13,596 research outputs found
Model Checking of Statechart Models: Survey and Research Directions
We survey existing approaches to the formal verification of statecharts using
model checking. Although the semantics and subset of statecharts used in each
approach varies considerably, along with the model checkers and their
specification languages, most approaches rely on translating the hierarchical
structure into the flat representation of the input language of the model
checker. This makes model checking difficult to scale to industrial models, as
the state space grows exponentially with flattening. We look at current
approaches to model checking hierarchical structures and find that their
semantics is significantly different from statecharts. We propose to address
the problem of state space explosion using a combination of techniques, which
are proposed as directions for further research
Perturbation of closed range operators and Moore-Penrose inverse
Let be complex Hilbert spaces and be a
densely defined closed operator with domain and
be the Moore-Penrose inverse of . Let
be a bounded operator. In this article we focus our attention on the following
questions:
Under what conditions closedness of range of will imply the
closedness of range of ?
What is the relation between and ?
What is the relation between and ?
Operators that attain the reduced minimum
Let be complex Hilbert spaces and be a densely defined closed
linear operator from its domain , a dense subspace of , into .
Let denote the null space of and denote the range of .
Recall that is called the {\it carrier space
of} and the {\it reduced minimum modulus } of is defined
as:
Further, we say that
{\it attains its reduced minimum modulus} if there exists
such that and .
We discuss some properties of operators that attain reduced minimum modulus.
In particular, the following results are proved.Comment: submitted to a journal. arXiv admin note: text overlap with
arXiv:1606.05736, arXiv:1609.06869. Deleted the last section from the earlier
versio
On the Convergence of Quasilinear Viscous Approximations Using Compensated Compactness
Method of compensated compactness is used to show that the almost everywhere
limit of quasilinear viscous approximations is the unique entropy solution (in
the sense of {\it Bardos et.al}\cite{MR542510}) of the corresponding scalar
conservation laws in a bounded domain in , where the viscous
term is of the form
Medical Image Compression using Wavelet Decomposition for Prediction Method
In this paper offers a simple and lossless compression method for compression
of medical images. Method is based on wavelet decomposition of the medical
images followed by the correlation analysis of coefficients. The correlation
analyses are the basis of prediction equation for each sub band. Predictor
variable selection is performed through coefficient graphic method to avoid
multicollinearity problem and to achieve high prediction accuracy and
compression rate. The method is applied on MRI and CT images. Results show that
the proposed approach gives a high compression rate for MRI and CT images
comparing with state of the art methods.Comment: IEEE format, International Journal of Computer Science and
Information Security, IJCSIS January 2010, ISSN 1947 5500,
http://sites.google.com/site/ijcsis
On the convergence of quasilinear viscous approximations with BV initial data
We show that the almost everywhere limit of quasilinear viscous
approximations is the unique entropy solution (in the sense of {\it
Bardos-Leroux-Nedelec}) of the corresponding scalar conservation laws on a
bounded domain in whenever the initial data is essentially
bounded and a function of bounded variation
Black Hole Paradoxes
We propose here that the well-known black hole paradoxes such as the
information loss and teleological nature of the event horizon are restricted to
a particular idealized case, which is the homogeneous dust collapse model. In
this case, the event horizon, which defines the boundary of the black hole,
forms initially, and the singularity in the interior of the black hole at a
later time. We show that, in contrast, gravitational collapse from physically
more realistic initial conditions typically leads to the scenario in which the
event horizon and space-time singularity form simultaneously. We point out that
this apparently simple modification can mitigate the causality and teleological
paradoxes, and also lends support to two recently suggested solutions to the
information paradox, namely, the `firewall' and `classical chaos' proposals.Comment: Revised version; minor corrections and title change
CRLB Calculations for Joint AoA, AoD and Multipath Gain Estimation in Millimeter Wave Wireless Networks
In this report we present an analysis of the non-random and the Bayesian
Cramer-Rao lower bound (CRLB) for the joint estimation of angle-of-arrival
(AoA), angle-of-departure (AoD), and the multipath amplitudes, for the
millimeter-wave (mmWave) wireless networks. Our analysis is applicable to
multipath channels with Gaussian noise and independent path parameters.
Numerical results based on uniform AoA and AoD in , and Rician fading
path amplitudes, reveal that the Bayesian CRLB decreases monotonically with an
increase in the Rice factor. Further, the CRLB obtained by using beamforming
and combining code books generated by quantizing directly the domain of AoA and
AoD was found to be lower than those obtained with other types of beamforming
and combining code books
Energy distribution of solar flare events
Observational evidence of the braiding of magnetic field lines has been
reported. The magnetic reconnection within the loop (nanoflares) and with other
loops (microflares) disentangle the field. The coronal field then reorganizes
itself to attain a force-free field configuration. We have evaluated the power
law index of the energy distribution by using a model of
relaxation incorporating different profile functions of winding number
distribution based on braided topologies. We study the radio signatures
that occur in the solar corona using the radio data obtained from the
Gauribidanur Radio Observatory (IIA) and extract the power law index by using
the Statistic-sensitive nonlinear iterative peak clipping (SNIP) algorithm. We
see that the power law index obtained from the model is in good agreement with
the calculated value from the radio data observation.Comment: 2 pages, 1 figure; to appear in proceedings of IAU Symposium 340:
Long-term datasets for the understanding of solar and stellar magnetic cycle
An Intelligent Call Admission Control Decision Mechanism for Wireless Networks
The Call admission control (CAC) is one of the Radio Resource Management
(RRM) techniques plays instrumental role in ensuring the desired Quality of
Service (QoS) to the users working on different applications which have
diversified nature of QoS requirements. This paper proposes a fuzzy neural
approach for call admission control in a multi class traffic based Next
Generation Wireless Networks (NGWN). The proposed Fuzzy Neural Call Admission
Control (FNCAC) scheme is an integrated CAC module that combines the linguistic
control capabilities of the fuzzy logic controller and the learning
capabilities of the neural networks .The model is based on Recurrent Radial
Basis Function Networks (RRBFN) which have better learning and adaptability
that can be used to develop the intelligent system to handle the incoming
traffic in the heterogeneous network environment. The proposed FNCAC can
achieve reduced call blocking probability keeping the resource utilisation at
an optimal level. In the proposed algorithm we have considered three classes of
traffic having different QoS requirements. We have considered the heterogeneous
network environment which can effectively handle this traffic. The traffic
classes taken for the study are Conversational traffic, Interactive traffic and
back ground traffic which are with varied QoS parameters. The paper also
presents the analytical model for the CAC .The paper compares the call blocking
probabilities for all the three types of traffic in both the models. The
simulation results indicate that compared to Fuzzy logic based CAC,
Conventional CAC, The simulation results are optimistic and indicates that the
proposed FNCAC algorithm performs better where the call blocking probability is
minimal when compared to other two methods.Comment: Journal of Computing online at
https://sites.google.com/site/journalofcomputing
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