Abstract: Modernizing legacy applications is the key issue facing IT managers today because there's enormous pressure on organizations to change the way they run their business to meet the new requirements. The importance of software maintenance and reengineering is forever increasing. Understanding the architecture of existing legacy applications is the most critical issue for maintenance and reengineering. The artifacts recovery can be facilitated with different recovery approaches, methods and tools. The existing methods provide static and dynamic set of techniques for extracting architectural information, but are not suitable for all users in different domains. This paper presents a simple and lightweight pattern extraction technique to extract different artifacts from legacy systems using regular expression pattern specifications with multiple language support. We used our custom-built tool DRT to recover artifacts from existing system at different levels of abstractions. In order to evaluate our approach a case study is conducted.
Abstract: Software crisis refers to the situation in which the developers are not able to complete the projects within time and budget constraints and moreover these overscheduled and over budget projects are of low quality as well. Several methodologies have been adopted form time to time to overcome this situation and now in the focus is component based software engineering. In this approach, emphasis is on reuse of already existing software artifacts. But the results can not be achieved just by preaching the principles; they need to be practiced as well. This paper highlights some of the very basic elements of this approach, which has to be in place to get the desired goals of high quality, low cost with shorter time-to-market software products.
Abstract: The world is moving rapidly toward the deployment
of information and communication systems. Nowadays, computing
systems with their fast growth are found everywhere and one of the main challenges for these systems is increasing attacks and security threats against them. Thus, capturing, analyzing and verifying security requirements becomes a very important activity in
development process of computing systems, specially in developing
systems such as banking, military and e-business systems. For
developing every system, a process model which includes a process,
methods and tools is chosen. The Rational Unified Process (RUP) is
one of the most popular and complete process models which is used
by developers in recent years. This process model should be extended to be used in developing secure software systems. In this
paper, the Requirement Discipline of RUP is extended to improve RUP for developing secure software systems. These proposed extensions are adding and integrating a number of Activities, Roles,
and Artifacts to RUP in order to capture, document and model threats
and security requirements of system. These extensions introduce a
group of clear and stepwise activities to developers. By following these activities, developers assure that security requirements are
captured and modeled. These models are used in design, implementation and test activitie
Abstract: Concatenative speech synthesis is a method that can
make speech sound which has naturalness and high-individuality of a
speaker by introducing a large speech corpus. Based on this method, in
this paper, we propose a voice conversion method whose conversion
speech has high-individuality and naturalness. The authors also have
two subjective evaluation experiments for evaluating individuality and
sound quality of conversion speech. From the results, following three
facts have be confirmed: (a) the proposal method can convert the
individuality of speakers well, (b) employing the framework of unit
selection (especially join cost) of concatenative speech synthesis into
conventional voice conversion improves the sound quality of
conversion speech, and (c) the proposal method is robust against the
difference of genders between a source speaker and a target speaker.
Abstract: In this paper, genetic algorithm (GA) opmization technique is applied to design Flexible AC Transmission System (FACTS)-based damping controllers. Two types of controller structures, namely a proportional-integral (PI) and a lead-lag (LL) are considered. The design problem of the proposed controllers is formulated as an optimization problem and GA is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The proposed controllers are tested on a weakly connected power system subjected to different disturbances. The non-linear simulation results are presented to show the effectiveness of the proposed controller and their ability to provide efficient damping of low frequency oscillations. It is also observed that the proposed SSSC-based controllers improve greatly the voltage profile of the system under severe disturbances. Further, the dynamic performances of both the PI and LL structured FACTS-controller are analyzed at different loading conditions and under various disturbance condition as well as under unbalanced fault conditions..
Abstract: This paper presents the impact study of apparent
reactance injected by series Flexible AC Transmission System
(FACTS) i.e. Thyristor Controlled Series Reactor (TCSR) on the
measured impedance of a 400 kV single electrical transmission line
in the presence of phase to earth fault with fault resistance. The study
deals with an electrical transmission line of Eastern Algerian
transmission networks at Group Sonelgaz (Algerian Company of
Electrical and Gas) compensated by TCSR connected at midpoint of
the line. This compensator used to inject active and reactive powers
is controlled by three TCSR-s. The simulations results investigate the
impacts of the TCSR on the parameters of short circuit calculation
and parameters of measured impedance by distance relay in the
presence of earth fault for three cases study.
Abstract: The study of a real function of two real variables can be supported by visualization using a Computer Algebra System (CAS). One type of constraints of the system is due to the algorithms implemented, yielding continuous approximations of the given function by interpolation. This often masks discontinuities of the function and can provide strange plots, not compatible with the mathematics. In recent years, point based geometry has gained increasing attention as an alternative surface representation, both for efficient rendering and for flexible geometry processing of complex surfaces. In this paper we present different artifacts created by mesh surfaces near discontinuities and propose a point based method that controls and reduces these artifacts. A least squares penalty method for an automatic generation of the mesh that controls the behavior of the chosen function is presented. The special feature of this method is the ability to improve the accuracy of the surface visualization near a set of interior points where the function may be discontinuous. The present method is formulated as a minimax problem and the non uniform mesh is generated using an iterative algorithm. Results show that for large poorly conditioned matrices, the new algorithm gives more accurate results than the classical preconditioned conjugate algorithm.
Abstract: In this work, we improve a previously developed
segmentation scheme aimed at extracting edge information from
speckled images using a maximum likelihood edge detector. The
scheme was based on finding a threshold for the probability density
function of a new kernel defined as the arithmetic mean-to-geometric
mean ratio field over a circular neighborhood set and, in a general
context, is founded on a likelihood random field model (LRFM). The
segmentation algorithm was applied to discriminated speckle areas
obtained using simple elliptic discriminant functions based on
measures of the signal-to-noise ratio with fractional order moments.
A rigorous stochastic analysis was used to derive an exact expression
for the cumulative density function of the probability density
function of the random field. Based on this, an accurate probability
of error was derived and the performance of the scheme was
analysed. The improved segmentation scheme performed well for
both simulated and real images and showed superior results to those
previously obtained using the original LRFM scheme and standard
edge detection methods. In particular, the false alarm probability was
markedly lower than that of the original LRFM method with
oversegmentation artifacts virtually eliminated. The importance of
this work lies in the development of a stochastic-based segmentation,
allowing an accurate quantification of the probability of false
detection. Non visual quantification and misclassification in medical
ultrasound speckled images is relatively new and is of interest to
clinicians.
Abstract: Innovation, technology and knowledge are the trilogy
of impact to support the challenges arising from uncertainty.
Evidence showed an opportunity to ask how to manage in this
environment under constant innovation. In an attempt to get a
response from the field of Management Sciences, based in the
Contingency Theory, a research was conducted, with
phenomenological and descriptive approaches, using the Case Study
Method and the usual procedures for this task involving a focus
group composed of managers and employees working in the
pharmaceutical field. The problem situation was raised; the state of
the art was interpreted and dissected the facts. In this tasks were
involved four establishments. The result indicates that these focused
ventures have been managed by its founder empirically and is
experimenting agility described in this work. The expectation of this
study is to improve concepts for stakeholders on creativity in
business.