerical results show the effectiveness of the proposed network to realize 1000 times higher system rate than the current network in 10 years which is not achieved by the small cells using commonly considered 3.5 GHz band. Furthermore, the paper also gives latest status of mm-wave devices and regulations to show the feasibility of using mm-wave in the 5G systems.

  3. Structuring evolution: biochemical networks and metabolic diversification in birds.

    Science.gov (United States)

    Morrison, Erin S; Badyaev, Alexander V

    2016-08-25

    Recurrence and predictability of evolution are thought to reflect the correspondence between genomic and phenotypic dimensions of organisms, and the connectivity in deterministic networks within these dimensions. Direct examination of the correspondence between opportunities for diversification imbedded in such networks and realized diversity is illuminating, but is empirically challenging because both the deterministic networks and phenotypic diversity are modified in the course of evolution. Here we overcome this problem by directly comparing the structure of a "global" carotenoid network - comprising of all known enzymatic reactions among naturally occurring carotenoids - with the patterns of evolutionary diversification in carotenoid-producing metabolic networks utilized by birds. We found that phenotypic diversification in carotenoid networks across 250 species was closely associated with enzymatic connectivity of the underlying biochemical network - compounds with greater connectivity occurred the most frequently across species and were the hotspots of metabolic pathway diversification. In contrast, we found no evidence for diversification along the metabolic pathways, corroborating findings that the utilization of the global carotenoid network was not strongly influenced by history in avian evolution. The finding that the diversification in species-specific carotenoid networks is qualitatively predictable from the connectivity of the underlying enzymatic network points to significant structural determinism in phenotypic evolution.

  4. Research on the Evolution and Analysis Technique of Network Public Opinion Based on BBS%基于BBS的网络舆情演变和分析技术研究

    Institute of Scientific and Technical Information of China (English)

    葛晓滨

    2014-01-01

    The evolution of the mechanism network public opinion were explored on the use of life-cycle approach that based on the analysis of the basic content network public opinion. and the network of public opinion development process exhibited the characteristics and laws were summarized and concluded. On this basis,the network public opinion technical analysis model were established that based on BBS to carry out as the subject network public opinion analysis techniques of inquiry. the evolution mechanism of network public opinion were proved through the BBS public opinion hot issues experiment that reveals the internal laws of the network of public opinion derivative.%在分析网络舆情基本内涵的基础上,采用生命周期方法探索了网络舆情的演变机制,并对网络舆情发展过程中所表现出的特征和规律进行了归纳和总结。在此基础上,以BBS为标的对网络舆情的分析技术进行了探究,建立了以BBS为基础的网络舆情技术分析模型,通过BBS舆情热点事件实验,验证了网络舆情的演变机制,揭示了网络舆情的内在衍生规律。

  5. Evolution of a Non-Abelian Cosmic String Network

    CERN Document Server

    McGraw, P N

    1998-01-01

    We describe a numerical simulation of the evolution of an $S_3$ cosmic string network which takes fully into account the non-commutative nature of the cosmic string fluxes and the topological obstructions which hinder strings from moving past each other or intercommuting. The influence of initial conditions, string tensions, and other parameters on the network's evolution is explored. In a broad range of regimes, the total energy density as a function of time exhibits a familiar power-law behavior, and we do not find strong support for a string-dominated cosmological scenario. However, the speed of the network's collapse (coefficient of the power law) can vary quite a bit, as can the qualitative features of the network. There is a surprisingly strong dependence on the statistical properties of the initial conditions. The results give some insight as to which processes play the most important roles in the evolution of a non-Abelian network.

  6. A random walk evolution model of wireless sensor networks and virus spreading

    Institute of Scientific and Technical Information of China (English)

    Wang Ya-Qi; Yang Xiao-Yuan

    2013-01-01

    In this paper,considering both cluster heads and sensor nodes,we propose a novel evolving a network model based on a random walk to study the fault tolerance decrease of wireless sensor networks (WSNs) due to node failure,and discuss the spreading dynamic behavior of viruses in the evolution model.A theoretical analysis shows that the WSN generated by such an evolution model not only has a strong fault tolerance,but also can dynamically balance the energy loss of the entire network.It is also found that although the increase of the density of cluster heads in the network reduces the network efficiency,it can effectively inhibit the spread of viruses.In addition,the heterogeneity of the network improves the network efficiency and enhances the virus prevalence.We confirm all the theoretical results with sufficient numerical simulations.

  7. Evolution of sociology freshmen into a friendship network

    NARCIS (Netherlands)

    Duijn, Marijtje A.J. van; Zeggelink, Evelien P.H.; Huisman, Mark; Stokman, Frans N.; Wasseur, Frans W.

    2003-01-01

    In this paper we both describe and analyze the meeting process and the evolution of a friendship network among sociology freshmen in the Netherlands. We develop a theory that explains how changes in the network structure depend on one or more of four main effects: proximity, visible similarity, invi

  8. Evolution of the Converged NGN Service Platforms Towards Future Networks

    NARCIS (Netherlands)

    Mikóczy, E.; Kotuliak, I.; Deventer, M.O. van

    2011-01-01

    This article presents a comparison of main characteristics of the Next Generation Networks (NGN) and Future Generation Internet (FGI). The aim is to discuss and compare two approaches to Future Networks (FN) and services: the evolution of NGN, and the revolutionary approach of a new FGI. We present

  9. Dynamic evolution model of operational network based on complex network theory%复杂网络理论的作战网络动态演化模型

    Institute of Scientific and Technical Information of China (English)

    张强; 李建华; 沈迪; 赵军伟

    2015-01-01

    为动态评估作战组织结构对作战效能的作用影响,采用复杂网络分析了信息化条件下作战组织结构的网络化特性,综合考虑作战组织实体及组织结构关系的异质性,构建了基于多维加权的作战网络模型,定义了刻画作战网络性能的协同增益特征量.以提高作战效能作为网络演化动力,分别设计了择优演化和随机演化两种作战网络动态演化模型,结合协同增益指标提出了分析作战网络动态演化与作战效能之间内在关联及影响规律的方法,仿真结果验证了方法的可行性,可为设计与优化作战组织结构提供理论依据.%In order to assess the influence of combat organizational structure on operational effectiveness dynamically, the network characteristic of combat organizational structure on condition of information was analyzed by using complex network theory. Considering the heterogeneity of combat organizational entity and organizational structure relation, a multi-dimensions weighted operational network model was firstly constructed, and then the characteristic value of cooperative gain, which depicts the performance of operational network, was defined. Under this, to enhance operational effectiveness, two dynamic evolution models of operational network, which are random evolution model and preferred evolution model, were designed, and the internal relation and influence law between operational network dynamic evolution and operational effectiveness was analyzed by using the models along with the characteristic values of cooperative gain. Finally, simulation results show the feasibility of the proposed method, which can be used to provide theoretical basis for designing and optimizing combat organizational structure.

  10. Evolution of Weighted Networks by Duplication-Divergence Mechanism

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jian-Guo; YAN Jia-Ren; LIU Zi-Ran; WANG Li

    2006-01-01

    @@ The duplication and divergence process is ubiquitous in nature and man-made networks. Motivated by the duplication-divergence mechanism which depicts the growth of protein networks, we propose a weighted network model in which topological evolution is coupled with weight dynamics. Large scale numerical results indicate that our model can naturally generate networks with power-law-like distributions of degree, strength and weight.The degree-strength correlation is illustrated as well. These properties are in agreement well with empirical data observed in real-world systems. Furthermore, by altering the retention probability σ, weighted, structured exponential networks are realized.

  11. Modeling protein network evolution under genome duplication and domain shuffling

    Directory of Open Access Journals (Sweden)

    Isambert Hervé

    2007-11-01

    Full Text Available Abstract Background Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such exponential evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI networks by outweighing, in particular, all time-linear network growths modeled so far. Results We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from i prevailing exponential network dynamics under duplication and ii asymmetric divergence of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of direct and indirect PPI networks of S. cerevisiae are well reproduced numerically with only two adjusted parameters of clear biological significance (i.e. network effective growth rate and average number of protein-binding domains per protein. Conclusion This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale

  12. Automata network models of galaxy evolution

    Science.gov (United States)

    Chappell, David; Scalo, John

    1993-01-01

    Two ideas appear frequently in theories of star formation and galaxy evolution: (1) star formation is nonlocally excitatory, stimulating star formation in neighboring regions by propagation of a dense fragmenting shell or the compression of preexisting clouds; and (2) star formation is nonlocally inhibitory, making H2 regions and explosions which can create low-density and/or high temperature regions and increase the macroscopic velocity dispersion of the cloudy gas. Since it is not possible, given the present state of hydrodynamic modeling, to estimate whether one of these effects greatly dominates the other, it is of interest to investigate the predicted spatial pattern of star formation and its temporal behavior in simple models which incorporate both effects in a controlled manner. The present work presents preliminary results of such a study which is based on lattice galaxy models with various types of nonlocal inhibitory and excitatory couplings of the local SFR to the gas density, temperature, and velocity field meant to model a number of theoretical suggestions.

  13. Evolution of cooperation in multiplex networks.

    Science.gov (United States)

    Gómez-Gardeñes, Jesús; Reinares, Irene; Arenas, Alex; Floría, Luis Mario

    2012-01-01

    We study evolutionary game dynamics on structured populations in which individuals take part in several layers of networks of interactions simultaneously. This multiplex of interdependent networks accounts for the different kind of social ties each individual has. By coupling the evolutionary dynamics of a Prisoner's Dilemma game in each of the networks, we show that the resilience of cooperative behaviors for extremely large values of the temptation to defect is enhanced by the multiplex structure. Furthermore, this resilience is intrinsically related to a non-trivial organization of cooperation across the network layers, thus providing a new way out for cooperation to survive in structured populations.

  14. Dynamic Evolution Model of Equipment Maintenance Organizational Structure Based on Multielement-Weighted Network%基于多元加权网络的装备维修保障组织结构动态演化模型

    Institute of Scientific and Technical Information of China (English)

    徐玉国; 邱静; 刘冠军

    2012-01-01

    针对维修保障组织结构的动态性分析与设计,引入了复杂网络的描述与分析方法,分析了现代维修保障组织的网络化特性,提出了描述维修保障组织结构的多元加权网络模型,并定义了刻画维修保障组织结构的5个特征量.通过分析拓扑结构特性与动态演化对维修保障组织结构的影响,提出了适应演化与随机演化2种维修保障组织结构的动态演化模型,并将其与5个特征量相结合提出了分析组织结构模型动态演化规律的算法,最终验证了该方法的可行性.结果表明该方法可以为维修保障组织结构的设计提供重要支持.%The dynamic analysis and design of equipment maintenance logistics organizational structure is a critical challenge in a complex networked environment. The network characteristics of equipment maintenance logistics organization was analyzed by using the complex network theory. A multielement-weighted network model of equipment maintenance logistics organizational structure was addressed, and five characteristic values which depict the maintenance logistics organizational structure were defined. The impact of topology characteristics and dynamic evolution on the equipment maintenance logistics organizational structure was analyzed. Two dynamic evolution models of equipment maintenance logistics organizational structure were proposed based on the multielement-weighted network, which are the random evolution model and the adaptive evolution model. And an algorithm for the analysis of organizational structure dynamics was proposed using the models along with those five characteristic values. Finally, an equipment maintenance logistics organizational structure was provided to illustrate the feasibility of the proposed method. The impact of adaptive evolution model parameters on the organizational structure performance was analyzed. The result shows the proposed method can be used to obtain the best maintenance

  15. Extended evolution: A conceptual framework for integrating regulatory networks and niche construction.

    Science.gov (United States)

    Laubichler, Manfred D; Renn, Jürgen

    2015-11-01

    This paper introduces a conceptual framework for the evolution of complex systems based on the integration of regulatory network and niche construction theories. It is designed to apply equally to cases of biological, social and cultural evolution. Within the conceptual framework we focus especially on the transformation of complex networks through the linked processes of externalization and internalization of causal factors between regulatory networks and their corresponding niches and argue that these are an important part of evolutionary explanations. This conceptual framework extends previous evolutionary models and focuses on several challenges, such as the path-dependent nature of evolutionary change, the dynamics of evolutionary innovation and the expansion of inheritance systems.

  16. Evolution of a designless nanoparticle network into reconfigurable Boolean logic

    Science.gov (United States)

    Bose, S. K.; Lawrence, C. P.; Liu, Z.; Makarenko, K. S.; van Damme, R. M. J.; Broersma, H. J.; van der Wiel, W. G.

    2015-12-01

    Natural computers exploit the emergent properties and massive parallelism of interconnected networks of locally active components. Evolution has resulted in systems that compute quickly and that use energy efficiently, utilizing whatever physical properties are exploitable. Man-made computers, on the other hand, are based on circuits of functional units that follow given design rules. Hence, potentially exploitable physical processes, such as capacitive crosstalk, to solve a problem are left out. Until now, designless nanoscale networks of inanimate matter that exhibit robust computational functionality had not been realized. Here we artificially evolve the electrical properties of a disordered nanomaterials system (by optimizing the values of control voltages using a genetic algorithm) to perform computational tasks reconfigurably. We exploit the rich behaviour that emerges from interconnected metal nanoparticles, which act as strongly nonlinear single-electron transistors, and find that this nanoscale architecture can be configured in situ into any Boolean logic gate. This universal, reconfigurable gate would require about ten transistors in a conventional circuit. Our system meets the criteria for the physical realization of (cellular) neural networks: universality (arbitrary Boolean functions), compactness, robustness and evolvability, which implies scalability to perform more advanced tasks. Our evolutionary approach works around device-to-device variations and the accompanying uncertainties in performance. Moreover, it bears a great potential for more energy-efficient computation, and for solving problems that are very hard to tackle in conventional architectures.

  17. Evolution of social networks: the example of obesity.

    Science.gov (United States)

    Demongeot, Jacques; Taramasco, Carla

    2014-12-01

    The present paper deals with the effect of the social transmission of nutrition habits in a social and biological age-dependent context on obesity, and accordingly on type II diabetes and among its complications, the neurodegenerative diseases. The evolution of social networks and inside a network the healthy weight of a person are depending on the context in which this person has contacts and exchanges concerning his alimentation, physical activity and sedentary habits, inside the dominant social network in which the person lives (e.g., scholar for young, professional for adult, home or institution for elderly people). Three successive steps of evolution will be considered for social networks (like for neural one's): initial random connectivity, destruction and consolidation of links following a new transition rule called homophilic until an asymptotic architectural organization and configuration of states. The application of such a network dynamics concerns the sequence overweight/obesity/type II diabetes and neurodegenerative diseases.

  18. Evolution of enzymes in metabolism: a network perspective.

    Science.gov (United States)

    Alves, Rui; Chaleil, Raphael A G; Sternberg, Michael J E

    2002-07-19

    Several models have been proposed to explain the origin and evolution of enzymes in metabolic pathways. Initially, the retro-evolution model proposed that, as enzymes at the end of pathways depleted their substrates in the primordial soup, there was a pressure for earlier enzymes in pathways to be created, using the later ones as initial template, in order to replenish the pools of depleted metabolites. Later, the recruitment model proposed that initial templates from other pathways could be used as long as those enzymes were similar in chemistry or substrate specificity. These two models have dominated recent studies of enzyme evolution. These studies are constrained by either the small scale of the study or the artificial restrictions imposed by pathway definitions. Here, a network approach is used to study enzyme evolution in fully sequenced genomes, thus removing both constraints. We find that homologous pairs of enzymes are roughly twice as likely to have evolved from enzymes that are less than three steps away from each other in the reaction network than pairs of non-homologous enzymes. These results, together with the conservation of the type of chemical reaction catalyzed by evolutionarily related enzymes, suggest that functional blocks of similar chemistry have evolved within metabolic networks. One possible explanation for these observations is that this local evolution phenomenon is likely to cause less global physiological disruptions in metabolism than evolution of enzymes from other enzymes that are distant from them in the metabolic network.

  19. Evolution after whole-genome duplication: a network perspective.

    Science.gov (United States)

    Zhu, Yun; Lin, Zhenguo; Nakhleh, Luay

    2013-11-06

    Gene duplication plays an important role in the evolution of genomes and interactomes. Elucidating how evolution after gene duplication interplays at the sequence and network level is of great interest. In this work, we analyze a data set of gene pairs that arose through whole-genome duplication (WGD) in yeast. All these pairs have the same duplication time, making them ideal for evolutionary investigation. We investigated the interplay between evolution after WGD at the sequence and network levels and correlated these two levels of divergence with gene expression and fitness data. We find that molecular interactions involving WGD genes evolve at rates that are three orders of magnitude slower than the rates of evolution of the corresponding sequences. Furthermore, we find that divergence of WGD pairs correlates strongly with gene expression and fitness data. Because of the role of gene duplication in determining redundancy in biological systems and particularly at the network level, we investigated the role of interaction networks in elucidating the evolutionary fate of duplicated genes. We find that gene neighborhoods in interaction networks provide a mechanism for inferring these fates, and we developed an algorithm for achieving this task. Further epistasis analysis of WGD pairs categorized by their inferred evolutionary fates demonstrated the utility of these techniques. Finally, we find that WGD pairs and other pairs of paralogous genes of small-scale duplication origin share similar properties, giving good support for generalizing our results from WGD pairs to evolution after gene duplication in general.

  20. Evolution of individual versus social learning on social networks.

    Science.gov (United States)

    Tamura, Kohei; Kobayashi, Yutaka; Ihara, Yasuo

    2015-03-06

    A number of studies have investigated the roles played by individual and social learning in cultural phenomena and the relative advantages of the two learning strategies in variable environments. Because social learning involves the acquisition of behaviours from others, its utility depends on the availability of 'cultural models' exhibiting adaptive behaviours. This indicates that social networks play an essential role in the evolution of learning. However, possible effects of social structure on the evolution of learning have not been fully explored. Here, we develop a mathematical model to explore the evolutionary dynamics of learning strategies on social networks. We first derive the condition under which social learners (SLs) are selectively favoured over individual learners in a broad range of social network. We then obtain an analytical approximation of the long-term average frequency of SLs in homogeneous networks, from which we specify the condition, in terms of three relatedness measures, for social structure to facilitate the long-term evolution of social learning. Finally, we evaluate our approximation by Monte Carlo simulations in complete graphs, regular random graphs and scale-free networks. We formally show that whether social structure favours the evolution of social learning is determined by the relative magnitudes of two effects of social structure: localization in competition, by which competition between learning strategies is evaded, and localization in cultural transmission, which slows down the spread of adaptive traits. In addition, our estimates of the relatedness measures suggest that social structure disfavours the evolution of social learning when selection is weak.

  1. Community Evolution in International Migration Top1 Networks.

    Science.gov (United States)

    Peres, Mihaela; Xu, Helian; Wu, Gang

    2016-01-01

    Focusing on each country's topmost destination/origin migration relation with other countries, this study builds top1 destination networks and top1 origin networks in order to understand their skeletal construction and community dynamics. Each top1 network covers approximately 50% of the complete migrant network stock for each decade between 1960 and 2000. We investigate the community structure by implementing the Girvan-Newman algorithm and compare the number of components and communities to illustrate their differences. We find that (i) both top1 networks (origin and destination) exhibited communities with a clear structure and a surprising evolution, although 80% edges persist between each decade; (ii) top1 destination networks focused on developed countries exhibiting shorter paths and preferring more advance countries, while top1 origin networks focused both on developed as well as more substantial developing nations that presented a longer path and more stable groups; (iii) only few countries have a decisive influence on community evolution of both top1 networks. USA took the leading position as a destination country in top1 destination networks, while China and India were the main Asian emigration countries in top1 origin networks; European countries and the Russian Federation played an important role in both.

  2. Community Evolution in International Migration Top1 Networks.

    Directory of Open Access Journals (Sweden)

    Mihaela Peres

    Full Text Available Focusing on each country's topmost destination/origin migration relation with other countries, this study builds top1 destination networks and top1 origin networks in order to understand their skeletal construction and community dynamics. Each top1 network covers approximately 50% of the complete migrant network stock for each decade between 1960 and 2000. We investigate the community structure by implementing the Girvan-Newman algorithm and compare the number of components and communities to illustrate their differences. We find that (i both top1 networks (origin and destination exhibited communities with a clear structure and a surprising evolution, although 80% edges persist between each decade; (ii top1 destination networks focused on developed countries exhibiting shorter paths and preferring more advance countries, while top1 origin networks focused both on developed as well as more substantial developing nations that presented a longer path and more stable groups; (iii only few countries have a decisive influence on community evolution of both top1 networks. USA took the leading position as a destination country in top1 destination networks, while China and India were the main Asian emigration countries in top1 origin networks; European countries and the Russian Federation played an important role in both.

  3. Opinion evolution mo del of so cial network based on information entropy%基于信息熵的社交网络观点演化模型

    Institute of Scientific and Technical Information of China (English)

    黄飞虎; 彭舰; 宁黎苗

    2014-01-01

    随着网络服务的发展,社交网络逐渐成为信息传播的新媒介。因此,研究网络舆情演化具有重要意义和实用价值。为了更好地研究网络舆论,在信息熵的基础上,提出了一个社交网络观点演化模型。此模型存在以下两个特点:一是可以反映个体面对正负两种观点趋向做出抉择时的心理过程;二是可以反映个体形成新观点时主观因素和客观因素的影响。在仿真实验中,讨论了舆论环境对个体观点演化的影响,初始观点和自信度对观点演化的影响,以及意见领袖对群体观点演化的影响。实验结果表明,该模型可以反映真实社交网络中个体的心理学特征,比如个体的观点形成会受到舆论环境的影响,自信的个体不愿意接受他人的观点,当意见领袖存在时群体的观点会受到影响等。%With the development of network services, social networking has become a new medium of information dissemination. Thus, many scholars pay close attention to the evolution of network public opinion which has great significance and practical value. In this paper, an opinion evolution model of social network based on information entropy is proposed, which is helpful to investigate the evolution of network public opinion. The model has two characteristics: firstly, it can reflect the psychological process when an individual makes a choice facing with two opposite views;secondly, it can reflect the influence of subjective and objective factors when the individual forms new ideas. In the simulation, some issues are discussed which includes the effects of the public opinion environment on the individual opinion evolution, the influences of the initial opinion and self-confidence on the individual opinion evolution, and the effects of leaders’ opinions on the opinion evolution of populations. From the experimental results it follows that the model works well and can reflect the

  4. Complete trails of coauthorship network evolution

    Science.gov (United States)

    Lee, Deokjae; Goh, K.-I.; Kahng, B.; Kim, D.

    2010-08-01

    The rise and fall of a research field is the cumulative outcome of its intrinsic scientific value and social coordination among scientists. The structure of the social component is quantifiable by the social network of researchers linked via coauthorship relations, which can be tracked through digital records. Here, we use such coauthorship data in theoretical physics and study their complete evolutionary trail since inception, with a particular emphasis on the early transient stages. We find that the coauthorship networks evolve through three common major processes in time: the nucleation of small isolated components, the formation of a treelike giant component through cluster aggregation, and the entanglement of the network by large-scale loops. The giant component is constantly changing yet robust upon link degradations, forming the network’s dynamic core. The observed patterns are successfully reproducible through a network model.

  5. Study on Evolution Direction of Express Delivery Network Based on Sharing Economy%考虑共享经济的快递网络演化方向研究

    Institute of Scientific and Technical Information of China (English)

    牟能冶; 陈召

    2016-01-01

    共享经济在为快递行业提供发展契机的同时影响着快递网络的演化方向.首先结合图论对快递网络的结构特征进行剖析,并对轴辐式和全连通这两种典型快递网络的演化模型进行区别研究,在此基础上考虑共享经济作用下快递需求量、单位运费、规模经济系数等因素的变化,得出快递网络在共享经济下同时具备轴辐式和全连通两种演化趋势的结论,为企业快递网络的拓展提供决策支持.%In this paper, we first analyzed the structural characteristics of the express delivery network based on the graph theory, then differentiated the evolution mode of the hub-and-spoke network and the fully-connected network, and then on such basis, considering the changes in the demand for the express services, unit charge, economy-of-scale coefficient, etc., under the sharing economy, concluded that under the sharing economy, the evolution trend of the express delivery network would take on both the characteristics of the hub-and-spoke and fully-connected networks.

  6. The Evolution of Community Structure in a Coauthorship Network

    Directory of Open Access Journals (Sweden)

    William Mcdowell

    2011-12-01

    Full Text Available Mechanisms such as triadic closure and preferential attachment drive the evolution of social networks. Many models use these mechanisms to predict future links, and they generate realistic networks with scale-free degree distributions. These social networks also have community structure, or sets of vertices which are more connected to each other than the rest of the network. To study the evolution of research groups of scientists in a coauthorship network, we use a timeheterarchy representation to extend the mechanisms driving the evolution of the network to the level of this community structure. Specifically, we examine changes in the structure of groups in terms of mechanisms analogous to triadic closure and preferential attachment, and as a result, we find that the network evolves in the same way at the group-level and the individual-level. In addition, we find that interactions at the group-level might affect interactions at the individual-level in that members of a single group are more likely to strengthen their relationships than members of separate groups.

  7. A Convergence Strategy of Data and Optical Networks Based on a Novel Node Structure

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    The convergence of data and optical networks is a charming tendency of the current network evolution. In this paper, we propose a novel data and optical network integrating device. Based on it, a converging network structure is put forward and named Hierarchical Data and Optical Networking Integrating (HDONI) networking architecture.

  8. Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation

    Science.gov (United States)

    Kwak, Doyeon

    2017-01-01

    It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks. PMID:28542367

  9. Community core evolution in mobile social networks.

    Science.gov (United States)

    Xu, Hao; Xiao, Weidong; Tang, Daquan; Tang, Jiuyang; Wang, Zhenwen

    2013-01-01

    Community detection in social networks attracts a lot of attention in the recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. For example, a casual visit in Facebook cannot be seen as an establishment of friendship. Hence, our question is the following: how to cluster the real friends in mobile social networks? In this paper, we study the problem of detecting the stable community core in mobile social networks. The cumulative stable contact is proposed to depict the relationship among nodes. The whole process is divided into timestamps. Nodes and their connections can be added or removed at each timestamp, and historical contacts are considered when detecting the community core. Also, community cores can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community cores in mobile social networks.

  10. Community Core Evolution in Mobile Social Networks

    Directory of Open Access Journals (Sweden)

    Hao Xu

    2013-01-01

    Full Text Available Community detection in social networks attracts a lot of attention in the recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. For example, a casual visit in Facebook cannot be seen as an establishment of friendship. Hence, our question is the following: how to cluster the real friends in mobile social networks? In this paper, we study the problem of detecting the stable community core in mobile social networks. The cumulative stable contact is proposed to depict the relationship among nodes. The whole process is divided into timestamps. Nodes and their connections can be added or removed at each timestamp, and historical contacts are considered when detecting the community core. Also, community cores can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community cores in mobile social networks.

  11. Differential Evolution Algorithm for Route Optimization Problems of Engineering Networks

    Directory of Open Access Journals (Sweden)

    O. G. Monahov

    2015-01-01

    Full Text Available The paper considers problems of structure optimization of engineering networks to provide a minimum total cost of engineering networks in construction and operation. The mathematical statement of the problem in terms of the hyper-network theory takes into account the interdependence of indicators of hyper-network elements, a layout area and a projected network. A digital model of terrain presents the placement area of engineering networks (a territory. In our case, it will be a weighted mesh (graph of primary network of dedicated vertices-consumers and a vertex-source for the utilities. The edges weights will be determined by the costs of construction and operation of the route between the given vertices of the network. The initial solution of the problem of minimizing the total cost will be using the minimum spanning tree, obtained on a weighted complete graph the vertices of which are defined by vertices-consumers and the vertexsource for the utilities, and the weights of edges are the distance between the vertices on the given weighted graph of the primary network. The work offers a method of differential evolution to solve the problem in hyper-network formulation that improves the initial solution by the mapping the edges of the secondary network in the primary network using additional Steiner points. As numerical experiments have shown, a differential evolution algorithm allows us to reduce the average total cost for a given engineering network compared to the initial solution by 5% - 15%, depending on the configuration, parameters, and layout area.

  12. Network Evolution by Relevance and Importance Preferential Attachment

    CERN Document Server

    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.

  13. Evolution of Controllability in Interbank Networks

    Science.gov (United States)

    Delpini, Danilo; Battiston, Stefano; Riccaboni, Massimo; Gabbi, Giampaolo; Pammolli, Fabio; Caldarelli, Guido

    2013-04-01

    The Statistical Physics of Complex Networks has recently provided new theoretical tools for policy makers. Here we extend the notion of network controllability to detect the financial institutions, i.e. the drivers, that are most crucial to the functioning of an interbank market. The system we investigate is a paradigmatic case study for complex networks since it undergoes dramatic structural changes over time and links among nodes can be observed at several time scales. We find a scale-free decay of the fraction of drivers with increasing time resolution, implying that policies have to be adjusted to the time scales in order to be effective. Moreover, drivers are often not the most highly connected ``hub'' institutions, nor the largest lenders, contrary to the results of other studies. Our findings contribute quantitative indicators which can support regulators in developing more effective supervision and intervention policies.

  14. 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.

  15. Leveraging social networks for understanding the evolution of epidemics

    Directory of Open Access Journals (Sweden)

    Martín Gonzalo

    2011-12-01

    Full Text Available Abstract Background To understand how infectious agents disseminate throughout a population it is essential to capture the social model in a realistic manner. This paper presents a novel approach to modeling the propagation of the influenza virus throughout a realistic interconnection network based on actual individual interactions which we extract from online social networks. The advantage is that these networks can be extracted from existing sources which faithfully record interactions between people in their natural environment. We additionally allow modeling the characteristics of each individual as well as customizing his daily interaction patterns by making them time-dependent. Our purpose is to understand how the infection spreads depending on the structure of the contact network and the individuals who introduce the infection in the population. This would help public health authorities to respond more efficiently to epidemics. Results We implement a scalable, fully distributed simulator and validate the epidemic model by comparing the simulation results against the data in the 2004-2005 New York State Department of Health Report (NYSDOH, with similar temporal distribution results for the number of infected individuals. We analyze the impact of different types of connection models on the virus propagation. Lastly, we analyze and compare the effects of adopting several different vaccination policies, some of them based on individual characteristics -such as age- while others targeting the super-connectors in the social model. Conclusions This paper presents an approach to modeling the propagation of the influenza virus via a realistic social model based on actual individual interactions extracted from online social networks. We implemented a scalable, fully distributed simulator and we analyzed both the dissemination of the infection and the effect of different vaccination policies on the progress of the epidemics. The epidemic values

  16. EVOLUTION OF WIRELESS MOBILE COMMUNICATION NETWORKS AND FUTURE OF CELLULAR MARKET IN INDIA

    Directory of Open Access Journals (Sweden)

    Arjun Kondur

    2012-10-01

    Full Text Available In this paper, we discuss the evolution of the mobile communication systems from GSM to LTE (2G to 4G and the trends in the mobile communication industry. The Global System for Mobile Communication (GSM is a well established cellular system targeted here due to its engineering success and the large number of users currently using the services. The flexibility of wireless networks over voice and data transmission makes it one of the most popular modes of communication. Evolution to next generation services depends on an addition of new services and new features to the existing networks or even an integration of different communication technologies. With the invention of the devices such as tablets and smart phones the need to improve the data transmission rates and transmission efficiency has increased to higher than ever before. In this paper, we focus at some of the important issues pertaining to the evolution of mobile communication networks and predict the future of the networks based on the analysis of the cellular market in India. Since GSM networks accounts for more than 75% of the world wide cellular network, only the evolution of GSM network has been discussed in this paper.

  17. A New Evolution Mechanism Model for B2B E-Commerce Network

    OpenAIRE

    Zhihong Tian; Zhenji Zhang; Xiaolan Guan

    2013-01-01

    To study the structure and evolution mechanism of B2B e-commerce network, the authors propose a network with several layers description of B2B e-commerce market. The empirical analysis from Alibaba.com shows that degree distribution of the network structure follows power-law. Based on modified BA (Barabasi-Albert) model, a new model is proposed, adding layers, fitness parameters, and more reasonable growth mechanism. The model reveals that, the structure of the network is stable, and the aver...

  18. Degree mixing in multilayer networks impedes the evolution of cooperation.

    Science.gov (United States)

    Wang, Zhen; Wang, Lin; Perc, Matjaž

    2014-05-01

    Traditionally, the evolution of cooperation has been studied on single, isolated networks. Yet a player, especially in human societies, will typically be a member of many different networks, and those networks will play different roles in the evolutionary process. Multilayer networks are therefore rapidly gaining on popularity as the more apt description of a networked society. With this motivation, we here consider two-layer scale-free networks with all possible combinations of degree mixing, wherein one network layer is used for the accumulation of payoffs and the other is used for strategy updating. We find that breaking the symmetry through assortative mixing in one layer and/or disassortative mixing in the other layer, as well as preserving the symmetry by means of assortative mixing in both layers, impedes the evolution of cooperation. We use degree-dependent distributions of strategies and cluster-size analysis to explain these results, which highlight the importance of hubs and the preservation of symmetry between multilayer networks for the successful resolution of social dilemmas.

  19. Functional evolution of new and expanded attention networks in humans.

    Science.gov (United States)

    Patel, Gaurav H; Yang, Danica; Jamerson, Emery C; Snyder, Lawrence H; Corbetta, Maurizio; Ferrera, Vincent P

    2015-07-28

    Macaques are often used as a model system for invasive investigations of the neural substrates of cognition. However, 25 million years of evolution separate humans and macaques from their last common ancestor, and this has likely substantially impacted the function of the cortical networks underlying cognitive processes, such as attention. We examined the homology of frontoparietal networks underlying attention by comparing functional MRI data from macaques and humans performing the same visual search task. Although there are broad similarities, we found fundamental differences between the species. First, humans have more dorsal attention network areas than macaques, indicating that in the course of evolution the human attention system has expanded compared with macaques. Second, potentially homologous areas in the dorsal attention network have markedly different biases toward representing the contralateral hemifield, indicating that the underlying neural architecture of these areas may differ in the most basic of properties, such as receptive field distribution. Third, despite clear evidence of the temporoparietal junction node of the ventral attention network in humans as elicited by this visual search task, we did not find functional evidence of a temporoparietal junction in macaques. None of these differences were the result of differences in training, experimental power, or anatomical variability between the two species. The results of this study indicate that macaque data should be applied to human models of cognition cautiously, and demonstrate how evolution may shape cortical networks.

  20. MANET: tracing evolution of protein architecture in metabolic networks.

    Science.gov (United States)

    Kim, Hee Shin; Mittenthal, Jay E; Caetano-Anollés, Gustavo

    2006-07-19

    Cellular metabolism can be characterized by networks of enzymatic reactions and transport processes capable of supporting cellular life. Our aim is to find evolutionary patterns and processes embedded in the architecture and function of modern metabolism, using information derived from structural genomics. The Molecular Ancestry Network (MANET) project traces evolution of protein architecture in biomolecular networks. We describe metabolic MANET, a database that links information in the Structural Classification of Proteins (SCOP), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and phylogenetic reconstructions depicting the evolution of protein fold architecture. Metabolic MANET literally 'paints' the ancestries of enzymes derived from rooted phylogenomic trees directly onto over one hundred metabolic subnetworks, enabling the study of evolutionary patterns at global and local levels. An initial analysis of painted subnetworks reveals widespread enzymatic recruitment and an early origin of amino acid metabolism. MANET maps evolutionary relationships directly and globally onto biological networks, and can generate and test hypotheses related to evolution of metabolism. We anticipate its use in the study of other networks, such as signaling and other protein-protein interaction networks.

  1. Evolution of international trade and investment networks

    Science.gov (United States)

    Zhang, Shuhong; Wang, Lin; Liu, Zhixin; Wang, Xiaofan

    2016-11-01

    In this paper, an evolving two-layer international economy network (IEN) consisting of international trade network (ITN) and international investment network (IIN) as layers, is constructed to investigate the world economy from 2001 to 2010. First, the structure analysis shows that the average partner numbers for both trade and investment are increasing year by year, and the average volume has a significant decrease in 2008 for investment and 2009 for trade. The IIN has longer average path length and dramatically lower edge density compared with the ITN, yet its clustering coefficient is larger in all years. Then, the regional relativity indicates that the longer the distance between two countries, the smaller trade and investment volumes they carry in are general, and the impact of the geographical distance gradually reduces as time goes on. Furthermore, the countries and regions are ranked by Pagerank in ITN, IIN and IEN to illustrate the roles they played. And finally, community structures are detected to visualize the global economic landscape, with countries and regions in the same community ranked according to the total volume of trade or investment.

  2. egoSlider: Visual Analysis of Egocentric Network Evolution.

    Science.gov (United States)

    Wu, Yanhong; Pitipornvivat, Naveen; Zhao, Jian; Yang, Sixiao; Huang, Guowei; Qu, Huamin

    2016-01-01

    Ego-network, which represents relationships between a specific individual, i.e., the ego, and people connected to it, i.e., alters, is a critical target to study in social network analysis. Evolutionary patterns of ego-networks along time provide huge insights to many domains such as sociology, anthropology, and psychology. However, the analysis of dynamic ego-networks remains challenging due to its complicated time-varying graph structures, for example: alters come and leave, ties grow stronger and fade away, and alter communities merge and split. Most of the existing dynamic graph visualization techniques mainly focus on topological changes of the entire network, which is not adequate for egocentric analytical tasks. In this paper, we present egoSlider, a visual analysis system for exploring and comparing dynamic ego-networks. egoSlider provides a holistic picture of the data through multiple interactively coordinated views, revealing ego-network evolutionary patterns at three different layers: a macroscopic level for summarizing the entire ego-network data, a mesoscopic level for overviewing specific individuals' ego-network evolutions, and a microscopic level for displaying detailed temporal information of egos and their alters. We demonstrate the effectiveness of egoSlider with a usage scenario with the DBLP publication records. Also, a controlled user study indicates that in general egoSlider outperforms a baseline visualization of dynamic networks for completing egocentric analytical tasks.

  3. Signed Networks, Triadic Interactions and the Evolution of Cooperation

    Directory of Open Access Journals (Sweden)

    Károly Takács

    2013-09-01

    Full Text Available We outline a model to study the evolution of cooperation in a population of agents playing the prisoner's dilemma in signed networks. We highlight that if only dyadic interactions are taken into account, cooperation never evolves. However, when triadic considerations are introduced, a window of opportunity for emergence of cooperation as a stable behaviour emerges.

  4. Exploration, Exploitation and Co-evolution in Innovation Networks

    NARCIS (Netherlands)

    V.A. Gilsing (Victor)

    2003-01-01

    textabstractThis PhD-thesis describes the co-evolution of sectoral characteristics, networks of firms and the embedded learning regime from the perspective of a sectoral innovation system (SIS). More specifically, this research aims to shed light on how the institutional environment of a SIS conditi

  5. Evolution of a designless nanoparticle network into reconfigurable Boolean logic

    NARCIS (Netherlands)

    Bose, S.K.; Lawrence, C.P.; Liu, Z.; Makarenko, K.S.; Damme, van R.M.J.; Broersma, H.J.; Wiel, van der W.G.

    2015-01-01

    Natural computers exploit the emergent properties and massive parallelism of interconnected networks of locally active components. Evolution has resulted in systems that compute quickly and that use energy efficiently, utilizing whatever physical properties are exploitable. Man-made computers, on th

  6. Cooperative quantum differential evolution algorithm based method for optimizing neural networks%基于量子差分进化算法的神经网络优化方法

    Institute of Scientific and Technical Information of China (English)

    杜文莉; 周仁; 赵亮; 钱锋

    2012-01-01

    一般的神经网络的结构是固定的,在实际应用中容易造成冗余连接和高计算成本。该文采用了协同量子差分进化算法(cooperative quantum differential evolution algo-rithm,CQGADE)以同时优化神经网络的结构和参数,即采用量子遗传算法(quantum genetic algorithm,QGA)来优化神经网络的结构和隐层节点数,采用差分算法来优化神经网络的权值。训练后的神经网络的连接开关能有效删除冗余连接,算法的量子概率幅编码和协同机制可以提高神经网络的学习效率、逼近精度和泛化能力。仿真实验结果表明:用训练后的神经网络预测太阳黑子和蒸汽透平流量具有更好的预测精度和鲁棒性。%Neural network structures are fixed, which results in redundant connections and high computing costs. This paper presents a cooperative quantum differential evolution algorithm (CQGADE) that simultaneously optimizes the neural network structure and parameters. The quantum genetic algorithm is used to optimize the neural network structure and-the number of hidden nodes, while the differential evolution algorithm is used to optimize the neural network weights. This reduces redundant neural network structures, while the amplitude-based coding method and a cooperation mechanism improve the learning efficiency, approximation accuracy, and generalization. Simulations show that this algorithm has better prediction accuracy and robustness for predicting the number of sunspots and the flow of steam turbine.

  7. Structural Approaches to Sequence Evolution Molecules, Networks, Populations

    CERN Document Server

    Bastolla, Ugo; Roman, H. Eduardo; Vendruscolo, Michele

    2007-01-01

    Structural requirements constrain the evolution of biological entities at all levels, from macromolecules to their networks, right up to populations of biological organisms. Classical models of molecular evolution, however, are focused at the level of the symbols - the biological sequence - rather than that of their resulting structure. Now recent advances in understanding the thermodynamics of macromolecules, the topological properties of gene networks, the organization and mutation capabilities of genomes, and the structure of populations make it possible to incorporate these key elements into a broader and deeply interdisciplinary view of molecular evolution. This book gives an account of such a new approach, through clear tutorial contributions by leading scientists specializing in the different fields involved.

  8. General trends in the evolution of prokaryotic transcriptional regulatory networks.

    Science.gov (United States)

    Madan Babu, M; Balaji, S; Aravind, L

    2007-01-01

    Gene expression in organisms is controlled by regulatory proteins termed transcription factors, which recognize and bind to specific nucleotide sequences. Over the years, considerable information has accumulated on the regulatory interactions between transcription factors and their target genes in various model prokaryotes, such as Escherichia coli and Bacillus subtilis. This has allowed the representation of this information in the form of a directed graph, which is commonly referred to as the transcriptional regulatory network. The network representation provides us with an excellent conceptual framework to understand the structure of the transcriptional regulation, both at local and global levels of organization. Several studies suggest that the transcriptional network inferred from model organisms may be approximated by a scale-free topology, which in turn implies the presence of a relatively small group of highly connected regulators (hubs or global regulators). While the graph theoretical principles have been applied to infer various properties of such networks, there have been few studies that have actually investigated the evolution of the transcriptional regulatory networks across diverse organisms. Using recently developed computational methods that exploit various evolutionary principles, we have attempted to reconstruct and compare these networks across a wide-range of prokaryotes. This has provided several insights on the modification and diversification of network structures of various organisms in course of evolution. Firstly, we observed that target genes show a much higher level of conservation than their transcriptional regulators. This in turn suggested that the same set of functions could be differently controlled across diverse organisms, contributing significantly to their adaptive radiations. In particular, at the local level of network structure, organism-specific optimization of the transcription network has evolved primarily via tinkering

  9. 基于演化博弈的社交网络模型演化研究%The research of the social network evolution based on the evolutionary game theory

    Institute of Scientific and Technical Information of China (English)

    刘群; 易佳

    2013-01-01

    The development of research on social network makes a great contribution to the study of network evolution though much of the work focuses on a macroscopic evolutionary mechanism. In this paper, based on public goods games, an optimized evolution-ary dynamic multi-community network model generated by the co-evolution process of evolutionary games and network topology is put forward (dMCPGG). Edges are revised according to the difference between expected payoff and effective payoff through time. Considering the heterogeneous topology, a new preferential rule based on the topological potential is introduced to quantify the nodes’ importance when choosing and updating the payoff of individuals in the public goods games. Finally, the results of simulations demon-strate that the dMCPGG model can reproduce the random world and scale-free world features, such as the nodes’ degree, clustering coefficient and average path length. Finally, we apply our model to United State Congress voting data and verify its rationality.%社会网络研究的兴起,为网络演化规律研究提供了有效工具,但大多数研究集中从宏观机制评估网络演化的动态过程。本文基于公共品博弈,通过演化博弈与网络拓扑共演化方式,从微观角度提出了多社区动态网络演化模型(dMCPGG)。即以节点间演化博弈为动力,修改节点间边的关系,驱动网络拓扑演化。考虑到网络异质性,采用基于拓扑势的偏好规则更准确全面的描述节点影响力。通过数值模拟和仿真实验,验证了本模型的合理性,不仅重现了无标度网络及随机网络的节点度、聚类系数及平均路径长度的结构特性,还准确捕捉到真实社交网络的演化过程。

  10. Natural Models for Evolution on Networks

    CERN Document Server

    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...

  11. Micro-droplet based directed evolution outperforms conventional laboratory evolution

    DEFF Research Database (Denmark)

    Sjostrom, Staffan L.; Huang, Mingtao; Nielsen, Jens

    2014-01-01

    are confined in microfluidic droplets to prevent the phenotype, e.g. secreted enzymes, from leaking between cells. The method was benchmarked against and found to significantly outperform conventional adaptive laboratory evolution (ALE) in enriching enzyme producing cells. It was furthermore applied to enrich......We present droplet adaptive laboratory evolution (DrALE), a directed evolution method used to improve industrial enzyme producing microorganisms for e.g. feedstock digestion. DrALE is based linking a desired phenotype to growth rate allowing only desired cells to proliferate. Single cells...

  12. The Evolution of Inventor Networks of the Smart Phone Patents Based on the Social Network Analysis%基于社会网络分析的智能手机专利发明人合作网络演化研究

    Institute of Scientific and Technical Information of China (English)

    李红; 陈少龙

    2013-01-01

    This paper first researches into the overall evolution of inventor networks of the smart phone patents based on the social network analysis , then it carries on stage analysis of detailed evolution characteristics of such inventor networks in terms of emerging stage , growing stage and maturing stage.It furthermore identifies the core inventors and core inventor groups of the smart phone patents.It has been found out that inventor networks of the smart phone patents bear characteris -tics of small world effect , increasing team size , the intensity of collaboration and network structures of higher connectivity a-mong inventors.%首先利用社会网络分析法对智能手机专利发明人合作网络进行总体演化分析,继而按初始期、成长期、繁荣期的划分对该合作网络的特征进行分阶段分析,进一步定位智能手机核心发明人和核心发明人团队。研究显示,智能手机发明人合作网络呈现小世界效应、规模不断扩大、合作日益紧密和团体性凸显等特征,业已形成三种类型的核心发明人团队。

  13. Location based Network Optimizations for Mobile Wireless Networks

    DEFF Research Database (Denmark)

    Nielsen, Jimmy Jessen

    selection in Wi-Fi networks and predictive handover optimization in heterogeneous wireless networks. The investigations in this work have indicated that location based network optimizations are beneficial compared to typical link measurement based approaches. Especially the knowledge of geographical...

  14. The evolution of generalized reciprocity on social interaction networks.

    Science.gov (United States)

    van Doorn, Gerrit Sander; Taborsky, Michael

    2012-03-01

    Generalized reciprocity (help anyone, if helped by someone) is a minimal strategy capable of supporting cooperation between unrelated individuals. Its simplicity makes it an attractive model to explain the evolution of reciprocal altruism in animals that lack the information or cognitive skills needed for other types of reciprocity. Yet, generalized reciprocity is anonymous and thus defenseless against exploitation by defectors. Recognizing that animals hardly ever interact randomly, we investigate whether social network structure can mitigate this vulnerability. Our results show that heterogeneous interaction patterns strongly support the evolution of generalized reciprocity. The future probability of being rewarded for an altruistic act is inversely proportional to the average connectivity of the social network when cooperators are rare. Accordingly, sparse networks are conducive to the invasion of reciprocal altruism. Moreover, the evolutionary stability of cooperation is enhanced by a modular network structure. Communities of reciprocal altruists are protected against exploitation, because modularity increases the mean access time, that is, the average number of steps that it takes for a random walk on the network to reach a defector. Sparseness and community structure are characteristic properties of vertebrate social interaction patterns, as illustrated by network data from natural populations ranging from fish to primates.

  15. Evolution properties of the community members for dynamic networks

    Science.gov (United States)

    Yang, Kai; Guo, Qiang; Li, Sheng-Nan; Han, Jing-Ti; Liu, Jian-Guo

    2017-03-01

    The collective behaviors of community members for dynamic social networks are significant for understanding evolution features of communities. In this Letter, we empirically investigate the evolution properties of the new community members for dynamic networks. Firstly, we separate data sets into different slices, and analyze the statistical properties of new members as well as communities they joined in for these data sets. Then we introduce a parameter φ to describe community evolution between different slices and investigate the dynamic community properties of the new community members. The empirical analyses for the Facebook, APS, Enron and Wiki data sets indicate that both the number of new members and joint communities increase, the ratio declines rapidly and then becomes stable over time, and most of the new members will join in the small size communities that is s ≤ 10. Furthermore, the proportion of new members in existed communities decreases firstly and then becomes stable and relatively small for these data sets. Our work may be helpful for deeply understanding the evolution properties of community members for social networks.

  16. Energy-Aware Topology Evolution Model with Link and Node Deletion in Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xiaojuan Luo

    2012-01-01

    Full Text Available Based on the complex network theory, a new topological evolving model is proposed. In the evolution of the topology of sensor networks, the energy-aware mechanism is taken into account, and the phenomenon of change of the link and node in the network is discussed. Theoretical analysis and numerical simulation are conducted to explore the topology characteristics and network performance with different node energy distribution. We find that node energy distribution has the weak effect on the degree distribution P(k that evolves into the scale-free state, nodes with more energy carry more connections, and degree correlation is nontrivial disassortative. Moreover, the results show that, when nodes energy is more heterogeneous, the network is better clustered and enjoys higher performance in terms of the network efficiency and the average path length for transmitting data.

  17. Evolution and selection of river networks: statics, dynamics, and complexity.

    Science.gov (United States)

    Rinaldo, Andrea; Rigon, Riccardo; Banavar, Jayanth R; Maritan, Amos; Rodriguez-Iturbe, Ignacio

    2014-02-18

    Moving from the exact result that drainage network configurations minimizing total energy dissipation are stationary solutions of the general equation describing landscape evolution, we review the static properties and the dynamic origins of the scale-invariant structure of optimal river patterns. Optimal channel networks (OCNs) are feasible optimal configurations of a spanning network mimicking landscape evolution and network selection through imperfect searches for dynamically accessible states. OCNs are spanning loopless configurations, however, only under precise physical requirements that arise under the constraints imposed by river dynamics--every spanning tree is exactly a local minimum of total energy dissipation. It is remarkable that dynamically accessible configurations, the local optima, stabilize into diverse metastable forms that are nevertheless characterized by universal statistical features. Such universal features explain very well the statistics of, and the linkages among, the scaling features measured for fluvial landforms across a broad range of scales regardless of geology, exposed lithology, vegetation, or climate, and differ significantly from those of the ground state, known exactly. Results are provided on the emergence of criticality through adaptative evolution and on the yet-unexplored range of applications of the OCN concept.

  18. Molecular chaperones: The modular evolution of cellular networks

    Indian Academy of Sciences (India)

    Tamás Korcsmáros; István A Kovács; Máté S Szalay; Péter Csermely

    2007-04-01

    Molecular chaperones play a prominent role in signaling and transcriptional regulatory networks of the cell. Recent advances uncovered that chaperones act as genetic buffers stabilizing the phenotype of various cells and organisms and may serve as potential regulators of evolvability. Chaperones have weak links, connect hubs, are in the overlaps of network modules and may uncouple these modules during stress, which gives an additional protection for the cell at the network-level. Moreover, after stress chaperones are essential to re-build inter-modular contacts by their low affinity sampling of the potential interaction partners in different modules. This opens the way to the chaperone-regulated modular evolution of cellular networks, and helps us to design novel therapeutic and anti-aging strategies.

  19. Dynamical evolution of the community structure of complex earthquake network

    CERN Document Server

    Abe, Sumiyoshi

    2012-01-01

    Earthquake network is known to be complex in the sense that it is scale-free, small-world, hierarchically organized and assortatively mixed. Here, the time evolution of earthquake networks is analyzed around main shocks in the context of the community structure. It is found that the maximum of the modularity measure quantifying existence of communities exhibits a peculiar behavior: its maximum value stays at a large value before a main shock, suddenly drops to a small values at the main shock, and then increases to relax to a large value again relatively slowly. In this way, a main shock is characterized in the language of theory of complex networks. The result is also interpreted in terms of the clustering structure of the earthquake network.

  20. Influence Activation Model: A New Perspective in Social Influence Analysis and Social Network Evolution

    CERN Document Server

    Yang, Yang; Lichtenwalter, Ryan N; Dong, Yuxiao

    2016-01-01

    What drives the propensity for the social network dynamics? Social influence is believed to drive both off-line and on-line human behavior, however it has not been considered as a driver of social network evolution. Our analysis suggest that, while the network structure affects the spread of influence in social networks, the network is in turn shaped by social influence activity (i.e., the process of social influence wherein one person's attitudes and behaviors affect another's). To that end, we develop a novel model of network evolution where the dynamics of network follow the mechanism of influence propagation, which are not captured by the existing network evolution models. Our experiments confirm the predictions of our model and demonstrate the important role that social influence can play in the process of network evolution. As well exploring the reason of social network evolution, different genres of social influence have been spotted having different effects on the network dynamics. These findings and ...

  1. Modified Penna bit-string network evolution model for scale-free networks with assortative mixing

    Science.gov (United States)

    Kim, Yup; Choi, Woosik; Yook, Soon-Hyung

    2012-02-01

    Motivated by biological aging dynamics, we introduce a network evolution model for social interaction networks. In order to study the effect of social interactions originating from biological and sociological reasons on the topological properties of networks, we introduce the activitydependent rewiring process. From the numerical simulations, we show that the degree distribution of the obtained networks follows a power-law distribution with an exponentially decaying tail, P( k) ˜ ( k + c)- γ exp(- k/k 0). The obtained value of γ is in the range 2 < γ š 3, which is consistent with the values for real social networks. Moreover, we also show that the degree-degree correlation of the network is positive, which is a characteristic of social interaction networks. The possible applications of our model to real systems are also discussed.

  2. Evolution of a polymodal sensory response network

    Directory of Open Access Journals (Sweden)

    Sternberg Paul W

    2008-12-01

    neurons mediating osmosensation and mechanosensation. Conclusion The overall conservation of ASH mediated polymodal nociception suggests that it is an ancestral evolutionarily stable feature of sensation. However, the finding that contribution from non-ASH sensory neurons mediates polymodal nociception in some nematode species suggests that even in conserved sensory behaviors, the cellular response network is dynamic over evolutionary time, perhaps shaped by adaptation of each species to its environment.

  3. The transmission process: A combinatorial stochastic process for the evolution of transmission trees over networks.

    Science.gov (United States)

    Sainudiin, Raazesh; Welch, David

    2016-12-07

    We derive a combinatorial stochastic process for the evolution of the transmission tree over the infected vertices of a host contact network in a susceptible-infected (SI) model of an epidemic. Models of transmission trees are crucial to understanding the evolution of pathogen populations. We provide an explicit description of the transmission process on the product state space of (rooted planar ranked labelled) binary transmission trees and labelled host contact networks with SI-tags as a discrete-state continuous-time Markov chain. We give the exact probability of any transmission tree when the host contact network is a complete, star or path network - three illustrative examples. We then develop a biparametric Beta-splitting model that directly generates transmission trees with exact probabilities as a function of the model parameters, but without explicitly modelling the underlying contact network, and show that for specific values of the parameters we can recover the exact probabilities for our three example networks through the Markov chain construction that explicitly models the underlying contact network. We use the maximum likelihood estimator (MLE) to consistently infer the two parameters driving the transmission process based on observations of the transmission trees and use the exact MLE to characterize equivalence classes over the space of contact networks with a single initial infection. An exploratory simulation study of the MLEs from transmission trees sampled from three other deterministic and four random families of classical contact networks is conducted to shed light on the relation between the MLEs of these families with some implications for statistical inference along with pointers to further extensions of our models. The insights developed here are also applicable to the simplest models of "meme" evolution in online social media networks through transmission events that can be distilled from observable actions such as "likes", "mentions

  4. The Evolution of Ultracapital and Actor-Network Capitalism

    OpenAIRE

    Cloke, Jon

    2013-01-01

    This paper reviews distinct critical writings on the current global economic crisis in order to suggest that the crisis represents a distinctly new form of actor-network capitalism, originating in the hybrid financial innovations since the 1970s, the explosive growth in cyber-space potential during the 1990s and the subsuming of the State by finance that accompanied these two processes. The paper proposes the evolution of what is referred to as ultracapital (capital beyond capital) from withi...

  5. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1999-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  6. Sinc-function based Network

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    1998-01-01

    The purpose of this paper is to describe a neural network (SNN), that is based on Shannons ideas of reconstruction of a real continuous function from its samples. The basic function, used in this network, is the Sinc-function. Two learning algorithms are described. A simple one called IM...

  7. The nature of protein domain evolution: shaping the interaction network.

    Science.gov (United States)

    Bagowski, Christoph P; Bruins, Wouter; Te Velthuis, Aartjan J W

    2010-08-01

    The proteomes that make up the collection of proteins in contemporary organisms evolved through recombination and duplication of a limited set of domains. These protein domains are essentially the main components of globular proteins and are the most principal level at which protein function and protein interactions can be understood. An important aspect of domain evolution is their atomic structure and biochemical function, which are both specified by the information in the amino acid sequence. Changes in this information may bring about new folds, functions and protein architectures. With the present and still increasing wealth of sequences and annotation data brought about by genomics, new evolutionary relationships are constantly being revealed, unknown structures modeled and phylogenies inferred. Such investigations not only help predict the function of newly discovered proteins, but also assist in mapping unforeseen pathways of evolution and reveal crucial, co-evolving inter- and intra-molecular interactions. In turn this will help us describe how protein domains shaped cellular interaction networks and the dynamics with which they are regulated in the cell. Additionally, these studies can be used for the design of new and optimized protein domains for therapy. In this review, we aim to describe the basic concepts of protein domain evolution and illustrate recent developments in molecular evolution that have provided valuable new insights in the field of comparative genomics and protein interaction networks.

  8. 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

  9. Analysis of the influence of tectonics on the evolution valley network based on the SRTM DEM and the relationship of automatically extracted lineaments and the tectonic faults, Jemma River basin, Ethiopia

    Science.gov (United States)

    Kusák, Michal

    2016-04-01

    The Ethiopian Highland is good example of high plateau landscape formed by combination of tectonic uplift and episodic volcanism (Kazmin, 1975; Pik et al., 2003; Gani et al., 2009). Deeply incised gorges indicate active fluvial erosion which leads to instabilities of over-steepened slopes. In this study we focus on Jemma River basin which is a left tributary of Abay - Blue Nile to assess the influence of neotectonics on the evolution of its river and valley network. Tectonic lineaments, shape of valley networks, direction of river courses and intensity of fluvial erosion were compared in six subregions which were delineate beforehand by means of morphometric analysis. The influence of tectonics on the valley network is low in the older deep and wide canyons and in the and on the high plateau covered with Tertiary lava flows while younger upper part of the canyons it is high. Furthermore, the coincidence of the valley network with the tectonic lineaments differs in the subregions. The fluvial erosion along the main tectonic zones (NE-SW) direction made the way for backward erosion possible to reach far distant areas in E for the fluvial erosion. This tectonic zone also separates older areas in the W from the youngest landscape evolution subregions in the E, next to the Rift Valley. We studied the functions that can automatically extract lineaments in programs ArcGIS 10.1 and PCI Geomatica. The values of input parameters and their influence of the final shape and number of lineaments. A map of automated extracted lineaments was created and compared with 1) the tectonic faults by Geology Survey of Ethiopia (1996); and 2) the lineaments based on visual interpretation of by the author. The comparation of lineaments by automated visualization in GIS and visual interpretation of lineaments by the author proves that both sets of lineaments are in the same azimuth (NE-SW) - the same direction as the orientation of the rift. But it the mapping of lineaments by automated

  10. Risk Analysis and Control for the Evolution Disaster System of Typhoon Based on Complex Network%基于复杂网络的台风灾害演化系统风险分析与控制研究

    Institute of Scientific and Technical Information of China (English)

    陈长坤; 纪道溪

    2012-01-01

    Based on the complex networks theory, an idea or method of risk analysis and controlling on natural disasters evolution system is proposed. Taking the Morakot as an example, the network model including 30 crisis nodes and 39 evolution connections is established. The out-in degrees, number of nodes in its subnets and number of branched chains that every node involved in the network are discussed for risk analysis, and then the key nodes and the solutions on disconnecting chains are presented. The results show that fierce wind, rainstorm, flood, landslide, mudslide, traffic jam and village-destroying are the crucial nodes in the network. Afterwards the suggestions for disaster controlling are offered, consisting of improving the operation ability of the urban drainage system, reinforcing the supervision and scheduling for traffic system and starting the rural emergency plans of post-disaster placement and reconstruction.%基于复杂网络理论,提出了一种针对自然灾害演化系统的风险分析与控制的思路与方法.以“莫拉克”台风为例,构建了包含30个危机事件与39条连接边的台风网络演化模型;采用网络节点的出入度、子网节点数和包含节点的支链数进行风险分析,并确定关键节点,进一步提出断链方案和控制建议.结果表明:狂风、暴雨、洪水、山体滑坡、泥石流、交通堵塞和村庄毁坏等事件风险较大,是台风灾害系统的关键节点.据此提出建议:提高城市排水系统运行能力,加强交通系统监管和调度力度,启动农村人员安置和灾后重建预案.

  11. The underlying molecular and network level mechanisms in the evolution of robustness in gene regulatory networks.

    Directory of Open Access Journals (Sweden)

    Mario Pujato

    Full Text Available Gene regulatory networks show robustness to perturbations. Previous works identified robustness as an emergent property of gene network evolution but the underlying molecular mechanisms are poorly understood. We used a multi-tier modeling approach that integrates molecular sequence and structure information with network architecture and population dynamics. Structural models of transcription factor-DNA complexes are used to estimate relative binding specificities. In this model, mutations in the DNA cause changes on two levels: (a at the sequence level in individual binding sites (modulating binding specificity, and (b at the network level (creating and destroying binding sites. We used this model to dissect the underlying mechanisms responsible for the evolution of robustness in gene regulatory networks. Results suggest that in sparse architectures (represented by short promoters, a mixture of local-sequence and network-architecture level changes are exploited. At the local-sequence level, robustness evolves by decreasing the probabilities of both the destruction of existent and generation of new binding sites. Meanwhile, in highly interconnected architectures (represented by long promoters, robustness evolves almost entirely via network level changes, deleting and creating binding sites that modify the network architecture.

  12. Power grid complex network evolutions for the smart grid

    Science.gov (United States)

    Pagani, Giuliano Andrea; Aiello, Marco

    2014-02-01

    The shift towards an energy grid dominated by prosumers (consumers and producers of energy) will inevitably have repercussions on the electricity distribution infrastructure. Today the grid is a hierarchical one delivering energy from large scale facilities to end-users. Tomorrow it will be a capillary infrastructure at the medium and low voltage levels that will support local energy trading among prosumers. We investigate how different network topologies and growth models facilitate a more efficient and reliable network, and how they can facilitate the emergence of a decentralized electricity market. We show how connectivity plays an important role in improving the properties of reliability and path-cost reduction. Our results indicate that a specific type of evolution balances best the ratio between increased connectivity and costs to achieve the network growth.

  13. Stability of Random Networks under Evolution of Attack and Repair

    Institute of Scientific and Technical Information of China (English)

    CHI Li-Ping; YANG Chun-Bin; CAI Xu

    2006-01-01

    With a simple model, we study the stability of random networks under the evolution of attack and repair. We introduce a new quantity, i.e. invulnerability I(s), to describe the stability of the system. It is found that the network can evolve to a stationary state. The stationary value Ic has a power-law dependence on the initial average degree , with the slope about -1.5. In the stationary state, the degree distribution is a normal distribution, rather than a typical Poisson distribution for general random graphs. The clustering coefficient in the stationary state is much larger than that in the initial state. The stability of the network depends only on the initial average degree , which increases rapidly with the decrease of .

  14. Network evolution driven by dynamics applied to graph coloring

    Institute of Scientific and Technical Information of China (English)

    Wu Jian-She; Li Li-Guang; Wang Xiao-Hua; Yu Xin; Jiao Li-Cheng

    2013-01-01

    An evolutionary network driven by dynamics is studied and applied to the graph coloring problem.From an initial structure,both the topology and the coupling weights evolve according to the dynamics.On the other hand,the dynamics of the network are determined by the topology and the coupling weights,so an interesting structure-dynamics co-evolutionary scheme appears.By providing two evolutionary strategies,a network described by the complement of a graph will evolve into several clusters of nodes according to their dynamics.The nodes in each cluster can be assigned the same color and nodes in different clusters assigned different colors.In this way,a co-evolution phenomenon is applied to the graph coloring problem.The proposed scheme is tested on several benchmark graphs for graph coloring.

  15. Adaptive Network Dynamics and Evolution of Leadership in Collective Migration

    CERN Document Server

    Pais, Darren

    2013-01-01

    The evolution of leadership in migratory populations depends not only on costs and benefits of leadership investments but also on the opportunities for individuals to rely on cues from others through social interactions. We derive an analytically tractable adaptive dynamic network model of collective migration with fast timescale migration dynamics and slow timescale adaptive dynamics of individual leadership investment and social interaction. For large populations, our analysis of bifurcations with respect to investment cost explains the observed hysteretic effect associated with recovery of migration in fragmented environments. Further, we show a minimum connectivity threshold above which there is evolutionary branching into leader and follower populations. For small populations, we show how the topology of the underlying social interaction network influences the emergence and location of leaders in the adaptive system. Our model and analysis can describe other adaptive network dynamics involving collective...

  16. Statistically validated mobile communication networks: the evolution of motifs in European and Chinese data

    Science.gov (United States)

    Li, Ming-Xia; Palchykov, Vasyl; Jiang, Zhi-Qiang; Kaski, Kimmo; Kertész, János; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N.

    2014-08-01

    Big data open up unprecedented opportunities for investigating complex systems, including society. In particular, communication data serve as major sources for computational social sciences, but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple-hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, generalized to the directed case. We study two large datasets of mobile phone records, one from Europe and the other from China. For both datasets we compare the raw data networks with the corresponding Bonferroni networks and point out significant differences in the structures and in the basic network measures. We show evidence that the Bonferroni network provides a better proxy for the network of social interactions than the original one. Using the filtered networks, we investigated the statistics and temporal evolution of small directed 3-motifs and concluded that closed communication triads have a formation time scale, which is quite fast and typically intraday. We also find that open communication triads preferentially evolve into other open triads with a higher fraction of reciprocated calls. These stylized facts were observed for both datasets.

  17. Insights into the Ecology and Evolution of Polyploid Plants through Network Analysis.

    Science.gov (United States)

    Gallagher, Joseph P; Grover, Corrinne E; Hu, Guanjing; Wendel, Jonathan F

    2016-06-01

    Polyploidy is a widespread phenomenon throughout eukaryotes, with important ecological and evolutionary consequences. Although genes operate as components of complex pathways and networks, polyploid changes in genes and gene expression have typically been evaluated as either individual genes or as a part of broad-scale analyses. Network analysis has been fruitful in associating genomic and other 'omic'-based changes with phenotype for many systems. In polyploid species, network analysis has the potential not only to facilitate a better understanding of the complex 'omic' underpinnings of phenotypic and ecological traits common to polyploidy, but also to provide novel insight into the interaction among duplicated genes and genomes. This adds perspective to the global patterns of expression (and other 'omic') change that accompany polyploidy and to the patterns of recruitment and/or loss of genes following polyploidization. While network analysis in polyploid species faces challenges common to other analyses of duplicated genomes, present technologies combined with thoughtful experimental design provide a powerful system to explore polyploid evolution. Here, we demonstrate the utility and potential of network analysis to questions pertaining to polyploidy with an example involving evolution of the transgressively superior cotton fibres found in polyploid Gossypium hirsutum. By combining network analysis with prior knowledge, we provide further insights into the role of profilins in fibre domestication and exemplify the potential for network analysis in polyploid species. © 2016 John Wiley & Sons Ltd.

  18. Network-based recommendation algorithms: A review

    CERN Document Server

    Yu, Fei; Gillard, Sebastien; Medo, Matus

    2015-01-01

    Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use - such as the possible influence of recommendation on the evolution of systems that use it - and finally discuss open research directions and challenges.

  19. Network-based recommendation algorithms: A review

    Science.gov (United States)

    Yu, Fei; Zeng, An; Gillard, Sébastien; Medo, Matúš

    2016-06-01

    Recommender systems are a vital tool that helps us to overcome the information overload problem. They are being used by most e-commerce web sites and attract the interest of a broad scientific community. A recommender system uses data on users' past preferences to choose new items that might be appreciated by a given individual user. While many approaches to recommendation exist, the approach based on a network representation of the input data has gained considerable attention in the past. We review here a broad range of network-based recommendation algorithms and for the first time compare their performance on three distinct real datasets. We present recommendation topics that go beyond the mere question of which algorithm to use-such as the possible influence of recommendation on the evolution of systems that use it-and finally discuss open research directions and challenges.

  20. Limited Influence of Oxygen on the Evolution of Chemical Diversity in Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Kazuhiro Takemoto

    2013-10-01

    Full Text Available Oxygen is thought to promote species and biomolecule diversity. Previous studies have suggested that oxygen expands metabolic networks by acquiring metabolites with different chemical properties (higher hydrophobicity, for example. However, such conclusions are typically based on biased evaluation, and are therefore non-conclusive. Thus, we re-investigated the effect of oxygen on metabolic evolution using a phylogenetic comparative method and metadata analysis to reduce the bias as much as possible. Notably, we found no difference in metabolic network expansion between aerobes and anaerobes when evaluating phylogenetic relationships. Furthermore, we showed that previous studies have overestimated or underestimated the degrees of differences in the chemical properties (e.g., hydrophobicity between oxic and anoxic metabolites in metabolic networks of unicellular organisms; however, such overestimation was not observed when considering the metabolic networks of multicellular organisms. These findings indicate that the contribution of oxygen to increased chemical diversity in metabolic networks is lower than previously thought; rather, phylogenetic signals and cell-cell communication result in increased chemical diversity. However, this conclusion does not contradict the effect of oxygen on metabolic evolution; instead, it provides a deeper understanding of how oxygen contributes to metabolic evolution despite several limitations in data analysis methods.

  1. Network-based functional enrichment

    Directory of Open Access Journals (Sweden)

    Poirel Christopher L

    2011-11-01

    Full Text Available Abstract Background Many methods have been developed to infer and reason about molecular interaction networks. These approaches often yield networks with hundreds or thousands of nodes and up to an order of magnitude more edges. It is often desirable to summarize the biological information in such networks. A very common approach is to use gene function enrichment analysis for this task. A major drawback of this method is that it ignores information about the edges in the network being analyzed, i.e., it treats the network simply as a set of genes. In this paper, we introduce a novel method for functional enrichment that explicitly takes network interactions into account. Results Our approach naturally generalizes Fisher’s exact test, a gene set-based technique. Given a function of interest, we compute the subgraph of the network induced by genes annotated to this function. We use the sequence of sizes of the connected components of this sub-network to estimate its connectivity. We estimate the statistical significance of the connectivity empirically by a permutation test. We present three applications of our method: i determine which functions are enriched in a given network, ii given a network and an interesting sub-network of genes within that network, determine which functions are enriched in the sub-network, and iii given two networks, determine the functions for which the connectivity improves when we merge the second network into the first. Through these applications, we show that our approach is a natural alternative to network clustering algorithms. Conclusions We presented a novel approach to functional enrichment that takes into account the pairwise relationships among genes annotated by a particular function. Each of the three applications discovers highly relevant functions. We used our methods to study biological data from three different organisms. Our results demonstrate the wide applicability of our methods. Our algorithms are

  2. Community structure of complex networks based on continuous neural network

    Science.gov (United States)

    Dai, Ting-ting; Shan, Chang-ji; Dong, Yan-shou

    2017-09-01

    As a new subject, the research of complex networks has attracted the attention of researchers from different disciplines. Community structure is one of the key structures of complex networks, so it is a very important task to analyze the community structure of complex networks accurately. In this paper, we study the problem of extracting the community structure of complex networks, and propose a continuous neural network (CNN) algorithm. It is proved that for any given initial value, the continuous neural network algorithm converges to the eigenvector of the maximum eigenvalue of the network modularity matrix. Therefore, according to the stability of the evolution of the network symbol will be able to get two community structure.

  3. Dynamical complexity in the perception-based network formation model

    Science.gov (United States)

    Jo, Hang-Hyun; Moon, Eunyoung

    2016-12-01

    Many link formation mechanisms for the evolution of social networks have been successful to reproduce various empirical findings in social networks. However, they have largely ignored the fact that individuals make decisions on whether to create links to other individuals based on cost and benefit of linking, and the fact that individuals may use perception of the network in their decision making. In this paper, we study the evolution of social networks in terms of perception-based strategic link formation. Here each individual has her own perception of the actual network, and uses it to decide whether to create a link to another individual. An individual with the least perception accuracy can benefit from updating her perception using that of the most accurate individual via a new link. This benefit is compared to the cost of linking in decision making. Once a new link is created, it affects the accuracies of other individuals' perceptions, leading to a further evolution of the actual network. As for initial actual networks, we consider both homogeneous and heterogeneous cases. The homogeneous initial actual network is modeled by Erdős-Rényi (ER) random networks, while we take a star network for the heterogeneous case. In any cases, individual perceptions of the actual network are modeled by ER random networks with controllable linking probability. Then the stable link density of the actual network is found to show discontinuous transitions or jumps according to the cost of linking. As the number of jumps is the consequence of the dynamical complexity, we discuss the effect of initial conditions on the number of jumps to find that the dynamical complexity strongly depends on how much individuals initially overestimate or underestimate the link density of the actual network. For the heterogeneous case, the role of the highly connected individual as an information spreader is also discussed.

  4. Evolution of communication protocols using an artificial regulatory network.

    Science.gov (United States)

    Mitchener, W Garrett

    2014-01-01

    I describe the Utrecht Machine (UM), a discrete artificial regulatory network designed for studying how evolution discovers biochemical computation mechanisms. The corresponding binary genome format is compatible with gene deletion, duplication, and recombination. In the simulation presented here, an agent consisting of two UMs, a sender and a receiver, must encode, transmit, and decode a binary word over time using the narrow communication channel between them. This communication problem has chicken-and-egg structure in that a sending mechanism is useless without a corresponding receiving mechanism. An in-depth case study reveals that a coincidence creates a minimal partial solution, from which a sequence of partial sending and receiving mechanisms evolve. Gene duplications contribute by enlarging the regulatory network. Analysis of 60,000 sample runs under a variety of parameter settings confirms that crossover accelerates evolution, that stronger selection tends to find clumsier solutions and finds them more slowly, and that there is implicit selection for robust mechanisms and genomes at the codon level. Typical solutions associate each input bit with an activation speed and combine them almost additively. The parents of breakthrough organisms sometimes have lower fitness scores than others in the population, indicating that populations can cross valleys in the fitness landscape via outlying members. The simulation exhibits back mutations and population-level memory effects not accounted for in traditional population genetics models. All together, these phenomena suggest that new evolutionary models are needed that incorporate regulatory network structure.

  5. Evolution of a non-Abelian cosmic string network

    Energy Technology Data Exchange (ETDEWEB)

    McGraw, P. [California Institute of Technology, Pasadena, California 91125 (United States)]|[Institute of Field Physics, Department of Physics and Astronomy, University of North Carolina, Chapel Hill, North Carolina 27599 (United States)

    1998-03-01

    We describe a numerical simulation of the evolution of an S{sub 3} cosmic string network which takes fully into account the noncommutative nature of the cosmic string fluxes and the topological obstructions which hinder strings from moving past each other or intercommuting. The influence of initial conditions, string tensions, and other parameters on the network{close_quote}s evolution is explored. Contrary to some previous suggestions, we find no strong evidence of the {open_quotes}freezing{close_quotes} required for a string-dominated cosmological scenario. Instead, the results in a broad range of regimes are consistent with the familiar scaling law, i.e., a constant number of strings per horizon volume. The size of this number, however, can vary quite a bit, as can other overall features. There is a surprisingly strong dependence on the statistical properties of the initial conditions. We also observe a rich variety of interesting new structures, such as light string webs stretched between heavier strings, which are not seen in Abelian networks. {copyright} {ital 1998} {ital The American Physical Society}

  6. Relationship between topology and functions in metabolic network evolution

    Institute of Scientific and Technical Information of China (English)

    WANG Zhuo; CHEN Qi; LIU Lei

    2009-01-01

    What is the relationship between the topological connections among enzymes and their functions during metabolic network evolution? Does this relationship show similarity among closely related or-ganisms? Here we investigated the relationship between enzyme connectivity and functions in meta-bolic networks of chloroplast and its endosymbiotic ancestor, cyanobacteria (Synechococcus sp. WH8102). Also several other species, including E. coil, Arabidopsis thaliana and Cyanidioschyzon merolae, were used for the comparison. We found that the average connectivity among different func-tional pathways and enzyme classifications (EC) was different in all the species examined. However, the average connectivity of enzymes in the same functional classification was quite similar between chloroplast and one representative of cyanobacteria, syw. In addition, the enzymes in the highly con-served modules between chloroplast and syw, such as amino acid metabolism, were highly connected compared with other modules. We also discovered that the isozymes of chloroplast and syw often had higher connectivity, corresponded to primary metabolism and also existed in conserved module. In conclusion, despite the drastic re-organization of metabolism in chloroplast during endosymbiosis, the relationship between network topology and functions is very similar between chloroplast and its pre-cursor cyanobacteria, which demonstrates that the relationship may be used as an indicator of the closeness in evolution.

  7. Structure and evolution of the global seafood trade network

    Science.gov (United States)

    Gephart, Jessica A.; Pace, Michael L.

    2015-12-01

    The food production system is increasingly global and seafood is among the most highly traded commodities. Global trade can improve food security by providing access to a greater variety of foods, increasing wealth, buffering against local supply shocks, and benefit the environment by increasing overall use efficiency for some resources. However, global trade can also expose countries to external supply shocks and degrade the environment by increasing resource demand and loosening feedbacks between consumers and the impacts of food production. As a result, changes in global food trade can have important implications for both food security and the environmental impacts of production. Measurements of globalization and the environmental impacts of food production require data on both total trade and the origin and destination of traded goods (the network structure). While the global trade network of agricultural and livestock products has previously been studied, seafood products have been excluded. This study describes the structure and evolution of the global seafood trade network, including metrics quantifying the globalization of seafood, shifts in bilateral trade flows, changes in centrality and comparisons of seafood to agricultural and industrial trade networks. From 1994 to 2012 the number of countries trading in the network remained relatively constant, while the number of trade partnerships increased by over 65%. Over this same period, the total quantity of seafood traded increased by 58% and the value increased 85% in real terms. These changes signify the increasing globalization of seafood products. Additionally, the trade patterns in the network indicate: increased influence of Thailand and China, strengthened intraregional trade, and increased exports from South America and Asia. In addition to characterizing these network changes, this study identifies data needs in order to connect seafood trade with environmental impacts and food security outcomes.

  8. Multifractal to monofractal evolution of the London's street network

    CERN Document Server

    Murcio, Roberto; Arcaute, Elsa; Batty, Michael

    2015-01-01

    We perform a multifractal analysis of the evolution of London's street network from 1786 to 2010. First, we show that a single fractal dimension, commonly associated with the morphological description of cities, does not su ce to capture the dynamics of the system. Instead, for a proper characterization of such a dynamics, the multifractal spectrum needs to be considered. Our analysis reveals that London evolves from an inhomogeneous fractal structure, that can be described in terms of a multifractal, to a homogeneous one, that converges to monofractality. We argue that London's multifractal to monofracal evolution might be a special outcome of the constraint imposed on its growth by a green belt. Through a series of simulations, we show that multifractal objects, constructed through di usion limited aggregation, evolve towards monofractality if their growth is constrained by a non-permeable boundary.

  9. Broadcast Networks based on the Virus Evolutionary Algorithm

    Directory of Open Access Journals (Sweden)

    Jian-xin Zhu

    2014-05-01

    Full Text Available An optimization algorithm for virus evolution is to research the spread process of a computer or biological virus in network system. The objective of the algorithm is mainly to control the speed of the virus evolution with limited network resource and to study how users can be infected in the network. A dynamical probabilistic system on a connected graph is adopted to model the virus evolution. A traditional virus evolution model needs to solve a non-convex optimization problem taking the spectral radius function of a nonnegative matrix as an optimization objective in the description of virus evolution model. On this basis, two novel approximation algorithms are proposed in this paper. Based on continuous convex approximation, the first one is a suboptimal with rapid speed. The second one can adopt branch-and-bound techniques to achieve a global optimal solution, which use some key inequalities of nonnegative matrix. Comparing with traditional virus evolution model, the simulation experiment shows that the improved algorithm can reach the global optimum in the process of virus evolution and has fast convergence capability in different network conditions.

  10. TWO-STAGE LOCALISATION ALGORITHM FOR WIRELESS SENSOR NETWORK BASED ON DIFFERENTIAL EVOLUTION%基于差分进化的无线传感器网络二阶段定位算法

    Institute of Scientific and Technical Information of China (English)

    武富平; 张瑞华

    2011-01-01

    In recent years the optimisation algorithm has been widely used in wireless sensor network localisation algorithms. Based on an in-depth study on differential evolution algorithm, the authors propose a two-stage localisation algorithm. In the first phase, based on the Euclidean localisation algorithm, they added the idea of distance routing, which is to work with two anchor nodes within two-hop of the unknown node and with any one anchor node which locates two-hop away from the unknown node to calculate the estimated location. In the second phase,they used differential evolution algorithm to perform the iterative optimisation. The proposed algorithm is called the DE-Euclidean localisation algorithm. Simulation results show that,the DE-Euclidean algorithm significantly improves the precision of localisation.%近年来优化算法在无线传感器网络定位算法中得到了广泛应用.在对差分进化算法研究的基础上提出一种二阶段定位算法,第一阶段在Euclidean定位算法的基础上,加入了距离路由思想,通过与未知节点距离两跳之内的两个锚节点和距离两跳之外的任一锚节点利用Euclidean算法来计算估计位置.第二阶段利用差分进化算法进行迭代寻优,提出的新算法称之为DE-Euclidean定位算法.仿真结果表明,DE- Euclidean算法明显提高了定位精度.

  11. Evolution of domain wall networks: the PRS algorithm

    CERN Document Server

    Sousa, L

    2011-01-01

    The Press-Ryden-Spergel (PRS) algorithm is a modification to the field theory equations of motion, parametrized by two parameters ($\\alpha$ and $\\beta$), implemented in numerical simulations of cosmological domain wall networks, in order to ensure a fixed comoving resolution. In this paper we explicitly demonstrate that the PRS algorithm provides the correct domain wall dynamics in $N+1$-dimensional Friedmann-Robertson-Walker (FRW) universes if $\\alpha+\\beta/2=N$, fully validating its use in numerical studies of cosmic domain evolution. We further show that this result is valid for generic thin featureless domain walls, independently of the Lagrangian of the model.

  12. Molecular networks and the evolution of human cognitive specializations.

    Science.gov (United States)

    Fontenot, Miles; Konopka, Genevieve

    2014-12-01

    Inroads into elucidating the origins of human cognitive specializations have taken many forms, including genetic, genomic, anatomical, and behavioral assays that typically compare humans to non-human primates. While the integration of all of these approaches is essential for ultimately understanding human cognition, here, we review the usefulness of coexpression network analysis for specifically addressing this question. An increasing number of studies have incorporated coexpression networks into brain expression studies comparing species, disease versus control tissue, brain regions, or developmental time periods. A clearer picture has emerged of the key genes driving brain evolution, as well as the developmental and regional contributions of gene expression patterns important for normal brain development and those misregulated in cognitive diseases. Copyright © 2014 Elsevier Ltd. All rights reserved.

  13. Heterogeneous Deployment Analysis for Cost-Effective Mobile Network Evolution

    DEFF Research Database (Denmark)

    Coletti, Claudio

    2013-01-01

    The plethora of connected devices, such as attractive smartphones, data dongles and 3G/4G built-in tablet computers, has brought mobile operators to face increasing demand in mobile broadband traffic and services. In addition to the roll-out of Long Term Evolution (LTE), the deployment of small low...... available at the macro layer for wireless backhaul. The main goal is to investigate the LTE downlink performance of different deployment configurations, focusing on spectrum allocation schemes and deployment strategies that are needed to maximize network coverage. Differently from most studies using...... statistical models of deployment areas, the performance analysis is carried out in the form of operator case studies for large-scale deployment scenarios, including realistic macro network layouts and inhomogeneous spatial traffic distributions. Deployment of small cells is performed by means of proposed...

  14. Network evolution induced by the dynamical rules of two populations

    Science.gov (United States)

    Platini, Thierry; Zia, R. K. P.

    2010-10-01

    We study the dynamical properties of a finite dynamical network composed of two interacting populations, namely extrovert (a) and introvert (b). In our model, each group is characterized by its size (Na and Nb) and preferred degree (κa and \\kappa_b\\ll \\kappa_a ). The network dynamics is governed by the competing microscopic rules of each population that consist of the creation and destruction of links. Starting from an unconnected network, we give a detailed analysis of the mean field approach which is compared to Monte Carlo simulation data. The time evolution of the restricted degrees langkbbrang and langkabrang presents three time regimes and a non-monotonic behavior well captured by our theory. Surprisingly, when the population sizes are equal Na = Nb, the ratio of the restricted degree θ0 = langkabrang/langkbbrang appears to be an integer in the asymptotic limits of the three time regimes. For early times (defined by t introverts remains constant while the number of connections increases linearly in the extrovert population. Finally, due to the competing dynamics, the network presents a frustrated stationary state characterized by a ratio θ0 = 3.

  15. Evolution of coauthorship networks: worldwide scientific production on leishmaniasis

    Directory of Open Access Journals (Sweden)

    Gregorio Gonzalez-Alcaide

    2013-12-01

    Full Text Available Introduction Collaboration is one of the defining features of contemporary scientific research, and it is particularly important with regard to neglected diseases that primarily affect developing countries. Methods The present study has identified publications on leishmaniasis in the Medline database from 1945 to 2010, analyzing them according to bibliometric indicators and statistics from social network analysis. Examining aspects such as scientific production, diachronic evolution, and collaboration and configuration of the research groups in the field, we have considered the different types of Leishmania studied and the institutional affiliation and nationality of the authors. Results Seven-hundred and thirty-five authors participate in 154 prominent research clusters or groups. Although the most predominant and consolidated collaborations are characterized by members from the same country studying the same type of Leishmania, there are also notable links between authors from different countries or who study different clinical strains of the disease. Brazil took the lead in this research, with numerous Brazilian researchers heading different clusters in the center of the collaboration network. Investigators from the USA, India, and European countries, such as France, Spain, the United Kingdom, and Italy, also stand out within the network. Conclusions Research should be fostered in countries such as Bangladesh, Nepal, Sudan, and Ethiopia, where there is a high prevalence of different forms of the disease but limited research development with reference authors integrated into the collaboration networks.

  16. Evolution of cooperation under social pressure in multiplex networks

    Science.gov (United States)

    Pereda, María

    2016-09-01

    In this work, we aim to contribute to the understanding of human prosocial behavior by studying the influence that a particular form of social pressure, "being watched," has on the evolution of cooperative behavior. We study how cooperation emerges in multiplex complex topologies by analyzing a particular bidirectionally coupled dynamics on top of a two-layer multiplex network (duplex). The coupled dynamics appears between the prisoner's dilemma game in a network and a threshold cascade model in the other. The threshold model is intended to abstract the behavior of a network of vigilant nodes that impose the pressure of being observed altering hence the temptation to defect of the dilemma. Cooperation or defection in the game also affects the state of a node of being vigilant. We analyze these processes on different duplex networks structures and assess the influence of the topology, average degree and correlated multiplexity, on the outcome of cooperation. Interestingly, we find that the social pressure of vigilance may impact cooperation positively or negatively, depending on the duplex structure, specifically the degree correlations between layers is determinant. Our results give further quantitative insights in the promotion of cooperation under social pressure.

  17. Evolution of cooperation under social pressure in multiplex networks.

    Science.gov (United States)

    Pereda, María

    2016-09-01

    In this work, we aim to contribute to the understanding of human prosocial behavior by studying the influence that a particular form of social pressure, "being watched," has on the evolution of cooperative behavior. We study how cooperation emerges in multiplex complex topologies by analyzing a particular bidirectionally coupled dynamics on top of a two-layer multiplex network (duplex). The coupled dynamics appears between the prisoner's dilemma game in a network and a threshold cascade model in the other. The threshold model is intended to abstract the behavior of a network of vigilant nodes that impose the pressure of being observed altering hence the temptation to defect of the dilemma. Cooperation or defection in the game also affects the state of a node of being vigilant. We analyze these processes on different duplex networks structures and assess the influence of the topology, average degree and correlated multiplexity, on the outcome of cooperation. Interestingly, we find that the social pressure of vigilance may impact cooperation positively or negatively, depending on the duplex structure, specifically the degree correlations between layers is determinant. Our results give further quantitative insights in the promotion of cooperation under social pressure.

  18. A neural network dynamics that resembles protein evolution

    Science.gov (United States)

    Ferrán, Edgardo A.; Ferrara, Pascual

    1992-06-01

    We use neutral networks to classify proteins according to their sequence similarities. A network composed by 7 × 7 neurons, was trained with the Kohonen unsupervised learning algorithm using, as inputs, matrix patterns derived from the bipeptide composition of cytochrome c proteins belonging to 76 different species. As a result of the training, the network self-organized the activation of its neurons into topologically ordered maps, wherein phylogenetically related sequences were positioned close to each other. The evolution of the topological map during learning, in a representative computational experiment, roughly resembles the way in which one species evolves into several others. For instance, sequences corresponding to vertebrates, initially grouped together into one neuron, were placed in a contiguous zone of the final neural map, with sequences of fishes, amphibia, reptiles, birds and mammals associated to different neurons. Some apparent wrong classifications are due to the fact that some proteins have a greater degree of sequence identity than the one expected by phylogenetics. In the final neural map, each synaptic vector may be considered as the pattern corresponding to the ancestor of all the proteins that are attached to that neuron. Although it may be also tempting to link real time with learning epochs and to use this relationship to calibrate the molecular evolutionary clock, this is not correct because the evolutionary time schedule obtained with the neural network depends highly on the discrete way in which the winner neighborhood is decreased during learning.

  19. Temporal Evolution Of Information In Neural Networks With Feedback

    Science.gov (United States)

    Giahi Saravani, Aram; Pitkow, Xaq

    2015-03-01

    Recurrent neural networks are pivotal for information processing in the brain. Here we analyze how the information content of a neural population is altered by dynamic feedback of a stimulus estimated from the network activity. We find that the temporal evolution of the Fisher information in the model with feedback is bounded by the Fisher information in a network of pure integrators. The available information in the feedback model saturates with a time constant and to a final level both determined by the match between the estimator weights and the feedback weights. This network then encodes signals specifically from either the beginning or the end of the stimulus presentation, depending on this match. These results are relevant to recent experimental measurements of psychophysical kernels indicating that earlier stimuli have a stronger influence on perceptual discriminations than more recent stimuli. We discuss consequences of this description for choice correlations, a measure of how individual neuronal responses relate to perceptual estimates. McNair Foundation, Baylor College of Medicine, Rice University.

  20. Recasting developmental evolution in terms of genetic pathway and network evolution ... and the implications for comparative biology.

    Science.gov (United States)

    Wilkins, Adam S

    2005-09-15

    The morphological features of complex organisms are the outcomes of developmental processes. Developmental processes, in turn, reflect the genetic networks that underlie them. Differences in morphology must ultimately, therefore, reflect differences in the underlying genetic networks. A mutation that affects a developmental process does so by affecting either a gene whose product acts as an upstream controlling element, an intermediary connecting link, or as a downstream output of the network that governs the trait's development. Although the immense diversity of gene networks in the animal and plant kingdoms would seem to preclude any general "rules" of network evolution, the material discussed here suggests that the patterns of genetic pathway and network evolution actually fall into a number of discrete modes. The potential utility of this conceptual framework in reconstructing instances of developmental evolution and for comparative neurobiology will be discussed.

  1. The Evolution of Networks in Extreme and Isolated Environment

    Science.gov (United States)

    Johnson, Jeffrey C.; Boster, James S.; Palinkas, Lawrence A.

    2000-01-01

    This article reports on the evolution of network structure as it relates to the formal and informal aspects of social roles in well bounded, isolated groups. Research was conducted at the Amundsen-Scott South Pole Station over a 3-year period. Data was collected on crewmembers' networks of social interaction and personal advice over each of the 8.5-month winters during a time of complete isolation. In addition, data was collected on informal social role structure (e.g., instrumental leadership, expressive leadership). It was hypothesized that development and maintenance of a cohesive group structure was related to the presence of and group consensus on various informal social roles. The study found that core-periphery structures (i.e., reflecting cohesion) in winter-over groups were associated with the presence of critically important informal social roles (e.g., expressive leadership) and high group consensus on such informal roles. On the other hand, the evolution of clique structures (i.e., lack of cohesion) were associated with the absence of critical roles and a lack of consensus on these roles, particularly the critically important role of instrumental leader.

  2. Generic patterns in the evolution of urban water networks: Evidence from a large Asian city

    Science.gov (United States)

    Krueger, Elisabeth; Klinkhamer, Christopher; Urich, Christian; Zhan, Xianyuan; Rao, P. Suresh C.

    2017-03-01

    We examine high-resolution urban infrastructure data using every pipe for the water distribution network (WDN) and sanitary sewer network (SSN) in a large Asian city (≈4 million residents) to explore the structure as well as the spatial and temporal evolution of these infrastructure networks. Network data were spatially disaggregated into multiple subnets to examine intracity topological differences for functional zones of the WDN and SSN, and time-stamped SSN data were examined to understand network evolution over several decades as the city expanded. Graphs were generated using a dual-mapping technique (Hierarchical Intersection Continuity Negotiation), which emphasizes the functional attributes of these networks. Network graphs for WDNs and SSNs are characterized by several network topological metrics, and a double Pareto (power-law) model approximates the node-degree distributions of both water infrastructure networks (WDN and SSN), across spatial and hierarchical scales relevant to urban settings, and throughout their temporal evolution over several decades. These results indicate that generic mechanisms govern the networks' evolution, similar to those of scale-free networks found in nature. Deviations from the general topological patterns are indicative of (1) incomplete establishment of network hierarchies and functional network evolution, (2) capacity for growth (expansion) or densification (e.g., in-fill), and (3) likely network vulnerabilities. We discuss the implications of our findings for the (re-)design of urban infrastructure networks to enhance their resilience to external and internal threats.

  3. Partial evolution based local adiabatic quantum search

    Institute of Scientific and Technical Information of China (English)

    Sun Jie; Lu Song-Feng; Liu Fang; Yang Li-Ping

    2012-01-01

    Recently,Zhang and Lu provided a quantum search algorithm based on partial adiabatic evolution,which beats the time bound of local adiabatic search when the number of marked items in the unsorted database is larger than one.Later,they found that the above two adiabatic search algorithms had the same time complexity when there is only one marked item in the database.In the present paper,following the idea of Roland and Cerf [Roland J and Cerf N J 2002Phys.Rev.A 65 042308],if within the small symmetric evolution interval defined by Zhang et al.,a local adiabatic evolution is performed instead of the original “global” one,this “new” algorithm exhibits slightly better performance,although they are progressively equivalent with M increasing.In addition,the proof of the optimality for this partial evolution based local adiabatic search when M =1 is also presented.Two other special cases of the adiabatic algorithm obtained by appropriately tuning the evolution interval of partial adiabatic evolution based quantum search,which are found to have the same phenomenon above,are also discussed.

  4. Optimal Design of Signal Controlled Road Networks Using Differential Evolution Optimization Algorithm

    Directory of Open Access Journals (Sweden)

    Huseyin Ceylan

    2013-01-01

    Full Text Available This study proposes a traffic congestion minimization model in which the traffic signal setting optimization is performed through a combined simulation-optimization model. In this model, the TRANSYT traffic simulation software is combined with Differential Evolution (DE optimization algorithm, which is based on the natural selection paradigm. In this context, the EQuilibrium Network Design (EQND problem is formulated as a bilevel programming problem in which the upper level is the minimization of the total network performance index. In the lower level, the traffic assignment problem, which represents the route choice behavior of the road users, is solved using the Path Flow Estimator (PFE as a stochastic user equilibrium assessment. The solution of the bilevel EQND problem is carried out by the proposed Differential Evolution and TRANSYT with PFE, the so-called DETRANSPFE model, on a well-known signal controlled test network. Performance of the proposed model is compared to that of two previous works where the EQND problem has been solved by Genetic-Algorithms- (GAs- and Harmony-Search- (HS- based models. Results show that the DETRANSPFE model outperforms the GA- and HS-based models in terms of the network performance index and the computational time required.

  5. Structure and evolution of a European Parliament via a network and correlation analysis

    CERN Document Server

    Puccio, Elena; Piilo, Jyrki; Tumminello, Michele

    2016-01-01

    We present a study of the network of relationships among elected members of the Finnish parliament, based on a quantitative analysis of initiative co-signatures, and its evolution over 16 years. To understand the structure of the parliament, we constructed a statistically validated network of members, based on the similarity between the patterns of initiatives they signed. We looked for communities within the network and characterized them in terms of members' attributes, such as electoral district and party. To gain insight on the nested structure of communities, we constructed a hierarchical tree of members from the correlation matrix. Afterwards, we studied parliament dynamics yearly, with a focus on correlations within and between parties, by also distinguishing between government and opposition. Finally, we investigated the role played by specific individuals, at a local level. In particular, whether they act as proponents who gather consensus, or as signers. Our results provide a quantitative background...

  6. Neural Network based Consumption Forecasting

    DEFF Research Database (Denmark)

    Madsen, Per Printz

    2016-01-01

    This paper describe a Neural Network based method for consumption forecasting. This work has been financed by the The ENCOURAGE project. The aims of The ENCOURAGE project is to develop embedded intelligence and integration technologies that will directly optimize energy use in buildings and enable...

  7. Toward next-generation optical networks: a network operator perspective based on experimental tests and economic analysis

    Science.gov (United States)

    Xiao, Xiaojun; Du, Chunsheng; Zhou, Rongsheng

    2004-04-01

    As a result of data traffic"s exponential growth, network is currently evolving from fixed circuit switched services to dynamic packet switched services, which has brought unprecedented changes to the existing transport infrastructure. It is generally agreed that automatic switched optical network (ASON) is one of the promising solutions for the next generation optical networks. In this paper, we present the results of our experimental tests and economic analysis on ASON. The intention of this paper is to present our perspective, in terms of evolution strategy toward ASON, on next generation optical networks. It is shown through experimental tests that the performance of current Pre-standard ASON enabled equipments satisfies the basic requirements of network operators and is ready for initial deployment. The results of the economic analysis show that network operators can be benefit from the deployment of ASON from three sides. Firstly, ASON can reduce the CAPEX for network expanding by integrating multiple ADM & DCS into one box. Secondly, ASON can reduce the OPEX for network operation by introducing automatic resource control scheme. Finally, ASON can increase margin revenue by providing new optical network services such as Bandwidth on Demand, optical VPN etc. Finally, the evolution strategy is proposed as our perspective toward next generation optical networks. We hope the evolution strategy introduced may be helpful for the network operators to gracefully migrate their fixed ring based legacy networks to next generation dynamic mesh based network.

  8. Analysis and evolution of air quality monitoring networks using combined statistical information indexes

    Directory of Open Access Journals (Sweden)

    Axel Osses

    2013-10-01

    Full Text Available In this work, we present combined statistical indexes for evaluating air quality monitoring networks based on concepts derived from the information theory and Kullback–Liebler divergence. More precisely, we introduce: (1 the standard measure of complementary mutual information or ‘specificity’ index; (2 a new measure of information gain or ‘representativity’ index; (3 the information gaps associated with the evolution of a network and (4 the normalised information distance used in clustering analysis. All these information concepts are illustrated by applying them to 14 yr of data collected by the air quality monitoring network in Santiago de Chile (33.5 S, 70.5 W, 500 m a.s.l.. We find that downtown stations, located in a relatively flat area of the Santiago basin, generally show high ‘representativity’ and low ‘specificity’, whereas the contrary is found for a station located in a canyon to the east of the basin, consistently with known emission and circulation patterns of Santiago. We also show interesting applications of information gain to the analysis of the evolution of a network, where the choice of background information is also discussed, and of mutual information distance to the classifications of stations. Our analyses show that information as those presented here should of course be used in a complementary way when addressing the analysis of an air quality network for planning and evaluation purposes.

  9. Network Evolution Induced by the Dynamical Rules of Two Populations

    CERN Document Server

    Platini, T

    2010-01-01

    We study the dynamical properties of a finite dynamical network composed of two interacting populations, namely; extrovert ($a$) and introvert ($b$). In our model, each group is characterized by its size ($N_a$ and $N_b$) and preferred degree ($\\kappa_a$ and $\\kappa_b\\ll\\kappa_a$). The network dynamics is governed by the competing microscopic rules of each population that consist of the creation and destruction of links. Starting from an unconnected network, we give a detailed analysis of the mean field approach which is compared to Monte Carlo simulation data. The time evolution of the restricted degrees $\\moyenne{k_{bb}}$ and $\\moyenne{k_{ab}}$ presents three time regimes and a non monotonic behavior well captured by our theory. Surprisingly, when the population size are equal $N_a=N_b$, the ratio of the restricted degree $\\theta_0=\\moyenne{k_{ab}}/\\moyenne{k_{bb}}$ appears to be an integer in the asymptotic limits of the three time regimes. For early times (defined by $t

  10. Evolution of the global virtual water trade network.

    Science.gov (United States)

    Dalin, Carole; Konar, Megan; Hanasaki, Naota; Rinaldo, Andrea; Rodriguez-Iturbe, Ignacio

    2012-04-17

    Global freshwater resources are under increasing pressure from economic development, population growth, and climate change. The international trade of water-intensive products (e.g., agricultural commodities) or virtual water trade has been suggested as a way to save water globally. We focus on the virtual water trade network associated with international food trade built with annual trade data and annual modeled virtual water content. The evolution of this network from 1986 to 2007 is analyzed and linked to trade policies, socioeconomic circumstances, and agricultural efficiency. We find that the number of trade connections and the volume of water associated with global food trade more than doubled in 22 years. Despite this growth, constant organizational features were observed in the network. However, both regional and national virtual water trade patterns significantly changed. Indeed, Asia increased its virtual water imports by more than 170%, switching from North America to South America as its main partner, whereas North America oriented to a growing intraregional trade. A dramatic rise in China's virtual water imports is associated with its increased soy imports after a domestic policy shift in 2000. Significantly, this shift has led the global soy market to save water on a global scale, but it also relies on expanding soy production in Brazil, which contributes to deforestation in the Amazon. We find that the international food trade has led to enhanced savings in global water resources over time, indicating its growing efficiency in terms of global water use.

  11. Selfish cellular networks and the evolution of complex organisms.

    Science.gov (United States)

    Kourilsky, Philippe

    2012-03-01

    Human gametogenesis takes years and involves many cellular divisions, particularly in males. Consequently, gametogenesis provides the opportunity to acquire multiple de novo mutations. A significant portion of these is likely to impact the cellular networks linking genes, proteins, RNA and metabolites, which constitute the functional units of cells. A wealth of literature shows that these individual cellular networks are complex, robust and evolvable. To some extent, they are able to monitor their own performance, and display sufficient autonomy to be termed "selfish". Their robustness is linked to quality control mechanisms which are embedded in and act upon the individual networks, thereby providing a basis for selection during gametogenesis. These selective processes are equally likely to affect cellular functions that are not gamete-specific, and the evolution of the most complex organisms, including man, is therefore likely to occur via two pathways: essential housekeeping functions would be regulated and evolve during gametogenesis within the parents before being transmitted to their progeny, while classical selection would operate on other traits of the organisms that shape their fitness with respect to the environment.

  12. Phase transitions in the evolution of gene regulatory networks

    Science.gov (United States)

    Skanata, Antun; Kussell, Edo

    The role of gene regulatory networks is to respond to environmental conditions and optimize growth of the cell. A typical example is found in bacteria, where metabolic genes are activated in response to nutrient availability, and are subsequently turned off to conserve energy when their specific substrates are depleted. However, in fluctuating environmental conditions, regulatory networks could experience strong evolutionary pressures not only to turn the right genes on and off, but also to respond optimally under a wide spectrum of fluctuation timescales. The outcome of evolution is predicted by the long-term growth rate, which differentiates between optimal strategies. Here we present an analytic computation of the long-term growth rate in randomly fluctuating environments, by using mean-field and higher order expansion in the environmental history. We find that optimal strategies correspond to distinct regions in the phase space of fluctuations, separated by first and second order phase transitions. The statistics of environmental randomness are shown to dictate the possible evolutionary modes, which either change the structure of the regulatory network abruptly, or gradually modify and tune the interactions between its components.

  13. 基于网络功能虚拟化(NFV)的IMS核心网演进%IMS Core Network Evolution Based on NFV

    Institute of Scientific and Technical Information of China (English)

    何华江; 陈丹

    2015-01-01

    Mobile core network virtualization has become a trend in the industry. As the core of service control, how can IMS be gradual y evolved from non-virtualized architecture to be an ETSI NFV compliant one? An ETSI NFV compliant IMS core requires not only software virtualization, but also integration with NFV management & orchestration which is stil under development yet. Ac-cording to deployment experience, a safe and feasible approach is to evolve IMS towards simplified NFV architecture without MANO firstly. While benefiting from virtualization, operators can also learn virtualization operation experience and get ready for NFV. Once MANO product matures, the IMS can then be evolved to an ETSI NFV compliant architecture.%移动通信核心网的虚拟化已经成为业界的趋势,作为业务控制核心的IMS该如何从非虚拟化逐步演进到符合ETSI NFV规范的虚拟化架构。完全符合ETSI NFV架构的IMS核心网不仅需要完成软件的虚拟化,还需要与NFV Manage-ment&Orchestration(MANO)进行对接,目前还不是很成熟。通过实践发现,一种稳妥可行的方法是IMS核心网先向简化的NFV架构演进,在受益虚拟化实现的基础上,累积相关运营经验。等MANO产品逐步成熟后,再完成向ETSI NFV的演进。

  14. The vertebrate Hox gene regulatory network for hindbrain segmentation: Evolution and diversification: Coupling of a Hox gene regulatory network to hindbrain segmentation is an ancient trait originating at the base of vertebrates.

    Science.gov (United States)

    Parker, Hugo J; Bronner, Marianne E; Krumlauf, Robb

    2016-06-01

    Hindbrain development is orchestrated by a vertebrate gene regulatory network that generates segmental patterning along the anterior-posterior axis via Hox genes. Here, we review analyses of vertebrate and invertebrate chordate models that inform upon the evolutionary origin and diversification of this network. Evidence from the sea lamprey reveals that the hindbrain regulatory network generates rhombomeric compartments with segmental Hox expression and an underlying Hox code. We infer that this basal feature was present in ancestral vertebrates and, as an evolutionarily constrained developmental state, is fundamentally important for patterning of the vertebrate hindbrain across diverse lineages. Despite the common ground plan, vertebrates exhibit neuroanatomical diversity in lineage-specific patterns, with different vertebrates revealing variations of Hox expression in the hindbrain that could underlie this diversification. Invertebrate chordates lack hindbrain segmentation but exhibit some conserved aspects of this network, with retinoic acid signaling playing a role in establishing nested domains of Hox expression. © 2016 WILEY Periodicals, Inc.

  15. 基于多策略差分进化算法的输电网规划%Transmission network planning based on multi-strategy differential evolution algorithm

    Institute of Scientific and Technical Information of China (English)

    聂宏展; 郑鹏飞; 于婷; 刘小满

    2013-01-01

    Differential evolution (DE) algorithm is a real number coding heuristic and global optimization of performance algorithm based on population. But the searching strategy of DE algorithm is too unitary and the local searching capability is very poor, so more mutation strategies and local optimization strategy can raise more global and local searching ability and reduce the searching time, which adapted to solving large-scale transmission network planning. Taking line investment costs, network loss cost, the over-load cost of normal operation and transmission corridor cost as objectives, and through the results of Garver -6 system and 18 node system, it can not only prove the DE algorithm and model correctness and effectiveness in transmission network planning, but also can demonstrate that the algorithm has high computing speed and convergence, which lay the foundation to the further improving of DE algorithm.%差分进化(DE)算法是一类基于种群的、具有全局优化性能的、通过实数编码的启发式算法.但差分算法搜索策略过于单一,局部搜索能力差,因此通过增加多策略变异和局部寻优策略来提升全局和局部搜索能力,同时降低搜索时间,使其适应于求解大规模输电网规划问题.采用基于线路投资费用、网损费用、正常运行时的过负荷费用及输电走廊费用的输电网规划模型,通过对Garver-6系统和18节点系统的计算,不仅验证了算法及模型应用于输电网规划的正确性和有效性,而且验证了算法具有很高的计算速度和收敛性,为DE算法的进一步改进应用打下基础.

  16. Public authority control strategy for opinion evolution in social networks

    Science.gov (United States)

    Chen, Xi; Xiong, Xi; Zhang, Minghong; Li, Wei

    2016-08-01

    This paper addresses the need to deal with and control public opinion and rumors. Existing strategies to control public opinion include degree, random, and adaptive bridge control strategies. In this paper, we use the HK model to present a public opinion control strategy based on public authority (PA). This means utilizing the influence of expert or high authority individuals whose opinions we control to obtain the optimum effect in the shortest time possible and thus reach a consensus of public opinion. Public authority (PA) is only influenced by individuals' attributes (age, economic status, and education level) and not their degree distribution; hence, in this paper, we assume that PA complies with two types of public authority distribution (normal and power-law). According to the proposed control strategy, our experiment is based on random, degree, and public authority control strategies in three different social networks (small-world, scale-free, and random) and we compare and analyze the strategies in terms of convergence time (T), final number of controlled agents (C), and comprehensive efficiency (E). We find that different network topologies and the distribution of the PA in the network can influence the final controlling effect. While the effect of PA strategy differs in different network topology structures, all structures achieve comprehensive efficiency with any kind of public authority distribution in any network. Our findings are consistent with several current sociological phenomena and show that in the process of public opinion/rumor control, considerable attention should be paid to high authority individuals.

  17. Upstream plasticity and downstream robustness in evolution of molecular networks

    Directory of Open Access Journals (Sweden)

    Eriksen Kasper

    2004-03-01

    Full Text Available Abstract Background Gene duplication followed by the functional divergence of the resulting pair of paralogous proteins is a major force shaping molecular networks in living organisms. Recent species-wide data for protein-protein interactions and transcriptional regulations allow us to assess the effect of gene duplication on robustness and plasticity of these molecular networks. Results We demonstrate that the transcriptional regulation of duplicated genes in baker's yeast Saccharomyces cerevisiae diverges fast so that on average they lose 3% of common transcription factors for every 1% divergence of their amino acid sequences. The set of protein-protein interaction partners of their protein products changes at a slower rate exhibiting a broad plateau for amino acid sequence similarity above 70%. The stability of functional roles of duplicated genes at such relatively low sequence similarity is further corroborated by their ability to substitute for each other in single gene knockout experiments in yeast and RNAi experiments in a nematode worm Caenorhabditis elegans. We also quantified the divergence rate of physical interaction neighborhoods of paralogous proteins in a bacterium Helicobacter pylori and a fly Drosophila melanogaster. However, in the absence of system-wide data on transcription factors' binding in these organisms we could not compare this rate to that of transcriptional regulation of duplicated genes. Conclusions For all molecular networks studied in this work we found that even the most distantly related paralogous proteins with amino acid sequence identities around 20% on average have more similar positions within a network than a randomly selected pair of proteins. For yeast we also found that the upstream regulation of genes evolves more rapidly than downstream functions of their protein products. This is in accordance with a view which puts regulatory changes as one of the main driving forces of the evolution. In this

  18. The evolution of metabolic networks of E. coli

    Directory of Open Access Journals (Sweden)

    Baumler David J

    2011-11-01

    genome-scale metabolic model based on conserved ortholog groups in all 16 E. coli genomes was also constructed, reflecting the conserved ancestral core of E. coli metabolism (iEco1053_core. Comparative analysis of all six strain-specific E. coli models revealed that some of the pathogenic E. coli strains possess reactions in their metabolic networks enabling higher biomass yields on glucose. Finally the lineage-specific metabolic traits were compared to the ancestral core model predictions to derive new insight into the evolution of metabolism within this species. Conclusion Our findings demonstrate that a pangenome-scale metabolic model can be used to rapidly construct additional E. coli strain-specific models, and that quantitative models of different strains of E. coli can accurately predict strain-specific phenotypes. Such pangenome and strain-specific models can be further used to engineer metabolic phenotypes of interest, such as designing new industrial E. coli strains.

  19. Good Samaritans in Networks: An Experiment on How Networks Influence Egalitarian Sharing and the Evolution of Inequality.

    Science.gov (United States)

    Chiang, Yen-Sheng

    2015-01-01

    The fact that the more resourceful people are sharing with the poor to mitigate inequality-egalitarian sharing-is well documented in the behavioral science research. How inequality evolves as a result of egalitarian sharing is determined by the structure of "who gives whom". While most prior experimental research investigates allocation of resources in dyads and groups, the paper extends the research of egalitarian sharing to networks for a more generalized structure of social interaction. An agent-based model is proposed to predict how actors, linked in networks, share their incomes with neighbors. A laboratory experiment with human subjects further shows that income distributions evolve to different states in different network topologies. Inequality is significantly reduced in networks where the very rich and the very poor are connected so that income discrepancy is salient enough to motivate the rich to share their incomes with the poor. The study suggests that social networks make a difference in how egalitarian sharing influences the evolution of inequality.

  20. Formation and Evolution of Science Knowledge Network (Ⅰ): A New Research Method Based on Co-word Network%科学知识网络的形成与演化(Ⅰ):共词网络方法的提出

    Institute of Scientific and Technical Information of China (English)

    王晓光

    2009-01-01

    知识网络观已经被情报学界普遍接受.已往的科学知识网络研究多以引文关系和合著关系为线索,其结果揭示的是科学界高阶的学科结构和智力结构,而非知识概念结构.为了在微观层面上揭示科学知识网络的形成与演化机理,我们将目光关注在了文章关键词与关键词共现关系上.通过回顾认知地图、科学知识领域绘图与共词分析三个领域的发展历史,本文提出了共词网络方法,并以此为基础分析了科学知识体系的网络结构和知识单元的增长模式.借助对共词网络的结构与演化过程的分析,本文首次从词汇维度定性解释了科学知识网络的形成与演化机理.%The vision of knowledge network has been accepted in LIS science. Most of the previous research on science knowledge network was based on citations and co-authorship, which represented the discipline structures and intelligence structures, rather than the concept structures. In order to demonstrate the formation and evolution mechanism of knowledge network from the micro aspect, we focus the paper on author keywords and co-word relationships. After a review of cognitive map, mapping knowledge domains and co-word analysis method, the paper proposes a new research method named co-word network. Based on the new method, this paper qualitatively analyzes the formation and evolution mechanism of science knowledge network and the increasing patterns of knowledge cells from the word dimension for the first time.

  1. Network fingerprint: a knowledge-based characterization of biomedical networks

    Science.gov (United States)

    Cui, Xiuliang; He, Haochen; He, Fuchu; Wang, Shengqi; Li, Fei; Bo, Xiaochen

    2015-01-01

    It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical researchers, we introduce a knowledge-based computational framework to decipher biomedical networks by making systematic comparisons to well-studied “basic networks”. A biomedical network is characterized as a spectrum-like vector called “network fingerprint”, which contains similarities to basic networks. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular networks, especially for large-scale network comparisons and clustering analyses. As an example, we extracted network fingerprints of 44 disease networks in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The comparisons among the network fingerprints of disease networks revealed informative disease-disease and disease-signaling pathway associations, illustrating that the network fingerprinting framework will lead to new approaches for better understanding of biomedical networks. PMID:26307246

  2. Power Grid Network Evolutions for Local Energy Trading

    CERN Document Server

    Pagani, Giuliano Andrea

    2012-01-01

    The shift towards a energy Grid dominated by prosumers (consumers and producers of energy) will inevitably have repercussions on the distribution infrastructure. Today it is a hierarchical one designed to deliver energy from large scale facilities to end-users. Tomorrow it will be a capillary infrastructure at the medium and Low Voltage levels that will support local energy trading among prosumers. In our previous work, we analyzed the Dutch Power Grid and made an initial analysis of the economic impact topological properties have on decentralized energy trading. In this paper, we go one step further and investigate how different networks topologies and growth models facilitate the emergence of a decentralized market. In particular, we show how the connectivity plays an important role in improving the properties of reliability and path-cost reduction. From the economic point of view, we estimate how the topological evolutions facilitate local electricity distribution, taking into account the main cost ingredi...

  3. Evolution of a vertebrate social decision-making network.

    Science.gov (United States)

    O'Connell, Lauren A; Hofmann, Hans A

    2012-06-01

    Animals evaluate and respond to their social environment with adaptive decisions. Revealing the neural mechanisms of such decisions is a major goal in biology. We analyzed expression profiles for 10 neurochemical genes across 12 brain regions important for decision-making in 88 species representing five vertebrate lineages. We found that behaviorally relevant brain regions are remarkably conserved over 450 million years of evolution. We also find evidence that different brain regions have experienced different selection pressures, because spatial distribution of neuroendocrine ligands are more flexible than their receptors across vertebrates. Our analysis suggests that the diversity of social behavior in vertebrates can be explained, in part, by variations on a theme of conserved neural and gene expression networks.

  4. Chemical and genomic evolution of enzyme-catalyzed reaction networks.

    Science.gov (United States)

    Kanehisa, Minoru

    2013-09-02

    There is a tendency that a unit of enzyme genes in an operon-like structure in the prokaryotic genome encodes enzymes that catalyze a series of consecutive reactions in a metabolic pathway. Our recent analysis shows that this and other genomic units correspond to chemical units reflecting chemical logic of organic reactions. From all known metabolic pathways in the KEGG database we identified chemical units, called reaction modules, as the conserved sequences of chemical structure transformation patterns of small molecules. The extracted patterns suggest co-evolution of genomic units and chemical units. While the core of the metabolic network may have evolved with mechanisms involving individual enzymes and reactions, its extension may have been driven by modular units of enzymes and reactions.

  5. Host Event Based Network Monitoring

    Energy Technology Data Exchange (ETDEWEB)

    Jonathan Chugg

    2013-01-01

    The purpose of INL’s research on this project is to demonstrate the feasibility of a host event based network monitoring tool and the effects on host performance. Current host based network monitoring tools work on polling which can miss activity if it occurs between polls. Instead of polling, a tool could be developed that makes use of event APIs in the operating system to receive asynchronous notifications of network activity. Analysis and logging of these events will allow the tool to construct the complete real-time and historical network configuration of the host while the tool is running. This research focused on three major operating systems commonly used by SCADA systems: Linux, WindowsXP, and Windows7. Windows 7 offers two paths that have minimal impact on the system and should be seriously considered. First is the new Windows Event Logging API, and, second, Windows 7 offers the ALE API within WFP. Any future work should focus on these methods.

  6. Evolution of a core gene network for skeletogenesis in chordates.

    Directory of Open Access Journals (Sweden)

    Jochen Hecht

    2008-03-01

    Full Text Available The skeleton is one of the most important features for the reconstruction of vertebrate phylogeny but few data are available to understand its molecular origin. In mammals the Runt genes are central regulators of skeletogenesis. Runx2 was shown to be essential for osteoblast differentiation, tooth development, and bone formation. Both Runx2 and Runx3 are essential for chondrocyte maturation. Furthermore, Runx2 directly regulates Indian hedgehog expression, a master coordinator of skeletal development. To clarify the correlation of Runt gene evolution and the emergence of cartilage and bone in vertebrates, we cloned the Runt genes from hagfish as representative of jawless fish (MgRunxA, MgRunxB and from dogfish as representative of jawed cartilaginous fish (ScRunx1-3. According to our phylogenetic reconstruction the stem species of chordates harboured a single Runt gene and thereafter Runt locus duplications occurred during early vertebrate evolution. All newly isolated Runt genes were expressed in cartilage according to quantitative PCR. In situ hybridisation confirmed high MgRunxA expression in hard cartilage of hagfish. In dogfish ScRunx2 and ScRunx3 were expressed in embryonal cartilage whereas all three Runt genes were detected in teeth and placoid scales. In cephalochordates (lancelets Runt, Hedgehog and SoxE were strongly expressed in the gill bars and expression of Runt and Hedgehog was found in endo- as well as ectodermal cells. Furthermore we demonstrate that the lancelet Runt protein binds to Runt binding sites in the lancelet Hedgehog promoter and regulates its activity. Together, these results suggest that Runt and Hedgehog were part of a core gene network for cartilage formation, which was already active in the gill bars of the common ancestor of cephalochordates and vertebrates and diversified after Runt duplications had occurred during vertebrate evolution. The similarities in expression patterns of Runt genes support the view

  7. The structure and evolution of buyer-supplier networks.

    Science.gov (United States)

    Mizuno, Takayuki; Souma, Wataru; Watanabe, Tsutomu

    2014-01-01

    In this paper, we investigate the structure and evolution of customer-supplier networks in Japan using a unique dataset that contains information on customer and supplier linkages for more than 500,000 incorporated non-financial firms for the five years from 2008 to 2012. We find, first, that the number of customer links is unequal across firms; the customer link distribution has a power-law tail with an exponent of unity (i.e., it follows Zipf's law). We interpret this as implying that competition among firms to acquire new customers yields winners with a large number of customers, as well as losers with fewer customers. We also show that the shortest path length for any pair of firms is, on average, 4.3 links. Second, we find that link switching is relatively rare. Our estimates indicate that the survival rate per year for customer links is 92 percent and for supplier links 93 percent. Third and finally, we find that firm growth rates tend to be more highly correlated the closer two firms are to each other in a customer-supplier network (i.e., the smaller is the shortest path length for the two firms). This suggests that a non-negligible portion of fluctuations in firm growth stems from the propagation of microeconomic shocks - shocks affecting only a particular firm - through customer-supplier chains.

  8. Leader's opinion priority bounded confidence model for network opinion evolution

    Science.gov (United States)

    Zhu, Meixia; Xie, Guangqiang

    2017-08-01

    Aiming at the weight of trust someone given to participate in the interaction in Hegselmann-Krause's type consensus model is the same and virtual social networks among individuals with different level of education, personal influence, etc. For differences between agents, a novelty bounded confidence model was proposed with leader's opinion considered priority. Interaction neighbors can be divided into two kinds. The first kind is made up of "opinion leaders" group, another kind is made up of ordinary people. For different groups to give different weights of trust. We also analyzed the related characteristics of the new model under the symmetrical bounded confidence parameters and combined with the classical HK model were analyzed. Simulation experiment results show that no matter the network size and initial view is subject to uniform distribution or discrete distribution. We can control the "opinion-leader" good change the number of views and values, and even improve the convergence speed. Experiment also found that the choice of "opinion leaders" is not the more the better, the model well explain how the "opinion leader" in the process of the evolution of the public opinion play the role of the leader.

  9. Predicting epidemic evolution on contact networks from partial observations

    CERN Document Server

    Bindi, Jacopo; Dall'Asta, Luca

    2016-01-01

    The massive employment of computational models in network epidemiology calls for the development of improved inference methods for epidemic forecast. For simple compartment models, such as the Susceptible-Infected-Recovered model, Belief Propagation was proved to be a reliable and efficient method to identify the origin of an observed epidemics. Here we show that the same method can be applied to predict the future evolution of an epidemic outbreak from partial observations at the early stage of the dynamics. The results obtained using Belief Propagation are compared with Monte Carlo direct sampling in the case of SIR model on random (regular and power-law) graphs for different observation methods and on an example of real-world contact network. Belief Propagation gives in general a better prediction that direct sampling, although the quality of the prediction depends on the quantity under study (e.g. marginals of individual states, epidemic size, extinction-time distribution) and on the actual number of obse...

  10. The Evolution of Social Network and the Embeddedness of Intrapreneurship Firm A Perspective Based on Dyadic Distance of Dynamic Boundary%社会网络演化与内创企业嵌入——基于动态边界二元距离的视角

    Institute of Scientific and Technical Information of China (English)

    王涛; 罗仲伟

    2011-01-01

    社会网络可以利用演化活动对网络结构进行调整以获得持续竞争力,嵌入活动则是推动内创企业进入社会网络的合适方式。社会网络和内创企业属于组织系统中不同层次的二元主体。处于高层次的社会网络会通过变异、选择、复制和保留的演化活动路径作用于企业,实现对网络边界的动态调整:处于低层次的内创企业则会通过替代嵌入和延展嵌入进入网络边界。因而.社会网络演化与内创企业嵌入之间的关联是发生在网络边界的跨层次互动.其本质是内创企业与网络边界的距离。内创企业可以利用社会网络演化的契机,通过缩短与网络边界之间的制度距离、能力距离和文化距离来实现有效嵌入.同时也反过来推动社会网络战略演化的实现。%Applied evolution, the social network achieves sustainable competition by adjusting the construct of the network. Embeddedness is an appropriate method to help intrapreneurship firm join with social network. The social network and the intrapreneurship firm are dyadic, both belonging to different levels of organizational system. The social network, belonging to the higher level, can adjust the network boundary by variation, choice, copy, and retain. And the intrapreneurship firm is of the lower level which can join network boundary by substitute embeddedness and extend embeddedness. Thus, the relationship between the evolution of social network and the embeddenss of intrapreneurship firm is cross level interaction, happened in network boundary. The essence of the cross level interaction is the distance between intrapreneurship firm and social network boundary. Therefore, based on the opportunity of the evolution of network, the intrapreneurship firm can embed into the network boundary by shortened the institutional distance, capability distance, and culture distance. In turn, the embededness promotes social network to achieve

  11. A data base for galaxy evolution modeling

    NARCIS (Netherlands)

    Leitherer, C; Alloin, D; FritzVonAlvensleben, U; Gallagher, JS; Huchra, JP; Matteucci, F; OConnell, RW; Beckman, JE; Bertelli, GP; Bica, E; Boisson, C; Bonatto, C; Bothun, GD; Bressan, A; Brodie, JP; Bruzual, G; Burstein, D; Buser, R; Caldwell, N; Casuso, E; Cervino, M; Charlot, S; Chavez, M; Chiosi, C; Christian, CA; Cuisinier, F; Dallier, R; deKoter, A; Delisle, S; Diaz, AI; Dopita, MA; Dorman, B; Fagotto, F; Fanelli, MN; Fioc, M; GarciaVargas, ML; Girardi, L; Goldader, JD; Hardy, E; Heckman, TM; Iglesias, J; Jablonka, P; Joly, M; Jones, L; Kurth, O; Lancon, A; Lejeune, T; Loxen, J; Maeder, A; Malagnini, ML; Marigo, P; MasHesse, JM; Meynet, G; Moller, CS; Molla, ML; Morossi, C; Nasi, E; Nichols, JS; Odegaard, KJR; Parker, JWM; Pastoriza, MG; Peletier, R; Robert, C; RoccaVolmerange, B; Schaerer, D; Schmidt, A; Schmitt, HR; Schommer, RA; Schmutz, W; Silva, L; Stasinska, G; Sutherland, RS; Tantalo, R; Traat, P; Vallenari, A; Vazdekis, A; Walborn, NR; Worthey, G

    1996-01-01

    This paper represents a collective effort to provide an extensive electronic data base useful for the interpretation of the spectra and evolution of galaxies. A broad variety of empirical and theoretical data is discussed here, and the data are made fully available in the AAS CD-ROM Series, Vol. 7.

  12. Large-scale transportation network congestion evolution prediction using deep learning theory.

    Science.gov (United States)

    Ma, Xiaolei; Yu, Haiyang; Wang, Yunpeng; Wang, Yinhai

    2015-01-01

    Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS) and Internet of Things (IoT), transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS) data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU)-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

  13. Large-scale transportation network congestion evolution prediction using deep learning theory.

    Directory of Open Access Journals (Sweden)

    Xiaolei Ma

    Full Text Available Understanding how congestion at one location can cause ripples throughout large-scale transportation network is vital for transportation researchers and practitioners to pinpoint traffic bottlenecks for congestion mitigation. Traditional studies rely on either mathematical equations or simulation techniques to model traffic congestion dynamics. However, most of the approaches have limitations, largely due to unrealistic assumptions and cumbersome parameter calibration process. With the development of Intelligent Transportation Systems (ITS and Internet of Things (IoT, transportation data become more and more ubiquitous. This triggers a series of data-driven research to investigate transportation phenomena. Among them, deep learning theory is considered one of the most promising techniques to tackle tremendous high-dimensional data. This study attempts to extend deep learning theory into large-scale transportation network analysis. A deep Restricted Boltzmann Machine and Recurrent Neural Network architecture is utilized to model and predict traffic congestion evolution based on Global Positioning System (GPS data from taxi. A numerical study in Ningbo, China is conducted to validate the effectiveness and efficiency of the proposed method. Results show that the prediction accuracy can achieve as high as 88% within less than 6 minutes when the model is implemented in a Graphic Processing Unit (GPU-based parallel computing environment. The predicted congestion evolution patterns can be visualized temporally and spatially through a map-based platform to identify the vulnerable links for proactive congestion mitigation.

  14. Functional evolution of the p53 regulatory network through its target response elements

    Science.gov (United States)

    Jegga, Anil G.; Inga, Alberto; Menendez, Daniel; Aronow, Bruce J.; Resnick, Michael A.

    2008-01-01

    Transcriptional network evolution is central to the development of complex biological systems. Networks can evolve through variation of master regulators and/or by changes in regulation of genes within networks. To gain insight into meaningful evolutionary differences in large networks, it is essential to address the functional consequences of sequence differences in response elements (REs) targeted by transcription factors. Using a combination of custom bioinformatics and multispecies alignment of promoter regions, we investigated the functional evolution of REs in terms of responsiveness to the sequence-specific transcription factor p53, a tumor suppressor and master regulator of stress responses. We identified REs orthologous to known p53 targets in human and rodent cells or alternatively REs related to the established p53 consensus. The orthologous REs were assigned p53 transactivation capabilities based on rules determined from model systems, and a functional heat map was developed to visually summarize conservation of sequence and relative level of responsiveness to p53 for 47 REs in 14 species. Individual REs exhibited marked differences in transactivation potentials and widespread evolutionary turnover. Functional differences were often not predicted from consensus sequence evaluations. Of the established human p53 REs analyzed, 91% had sequence conservation in at least one nonprimate species compared with 67.5% for functional conservation. Surprisingly, there was almost no conservation of functional REs for genes involved in DNA metabolism or repair between humans and rodents, suggesting important differences in p53 stress responses and cancer development. PMID:18187580

  15. Convergent evolution of modularity in metabolic networks through different community structures.

    Science.gov (United States)

    Zhou, Wanding; Nakhleh, Luay

    2012-09-14

    It has been reported that the modularity of metabolic networks of bacteria is closely related to the variability of their living habitats. However, given the dependency of the modularity score on the community structure, it remains unknown whether organisms achieve certain modularity via similar or different community structures. In this work, we studied the relationship between similarities in modularity scores and similarities in community structures of the metabolic networks of 1021 species. Both similarities are then compared against the genetic distances. We revisited the association between modularity and variability of the microbial living environments and extended the analysis to other aspects of their life style such as temperature and oxygen requirements. We also tested both topological and biological intuition of the community structures identified and investigated the extent of their conservation with respect to the taxonomy. We find that similar modularities are realized by different community structures. We find that such convergent evolution of modularity is closely associated with the number of (distinct) enzymes in the organism's metabolome, a consequence of different life styles of the species. We find that the order of modularity is the same as the order of the number of the enzymes under the classification based on the temperature preference but not on the oxygen requirement. Besides, inspection of modularity-based communities reveals that these communities are graph-theoretically meaningful yet not reflective of specific biological functions. From an evolutionary perspective, we find that the community structures are conserved only at the level of kingdoms. Our results call for more investigation into the interplay between evolution and modularity: how evolution shapes modularity, and how modularity affects evolution (mainly in terms of fitness and evolvability). Further, our results call for exploring new measures of modularity and network

  16. Convergent evolution of modularity in metabolic networks through different community structures

    Directory of Open Access Journals (Sweden)

    Zhou Wanding

    2012-09-01

    Full Text Available Abstract Background It has been reported that the modularity of metabolic networks of bacteria is closely related to the variability of their living habitats. However, given the dependency of the modularity score on the community structure, it remains unknown whether organisms achieve certain modularity via similar or different community structures. Results In this work, we studied the relationship between similarities in modularity scores and similarities in community structures of the metabolic networks of 1021 species. Both similarities are then compared against the genetic distances. We revisited the association between modularity and variability of the microbial living environments and extended the analysis to other aspects of their life style such as temperature and oxygen requirements. We also tested both topological and biological intuition of the community structures identified and investigated the extent of their conservation with respect to the taxomony. Conclusions We find that similar modularities are realized by different community structures. We find that such convergent evolution of modularity is closely associated with the number of (distinct enzymes in the organism’s metabolome, a consequence of different life styles of the species. We find that the order of modularity is the same as the order of the number of the enzymes under the classification based on the temperature preference but not on the oxygen requirement. Besides, inspection of modularity-based communities reveals that these communities are graph-theoretically meaningful yet not reflective of specific biological functions. From an evolutionary perspective, we find that the community structures are conserved only at the level of kingdoms. Our results call for more investigation into the interplay between evolution and modularity: how evolution shapes modularity, and how modularity affects evolution (mainly in terms of fitness and evolvability. Further, our results

  17. 基于非支配排序差分进化算法的多目标电网规划%Multi-objective Transmission Network Planning Based on Non-dominated Sorting Differential Evolution

    Institute of Scientific and Technical Information of China (English)

    黄映; 李扬; 高赐威

    2011-01-01

    在多目标电网规划问题中,综合考虑经济性、安全可靠性和环境影响等因素后,提出了非支配排序差分进化算法.以电网投资、运行维护费用、网损费用、线路走廊面积最小为目标建立了多目标电网规划模型.非支配排序差分进化算法将Paret0非支配排序法与差分进化算法相结合,采用动态调整策略调整差分进化算法控制参数,改进了个体拥挤比较机制,提高了算法的全局搜索能力和种群多样性,并基于模糊集理论选取最优折衷解.Garver-6节点和Garver-18节点系统算例结果表明,该算法可以有效生成分布均匀的Pareto最优解集,在求解多目标电网规划问题中具有可行性和优越性.%Considering the factors in multi-objective power network planning such as economy, security and reliability as well as environment influences, a non-dominated sorting differential evolution algorithm is proposed. Taking minimized investment for power network, operation and maintenance costs, network loss cost and line corridor as objectives, a multi-objective power network planning model is built. The non-dominated sorting differential evolution algorithm integrates Pareto non-dominated sorting algorithm with differential evolution algorithm and the control parameters of differential evolution are regulated by dynamic adjustment strategy; the crowding comparison mechanism of individuals is modified to improve the global search ability and population diversity, and the optimal compromise solution is chosen according to fuzzy set theory. Numerical results of Garver 6-bus system and Garver 18-bus system show that the proposed algorithm is better than non-dominated sorting genetic algorithm-II (NSGA-II) and can effectively generate optimal Pareto solution set, so it is of feasibility and superiority in solving multi-objective power network planning.

  18. A new approach to the automatic identification of organism evolution using neural networks.

    Science.gov (United States)

    Kasperski, Andrzej; Kasperska, Renata

    2016-01-01

    Automatic identification of organism evolution still remains a challenging task, which is especially exiting, when the evolution of human is considered. The main aim of this work is to present a new idea to allow organism evolution analysis using neural networks. Here we show that it is possible to identify evolution of any organisms in a fully automatic way using the designed EvolutionXXI program, which contains implemented neural network. The neural network has been taught using cytochrome b sequences of selected organisms. Then, analyses have been carried out for the various exemplary organisms in order to demonstrate capabilities of the EvolutionXXI program. It is shown that the presented idea allows supporting existing hypotheses, concerning evolutionary relationships between selected organisms, among others, Sirenia and elephants, hippopotami and whales, scorpions and spiders, dolphins and whales. Moreover, primate (including human), tree shrew and yeast evolution has been reconstructed.

  19. On Tree-Based Phylogenetic Networks.

    Science.gov (United States)

    Zhang, Louxin

    2016-07-01

    A large class of phylogenetic networks can be obtained from trees by the addition of horizontal edges between the tree edges. These networks are called tree-based networks. We present a simple necessary and sufficient condition for tree-based networks and prove that a universal tree-based network exists for any number of taxa that contains as its base every phylogenetic tree on the same set of taxa. This answers two problems posted by Francis and Steel recently. A byproduct is a computer program for generating random binary phylogenetic networks under the uniform distribution model.

  20. Location-Based Services in Vehicular Networks

    Science.gov (United States)

    Wu, Di

    2013-01-01

    Location-based services have been identified as a promising communication paradigm in highly mobile and dynamic vehicular networks. However, existing mobile ad hoc networking cannot be directly applied to vehicular networking due to differences in traffic conditions, mobility models and network topologies. On the other hand, hybrid architectures…

  1. Numerical study on the perception-based network formation model

    CERN Document Server

    Jo, Hang-Hyun

    2015-01-01

    In order to understand the evolution of social networks in terms of perception-based strategic link formation, we numerically study a perception-based network formation model. Here each individual is assumed to have his/her own perception of the actual network, and use it to decide whether to create a link to other individual. An individual with the least perception accuracy can benefit from updating his/her perception using that of the most accurate individual via a new link. This benefit is compared to the cost of linking in decision making. Once a new link is created, it affects the accuracies of other individuals' perceptions, leading to a further evolution of the actual network. The initial actual network and initial perceptions are modeled by Erd\\H{o}s-R\\'enyi random networks but with different linking probabilities. Then the stable link density of the actual network is found to show discontinuous transitions or jumps according to the cost of linking. The effect of initial conditions on the complexity o...

  2. Evolution of regulatory networks towards adaptability and stability in a changing environment

    Science.gov (United States)

    Lee, Deok-Sun

    2014-11-01

    Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which evolve by selectively rewiring links towards enhancing adaptability to a changing environment and stability against dynamical perturbations. We find that sparse and heterogeneous connectivity patterns emerge, which show qualitative agreement with real transcriptional regulatory networks and metabolic networks. The characteristic scaling behavior of stability reflects the balance between robustness and flexibility. The scaling of fluctuation in the perturbation spread shows a dynamic crossover, which is analyzed by investigating separately the stochasticity of internal dynamics and the network structure differences depending on the evolution pathways. Our study delineates how the ambivalent pressure of evolution shapes biological networks, which can be helpful for studying general complex systems interacting with environments.

  3. Evolution of gene network activity by tuning the strength of negative-feedback regulation.

    Science.gov (United States)

    Peng, Weilin; Liu, Ping; Xue, Yuan; Acar, Murat

    2015-02-11

    Despite the examples of protein evolution via mutations in coding sequences, we have very limited understanding on gene network evolution via changes in cis-regulatory elements. Using the galactose network as a model, here we show how the regulatory promoters of the network contribute to the evolved network activity between two yeast species. In Saccharomyces cerevisiae, we combinatorially replace all regulatory network promoters by their counterparts from Saccharomyces paradoxus, measure the resulting network inducibility profiles, and model the results. Lowering relative strength of GAL80-mediated negative feedback by replacing GAL80 promoter is necessary and sufficient to have high network inducibility levels as in S. paradoxus. This is achieved by increasing OFF-to-ON phenotypic switching rates. Competitions performed among strains with or without the GAL80 promoter replacement show strong relationships between network inducibility and fitness. Our results support the hypothesis that gene network activity can evolve by optimizing the strength of negative-feedback regulation.

  4. A Bayesian Approach to the Evolution of Metabolic Networks on a Phylogeny

    Science.gov (United States)

    Mithani, Aziz; Preston, Gail M.; Hein, Jotun

    2010-01-01

    The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions) or complex (incorporating dependencies among reactions) stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral pseudomonads. The results suggest that pathway maps that are conserved across the Pseudomonas phylogeny have a stronger neighborhood structure than those which have a variable distribution of reactions across the phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks. PMID:20700467

  5. A Bayesian approach to the evolution of metabolic networks on a phylogeny.

    Directory of Open Access Journals (Sweden)

    Aziz Mithani

    Full Text Available The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions or complex (incorporating dependencies among reactions stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral pseudomonads. The results suggest that pathway maps that are conserved across the Pseudomonas phylogeny have a stronger neighborhood structure than those which have a variable distribution of reactions across the phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks.

  6. Network based automation for SMEs

    DEFF Research Database (Denmark)

    Shahabeddini Parizi, Mohammad; Radziwon, Agnieszka

    2017-01-01

    could be obtained through network interaction. Based on two extreme cases of SMEs representing low-tech industry and an in-depth analysis of their manufacturing facilities this paper presents how collaboration between firms embedded in a regional ecosystem could result in implementation of new...... automation solutions. The empirical data collection involved application of a combination of comparative case study method with action research elements. This article provides an outlook over the challenges in implementing technological improvements and the way how it could be resolved in collaboration......, this paper develops and discusses a set of guidelines for systematic productivity improvement within an innovative collaboration in regards to automation processes in SMEs....

  7. Evolution of microcomputer-based medical instrumentation.

    Science.gov (United States)

    Tompkins, Willis J

    2009-01-01

    This paper provides a historical review of the evolution of the technologies that led to modern microcomputer-based medical instrumentation. I review the history of the microprocessor-based system because of the importance of the microprocessor in the design of modern medical instruments. I then give some examples of medical instruments in which the microprocessor has played a key role and in some cases has even empowered us to develop new instruments that were not possible before. I include a discussion of the role of the microprocessor-based personal computer in development of medical instruments.

  8. A network approach based on cliques

    Science.gov (United States)

    Fadigas, I. S.; Pereira, H. B. B.

    2013-05-01

    The characterization of complex networks is a procedure that is currently found in several research studies. Nevertheless, few studies present a discussion on networks in which the basic element is a clique. In this paper, we propose an approach based on a network of cliques. This approach consists not only of a set of new indices to capture the properties of a network of cliques but also of a method to characterize complex networks of cliques (i.e., some of the parameters are proposed to characterize the small-world phenomenon in networks of cliques). The results obtained are consistent with results from classical methods used to characterize complex networks.

  9. Comparative empirical analysis of flow-weighted transit route networks in R-space and evolution modeling

    Science.gov (United States)

    Huang, Ailing; Zang, Guangzhi; He, Zhengbing; Guan, Wei

    2017-05-01

    Urban public transit system is a typical mixed complex network with dynamic flow, and its evolution should be a process coupling topological structure with flow dynamics, which has received little attention. This paper presents the R-space to make a comparative empirical analysis on Beijing’s flow-weighted transit route network (TRN) and we found that both the Beijing’s TRNs in the year of 2011 and 2015 exhibit the scale-free properties. As such, we propose an evolution model driven by flow to simulate the development of TRNs with consideration of the passengers’ dynamical behaviors triggered by topological change. The model simulates that the evolution of TRN is an iterative process. At each time step, a certain number of new routes are generated driven by travel demands, which leads to dynamical evolution of new routes’ flow and triggers perturbation in nearby routes that will further impact the next round of opening new routes. We present the theoretical analysis based on the mean-field theory, as well as the numerical simulation for this model. The results obtained agree well with our empirical analysis results, which indicate that our model can simulate the TRN evolution with scale-free properties for distributions of node’s strength and degree. The purpose of this paper is to illustrate the global evolutional mechanism of transit network that will be used to exploit planning and design strategies for real TRNs.

  10. Isolation and evolution of labile sulfur allotropes via kinetic encapsulation in interactive porous networks

    Directory of Open Access Journals (Sweden)

    Hakuba Kitagawa

    2016-07-01

    Full Text Available The isolation and characterization of small sulfur allotropes have long remained unachievable because of their extreme lability. This study reports the first direct observation of disulfur (S2 with X-ray crystallography. Sulfur gas was kinetically trapped and frozen into the pores of two Cu-based porous coordination networks containing interactive iodide sites. Stabilization of S2 was achieved either through physisorption or chemisorption on iodide anions. One of the networks displayed shape selectivity for linear molecules only, therefore S2 was trapped and remained stable within the material at room temperature and higher. In the second network, however, the S2 molecules reacted further to produce bent-S3 species as the temperature was increased. Following the thermal evolution of the S2 species in this network using X-ray diffraction and Raman spectroscopy unveiled the generation of a new reaction intermediate never observed before, the cyclo-trisulfur dication (cyclo-S32+. It is envisaged that kinetic guest trapping in interactive crystalline porous networks will be a promising method to investigate transient chemical species.

  11. Thermal process identification based on differential evolution and RBF neural network%基于差分进化与 RBF 神经网络的热工过程辨识

    Institute of Scientific and Technical Information of China (English)

    薛晓岑; 向文国; 吕剑虹

    2014-01-01

    针对热工过程的非线性辨识问题,提出了一种基于差分进化算法( DE )的径向基函数神经网络( RBFNN)模型设计方法。该方法将DE算法的种群分解为几组并行的子种群,每组子种群对应于一类隐节点数相同的RBF网络。在RBFNN的学习过程中进行多子种群并行优化,从而实现RBF网络结构与参数的同时调整。算法可以利用热工对象的输入输出数据,自动设计出满足误差精度要求且结构较小的RBFNN模型。然后将该算法应用于热工对象的辨识,对于单输入单输出系统,得到的RBFNN模型只需1个隐节点。对于多输入单输出系统,RBF网络也仅需较少的隐层节点。仿真结果表明,用该方法设计的RBFNN模型结构简单,且辨识误差小,具有较好的泛化能力。%For the nonlinear identification of thermal process, a new radial basis function neural net-work ( RBFNN) design method is proposed based on the differential evolution algorithm ( DE) .In the method, the population in the DE algorithm is divided into several parallel subpopulations, and each subpopulation corresponds to a class of RBF network solutions with the same hidden nodes.In the RBFNN learning process, the network structure and parameters are adjusted simultaneously through the parallel optimization of the subpopulations.Under the given error limit, the algorithm can design an RBF model automatically with fewer hidden nodes according to thermal input and out-put data.Then, the algorithm is used to identify nonlinear thermal processes.For single-input sin-gle-output system identification, only one node is required in the RBFNN hidden layer.For multi-in-put single-output system identification, the RBFNN model also requires less hidden nodes.The sim-ulation results show that the proposed approach can achieve the given identification accuracy with fe-wer hidden nodes, and has good generalization ability.

  12. Networks of lexical borrowing and lateral gene transfer in language and genome evolution.

    Science.gov (United States)

    List, Johann-Mattis; Nelson-Sathi, Shijulal; Geisler, Hans; Martin, William

    2014-02-01

    Like biological species, languages change over time. As noted by Darwin, there are many parallels between language evolution and biological evolution. Insights into these parallels have also undergone change in the past 150 years. Just like genes, words change over time, and language evolution can be likened to genome evolution accordingly, but what kind of evolution? There are fundamental differences between eukaryotic and prokaryotic evolution. In the former, natural variation entails the gradual accumulation of minor mutations in alleles. In the latter, lateral gene transfer is an integral mechanism of natural variation. The study of language evolution using biological methods has attracted much interest of late, most approaches focusing on language tree construction. These approaches may underestimate the important role that borrowing plays in language evolution. Network approaches that were originally designed to study lateral gene transfer may provide more realistic insights into the complexities of language evolution.

  13. A Network Coding Based Routing Protocol for Underwater Sensor Networks

    Directory of Open Access Journals (Sweden)

    Xin Guan

    2012-04-01

    Full Text Available Due to the particularities of the underwater environment, some negative factors will seriously interfere with data transmission rates, reliability of data communication, communication range, and network throughput and energy consumption of underwater sensor networks (UWSNs. Thus, full consideration of node energy savings, while maintaining a quick, correct and effective data transmission, extending the network life cycle are essential when routing protocols for underwater sensor networks are studied. In this paper, we have proposed a novel routing algorithm for UWSNs. To increase energy consumption efficiency and extend network lifetime, we propose a time-slot based routing algorithm (TSR.We designed a probability balanced mechanism and applied it to TSR. The theory of network coding is introduced to TSBR to meet the requirement of further reducing node energy consumption and extending network lifetime. Hence, time-slot based balanced network coding (TSBNC comes into being. We evaluated the proposed time-slot based balancing routing algorithm and compared it with other classical underwater routing protocols. The simulation results show that the proposed protocol can reduce the probability of node conflicts, shorten the process of routing construction, balance energy consumption of each node and effectively prolong the network lifetime.

  14. Managerial capabilities of the home base in an intra-organisational global network

    DEFF Research Database (Denmark)

    Mykhaylenko, Alona

    of organisations towards globally dispersed network structures. For many such organisations, the home base (HB) has historically served as the center of technological and organisational knowledge, as well as the creator and manager of globally dispersed operations. However, little is known about how and when...... of the HB change in the process of its global intra-organisational network evolution. In particular, the four papers constituting this thesis investigate how global intra-organisational networks evolve, how the types of network management capabilities of the HB change along with such network evolution...... of experiential knowledge enabling the intra-organisational network evolution process, its drivers, and relationships between the parts of the model. The findings also suggest the existence of distinguishable evolutionary stages. Additionally, the resu lts indicate that changes in particular network configuration...

  15. Structure and evolution of a European Parliament via a network and correlation analysis

    Science.gov (United States)

    Puccio, Elena; Pajala, Antti; Piilo, Jyrki; Tumminello, Michele

    2016-11-01

    We present a study of the network of relationships among elected members of the Finnish parliament, based on a quantitative analysis of initiative co-signatures, and its evolution over 16 years. To understand the structure of the parliament, we constructed a statistically validated network of members, based on the similarity between the patterns of initiatives they signed. We looked for communities within the network and characterized them in terms of members' attributes, such as electoral district and party. To gain insight on the nested structure of communities, we constructed a hierarchical tree of members from the correlation matrix. Afterwards, we studied parliament dynamics yearly, with a focus on correlations within and between parties, by also distinguishing between government and opposition. Finally, we investigated the role played by specific individuals, at a local level. In particular, whether they act as proponents who gather consensus, or as signers. Our results provide a quantitative background to current theories in political science. From a methodological point of view, our network approach has proven able to highlight both local and global features of a complex social system.

  16. Network Traffic Prediction based on Particle Swarm BP Neural Network

    Directory of Open Access Journals (Sweden)

    Yan Zhu

    2013-11-01

    Full Text Available The traditional BP neural network algorithm has some bugs such that it is easy to fall into local minimum and the slow convergence speed. Particle swarm optimization is an evolutionary computation technology based on swarm intelligence which can not guarantee global convergence. Artificial Bee Colony algorithm is a global optimum algorithm with many advantages such as simple, convenient and strong robust. In this paper, a new BP neural network based on Artificial Bee Colony algorithm and particle swarm optimization algorithm is proposed to optimize the weight and threshold value of BP neural network. After network traffic prediction experiment, we can conclude that optimized BP network traffic prediction based on PSO-ABC has high prediction accuracy and has stable prediction performance.

  17. The Evolution of the Personal Networks of Novice Librarian Researchers

    Science.gov (United States)

    Kennedy, Marie R.; Kennedy, David P.; Brancolini, Kristine R.

    2017-01-01

    This article describes for the first time the composition and structure of the personal networks of novice librarian researchers. We used social network analysis to observe if participating in the Institute for Research Design in Librarianship (IRDL) affected the development of the librarians' personal networks and how the networks changed over…

  18. The Evolution of the Personal Networks of Novice Librarian Researchers

    Science.gov (United States)

    Kennedy, Marie R.; Kennedy, David P.; Brancolini, Kristine R.

    2017-01-01

    This article describes for the first time the composition and structure of the personal networks of novice librarian researchers. We used social network analysis to observe if participating in the Institute for Research Design in Librarianship (IRDL) affected the development of the librarians' personal networks and how the networks changed over…

  19. Phenotypic evolution from genetic polymorphisms in a radial network architecture

    Directory of Open Access Journals (Sweden)

    Siegel Paul B

    2007-11-01

    Full Text Available Abstract Background The genetic architecture of a quantitative trait influences the phenotypic response to natural or artificial selection. One of the main objectives of genetic mapping studies is to identify the genetic factors underlying complex traits and understand how they contribute to phenotypic expression. Presently, we are good at identifying and locating individual loci with large effects, but there is a void in describing more complex genetic architectures. Although large networks of connected genes have been reported, there is an almost complete lack of information on how polymorphisms in these networks contribute to phenotypic variation and change. To date, most of our understanding comes from theoretical, model-based studies, and it remains difficult to assess how realistic their conclusions are as they lack empirical support. Results A previous study provided evidence that nearly half of the difference in eight-week body weight between two divergently selected lines of chickens was a result of four loci organized in a 'radial' network (one central locus interacting with three 'radial' loci that, in turn, only interacted with the central locus. Here, we study the relationship between phenotypic change and genetic polymorphism in this empirically detected network. We use a model-free approach to study, through individual-based simulations, the dynamic properties of this polymorphic and epistatic genetic architecture. The study provides new insights to how epistasis can modify the selection response, buffer and reveal effects of major loci leading to a progressive release of genetic variation. We also illustrate the difficulty of predicting genetic architecture from observed selection response, and discuss mechanisms that might lead to misleading conclusions on underlying genetic architectures from quantitative trait locus (QTL experiments in selected populations. Conclusion Considering both molecular (QTL and phenotypic (selection

  20. History, Epidemic Evolution, and Model Burn-In for a Network of Annual Invasion: Soybean Rust.

    Science.gov (United States)

    Sanatkar, M R; Scoglio, C; Natarajan, B; Isard, S A; Garrett, K A

    2015-07-01

    Ecological history may be an important driver of epidemics and disease emergence. We evaluated the role of history and two related concepts, the evolution of epidemics and the burn-in period required for fitting a model to epidemic observations, for the U.S. soybean rust epidemic (caused by Phakopsora pachyrhizi). This disease allows evaluation of replicate epidemics because the pathogen reinvades the United States each year. We used a new maximum likelihood estimation approach for fitting the network model based on observed U.S. epidemics. We evaluated the model burn-in period by comparing model fit based on each combination of other years of observation. When the miss error rates were weighted by 0.9 and false alarm error rates by 0.1, the mean error rate did decline, for most years, as more years were used to construct models. Models based on observations in years closer in time to the season being estimated gave lower miss error rates for later epidemic years. The weighted mean error rate was lower in backcasting than in forecasting, reflecting how the epidemic had evolved. Ongoing epidemic evolution, and potential model failure, can occur because of changes in climate, host resistance and spatial patterns, or pathogen evolution.

  1. ENERGY AWARE NETWORK: BAYESIAN BELIEF NETWORKS BASED DECISION MANAGEMENT SYSTEM

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Chaudhari

    2011-06-01

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

  2. Dynamic Evolution in Social Cooperation Networks with Node Failure

    OpenAIRE

    Yaofeng Zhang; Renbin Xiao

    2013-01-01

    Social cooperation networks are a kind of social networks in which individuals are linked through cooperation. Interference of economic crises, natural disasters and other emergencies may cause the node fails in social cooperation networks. To further study the influences of node failure on the total fitness degree and the cooperative ratio in social cooperation networks, the update rules of individual strategy and networks self-repair are constructed on the basis of the social cooperation ne...

  3. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    Science.gov (United States)

    Liu, Fei; Zhang, Shao-Wu; Guo, Wei-Feng; Wei, Ze-Gang; Chen, Luonan

    2016-08-01

    The inference of gene regulatory networks (GRNs) from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN) methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN), to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI) to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI) significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only effectively reduce

  4. Reconstruction of social group networks from friendship networks using a tag-based model

    Science.gov (United States)

    Guan, Yuan-Pan; You, Zhi-Qiang; Han, Xiao-Pu

    2016-12-01

    Social group is a type of mesoscopic structure that connects human individuals in microscopic level and the global structure of society. In this paper, we propose a tag-based model considering that social groups expand along the edge that connects two neighbors with a similar tag of interest. The model runs on a real-world friendship network, and its simulation results show that various properties of simulated group network can well fit the empirical analysis on real-world social groups, indicating that the model catches the major mechanism driving the evolution of social groups and successfully reconstructs the social group network from a friendship network and throws light on digging of relationships between social functional organizations.

  5. Competition Based Neural Networks for Assignment Problems

    Institute of Scientific and Technical Information of China (English)

    李涛; LuyuanFang

    1991-01-01

    Competition based neural networks have been used to solve the generalized assignment problem and the quadratic assignment problem.Both problems are very difficult and are ε approximation complete.The neural network approach has yielded highly competitive performance and good performance for the quadratic assignment problem.These neural networks are guaranteed to produce feasible solutions.

  6. Durer-pentagon-based complex network

    Directory of Open Access Journals (Sweden)

    Rui Hou

    2016-04-01

    Full Text Available A novel Durer-pentagon-based complex network was constructed by adding a centre node. The properties of the complex network including the average degree, clustering coefficient, average path length, and fractal dimension were determined. The proposed complex network is small-world and fractal.

  7. Metabolism and evolution: A comparative study of reconstructed genome-level metabolic networks

    Science.gov (United States)

    Almaas, Eivind

    2008-03-01

    The availability of high-quality annotations of sequenced genomes has made it possible to generate organism-specific comprehensive maps of cellular metabolism. Currently, more than twenty such metabolic reconstructions are publicly available, with the majority focused on bacteria. A typical metabolic reconstruction for a bacterium results in a complex network containing hundreds of metabolites (nodes) and reactions (links), while some even contain more than a thousand. The constrain-based optimization approach of flux-balance analysis (FBA) is used to investigate the functional characteristics of such large-scale metabolic networks, making it possible to estimate an organism's growth behavior in a wide variety of nutrient environments, as well as its robustness to gene loss. We have recently completed the genome-level metabolic reconstruction of Yersinia pseudotuberculosis, as well as the three Yersinia pestis biovars Antiqua, Mediaevalis, and Orientalis. While Y. pseudotuberculosis typically only causes fever and abdominal pain that can mimic appendicitis, the evolutionary closely related Y. pestis strains are the aetiological agents of the bubonic plague. In this presentation, I will discuss our results and conclusions from a comparative study on the evolution of metabolic function in the four Yersiniae networks using FBA and related techniques, and I will give particular focus to the interplay between metabolic network topology and evolutionary flexibility.

  8. Dynamic Evolution of Financial Network and its Relation to Economic Crises

    Science.gov (United States)

    Gao, Ya-Chun; Wei, Zong-Wen; Wang, Bing-Hong

    2013-02-01

    The static topology properties of financial networks have been widely investigated since the work done by Mantegna, yet their dynamic evolution with time is little considered. In this paper, we comprehensively study the dynamic evolution of financial network by a sliding window technique. The vertices and edges of financial network are represented by the stocks from S&P500 components and correlations between pairs of daily returns of price fluctuation, respectively. Furthermore, the duration of stock price fluctuation, spanning from January 4, 1985 to September 14, 2009, makes us to carefully observe the relation between the dynamic topological properties and big financial crashes. The empirical results suggest that the financial network has the robust small-world property when the time evolves, and the topological structure drastically changes when the big financial crashes occur. This correspondence between the dynamic evolution of financial network and big financial crashes may provide a novel view to understand the origin of economic crisis.

  9. FLOOD ROUTING BASED ON NETWORK CODING (NCF)

    OpenAIRE

    HOSSEIN BALOOCHIAN; MOZAFAR BAGMOHAMMADI

    2010-01-01

    Most of the energy in a sensor network is used for transmission of data packets. For this reason, optimization of energy consumption is of utmost importance in these networks. This paper presents NCF, a flood routing protocol based on network coding. Simulations show that in addition to eliminating the drawbacks of traditional flooding methods, like the explosion phenomenon, NCF increases the lifetime of the network by at least 20% and decreases the number of packet transmissions. Another adv...

  10. Agent-based modeling and network dynamics

    CERN Document Server

    Namatame, Akira

    2016-01-01

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

  11. Understanding the Evolution of Industrial Symbiosis Research : A Bibliometric and Network Analysis (1997-2012)

    NARCIS (Netherlands)

    Yu, Chang; Davis, Chris; Dijkema, Gerard P. J.

    2014-01-01

    This study analyzes the evolution of the research field of industrial symbiosis (IS). We elucidate its embedding in industrial ecology (IE), trace the development of research themes, and reveal the evolution of the research network through analysis of the core literature and journals that appeared f

  12. A Stochastic Model of the Co-evolution of Networks and Strategies

    Directory of Open Access Journals (Sweden)

    Siegfried K. Berninghaus

    2009-01-01

    Full Text Available We consider a theoretical model of co-evolution of networks and strategies whose components are exclusively supported by experimental observations. We can show that a particular kind of sophisticated behavior (anticipatory better reply will result in stable population states which are most frequently visited in co-evolution experiments.

  13. Emergence, evolution and scaling of online social networks.

    Science.gov (United States)

    Wang, Le-Zhi; Huang, Zi-Gang; Rong, Zhi-Hai; Wang, Xiao-Fan; Lai, Ying-Cheng

    2014-01-01

    Online social networks have become increasingly ubiquitous and understanding their structural, dynamical, and scaling properties not only is of fundamental interest but also has a broad range of applications. Such networks can be extremely dynamic, generated almost instantaneously by, for example, breaking-news items. We investigate a common class of online social networks, the user-user retweeting networks, by analyzing the empirical data collected from Sina Weibo (a massive twitter-like microblogging social network in China) with respect to the topic of the 2011 Japan earthquake. We uncover a number of algebraic scaling relations governing the growth and structure of the network and develop a probabilistic model that captures the basic dynamical features of the system. The model is capable of reproducing all the empirical results. Our analysis not only reveals the basic mechanisms underlying the dynamics of the retweeting networks, but also provides general insights into the control of information spreading on such networks.

  14. 基于演化博弈的战略网络形成机理研究%Research on the Formation Mechanism of Strategic Network Based on Evolution Games

    Institute of Scientific and Technical Information of China (English)

    刘宇; 张敬文; 阮平南

    2011-01-01

    As a new strategic partnership network of the organizations, strategic network is increasingly becoming an important business tool for obtaining competitive advantage. Based on evolutionary games theory, this paper shows the inherent mechanism of the formation in strategic network, and obtains the ESS of strategic network in which enterprises join. Through the research, it is very important for the enterprise to choose and construct proper strategic network.%战略网络作为组织间具有战略意义的新型合作关系网络,正日益成为企业获取竞争优势的重要手段.利用演化博弈的复制动态方法.通过对战略网络形成的演化博弈构建和分析,得到企业进入战略网络的演化稳定策略(ESS),揭示了战略网络形成的内在机理.通过研究,对于战略网络的构建以及企业如何选择战略网络具有重要意义.

  15. RELAY ALGORITHM BASED ON NETWORK CODING IN WIRELESS LOCAL NETWORK

    Institute of Scientific and Technical Information of China (English)

    Wang Qi; Wang Qingshan; Wang Dongxue

    2013-01-01

    The network coding is a new technology in the field of information in 21st century.It could enhance the network throughput and save the energy consumption,and is mainly based on the single transmission rate.However,with the development of wireless network and equipment,wireless local network MAC protocols have already supported the multi-rate transmission.This paper investigates the optimal relay selection problem based on network coding.Firstly,the problem is formulated as an optimization problem.Moreover,a relay algorithm based on network coding is proposed and the transmission time gain of our algorithm over the traditional relay algorithm is analyzed.Lastly,we compare total transmission time and the energy consumption of our proposed algorithm,Network Coding with Relay Assistance (NCRA),Transmission Request (TR),and the Direct Transmission (DT) without relay algorithm by adopting IEEE 802.11b.The simulation results demonstrate that our algorithm that improves the coding opportunity by the cooperation of the relay nodes leads to the transmission time decrease of up to 17% over the traditional relay algorithms.

  16. Honeypot based Secure Network System

    Directory of Open Access Journals (Sweden)

    Yogendra Kumar Jain

    2011-02-01

    Full Text Available A honeypot is a non-production system, design to interact with cyber-attackers to collect intelligence on attack techniques and behaviors. There has been great amount of work done in the field of networkintrusion detection over the past three decades. With networks getting faster and with the increasing dependence on the Internet both at the personal and commercial level, intrusion detection becomes a challenging process. The challenge here is not only to be able to actively monitor large numbers of systems, but also to be able to react quickly to different events. Before deploying a honeypot it is advisable to have a clear idea of what the honeypot should and should not do. There should be clear understandingof the operating systems to be used and services (like a web server, ftp server etc a honeypot will run. The risks involved should be taken into consideration and methods to tackle or reduce these risks should be understood. It is also advisable to have a plan on what to do should the honeypot be compromised. In case of production honeypots, a honeypot policy addressing security issues should be documented. Any legal issues with respect to the honeypots or their functioning should also be taken into consideration. In this paper we explain the relatively new concept of “honeypot.” Honeypots are a computer specifically designed to help learn the motives, skills and techniques of the hacker community and also describes in depth the concepts of honeypots and their contribution to the field of network security. The paper then proposes and designs an intrusion detection tool based on some of the existing intrusion detection techniques and the concept of honeypots.

  17. Network Medicine: A Network-based Approach to Human Diseases

    Science.gov (United States)

    Ghiassian, Susan Dina

    With the availability of large-scale data, it is now possible to systematically study the underlying interaction maps of many complex systems in multiple disciplines. Statistical physics has a long and successful history in modeling and characterizing systems with a large number of interacting individuals. Indeed, numerous approaches that were first developed in the context of statistical physics, such as the notion of random walks and diffusion processes, have been applied successfully to study and characterize complex systems in the context of network science. Based on these tools, network science has made important contributions to our understanding of many real-world, self-organizing systems, for example in computer science, sociology and economics. Biological systems are no exception. Indeed, recent studies reflect the necessity of applying statistical and network-based approaches in order to understand complex biological systems, such as cells. In these approaches, a cell is viewed as a complex network consisting of interactions among cellular components, such as genes and proteins. Given the cellular network as a platform, machinery, functionality and failure of a cell can be studied with network-based approaches, a field known as systems biology. Here, we apply network-based approaches to explore human diseases and their associated genes within the cellular network. This dissertation is divided in three parts: (i) A systematic analysis of the connectivity patterns among disease proteins within the cellular network. The quantification of these patterns inspires the design of an algorithm which predicts a disease-specific subnetwork containing yet unknown disease associated proteins. (ii) We apply the introduced algorithm to explore the common underlying mechanism of many complex diseases. We detect a subnetwork from which inflammatory processes initiate and result in many autoimmune diseases. (iii) The last chapter of this dissertation describes the

  18. Distribution network planning algorithm based on Hopfield neural network

    Institute of Scientific and Technical Information of China (English)

    GAO Wei-xin; LUO Xian-jue

    2005-01-01

    This paper presents a new algorithm based on Hopfield neural network to find the optimal solution for an electric distribution network. This algorithm transforms the distribution power network-planning problem into a directed graph-planning problem. The Hopfield neural network is designed to decide the in-degree of each node and is in combined application with an energy function. The new algorithm doesn't need to code city streets and normalize data, so the program is easier to be realized. A case study applying the method to a district of 29 street proved that an optimal solution for the planning of such a power system could be obtained by only 26 iterations. The energy function and algorithm developed in this work have the following advantages over many existing algorithms for electric distribution network planning: fast convergence and unnecessary to code all possible lines.

  19. Evolution of biomolecular networks: lessons from metabolic and protein interactions.

    Science.gov (United States)

    Yamada, Takuji; Bork, Peer

    2009-11-01

    Despite only becoming popular at the beginning of this decade, biomolecular networks are now frameworks that facilitate many discoveries in molecular biology. The nodes of these networks are usually proteins (specifically enzymes in metabolic networks), whereas the links (or edges) are their interactions with other molecules. These networks are made up of protein-protein interactions or enzyme-enzyme interactions through shared metabolites in the case of metabolic networks. Evolutionary analysis has revealed that changes in the nodes and links in protein-protein interaction and metabolic networks are subject to different selection pressures owing to distinct topological features. However, many evolutionary constraints can be uncovered only if temporal and spatial aspects are included in the network analysis.

  20. Community Based Networks and 5G

    DEFF Research Database (Denmark)

    Williams, Idongesit

    2016-01-01

    The deployment of previous wireless standards has provided more benefits for urban dwellers than rural dwellers. 5G deployment may not be different. This paper identifies that Community Based Networks as carriers that deserve recognition as potential 5G providers may change this. The argument...... is hinged on a research aimed at understanding how and why Community Based Networks deploy telecom and Broadband infrastructure. The study was a qualitative study carried out inductively using Grounded Theory. Six cases were investigated.Two Community Based Network Mobilization models were identified....... The findings indicate that 5G connectivity can be extended to rural areas by these networks, via heterogenous networks. Hence the delivery of 5G data rates delivery via Wireless WAN in rural areas can be achieved by utilizing the causal factors of the identified models for Community Based Networks....

  1. River Flow Forecasting Using Neural Networks and Auto-Calibrated NAM Model with Shuffled Complex Evolution

    Science.gov (United States)

    Zakermoshfegh, M.; Ghodsian, M.; Salehi Neishabouri, S. A. A.; Shakiba, M.

    River flow forecasting is required to provide important information on a wide range of cases related to design and operation of river systems. Since there are a lot of parameters with uncertainties and non-linear relationships, the calibration of conceptual or physically-based models is often a difficult and time consuming procedure. So it is preferred to implement a heuristic black box model to perform a non-linear mapping between the input and output spaces without detailed consideration of the internal structure of the physical process. In this study, the capability of artificial neural networks for stream flow forecasting in Kashkan River in West of Iran is investigated and compared to a NAM model which is a lumped conceptual model with shuffled complex evolution algorithm for auto calibration. Multi Layer Perceptron and Radial Basis Function neural networks are introduced and implemented. The results show that the discharge can be more adequately forecasted by Multi Layer Perceptron neural network, compared to other implemented models, in case of both peak discharge and base flow forecasting.

  2. Finite size effects and symmetry breaking in the evolution of networks of competing Boolean nodes

    Energy Technology Data Exchange (ETDEWEB)

    Liu, M; Bassler, K E, E-mail: bassler@uh.edu [Department of Physics, University of Houston, 617 Science and Research 1, Houston, TX 77204-5005 (United States)

    2011-01-28

    Finite size effects on the evolutionary dynamics of Boolean networks are analyzed. In the model considered, Boolean networks evolve via a competition between nodes that punishes those in the majority. Previous studies have found that large networks evolve to a statistical steady state that is both critical and highly canalized, and that the evolution of canalization, which is a form of robustness found in genetic regulatory networks, is associated with a particular symmetry of the evolutionary dynamics. Here, it is found that finite size networks evolve in a fundamentally different way than infinitely large networks do. The symmetry of the evolutionary dynamics of infinitely large networks that selects for canalizing Boolean functions is broken in the evolutionary dynamics of finite size networks. In finite size networks, there is an additional selection for input-inverting Boolean functions that output a value opposite to the majority of input values. The reason for the symmetry breaking in the evolutionary dynamics is found to be due to the need for nodes in finite size networks to behave differently in order to cooperate so that the system collectively performs as efficiently as possible. The results suggest that both finite size effects and symmetry are fundamental for understanding the evolution of real-world complex networks, including genetic regulatory networks.

  3. An FDDI-based solution for the Systems Management Department Computer Laboratory Network

    OpenAIRE

    Chavez, Carlos M.

    1996-01-01

    FDDI is one of the latest evolutions in shared-media technology. Original intended as a high-speed backbone tor interconnecting networks, it has become a viable alternative tor organizations that seek better response time and bandwidth capacity from their local area networks (LANs). However, this fiber- based standard is an expensive departure from the more similar, and perhaps more mature, IEEE 802 token-ring and Ethernet standards. Thus, developing an FDDI- based network may present conside...

  4. Neuron-Based Heredity and Human Evolution

    Directory of Open Access Journals (Sweden)

    Don Marshall Gash

    2015-06-01

    Full Text Available Abstract:Abstract: It is widely recognized that human evolution has been driven by two systems of heredity: one DNA-based and the other based on the transmission of behaviorally acquired information via nervous system functions. The genetic system is ancient, going back to the appearance of life on Earth. It is responsible for the evolutionary processes described by Darwin. By comparison, the nervous system is relatively newly minted and in its highest form, responsible for ideation and mind-to-mind transmission of information. Here the informational capabilities and functions of the two systems are compared. While employing quite different mechanisms for encoding, storing and transmission of information, both systems perform these generic hereditary functions. Three additional features of neuron-based heredity in humans are identified: the ability to transfer hereditary information to other members of their population, not just progeny; a selection process for the information being transferred; and a profoundly shorter time span for creation and dissemination of survival-enhancing information in a population. The mechanisms underlying neuron-based heredity involve hippocampal neurogenesis and memory and learning processes modifying and creating new neural assemblages changing brain structure and functions. A fundamental process in rewiring brain circuitry is through increased neural activity (use strengthening and increasing the number of synaptic connections. Decreased activity in circuitry (disuse leads to loss of synapses. Use and disuse modifying an organ to bring about new modes of living, habits and functions are processes are in line with Neolamarckian concepts of evolution (Packard, 1901. Evidence is presented of bipartite evolutionary processes – Darwinian and Neolamarckian – driving human descent from a common ancestor shared with the great apes.

  5. Evolution and Controllability of Cancer Networks: A Boolean Perspective.

    Science.gov (United States)

    Srihari, Sriganesh; Raman, Venkatesh; Leong, Hon Wai; Ragan, Mark A

    2014-01-01

    Cancer forms a robust system capable of maintaining stable functioning (cell sustenance and proliferation) despite perturbations. Cancer progresses as stages over time typically with increasing aggressiveness and worsening prognosis. Characterizing these stages and identifying the genes driving transitions between them is critical to understand cancer progression and to develop effective anti-cancer therapies. In this work, we propose a novel model for the `cancer system' as a Boolean state space in which a Boolean network, built from protein-interaction and gene-expression data from different stages of cancer, transits between Boolean satisfiability states by "editing" interactions and "flipping" genes. Edits reflect rewiring of the PPI network while flipping of genes reflect activation or silencing of genes between stages. We formulate a minimization problem min flip to identify these genes driving the transitions. The application of our model (called BoolSpace) on three case studies-pancreatic and breast tumours in human and post spinal-cord injury (SCI) in rats-reveals valuable insights into the phenomenon of cancer progression: (i) interactions involved in core cell-cycle and DNA-damage repair pathways are significantly rewired in tumours, indicating significant impact to key genome-stabilizing mechanisms; (ii) several of the genes flipped are serine/threonine kinases which act as biological switches, reflecting cellular switching mechanisms between stages; and (iii) different sets of genes are flipped during the initial and final stages indicating a pattern to tumour progression. Based on these results, we hypothesize that robustness of cancer partly stems from "passing of the baton" between genes at different stages-genes from different biological processes and/or cellular components are involved in different stages of tumour progression thereby allowing tumour cells to evade targeted therapy, and therefore an effective therapy should target a "cover set" of

  6. Efficiency of the immunome protein interaction network increases during evolution.

    Science.gov (United States)

    Ortutay, Csaba; Vihinen, Mauno

    2008-04-22

    Details of the mechanisms and selection pressures that shape the emergence and development of complex biological systems, such as the human immune system, are poorly understood. A recent definition of a reference set of proteins essential for the human immunome, combined with information about protein interaction networks for these proteins, facilitates evolutionary study of this biological machinery. Here, we present a detailed study of the development of the immunome protein interaction network during eight evolutionary steps from Bilateria ancestors to human. New nodes show preferential attachment to high degree proteins. The efficiency of the immunome protein interaction network increases during the evolutionary steps, whereas the vulnerability of the network decreases. Our results shed light on selective forces acting on the emergence of biological networks. It is likely that the high efficiency and low vulnerability are intrinsic properties of many biological networks, which arise from the effects of evolutionary processes yet to be uncovered.

  7. Developmental evolution in social insects: regulatory networks from genes to societies.

    Science.gov (United States)

    Linksvayer, Timothy A; Fewell, Jennifer H; Gadau, Jürgen; Laubichler, Manfred D

    2012-05-01

    The evolution and development of complex phenotypes in social insect colonies, such as queen-worker dimorphism or division of labor, can, in our opinion, only be fully understood within an expanded mechanistic framework of Developmental Evolution. Conversely, social insects offer a fertile research area in which fundamental questions of Developmental Evolution can be addressed empirically. We review the concept of gene regulatory networks (GRNs) that aims to fully describe the battery of interacting genomic modules that are differentially expressed during the development of individual organisms. We discuss how distinct types of network models have been used to study different levels of biological organization in social insects, from GRNs to social networks. We propose that these hierarchical networks spanning different organizational levels from genes to societies should be integrated and incorporated into full GRN models to elucidate the evolutionary and developmental mechanisms underlying social insect phenotypes. Finally, we discuss prospects and approaches to achieve such an integration.

  8. Optical OFDM-based Data Center Networks

    Directory of Open Access Journals (Sweden)

    Christoforos Kachris

    2013-07-01

    Full Text Available Cloud computing and web emerging application has created the need for more powerful data centers with high performance interconnection networks.Current data center networks,based on electronic packet switches,will not be able to satisfy the required communication bandwidth of emerging applications without consuming excessive power.Optical interconnercts have gained attention recently as a promising solution offering high throughput,low latency and reduced energy cosumption compared to current networks based in commidity switches.This paper presents a novel architecture for data center networks based on optical OFDM using Wavelength Selective Swithces(WSS. The OFDM-based solution provides high throughput,reduced latency and fine grain bandwidth allocation. A heuristic algorithm for the bandwidth allocation is presented and evaluated in terms of utilization. The power analysis shows that the proposed scheme is almost 60% more energy efficient compared to the current networks based on eommodity switches.

  9. Robustness in semantic networks based on cliques

    Science.gov (United States)

    Grilo, M.; Fadigas, I. S.; Miranda, J. G. V.; Cunha, M. V.; Monteiro, R. L. S.; Pereira, H. B. B.

    2017-04-01

    Here, we present a study on how the structure of semantic networks based on cliques (specifically, article titles) behaves when vertex removal strategies (i.e., random and uniform vertex removal - RUR, highest degree vertex removal - HDR, and highest intermediation centrality vertex removal - HICR) are applied to this type of network. We propose a method for calculation of the average size of the small components and we identify the existence of a fraction (fp) where the topological structure of the network changes. Semantic networks based on cliques maintain the small-world phenomenon when subjected to RUR, HDR and HICR for fractions of removed vertices less than or equal to fp.

  10. Community Based Networks and 5G

    DEFF Research Database (Denmark)

    Williams, Idongesit

    2016-01-01

    The deployment of previous wireless standards has provided more benefits for urban dwellers than rural dwellers. 5G deployment may not be different. This paper identifies that Community Based Networks as carriers that deserve recognition as potential 5G providers may change this. The argument....... The findings indicate that 5G connectivity can be extended to rural areas by these networks, via heterogenous networks. Hence the delivery of 5G data rates delivery via Wireless WAN in rural areas can be achieved by utilizing the causal factors of the identified models for Community Based Networks....

  11. Feature-Based Classification of Networks

    CERN Document Server

    Barnett, Ian; Kuijjer, Marieke L; Mucha, Peter J; Onnela, Jukka-Pekka

    2016-01-01

    Network representations of systems from various scientific and societal domains are neither completely random nor fully regular, but instead appear to contain recurring structural building blocks. These features tend to be shared by networks belonging to the same broad class, such as the class of social networks or the class of biological networks. At a finer scale of classification within each such class, networks describing more similar systems tend to have more similar features. This occurs presumably because networks representing similar purposes or constructions would be expected to be generated by a shared set of domain specific mechanisms, and it should therefore be possible to classify these networks into categories based on their features at various structural levels. Here we describe and demonstrate a new, hybrid approach that combines manual selection of features of potential interest with existing automated classification methods. In particular, selecting well-known and well-studied features that ...

  12. Mobile Cell Selection In 4G Long Term Evolution-Advanced (LTE-A Networks

    Directory of Open Access Journals (Sweden)

    Murtadha Ali Nsaif Shukur

    2016-08-01

    Full Text Available With the high demands for broadband mobile wireless communications and the emergence of new wireless multimedia applications constitute the motivation to the development of broadband wireless access technologies in recent years. The Long Term Evolution/System Architecture Evolution (LTE/SAE system has been specified by the Third Generation Partnership Project (3GPP on the way towards fourth-generation (4G mobile to ensure 3GPP keeping the dominance of the cellular communication technologies. Through the design and optimization of new radio access techniques and a further evolution of the LTE-A systems, Cell selection is the process of determining the cell(s that provide service to each mobile station. By study the potential benefits of global cell selection versus the current local mobile SNR-based decision protocol. In particular, and present the new possibility available in OFDMA & SC-FDMA based systems, such as IEEE 802.16m and LTEAdvanced, of satisfying the minimal demand of a mobile station simultaneously by more than one base station. After formalized the problems as an optimization problem; it's present how the mobile unit establishes this connection with the strongest cell station in vicinity. To do this, the mobile unit has to overcome the challenges of estimating the channel to communicate with the cell site and frequency synchronization. Also, multiple mobile units communicate to the same receiver and from various distances. Hence, it is up to the mobile to synchronize itself appropriately to the base stations. LTE-A uses two signals, the Primary Synchronization Signal and the Secondary Synchronization Signal sequentially to determine which of the available cell sites, a mobile would lock in to it. While inter-cell interference (ICI one of problems for the downlink and uplink of multi-cell systems (in general and OFDMA& SC-FDMA networks (in particular.

  13. An Analysis of the Structure and Evolution of Networks

    Science.gov (United States)

    Hua, Guangying

    2011-01-01

    As network research receives more and more attention from both academic researchers and practitioners, network analysis has become a fast growing field attracting many researchers from diverse fields such as physics, computer science, and sociology. This dissertation provides a review of theory and research on different real data sets from the…

  14. A Novel Cluster-head Selection Algorithm Based on Hybrid Genetic Optimization for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Lejiang Guo

    2011-05-01

    Full Text Available Wireless Sensor Networks (WSN represent a new dimension in the field of network research. The cluster algorithm can significantly reduce the energy consumption of wireless sensor networks and prolong the network lifetime. This paper uses neuron to describe the WSN node and constructs neural network model for WSN. The neural network model includes three aspects: WSN node neuron model, WSN node control model and WSN node connection model. Through learning the framework of cluster algorithm for wireless sensor networks, this paper presents a weighted average of cluster-head selection algorithm based on an improved Genetic Optimization which makes the node weights directly related to the decision-making predictions. The Algorithm consists of two stages: single-parent evolution and population evolution. The initial population is formed in the stage of single-parent evolution by using gene pool, then the algorithm continues to the next further evolution process, finally the best solution will be generated and saved in the population. The simulation results illustrate that the new algorithm has the high convergence speed and good global searching capacity. It is to effectively balance the network energy consumption, improve the network life-cycle, ensure the communication quality and provide a certain theoretical foundation for the applications of the neural networks.

  15. Inference of Gene Regulatory Network Based on Local Bayesian Networks.

    Directory of Open Access Journals (Sweden)

    Fei Liu

    2016-08-01

    Full Text Available The inference of gene regulatory networks (GRNs from expression data can mine the direct regulations among genes and gain deep insights into biological processes at a network level. During past decades, numerous computational approaches have been introduced for inferring the GRNs. However, many of them still suffer from various problems, e.g., Bayesian network (BN methods cannot handle large-scale networks due to their high computational complexity, while information theory-based methods cannot identify the directions of regulatory interactions and also suffer from false positive/negative problems. To overcome the limitations, in this work we present a novel algorithm, namely local Bayesian network (LBN, to infer GRNs from gene expression data by using the network decomposition strategy and false-positive edge elimination scheme. Specifically, LBN algorithm first uses conditional mutual information (CMI to construct an initial network or GRN, which is decomposed into a number of local networks or GRNs. Then, BN method is employed to generate a series of local BNs by selecting the k-nearest neighbors of each gene as its candidate regulatory genes, which significantly reduces the exponential search space from all possible GRN structures. Integrating these local BNs forms a tentative network or GRN by performing CMI, which reduces redundant regulations in the GRN and thus alleviates the false positive problem. The final network or GRN can be obtained by iteratively performing CMI and local BN on the tentative network. In the iterative process, the false or redundant regulations are gradually removed. When tested on the benchmark GRN datasets from DREAM challenge as well as the SOS DNA repair network in E.coli, our results suggest that LBN outperforms other state-of-the-art methods (ARACNE, GENIE3 and NARROMI significantly, with more accurate and robust performance. In particular, the decomposition strategy with local Bayesian networks not only

  16. Paired Comparisons-based Interactive Differential Evolution

    CERN Document Server

    Takagi, Hideyuki

    2009-01-01

    We propose Interactive Differential Evolution (IDE) based on paired comparisons for reducing user fatigue and evaluate its convergence speed in comparison with Interactive Genetic Algorithms (IGA) and tournament IGA. User interface and convergence performance are two big keys for reducing Interactive Evolutionary Computation (IEC) user fatigue. Unlike IGA and conventional IDE, users of the proposed IDE and tournament IGA do not need to compare whole individuals each other but compare pairs of individuals, which largely decreases user fatigue. In this paper, we design a pseudo-IEC user and evaluate another factor, IEC convergence performance, using IEC simulators and show that our proposed IDE converges significantly faster than IGA and tournament IGA, i.e. our proposed one is superior to others from both user interface and convergence performance points of view.

  17. Evolution of network architecture in a granular material under compression

    Science.gov (United States)

    Papadopoulos, Lia; Puckett, James G.; Daniels, Karen E.; Bassett, Danielle S.

    2016-09-01

    As a granular material is compressed, the particles and forces within the system arrange to form complex and heterogeneous collective structures. Force chains are a prime example of such structures, and are thought to constrain bulk properties such as mechanical stability and acoustic transmission. However, capturing and characterizing the evolving nature of the intrinsic inhomogeneity and mesoscale architecture of granular systems can be challenging. A growing body of work has shown that graph theoretic approaches may provide a useful foundation for tackling these problems. Here, we extend the current approaches by utilizing multilayer networks as a framework for directly quantifying the progression of mesoscale architecture in a compressed granular system. We examine a quasi-two-dimensional aggregate of photoelastic disks, subject to biaxial compressions through a series of small, quasistatic steps. Treating particles as network nodes and interparticle forces as network edges, we construct a multilayer network for the system by linking together the series of static force networks that exist at each strain step. We then extract the inherent mesoscale structure from the system by using a generalization of community detection methods to multilayer networks, and we define quantitative measures to characterize the changes in this structure throughout the compression process. We separately consider the network of normal and tangential forces, and find that they display a different progression throughout compression. To test the sensitivity of the network model to particle properties, we examine whether the method can distinguish a subsystem of low-friction particles within a bath of higher-friction particles. We find that this can be achieved by considering the network of tangential forces, and that the community structure is better able to separate the subsystem than a purely local measure of interparticle forces alone. The results discussed throughout this study

  18. An immunity based network security risk estimation

    Institute of Scientific and Technical Information of China (English)

    LI Tao

    2005-01-01

    According to the relationship between the antibody concentration and the pathogen intrusion intensity, here we present an immunity-based model for the network security risk estimation (Insre). In Insre, the concepts and formal definitions of self,nonself, antibody, antigen and lymphocyte in the network security domain are given. Then the mathematical models of the self-tolerance, the clonal selection, the lifecycle of mature lymphocyte, immune memory and immune surveillance are established. Building upon the above models, a quantitative computation model for network security risk estimation,which is based on the calculation of antibody concentration, is thus presented. By using Insre, the types and intensity of network attacks, as well as the risk level of network security, can be calculated quantitatively and in real-time. Our theoretical analysis and experimental results show that Insre is a good solution to real-time risk evaluation for the network security.

  19. Investigating the Relationship between Topology and Evolution in a Dynamic Nematode Odor Genetic Network

    Directory of Open Access Journals (Sweden)

    David A. Fitzpatrick

    2012-01-01

    Full Text Available The relationship between biological network architectures and evolution is unclear. Within the phylum nematoda olfaction represents a critical survival tool. For nematodes, olfaction contributes to multiple processes including the finding of food, hosts, and reproductive partners, making developmental decisions, and evading predators. Here we examine a dynamic nematode odor genetic network to investigate how divergence, diversity, and contribution are shaped by network topology. Our findings describe connectivity frameworks and characteristics that correlate with molecular evolution and contribution across the olfactory network. Our data helps guide the development of a robust evolutionary description of the nematode odor network that may eventually aid in the prediction of interactive and functional qualities of novel nodes.

  20. [The motive force of evolution based on the principle of organismal adjustment evolution.].

    Science.gov (United States)

    Cao, Jia-Shu

    2010-08-01

    From the analysis of the existing problems of the prevalent theories of evolution, this paper discussed the motive force of evolution based on the knowledge of the principle of organismal adjustment evolution to get a new understanding of the evolution mechanism. In the guide of Schrodinger's theory - "life feeds on negative entropy", the author proposed that "negative entropy flow" actually includes material flow, energy flow and information flow, and the "negative entropy flow" is the motive force for living and development. By modifying my own theory of principle of organismal adjustment evolution (not adaptation evolution), a new theory of "regulation system of organismal adjustment evolution involved in DNA, RNA and protein interacting with environment" is proposed. According to the view that phylogenetic development is the "integral" of individual development, the difference of negative entropy flow between organisms and environment is considered to be a motive force for evolution, which is a new understanding of the mechanism of evolution. Based on such understanding, evolution is regarded as "a changing process that one subsystem passes all or part of its genetic information to the next generation in a larger system, and during the adaptation process produces some new elements, stops some old ones, and thereby lasts in the larger system". Some other controversial questions related to evolution are also discussed.

  1. Neutral networks of genotypes: evolution behind the curtain

    Directory of Open Access Journals (Sweden)

    Manrubia, Susanna C.

    2010-12-01

    Full Text Available Our understanding of the evolutionary process has gone a long way since the publication, 150 years ago, of “On the origin of species” by Charles R. Darwin. The XXth Century witnessed great efforts to embrace replication, mutation, and selection within the framework of a formal theory, able eventually to predict the dynamics and fate of evolving populations. However, a large body of empirical evidence collected over the last decades strongly suggests that some of the assumptions of those classical models necessitate a deep revision. The viability of organisms is not dependent on a unique and optimal genotype. The discovery of huge sets of genotypes (or neutral networks yielding the same phenotype –in the last term the same organism–, reveals that, most likely, very different functional solutions can be found, accessed and fixed in a population through low-cost exploration of the space of genomes. The “evolution behind the curtain’ may be the answer to some of the current puzzles that evolutionary theory faces, like the fast speciation process that is observed in the fossil record after very long stasis periods.

    Nuestra compresión de los procesos evolutivos ha progresado mucho desde la publicación, hace 150 años, de “El Origen de las Especies” de Charles R. Darwin. En el siglo XX se han realizado grandes esfuerzos para unificar la replicación, la mutación y la selección en el marco de una teoría formal, capaz de llegar a predecir la dinámica y el destino final de poblaciones en evolución. Sin embargo, la vasta evidencia experimental acumulada a lo largo de las últimas décadas indica, sin lugar a dudas, que algunas de las hipótesis de esos modelos clásicos necesitan una profunda revisión. La viabilidad de los organismos no depende de un único genotipo óptimo. El descubrimiento de enormes conjuntos de genotipos (o redes neutras que dan lugar al mismo fenotipo –en última instancia, al mismo organismo

  2. Simulated evolution of protein-protein interaction networks with realistic topology.

    Science.gov (United States)

    Peterson, G Jack; Pressé, Steve; Peterson, Kristin S; Dill, Ken A

    2012-01-01

    We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein's neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution.

  3. Evolution characteristics of the network core in the Facebook.

    Directory of Open Access Journals (Sweden)

    Jian-Guo Liu

    Full Text Available Statistical properties of the static networks have been extensively studied. However, online social networks are evolving dynamically, understanding the evolving characteristics of the core is one of major concerns in online social networks. In this paper, we empirically investigate the evolving characteristics of the Facebook core. Firstly, we separate the Facebook-link(FL and Facebook-wall(FW datasets into 28 snapshots in terms of timestamps. By employing the k-core decomposition method to identify the core of each snapshot, we find that the core sizes of the FL and FW networks approximately contain about 672 and 373 nodes regardless of the exponential growth of the network sizes. Secondly, we analyze evolving topological properties of the core, including the k-core value, assortative coefficient, clustering coefficient and the average shortest path length. Empirical results show that nodes in the core are getting more interconnected in the evolving process. Thirdly, we investigate the life span of nodes belonging to the core. More than 50% nodes stay in the core for more than one year, and 19% nodes always stay in the core from the first snapshot. Finally, we analyze the connections between the core and the whole network, and find that nodes belonging to the core prefer to connect nodes with high k-core values, rather than the high degrees ones. This work could provide new insights into the online social network analysis.

  4. 产学研合作创新网络时空演化模型及实证研究——基于广西2000—2013年的专利数据分析%The Time-Space Evolution Model and Empirical Research of I-U-R Cooperative Innovation Network: Based on the Analysis of Cooperative Patent Data in Guangxi from 2000 to 2013

    Institute of Scientific and Technical Information of China (English)

    刘国巍

    2015-01-01

    This paper is about to explore the collaborative evolution path of the industry-university-research (I-U-R) cooperative innovation network, which is in stages and spatial. Firstly, based on the dual perspective of life cycle and topological structure, we construct a time-space evolution model of I-U-R cooperative innovation network, and use social network to analyze spatiality of the network, measure the degree of network's order by entropy, con-firm the network's evolution path by optimal segmentation theory. Then we explore the network's evolution path based on an empirical study with the I-U-R cooperative patent data of electronic information industry in Guangxi from 2001 to 2013, and we find there are three stages of the network evolution, the chaotic formation, the unor-dered expansion and the orderly development. Therefore, we prove the scientificity and feasibility of the I-U-R coo-perative innovation network's evolution model.%为明晰产学研合作创新网络时间阶段递进和空间结构优化的协同演化路径.首先,基于生命周期和拓扑结构双重视角,构建了产学研合作创新网络时空演化模型,运用社会网络分析方法研究合作创新网络的空间状态,引入信息熵测度网络空间演化的有序度,并运用最优分割理论确定网络时空演化路径;然后,基于广西电子信息产业2001—2013年的产、学、研联合发明专利数据,实证探究广西产学研合作创新网络的时空演化路径,发现网络演化先后经历了混沌形成、无序扩张和有序发展三个阶段,据此验证了产学研合作创新网络时空演化模型的科学性和可行性.

  5. Evolution of two properties for scale-free network

    Institute of Scientific and Technical Information of China (English)

    Li Shouwei; Qian Xingsan

    2006-01-01

    Fitness of node can denote its competing power and clustering denotes the transitivity of network. Because the fitness of node is uncertain or fuzzy in some social networks, an explicit form of the degree distribution on fuzzy fitness is derived within a mean field approach. It is a weighted sum of different fuzzy fitness. It can be found that the fuzzy fitness of nodes may lead to multiscaling. Moreover, the clustering coefficient of node decays as power law and clustering coefficient of network behavior not-decrease-but-increase' phenomenon after some time. Some computer simulation results of these models illustrate these analytical results.

  6. Evolution of Weighted Networks with Exponential Aging of Sites

    Institute of Scientific and Technical Information of China (English)

    XU Xin-Jian; WU Zhi-Xi; WANG Ying-Hai

    2005-01-01

    @@ We study the growth of weighted networks with exponential aging of sites. Each new vertex of the network is connected to some old vertices with proportional (i) to the strength of the old vertex and (ii) to e-ατ, where τ is the age of the old vertex and α is a positive constant. As soon as the preferential attachment is moditied by such factors, the interesting quantities of the produced network (the vertex degree, vertex strength, clustering coefficient and average path length) will be significantly transformed.

  7. Trade networks evolution under the conditions of stock market globalization

    Directory of Open Access Journals (Sweden)

    Kopylova Olga Volodymyrivna

    2016-12-01

    Full Text Available The modern perception of the stock market in terms of information technologies rapid development and under the institutionalists influence has been significantly modified and becomes multifaceted. It was detected that the main function of the market is activated, information asymmetry is minimized and more advanced financial architecture space is formed through trade networks. Formation of the modern trade networks has started on the basis of the old infrastructure, that had the highest tendency to self-organization and adaptation. The proposed architecture of trade networks of the stock market has a very clear vector of subordination – from top to bottom and has a number of positive points.

  8. A general stochastic model for studying time evolution of transition networks

    Science.gov (United States)

    Zhan, Choujun; Tse, Chi K.; Small, Michael

    2016-12-01

    We consider a class of complex networks whose nodes assume one of several possible states at any time and may change their states from time to time. Such networks represent practical networks of rumor spreading, disease spreading, language evolution, and so on. Here, we derive a model describing the dynamics of this kind of network and a simulation algorithm for studying the network evolutionary behavior. This model, derived at a microscopic level, can reveal the transition dynamics of every node. A numerical simulation is taken as an "experiment" or "realization" of the model. We use this model to study the disease propagation dynamics in four different prototypical networks, namely, the regular nearest-neighbor (RN) network, the classical Erdös-Renyí (ER) random graph, the Watts-Strogátz small-world (SW) network, and the Barabási-Albert (BA) scalefree network. We find that the disease propagation dynamics in these four networks generally have different properties but they do share some common features. Furthermore, we utilize the transition network model to predict user growth in the Facebook network. Simulation shows that our model agrees with the historical data. The study can provide a useful tool for a more thorough understanding of the dynamics networks.

  9. Cost-effective add-drop fiber optic microcell system for CDMA cellular network evolution

    Science.gov (United States)

    Cheong, Jong M.; Ham, David; Song, Myoung H.; Son, Yong S.

    2001-10-01

    In this paper, we propose a cost effective add-drop fiber-optic microcell system for CDMA cellular network. The add-drop microcell is compatible with the existing PCS or digital cellular services (DCS) systems & networks. The proposed fiber-optic add-drop access network is independent of the different channels and gives flexibility in evolution scenarios. This add-drop network provides the optimum solution to cut-down the additional rental fees by sharing the existing fiber-optic cable for cellular/PCS service providers who want to provide third generation services.

  10. Optimal Location and Sizing of UPQC in Distribution Networks Using Differential Evolution Algorithm

    Directory of Open Access Journals (Sweden)

    Seyed Abbas Taher

    2012-01-01

    Full Text Available Differential evolution (DE algorithm is used to determine optimal location of unified power quality conditioner (UPQC considering its size in the radial distribution systems. The problem is formulated to find the optimum location of UPQC based on an objective function (OF defined for improving of voltage and current profiles, reducing power loss and minimizing the investment costs considering the OF's weighting factors. Hence, a steady-state model of UPQC is derived to set in forward/backward sweep load flow. Studies are performed on two IEEE 33-bus and 69-bus standard distribution networks. Accuracy was evaluated by reapplying the procedures using both genetic (GA and immune algorithms (IA. Comparative results indicate that DE is capable of offering a nearer global optimal in minimizing the OF and reaching all the desired conditions than GA and IA.

  11. Epidemic progression on networks based on disease generation time

    Science.gov (United States)

    Davoudi, Bahman; Moser, Flavia; Brauer, Fred; Pourbohloul, Babak

    2013-01-01

    We investigate the time evolution of disease spread on a network and present an analytical framework using the concept of disease generation time. Assuming a susceptible–infected–recovered epidemic process, this network-based framework enables us to calculate in detail the number of links (edges) within the network that are capable of producing new infectious nodes (individuals), the number of links that are not transmitting the infection further (non-transmitting links), as well as the number of contacts that individuals have with their neighbours (also known as degree distribution) within each epidemiological class, for each generation period. Using several examples, we demonstrate very good agreement between our analytical calculations and the results of computer simulations. PMID:23889499

  12. 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.

  13. How evolution affects network reciprocity in Prisoner's Dilemma

    CERN Document Server

    Cimini, Giulio

    2014-01-01

    Cooperative behavior lies at the foundations of human societies, yet why people cooperate remains a conundrum. The issue, known as network reciprocity, of whether population structure can foster cooperation in social dilemmas has been addressed by many, but theoretical studies have yielded contradictory results so far---as the problem is very sensitive to how players adapt their strategy. However, recent experiments with the prisoner's dilemma game on different networks have shown that humans do not consider neighbors' payoffs when making their decisions, and that the network structure does not influence the final outcome. In this work we carry out an extensive analysis of different evolutionary dynamics for players' strategies, showing that the absence of network reciprocity is a general feature of those dynamics that do not take neighbors' payoffs into account. Our results, together with experimental evidence, hint at how to properly model real people's behavior.

  14. Molecular networks and the evolution of human cognitive specializations

    OpenAIRE

    Fontenot, Miles; Konopka, Genevieve

    2014-01-01

    Inroads into elucidating the origins of human cognitive specializations have taken many forms, including genetic, genomic, anatomical, and behavioral assays that typically compare humans to non-human primates. While the integration of all of these approaches is essential for ultimately understanding human cognition, here, we review the usefulness of coexpression network analysis for specifically addressing this question. An increasing number of studies have incorporated coexpression networks ...

  15. Prototyping Web Services based Network Monitoring

    NARCIS (Netherlands)

    Drevers, Thomas; van de Meent, R.; Pras, Aiko; Harjo, J.; Moltchanov, D.; Silverajan, B.

    Web services is one of the emerging approaches in network management. This paper describes the design and implementation of four Web services based network monitoring prototypes. Each prototype follows a speci��?c approach to retrieve management data, ranging from retrieving a single management

  16. Dynamic QoS Provisioning for Ethernet-based Networks

    Science.gov (United States)

    Angelopoulos, J.; Kanonakis, K.; Leligou, H. C.; Orfanoudakis, Th.; Katsigiannis, M.

    2008-11-01

    The evolution towards packet-based access networks and the importance of quality of experience brings the need for access networks that support the offer of a wide range of multimedia services not currently available to the desired extent. Legacy networks based on circuit switching used explicit signalling that travelled to all nodes along the path to book resources before the launce of the media stream. This approach does not scale well and is not in line with the philosophy of packet networks. Still, the need to reserve resources in advance remains since real-time services have limited if any means of adjusting their rates to the prevailing network conditions and to preserve customer satisfaction the traditional preventive approach that needs accurate estimates of resource needs for the duration of the session is the only option. The paper describes a possible CAC solution based on measuring flows and enriches the network with implicit admission control (without obviating explicit control if available) and can manage resource allocation to protect quality-demanding services from degradation. The basis is a flow measurement system, which will estimate the traffic load produced by the flow and activate admission control. However, because in most cases these initial indication may well be misleading, it will be cross checked against a database of previously recorded flows per customer interface which can provide long term data on the flows leaving only a few cases that have to be corrected on the fly. The overall product is a self-learning autonomic system that supports QoS in the access network for services that do not communicate with the network layer such as, for example, peer-to-peer real-time multimedia applications.

  17. Transition Characteristic Analysis of Traffic Evolution Process for Urban Traffic Network

    Science.gov (United States)

    Chen, Hong; Li, Yang

    2014-01-01

    The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen's Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns. PMID:24982969

  18. Transition characteristic analysis of traffic evolution process for urban traffic network.

    Science.gov (United States)

    Wang, Longfei; Chen, Hong; Li, Yang

    2014-01-01

    The characterization of the dynamics of traffic states remains fundamental to seeking for the solutions of diverse traffic problems. To gain more insights into traffic dynamics in the temporal domain, this paper explored temporal characteristics and distinct regularity in the traffic evolution process of urban traffic network. We defined traffic state pattern through clustering multidimensional traffic time series using self-organizing maps and construct a pattern transition network model that is appropriate for representing and analyzing the evolution progress. The methodology is illustrated by an application to data flow rate of multiple road sections from Network of Shenzhen's Nanshan District, China. Analysis and numerical results demonstrated that the methodology permits extracting many useful traffic transition characteristics including stability, preference, activity, and attractiveness. In addition, more information about the relationships between these characteristics was extracted, which should be helpful in understanding the complex behavior of the temporal evolution features of traffic patterns.

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

    Science.gov (United States)

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

    2017-10-01

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

  20. Trust Based Routing in Ad Hoc Network

    Science.gov (United States)

    Talati, Mikita V.; Valiveti, Sharada; Kotecha, K.

    Ad Hoc network often termed as an infrastructure-less, self- organized or spontaneous network.The execution and survival of an ad-hoc network is solely dependent upon the cooperative and trusting nature of its nodes. However, this naive dependency on intermediate nodes makes the ad-hoc network vulnerable to passive and active attacks by malicious nodes and cause inflict severe damage. A number of protocols have been developed to secure ad-hoc networks using cryptographic schemes, but all rely on the presence of trust authority. Due to mobility of nodes and limitation of resources in wireless network one interesting research area in MANET is routing. This paper offers various trust models and trust based routing protocols to improve the trustworthiness of the neighborhood.Thus it helps in selecting the most secure and trustworthy route from the available ones for the data transfer.

  1. Model-based control of networked systems

    CERN Document Server

    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 ...

  2. Facial Beautification Method Based on Age Evolution

    Institute of Scientific and Technical Information of China (English)

    CHEN Yan; DING Shou-hong; HU Gan-le; MA Li-zhuang

    2013-01-01

    This paper proposes a new facial beautification method using facial rejuvenation based on the age evolution. Traditional facial beautification methods only focus on the color of skin and deformation and do the transformation based on an experimental standard of beauty. Our method achieves the beauty effect by making facial image looks younger, which is different from traditional methods and is more reasonable than them. Firstly, we decompose the image into different layers and get a detail layer. Secondly, we get an age-related parameter:the standard deviation of the Gaussian distribution that the detail layer follows, and the support vector machine (SVM) regression is used to fit a function about the age and the standard deviation. Thirdly, we use this function to estimate the age of input image and generate a new detail layer with a new standard deviation which is calculated by decreasing the age. Lastly, we combine the original layers and the new detail layer to get a new face image. Experimental results show that this algo-rithm can make facial image become more beautiful by facial rejuvenation. The proposed method opens up a new way about facial beautification, and there are great potentials for applications.

  3. Evolution of Intra-specific Regulatory Networks in a Multipartite Bacterial Genome.

    Directory of Open Access Journals (Sweden)

    Marco Galardini

    2015-09-01

    Full Text Available Reconstruction of the regulatory network is an important step in understanding how organisms control the expression of gene products and therefore phenotypes. Recent studies have pointed out the importance of regulatory network plasticity in bacterial adaptation and evolution. The evolution of such networks within and outside the species boundary is however still obscure. Sinorhizobium meliloti is an ideal species for such study, having three large replicons, many genomes available and a significant knowledge of its transcription factors (TF. Each replicon has a specific functional and evolutionary mark; which might also emerge from the analysis of their regulatory signatures. Here we have studied the plasticity of the regulatory network within and outside the S. meliloti species, looking for the presence of 41 TFs binding motifs in 51 strains and 5 related rhizobial species. We have detected a preference of several TFs for one of the three replicons, and the function of regulated genes was found to be in accordance with the overall replicon functional signature: house-keeping functions for the chromosome, metabolism for the chromid, symbiosis for the megaplasmid. This therefore suggests a replicon-specific wiring of the regulatory network in the S. meliloti species. At the same time a significant part of the predicted regulatory network is shared between the chromosome and the chromid, thus adding an additional layer by which the chromid integrates itself in the core genome. Furthermore, the regulatory network distance was found to be correlated with both promoter regions and accessory genome evolution inside the species, indicating that both pangenome compartments are involved in the regulatory network evolution. We also observed that genes which are not included in the species regulatory network are more likely to belong to the accessory genome, indicating that regulatory interactions should also be considered to predict gene conservation in

  4. Evolution of Intra-specific Regulatory Networks in a Multipartite Bacterial Genome.

    Science.gov (United States)

    Galardini, Marco; Brilli, Matteo; Spini, Giulia; Rossi, Matteo; Roncaglia, Bianca; Bani, Alessia; Chiancianesi, Manuela; Moretto, Marco; Engelen, Kristof; Bacci, Giovanni; Pini, Francesco; Biondi, Emanuele G; Bazzicalupo, Marco; Mengoni, Alessio

    2015-09-01

    Reconstruction of the regulatory network is an important step in understanding how organisms control the expression of gene products and therefore phenotypes. Recent studies have pointed out the importance of regulatory network plasticity in bacterial adaptation and evolution. The evolution of such networks within and outside the species boundary is however still obscure. Sinorhizobium meliloti is an ideal species for such study, having three large replicons, many genomes available and a significant knowledge of its transcription factors (TF). Each replicon has a specific functional and evolutionary mark; which might also emerge from the analysis of their regulatory signatures. Here we have studied the plasticity of the regulatory network within and outside the S. meliloti species, looking for the presence of 41 TFs binding motifs in 51 strains and 5 related rhizobial species. We have detected a preference of several TFs for one of the three replicons, and the function of regulated genes was found to be in accordance with the overall replicon functional signature: house-keeping functions for the chromosome, metabolism for the chromid, symbiosis for the megaplasmid. This therefore suggests a replicon-specific wiring of the regulatory network in the S. meliloti species. At the same time a significant part of the predicted regulatory network is shared between the chromosome and the chromid, thus adding an additional layer by which the chromid integrates itself in the core genome. Furthermore, the regulatory network distance was found to be correlated with both promoter regions and accessory genome evolution inside the species, indicating that both pangenome compartments are involved in the regulatory network evolution. We also observed that genes which are not included in the species regulatory network are more likely to belong to the accessory genome, indicating that regulatory interactions should also be considered to predict gene conservation in bacterial

  5. The evolution of generalized reciprocity on social interaction networks

    NARCIS (Netherlands)

    van Doorn, Gerrit Sander; Taborsky, Michael

    2012-01-01

    Generalized reciprocity (help anyone, if helped by someone) is a minimal strategy capable of supporting cooperation between unrelated individuals. Its simplicity makes it an attractive model to explain the evolution of reciprocal altruism in animals that lack the information or cognitive skills need

  6. Dynamics-based centrality for directed networks

    Science.gov (United States)

    Masuda, Naoki; Kori, Hiroshi

    2010-11-01

    Determining the relative importance of nodes in directed networks is important in, for example, ranking websites, publications, and sports teams, and for understanding signal flows in systems biology. A prevailing centrality measure in this respect is the PageRank. In this work, we focus on another class of centrality derived from the Laplacian of the network. We extend the Laplacian-based centrality, which has mainly been applied to strongly connected networks, to the case of general directed networks such that we can quantitatively compare arbitrary nodes. Toward this end, we adopt the idea used in the PageRank to introduce global connectivity between all the pairs of nodes with a certain strength. Numerical simulations are carried out on some networks. We also offer interpretations of the Laplacian-based centrality for general directed networks in terms of various dynamical and structural properties of networks. Importantly, the Laplacian-based centrality defined as the stationary density of the continuous-time random walk with random jumps is shown to be equivalent to the absorption probability of the random walk with sinks at each node but without random jumps. Similarly, the proposed centrality represents the importance of nodes in dynamics on the original network supplied with sinks but not with random jumps.

  7. 2D pattern evolution constrained by complex network dynamics

    CERN Document Server

    Rocha, L E C; Costa, Luciano da Fontoura; Rocha, Luis Enrique Correa da

    2006-01-01

    Complex networks have established themselves along the last years as being particularly suitable and flexible for representing and modeling several complex natural and human-made systems. At the same time in which the structural intricacies of such networks are being revealed and understood, efforts have also been directed at investigating how such connectivity properties define and constrain the dynamics of systems unfolding on such structures. However, lesser attention has been focused on hybrid systems, \\textit{i.e.} involving more than one type of network and/or dynamics. Because several real systems present such an organization (\\textit{e.g.} the dynamics of a disease coexisting with the dynamics of the immune system), it becomes important to address such hybrid systems. The current paper investigates a specific system involving a diffusive (linear and non-linear) dynamics taking place in a regular network while interacting with a complex network of defensive agents following Erd\\"os-R\\'enyi and Barab\\'a...

  8. Evolution of the mammalian embryonic pluripotency gene regulatory network

    Science.gov (United States)

    Fernandez-Tresguerres, Beatriz; Cañon, Susana; Rayon, Teresa; Pernaute, Barbara; Crespo, Miguel; Torroja, Carlos; Manzanares, Miguel

    2010-01-01

    Embryonic pluripotency in the mouse is established and maintained by a gene-regulatory network under the control of a core set of transcription factors that include octamer-binding protein 4 (Oct4; official name POU domain, class 5, transcription factor 1, Pou5f1), sex-determining region Y (SRY)-box containing gene 2 (Sox2), and homeobox protein Nanog. Although this network is largely conserved in eutherian mammals, very little information is available regarding its evolutionary conservation in other vertebrates. We have compared the embryonic pluripotency networks in mouse and chick by means of expression analysis in the pregastrulation chicken embryo, genomic comparisons, and functional assays of pluripotency-related regulatory elements in ES cells and blastocysts. We find that multiple components of the network are either novel to mammals or have acquired novel expression domains in early developmental stages of the mouse. We also find that the downstream action of the mouse core pluripotency factors is mediated largely by genomic sequence elements nonconserved with chick. In the case of Sox2 and Fgf4, we find that elements driving expression in embryonic pluripotent cells have evolved by a small number of nucleotide changes that create novel binding sites for core factors. Our results show that the network in charge of embryonic pluripotency is an evolutionary novelty of mammals that is related to the comparatively extended period during which mammalian embryonic cells need to be maintained in an undetermined state before engaging in early differentiation events. PMID:21048080

  9. Applying Model Based Systems Engineering to NASA's Space Communications Networks

    Science.gov (United States)

    Bhasin, Kul; Barnes, Patrick; Reinert, Jessica; Golden, Bert

    2013-01-01

    System engineering practices for complex systems and networks now require that requirement, architecture, and concept of operations product development teams, simultaneously harmonize their activities to provide timely, useful and cost-effective products. When dealing with complex systems of systems, traditional systems engineering methodology quickly falls short of achieving project objectives. This approach is encumbered by the use of a number of disparate hardware and software tools, spreadsheets and documents to grasp the concept of the network design and operation. In case of NASA's space communication networks, since the networks are geographically distributed, and so are its subject matter experts, the team is challenged to create a common language and tools to produce its products. Using Model Based Systems Engineering methods and tools allows for a unified representation of the system in a model that enables a highly related level of detail. To date, Program System Engineering (PSE) team has been able to model each network from their top-level operational activities and system functions down to the atomic level through relational modeling decomposition. These models allow for a better understanding of the relationships between NASA's stakeholders, internal organizations, and impacts to all related entities due to integration and sustainment of existing systems. Understanding the existing systems is essential to accurate and detailed study of integration options being considered. In this paper, we identify the challenges the PSE team faced in its quest to unify complex legacy space communications networks and their operational processes. We describe the initial approaches undertaken and the evolution toward model based system engineering applied to produce Space Communication and Navigation (SCaN) PSE products. We will demonstrate the practice of Model Based System Engineering applied to integrating space communication networks and the summary of its

  10. Systems Engineering Education Based on Evolutional Project-Based Learning

    Science.gov (United States)

    Inoue, Masahiro; Hasegawa, Hiroshi

    The knowledge and skills in systems engineering including project management are necessary for engineers who are engaged in planning and developing systems. Experiences of project execution are necessary for understanding systems engineering. Challenge is how to teach systems engineering to students who have scarce project experiences. In the education, giving the experience including a real experience and a pseudo-experience will be indispensable. In this paper, systems engineering education by evolutional Project-Based Learning (PBL) is designed and evaluated. In curriculum, exercises and lectures are executed alternately and evolutionally in three steps of PBLs ; Workshop of System Thinking, mathematical knowledge and technique are delivered in the first step PBL. Techniques of systems engineering are provided in the second step PBL. Finally project management is obtained in the third step PBL. Execution and evaluation of the education show that the Evolutional Project-Based Learning of systems engineering is effective not only to improve knowledge and experience of students but also to motivate students to study systems engineering.

  11. Clustering in mobile ad hoc network based on neural network

    Institute of Scientific and Technical Information of China (English)

    CHEN Ai-bin; CAI Zi-xing; HU De-wen

    2006-01-01

    An on-demand distributed clustering algorithm based on neural network was proposed. The system parameters and the combined weight for each node were computed, and cluster-heads were chosen using the weighted clustering algorithm, then a training set was created and a neural network was trained. In this algorithm, several system parameters were taken into account, such as the ideal node-degree, the transmission power, the mobility and the battery power of the nodes. The algorithm can be used directly to test whether a node is a cluster-head or not. Moreover, the clusters recreation can be speeded up.

  12. Adaptive topology evolution in information-sharing social networks

    CERN Document Server

    Chen, Duanbing; Lu, Linyuan; Medo, Matus; Zhang, Yi-Cheng; Zhou, Tao

    2011-01-01

    The advent of Internet and World Wide Web has led to unprecedent growth of the information available. People usually face the information overload by following a limited number of sources which best fit their interests. In order to get the picture it is important to address issues like who people do follow and how they search for better information sources. In this work we conduct an empirical analysis on different on-line social networking sites, and draw inspiration from its results to present different source selection strategies in an adaptive model for social recommendation. We show that local search rules which enhance the typical topological features of real social communities give rise to network configurations that are globally optimal. Hence these abstract rules help to create networks which are both effective in information diffusion and people friendly.

  13. Network homophily and the evolution of the pay-it-forward reciprocity.

    Science.gov (United States)

    Chiang, Yen-Sheng; Takahashi, Nobuyuki

    2011-01-01

    The pay-it-forward reciprocity is a type of cooperative behavior that people who have benefited from others return favors to third parties other than the benefactors, thus pushing forward a cascade of kindness. The phenomenon of the pay-it-forward reciprocity is ubiquitous, yet how it evolves to be part of human sociality has not been fully understood. We develop an evolutionary dynamics model to investigate how network homophily influences the evolution of the pay-it-forward reciprocity. Manipulating the extent to which actors carrying the same behavioral trait are linked in networks, the computer simulation model shows that strong network homophily helps consolidate the adaptive advantage of cooperation, yet introducing some heterophily to the formation of network helps advance cooperation's scale further. Our model enriches the literature of inclusive fitness theory by demonstrating the conditions under which cooperation or reciprocity can be selected for in evolution when social interaction is not confined exclusively to relatives.

  14. Modeling community succession and assembly: A novel method for network evolution

    Directory of Open Access Journals (Sweden)

    WenJun Zhang

    2012-06-01

    Full Text Available The process of modeling community succession and assembly is in some sense a method for network evolution, as done by Barabasi and Albert (1999. It is also one of the methods to create a sample networkfrom the statistic network I proposed earlier. I think that the mechanism of network evolution supposed by Barabasi and Albert is most likely applicable to the natural phenomena with emergency property. For natural phenomena without emergency property, the present study indicated that a scale-free network may be produced through a new mechanism, i.e., whether the connection of a taxon x occurs, dependent on the type and property of taxon y (in particular, the degree of its direct correlation with x to be connected but not necessarily the existing number of connections of taxon y, as proposed in present study.

  15. Network homophily and the evolution of the pay-it-forward reciprocity.

    Directory of Open Access Journals (Sweden)

    Yen-Sheng Chiang

    Full Text Available The pay-it-forward reciprocity is a type of cooperative behavior that people who have benefited from others return favors to third parties other than the benefactors, thus pushing forward a cascade of kindness. The phenomenon of the pay-it-forward reciprocity is ubiquitous, yet how it evolves to be part of human sociality has not been fully understood. We develop an evolutionary dynamics model to investigate how network homophily influences the evolution of the pay-it-forward reciprocity. Manipulating the extent to which actors carrying the same behavioral trait are linked in networks, the computer simulation model shows that strong network homophily helps consolidate the adaptive advantage of cooperation, yet introducing some heterophily to the formation of network helps advance cooperation's scale further. Our model enriches the literature of inclusive fitness theory by demonstrating the conditions under which cooperation or reciprocity can be selected for in evolution when social interaction is not confined exclusively to relatives.

  16. Building a Network Based Laboratory Environment

    Directory of Open Access Journals (Sweden)

    Sea Shuan Luo

    2009-12-01

    Full Text Available This paper presents a comparative study about the development of a network based laboratory environment in the “Unix introduction” course for the undergraduate students. The study results and the response from the students from 2005 to 2006 will be used to better understand what kind of method is more suitable for students. We also use the data collected to adjust our teaching strategy and try to build up a network based laboratory environment.

  17. A Developed Network Layer Handover Based Wireless Networks

    Directory of Open Access Journals (Sweden)

    Ali Safa Sadiq

    2015-02-01

    Full Text Available This paper proposes an Advanced Mobility Handover (AMH scheme based on Wireless Local Area Networks (WLANs by developing a network layer handover procedure which triggers messages to be sent to the next access point. The proposed AMH scheme performs the network handover process, which is represented by binding update procedure in advance during the time mobile node is still connected to the current AP in the link layer. Furthermore, a unique home IPv6 address is developed to maintain an IP communication with other corresponding nodes without a care-of-address during mobile node$'$s roaming process. This can contribute significantly to reducing network layer handover delays and signaling costs by eliminate the process of obtaining a new care-of-address and processing the handover of network layer in advance while the mobile node is still communicating with the current access point. Eventually, the conducted OMNET++ simulated scenario shows that the proposed AMH scheme performs the best in terms of reducing the handover delay as compared to the state of the art.

  18. Evolution of Cooperation in Continuous Prisoner's Dilemma Games on Barabasi—Albert Networks with Degree-Dependent Guilt Mechanism

    Science.gov (United States)

    Wang, Xian-Jia; Quan, Ji; Liu, Wei-Bing

    2012-05-01

    This paper studies the continuous prisoner's dilemma games (CPDG) on Barabasi—Albert (BA) networks. In the model, each agent on a vertex of the networks makes an investment and interacts with all of his neighboring agents. Making an investment is costly, but which benefits its neighboring agents, where benefit and cost depend on the level of investment made. The payoff of each agent is given by the sum of payoffs it receives in its interactions with all its neighbors. Not only payoff, individual's guilty emotion in the games has also been considered. The negative guilty emotion produced in comparing with its neighbors can reduce the utility of individuals directly. We assume that the reduction amount depends on the individual's degree and a baseline level parameter. The group's cooperative level is characterized by the average investment of the population. Each player makes his investment in the next step based on a convex combination of the investment of his best neighbors in the last step, his best history strategies in the latest steps which number is controlled by a memory length parameter, and a uniformly distributed random number. Simulation results show that this degree-dependent guilt mechanism can promote the evolution of cooperation dramatically comparing with degree-independent guilt or no guilt cases. Imitation, memory, uncertainty coefficients and network structure also play determinant roles in the cooperation level of the population. All our results may shed some new light on studying the evolution of cooperation based on network reciprocity mechanisms.

  19. The Evolution of IDS Solutions in Wireless Ad-Hoc Networks To Wireless Mesh Networks

    Directory of Open Access Journals (Sweden)

    Novarun Deb

    2011-12-01

    Full Text Available The domain of wireless networks is inherently vulnerable to attacks due to the unreliable wireless medium. Such networks can be secured from intrusions using either prevention or detection schemes. This paper focuses its study on intrusion detection rather than prevention of attacks. As attackers keep onimprovising too, an active prevention method alone cannot provide total security to the system. Here in lies the importance of intrusion detection systems (IDS that are solely designed to detect intrusions in real time. Wireless networks are broadly classified into Wireless Ad-hoc Networks (WAHNs, Mobile Adhoc Networks (MANETs, Wireless Sensor Networks (WSNs and the most recent Wireless Mesh Networks (WMNs. Several IDS solutions have been proposed for these networks. This paper is an extension to a survey of IDS solutions for MANETs and WMNs published earlier in the sense that the present survey offers a comparative insight of recent IDS solutions for all the sub domains of wireless networks.

  20. A Complex Network Analysis of Granular Fabric Evolution in Three-Dimensions

    Science.gov (United States)

    2011-01-01

    fundamental significance to geomechanics and, more broadly, to geotechnical engineering analysis and design. As with other complex systems, the behavior of...formalism of Com- plex Networks and only recently have there been attempts to characterize granular networks that arise in geomechanical settings. We...J. Shi, and T. Tshaikiwsky. Stress-dilatancy and force chain evolution. International Journal for Numerical and Analytical Methods in Geomechanics

  1. Stochastic signalling rewires the interaction map of a multiple feedback network during yeast evolution

    OpenAIRE

    2012-01-01

    During evolution, genetic networks are rewired through strengthening or weakening their interactions to develop new regulatory schemes. In the galactose network, the GAL1/GAL3 paralogues and the GAL2 gene enhance their own expression mediated by the Gal4p transcriptional activator. The wiring strength in these feedback loops is set by the number of Gal4p binding sites. Here we show using synthetic circuits that multiplying the binding sites increases the expression of a gene under the direct ...

  2. Deconvoluting lung evolution: from phenotypes to gene regulatory networks

    DEFF Research Database (Denmark)

    Torday, J.S.; Rehan, V.K.; Hicks, J.W.

    2007-01-01

    Speakers in this symposium presented examples of respiratory regulation that broadly illustrate principles of evolution from whole organ to genes. The swim bladder and lungs of aquatic and terrestrial organisms arose independently from a common primordial "respiratory pharynx" but not from each...... other. Pathways of lung evolution are similar between crocodiles and birds but a low compliance of mammalian lung may have driven the development of the diaphragm to permit lung inflation during inspiration. To meet the high oxygen demands of flight, bird lungs have evolved separate gas exchange...... diffusing capacities than required by their oxygen consumption. The "primitive" central admixture of oxygenated and deoxygenated blood in the incompletely divided reptilian heart is actually co-regulated with other autonomic cardiopulmonary responses to provide flexible control of arterial oxygen tension...

  3. The emergence of groups in the evolution of friendship networks

    NARCIS (Netherlands)

    Zeggelink, Evelien P.H.; Stokman, Frans N.; Bunt, Gerhard G. van der

    1996-01-01

    Friendship networks usually show a certain degree of segmentation: subgroups of friends. The explanation of the emergence of such groups from initially dyadic pair friendships is a difficult but important problem. In this paper we attempt to provide a first contribution to the explanation of subgrou

  4. The Emergence Of Groups In The Evolution Of Friendship Networks

    NARCIS (Netherlands)

    Zeggelink, Evelien P.H.; Stokman, Frans N.; Bunt, Gerhard G. van der

    1997-01-01

    Friendship networks usually show a certain degree of segmentation: subgroups of friends. The explanation of the emergence of such groups from initially dyadic pair friendships is a diflicult but important problem. In this paper we attempt to provide a first contribution to the explanation of subgrou

  5. Remote radio heads and the evolution towards 4G networks

    DEFF Research Database (Denmark)

    Lanzani, Christian; Kardaras, Georgios; Boppana, Deepak

    2009-01-01

    , and WiMAX standards and advanced software configurability are key features in the deployment of more flexible and energy-efficient radio networks. This white paper describes the key market and technology requirements for RRHs and how Radiocomps state-of-the-art WiMAX/LTE RRH and intellectual property (IP...

  6. Remote radio heads and the evolution towards 4G networks

    DEFF Research Database (Denmark)

    Lanzani, Christian; Kardaras, Georgios; Boppana, Deepak

    2009-01-01

    , and WiMAX standards and advanced software configurability are key features in the deployment of more flexible and energy-efficient radio networks. This white paper describes the key market and technology requirements for RRHs and how Radiocomps state-of-the-art WiMAX/LTE RRH and intellectual property (IP...

  7. Co-evolution of conventions and networks : an experimental study

    NARCIS (Netherlands)

    Corten, R.; Buskens, V.W.

    2010-01-01

    We study the emergence of conventions in dynamic networks experimentally. Conventions are modeled in terms of coordination games in which actors can choose both their behavior and their interaction partners. We study how macro-level outcomes of the process in terms of Pareto-efficiency and heterogen

  8. Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: Based on two-mode affiliation network

    Science.gov (United States)

    Li, Huajiao; An, Haizhong; Wang, Yue; Huang, Jiachen; Gao, Xiangyun

    2016-05-01

    Keeping abreast of trends in the articles and rapidly grasping a body of article's key points and relationship from a holistic perspective is a new challenge in both literature research and text mining. As the important component, keywords can present the core idea of the academic article. Usually, articles on a single theme or area could share one or some same keywords, and we can analyze topological features and evolution of the articles co-keyword networks and keywords co-occurrence networks to realize the in-depth analysis of the articles. This paper seeks to integrate statistics, text mining, complex networks and visualization to analyze all of the academic articles on one given theme, complex network(s). All 5944 "complex networks" articles that were published between 1990 and 2013 and are available on the Web of Science are extracted. Based on the two-mode affiliation network theory, a new frontier of complex networks, we constructed two different networks, one taking the articles as nodes, the co-keyword relationships as edges and the quantity of co-keywords as the weight to construct articles co-keyword network, and another taking the articles' keywords as nodes, the co-occurrence relationships as edges and the quantity of simultaneous co-occurrences as the weight to construct keyword co-occurrence network. An integrated method for analyzing the topological features and evolution of the articles co-keyword network and keywords co-occurrence networks is proposed, and we also defined a new function to measure the innovation coefficient of the articles in annual level. This paper provides a useful tool and process for successfully achieving in-depth analysis and rapid understanding of the trends and relationships of articles in a holistic perspective.

  9. The quantization of river network morphology based on the Tokunaga network

    Institute of Scientific and Technical Information of China (English)

    2009-01-01

    River network morphology not only reflects the structure of river stream but also has great effects on hydrological process, soil erosion, river evolution, and watershed topography. Here we propose and define a new sequence of self-similar networks and corresponding parameters for the generated Tokunaga network. We also discuss the topological and numerical characteristics of self-similar networks with different iteration rules by utilizing links and fractal dimension. Application results indicate that the proposed method could be used to generate river network, which is much consistent with natural river network. The proposed parameter λ could well reflect the river network morphology.

  10. Role-based similarity in directed networks

    CERN Document Server

    Cooper, Kathryn

    2010-01-01

    The widespread relevance of increasingly complex networks requires methods to extract meaningful coarse-grained representations of such systems. For undirected graphs, standard community detection methods use criteria largely based on density of connections to provide such representations. We propose a method for grouping nodes in directed networks based on the role of the nodes in the network, understood in terms of patterns of incoming and outgoing flows. The role groupings are obtained through the clustering of a similarity matrix, formed by the distances between feature vectors that contain the number of in and out paths of all lengths for each node. Hence nodes operating in a similar flow environment are grouped together although they may not themselves be densely connected. Our method, which includes a scale factor that reveals robust groupings based on increasingly global structure, provides an alternative criterion to uncover structure in networks where there is an implicit flow transfer in the system...

  11. Evolution and Function of the Insulin and Insulin-like Signaling Network in Ectothermic Reptiles: Some Answers and More Questions.

    Science.gov (United States)

    Schwartz, Tonia S; Bronikowski, Anne M

    2016-08-01

    The insulin and insulin-like signaling (IIS) molecular network regulates cellular growth and division, and influences organismal metabolism, growth and development, reproduction, and lifespan. As a group, reptiles have incredible diversity in the complex life history traits that have been associated with the IIS network, yet the research on the IIS network in ectothermic reptiles is sparse. Here, we review the IIS network and synthesize what is known about the function and evolution of the IIS network in ectothermic reptiles. The primary hormones of this network-the insulin-like growth factors 1 and 2 (IGFs) likely function in reproduction in ectothermic reptiles, but the precise mechanisms are unclear, and likely range from influencing mating and ovulation to maternal investment in embryonic development. In general, plasma levels of IGF1 increase with food intake in ectothermic reptiles, but the magnitude of the response to food varies across species or populations and the ages of animals. Long-term temperature treatments as well as thermal stress can alter expression of genes within the IIS network. Although relatively little work has been done on IGF2 in ectothermic reptiles, IGF2 is consistently expressed at higher levels than IGF1 in juvenile ectothermic reptiles. Furthermore, in contrast to mammals that have genetic imprinting that silences the maternal IGF2 allele, in reptiles IGF2 is bi-allelically expressed (based on findings in chickens, a snake, and a lizard). Evolutionary analyses indicate some members of the IIS network are rapidly evolving across reptile species, including IGF1, insulin (INS), and their receptors. In particular, IGF1 displays extensive nucleotide variation across lizards and snakes, which suggests that its functional role may vary across this group. In addition, genetic variation across families and populations in the response of the IIS network to environmental conditions illustrates that components of this network may be evolving in

  12. Rule-Based Network Service Provisioning

    Directory of Open Access Journals (Sweden)

    Rudy Deca

    2012-10-01

    Full Text Available Due to the unprecedented development of networks, manual network service provisioning is becoming increasingly risky, error-prone, expensive, and time-consuming. To solve this problem,rule-based methods can provide adequate leverage for automating various network management tasks. This paper presents a rule-based solution for automated network service provisioning. The proposed approach captures configuration data interdependencies using high-level, service-specific, user-configurable rules. We focus on the service validation task, which is illustrated by means of a case study.Based on numerical results, we analyse the influence of the network-level complexity factors and rule descriptive features on the rule efficiency. This analysis shows the operators how to increase rule efficiency while keeping the rules simple and the rule set compact. We present a technique that allows operators to increase the error coverage, and we show that high error coverage scales well when the complexity of networks and services increases.We reassess the correlation function between specific rule efficiency and rule complexity metrics found in previous work, and show that this correlation function holds for various sizes, types, and complexities of networks and services.

  13. Anatomical network analysis shows decoupling of modular lability and complexity in the evolution of the primate skull.

    Directory of Open Access Journals (Sweden)

    Borja Esteve-Altava

    Full Text Available Modularity and complexity go hand in hand in the evolution of the skull of primates. Because analyses of these two parameters often use different approaches, we do not know yet how modularity evolves within, or as a consequence of, an also-evolving complex organization. Here we use a novel network theory-based approach (Anatomical Network Analysis to assess how the organization of skull bones constrains the co-evolution of modularity and complexity among primates. We used the pattern of bone contacts modeled as networks to identify connectivity modules and quantify morphological complexity. We analyzed whether modularity and complexity evolved coordinately in the skull of primates. Specifically, we tested Herbert Simon's general theory of near-decomposability, which states that modularity promotes the evolution of complexity. We found that the skulls of extant primates divide into one conserved cranial module and up to three labile facial modules, whose composition varies among primates. Despite changes in modularity, statistical analyses reject a positive feedback between modularity and complexity. Our results suggest a decoupling of complexity and modularity that translates to varying levels of constraint on the morphological evolvability of the primate skull. This study has methodological and conceptual implications for grasping the constraints that underlie the developmental and functional integration of the skull of humans and other primates.

  14. 基于动态网络分析的专利合作网络演化分析*--以纳米技术为例%Evolution of Patent Cooperation Network Based on Dynamic Network Analysis:Taking Nano Technology as an Example

    Institute of Scientific and Technical Information of China (English)

    刘彤; 郭鲁钢; 杨冠灿

    2014-01-01

    专利信息的复杂性决定了研究专利问题需要从多个关系层面共同进行观察。本文在介绍了动态网络分析及与社会网络分析的联系和区别后,以北京地区纳米技术领域专利为例构造具有多重属性节点的专利网络,利用动态网络分析方法对专利合作网络的演化与动态特征进行了分析,对网络中潜在的重要关系和变化进行了识别,最后对分析结果进行了总结。%The complexity of patent determines that the related researches of patent should be from many aspects. In this paper, after the introduction of the connection and difference between dynamic network analysis ( DNA) and social network analysis ( SNA) , the patent network with multi attributes is constructed on the basis of Beijing nano patents, then the DNA approach is used to analyze the patent net-work's evolution and dynamic features, the potential important relations and changes are identified, and finally the analysis result is conclu-ded.

  15. Evolution of emotions on networks leads to the evolution of cooperation in social dilemmas

    CERN Document Server

    Szolnoki, Attila; Ye, Ye; Perc, Matjaz

    2013-01-01

    We show that the resolution of social dilemmas on random graphs and scale-free networks is facilitated by imitating not the strategy of better performing players but rather their emotions. We assume sympathy and envy as the two emotions that determine the strategy of each player by any given interaction, and we define them as probabilities to cooperate with players having a lower and higher payoff, respectively. Starting with a population where all possible combinations of the two emotions are available, the evolutionary process leads to a spontaneous fixation to a single emotional profile that is eventually adopted by all players. However, this emotional profile depends not only on the payoffs but also on the heterogeneity of the interaction network. Homogeneous networks, such as lattices and regular random graphs, lead to fixations that are characterized by high sympathy and high envy, while heterogeneous networks lead to low or modest sympathy but also low envy. Our results thus suggest that public emotion...

  16. Improving care and wellness in bipolar disorder: origins, evolution and future directions of a collaborative knowledge exchange network

    Directory of Open Access Journals (Sweden)

    Michalak Erin E

    2012-09-01

    Full Text Available Abstract The Collaborative RESearch team to study psychosocial factors in bipolar disorder (CREST.BD is a multidisciplinary, cross-sectoral network dedicated to both fundamental research and knowledge exchange on bipolar disorder (BD. The core mission of the network is to advance the science and understanding of psychological and social issues associated with BD, improve the care and wellness of people living with BD, and strengthen services and supports for these individuals. CREST.BD bridges traditional and newer research approaches, particularly embracing community-based participatory research (CBPR methods. Membership of CREST is broad, including academic researchers, people with BD, their family members and supports, and a variety of health care providers. Here, we describe the origins, evolution, approach to planning and evaluation and future vision for our network within the landscape of CBPR and integrated knowledge translation (KT, and explore the keys and challenges to success we have encountered working within this framework.

  17. Network-based Database Course

    DEFF Research Database (Denmark)

    Nielsen, J.N.; Knudsen, Morten; Nielsen, Jens Frederik Dalsgaard

    A course in database design and implementation has been de- signed, utilizing existing network facilities. The course is an elementary course for students of computer engineering. Its purpose is to give the students a theoretical database knowledge as well as practical experience with design...... and implementation. A tutorial relational database and the students self-designed databases are implemented on the UNIX system of Aalborg University, thus giving the teacher the possibility of live demonstrations in the lecture room, and the students the possibility of interactive learning in their working rooms...

  18. Network-based Database Course

    DEFF Research Database (Denmark)

    Nielsen, J.N.; Knudsen, Morten; Nielsen, Jens Frederik Dalsgaard

    A course in database design and implementation has been de- signed, utilizing existing network facilities. The course is an elementary course for students of computer engineering. Its purpose is to give the students a theoretical database knowledge as well as practical experience with design...... and implementation. A tutorial relational database and the students self-designed databases are implemented on the UNIX system of Aalborg University, thus giving the teacher the possibility of live demonstrations in the lecture room, and the students the possibility of interactive learning in their working rooms...

  19. Network Intrusion Detection based on GMKL Algorithm

    Directory of Open Access Journals (Sweden)

    Li Yuxiang

    2013-06-01

    Full Text Available According to the 31th statistical reports of China Internet network information center (CNNIC, by the end of December 2012, the number of Chinese netizens has reached 564 million, and the scale of mobile Internet users also reached 420 million. But when the network brings great convenience to people's life, it also brings huge threat in the life of people. So through collecting and analyzing the information in the computer system or network we can detect any possible behaviors that can damage the availability, integrity and confidentiality of the computer resource, and make timely treatment to these behaviors which have important research significance to improve the operation environment of network and network service. At present, the Neural Network, Support Vector machine (SVM and Hidden Markov Model, Fuzzy inference and Genetic Algorithms are introduced into the research of network intrusion detection, trying to build a healthy and secure network operation environment. But most of these algorithms are based on the total sample and it also hypothesizes that the number of the sample is infinity. But in the field of network intrusion the collected data often cannot meet the above requirements. It often shows high latitudes, variability and small sample characteristics. For these data using traditional machine learning methods are hard to get ideal results. In view of this, this paper proposed a Generalized Multi-Kernel Learning method to applied to network intrusion detection. The Generalized Multi-Kernel Learning method can be well applied to large scale sample data, dimension complex, containing a large number of heterogeneous information and so on. The experimental results show that applying GMKL to network attack detection has high classification precision and low abnormal practical precision.

  20. The evolution of distributed association networks in the human brain.

    Science.gov (United States)

    Buckner, Randy L; Krienen, Fenna M

    2013-12-01

    The human cerebral cortex is vastly expanded relative to other primates and disproportionately occupied by distributed association regions. Here we offer a hypothesis about how association networks evolved their prominence and came to possess circuit properties vital to human cognition. The rapid expansion of the cortical mantle may have untethered large portions of the cortex from strong constraints of molecular gradients and early activity cascades that lead to sensory hierarchies. What fill the gaps between these hierarchies are densely interconnected networks that widely span the cortex and mature late into development. Limitations of the tethering hypothesis are discussed as well as its broad implications for understanding critical features of the human brain as a byproduct of size scaling. Copyright © 2013 Elsevier Ltd. All rights reserved.

  1. Development and Evolution of Neural Networks in an Artificial Chemistry

    CERN Document Server

    Astor, J C; Astor, Jens C.; Adami, Christoph

    1998-01-01

    We present a model of decentralized growth for Artificial Neural Networks (ANNs) inspired by the development and the physiology of real nervous systems. In this model, each individual artificial neuron is an autonomous unit whose behavior is determined only by the genetic information it harbors and local concentrations of substrates modeled by a simple artificial chemistry. Gene expression is manifested as axon and dendrite growth, cell division and differentiation, substrate production and cell stimulation. We demonstrate the model's power with a hand-written genome that leads to the growth of a simple network which performs classical conditioning. To evolve more complex structures, we implemented a platform-independent, asynchronous, distributed Genetic Algorithm (GA) that allows users to participate in evolutionary experiments via the World Wide Web.

  2. Self-organized Criticality in a Modified Evolution Model on Generalized Barabási-Albert Scale-Free Networks

    Institute of Scientific and Technical Information of China (English)

    LIN Min; WANG Gang; CHEN Tian-Lun

    2007-01-01

    A modified evolution model of self-organized criticality on generalized Barabási-Albert (GBA) scale-free networks is investigated. In our model, we find that spatial and temporal correlations exhibit critical behaviors. More importantly, these critical behaviors change with the parameter b, which weights the distance in comparison with the degree in the GBA network evolution.

  3. Evolution of Plastic Learning in Spiking Networks via Memristive Connections

    OpenAIRE

    Howard, Gerard; Gale, Ella; Bull, Larry; Costello, Ben de Lacy; Adamatzky, Andy

    2012-01-01

    This article presents a spiking neuroevolutionary system which implements memristors as plastic connections, i.e. whose weights can vary during a trial. The evolutionary design process exploits parameter self-adaptation and variable topologies, allowing the number of neurons, connection weights, and inter-neural connectivity pattern to emerge. By comparing two phenomenological real-world memristor implementations with networks comprised of (i) linear resistors (ii) constant-valued connections...

  4. Intimate Transactions: The Evolution of an Ecosophical Networked Practice

    Directory of Open Access Journals (Sweden)

    Keith Armstrong

    2005-01-01

    Full Text Available Intimate Transactions is a networked interactive installation for two participants located in different geographical locations. During a 30-minute, one-on-one session they individually and collaboratively explore a range of virtual, interactive environments mediated by digital image, sound and haptic feedback. This major work evolved from a single site, non-networked version to a multi-site, server-driven artwork that operates in mixed online/offline modes. In 2005, the work was awarded an Honorary Mention in the Prix Ars Electronica and began an international tour of several high profile festivals and arts’ venues. Intimate Transactions is a product of the Transmute Collective (http://www.intimatetransactions.com.Intimate Transactions networked inter-relational design was inspired by a range of conditions, discourses and practices drawn from scientific and critical ecologies, new media and innovative performance that I collectively name ‘ecosophical praxis’. An inherent part of this approach involves the continual development of contextualizing questions, which in turn mould the work’s practice and presentation. This paper considers the issues and implications of applying this approach during the Intimate Transactions project. The concluding questions are relevant as a guiding method for othercreative practitioners similarly interested in eco-social and eco-political engagement.

  5. Integrating Field Measurements and Numerical Modeling to Investigate Gully Network Evolution

    Science.gov (United States)

    Rengers, F. K.; Tucker, G. E.

    2011-12-01

    With the advent of numerical modeling the exploration of landscape evolution has advanced from simple thought experiments to investigation of increasingly complex landforming processes. A common criticism of landscape evolution modeling, however, is the lack of model validation with actual field data. Here we present research that continues the advancement of landscape evolution theory by combining detailed field observations with numerical modeling. The focus of our investigation is gully networks on soft-rock strata, where rates of morphologic change are fast enough to measure on annual to decadal time scales. Our research focuses on a highly transient landscape on the high plains of eastern Colorado (40 miles east of Denver, CO) where convective thunderstorms drive ephemeral stream flow, resulting in incised gullies with vertical knickpoints. The site has yielded a comprehensive dataset of hydrology, topography, and geomorphic change. We are continuously monitoring several environmental parameters (including rainfall, overland flow, stream discharge, and soil moisture), and have explored the physical properties of the soil on the site through grain size analysis and infiltration measurements. In addition, time-lapse photography and repeat terrestrial lidar scanning make it possible to track knickpoint dynamics through time. The resulting dataset provides a case study for testing the ability of landscape evolution models to reproduce annual to decadal patterns of erosion and deposition. Knickpoint erosion is the largest contributor to landscape evolution and the controlling factor for gully migration rate. Average knickpoint retreat rates, based on historic aerial photographs and ongoing laser surveying, range between 0.1 and 2.5 m/yr. Knickpoint retreat appears to be driven by a combination of plunge-pool scour, large block failure, and grain-by-grain entrainment of sediment from the wall. Erosion is correlated with flash floods in the summer months. To test our

  6. Genotypic variation in foundation species generates network structure that may drive community dynamics and evolution.

    Science.gov (United States)

    Lau, Matthew K; Keith, Arthur R; Borrett, Stuart R; Shuster, Stephen M; Whitham, Thomas G

    2016-03-01

    Although genetics in a single species is known to impact whole communities, little is known about how genetic variation influences species interaction networks in complex ecosystems. Here, we examine the interactions in a community of arthropod species on replicated genotypes (clones) of a foundation tree species, Populus angustifolia James (narrowleaf cottonwood), in a long-term, common garden experiment using a bipartite "genotype-species" network perspective. We combine this empirical work with a simulation experiment designed to further investigate how variation among individual tree genotypes can impact network structure. Three findings emerged: (1) the empirical "genotype-species network" exhibited significant network structure with modularity being greater than the highly conservative null model; (2) as would be expected given a modular network structure, the empirical network displayed significant positive arthropod co-occurrence patterns; and (3) furthermore, the simulations of "genotype-species" networks displayed variation in network structure, with modularity in particular clearly increasing, as genotypic variation increased. These results support the conclusion that genetic variation in a single species contributes to the structure of ecological interaction networks, which could influence eco-ogical dynamics (e.g., assembly and stability) and evolution in a community context.

  7. Identifying network public opinion leaders based on Markov Logic Networks.

    Science.gov (United States)

    Zhang, Weizhe; Li, Xiaoqiang; He, Hui; Wang, Xing

    2014-01-01

    Public opinion emergencies have important effect on social activities. Recognition of special communities like opinion leaders can contribute to a comprehensive understanding of the development trend of public opinion. In this paper, a network opinion leader recognition method based on relational data was put forward, and an opinion leader recognition system integrating public opinion data acquisition module, data characteristic selection, and fusion module as well as opinion leader discovery module based on Markov Logic Networks was designed. The designed opinion leader recognition system not only can overcome the incomplete data acquisition and isolated task of traditional methods, but also can recognize opinion leaders comprehensively with considerations to multiple problems by using the relational model. Experimental results demonstrated that, compared with the traditional methods, the proposed method can provide a more accurate opinion leader recognition and has good noise immunity.

  8. Theory of Networked Minority Games based on Strategy Pattern Dynamics

    OpenAIRE

    Lo, T. S.; H.Y. Chan; P.M. Hui; Johnson, N F

    2004-01-01

    We formulate a theory of agent-based models in which agents compete to be in a winning group. The agents may be part of a network or not, and the winning group may be a minority group or not. The novel feature of the present formalism is its focus on the dynamical pattern of strategy rankings, and its careful treatment of the strategy ties which arise during the system's temporal evolution. We apply it to the Minority Game (MG) with connected populations. Expressions for the mean success rate...

  9. Handwritten digits recognition based on immune network

    Science.gov (United States)

    Li, Yangyang; Wu, Yunhui; Jiao, Lc; Wu, Jianshe

    2011-11-01

    With the development of society, handwritten digits recognition technique has been widely applied to production and daily life. It is a very difficult task to solve these problems in the field of pattern recognition. In this paper, a new method is presented for handwritten digit recognition. The digit samples firstly are processed and features extraction. Based on these features, a novel immune network classification algorithm is designed and implemented to the handwritten digits recognition. The proposed algorithm is developed by Jerne's immune network model for feature selection and KNN method for classification. Its characteristic is the novel network with parallel commutating and learning. The performance of the proposed method is experimented to the handwritten number datasets MNIST and compared with some other recognition algorithms-KNN, ANN and SVM algorithm. The result shows that the novel classification algorithm based on immune network gives promising performance and stable behavior for handwritten digits recognition.

  10. An Improved Interconnection Network Based on NIN

    Institute of Scientific and Technical Information of China (English)

    Li Fei; Li Zhi-tang

    2004-01-01

    The Novel Interconnection Network (NIN)based on inverted-graph topology and crossbar switch is a kind of lower latency and higher throughput interconnection network. But it bas a vital disadvantage, high hardware complexity. In order to reduce system hardware cost, an improved NIN (ININ) structure is proposed. As same as NIN,ININ has constant network diameter. Besides of keeping ad vantages of NIN, hardware cost of ININ is lower than NIN.Furthermore, we design a new deadlock-free routing algorithm for the improved NIN.

  11. Network evolution and QOS provisioning for integrated femtocell/macrocell networks

    CERN Document Server

    Chowdhury, Mostafa Zaman; Haas, Zygmunt J

    2010-01-01

    Integrated femtocell/macrocell networks, comprising a conventional cellular network overlaid with femtocells, offer an economically appealing way to improve coverage, quality of service, and access network capacity. The key element to successful femtocells/macrocell integration lies in its self-organizing capability. Provisioning of quality of service is the main technical challenge of the femtocell/macrocell integrated networks, while the main administrative challenge is the choice of the proper evolutionary path from the existing macrocellular networks to the integrated network. In this article, we introduce three integrated network architectures which, while increasing the access capacity, they also reduce the deployment and operational costs. Then, we discuss a number of technical issues, which are key to making such integration a reality, and we offer possible approaches to their solution. These issues include efficient frequency and interference management, quality of service provisioning of the xDSL-ba...

  12. Simulated evolution of fractures and fracture networks subject to thermal cooling: A coupled discrete element and heat conduction model

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Hai; Plummer, Mitchell; Podgorney, Robert

    2013-02-01

    Advancement of EGS requires improved prediction of fracture development and growth during reservoir stimulation and long-term operation. This, in turn, requires better understanding of the dynamics of the strongly coupled thermo-hydro-mechanical (THM) processes within fractured rocks. We have developed a physically based rock deformation and fracture propagation simulator by using a quasi-static discrete element model (DEM) to model mechanical rock deformation and fracture propagation induced by thermal stress and fluid pressure changes. We also developed a network model to simulate fluid flow and heat transport in both fractures and porous rock. In this paper, we describe results of simulations in which the DEM model and network flow & heat transport model are coupled together to provide realistic simulation of the changes of apertures and permeability of fractures and fracture networks induced by thermal cooling and fluid pressure changes within fractures. Various processes, such as Stokes flow in low velocity pores, convection-dominated heat transport in fractures, heat exchange between fluid-filled fractures and solid rock, heat conduction through low-permeability matrices and associated mechanical deformations are all incorporated into the coupled model. The effects of confining stresses, developing thermal stress and injection pressure on the permeability evolution of fracture and fracture networks are systematically investigated. Results are summarized in terms of implications for the development and evolution of fracture distribution during hydrofracturing and thermal stimulation for EGS.

  13. Long division unites - long union divides, a model for social network evolution

    CERN Document Server

    Jian, Jiang; Michel, Pezeril; Qiuping-Alexandre, Wang

    2013-01-01

    A remarkable phenomenon in the time evolution of many networks such as cultural, political, national and economic systems, is the recurrent transition between the states of union and division of nodes. In this work, we propose a phenomenological modeling, inspired by the maxim "long union divides and long division unites", in order to investigate the evolutionary characters of these networks composed of the entities whose behaviors are dominated by these two events. The nodes are endowed with quantities such as identity, ingredient, richness (power), openness (connections), age, distance, interaction etc. which determine collectively the evolution in a probabilistic way. Depending on a tunable parameter, the time evolution of this model is mainly an alternative domination of union or division state, with a possible state of final union dominated by one single node.

  14. Evolution of emotions on networks leads to the evolution of cooperation in social dilemmas.

    Science.gov (United States)

    Szolnoki, Attila; Xie, Neng-Gang; Ye, Ye; Perc, Matjaž

    2013-04-01

    We show that the resolution of social dilemmas in random graphs and scale-free networks is facilitated by imitating not the strategy of better-performing players but, rather, their emotions. We assume sympathy and envy to be the two emotions that determine the strategy of each player in any given interaction, and we define them as the probabilities of cooperating with players having a lower and a higher payoff, respectively. Starting with a population where all possible combinations of the two emotions are available, the evolutionary process leads to a spontaneous fixation to a single emotional profile that is eventually adopted by all players. However, this emotional profile depends not only on the payoffs but also on the heterogeneity of the interaction network. Homogeneous networks, such as lattices and regular random graphs, lead to fixations that are characterized by high sympathy and high envy, while heterogeneous networks lead to low or modest sympathy but also low envy. Our results thus suggest that public emotions and the propensity to cooperate at large depend, and are in fact determined by, the properties of the interaction network.

  15. Analysis And Augmentation Of Timing Advance Based Geolocation In Lte Cellular Networks

    Science.gov (United States)

    2016-12-01

    NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA DISSERTATION ANALYSIS AND AUGMENTATION OF TIMING ADVANCE-BASED GEOLOCATION IN LTE CELLULAR NETWORKS by...AND SUBTITLE ANALYSIS AND AUGMENTATION OF TIMING ADVANCE-BASED GEOLOCA- TION IN LTE CELLULAR NETWORKS 5. FUNDING NUMBERS 6. AUTHOR(S) John D. Roth 7...protection, and direct marketing. This work provides in-depth analysis of cellular positioning, which leverages the Long Term Evolution (LTE) signaling

  16. Rank-based deactivation model for networks with age

    Institute of Scientific and Technical Information of China (English)

    Wang Xue-Wen; Yang Guo-Hong; Li Xiao-Lin; Xu Xin-Jian

    2013-01-01

    We study the impact of age on network evolution which couples addition of new nodes and deactivation of old ones.During evolution,each node experiences two stages:active and inactive.The transition from the active state to the inactive one is based on the rank of the node.In this paper,we adopt age as a criterion of ranking,and propose two deactivation models that generalize previous research.In model A,the older active node possesses the higher rank,whereas in model B,the younger active node takes the higher rank.We make a comparative study between the two models through the node-degree distribution.

  17. The Earthscope USArray Array Network Facility (ANF): Evolution of Data Acquisition, Processing, and Storage Systems

    Science.gov (United States)

    Davis, G. A.; Battistuz, B.; Foley, S.; Vernon, F. L.; Eakins, J. A.

    2009-12-01

    Since April 2004 the Earthscope USArray Transportable Array (TA) network has grown to over 400 broadband seismic stations that stream multi-channel data in near real-time to the Array Network Facility in San Diego. In total, over 1.7 terabytes per year of 24-bit, 40 samples-per-second seismic and state of health data is recorded from the stations. The ANF provides analysts access to real-time and archived data, as well as state-of-health data, metadata, and interactive tools for station engineers and the public via a website. Additional processing and recovery of missing data from on-site recorders (balers) at the stations is performed before the final data is transmitted to the IRIS Data Management Center (DMC). Assembly of the final data set requires additional storage and processing capabilities to combine the real-time data with baler data. The infrastructure supporting these diverse computational and storage needs currently consists of twelve virtualized Sun Solaris Zones executing on nine physical server systems. The servers are protected against failure by redundant power, storage, and networking connections. Storage needs are provided by a hybrid iSCSI and Fiber Channel Storage Area Network (SAN) with access to over 40 terabytes of RAID 5 and 6 storage. Processing tasks are assigned to systems based on parallelization and floating-point calculation needs. On-site buffering at the data-loggers provide protection in case of short-term network or hardware problems, while backup acquisition systems at the San Diego Supercomputer Center and the DMC protect against catastrophic failure of the primary site. Configuration management and monitoring of these systems is accomplished with open-source (Cfengine, Nagios, Solaris Community Software) and commercial tools (Intermapper). In the evolution from a single server to multiple virtualized server instances, Sun Cluster software was evaluated and found to be unstable in our environment. Shared filesystem

  18. Establishment of National Gravity Base Network of Iran

    Science.gov (United States)

    Hatam Chavari, Y.; Bayer, R.; Hinderer, J.; Ghazavi, K.; Sedighi, M.; Luck, B.; Djamour, Y.; Le Moign, N.; Saadat, R.; Cheraghi, H.

    2009-04-01

    A gravity base network is supposed to be a set of benchmarks uniformly distributed across the country and the absolute gravity values at the benchmarks are known to the best accessible accuracy. The gravity at the benchmark stations are either measured directly with absolute devices or transferred by gravity difference measurements by gravimeters from known stations. To decrease the accumulation of random measuring errors arising from these transfers, the number of base stations distributed across the country should be as small as possible. This is feasible if the stations are selected near to the national airports long distances apart but faster accessible and measurable by a gravimeter carried in an airplane between the stations. To realize the importance of such a network, various applications of a gravity base network are firstly reviewed. A gravity base network is the required reference frame for establishing 1st , 2nd and 3rd order gravity networks. Such a gravity network is used for the following purposes: a. Mapping of the structure of upper crust in geology maps. The required accuracy for the measured gravity values is about 0.2 to 0.4 mGal. b. Oil and mineral explorations. The required accuracy for the measured gravity values is about 5 µGal. c. Geotechnical studies in mining areas for exploring the underground cavities as well as archeological studies. The required accuracy is about 5 µGal and better. d. Subsurface water resource explorations and mapping crustal layers which absorb it. An accuracy of the same level of previous applications is required here too. e. Studying the tectonics of the Earth's crust. Repeated precise gravity measurements at the gravity network stations can assist us in identifying systematic height changes. The accuracy of the order of 5 µGal and more is required. f. Studying volcanoes and their evolution. Repeated precise gravity measurements at the gravity network stations can provide valuable information on the gradual

  19. A resonance based model of biological evolution

    Science.gov (United States)

    Damasco, Achille; Giuliani, Alessandro

    2017-04-01

    We propose a coarse grained physical model of evolution. The proposed model 'at least in principle' is amenable of an experimental verification even if this looks as a conundrum: evolution is a unique historical process and the tape cannot be reversed and played again. Nevertheless, we can imagine a phenomenological scenario tailored upon state transitions in physical chemistry in which different agents of evolution play the role of the elements of a state transition like thermal noise or resonance effects. The abstract model we propose can be of help for sketching hypotheses and getting rid of some well-known features of natural history like the so-called Cambrian explosion. The possibility of an experimental proof of the model is discussed as well.

  20. The co-evolution of brand effect and competitiveness in evolving networks

    CERN Document Server

    Guo, Jin-Li

    2013-01-01

    The principle that "the brand effect is attractive" underlies preferential attachment. If new connections are made preferentially to more popular nodes, then the degree distribution of nodes follows power laws. Here we show that the brand effect is just one element of attractiveness; another element is the competitiveness. We develop a framework that allows us to investigate this competitive aspect of real networks, instead of simply preferring popular nodes. As opposed to preferential attachment, our model accurately describes the evolution of social and technological networks. We find that this competition for links allows more competitive nodes to obtain the more connected but less competitive ones. The phenomenon which more competitive nodes get richer links can help us understand the evolution of many competitive systems in nature and society. Through theoretical analysis and numerical simulations, we also find that our model has not only the universality for the homogeneous weighted network, but also th...

  1. The evolution of your success lies at the centre of your co-authorship network.

    Directory of Open Access Journals (Sweden)

    Sandra Servia-Rodríguez

    Full Text Available Collaboration among scholars and institutions is progressively becoming essential to the success of research grant procurement and to allow the emergence and evolution of scientific disciplines. Our work focuses on analysing if the volume of collaborations of one author together with the relevance of his collaborators is somewhat related to his research performance over time. In order to prove this relation we collected the temporal distributions of scholars' publications and citations from the Google Scholar platform and the co-authorship network (of Computer Scientists underlying the well-known DBLP bibliographic database. By the application of time series clustering, social network analysis and non-parametric statistics, we observe that scholars with similar publications (citations patterns also tend to have a similar centrality in the co-authorship network. To our knowledge, this is the first work that considers success evolution with respect to co-authorship.

  2. Evolution of opinions on social networks in the presence of competing committed groups.

    Science.gov (United States)

    Xie, Jierui; Emenheiser, Jeffrey; Kirby, Matthew; Sreenivasan, Sameet; Szymanski, Boleslaw K; Korniss, Gyorgy

    2012-01-01

    Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about 10% of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions A and B, and constituting fractions pA and pB of the total population respectively, are present in the network. We show for stylized social networks (including Erdös-Rényi random graphs and Barabási-Albert scale-free networks) that the phase diagram of this system in parameter space (pA,pB) consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point.

  3. The Integrated Control-Mechanism in ATM-Based Networks

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Survivability is one of the important issues in ATM-based networks since even a single network element failure may cause a serious data loss. This paper introduces a new restoration mechanism based on multi-layer ATM survivable network management architecture. This mechanism integrates the general control and restoration control by establishing the Working VPs logical network, Backup VPs logical network and spare logical network in order to optimally utilize the network resources while maintaining the restoration requirements.

  4. Evolution of karst conduit networks in transition from pressurised flow to free surface flow

    Science.gov (United States)

    Perne, M.; Covington, M. D.; Gabrovšek, F.

    2014-06-01

    We present a novel modelling approach to study the evolution of conduit networks in soluble rocks. Unlike the models presented so far, the model allows a transition from pressurised (pipe) flow to a free surface (open channel) flow in evolving discrete conduit networks. It calculates flow, solute transport and dissolutional enlargement within each time step and steps through time until a stable flow pattern establishes. The flow in each time step is calculated by calling the EPA Storm Water Management Model (EPA SWMM), which efficiently solves the 1-D Saint Venant equations in a network of conduits. We present several cases with low dip and sub-vertical networks to demonstrate mechanisms of flow pathway selection. In low dip models the inputs were randomly distributed to several junctions. The evolution of pathways progresses upstream: initially pathways linking outlets to the closest inputs evolve fastest because the gradient along these pathways is largest. When a pathway efficiently drains the available recharge, the head drop along the pathway attracts flow from the neighbouring upstream junctions and new connecting pathways evolve. The mechanism progresses from the output boundary inwards until all inputs are connected to the stable flow system. In the pressurised phase, each junction is drained by at least one conduit, but only one conduit remains active in the vadose phase. The selection depends on the initial geometry of a junction, initial distribution of diameters, the evolution in a pressurised regime, and on the dip of the conduits, which plays an important role in vadose entrenchment. In high dip networks, the vadose zone propagates downwards and inwards from the rim of the massif. When a network with randomly distributed initial diameters is supplied with concentrated recharge from the adjacent area, the sink point regresses up upstream along junctions connected to the prominent pathways. Large conductive structures provide deep penetration of high

  5. Evolution of karst conduit networks in transition from pressurised flow to free surface flow

    Directory of Open Access Journals (Sweden)

    M. Perne

    2014-06-01

    Full Text Available We present a novel modelling approach to study the evolution of conduit networks in soluble rocks. Unlike the models presented so far, the model allows a transition from pressurised (pipe flow to a free surface (open channel flow in evolving discrete conduit networks. It calculates flow, solute transport and dissolutional enlargement within each time step and steps through time until a stable flow pattern establishes. The flow in each time step is calculated by calling the EPA Storm Water Management Model (EPA SWMM, which efficiently solves the 1-D Saint Venant equations in a network of conduits. We present several cases with low dip and sub-vertical networks to demonstrate mechanisms of flow pathway selection. In low dip models the inputs were randomly distributed to several junctions. The evolution of pathways progresses upstream: initially pathways linking outlets to the closest inputs evolve fastest because the gradient along these pathways is largest. When a pathway efficiently drains the available recharge, the head drop along the pathway attracts flow from the neighbouring upstream junctions and new connecting pathways evolve. The mechanism progresses from the output boundary inwards until all inputs are connected to the stable flow system. In the pressurised phase, each junction is drained by at least one conduit, but only one conduit remains active in the vadose phase. The selection depends on the initial geometry of a junction, initial distribution of diameters, the evolution in a pressurised regime, and on the dip of the conduits, which plays an important role in vadose entrenchment. In high dip networks, the vadose zone propagates downwards and inwards from the rim of the massif. When a network with randomly distributed initial diameters is supplied with concentrated recharge from the adjacent area, the sink point regresses up upstream along junctions connected to the prominent pathways. Large conductive structures provide deep

  6. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    This paper introduces Rank-based Interactive Evolution (RIE) which is an alternative to interactive evolution driven by computational models of user preferences to generate personalized content. In RIE, the computational models are adapted to the preferences of users which, in turn, are used as f...

  7. A Line Based Visualization of Code Evolution

    NARCIS (Netherlands)

    Voinea, S.L.; Telea, A.; Wijk, J.J. van

    2005-01-01

    The source code of software systems changes many times during the system lifecycle. We study how developers can get insight in these changes in order to understand the project context and the product artifacts. For this we propose new techniques for code evolution representation and visualization in

  8. Evolution of Web-based International Marketing

    DEFF Research Database (Denmark)

    Rask, Morten

    2002-01-01

    Companies that have been doing international business do not usually make the transition from traditional marketers to full-blown Web marketers in one sharp step. In our study of Danish firms, we found that in terms of the evolution of their Web strategies, these Danish companies went through three...

  9. Blind Equalization Based on Evolution Strategies

    Institute of Scientific and Technical Information of China (English)

    SongYu; ZhangXianda; 等

    1997-01-01

    Conventional blind equalization algorithms suffer from ill convergence to local minima and slow convergence speed.This paper proposes a novel blind equalization algorithm.using random search methods-evolution strategies and existing cost functions,Simulation results verify the fast and global convergence of the proposed algorithm.

  10. A File Based Visualization of Software Evolution

    NARCIS (Netherlands)

    Voinea, S.L.; Telea, A.

    2006-01-01

    Software Configuration Management systems are important instruments for supporting development of large software projects. They accumulate large amounts of evolution data that can be used for process accounting and auditing. We study how visualization can help developers and managers to get insight

  11. Long-term evolution of upper stratospheric ozone at selected stations of the Network for the Detection of Stratospheric Change (NDSC)

    NARCIS (Netherlands)

    Steinbrecht, W; Claude, H; Schönenborn, F; McDermid, I S; Leblanc, T; Godin, S; Song, T; Swart, D P J; Meijer, Y J; Bodeker, G E; Connor, B J; Kämpfer, N; Hocke, K; Calisesi, Y; Schneider, N; Noë, J de la; Parrish, A D; Boyd, I S; Brühl, C; Steil, B; Giorgetta, M A; Manzini, E; Thomason, L W; Zawodny, J M; McCormick, M P; Russell, J M; Bhartia, P K; Stolarski, R S; Hollandsworth-Frith, S M

    2006-01-01

    The long-term evolution of upper stratospheric ozone has been recorded by lidars and microwave radiometers within the ground-based Network for the Detection of Stratospheric Change (NDSC), and by the space-borne Solar Backscatter Ultra-Violet instruments (SBUV), Stratospheric Aerosol and Gas

  12. A network-based dynamical ranking system

    CERN Document Server

    Motegi, Shun

    2012-01-01

    Ranking players or teams in sports is of practical interests. From the viewpoint of networks, a ranking system is equivalent a centrality measure for sports networks, whereby a directed link represents the result of a single game. Previously proposed network-based ranking systems are derived from static networks, i.e., aggregation of the results of games over time. However, the score (i.e., strength) of a player, for example, depends on time. Defeating a renowned player in the peak performance is intuitively more rewarding than defeating the same player in other periods. To account for this factor, we propose a dynamic variant of such a network-based ranking system and apply it to professional men's tennis data. Our ranking system, also interpreted as a centrality measure for directed temporal networks, has two parameters. One parameter represents the exponential decay rate of the past score, and the other parameter controls the effect of indirect wins on the score. We derive a set of linear online update equ...

  13. Vessel network detection using contour evolution and color components

    Energy Technology Data Exchange (ETDEWEB)

    Ushizima, Daniela; Medeiros, Fatima; Cuadros, Jorge; Martins, Charles

    2011-06-22

    Automated retinal screening relies on vasculature segmentation before the identification of other anatomical structures of the retina. Vasculature extraction can also be input to image quality ranking, neovascularization detection and image registration, among other applications. There is an extensive literature related to this problem, often excluding the inherent heterogeneity of ophthalmic clinical images. The contribution of this paper relies on an algorithm using front propagation to segment the vessel network. The algorithm includes a penalty in the wait queue on the fast marching heap to minimize leakage of the evolving interface. The method requires no manual labeling, a minimum number of parameters and it is capable of segmenting color ocular fundus images in real scenarios, where multi-ethnicity and brightness variations are parts of the problem.

  14. Multiuser detector based on wavelet networks

    Institute of Scientific and Technical Information of China (English)

    王伶; 焦李成; 陶海红; 刘芳

    2004-01-01

    Multiple access interference (MAI) and near-far problem are two major obstacles in DS-CDMA systems.Combining wavelet neural networks and two matched filters, the novel multiuser detector, which is based on multiple variable function estimation wavelet networks over single path asynchronous channel and space-time channel respectively is presented. Excellent localization characteristics of wavelet functions in both time and frequency domains allowed hierarchical multiple resolution learning of input-output data mapping. The mathematic frame of the neural networks and error back ward propagation algorithm are introduced. The complexity of the multiuser detector only depends on that of wavelet networks. With numerical simulations and performance analysis, it indicates that the multiuser detector has excellent performance in eliminating MAI and near-far resistance.

  15. Neural Network Based 3D Surface Reconstruction

    Directory of Open Access Journals (Sweden)

    Vincy Joseph

    2009-11-01

    Full Text Available This paper proposes a novel neural-network-based adaptive hybrid-reflectance three-dimensional (3-D surface reconstruction model. The neural network combines the diffuse and specular components into a hybrid model. The proposed model considers the characteristics of each point and the variant albedo to prevent the reconstructed surface from being distorted. The neural network inputs are the pixel values of the two-dimensional images to be reconstructed. The normal vectors of the surface can then be obtained from the output of the neural network after supervised learning, where the illuminant direction does not have to be known in advance. Finally, the obtained normal vectors can be applied to integration method when reconstructing 3-D objects. Facial images were used for training in the proposed approach

  16. 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....

  17. Artificial neural networks and the study of evolution of prey coloration.

    Science.gov (United States)

    Merilaita, Sami

    2007-03-29

    In this paper, I investigate the use of artificial neural networks in the study of prey coloration. I briefly review the anti-predator functions of prey coloration and describe both in general terms and with help of two studies as specific examples the use of neural network models in the research on prey coloration. The first example investigates the effect of visual complexity of background on evolution of camouflage. The second example deals with the evolutionary choice of defence strategy, crypsis or aposematism. I conclude that visual information processing by predators is central in evolution of prey coloration. Therefore, the capability to process patterns as well as to imitate aspects of predator's information processing and responses to visual information makes neural networks a well-suited modelling approach for the study of prey coloration. In addition, their suitability for evolutionary simulations is an advantage when complex or dynamic interactions are modelled. Since not all behaviours of neural network models are necessarily biologically relevant, it is important to validate a neural network model with empirical data. Bringing together knowledge about neural networks with knowledge about topics of prey coloration would provide a potential way to deepen our understanding of the specific appearances of prey coloration.

  18. US long distance fiber optic networks: Technology, evolution and advanced concepts. Volume 1: Executive summary

    Science.gov (United States)

    1986-01-01

    Over the past two decades, fiber optics has emerged as a highly practical and cost-efficient communications technology. Its competitiveness vis-a-vis other transmission media, especially satellite, has become a critical question. This report studies the likely evolution and application of fiber optic networks in the United States to the end of the century. The outlook for the technology of fiber systems is assessed and forecast, scenarios of the evolution of fiber optic network development are constructed, and costs to provide service are determined and examined parametrically as a function of network size and traffic carried. Volume 1 consists of the Executive Summary. Volume 2 focuses on fiber optic technology and long distance fiber optic networks. Volume 3 develops a traffic and financial model of a nationwide long distance transmission network. Among the study's most important conclusions are: revenue requirements per circuit for LATA-to-LATA fiber optic links are less than one cent per call minute; multiplex equipment, which is likely to be required in any competing system, is the largest contributor to circuit costs; the potential capacity of fiber optic cable is very large and as yet undefined; and fiber optic transmission combined with other network optimization schemes can lead to even lower costs than those identified in this study.

  19. Network Entropy Based on Topology Configuration and Its Computation to Random Networks

    Institute of Scientific and Technical Information of China (English)

    LI Ji; WANG Bing-Hong; WANG Wen-Xu; ZHOU Tao

    2008-01-01

    A definition of network entropy is presented, and as an example, the relationship between the value of network entropy of ER network model and the connect probability p as well as the total nodes N is discussed. The theoretical result and the simulation result based on the network entropy of the ER network are in agreement well with each other. The result indicated that different from the other network entropy reported before, the network entropy defined here has an obvious difference from different type of random networks or networks having different total nodes. Thus, this network entropy may portray the characters of complex networks better. It is also pointed out that, with the aid of network entropy defined, the concept of equilibrium networks and the concept of non-equilibrium networks may be introduced, and a quantitative measurement to describe the deviation to equilibrium state of a complex network is carried out.

  20. Packet transport network in metro

    Science.gov (United States)

    Huang, Feng; Yi, Xiaobo; Zhang, Hanzheng; Gong, Ping

    2008-11-01

    IP packet based services such as high speed internet, IP voice and IP video will be widely deployed in telecom network, which make transport network evolution to packet transport network. Characteristics of transport network and requirements of packet transport network are analyzed, T-MPLS/MPLS-TP based PTN technology is given and it will be used in metro (access, aggregation and core) network.

  1. Network of listed companies based on common shareholders and the prediction of market volatility

    Science.gov (United States)

    Li, Jie; Ren, Da; Feng, Xu; Zhang, Yongjie

    2016-11-01

    In this paper, we build a network of listed companies in the Chinese stock market based on common shareholding data from 2003 to 2013. We analyze the evolution of topological characteristics of the network (e.g., average degree, diameter, average path length and clustering coefficient) with respect to the time sequence. Additionally, we consider the economic implications of topological characteristic changes on market volatility and use them to make future predictions. Our study finds that the network diameter significantly predicts volatility. After adding control variables used in traditional financial studies (volume, turnover and previous volatility), network topology still significantly influences volatility and improves the predictive ability of the model.

  2. Discussion on the Trend of Mobile Core Network Virtualization Evolution%移动核心网虚拟化演进趋势探讨

    Institute of Scientific and Technical Information of China (English)

    苗杰; 高功应

    2014-01-01

    Based on the mobile Internet era background, it analyzes the conception of network function virtualization and the need for net-work virtualization evolution, presents the demand for mobile core network virtualization, and also discusses the architecture evolution trend for mobile core network.%从移动互联网时代背景出发,对网络功能虚拟化概念、网络虚拟化演进的必要性进行分析,指出了移动核心网虚拟化需求,并针对移动核心网虚拟化演进架构趋势进行了探讨。

  3. Identifying influential nodes in dynamic social networks based on degree-corrected stochastic block model

    Science.gov (United States)

    Wang, Tingting; Dai, Weidi; Jiao, Pengfei; Wang, Wenjun

    2016-05-01

    Many real-world data can be represented as dynamic networks which are the evolutionary networks with timestamps. Analyzing dynamic attributes is important to understanding the structures and functions of these complex networks. Especially, studying the influential nodes is significant to exploring and analyzing networks. In this paper, we propose a method to identify influential nodes in dynamic social networks based on identifying such nodes in the temporal communities which make up the dynamic networks. Firstly, we detect the community structures of all the snapshot networks based on the degree-corrected stochastic block model (DCBM). After getting the community structures, we capture the evolution of every community in the dynamic network by the extended Jaccard’s coefficient which is defined to map communities among all the snapshot networks. Then we obtain the initial influential nodes of the dynamic network and aggregate them based on three widely used centrality metrics. Experiments on real-world and synthetic datasets demonstrate that our method can identify influential nodes in dynamic networks accurately, at the same time, we also find some interesting phenomena and conclusions for those that have been validated in complex network or social science.

  4. Autonomous robot behavior based on neural networks

    Science.gov (United States)

    Grolinger, Katarina; Jerbic, Bojan; Vranjes, Bozo

    1997-04-01

    The purpose of autonomous robot is to solve various tasks while adapting its behavior to the variable environment, expecting it is able to navigate much like a human would, including handling uncertain and unexpected obstacles. To achieve this the robot has to be able to find solution to unknown situations, to learn experienced knowledge, that means action procedure together with corresponding knowledge on the work space structure, and to recognize working environment. The planning of the intelligent robot behavior presented in this paper implements the reinforcement learning based on strategic and random attempts for finding solution and neural network approach for memorizing and recognizing work space structure (structural assignment problem). Some of the well known neural networks based on unsupervised learning are considered with regard to the structural assignment problem. The adaptive fuzzy shadowed neural network is developed. It has the additional shadowed hidden layer, specific learning rule and initialization phase. The developed neural network combines advantages of networks based on the Adaptive Resonance Theory and using shadowed hidden layer provides ability to recognize lightly translated or rotated obstacles in any direction.

  5. Long-Term Evolution of Email Networks: Statistical Regularities, Predictability and Stability of Social Behaviors.

    Science.gov (United States)

    Godoy-Lorite, Antonia; Guimerà, Roger; Sales-Pardo, Marta

    2016-01-01

    In social networks, individuals constantly drop ties and replace them by new ones in a highly unpredictable fashion. This highly dynamical nature of social ties has important implications for processes such as the spread of information or of epidemics. Several studies have demonstrated the influence of a number of factors on the intricate microscopic process of tie replacement, but the macroscopic long-term effects of such changes remain largely unexplored. Here we investigate whether, despite the inherent randomness at the microscopic level, there are macroscopic statistical regularities in the long-term evolution of social networks. In particular, we analyze the email network of a large organization with over 1,000 individuals throughout four consecutive years. We find that, although the evolution of individual ties is highly unpredictable, the macro-evolution of social communication networks follows well-defined statistical patterns, characterized by exponentially decaying log-variations of the weight of social ties and of individuals' social strength. At the same time, we find that individuals have social signatures and communication strategies that are remarkably stable over the scale of several years.

  6. Building Service Delivery Networks: Partnership Evolution Among Children’s Behavioral Health Agencies in Response to New Funding

    Science.gov (United States)

    Bunger, Alicia C.; Doogan, Nathan J.; Cao, Yiwen

    2014-01-01

    Meeting the complex needs of youth with behavioral health problems requires a coordinated network of community-based agencies. Although fiscal scarcity or retrenchment can limit coordinated services, munificence can stimulate service delivery partnerships as agencies expand programs, hire staff, and spend more time coordinating services. This study examines the 2-year evolution of referral and staff expertise sharing networks in response to substantial new funding for services within a regional network of children’s mental health organizations. Quantitative network survey data were collected from directors of 22 nonprofit organizations that receive funding from a county government-based behavioral health service fund. Both referral and staff expertise sharing networks changed over time, but results of a stochastic actor-oriented model of network dynamics suggest the nature of this change varies for these networks. Agencies with higher numbers of referral and staff expertise sharing partners tend to maintain these ties and/or develop new relationships over the 2 years. Agencies tend to refer to agencies they trust, but trust was not associated with staff expertise sharing ties. However, agencies maintain or form staff expertise sharing ties with referral partners, or with organizations that provide similar services. In addition, agencies tend to reciprocate staff expertise sharing, but not referrals. Findings suggest that during periods of resource munificence and service expansion, behavioral health organizations build service delivery partnerships in complex ways that build upon prior collaborative history and coordinate services among similar types of providers. Referral partnerships can pave the way for future information sharing relationships. PMID:25574359

  7. Overlapping Community Detection based on Network Decomposition

    Science.gov (United States)

    Ding, Zhuanlian; Zhang, Xingyi; Sun, Dengdi; Luo, Bin

    2016-04-01

    Community detection in complex network has become a vital step to understand the structure and dynamics of networks in various fields. However, traditional node clustering and relatively new proposed link clustering methods have inherent drawbacks to discover overlapping communities. Node clustering is inadequate to capture the pervasive overlaps, while link clustering is often criticized due to the high computational cost and ambiguous definition of communities. So, overlapping community detection is still a formidable challenge. In this work, we propose a new overlapping community detection algorithm based on network decomposition, called NDOCD. Specifically, NDOCD iteratively splits the network by removing all links in derived link communities, which are identified by utilizing node clustering technique. The network decomposition contributes to reducing the computation time and noise link elimination conduces to improving the quality of obtained communities. Besides, we employ node clustering technique rather than link similarity measure to discover link communities, thus NDOCD avoids an ambiguous definition of community and becomes less time-consuming. We test our approach on both synthetic and real-world networks. Results demonstrate the superior performance of our approach both in computation time and accuracy compared to state-of-the-art algorithms.

  8. Automatic evolution of heat exchanger networks with simultaneous heat exchanger design

    Energy Technology Data Exchange (ETDEWEB)

    Liporace, F.S.; Pessoa, F.L.P.; Queiroz, E.M. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Escola de Quimica. Dept. de Engenharia Quimica]. E-mail: lipo@h2o.eq.ufrj.br; lipo@hexanet.com.br

    1999-03-01

    Recently, a new software (AtHENS) that automatically synthesizes a heat exchanger network with minima consumption of utilities was developed. This work deals with the next step, which represents the evolution of the initial network. Hence, new procedures to identify and break loops are incorporated, for which a new algorithm is proposed. Also, a heat exchanger design procedure which uses the available pressure drop to determine the film coefficient on the tube side and shell side is added, providing the utilization of more realistic heat exchangers in the network during its optimization. Results obtained from a case study point to the possibility of equipment design having a strong influence on the network synthesis. (author)

  9. AUTOMATIC EVOLUTION OF HEAT EXCHANGER NETWORKS WITH SIMULTANEOUS HEAT EXCHANGER DESIGN

    Directory of Open Access Journals (Sweden)

    F.S. LIPORACE

    1999-03-01

    Full Text Available Recently, a new software (AtHENS that automatically synthesizes a heat exchanger network with minima consumption of utilities was developed. This work deals with the next step, which represents the evolution of the initial network. Hence, new procedures to identify and break loops are incorporated, for which a new algorithm is proposed. Also, a heat exchanger design procedure which uses the available pressure drop to determine the film coefficient on the tube side and shell side is added, providing the utilization of more realistic heat exchangers in the network during its optimization. Results obtained from a case study point to the possibility of equipment design having a strong influence on the network synthesis.

  10. Evolution of a Network of Vortex Loops in the Turbulent Superfluid Helium; Derivation of the Vinen Equation

    OpenAIRE

    Nemirovskii, Sergey K.

    2006-01-01

    The evolution a network of vortex loops due to the fusion and breakdown in the turbulent superfluid helium is studied. We perform investigation on the base of the "rate equation" for the distribution function $n(l)$ of number of loops in space of their length $l$. There are two mechanisms for change of quantity $n(l)$. Firstly, the function changes due to deterministic process of mutual friction, when the length grows or decreases depending on orientation. Secondly, the change of $n(l)$ occur...

  11. Need Based Network Traffic Collection

    Science.gov (United States)

    2015-02-15

    release, distribution unlimited. 13. SUPPLEMENTARY NOTES The original document contains color images. 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY ...material is based upon work funded and supported by Department of Homeland Security Department of Defense under Contract No. FA8721-05-C-0003 with...Corruption #6 UDP: DNS DoS/DDoS Floods #8 DP: Remote Connections DoS/D,DoS Crashes #7 UDP: VoiiP Q I e Software Engineering Institute I Carnegie Mellon Uni

  12. Simulation of Neurocomputing Based on Photophobic Reactions of Euglena: Toward Microbe-Based Neural Network Computing

    Science.gov (United States)

    Ozasa, Kazunari; Aono, Masashi; Maeda, Mizuo; Hara, Masahiko

    In order to develop an adaptive computing system, we investigate microscopic optical feedback to a group of microbes (Euglena gracilis in this study) with a neural network algorithm, expecting that the unique characteristics of microbes, especially their strategies to survive/adapt against unfavorable environmental stimuli, will explicitly determine the temporal evolution of the microbe-based feedback system. The photophobic reactions of Euglena are extracted from experiments, and built in the Monte-Carlo simulation of a microbe-based neurocomputing. The simulation revealed a good performance of Euglena-based neurocomputing. Dynamic transition among the solutions is discussed from the viewpoint of feedback instability.

  13. Compensatory evolution for a gene deletion is not limited to its immediate functional network

    Directory of Open Access Journals (Sweden)

    Bull JJ

    2009-05-01

    Full Text Available Abstract Background Genetic disruption of an important phenotype should favor compensatory mutations that restore the phenotype. If the genetic basis of the phenotype is modular, with a network of interacting genes whose functions are specific to that phenotype, compensatory mutations are expected among the genes of the affected network. This perspective was tested in the bacteriophage T3 using a genome deleted of its DNA ligase gene, disrupting DNA metabolism. Results In two replicate, long-term adaptations, phage compensatory evolution accommodated the low ligase level provided by the host without reinventing its own ligase. In both lines, fitness increased substantially but remained well below that of the intact genome. Each line accumulated over a dozen compensating mutations during long-term adaptation, and as expected, many of the compensatory changes were within the DNA metabolism network. However, several compensatory changes were outside the network and defy any role in DNA metabolism or biochemical connection to the disruption. In one line, these extra-network changes were essential to the recovery. The genes experiencing compensatory changes were moderately conserved between T3 and its relative T7 (25% diverged, but the involvement of extra-network changes was greater in T3. Conclusion Compensatory evolution was only partly limited to the known functionally interacting partners of the deleted gene. Thus gene interactions contributing to fitness were more extensive than suggested by the functional properties currently ascribed to the genes. Compensatory evolution offers an easy method of discovering genome interactions among specific elements that does not rest on an a priori knowledge of those elements or their interactions.

  14. Optimization of air quantity regulation in mine ventilation networks using the improved differential evolution algorithm and critical path method

    Institute of Scientific and Technical Information of China (English)

    Chen Kaiyan; Si Junhong; Zhou Fubao; Zhang Renwei; Shao He; Zhao Hongmei

    2015-01-01

    In mine ventilation networks, the reasonable airflow distribution is very important for the production safety and economy. Three basic problems of the natural, full-controlled and semi-controlled splitting were reviewed in the paper. Aiming at the high difficulty semi-controlled splitting problem, the general nonlinear multi-objectives optimization mathematical model with constraints was established based on the theory of mine ventilation networks. A new algorithm, which combined the improved differential evaluation and the critical path method (CPM) based on the multivariable separate solution strategy, was put forward to search for the global optimal solution more efficiently. In each step of evolution, the feasible solutions of air quantity distribution are firstly produced by the improved differential evolu-tion algorithm, and then the optimal solutions of regulator pressure drop are obtained by the CPM. Through finite steps iterations, the optimal solution can be given. In this new algorithm, the population of feasible solutions were sorted and grouped for enhancing the global search ability and the individuals in general group were randomly initialized for keeping diversity. Meanwhile, the individual neighbor-hood in the fine group which may be closely to the optimal solutions were searched locally and slightly for achieving a balance between global searching and local searching, thus improving the convergence rate. The computer program was developed based on this method. Finally, the two ventilation networks with single-fan and multi-fans were solved. The results show that this algorithm has advantages of high effectiveness, fast convergence, good robustness and flexibility. This computer program could be used to solve large-scale generalized ventilation networks optimization problem in the future.

  15. Chaotic evolution of prisoner's dilemma game with volunteering on interdependent networks

    Science.gov (United States)

    Luo, Chao; Zhang, Xiaolin; Zheng, YuanJie

    2017-06-01

    In this article, the evolution of prisoner's dilemma game with volunteering on interdependent networks is investigated. Different from the traditional two-strategy game, voluntary participation as an additional strategy is involved in repeated game, that can introduce more complex evolutionary dynamics. And, interdependent networks provide a more generalized network architecture to study the intricate variability of dynamics. We have showed that voluntary participation could effectively promote the density of co-operation, that is also greatly affected by interdependent strength between two coupled networks. We further discussed the influence of interdependent strength on the densities of different strategies and found that an intermediate interdependence would play a bigger role on the evolution of dynamics. Subsequently, the critical values of the defection temptation for phase transitions under different conditions have been studied. Moreover, the global oscillations induced by the circle of dominance of three strategies on interdependent networks have been quantitatively investigated. Counter-intuitively, the oscillations of strategy densities are not periodic or stochastic, but have rich dynamical behaviors. By means of various analysis tools, we have demonstrated the global oscillations of strategy densities possessed chaotic characteristics.

  16. Application of detecting algorithm based on network

    Institute of Scientific and Technical Information of China (English)

    张凤斌; 杨永田; 江子扬; 孙冰心

    2004-01-01

    Because currently intrusion detection systems cannot detect undefined intrusion behavior effectively,according to the robustness and adaptability of the genetic algorithms, this paper integrates the genetic algorithms into an intrusion detection system, and a detection algorithm based on network traffic is proposed. This algorithm is a real-time and self-study algorithm and can detect undefined intrusion behaviors effectively.

  17. Location-based Forwarding in Vehicular Networks

    NARCIS (Netherlands)

    Klein Wolterink, W.

    2013-01-01

    In this thesis we focus on location-based message forwarding in vehicular networks to support intelligent transportation systems (ITSs). ITSs are transport systems that utilise information and communication technologies to increase their level of automation, in this way levering the performance of

  18. Evolution of egoism on semi-directed and undirected Barabási-Albert networks

    Science.gov (United States)

    Lima, F. W. S.

    2015-05-01

    Through Monte Carlo simulations, we study the evolution of the four strategies: Ethnocentric, altruistic, egoistic and cosmopolitan in one community of individuals. Interactions and reproduction among computational agents are simulated on undirected and semi-directed Barabási-Albert (BA) networks. We study the Hammond-Axelrod (HA) model on undirected and semi-directed BA networks for the asexual reproduction case. With a small modification in the traditional HA model, our simulations showed that egoism wins, differently from other results found in the literature where ethnocentric strategy is common. Here, mechanisms such as reciprocity are absent.

  19. Schwann cells and their transcriptional network: Evolution of key regulators of peripheral myelination.

    Science.gov (United States)

    Stolt, C Claus; Wegner, Michael

    2016-06-15

    As derivatives of the neural crest, Schwann cells represent a vertebrate invention. Their development and differentiation is under control of a newly constructed, vertebrate-specific regulatory network that contains Sox10, Oct6 and Krox20 as cornerstones and central regulators of peripheral myelination. In this review, we discuss the function and relationship of these transcription factors among each other and in the context of their regulatory network, and present ideas of how neofunctionalization may have helped to recruit them to their novel task in Schwann cells. This article is part of a Special Issue entitled SI: Myelin Evolution.

  20. Role of the FUL-SHP network in the evolution of fruit morphology and function.

    Science.gov (United States)

    Ferrándiz, Cristina; Fourquin, Chloé

    2014-08-01

    Arabidopsis research in the last decade has started to unravel the genetic networks directing gynoecium and fruit patterning in this model species. Only recently, the work from several groups has also started to address the conservation of these networks in a wide number of species with very different fruit morphologies, and we are now beginning to understand how they might have evolved. This review summarizes recent advances in this field, focusing mainly on MADS-box genes with a well-known role in dehiscence zone development, while also discussing how these studies may contribute to expand our views on fruit evolution.

  1. Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

    Science.gov (United States)

    Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P; Gerstein, Mark

    2010-05-18

    The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers' continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems.

  2. Evolution of Web-based International Marketing

    DEFF Research Database (Denmark)

    Rask, Morten

    2002-01-01

    Companies that have been doing international business do not usually make the transition from traditional marketers to full-blown Web marketers in one sharp step. In our study of Danish firms, we found that in terms of the evolution of their Web strategies, these Danish companies went through three...... stages. We call these stages: 1) the Electronic Brochure, 2) the Electronic Manual, and 3) the Electronic Store. Moving from the Brochure to the Manual to the Store stage entails an increasing intensity of interaction between the company's website and its customers. Companies have to go through...

  3. SAR ATR Based on Convolutional Neural Network

    Directory of Open Access Journals (Sweden)

    Tian Zhuangzhuang

    2016-06-01

    Full Text Available This study presents a new method of Synthetic Aperture Radar (SAR image target recognition based on a convolutional neural network. First, we introduce a class separability measure into the cost function to improve this network’s ability to distinguish between categories. Then, we extract SAR image features using the improved convolutional neural network and classify these features using a support vector machine. Experimental results using moving and stationary target acquisition and recognition SAR datasets prove the validity of this method.

  4. Statistically validated mobile communication networks: Evolution of motifs in European and Chinese data

    CERN Document Server

    Li, Ming-Xia; Jiang, Zhi-Qiang; Kaski, Kimmo; Kertész, Janos; Miccichè, Salvatore; Tumminello, Michele; Zhou, Wei-Xing; Mantegna, Rosario N

    2014-01-01

    Big data open up unprecedented opportunities to investigate complex systems including the society. In particular, communication data serve as major sources for computational social sciences but they have to be cleaned and filtered as they may contain spurious information due to recording errors as well as interactions, like commercial and marketing activities, not directly related to the social network. The network constructed from communication data can only be considered as a proxy for the network of social relationships. Here we apply a systematic method, based on multiple hypothesis testing, to statistically validate the links and then construct the corresponding Bonferroni network, generalized to the directed case. We study two large datasets of mobile phone records, one from Europe and the other from China. For both datasets we compare the raw data networks with the corresponding Bonferroni networks and point out significant differences in the structures and in the basic network measures. We show eviden...

  5. The interaction evolution model of mass incidents with delay in a social network

    Science.gov (United States)

    Huo, Liang'an; Ma, Chenyang

    2017-10-01

    Recent years have witnessed rapid development of information technology. Today, modern media is widely used for the purpose of spreading information rapidly and widely. In particular, through micro-blog promotions, individuals tend to express their viewpoints and spread information on the internet, which could easily lead to public opinions. Moreover, government authorities also disseminate official information to guide public opinion and eliminate any incorrect conjecture. In this paper, a dynamical model with two delays is investigated to exhibit the interaction evolution between the public and official opinion fields in network mass incidents. Based on the theory of differential equations, the interaction mechanism between two public opinion fields in a micro-blog environment is analyzed. Two delays are proposed in the model to depict the response delays of public and official opinion fields. Some stable conditions are obtained, which shows that Hopf bifurcation can occur as delays cross critical values. Further, some numerical simulations are carried out to verify theoretical results. Our model indicates that there exists a golden time for government intervention, which should be emphasized given the impact of modern media and inaccurate rumors. If the government releases official information during the golden time, mass incidents on the internet can be controlled effectively.

  6. A toolbox model of evolution of metabolic pathways on networks of arbitrary topology.

    Directory of Open Access Journals (Sweden)

    Tin Yau Pang

    2011-05-01

    Full Text Available In prokaryotic genomes the number of transcriptional regulators is known to be proportional to the square of the total number of protein-coding genes. A toolbox model of evolution was recently proposed to explain this empirical scaling for metabolic enzymes and their regulators. According to its rules, the metabolic network of an organism evolves by horizontal transfer of pathways from other species. These pathways are part of a larger "universal" network formed by the union of all species-specific networks. It remained to be understood, however, how the topological properties of this universal network influence the scaling law of functional content of genomes in the toolbox model. Here we answer this question by first analyzing the scaling properties of the toolbox model on arbitrary tree-like universal networks. We prove that critical branching topology, in which the average number of upstream neighbors of a node is equal to one, is both necessary and sufficient for quadratic scaling. We further generalize the rules of the model to incorporate reactions with multiple substrates/products as well as branched and cyclic metabolic pathways. To achieve its metabolic tasks, the new model employs evolutionary optimized pathways with minimal number of reactions. Numerical simulations of this realistic model on the universal network of all reactions in the KEGG database produced approximately quadratic scaling between the number of regulated pathways and the size of the metabolic network. To quantify the geometrical structure of individual pathways, we investigated the relationship between their number of reactions, byproducts, intermediate, and feedback metabolites. Our results validate and explain the ubiquitous appearance of the quadratic scaling for a broad spectrum of topologies of underlying universal metabolic networks. They also demonstrate why, in spite of "small-world" topology, real-life metabolic networks are characterized by a broad

  7. Implementation Method of Circuit Evolution Based on Artificial Neural Network Model%基于类神经网络模型的电路演化实现方法

    Institute of Scientific and Technical Information of China (English)

    崔新风; 娄建安; 褚杰; 原亮; 丁国良

    2011-01-01

    为解决目前数字型演化硬件研究中存在的电路编码困难问题,提出一个可用矩阵形式描述组合电路的类神经网络门级电路模型,讨论在此模型上进行电路编码的具体方法.根据编码矩阵特点,对标准遗传算法进行改进,设计遗传操作算子、适应度评估方法等.通过无刷直流电动机电子换相电路的成功演化实例,验证了采用矩阵编码和改进遗传算法实现数字电路演化的可行性.%For the purpose of solving the encoding problem harassed the digital Evolvable Hardware(EHW) researchers, a gate-level circuit model which is based on the similarities between combinatorial circuit and neural network is proposed, on which the matrix encoding scheme of combinatorial circuit is discussed. An improved genetic algorithm is used to evolve the encoding matrix, genetic operators and fitness evaluation method are designed according to the characteristics of circuit encoding. The implementation of the commutation circuit of brushless direct current motor proves the feasibility of the implementation method of digital EHW by the using of matrix encoding scheme and the improved genetic algorithm.

  8. Network Based High Speed Product Innovation

    DEFF Research Database (Denmark)

    Lindgren, Peter

    In the first decade of the 21st century, New Product Development has undergone major changes in the way NPD is managed and organised. This is due to changes in technology, market demands, and in the competencies of companies. As a result NPD organised in different forms of networks is predicted...... to be of ever-increasing importance to many different kinds of companies. This happens at the same times as the share of new products of total turnover and earnings is increasing at unprecedented speed in many firms and industries. The latter results in the need for very fast innovation and product development...... - a need that can almost only be resolved by organising NPD in some form of network configuration. The work of Peter Lindgren is on several aspects of network based high speed product innovation and contributes to a descriptive understanding of this phenomenon as well as with normative theory on how NPD...

  9. Quantum networks based on cavity QED

    Energy Technology Data Exchange (ETDEWEB)

    Ritter, Stephan; Bochmann, Joerg; Figueroa, Eden; Hahn, Carolin; Kalb, Norbert; Muecke, Martin; Neuzner, Andreas; Noelleke, Christian; Reiserer, Andreas; Uphoff, Manuel; Rempe, Gerhard [Max-Planck-Institut fuer Quantenoptik, Hans-Kopfermann-Strasse 1, 85748 Garching (Germany)

    2014-07-01

    Quantum repeaters require an efficient interface between stationary quantum memories and flying photons. Single atoms in optical cavities are ideally suited as universal quantum network nodes that are capable of sending, storing, retrieving, and even processing quantum information. We demonstrate this by presenting an elementary version of a quantum network based on two identical nodes in remote, independent laboratories. The reversible exchange of quantum information and the creation of remote entanglement are achieved by exchange of a single photon. Quantum teleportation is implemented using a time-resolved photonic Bell-state measurement. Quantum control over all degrees of freedom of the single atom also allows for the nondestructive detection of flying photons and the implementation of a quantum gate between the spin state of the atom and the polarization of a photon upon its reflection from the cavity. Our approach to quantum networking offers a clear perspective for scalability and provides the essential components for the realization of a quantum repeater.

  10. Agent-based model of information spread in social networks

    CERN Document Server

    Lande, D V; Berezin, B O

    2016-01-01

    We propose evolution rules of the multiagent network and determine statistical patterns in life cycle of agents - information messages. The main discussed statistical pattern is connected with the number of likes and reposts for a message. This distribution corresponds to Weibull distribution according to modeling results. We examine proposed model using the data from Twitter, an online social networking service.

  11. Faster convergence of imaginary time evolution tensor network algorithms by recycling the environment

    CERN Document Server

    Phien, Ho N; Vidal, Guifré

    2014-01-01

    We propose an environment recycling scheme to speed up a class of tensor network algorithms that produce an approximation to the ground state of a local Hamiltonian by simulating an evolution in imaginary time. Specifically, we consider the time-evolving block decimation (TEBD) algorithm applied to infinite systems in 1D and 2D, where the ground state is encoded, respectively, in a matrix product state (MPS) and in a projected entangled-pair state (PEPS). An important ingredient of the TEBD algorithm (and a main computational bottle-neck, especially with PEPS in 2D) is the computation of the so-called environment, which is used to determine how to optimally truncate the bond indices of the tensor network so that their dimension is kept constant. In current algorithms, the environment is computed at each step of the imaginary time evolution, to account for the changes that the time evolution introduces in the many-body state represented by the tensor network. Our key insight is that close to convergence, most ...

  12. A framework for Internet service evolution based on active object

    Institute of Scientific and Technical Information of China (English)

    HU Hua; ZHANG Yang

    2006-01-01

    The wide use of Internet Service in distributed computing and e-business has made the evolution of Internet Service to be one of the most prevalent research fields in software development domain. Traditional methods for software development cannot adapt to the challenge of Internet Service oriented software development. In this paper, we propose a new paradigm for the evolution of Internet Service with active objects from the characteristics of Internet Service and principles of active objects. The paradigm uses an automatic monitoring mechanism of active object to detect and process evolution requirement in system based on Internet Service.

  13. SOFM Neural Network Based Hierarchical Topology Control for Wireless Sensor Networks

    OpenAIRE

    2014-01-01

    Well-designed network topology provides vital support for routing, data fusion, and target tracking in wireless sensor networks (WSNs). Self-organization feature map (SOFM) neural network is a major branch of artificial neural networks, which has self-organizing and self-learning features. In this paper, we propose a cluster-based topology control algorithm for WSNs, named SOFMHTC, which uses SOFM neural network to form a hierarchical network structure, completes cluster head selection by the...

  14. Adaptive Game Level Creation through Rank-based Interactive Evolution

    DEFF Research Database (Denmark)

    Liapis, Antonios; Martínez, Héctor Pérez; Togelius, Julian

    2013-01-01

    as fitness functions for the optimization of the generated content. The preference models are built via ranking-based preference learning, while the content is generated via evolutionary search. The proposed method is evaluated on the creation of strategy game maps, and its performance is tested using...... artificial agents. Results suggest that RIE is both faster and more robust than standard interactive evolution and outperforms other state-of-the-art interactive evolution approaches....

  15. Convolutional Neural Network Based dem Super Resolution

    Science.gov (United States)

    Chen, Zixuan; Wang, Xuewen; Xu, Zekai; Hou, Wenguang

    2016-06-01

    DEM super resolution is proposed in our previous publication to improve the resolution for a DEM on basis of some learning examples. Meanwhile, the nonlocal algorithm is introduced to deal with it and lots of experiments show that the strategy is feasible. In our publication, the learning examples are defined as the partial original DEM and their related high measurements due to this way can avoid the incompatibility between the data to be processed and the learning examples. To further extent the applications of this new strategy, the learning examples should be diverse and easy to obtain. Yet, it may cause the problem of incompatibility and unrobustness. To overcome it, we intend to investigate a convolutional neural network based method. The input of the convolutional neural network is a low resolution DEM and the output is expected to be its high resolution one. A three layers model will be adopted. The first layer is used to detect some features from the input, the second integrates the detected features to some compressed ones and the final step transforms the compressed features as a new DEM. According to this designed structure, some learning DEMs will be taken to train it. Specifically, the designed network will be optimized by minimizing the error of the output and its expected high resolution DEM. In practical applications, a testing DEM will be input to the convolutional neural network and a super resolution will be obtained. Many experiments show that the CNN based method can obtain better reconstructions than many classic interpolation methods.

  16. Social roles and the evolution of networks in extreme and isolated environments

    Science.gov (United States)

    Johnson, Jeffrey C.; Boster, James S.; Palinkas, Lawrence A.

    2003-01-01

    This article reports on the evolution of network structure as it relates to formal and informal social roles in well-bounded, isolated groups. Research was conducted at the Amundsen-Scott South Pole Station. Data were collected on crewmembers' networks of social interaction over each of three winter-over periods, when the station is completely isolated. In addition, data were collected on the informal roles played by crewmembers (e.g., instrumental leadership, expressive leadership). The study found that globally coherent networks in winter-over groups were associated with group consensus on the presence of critically important informal social roles (e.g., expressive leadership) where global coherence is the extent to which a network forms a single group composed of a unitary core and periphery as opposed to being factionalized into two or more subgroups. Conversely, the evolution of multiple subgroups was associated with the absence of consensus on critical informal social roles, above all the critically important role of instrumental leader.

  17. Social roles and the evolution of networks in extreme and isolated environments

    Science.gov (United States)

    Johnson, Jeffrey C.; Boster, James S.; Palinkas, Lawrence A.

    2003-01-01

    This article reports on the evolution of network structure as it relates to formal and informal social roles in well-bounded, isolated groups. Research was conducted at the Amundsen-Scott South Pole Station. Data were collected on crewmembers' networks of social interaction over each of three winter-over periods, when the station is completely isolated. In addition, data were collected on the informal roles played by crewmembers (e.g., instrumental leadership, expressive leadership). The study found that globally coherent networks in winter-over groups were associated with group consensus on the presence of critically important informal social roles (e.g., expressive leadership) where global coherence is the extent to which a network forms a single group composed of a unitary core and periphery as opposed to being factionalized into two or more subgroups. Conversely, the evolution of multiple subgroups was associated with the absence of consensus on critical informal social roles, above all the critically important role of instrumental leader.

  18. C-GRAAL: common-neighbors-based global GRAph ALignment of biological networks.

    Science.gov (United States)

    Memišević, Vesna; Pržulj, Nataša

    2012-07-01

    Networks are an invaluable framework for modeling biological systems. Analyzing protein-protein interaction (PPI) networks can provide insight into underlying cellular processes. It is expected that comparison and alignment of biological networks will have a similar impact on our understanding of evolution, biological function, and disease as did sequence comparison and alignment. Here, we introduce a novel pairwise global alignment algorithm called Common-neighbors based GRAph ALigner (C-GRAAL) that uses heuristics for maximizing the number of aligned edges between two networks and is based solely on network topology. As such, it can be applied to any type of network, such as social, transportation, or electrical networks. We apply C-GRAAL to align PPI networks of eukaryotic and prokaryotic species, as well as inter-species PPI networks, and we demonstrate that the resulting alignments expose large connected and functionally topologically aligned regions. We use the resulting alignments to transfer biological knowledge across species, successfully validating many of the predictions. Moreover, we show that C-GRAAL can be used to align human-pathogen inter-species PPI networks and that it can identify patterns of pathogen interactions with host proteins solely from network topology.

  19. Evolution of ethnocentrism on undirected and directed Barabási-Albert networks

    Science.gov (United States)

    Lima, F. W. S.; Hadzibeganovic, Tarik; Stauffer, Dietrich

    2009-12-01

    Using Monte Carlo simulations, we study the evolution of contingent cooperation and ethnocentrism in the one-shot game. Interactions and reproduction among computational agents are simulated on undirected and directed Barabási-Albert (BA) networks. We first replicate the Hammond-Axelrod model of in-group favoritism on a square lattice and then generalize this model on undirected and directed BA networks for both asexual and sexual reproduction cases. Our simulations demonstrate that irrespective of the mode of reproduction, the ethnocentric strategy becomes common even though cooperation is individually costly and mechanisms such as reciprocity or conformity are absent. Moreover, our results indicate that the spread of favoritism towards similar others highly depends on the network topology and the associated heterogeneity of the studied population.

  20. Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution.

    Science.gov (United States)

    Mannakee, Brian K; Gutenkunst, Ryan N

    2016-07-01

    The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein's rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces.

  1. Selection on Network Dynamics Drives Differential Rates of Protein Domain Evolution.

    Directory of Open Access Journals (Sweden)

    Brian K Mannakee

    2016-07-01

    Full Text Available The long-held principle that functionally important proteins evolve slowly has recently been challenged by studies in mice and yeast showing that the severity of a protein knockout only weakly predicts that protein's rate of evolution. However, the relevance of these studies to evolutionary changes within proteins is unknown, because amino acid substitutions, unlike knockouts, often only slightly perturb protein activity. To quantify the phenotypic effect of small biochemical perturbations, we developed an approach to use computational systems biology models to measure the influence of individual reaction rate constants on network dynamics. We show that this dynamical influence is predictive of protein domain evolutionary rate within networks in vertebrates and yeast, even after controlling for expression level and breadth, network topology, and knockout effect. Thus, our results not only demonstrate the importance of protein domain function in determining evolutionary rate, but also the power of systems biology modeling to uncover unanticipated evolutionary forces.

  2. Structural power and the evolution of collective fairness in social networks.

    Science.gov (United States)

    Santos, Fernando P; Pacheco, Jorge M; Paiva, Ana; Santos, Francisco C

    2017-01-01

    From work contracts and group buying platforms to political coalitions and international climate and economical summits, often individuals assemble in groups that must collectively reach decisions that may favor each part unequally. Here we quantify to which extent our network ties promote the evolution of collective fairness in group interactions, modeled by means of Multiplayer Ultimatum Games (MUG). We show that a single topological feature of social networks-which we call structural power-has a profound impact on the tendency of individuals to take decisions that favor each part equally. Increased fair outcomes are attained whenever structural power is high, such that the networks that tie individuals allow them to meet the same partners in different groups, thus providing the opportunity to strongly influence each other. On the other hand, the absence of such close peer-influence relationships dismisses any positive effect created by the network. Interestingly, we show that increasing the structural power of a network leads to the appearance of well-defined modules-as found in human social networks that often exhibit community structure-providing an interaction environment that maximizes collective fairness.

  3. 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

  4. A Multiple Beamforming Network for Unequally Spaced Linear Array Based on CORPS

    Directory of Open Access Journals (Sweden)

    Armando Arce

    2015-01-01

    Full Text Available This paper proposes an alternative and innovative way to design a simpler beamforming network (BFN based on balancing alternated power combiners and dividers, to feed a nonuniformly spaced linear array with Gaussian amplitude and coherent (in-phase signals. Thus, a two-beam design configuration of the feeding network for a nonuniform array with beam steering capability is proposed and analyzed. The nonuniform aperture and the complex inputs of the feeding network are optimized by means of a differential evolution algorithm. In addition, a comparative analysis between a uniform and nonuniform linear array with the proposed feeding network is performed. Simulation results show the advantages and effectiveness of the proposed feeding network exploiting the nonuniformity of the antenna elements, in terms of side lobe level and directivity. Furthermore, research results show an inherent reduction in hardware complexity of the network.

  5. An Evolutionary Algorithm of the Regional Collaborative Innovation Based on Complex Network

    Directory of Open Access Journals (Sweden)

    Kun Wang

    2016-01-01

    Full Text Available This paper proposed a new perspective to study the evolution of regional collaborative innovation based on complex network theory. The two main conceptions of evolution, “graph with dynamic features” and “network evolution,” have been provided in advance. Afterwards, we illustrate the overall architecture and capability model of the regional collaborative innovation system, which contains several elements and participants. Therefore, we can definitely assume that the regional collaborative innovation system could be regarded as a complex network model. In the proposed evolutionary algorithm, we consider that each node in the network could only connect to less than a certain amount of neighbors, and the extreme value is determined by its importance. Through the derivation, we have created a probability density function as the most important constraint and supporting condition of our simulation experiments. Then, a case study was performed to explore the network topology and validate the effectiveness of our algorithm. All the raw datasets were obtained from the official website of the National Bureau of Statistic of China and some other open sources. Finally, some meaningful recommendations were presented to policy makers, especially based on the experimental results and some common conclusions of complex networks.

  6. Self-Assembly of Single-Layer CoAl-Layered Double Hydroxide Nanosheets on 3D Graphene Network Used as Highly Efficient Electrocatalyst for Oxygen Evolution Reaction.

    Science.gov (United States)

    Ping, Jianfeng; Wang, Yixian; Lu, Qipeng; Chen, Bo; Chen, Junze; Huang, Ying; Ma, Qinglang; Tan, Chaoliang; Yang, Jian; Cao, Xiehong; Wang, Zhijuan; Wu, Jian; Ying, Yibin; Zhang, Hua

    2016-09-01

    A non-noble metal based 3D porous electrocatalyst is prepared by self-assembly of the liquid-exfoliated single-layer CoAl-layered double hydroxide nanosheets (CoAl-NSs) onto 3D graphene network, which exhibits higher catalytic activity and better stability for electrochemical oxygen evolution reaction compared to the commercial IrO2 nanoparticle-based 3D porous electrocatalyst.

  7. An Empirical Research of Network Organization Evolution Based on Entropy Change Model%基于熵变模型的网络组织演化实证研究

    Institute of Scientific and Technical Information of China (English)

    丁月华; 王俊岭

    2014-01-01

    文章将表征网络组织运行状态的熵归纳为环境熵、结构熵、契约熵、运行熵等4种类型18个指标,从而运用信息熵公式计算出网络组织管理系统不同时点上的熵值,以此来判断其进化状态。以太原不锈钢产业园区企业网络为例,利用信息熵公式,计算出2007-2011各年的熵值,得出结论:该网络组织成员之间的关系越来越紧密,运行效率越来越高。%The paper sums up the entropy, which describes the operational status of the network organization, into four types with 18 indicators:environmental entropy, structural entropy, contractual entropy and operational entropy. It also calculates the entropy value of the network organization management system at different time points by applying information entropy formu-la to judge network organization’s evolutionary status. The paper takes the corporate network of Taiyuan Stainless Steel Industri-al Park as an example and calculates the annual entropy from the year of 2007 to 2011 by using information entropy formula. The conclusion is that the relationship between the members of the network organization is becoming more and more close,and the operation efficiency is getting more and more high.

  8. Network Tomography Based on Additive Metrics

    CERN Document Server

    Ni, Jian

    2008-01-01

    Inference of the network structure (e.g., routing topology) and dynamics (e.g., link performance) is an essential component in many network design and management tasks. In this paper we propose a new, general framework for analyzing and designing routing topology and link performance inference algorithms using ideas and tools from phylogenetic inference in evolutionary biology. The framework is applicable to a variety of measurement techniques. Based on the framework we introduce and develop several polynomial-time distance-based inference algorithms with provable performance. We provide sufficient conditions for the correctness of the algorithms. We show that the algorithms are consistent (return correct topology and link performance with an increasing sample size) and robust (can tolerate a certain level of measurement errors). In addition, we establish certain optimality properties of the algorithms (i.e., they achieve the optimal $l_\\infty$-radius) and demonstrate their effectiveness via model simulation.

  9. Neural Network-Based Hyperspectral Algorithms

    Science.gov (United States)

    2016-06-07

    Neural Network-Based Hyperspectral Algorithms Walter F. Smith, Jr. and Juanita Sandidge Naval Research Laboratory Code 7340, Bldg 1105 Stennis Space...our effort is development of robust numerical inversion algorithms , which will retrieve inherent optical properties of the water column as well as...validate the resulting inversion algorithms with in-situ data and provide estimates of the error bounds associated with the inversion algorithm . APPROACH

  10. Community detection based on network communicability

    Science.gov (United States)

    Estrada, Ernesto

    2011-03-01

    We propose a new method for detecting communities based on the concept of communicability between nodes in a complex network. This method, designated as N-ComBa K-means, uses a normalized version of the adjacency matrix to build the communicability matrix and then applies K-means clustering to find the communities in a graph. We analyze how this method performs for some pathological cases found in the analysis of the detection limit of communities and propose some possible solutions on the basis of the analysis of the ratio of local to global densities in graphs. We use four different quality criteria for detecting the best clustering and compare the new approach with the Girvan-Newman algorithm for the analysis of two "classical" networks: karate club and bottlenose dolphins. Finally, we analyze the more challenging case of homogeneous networks with community structure, for which the Girvan-Newman completely fails in detecting any clustering. The N-ComBa K-means approach performs very well in these situations and we applied it to detect the community structure in an international trade network of miscellaneous manufactures of metal having these characteristics. Some final remarks about the general philosophy of community detection are also discussed.

  11. Controls on stream network branching angles, tested using landscape evolution models

    Science.gov (United States)

    Theodoratos, Nikolaos; Seybold, Hansjörg; Kirchner, James W.

    2016-04-01

    Stream networks are striking landscape features. The topology of stream networks has been extensively studied, but their geometry has received limited attention. Analyses of nearly 1 million stream junctions across the contiguous United States [1] have revealed that stream branching angles vary systematically with climate and topographic gradients at continental scale. Stream networks in areas with wet climates and gentle slopes tend to have wider branching angles than in areas with dry climates or steep slopes, but the mechanistic linkages underlying these empirical correlations remain unclear. Under different climatic and topographic conditions different runoff generation mechanisms and, consequently, transport processes are dominant. Models [2] and experiments [3] have shown that the relative strength of channel incision versus diffusive hillslope transport controls the spacing between valleys, an important geometric property of stream networks. We used landscape evolution models (LEMs) to test whether similar factors control network branching angles as well. We simulated stream networks using a wide range of hillslope diffusion and channel incision parameters. The resulting branching angles vary systematically with the parameters, but by much less than the regional variability in real-world stream networks. Our results suggest that the competition between hillslope and channeling processes influences branching angles, but that other mechanisms may also be needed to account for the variability in branching angles observed in the field. References: [1] H. Seybold, D. H. Rothman, and J. W. Kirchner, 2015, Climate's watermark in the geometry of river networks, Submitted manuscript. [2] J. T. Perron, W. E. Dietrich, and J. W. Kirchner, 2008, Controls on the spacing of first-order valleys, Journal of Geophysical Research, 113, F04016. [3] K. E. Sweeney, J. J. Roering, and C. Ellis, 2015, Experimental evidence for hillslope control of landscape scale, Science, 349

  12. Evolving dynamics of trading behavior based on coordination game in complex networks

    Science.gov (United States)

    Bian, Yue-tang; Xu, Lu; Li, Jin-sheng

    2016-05-01

    This work concerns the modeling of evolvement of trading behavior in stock markets. Based on the assumption of the investors' limited rationality, the evolution mechanism of trading behavior is modeled according to the investment strategy of coordination game in network, that investors are prone to imitate their neighbors' activity through comprehensive analysis on the risk dominance degree of certain investment behavior, the network topology of their relationship and its heterogeneity. We investigate by mean-field analysis and extensive simulations the evolution of investors' trading behavior in various typical networks under different risk dominance degree of investment behavior. Our results indicate that the evolution of investors' behavior is affected by the network structure of stock market and the effect of risk dominance degree of investment behavior; the stability of equilibrium states of investors' behavior dynamics is directly related with the risk dominance degree of some behavior; connectivity and heterogeneity of the network plays an important role in the evolution of the investment behavior in stock market.

  13. Plasticity of brain wave network interactions and evolution across physiologic states

    Directory of Open Access Journals (Sweden)

    Kang K. L. Liu

    2015-10-01

    Full Text Available Neural plasticity transcends a range of spatio-temporal scales and serves as the basis of various brain activities and physiologic functions. At the microscopic level, it enables the emergence of brain waves with complex temporal dynamics. At the macroscopic level, presence and dominance of specific brain waves is associated with important brain functions. The role of neural plasticity at different levels in generating distinct brain rhythms and how brain rhythms communicate with each other across brain areas to generate physiologic states and functions remains not understood. Here we perform an empirical exploration of neural plasticity at the level of brain wave network interactions representing dynamical communications within and between different brain areas in the frequency domain. We introduce the concept of time delay stability to quantify coordinated bursts in the activity of brain waves, and we employ a system-wide Network Physiology integrative approach to probe the network of coordinated brain wave activations and its evolution across physiologic states. We find an association between network structure and physiologic states. We uncover a hierarchical reorganization in the brain wave networks in response to changes in physiologic state, indicating new aspects of neural plasticity at the integrated level. Globally, we find that the entire brain network undergoes a pronounced transition from low connectivity in Deep Sleep and REM to high connectivity in Light Sleep and Wake. In contrast, we find that locally, different brain areas exhibit different network dynamics of brain wave interactions to achieve differentiation in function during different sleep stages. Moreover, our analyses indicate that plasticity also emerges in frequency-specific networks, which represent interactions across brain locations mediated through a specific frequency band. Comparing frequency-specific networks within the same physiologic state we find very

  14. STRUCTURAL EVOLUTION IN BIORENEWABLE SOY BASED POLYURETHANES

    Institute of Scientific and Technical Information of China (English)

    Deepa Puthanparambil; Casey Kimball; Shaw Ling Hsu; Zhiyong Ren

    2009-01-01

    Spectroscopic studies have revealed that the amount of polyureas formed and the kinetics of their formation in soy based polyurethane systems are considerably different from traditional systems employing ethylene oxide-propylene oxide (EO-PO) based polyols. The aggregation of polyureas was characterized by the hydrogen bonds formed utilizing FTIR spectroscopy. This study offered the opportunity to assign the previously undefined infrared features. The structural transformation is reflected in the segmental relaxation kinetics characterized by spin-spin diffusion most conveniently measured using low field NMR. The reaction kinetics and the products formed are directly related to the hydrophobic nature of the soy based polyols and its inability to disperse water.

  15. Real-time network traffic classification technique for wireless local area networks based on compressed sensing

    Science.gov (United States)

    Balouchestani, Mohammadreza

    2017-05-01

    Network traffic or data traffic in a Wireless Local Area Network (WLAN) is the amount of network packets moving across a wireless network from each wireless node to another wireless node, which provide the load of sampling in a wireless network. WLAN's Network traffic is the main component for network traffic measurement, network traffic control and simulation. Traffic classification technique is an essential tool for improving the Quality of Service (QoS) in different wireless networks in the complex applications such as local area networks, wireless local area networks, wireless personal area networks, wireless metropolitan area networks, and wide area networks. Network traffic classification is also an essential component in the products for QoS control in different wireless network systems and applications. Classifying network traffic in a WLAN allows to see what kinds of traffic we have in each part of the network, organize the various kinds of network traffic in each path into different classes in each path, and generate network traffic matrix in order to Identify and organize network traffic which is an important key for improving the QoS feature. To achieve effective network traffic classification, Real-time Network Traffic Classification (RNTC) algorithm for WLANs based on Compressed Sensing (CS) is presented in this paper. The fundamental goal of this algorithm is to solve difficult wireless network management problems. The proposed architecture allows reducing False Detection Rate (FDR) to 25% and Packet Delay (PD) to 15 %. The proposed architecture is also increased 10 % accuracy of wireless transmission, which provides a good background for establishing high quality wireless local area networks.

  16. Simulating the Evolution of Functional Brain Networks in Alzheimer’s Disease: Exploring Disease Dynamics from the Perspective of Global Activity

    Science.gov (United States)

    Li, Wei; Wang, Miao; Zhu, Wenzhen; Qin, Yuanyuan; Huang, Yue; Chen, Xi

    2016-01-01

    Functional brain connectivity is altered during the pathological processes of Alzheimer’s disease (AD), but the specific evolutional rules are insufficiently understood. Resting-state functional magnetic resonance imaging indicates that the functional brain networks of individuals with AD tend to be disrupted in hub-like nodes, shifting from a small world architecture to a random profile. Here, we proposed a novel evolution model based on computational experiments to simulate the transition of functional brain networks from normal to AD. Specifically, we simulated the rearrangement of edges in a pathological process by a high probability of disconnecting edges between hub-like nodes, and by generating edges between random pair of nodes. Subsequently, four topological properties and a nodal distribution were used to evaluate our model. Compared with random evolution as a null model, our model captured well the topological alteration of functional brain networks during the pathological process. Moreover, we implemented two kinds of network attack to imitate the damage incurred by the brain in AD. Topological changes were better explained by ‘hub attacks’ than by ‘random attacks’, indicating the fragility of hubs in individuals with AD. This model clarifies the disruption of functional brain networks in AD, providing a new perspective on topological alterations. PMID:27677360

  17. Neural Network Model Based Cluster Head Selection for Power Control

    Directory of Open Access Journals (Sweden)

    Krishan Kumar

    2011-01-01

    Full Text Available Mobile ad-hoc network has challenge of the limited power to prolong the lifetime of the network, because power is a valuable resource in mobile ad-hoc network. The status of power consumption should be continuously monitored after network deployment. In this paper, we propose coverage aware neural network based power control routing with the objective of maximizing the network lifetime. Cluster head selection is proposed using adaptive learning in neural networks followed by coverage. The simulation results show that the proposed scheme can be used in wide area of applications in mobile ad-hoc network.

  18. Self-organized Collaboration Network Model Based on Module Emerging

    Science.gov (United States)

    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.

  19. Reality based scenarios facilitate knowledge network development.

    Science.gov (United States)

    Manning, J; Broughton, V; McConnell, E A

    1995-03-01

    The challenge in nursing education is to create a learning environment that enables students to learn new knowledge, access previously acquired information from a variety of disciplines, and apply this newly constructed knowledge to the complex and constantly changing world of practice. Faculty at the University of South Australia, School of Nursing, City Campus describe the use of reality based scenarios to acquire domain-specific knowledge and develop well connected associative knowledge networks, both of which facilitate theory based practice and the student's transition to the role of registered nurse.

  20. Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

    Science.gov (United States)

    Wu, Yu’e; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

    2017-01-01

    Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world. PMID:28112276

  1. Randomly biased investments and the evolution of public goods on interdependent networks

    Science.gov (United States)

    Chen, Wei; Wu, Te; Li, Zhiwu; Wang, Long

    2017-08-01

    Deciding how to allocate resources between interdependent systems is significant to optimize efficiency. We study the effects of heterogeneous contribution, induced by such interdependency, on the evolution of cooperation, through implementing the public goods games on two-layer networks. The corresponding players on different layers try to share a fixed amount of resources as the initial investment properly. The symmetry breaking of investments between players located on different layers is able to either prevent investments from, or extract them out of the deadlock. Results show that a moderate investment heterogeneity is best favorable for the evolution of cooperation, and random allocation of investment bias suppresses the cooperators at a wide range of the investment bias and the enhancement effect. Further studies on time evolution with different initial strategy configurations show that the non-interdependent cooperators along the interface of interdependent cooperators also are an indispensable factor in facilitating cooperative behavior. Our main results are qualitatively unchanged even diversifying investment bias that is subject to uniform distribution. Our study may shed light on the understanding of the origin of cooperative behavior on interdependent networks.

  2. Impact of Social Reward on the Evolution of the Cooperation Behavior in Complex Networks

    Science.gov (United States)

    Wu, Yu’E.; Chang, Shuhua; Zhang, Zhipeng; Deng, Zhenghong

    2017-01-01

    Social reward, as a significant mechanism explaining the evolution of cooperation, has attracted great attention both theoretically and experimentally. In this paper, we study the evolution of cooperation by proposing a reward model in network population, where a third strategy, reward, as an independent yet particular type of cooperation is introduced in 2-person evolutionary games. Specifically, a new kind of role corresponding to reward strategy, reward agents, is defined, which is aimed at increasing the income of cooperators by applying to them a social reward. Results from numerical simulations show that consideration of social reward greatly promotes the evolution of cooperation, which is confirmed for different network topologies and two evolutionary games. Moreover, we explore the microscopic mechanisms for the promotion of cooperation in the three-strategy model. As expected, the reward agents play a vital role in the formation of cooperative clusters, thus resisting the aggression of defectors. Our research might provide valuable insights into further exploring the nature of cooperation in the real world.

  3. Ecology and evolution affect network structure in an intimate marine mutualism.

    Science.gov (United States)

    Thompson, Andrew R; Adam, Thomas C; Hultgren, Kristin M; Thacker, Christine E

    2013-08-01

    Elucidating patterns and causes of interaction among mutualistic species is a major focus of ecology, and recent meta-analyses of terrestrial networks show that network-level reciprocal specialization tends to be higher in intimate mutualisms than in nonintimate mutualisms. It is largely unknown, however, whether this pattern holds for and what factors affect specialization in marine mutualisms. Here we present the first analysis of network specialization ([Formula: see text]) for marine mutualistic networks. Specialization among eight Indo-Pacific networks of obligate mutualistic gobies and shrimps was indistinguishable from that among comparably intimate terrestrial mutualisms (ants-myrmecophytes) and higher than that among nonintimate ones (seed dispersers). Specialization was affected by variability in habitat use for both gobies and shrimps and by phylogenetic history for shrimps. Habitat use was phylogenetically conserved among shrimp, and thus effects of shrimp phylogeny on partner choice were mediated in part by habitat. By contrast, habitat use and pairing patterns in gobies were not related to phylogenetic history. This asymmetry appears to result from evolutionary constraints on partner use in shrimps and convergence among distantly related gobies to utilize burrows provided by multiple shrimp species. Results indicate that the evolution of mutualism is affected by life-history characteristics that transcend environments and that different factors constrain interactions in disparate ecosystems.

  4. Structure Properties of Koch Networks Based on Networks Dynamical Systems

    CERN Document Server

    Zhai, Yinhu; Wang, Shaohui

    2016-01-01

    We introduce an informative labeling algorithm for the vertices of a family of Koch networks. Each of the labels is consisted of two parts, the precise position and the time adding to Koch networks. The shortest path routing between any two vertices is determined only on the basis of their labels, and the routing is calculated only by few computations. The rigorous solutions of betweenness centrality for every node and edge are also derived by the help of their labels. Furthermore, the community structure in Koch networks is studied by the current and voltage characteristics of its resistor networks.

  5. Network Lifetime Extension Based On Network Coding Technique In Underwater Acoustic Sensor Networks

    Directory of Open Access Journals (Sweden)

    Padmavathy.T.V

    2012-06-01

    Full Text Available Underwater acoustic sensor networks (UWASNs are playing a lot of interest in ocean applications, such as ocean pollution monitoring, ocean animal surveillance, oceanographic data collection, assisted- navigation, and offshore exploration, UWASN is composed of underwater sensors that engage sound to transmit information collected in the ocean. The reason to utilize sound is that radio frequency (RF signals used by terrestrial sensor networks (TWSNs can merely transmit a few meters in the water. Unfortunately, the efficiency of UWASNs is inferior to that of the terrestrial sensor networks (TWSNs. Some of the challenges in under water communication are propagation delay, high bit error rate and limited bandwidth. Our aim is to minimize the power consumption and to improve the reliability of data transmission by finding the optimum number of clusters based on energy consumption.

  6. Stochastic methods for measurement-based network control

    NARCIS (Netherlands)

    Ellens, W.

    2015-01-01

    The main task of network administrators is to ensure that their network functions properly. Whether they manage a telecommunication or a road network, they generally base their decisions on the analysis of measurement data. Inspired by such network control applications, this dissertation investigate

  7. Reliability-Based Optimization for Maintenance Management in Bridge Networks

    OpenAIRE

    Hu, Xiaofei

    2014-01-01

    This dissertation addresses the problem of optimizing maintenance, repair and reconstruction decisions for bridge networks. Incorporating network topologies into bridge management problems is computationally difficult. Because of the interdependencies among networked bridges, they have to be analyzed together. Simulation-based numerical optimization techniques adopted in past research are limited to networks of moderate sizes. In this dissertation, novel approaches are developed to dete...

  8. NASSN: a NAS-based storage network

    Institute of Scientific and Technical Information of China (English)

    HAN De-zhi

    2007-01-01

    With the digital information and application requirement on the Internet increasing fleetly nowadays,it is urgent to work out a network storage system with a large capacity, a high availability and scalability. To solve the above-mentioned issues, a NAS-based storage network ( for short NASSN) has been designed. Firstly,the NASSN integrates multi-NAS,iNAS (an iSCSI-based NAS) and enterprise SAN with the help of storage virtualization, which can provide a greater capacity and better scalability. Secondly, the NASSN can provide high availability with the help of server and storage subsystem redundancy technologies. Thirdly, the NASSN simultaneously serves for both the file I/O and the block L/O with the help of an iSCSI module, which has the advantages of NAS and SAN. Finally, the NASSN can provide higher I/O speed by a high network-attached channel which implements the direct data transfer between the storage device and client. In the experiments, the NASSN has ultra-high-throughput for both of the file I/O requests and the block I/O requests.

  9. Exploring photosynthesis evolution by comparative analysis of metabolic networks between chloroplasts and photosynthetic bacteria

    Directory of Open Access Journals (Sweden)

    Hou Jing

    2006-04-01

    Full Text Available Abstract Background Chloroplasts descended from cyanobacteria and have a drastically reduced genome following an endosymbiotic event. Many genes of the ancestral cyanobacterial genome have been transferred to the plant nuclear genome by horizontal gene transfer. However, a selective set of metabolism pathways is maintained in chloroplasts using both chloroplast genome encoded and nuclear genome encoded enzymes. As an organelle specialized for carrying out photosynthesis, does the chloroplast metabolic network have properties adapted for higher efficiency of photosynthesis? We compared metabolic network properties of chloroplasts and prokaryotic photosynthetic organisms, mostly cyanobacteria, based on metabolic maps derived from genome data to identify features of chloroplast network properties that are different from cyanobacteria and to analyze possible functional significance of those features. Results The properties of the entire metabolic network and the sub-network that consists of reactions directly connected to the Calvin Cycle have been analyzed using hypergraph representation. Results showed that the whole metabolic networks in chloroplast and cyanobacteria both possess small-world network properties. Although the number of compounds and reactions in chloroplasts is less than that in cyanobacteria, the chloroplast's metabolic network has longer average path length, a larger diameter, and is Calvin Cycle -centered, indicating an overall less-dense network structure with specific and local high density areas in chloroplasts. Moreover, chloroplast metabolic network exhibits a better modular organization than cyanobacterial ones. Enzymes involved in the same metabolic processes tend to cluster into the same module in chloroplasts. Conclusion In summary, the differences in metabolic network properties may reflect the evolutionary changes during endosymbiosis that led to the improvement of the photosynthesis efficiency in higher plants. Our

  10. Receiver Based Traffic Control Mechanism to Protect Low Capacity Network in Infrastructure Based Wireless Mesh Network

    Science.gov (United States)

    Gilani, Syed Sherjeel Ahmad; Zubair, Muhammad; Khan, Zeeshan Shafi

    Infrastructure-based Wireless Mesh Networks are emerging as an affordable, robust, flexible and scalable technology. With the advent of Wireless Mesh Networks (WMNs) the dream of connecting multiple technology based networks seems to come true. A fully secure WMN is still a challenge for the researchers. In infrastructure-based WMNs almost all types of existing Wireless Networks like Wi-Fi, Cellular, WiMAX, and Sensor etc can be connected through Wireless Mesh Routers (WMRs). This situation can lead to a security problem. Some nodes can be part of the network with high processing power, large memory and least energy issues while others may belong to a network having low processing power, small memory and serious energy limitations. The later type of the nodes is very much vulnerable to targeted attacks. In our research we have suggested to set some rules on the WMR to mitigate these kinds of targeted flooding attacks. The WMR will then share those set of rules with other WMRs for Effective Utilization of Resources.

  11. Sequence similarity network reveals the imprints of major diversification events in the evolution of microbial life

    Directory of Open Access Journals (Sweden)

    Shu eCheng

    2014-11-01

    Full Text Available Ancient transitions, such as between life that evolved in a reducing versus an oxidizing atmosphere precipitated by the Great Oxygenation Event (GOE ca. 2.4 billion years ago, fundamentally altered the space in which prokaryotes could derive metabolic energy. Despite fundamental changes in Earth’s redox state, there are very few comprehensive, proteome-wide analyses about the effects of these changes on gene content and evolution. Here, using a pan-proteome sequence similarity network applied to broadly sampled lifestyles of 84 prokaryotes that were categorized into four different redox groups (i.e., methanogens, obligate anaerobes, facultative anaerobes, and obligate aerobes, we reconstructed the genetic inventory of major respiratory communities. We show that a set of putative core homologs that is highly conserved in prokaryotic proteomes is characterized by the loss of canonical network connections and low conductance that correlates with differences in respiratory phenotypes. We suggest these different network patterns observed for different respiratory communities could be explained by two major evolutionary diversification events in the history of microbial life. The first event (M is a divergence between methanogenesis and other anaerobic lifestyles in prokaryotes (archaebacteria and eubacteria. The second diversification event (OX is from anaerobic to aerobic lifestyles that left a proteome-wide footprint among prokaryotes. Additional analyses revealed that oxidoreductase evolution played a central role in these two diversification events. Distinct cofactor binding domains were frequently recombined, allowing these enzymes to utilize increasingly oxidized substrates with high specificity.

  12. A Cluster- Based Secure Active Network Environment

    Institute of Scientific and Technical Information of China (English)

    CHEN Xiao-lin; ZHOU Jing-yang; DAI Han; LU Sang-lu; CHEN Gui-hai

    2005-01-01

    We introduce a cluster-based secure active network environment (CSANE) which separates the processing of IP packets from that of active packets in active routers. In this environment, the active code authorized or trusted by privileged users is executed in the secure execution environment (EE) of the active router, while others are executed in the secure EE of the nodes in the distributed shared memory (DSM) cluster. With the supports of a multi-process Java virtual machine and KeyNote, untrusted active packets are controlled to securely consume resource. The DSM consistency management makes that active packets can be parallelly processed in the DSM cluster as if they were processed one by one in ANTS (Active Network Transport System). We demonstrate that CSANE has good security and scalability, but imposing little changes on traditional routers.

  13. Predicting Scientific Success Based on Coauthorship Networks

    CERN Document Server

    Sarigöl, Emre; Scholtes, Ingo; Garas, Antonios; Schweitzer, Frank

    2014-01-01

    We address the question to what extent the success of scientific articles is due to social influence. Analyzing a data set of over 100000 publications from the field of Computer Science, we study how centrality in the coauthorship network differs between authors who have highly cited papers and those who do not. We further show that a machine learning classifier, based only on coauthorship network centrality measures at time of publication, is able to predict with high precision whether an article will be highly cited five years after publication. By this we provide quantitative insight into the social dimension of scientific publishing - challenging the perception of citations as an objective, socially unbiased measure of scientific success.

  14. Efficient community-based control strategies in adaptive networks

    CERN Document Server

    Yang, Hui; Zhang, Hai-Feng

    2012-01-01

    Most researches on adaptive networks mainly concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structures in transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing modularity $Q$, we investigate the evolution of community structures during the transient process, and find that very strong community structures are induced by rewiring mechanism in the early stage of epidemic spreading, which remarkably delays the outbreaks of epidemic. Then we study the effects of control strategies started from different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not "the earlier, the better" for the implementing of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of strong community structure. For immunization strategy, immunizing the S nodes on SI links a...

  15. Combining in silico evolution and nonlinear dimensionality reduction to redesign responses of signaling networks

    Science.gov (United States)

    Prescott, Aaron M.; Abel, Steven M.

    2016-12-01

    The rational design of network behavior is a central goal of synthetic biology. Here, we combine in silico evolution with nonlinear dimensionality reduction to redesign the responses of fixed-topology signaling networks and to characterize sets of kinetic parameters that underlie various input-output relations. We first consider the earliest part of the T cell receptor (TCR) signaling network and demonstrate that it can produce a variety of input-output relations (quantified as the level of TCR phosphorylation as a function of the characteristic TCR binding time). We utilize an evolutionary algorithm (EA) to identify sets of kinetic parameters that give rise to: (i) sigmoidal responses with the activation threshold varied over 6 orders of magnitude, (ii) a graded response, and (iii) an inverted response in which short TCR binding times lead to activation. We also consider a network with both positive and negative feedback and use the EA to evolve oscillatory responses with different periods in response to a change in input. For each targeted input-output relation, we conduct many independent runs of the EA and use nonlinear dimensionality reduction to embed the resulting data for each network in two dimensions. We then partition the results into groups and characterize constraints placed on the parameters by the different targeted response curves. Our approach provides a way (i) to guide the design of kinetic parameters of fixed-topology networks to generate novel input-output relations and (ii) to constrain ranges of biological parameters using experimental data. In the cases considered, the network topologies exhibit significant flexibility in generating alternative responses, with distinct patterns of kinetic rates emerging for different targeted responses.

  16. Rapid molecular evolution across amniotes of the IIS/TOR network.

    Science.gov (United States)

    McGaugh, Suzanne E; Bronikowski, Anne M; Kuo, Chih-Horng; Reding, Dawn M; Addis, Elizabeth A; Flagel, Lex E; Janzen, Fredric J; Schwartz, Tonia S

    2015-06-02

    The insulin/insulin-like signaling and target of rapamycin (IIS/TOR) network regulates lifespan and reproduction, as well as metabolic diseases, cancer, and aging. Despite its vital role in health, comparative analyses of IIS/TOR have been limited to invertebrates and mammals. We conducted an extensive evolutionary analysis of the IIS/TOR network across 66 amniotes with 18 newly generated transcriptomes from nonavian reptiles and additional available genomes/transcriptomes. We uncovered rapid and extensive molecular evolution between reptiles (including birds) and mammals: (i) the IIS/TOR network, including the critical nodes insulin receptor substrate (IRS) and phosphatidylinositol 3-kinase (PI3K), exhibit divergent evolutionary rates between reptiles and mammals; (ii) compared with a proxy for the rest of the genome, genes of the IIS/TOR extracellular network exhibit exceptionally fast evolutionary rates; and (iii) signatures of positive selection and coevolution of the extracellular network suggest reptile- and mammal-specific interactions between members of the network. In reptiles, positively selected sites cluster on the binding surfaces of insulin-like growth factor 1 (IGF1), IGF1 receptor (IGF1R), and insulin receptor (INSR); whereas in mammals, positively selected sites clustered on the IGF2 binding surface, suggesting that these hormone-receptor binding affinities are targets of positive selection. Further, contrary to reports that IGF2R binds IGF2 only in marsupial and placental mammals, we found positively selected sites clustered on the hormone binding surface of reptile IGF2R that suggest that IGF2R binds to IGF hormones in diverse taxa and may have evolved in reptiles. These data suggest that key IIS/TOR paralogs have sub- or neofunctionalized between mammals and reptiles and that this network may underlie fundamental life history and physiological differences between these amniote sister clades.

  17. Fuzzy Neural Network Based Traffic Prediction and Congestion Control in High-Speed Networks

    Institute of Scientific and Technical Information of China (English)

    费翔; 何小燕; 罗军舟; 吴介一; 顾冠群

    2000-01-01

    Congestion control is one of the key problems in high-speed networks, such as ATM. In this paper, a kind of traffic prediction and preventive congestion control scheme is proposed using neural network approach. Traditional predictor using BP neural network has suffered from long convergence time and dissatisfying error. Fuzzy neural network developed in this paper can solve these problems satisfactorily. Simulations show the comparison among no-feedback control scheme,reactive control scheme and neural network based control scheme.

  18. On the Use of Local Search in the Evolution of Neural Networks for the Diagnosis of Breast Cancer

    Directory of Open Access Journals (Sweden)

    Agam Gupta

    2015-07-01

    Full Text Available With the advancement in the field of Artificial Intelligence, there have been considerable efforts to develop technologies for pattern recognition related to medical diagnosis. Artificial Neural Networks (ANNs, a significant piece of Artificial Intelligence forms the base for most of the marvels in the former field. However, ANNs face the problem of premature convergence at a local minimum and inability to set hyper-parameters (like the number of neurons, learning rate, etc. while using Back Propagation Algorithm (BPA. In this paper, we have used the Genetic Algorithm (GA for the evolution of the ANN, which overcomes the limitations of the BPA. Since GA alone cannot fit for a high-dimensional, complex and multi-modal optimization landscape of the ANN, BPA is used as a local search algorithm to aid the evolution. The contributions of GA and BPA in the resultant approach are adjudged to determine the magnitude of local search necessary for optimization, striking a clear balance between exploration and exploitation in the evolution. The algorithm was applied to deal with the problem of Breast Cancer diagnosis. Results showed that under optimal settings, hybrid algorithm performs better than BPA or GA alone.

  19. A Scalable Policy and SNMP Based Network Management Framework

    Institute of Scientific and Technical Information of China (English)

    LIU Su-ping; DING Yong-sheng

    2009-01-01

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

  20. Networks uncover hidden lexical borrowing in Indo-European language evolution.

    Science.gov (United States)

    Nelson-Sathi, Shijulal; List, Johann-Mattis; Geisler, Hans; Fangerau, Heiner; Gray, Russell D; Martin, William; Dagan, Tal

    2011-06-22

    Language evolution is traditionally described in terms of family trees with ancestral languages splitting into descendent languages. However, it has long been recognized that language evolution also entails horizontal components, most commonly through lexical borrowing. For example, the English language was heavily influenced by Old Norse and Old French; eight per cent of its basic vocabulary is borrowed. Borrowing is a distinctly non-tree-like process--akin to horizontal gene transfer in genome evolution--that cannot be recovered by phylogenetic trees. Here, we infer the frequency of hidden borrowing among 2346 cognates (etymologically related words) of basic vocabulary distributed across 84 Indo-European languages. The dataset includes 124 (5%) known borrowings. Applying the uniformitarian principle to inventory dynamics in past and present basic vocabularies, we find that 1373 (61%) of the cognates have been affected by borrowing during their history. Our approach correctly identified 117 (94%) known borrowings. Reconstructed phylogenetic networks that capture both vertical and horizontal components of evolutionary history reveal that, on average, eight per cent of the words of basic vocabulary in each Indo-European language were involved in borrowing during evolution. Basic vocabulary is often assumed to be relatively resistant to borrowing. Our results indicate that the impact of borrowing is far more widespread than previously thought.