Abstract: In this paper, many techniques for blind identification of moving average (MA) process are presented. These methods utilize third- and fourth-order cumulants of the noisy observations of the system output. The system is driven by an independent and identically distributed (i.i.d) non-Gaussian sequence that is not observed. Two nonlinear optimization algorithms, namely the Gradient Descent and the Gauss-Newton algorithms are exposed. An algorithm based on the joint-diagonalization of the fourth-order cumulant matrices (FOSI) is also considered, as well as an improved version of the classical C(q, 0, k) algorithm based on the choice of the Best 1-D Slice of fourth-order cumulants. To illustrate the effectiveness of our methods, various simulation examples are presented.
Abstract: Wavelet transforms is a very powerful tools for image compression. One of its advantage is the provision of both spatial and frequency localization of image energy. However, wavelet transform coefficients are defined by both a magnitude and sign. While algorithms exist for efficiently coding the magnitude of the transform coefficients, they are not efficient for the coding of their sign. It is generally assumed that there is no compression gain to be obtained from the coding of the sign. Only recently have some authors begun to investigate the sign of wavelet coefficients in image coding. Some authors have assumed that the sign information bit of wavelet coefficients may be encoded with the estimated probability of 0.5; the same assumption concerns the refinement information bit. In this paper, we propose a new method for Separate Sign Coding (SSC) of wavelet image coefficients. The sign and the magnitude of wavelet image coefficients are examined to obtain their online probabilities. We use the scalar quantization in which the information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also examined. We show that the sign information and the refinement information may be encoded by the probability of approximately 0.5 only after about five bit planes. Two maps are separately entropy encoded: the sign map and the magnitude map. The refinement information of the wavelet coefficient to belong to the lower or to the upper sub-interval in the uncertainly interval is also entropy encoded. An algorithm is developed and simulations are performed on three standard images in grey scale: Lena, Barbara and Cameraman. Five scales are performed using the biorthogonal wavelet transform 9/7 filter bank. The obtained results are compared to JPEG2000 standard in terms of peak signal to noise ration (PSNR) for the three images and in terms of subjective quality (visual quality). It is shown that the proposed method outperforms the JPEG2000. The proposed method is also compared to other codec in the literature. It is shown that the proposed method is very successful and shows its performance in term of PSNR.
Abstract: Because of increasing demands for security in today-s
society and also due to paying much more attention to machine
vision, biometric researches, pattern recognition and data retrieval in
color images, face detection has got more application. In this article
we present a scientific approach for modeling human skin color, and
also offer an algorithm that tries to detect faces within color images
by combination of skin features and determined threshold in the
model. Proposed model is based on statistical data in different color
spaces. Offered algorithm, using some specified color threshold, first,
divides image pixels into two groups: skin pixel group and non-skin
pixel group and then based on some geometric features of face
decides which area belongs to face.
Two main results that we received from this research are as follow:
first, proposed model can be applied easily on different databases and
color spaces to establish proper threshold. Second, our algorithm can
adapt itself with runtime condition and its results demonstrate
desirable progress in comparison with similar cases.
Abstract: The design of a pattern classifier includes an attempt
to select, among a set of possible features, a minimum subset of
weakly correlated features that better discriminate the pattern classes.
This is usually a difficult task in practice, normally requiring the
application of heuristic knowledge about the specific problem
domain. The selection and quality of the features representing each
pattern have a considerable bearing on the success of subsequent
pattern classification. Feature extraction is the process of deriving
new features from the original features in order to reduce the cost of
feature measurement, increase classifier efficiency, and allow higher
classification accuracy. Many current feature extraction techniques
involve linear transformations of the original pattern vectors to new
vectors of lower dimensionality. While this is useful for data
visualization and increasing classification efficiency, it does not
necessarily reduce the number of features that must be measured
since each new feature may be a linear combination of all of the
features in the original pattern vector. In this paper a new approach is
presented to feature extraction in which feature selection, feature
extraction, and classifier training are performed simultaneously using
a genetic algorithm. In this approach each feature value is first
normalized by a linear equation, then scaled by the associated weight
prior to training, testing, and classification. A knn classifier is used to
evaluate each set of feature weights. The genetic algorithm optimizes
a vector of feature weights, which are used to scale the individual
features in the original pattern vectors in either a linear or a nonlinear
fashion. By this approach, the number of features used in classifying
can be finely reduced.
Abstract: In this paper we propose an enhanced equalization technique for multi-carrier code division multiple access (MC-CDMA). This method is based on the control of Equal Gain Combining (EGC) technique. Indeed, we introduce a new level changer to the EGC equalizer in order to adapt the equalization parameters to the channel coefficients. The optimal equalization level is, first, determined by channel training. The new approach reduces drastically the mutliuser interferences caused by interferes, without increasing the noise power. To compare the performances of the proposed equalizer, the theoretical analysis and numerical performances are given.
Abstract: In the present paper; an experimental and numerical
investigations of drag reduction on a grooved circular cylinder have
been performed. The experiments were carried out in closed circuit
subsonic wind tunnel (TE44); the pressure distribution on the
cylinder was conducted using a TE44DPS differential pressure
scanner and the drag forces were measured using the TE81 balance.
The display unit is linked to a computer, loaded with DATASLIM
software for data analysis and logging of result. The numerical study
was performed using the code ANSYS FLUENT solving the
Reynolds Averaged Navier-Stokes (RANS) equations. The k-ε and k-
ω SST models were tested. The results obtained from the
experimental and numerical investigations have showed a reduction
in the drag when using longitudinal grooves namely 2 and 6 on the
cylinder.
Abstract: For complete support of Quality of Service, it is better that environment itself predicts resource requirements of a job by using special methods in the Grid computing. The exact and correct prediction causes exact matching of required resources with available resources. After the execution of each job, the used resources will be saved in the active database named "History". At first some of the attributes will be exploit from the main job and according to a defined similarity algorithm the most similar executed job will be exploited from "History" using statistic terms such as linear regression or average, resource requirements will be predicted. The new idea in this research is based on active database and centralized history maintenance. Implementation and testing of the proposed architecture results in accuracy percentage of 96.68% to predict CPU usage of jobs and 91.29% of memory usage and 89.80% of the band width usage.
Abstract: The development of aid's systems for the medical
diagnosis is not easy thing because of presence of inhomogeneities in
the MRI, the variability of the data from a sequence to the other as
well as of other different source distortions that accentuate this
difficulty. A new automatic, contextual, adaptive and robust
segmentation procedure by MRI brain tissue classification is
described in this article. A first phase consists in estimating the
density of probability of the data by the Parzen-Rozenblatt method.
The classification procedure is completely automatic and doesn't
make any assumptions nor on the clusters number nor on the
prototypes of these clusters since these last are detected in an
automatic manner by an operator of mathematical morphology called
skeleton by influence zones detection (SKIZ). The problem of
initialization of the prototypes as well as their number is transformed
in an optimization problem; in more the procedure is adaptive since it
takes in consideration the contextual information presents in every
voxel by an adaptive and robust non parametric model by the
Markov fields (MF). The number of bad classifications is reduced by
the use of the criteria of MPM minimization (Maximum Posterior
Marginal).
Abstract: In MPEG and H.26x standards, to eliminate the
temporal redundancy we use motion estimation. Given that the
motion estimation stage is very complex in terms of computational
effort, a hardware implementation on a re-configurable circuit is
crucial for the requirements of different real time multimedia
applications. In this paper, we present hardware architecture for
motion estimation based on "Full Search Block Matching" (FSBM)
algorithm. This architecture presents minimum latency, maximum
throughput, full utilization of hardware resources such as embedded
memory blocks, and combining both pipelining and parallel
processing techniques. Our design is described in VHDL language,
verified by simulation and implemented in a Stratix II
EP2S130F1020C4 FPGA circuit. The experiment result show that the
optimum operating clock frequency of the proposed design is 89MHz
which achieves 160M pixels/sec.
Abstract: This paper looks into areas not covered by prominent
Agent-Oriented Software Engineering (AOSE) methodologies.
Extensive paper review led to the identification of two issues, first
most of these methodologies almost neglect semantic web and
ontology. Second, as expected, each one has its strength and
weakness and may focus on some phases of the development
lifecycle but not all of the phases. The work presented here builds
extensions to a highly regarded AOSE methodology (MaSE) in order
to cover the areas that this methodology does not concentrate on. The
extensions include introducing an ontology stage for semantic
representation and integrating early requirement specification from a
methodology which mainly focuses on that. The integration involved
developing transformation rules (with the necessary handling of nonmatching
notions) between the two sets of representations and
building the software which automates the transformation. The
application of this integration on a case study is also presented in the
paper. The main flow of MaSE stages was changed to smoothly
accommodate the new additions.
Abstract: Modular fixtures (MFs) are very important tools in
manufacturing processes in terms of reduction the cost and the
production time. This paper introduces an automated approach for
assembling MFs elements by employing SolidWorks as a powerful
3D CAD software. Visual Basic (VB) programming language was
applied integrating with SolidWorks API (Application programming
interface) functions. This integration allowed creating plug-in file and
generating new menus in the SolidWorks environment. The menus
allow the user to select, insert, and assemble MFs elements.
Abstract: Protein and Esterase electrophoresis were used to
genetically identify two Saudi tick species. Engorged females of the
camel tick Hyalomma dromedarii (Koch) (Acari: Ixodidae) and the
cattle tick Boophilus annulatus (Say) (Acari: Ixodidae) ticks
collected from infested camels and cattle in the animals resting
house at Hail region in KSA were used. The results showed that
there are a variation in both of protein and esterase activity levels and
a high polymorphism within and between the genera and species of
Hyalomma and Boophilus . In conclusion, the protein and esterase
electrophoretic analysis used in the present study could successfully
distinguish among tick species, commonly found in Saudi Arabia.
Abstract: In the present essay, a model of choice by actors is analysedby utilizing the theory of chaos to explain how change comes about. Then, by using ancient and modern sources of literature, the theory of the social contract is analysed as a historical phenomenon that first appeared during the period of Classical Greece. Then, based on the findings of this analysis, the practice of direct democracy and public choice in ancient Athens is analysed, through two historical cases: Eubulus and Lycurgus political program in the second half of the 4th century. The main finding of this research is that these policies can be interpreted as an implementation of a social contract, through which citizens were taking decisions based on rational choice according to economic considerations.
Abstract: In the present paper, we propose numerical methods for solving the Stein equation AXC - X - D = 0 where the matrix A is large and sparse. Such problems appear in discrete-time control problems, filtering and image restoration. We consider the case where the matrix D is of full rank and the case where D is factored as a product of two matrices. The proposed methods are Krylov subspace methods based on the block Arnoldi algorithm. We give theoretical results and we report some numerical experiments.
Abstract: In this paper we propose two first non-generic constructions
of multisignature scheme based on coding theory. The
first system make use of the CFS signature scheme and is secure
in random oracle while the second scheme is based on the KKS
construction and is a few times. The security of our construction relies
on a difficult problems in coding theory: The Syndrome Decoding
problem which has been proved NP-complete [4].
Abstract: The present study aimed to investigate whether
chlorophyll meter readings (SPAD) can be used as criterion of singleplant
selection in maize breeding. Experimentation was performed at
the ultra-low density of 0.74 plants/m2 in order the potential yield per
plant to be fully expressed. R-31 honeycomb experiments were
conducted in three different areas in Greece (Thessaloniki, Giannitsa
and Florina) using 30 inbred lines at well-watered and water-stressed
conditions during the 2012 growing season. The chlorophyll meter
readings had higher rates at dry conditions, except location of
Giannitsa where differences were not significant. Genotypes of
highest chlorophyll meter readings were consistent across areas,
emphasizing on the character’s stability. A positive correlation
between the chlorophyll meter readings and grain yield was
strengthening over time and culminated at the physiological maturity
stage. There was a clear sign that the chlorophyll meter readings has
the potential to be used for the selection of stress-adaptive genotypes
and may permit modern maize to be grown at wider range of
environments addressing the climate change scenarios.
Abstract: A wideband 2-1-1 cascaded ΣΔ modulator with a
single-bit quantizer in the two first stages and a 4-bit quantizer in the
final stage is developed. To reduce sensitivity of digital-to-analog
converter (DAC) nonlinearities in the feedback of the last stage,
dynamic element matching (DEM) is introduced. This paper presents
two modelling approaches: The first is MATLAB description and the
second is VHDL-AMS modelling of the proposed architecture and
exposes some high-level-simulation results allowing a behavioural
study. The detail of both ideal and non-ideal behaviour modelling are
presented. Then, the study of the effect of building blocks
nonidealities is presented; especially the influences of nonlinearity,
finite operational amplifier gain, amplifier slew rate limitation and
capacitor mismatch. A VHDL-AMS description presents a good
solution to predict system-s performances and can provide sensitivity
curves giving the impact of nonidealities on the system performance.
Abstract: Micro droplet formation is considered as a growing
emerging area of research due to its wide-range application in
chemistry as well as biology. The mechanism of micro droplet
formation using two immiscible liquids running through a T-junction
has been widely studied.
We believe that the flow of these two immiscible phases can be of
greater important factor that could have an impact on out-flow
hydrodynamic behavior, the droplets generated and the size of the
droplets. In this study, the type of the capillary tubes used also
represents another important factor that can have an impact on the
generation of micro droplets.
The tygon capillary tubing with hydrophilic inner surface doesn't
allow regular out-flows due to the fact that the continuous phase
doesn't adhere to the wall of the capillary inner surface.
Teflon capillary tubing, presents better wettability than tygon
tubing, and allows to obtain steady and regular regimes of out-flow,
and the micro droplets are homogeneoussize.
The size of the droplets is directly dependent on the flows of the
continuous and dispersed phases. Thus, as increasing the flow of the
continuous phase, to flow of the dispersed phase stationary, the size
of the drops decreases. Inversely, while increasing the flow of the
dispersed phase, to flow of the continuous phase stationary, the size
of the droplet increases.
Abstract: In recent years, we see an increase of interest for efficient tracking systems in surveillance applications. Many of the proposed techniques are designed for static cameras environments. When the camera is moving, tracking moving objects become more difficult and many techniques fail to detect and track the desired targets. The problem becomes more complex when we want to track a specific object in real-time using a moving Pan and Tilt camera system to keep the target within the image. This type of tracking is of high importance in surveillance applications. When a target is detected at a certain zone, the possibility of automatically tracking it continuously and keeping it within the image until action is taken is very important for security personnel working in very sensitive sites. This work presents a real-time tracking system permitting the detection and continuous tracking of targets using a Pan and Tilt camera platform. A novel and efficient approach for dealing with occlusions is presented. Also a new intelligent forget factor is introduced in order to take into account target shape variations and avoid learning non desired objects. Tests conducted in outdoor operational scenarios show the efficiency and robustness of the proposed approach.
Abstract: ERP systems are the largest software applications adopted by universities, along with quite significant investments in their implementation. However, unlike other applications little research has been conducted regarding these systems in a university environment. This paper aims at providing a critical review of previous research in ERP system in higher education with a special focus on higher education in Australia. The research not only forms the basis of an evaluation of previous research and research needs, it also makes inroads in identifying the payoff of ERPs in the sector from different perspectives with particular reference to the user. The paper is divided into two parts, the first part focuses on ERP literature in higher education at large, while the second focuses on ERP literature in higher education in Australia.