Abstract: In this paper we introduce a new unit test technique
called déjà-vu object. Déjà-vu objects replace real objects used by
classes under test, allowing the execution of isolated unit tests. A
déjà-vu object is able to observe and record the behaviour of a real
object during real sessions, and to replace it during unit tests,
returning previously recorded results. Consequently déjà-vu object
technique can be useful when a bottom-up development and testing
strategy is adopted. In this case déjà-vu objects can increase test
portability and test source code readability. At the same time they
can reduce the time spent by programmers to develop test code and
the risk of incompatibility during the switching between déjà-vu and
production code.
Abstract: In order to consider the effects of the higher modes in
the pushover analysis, during the recent years several multi-modal
pushover procedures have been presented. In these methods the
response of the considered modes are combined by the square-rootof-
sum-of-squares (SRSS) rule while application of the elastic modal
combination rules in the inelastic phases is no longer valid. In this
research the feasibility of defining an efficient alternative
combination method is investigated. Two steel moment-frame
buildings denoted SAC-9 and SAC-20 under ten earthquake records
are considered. The nonlinear responses of the structures are
estimated by the directed algebraic combination of the weighted
responses of the separate modes. The weight of the each mode is
defined so that the resulted response of the combination has a
minimum error to the nonlinear time history analysis. The genetic
algorithm (GA) is used to minimize the error and optimize the weight
factors. The obtained optimal factors for each mode in different cases
are compared together to find unique appropriate weight factors for
each mode in all cases.
Abstract: The emergence of the Internet has brewed the
revolution of information storage and retrieval. As most of the
data in the web is unstructured, and contains a mix of text,
video, audio etc, there is a need to mine information to cater to
the specific needs of the users without loss of important
hidden information. Thus developing user friendly and
automated tools for providing relevant information quickly
becomes a major challenge in web mining research. Most of
the existing web mining algorithms have concentrated on
finding frequent patterns while neglecting the less frequent
ones that are likely to contain outlying data such as noise,
irrelevant and redundant data. This paper mainly focuses on
Signed approach and full word matching on the organized
domain dictionary for mining web content outliers. This
Signed approach gives the relevant web documents as well as
outlying web documents. As the dictionary is organized based
on the number of characters in a word, searching and retrieval
of documents takes less time and less space.
Abstract: Nowadays viruses use polymorphic techniques to mutate their code on each replication, thus evading detection by antiviruses. However detection by emulation can defeat simple polymorphism: thus metamorphic techniques are used which thoroughly change the viral code, even after decryption. We briefly detail this evolution of virus protection techniques against detection and then study the METAPHOR virus, today's most advanced metamorphic virus.
Abstract: This paper presents the use of the predictive fuzzy logic controller (PFLC) applied to attitude control system for agile micro-satellite. In order to reduce the effect of unpredictable time delays and large uncertainties, the algorithm employs predictive control to predict the attitude of the satellite. Comparison of the PFLC and conventional fuzzy logic controller (FLC) is presented to evaluate the performance of the control system during attitude maneuver. The two proposed models have been analyzed with the same level of noise and external disturbances. Simulation results demonstrated the feasibility and advantages of the PFLC on the attitude determination and control system (ADCS) of agile satellite.
Abstract: E-services have significantly changed the way of
doing business in recent years. We can, however, observe poor use of
these services. There is a large gap between supply and actual eservices
usage. This is why we started a project to provide an
environment that will encourage the use of e-services. We believe
that only providing e-service does not automatically mean consumers
would use them. This paper shows the origins of our project and its
current position. We discuss the decision of using semantic web
technologies and their potential to improve e-services usage. We also
present current knowledge base and its real-world classification. In the paper, we discuss further work to be done in the project. Current
state of the project is promising.
Abstract: In this paper, we propose a new robust and secure
system that is based on the combination between two different
transforms Discrete wavelet Transform (DWT) and Contourlet
Transform (CT). The combined transforms will compensate the
drawback of using each transform separately. The proposed
algorithm has been designed, implemented and tested successfully.
The experimental results showed that selecting the best sub-band for
embedding from both transforms will improve the imperceptibility
and robustness of the new combined algorithm. The evaluated
imperceptibility of the combined DWT-CT algorithm which gave a
PSNR value 88.11 and the combination DWT-CT algorithm
improves robustness since it produced better robust against Gaussian
noise attack. In addition to that, the implemented system shored a
successful extraction method to extract watermark efficiently.
Abstract: This paper presents a comparison of metaheuristic
algorithms, Genetic Algorithm (GA) and Ant Colony Optimization
(ACO), in producing freeman chain code (FCC). The main problem
in representing characters using FCC is the length of the FCC
depends on the starting points. Isolated characters, especially the
upper-case characters, usually have branches that make the traversing
process difficult. The study in FCC construction using one
continuous route has not been widely explored. This is our
motivation to use the population-based metaheuristics. The
experimental result shows that the route length using GA is better
than ACO, however, ACO is better in computation time than GA.
Abstract: Biclustering is a very useful data mining technique for
identifying patterns where different genes are co-related based on a
subset of conditions in gene expression analysis. Association rules
mining is an efficient approach to achieve biclustering as in
BIMODULE algorithm but it is sensitive to the value given to its
input parameters and the discretization procedure used in the
preprocessing step, also when noise is present, classical association
rules miners discover multiple small fragments of the true bicluster,
but miss the true bicluster itself. This paper formally presents a
generalized noise tolerant bicluster model, termed as μBicluster. An
iterative algorithm termed as BIDENS based on the proposed model
is introduced that can discover a set of k possibly overlapping
biclusters simultaneously. Our model uses a more flexible method to
partition the dimensions to preserve meaningful and significant
biclusters. The proposed algorithm allows discovering biclusters that
hard to be discovered by BIMODULE. Experimental study on yeast,
human gene expression data and several artificial datasets shows that
our algorithm offers substantial improvements over several
previously proposed biclustering algorithms.
Abstract: This paper describes a concept of stereotype student
model in adaptive knowledge acquisition e-learning system. Defined
knowledge stereotypes are based on student's proficiency level and
on Bloom's knowledge taxonomy. The teacher module is responsible
for the whole adaptivity process: the automatic generation of
courseware elements, their dynamic selection and sorting, as well as
their adaptive presentation using templates for statements and
questions. The adaptation of courseware is realized according to
student-s knowledge stereotype.
Abstract: In order to achieve better road utilization and traffic
efficiency, there is an urgent need for a travel information delivery
mechanism to assist the drivers in making better decisions in the
emerging intelligent transportation system applications. In this paper,
we propose a relayed multicast scheme under heterogeneous networks
for this purpose. In the proposed system, travel information consisting
of summarized traffic conditions, important events, real-time traffic
videos, and local information service contents is formed into layers
and multicasted through an integration of WiMAX infrastructure and
Vehicular Ad hoc Networks (VANET). By the support of adaptive
modulation and coding in WiMAX, the radio resources can be
optimally allocated when performing multicast so as to dynamically
adjust the number of data layers received by the users. In addition to
multicast supported by WiMAX, a knowledge propagation and
information relay scheme by VANET is designed. The experimental
results validate the feasibility and effectiveness of the proposed
scheme.
Abstract: In many applications, magnetic suspension systems
are required to operate over large variations in air gap. As a result,
the nonlinearities inherent in most types of suspensions have a
significant impact on performance. Specifically, it may be difficult to
design a linear controller which gives satisfactory performance,
stability, and disturbance rejection over a wide range of operating
points. in this paper an optimal controller based on discontinuous
mathematical model of the system for an electromagnetic suspension
system which is applied in magnetic trains has been designed .
Simulations show that the new controller can adapt well to the
variance of suspension mass and gap, and keep its dynamic
performance, thus it is superior to the classic controller.
Abstract: Nowadays increasingly the population makes use of
Information Technology (IT). As such, in recent year the Portuguese
government increased its focus on using the IT for improving
people-s life and began to develop a set of measures to enable the
modernization of the Public Administration, and so reducing the gap
between Public Administration and citizens.Thus the Portuguese
Government launched the Simplex Program. However these
SIMPLEX eGov measures, which have been implemented over the
years, present a serious challenge: how to forecast its impact on
existing Information Systems Architecture (ISA). Thus, this research
is focus in addressing the problem of automating the evaluation of the
actual impact of implementation an eGovSimplification and
Modernization measures in the Information Systems Architecture. To
realize the evaluation we proposes a Framework, which is supported
by some key concepts as: Quality Factors, ISA modeling,
Multicriteria Approach, Polarity Profile and Quality Metrics
Abstract: Software security testing is an important means to ensure software security and trustiness. This paper first mainly discusses the definition and classification of software security testing, and investigates methods and tools of software security testing widely. Then it analyzes and concludes the advantages and disadvantages of various methods and the scope of application, presents a taxonomy of security testing tools. Finally, the paper points out future focus and development directions of software security testing technology.
Abstract: We suggest a novel method to incorporate longterm
redundancy (LTR) in signal time domain compression
methods. The proposition is based on block-sorting and curve
simplification. The proposition is illustrated on the ECG
signal as a post-processor for the FAN method. Test
applications on the new so-obtained FAN+ method using the
MIT-BIH database show substantial improvement of the
compression ratio-distortion behavior for a higher quality
reconstructed signal.
Abstract: The development of information and communication
technology, the increased use of the internet, as well as the effects of
the recession within the last years, have lead to the increased use of
cloud computing based solutions, also called on-demand solutions.
These solutions offer a large number of benefits to organizations as
well as challenges and risks, mainly determined by data visualization
in different geographic locations on the internet. As far as the specific
risks of cloud environment are concerned, data security is still
considered a peak barrier in adopting cloud computing. The present
study offers an approach upon ensuring the security of cloud data,
oriented towards the whole data life cycle. The final part of the study
focuses on the assessment of data security in the cloud, this
representing the bases in determining the potential losses and the
premise for subsequent improvements and continuous learning.
Abstract: This paper describes the authorization system
architecture for Pervasive Grid environment. It discusses the
characteristics of classical authorization system and requirements of
the authorization system in pervasive grid environment as well.
Based on our analysis of current systems and taking into account the
main requirements of such pervasive environment, we propose new
authorization system architecture as an extension of the existing grid
authorization mechanisms. This architecture not only supports user
attributes but also context attributes which act as a key concept for
context-awareness thought. The architecture allows authorization of
users dynamically when there are changes in the pervasive grid
environment. For this, we opt for hybrid authorization method that
integrates push and pull mechanisms to combine the existing grid
authorization attributes with dynamic context assertions. We will
investigate the proposed architecture using a real testing environment
that includes heterogeneous pervasive grid infrastructures mapped
over multiple virtual organizations. Various scenarios are described
in the last section of the article to strengthen the proposed mechanism
with different facilities for the authorization procedure.
Abstract: The current research paper is an implementation of
Eigen Faces and Karhunen-Loeve Algorithm for face recognition.
The designed program works in a manner where a unique
identification number is given to each face under trial. These faces
are kept in a database from where any particular face can be matched
and found out of the available test faces. The Karhunen –Loeve
Algorithm has been implemented to find out the appropriate right
face (with same features) with respect to given input image as test
data image having unique identification number. The procedure
involves usage of Eigen faces for the recognition of faces.
Abstract: In this paper, an ultrasonic technique is proposed to
predict oil content in a fresh palm fruit. This is accomplished by
measuring the attenuation based on ultrasonic transmission mode.
Several palm fruit samples with known oil content by Soxhlet
extraction (ISO9001:2008) were tested with our ultrasonic
measurement. Amplitude attenuation data results for all palm samples
were collected. The Feedforward Neural Networks (FNNs) are
applied to predict the oil content for the samples. The Root Mean
Square Error (RMSE) and Mean Absolute Error (MAE) of the FNN
model for predicting oil content percentage are 7.6186 and 5.2287
with the correlation coefficient (R) of 0.9193.
Abstract: Security risk models have been successful in estimating the likelihood of attack for simple security threats. However, modeling complex system and their security risk is even a challenge. Many methods have been proposed to face this problem. Often difficult to manipulate, and not enough all-embracing they are not as famous as they should with administrators and deciders. We propose in this paper a new tool to model big systems on purpose. The software, takes into account attack threats and security strength.