1,818 research outputs found
Towards a Formal Model of Privacy-Sensitive Dynamic Coalitions
The concept of dynamic coalitions (also virtual organizations) describes the
temporary interconnection of autonomous agents, who share information or
resources in order to achieve a common goal. Through modern technologies these
coalitions may form across company, organization and system borders. Therefor
questions of access control and security are of vital significance for the
architectures supporting these coalitions.
In this paper, we present our first steps to reach a formal framework for
modeling and verifying the design of privacy-sensitive dynamic coalition
infrastructures and their processes. In order to do so we extend existing
dynamic coalition modeling approaches with an access-control-concept, which
manages access to information through policies. Furthermore we regard the
processes underlying these coalitions and present first works in formalizing
these processes. As a result of the present paper we illustrate the usefulness
of the Abstract State Machine (ASM) method for this task. We demonstrate a
formal treatment of privacy-sensitive dynamic coalitions by two example ASMs
which model certain access control situations. A logical consideration of these
ASMs can lead to a better understanding and a verification of the ASMs
according to the aspired specification.Comment: In Proceedings FAVO 2011, arXiv:1204.579
Multi-Bernoulli Sensor-Control via Minimization of Expected Estimation Errors
This paper presents a sensor-control method for choosing the best next state
of the sensor(s), that provide(s) accurate estimation results in a multi-target
tracking application. The proposed solution is formulated for a multi-Bernoulli
filter and works via minimization of a new estimation error-based cost
function. Simulation results demonstrate that the proposed method can
outperform the state-of-the-art methods in terms of computation time and
robustness to clutter while delivering similar accuracy
Information theoretic approach to robust multi-Bernoulli sensor control
A novel sensor control solution is presented, formulated within a
Multi-Bernoulli-based multi-target tracking framework. The proposed method is
especially designed for the general multi-target tracking case, where no prior
knowledge of the clutter distribution or the probability of detection profile
are available. In an information theoretic approach, our method makes use of
R\`{e}nyi divergence as the reward function to be maximized for finding the
optimal sensor control command at each step. We devise a Monte Carlo sampling
method for computation of the reward. Simulation results demonstrate successful
performance of the proposed method in a challenging scenario involving five
targets maneuvering in a relatively uncertain space with unknown
distance-dependent clutter rate and probability of detection
Sensor Control for Multi-Object Tracking Using Labeled Multi-Bernoulli Filter
The recently developed labeled multi-Bernoulli (LMB) filter uses better
approximations in its update step, compared to the unlabeled multi-Bernoulli
filters, and more importantly, it provides us with not only the estimates for
the number of targets and their states, but also with labels for existing
tracks. This paper presents a novel sensor-control method to be used for
optimal multi-target tracking within the LMB filter. The proposed method uses a
task-driven cost function in which both the state estimation errors and
cardinality estimation errors are taken into consideration. Simulation results
demonstrate that the proposed method can successfully guide a mobile sensor in
a challenging multi-target tracking scenario
Critical Behavior of an Ising System on the Sierpinski Carpet: A Short-Time Dynamics Study
The short-time dynamic evolution of an Ising model embedded in an infinitely
ramified fractal structure with noninteger Hausdorff dimension was studied
using Monte Carlo simulations. Completely ordered and disordered spin
configurations were used as initial states for the dynamic simulations. In both
cases, the evolution of the physical observables follows a power-law behavior.
Based on this fact, the complete set of critical exponents characteristic of a
second-order phase transition was evaluated. Also, the dynamic exponent of the critical initial increase in magnetization, as well as the critical
temperature, were computed. The exponent exhibits a weak dependence
on the initial (small) magnetization. On the other hand, the dynamic exponent
shows a systematic decrease when the segmentation step is increased, i.e.,
when the system size becomes larger. Our results suggest that the effective
noninteger dimension for the second-order phase transition is noticeably
smaller than the Hausdorff dimension. Even when the behavior of the
magnetization (in the case of the ordered initial state) and the
autocorrelation (in the case of the disordered initial state) with time are
very well fitted by power laws, the precision of our simulations allows us to
detect the presence of a soft oscillation of the same type in both magnitudes
that we attribute to the topological details of the generating cell at any
scale.Comment: 10 figures, 4 tables and 14 page
Topological Effects caused by the Fractal Substrate on the Nonequilibrium Critical Behavior of the Ising Magnet
The nonequilibrium critical dynamics of the Ising magnet on a fractal
substrate, namely the Sierpinski carpet with Hausdorff dimension =1.7925,
has been studied within the short-time regime by means of Monte Carlo
simulations. The evolution of the physical observables was followed at
criticality, after both annealing ordered spin configurations (ground state)
and quenching disordered initial configurations (high temperature state), for
three segmentation steps of the fractal. The topological effects become evident
from the emergence of a logarithmic periodic oscillation superimposed to a
power law in the decay of the magnetization and its logarithmic derivative and
also from the dependence of the critical exponents on the segmentation step.
These oscillations are discussed in the framework of the discrete scale
invariance of the substrate and carefully characterized in order to determine
the critical temperature of the second-order phase transition and the critical
exponents corresponding to the short-time regime. The exponent of the
initial increase in the magnetization was also obtained and the results suggest
that it would be almost independent of the fractal dimension of the susbstrate,
provided that is close enough to d=2.Comment: 9 figures, 3 tables, 10 page
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