3,361 research outputs found
Critical exponents in stochastic sandpile models
We present large scale simulations of a stochastic sandpile model in two
dimensions. We use moments analysis to evaluate critical exponents and finite
size scaling method to consistently test the obtained results. The general
picture resulting from our analysis allows us to characterize the large scale
behavior of the present model with great accuracy.Comment: 6 pages, 4 figures. Invited talk presented at CCP9
Suboptimal solutions to network team optimization problems
Smoothness of the solutions to network team optimization problems with statistical information structure is investigated. Suboptimal solutions expressed as linear combinations of elements from sets of basis functions containing adjustable parameters are considered. Estimates of their accuracy are derived, for basis functions represented by sinusoids with variable frequencies and phases and
Gaussians with variable centers and widthss
Towards a Formal Verification Methodology for Collective Robotic Systems
We introduce a UML-based notation for graphically modeling
systems’ security aspects in a simple and intuitive
way and a model-driven process that transforms graphical
specifications of access control policies in XACML. These
XACML policies are then translated in FACPL, a policy
language with a formal semantics, and the resulting policies
are evaluated by means of a Java-based software tool
SPoT: Representing the Social, Spatial, and Temporal Dimensions of Human Mobility with a Unifying Framework
Modeling human mobility is crucial in the analysis and simulation of opportunistic networks, where contacts are exploited as opportunities for peer-topeer message forwarding. The current approach with human mobility modeling has been based on continuously modifying models, trying to embed in them the mobility properties (e.g., visiting patterns to locations or specific distributions of inter-contact times) as they came up from trace analysis. As
a consequence, with these models it is difficult, if not impossible, to modify the features of mobility or to control the exact shape of mobility metrics (e.g., modifying the distribution of inter-contact times). For these reasons, in this paper we propose a mobility framework rather than a mobility model, with the explicit goal of providing a exible and controllable tool for modeling mathematically and generating simulatively different possible features of human mobility. Our framework, named SPoT, is able to incorporate the three dimensions - spatial, social, and temporal - of human mobility. The way SPoT does it is by mapping the different social communities of the network into different locations, whose members visit with a configurable temporal pattern. In order to characterize the temporal patterns of user visits to locations and the relative positioning of locations based on their shared users, we analyze the traces of real user movements extracted from three location-based online social networks (Gowalla, Foursquare, and Altergeo). We observe that a Bernoulli process effectively approximates user visits to locations in the majority of cases and that locations that share many common users visiting them frequently tend to be located close to each other. In addition, we use these traces to test the exibility of the framework, and we show that SPoT is able to accurately reproduce the mobility behavior observed in traces. Finally, relying on the Bernoulli assumption for arrival processes, we provide a throughout mathematical analysis of the controllability of the framework, deriving the conditions under which heavy-tailed and exponentially-tailed aggregate inter-contact times (often observed in real traces) emerge
Towards Model-Driven Development of Access Control Policies for Web Applications
We introduce a UML-based notation for graphically modeling
systems’ security aspects in a simple and intuitive
way and a model-driven process that transforms graphical
specifications of access control policies in XACML. These
XACML policies are then translated in FACPL, a policy
language with a formal semantics, and the resulting policies
are evaluated by means of a Java-based software tool
Easing the Pain of Adjustment? Preferential Trading Agreements, Foreign Aid, and Credible Commitment to Economic Reform
In this article, we propose that wealthy donors give foreign aid to developing countries to
facilitate political adjustment, such as compensation for losers and side payments to influential
elite constituencies, towards mutually profitable economic reform. Only democratic developing
countries can credibly commit to using fungible revenue in ways that benefit the donor,
so the adjustment effect only applies to democracies. A quantitative test against data on preferential
trading agreements lends strong support to the theory. Strikingly, fully democratic
developing countries that form a preferential trading agreement obtain a threefold increase in
foreign aid in the short run. Additional tests show that this increase is not driven by macroeconomic
difficulties and that the beneficial effect on foreign aid is temporary. Both findings
are consistent with the theory. An important implication of these results is that if foreign aid
facilitates economic reform through preferential trading agreements, previous research could
have underestimated the benefits thereof
DNA as a medium for storing digital signals
Motivated by the storage capacity and efficiency of the DNA molecule in this paper we propose to utilize DNA molecules to store digital signals. We show that hybridization of DNA molecules can be used as a similarity criterion for retrieving digital signals encoded and stored in a DNA database. Since retrieval is achieved through hybridization of query and data carrying DNA molecules, we present a mathematical model to estimate hybridization efficiency (also known as selectivity annealing). We show that selectivity annealing is inversely proportional to the mean squared error (MSE) of the encoded signal values. In addition, we show that the concentration of the molecules plays the same role as the decision threshold employed in digital signal matching algorithms. Finally, similarly to the digital domain, we define a DNA signal-to-noise ratio (SNR) measure to assess the performance of the DNA-based retrieval scheme. Simulations are presented to validate our arguments
A Network Model characterized by a Latent Attribute Structure with Competition
The quest for a model that is able to explain, describe, analyze and simulate
real-world complex networks is of uttermost practical as well as theoretical
interest. In this paper we introduce and study a network model that is based on
a latent attribute structure: each node is characterized by a number of
features and the probability of the existence of an edge between two nodes
depends on the features they share. Features are chosen according to a process
of Indian-Buffet type but with an additional random "fitness" parameter
attached to each node, that determines its ability to transmit its own features
to other nodes. As a consequence, a node's connectivity does not depend on its
age alone, so also "young" nodes are able to compete and succeed in acquiring
links. One of the advantages of our model for the latent bipartite
"node-attribute" network is that it depends on few parameters with a
straightforward interpretation. We provide some theoretical, as well
experimental, results regarding the power-law behaviour of the model and the
estimation of the parameters. By experimental data, we also show how the
proposed model for the attribute structure naturally captures most local and
global properties (e.g., degree distributions, connectivity and distance
distributions) real networks exhibit. keyword: Complex network, social network,
attribute matrix, Indian Buffet processComment: 34 pages, second version (date of the first version: July, 2014).
Submitte
Effective Mechanism for Social Recommendation of News
Recommendation systems represent an important tool for news distribution on
the Internet. In this work we modify a recently proposed social recommendation
model in order to deal with no explicit ratings of users on news. The model
consists of a network of users which continually adapts in order to achieve an
efficient news traffic. To optimize network's topology we propose different
stochastic algorithms that are scalable with respect to the network's size.
Agent-based simulations reveal the features and the performance of these
algorithms. To overcome the resultant drawbacks of each method we introduce two
improved algorithms and show that they can optimize network's topology almost
as fast and effectively as other not-scalable methods that make use of much
more information
Generalized Erdos Numbers for network analysis
In this paper we consider the concept of `closeness' between nodes in a
weighted network that can be defined topologically even in the absence of a
metric. The Generalized Erd\H{o}s Numbers (GENs) satisfy a number of desirable
properties as a measure of topological closeness when nodes share a finite
resource between nodes as they are real-valued and non-local, and can be used
to create an asymmetric matrix of connectivities. We show that they can be used
to define a personalized measure of the importance of nodes in a network with a
natural interpretation that leads to a new global measure of centrality and is
highly correlated with Page Rank. The relative asymmetry of the GENs (due to
their non-metric definition) is linked also to the asymmetry in the mean first
passage time between nodes in a random walk, and we use a linearized form of
the GENs to develop a continuum model for `closeness' in spatial networks. As
an example of their practicality, we deploy them to characterize the structure
of static networks and show how it relates to dynamics on networks in such
situations as the spread of an epidemic
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