Abstract: Signature represents an individual characteristic of a
person which can be used for his / her validation. For such application
proper modeling is essential. Here we propose an offline signature
recognition and verification scheme which is based on extraction of
several features including one hybrid set from the input signature
and compare them with the already trained forms. Feature points
are classified using statistical parameters like mean and variance.
The scanned signature is normalized in slant using a very simple
algorithm with an intention to make the system robust which is
found to be very helpful. The slant correction is further aided by the
use of an Artificial Neural Network (ANN). The suggested scheme
discriminates between originals and forged signatures from simple
and random forgeries. The primary objective is to reduce the two
crucial parameters-False Acceptance Rate (FAR) and False Rejection
Rate (FRR) with lesser training time with an intension to make the
system dynamic using a cluster of ANNs forming a multiple classifier
system.
Abstract: In this research, the laminar heat transfer of natural convection on vertical surfaces has been investigated. Most of the studies on natural convection have been considered constantly whereas velocity and temperature domain, do not change with time, transient one are used a lot. Governing equations are solved using a finite volume approach. The convective terms are discretized using the power-law scheme, whereas for diffusive terms the central difference is employed. Coupling between the velocity and pressure is made with SIMPLE algorithm. The resultant system of discretized linear algebraic equations is solved with an alternating direction implicit scheme. Then a configuration of rectangular fins is put in different ways on the surface and heat transfer of natural convection on these surfaces without sliding is studied and finally optimization is done.
Abstract: A new decomposition form is introduced in this report
to establish a criterion for the bi-partite separability of Bell diagonal
states. A such criterion takes a quadratic inequality of the coefficients
of a given Bell diagonal states and can be derived via a simple
algorithmic calculation of its invariants. In addition, the criterion can
be extended to a quantum system of higher dimension.
Abstract: Electro-optical devices are increasingly used for
military sea-, land- and air applications to detect, recognize and track
objects. Typically, these devices produce video information that is
presented to an operator. However, with increasing availability of
electro-optical devices the data volume is becoming very large,
creating a rising need for automated analysis. In a military setting,
this typically involves detecting and recognizing objects at a large
distance, i.e. when they are difficult to distinguish from background
and noise. One may consider combining multiple images from a
video stream into a single enhanced image that provides more
information for the operator. In this paper we investigate a simple
algorithm to enhance simulated images from a military context and
investigate how the enhancement is affected by various types of
disturbance.