In this paper, based on the utility preferential attachment, we propose a new unified model to generate different network topologies such as scale-free, small-world and random networks. Moreover, a new network structure named super scale network is found, which has monopoly characteristic in our simulation experiments. Finally, the characteristics ofthis new network are given. 相似文献
A feedback mechanism that involves the proteins p53 and mdm2, induces cell death as a controlled response to severe DNA damage.
A minimal model for this mechanism demonstrates that the response may be dynamic and connected with the time needed to translate
the mdm2 protein. The response takes place if the dissociation constant k between p53 and mdm2 varies from its normal value. Although it is widely believed that it is an increase in k that triggers the response, we show that the experimental behaviour is better described by a decrease in the dissociation
constant. The response is quite robust upon changes in the parameters of the system, as required by any control mechanism,
except for few weak points, which could be connected with the onset of cancer.
Received 8 May 2002 / Received in final form 9 July 2002 Published online 17 September 2002 相似文献
We consider a Jackson-type network comprised of two queues having state-dependent service rates, in which the queue lengths
evolve periodically, exhibiting noisy cycles. To reduce this noise a certain heuristic, utilizing regions in the phase space
in which the system behaves almost deterministically, is applied. Using this heuristic, we show that in order to decrease
the probability of a customers overflow in one of the queues in the network, the server in that same queue – contrary to intuition
– should be shut down for a short period of time. Further noise reduction is obtained if the server in the second queue is
briefly shut down as well, when certain conditions hold. 相似文献
Snowball sampling methods are known to be a biased toward highly connected actors and consequently produce core-periphery networks when these may not necessarily be present. This leads to a biased perception of the underlying network which can have negative policy consequences, as in the identification of terrorist networks. When snowball sampling is used, the potential overload of the information collection system is a distinct problem due to the exponential growth of the number of suspects to be monitored. In this paper, we focus on evaluating the effectiveness of a wiretapping program in terms of its ability to map the rapidly evolving networks within a covert organization. By running a series of simulation-based experiments, we are able to evaluate a broad spectrum of information gathering regimes based on a consistent set of criteria. We conclude by proposing a set of information gathering programs that achieve higher effectiveness then snowball sampling, and at a lower cost.
Maksim Tsvetovat is an Assistant Professor at the Center for Social Complexity and department of Public and International Affairs at George Mason University, Fairfax, VA. He received his Ph.D. from the Computation, Organizations and Society program in the School of Computer Science, Carnegie Mellon University. His dissertation was centered on use of artificial intelligence techniques such as planning and semantic reasoning as a means of studying behavior and evolution of complex social networks, such as these of terrorist organizations. He received a Master of Science degree from University of Minnesota with a specialization in Artificial Intelligence and design of Multi-Agent Systems, and has also extensively studied organization theory and social science research methods. His research is centered on building high-fidelity simulations of social and organizational systems using concepts from distributed artificial intelligence and multi-agent systems. Other projects focus on social network analysis for mapping of internal corporate networks or study of covert and terrorist orgnaizations. Maksim’s vita and publications can be found on
Kathleen M. Carley is a professor in the School of Computer Science at Carnegie Mellon University and the director of the center for Compuational Analysis of Social and Organizational Systems (CASOS) which has over 25 members, both students and research staff. Her research combines cognitive science, social networks and computer science to address complex social and organizational problems. Her specific research areas are dynamic network analysis, computational social and organization theory, adaptation and evolution, text mining, and the impact of telecommunication technologies and policy on communication, information diffusion, disease contagion and response within and among groups particularly in disaster or crisis situations. She and her lab have developed infrastructure tools for analyzing large scale dynamic networks and various multi-agent simulation systems. The infrastructure tools include ORA, a statistical toolkit for analyzing and visualizing multi-dimensional networks. ORA results are organized into reports that meet various needs such as the management report, the mental model report, and the intelligence report. Another tool is AutoMap, a text-mining systems for extracting semantic networks from texts and then cross-classifying them using an organizational ontology into the underlying social, knowledge, resource and task networks. Her simulation models meld multi-agent technology with network dynamics and empirical data. Three of the large-scale multi-agent network models she and the CASOS group have developed in the counter-terrorism area are: BioWar a city-scale dynamic-network agent-based model for understanding the spread of disease and illness due to natural epidemics, chemical spills, and weaponized biological attacks; DyNet a model of the change in covert networks, naturally and in response to attacks, under varying levels of information uncertainty; and RTE a model for examining state failure and the escalation of conflict at the city, state, nation, and international as changes occur within and among red, blue, and green forces. She is the founding co-editor with Al. Wallace of the journal Computational Organization Theory and has co-edited several books and written over 100 articles in the computational organizations and dynamic network area. Her publications can be found at: http://www.casos.cs.cmu.edu/bios/carley/publications.php 相似文献
A nucleophilic substitution reaction between 4-tert-butylbenzyl bromide and a series of iodide salts has been performed in oil-in-water microemulsions based on either a fatty alcohol ethoxylate or a sugar surfactant. The reaction kinetics was compared with the kinetics of the same reaction performed in a microhomogeneous reaction medium, d-MeOH. Previous results showing a particularly high reactivity in the microemulsion based on the fatty alcohol ethoxylate was confirmed. It was shown that in both microemulsions the reaction rate was almost independent of the choice of counterion to iodide. This indicates that complexation of the cation with the surfactant headgroup, which, in particular, could have taken place with surfactants containing oligooxyethylene chains (a “crown ether effect”), seems not to be of importance.
127I NMR studies, as well as quadrupole splitting experiments performed by 2H NMR, indicate that there is a certain accumulation of iodide at the oil–water interface of the microemulsions. It is difficult to draw any quantitative conclusions in this respect, however.
The results obtained in this study, combined with results from previous investigations of the same reaction, indicate that the unexpectedly high reactivity obtained in the microemulsion based on a surfactant containing an oligooxyethylene headgroup is most probably due to the nucleophile being poorly solvated when present in the headgroup layer of such a microemulsion. Poorly solvated anions are known to be highly reactive nucleophiles. 相似文献
For vector quasivariational inequalities involving multifunctions in topological vector spaces, an existence result is obtained without a monotonicity assumption and with a convergence assumption weaker than semicontinuity. A new type of quasivariational inequality is proposed. Applications to quasicomplementarity problems and traffic network equilibria are considered. In particular, definitions of weak and strong Wardrop equilibria are introduced for the case of multivalued cost functions. 相似文献
A procedure is described for finding sets of key players in a social network. A key assumption is that the optimal selection
of key players depends on what they are needed for. Accordingly, two generic goals are articulated, called KPP-POS and KPP-NEG.
KPP-POS is defined as the identification of key players for the purpose of optimally diffusing something through the network
by using the key players as seeds. KPP-NEG is defined as the identification of key players for the purpose of disrupting or
fragmenting the network by removing the key nodes. It is found that off-the-shelf centrality measures are not optimal for
solving either generic problem, and therefore new measures are presented.
Stephen P. Borgatti is Professor of Organization Studies at the Carroll School of Management, Boston College. His research is focused on social
networks, social cognition and knowledge management. He is also interested in the application of social network analysis to
the solution of managerial problems. 相似文献