Abstract: The algorithm represents the DCT coefficients to concentrate signal energy and proposes combination and dictator to eliminate the correlation in the same level subband for encoding the DCT-based images. This work adopts DCT and modifies the SPIHT algorithm to encode DCT coefficients. The proposed algorithm also provides the enhancement function in low bit rate in order to improve the perceptual quality. Experimental results indicate that the proposed technique improves the quality of the reconstructed image in terms of both PSNR and the perceptual results close to JPEG2000 at the same bit rate.
Abstract: Modern managements of water distribution system
(WDS) need water quality models that are able to accurately predict
the dynamics of water quality variations within the distribution system
environment. Before water quality models can be applied to solve
system problems, they should be calibrated. Although former
researchers use GA solver to calibrate relative parameters, it is
difficult to apply on the large-scale or medium-scale real system for
long computational time. In this paper a new method is designed
which combines both macro and detailed model to optimize the water
quality parameters. This new combinational algorithm uses radial
basis function (RBF) metamodeling as a surrogate to be optimized for
the purpose of decreasing the times of time-consuming water quality
simulation and can realize rapidly the calibration of pipe wall reaction
coefficients of chlorine model of large-scaled WDS. After two cases
study this method is testified to be more efficient and promising, and
deserve to generalize in the future.
Abstract: The ElectroEncephaloGram (EEG) is useful for
clinical diagnosis and biomedical research. EEG signals often
contain strong ElectroOculoGram (EOG) artifacts produced
by eye movements and eye blinks especially in EEG recorded
from frontal channels. These artifacts obscure the underlying
brain activity, making its visual or automated inspection
difficult. The goal of ocular artifact removal is to remove
ocular artifacts from the recorded EEG, leaving the underlying
background signals due to brain activity. In recent times,
Independent Component Analysis (ICA) algorithms have
demonstrated superior potential in obtaining the least
dependent source components. In this paper, the independent
components are obtained by using the JADE algorithm (best
separating algorithm) and are classified into either artifact
component or neural component. Neural Network is used for
the classification of the obtained independent components.
Neural Network requires input features that exactly represent
the true character of the input signals so that the neural
network could classify the signals based on those key
characters that differentiate between various signals. In this
work, Auto Regressive (AR) coefficients are used as the input
features for classification. Two neural network approaches
are used to learn classification rules from EEG data. First, a
Polynomial Neural Network (PNN) trained by GMDH (Group
Method of Data Handling) algorithm is used and secondly,
feed-forward neural network classifier trained by a standard
back-propagation algorithm is used for classification and the
results show that JADE-FNN performs better than JADEPNN.
Abstract: This work considered the thermodynamic feasibility
of scrubbing volatile organic compounds into biodiesel in view of
designing a gas treatment process with this absorbent. A detailed
vapour – liquid equilibrium investigation was performed using the
original UNIFAC group contribution method. The four biodiesels
studied in this work are methyl oleate, methyl palmitate, methyl
linolenate and ethyl stearate. The original UNIFAC procedure was
used to estimate the infinite dilution activity coefficients of 13
selected volatile organic compounds in the biodiesels. The
calculations were done at the VOC mole fraction of 9.213x10-8. Ethyl
stearate gave the most favourable phase equilibrium. A close
agreement was found between the infinite dilution activity coefficient
of toluene found in this work and those reported in literature.
Thermodynamic models can efficiently be used to calculate vast
amount of phase equilibrium behaviour using limited number of
experimental data.
Abstract: This research work is aimed at speech recognition
using scaly neural networks. A small vocabulary of 11 words were
established first, these words are “word, file, open, print, exit, edit,
cut, copy, paste, doc1, doc2". These chosen words involved with
executing some computer functions such as opening a file, print
certain text document, cutting, copying, pasting, editing and exit.
It introduced to the computer then subjected to feature extraction
process using LPC (linear prediction coefficients). These features are
used as input to an artificial neural network in speaker dependent
mode. Half of the words are used for training the artificial neural
network and the other half are used for testing the system; those are
used for information retrieval.
The system components are consist of three parts, speech
processing and feature extraction, training and testing by using neural
networks and information retrieval.
The retrieve process proved to be 79.5-88% successful, which is
quite acceptable, considering the variation to surrounding, state of
the person, and the microphone type.
Abstract: The aim of this study was to compare the solubility of selected volatile organic compounds in water and silicon oil using the simple static headspace method. The experimental design allowed equilibrium achievement within 30 – 60 minutes. Infinite dilution activity coefficients and Henry-s law constants for various organics representing esters, ketones, alkanes, aromatics, cycloalkanes and amines were measured at 303K. The measurements were reproducible with a relative standard deviation and coefficient of variation of 1.3x10-3 and 1.3 respectively. The static determined activity coefficients using shaker flasks were reasonably comparable to those obtained using the gas liquid - chromatographic technique and those predicted using the group contribution methods mainly the UNIFAC. Silicon oil chemically known as polydimethysiloxane was found to be better absorbent for VOCs than water which quickly becomes saturated. For example the infinite dilution mole fraction based activity coefficients of hexane is 0.503 and 277 000 in silicon oil and water respectively. Thus silicon oil gives a superior factor of 550 696. Henry-s law constants and activity coefficients at infinite dilution play a significant role in the design of scrubbers for abatement of volatile organic compounds from contaminated air streams. This paper presents the phase equilibrium of volatile organic compounds in very dilute aqueous and polymeric solutions indicating the movement and fate of chemical in air and solvent. The successful comparison of the results obtained here and those obtained using other methods by the same authors and in literature, means that the results obtained here are reliable.
Abstract: The study was designed to develop a measurement of
the positive emotion regulation questionnaire (PERQ) that assesses
positive emotion regulation strategies through self-report. The 14
items developed for the surveying instrument of the study were based
upon literatures regarding elements of positive regulation strategies.
319 elementary students (age ranging from 12 to14) were recruited
among three public elementary schools to survey on their use of
positive emotion regulation strategies. Of 319 subjects, 20 invalid
questionnaire s yielded a response rate of 92%. The data collected
wasanalyzed through methods such as item analysis, factor analysis,
and structural equation models. In reference to the results from item
analysis, the formal survey instrument was reduced to 11 items. A
principal axis factor analysis with varimax was performed on
responses, resulting in a 2-factor equation (savoring strategy and
neutralizing strategy), which accounted for 55.5% of the total
variance. Then, the two-factor structure of scale was also identified by
structural equation models. Finally, the reliability coefficients of the
two factors were Cronbach-s α .92 and .74. Gender difference was
only found in savoring strategy. In conclusion, the positive emotion
regulation strategies questionnaire offers a brief, internally consistent,
and valid self-report measure for understanding the emotional
regulation strategies of children that may be useful to researchers and
applied professionals.
Abstract: In this paper, an image adaptive, invisible digital
watermarking algorithm with Orthogonal Polynomials based
Transformation (OPT) is proposed, for copyright protection of digital
images. The proposed algorithm utilizes a visual model to determine
the watermarking strength necessary to invisibly embed the
watermark in the mid frequency AC coefficients of the cover image,
chosen with a secret key. The visual model is designed to generate a
Just Noticeable Distortion mask (JND) by analyzing the low level
image characteristics such as textures, edges and luminance of the
cover image in the orthogonal polynomials based transformation
domain. Since the secret key is required for both embedding and
extraction of watermark, it is not possible for an unauthorized user to
extract the embedded watermark. The proposed scheme is robust to
common image processing distortions like filtering, JPEG
compression and additive noise. Experimental results show that the
quality of OPT domain watermarked images is better than its DCT
counterpart.
Abstract: This study compares family communication patterns in association with family socio-cultural status, especially marriage and family pattern, and couples- socio-economic status between Muslim and Santal communities in rural Bangladesh. A total of 288 couples, 145 couples from the Muslim and 143 couples from the Santal were randomly selected through cluster sampling procedure from Kalna village situated in Tanore Upazila of Rajshahi district of Bangladesh, where both the communities dwell as neighbors. In order to collect data from the selected samples, interview method with semistructural questionnaire schedule was applied. The responses given by the respondents were analyzed by Pearson-s chi-squire test and bivariate correlation techniques. The results of Pearson-s chi-squire test revealed that family communication patterns (X2= 25. 90, df= 2, p0.05) were significantly different between the Muslim and Santal communities. In addition, Spearman-s bivariate correlation coefficients suggested that among the exogenous factors, family type (rs=.135, p
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: Large volumes of fingerprints are collected and stored
every day in a wide range of applications, including forensics, access
control etc. It is evident from the database of Federal Bureau of
Investigation (FBI) which contains more than 70 million finger
prints. Compression of this database is very important because of this
high Volume. The performance of existing image coding standards
generally degrades at low bit-rates because of the underlying block
based Discrete Cosine Transform (DCT) scheme. Over the past
decade, the success of wavelets in solving many different problems
has contributed to its unprecedented popularity. Due to
implementation constraints scalar wavelets do not posses all the
properties which are needed for better performance in compression.
New class of wavelets called 'Multiwavelets' which posses more
than one scaling filters overcomes this problem. The objective of this
paper is to develop an efficient compression scheme and to obtain
better quality and higher compression ratio through multiwavelet
transform and embedded coding of multiwavelet coefficients through
Set Partitioning In Hierarchical Trees algorithm (SPIHT) algorithm.
A comparison of the best known multiwavelets is made to the best
known scalar wavelets. Both quantitative and qualitative measures of
performance are examined for Fingerprints.
Abstract: In this research, heat transfer of a poly Ethylene
fluidized bed reactor without reaction were studied experimentally
and computationally at different superficial gas velocities. A multifluid
Eulerian computational model incorporating the kinetic theory
for solid particles was developed and used to simulate the heat
conducting gas–solid flows in a fluidized bed configuration.
Momentum exchange coefficients were evaluated using the Syamlal–
O-Brien drag functions. Temperature distributions of different phases
in the reactor were also computed. Good agreement was found
between the model predictions and the experimentally obtained data
for the bed expansion ratio as well as the qualitative gas–solid flow
patterns. The simulation and experimental results showed that the gas
temperature decreases as it moves upward in the reactor, while the
solid particle temperature increases. Pressure drop and temperature
distribution predicted by the simulations were in good agreement
with the experimental measurements at superficial gas velocities
higher than the minimum fluidization velocity. Also, the predicted
time-average local voidage profiles were in reasonable agreement
with the experimental results. The study showed that the
computational model was capable of predicting the heat transfer and
the hydrodynamic behavior of gas-solid fluidized bed flows with
reasonable accuracy.
Abstract: X-ray mammography is the most effective method for
the early detection of breast diseases. However, the typical diagnostic
signs such as microcalcifications and masses are difficult to detect
because mammograms are of low-contrast and noisy. In this paper, a
new algorithm for image denoising and enhancement in Orthogonal
Polynomials Transformation (OPT) is proposed for radiologists to
screen mammograms. In this method, a set of OPT edge coefficients
are scaled to a new set by a scale factor called OPT scale factor. The
new set of coefficients is then inverse transformed resulting in
contrast improved image. Applications of the proposed method to
mammograms with subtle lesions are shown. To validate the
effectiveness of the proposed method, we compare the results to
those obtained by the Histogram Equalization (HE) and the Unsharp
Masking (UM) methods. Our preliminary results strongly suggest
that the proposed method offers considerably improved enhancement
capability over the HE and UM methods.
Abstract: The measurement of aerodynamic forces and moments
acting on an aircraft model is important for the development of wind
tunnel measurement technology to predict the performance of the full
scale vehicle. The potentials of an aircraft model with and without
winglet and aerodynamic characteristics with NACA wing No. 65-3-
218 have been studied using subsonic wind tunnel of 1 m × 1 m
rectangular test section and 2.5 m long of Aerodynamics Laboratory
Faculty of Engineering (University Putra Malaysia). Focusing on
analyzing the aerodynamic characteristics of the aircraft model, two
main issues are studied in this paper. First, a six component wind
tunnel external balance is used for measuring lift, drag and pitching
moment. Secondly, Tests are conducted on the aircraft model with
and without winglet of two configurations at Reynolds numbers
1.7×105, 2.1×105, and 2.5×105 for different angle of attacks. Fuzzy
logic approach is found as efficient for the representation,
manipulation and utilization of aerodynamic characteristics.
Therefore, the primary purpose of this work was to investigate the
relationship between lift and drag coefficients, with free-stream
velocities and angle of attacks, and to illustrate how fuzzy logic
might play an important role in study of lift aerodynamic
characteristics of an aircraft model with the addition of certain
winglet configurations. Results of the developed fuzzy logic were
compared with the experimental results. For lift coefficient analysis,
the mean of actual and predicted values were 0.62 and 0.60
respectively. The coreelation between actual and predicted values
(from FLS model) of lift coefficient in different angle of attack was
found as 0.99. The mean relative error of actual and predicted valus
was found as 5.18% for the velocity of 26.36 m/s which was found to
be less than the acceptable limits (10%). The goodness of fit of
prediction value was 0.95 which was close to 1.0.
Abstract: Most simple nonlinear thresholding rules for
wavelet- based denoising assume that the wavelet coefficients are independent. However, wavelet coefficients of natural images have significant dependencies. This paper attempts to give a recipe for selecting one of the popular image-denoising algorithms based
on VisuShrink, SureShrink, OracleShrink, BayesShrink and BiShrink and also this paper compares different Bivariate models used for image denoising applications. The first part of the paper
compares different Shrinkage functions used for image-denoising.
The second part of the paper compares different bivariate models
and the third part of this paper uses the Bivariate model with modified marginal variance which is based on Laplacian assumption. This paper gives an experimental comparison on six 512x512 commonly used images, Lenna, Barbara, Goldhill,
Clown, Boat and Stonehenge. The following noise powers 25dB,26dB, 27dB, 28dB and 29dB are added to the six standard images and the corresponding Peak Signal to Noise Ratio (PSNR) values
are calculated for each noise level.
Abstract: In this paper we present a combined
hashing/watermarking method for image authentication. A robust
image hash, invariant to legitimate modifications, but fragile to
illegitimate modifications is generated from the local image
characteristics. To increase security of the system the watermark is
generated using the image hash as a key. Quantized Index
Modulation of DCT coefficients is used for watermark embedding.
Watermark detection is performed without use of the original image.
Experimental results demonstrate the effectiveness of the presented
method in terms of robustness and fragility.
Abstract: In this paper, an efficient local appearance feature
extraction method based the multi-resolution Curvelet transform is
proposed in order to further enhance the performance of the well
known Linear Discriminant Analysis(LDA) method when applied
to face recognition. Each face is described by a subset of band
filtered images containing block-based Curvelet coefficients. These
coefficients characterize the face texture and a set of simple statistical
measures allows us to form compact and meaningful feature vectors.
The proposed method is compared with some related feature extraction
methods such as Principal component analysis (PCA), as well
as Linear Discriminant Analysis LDA, and independent component
Analysis (ICA). Two different muti-resolution transforms, Wavelet
(DWT) and Contourlet, were also compared against the Block Based
Curvelet-LDA algorithm. Experimental results on ORL, YALE and
FERET face databases convince us that the proposed method provides
a better representation of the class information and obtains much
higher recognition accuracies.
Abstract: The implicit block methods based on the backward
differentiation formulae (BDF) for the solution of stiff initial value
problems (IVPs) using variable step size is derived. We construct a
variable step size block methods which will store all the coefficients
of the method with a simplified strategy in controlling the step size
with the intention of optimizing the performance in terms of
precision and computation time. The strategy involves constant,
halving or increasing the step size by 1.9 times the previous step size.
Decision of changing the step size is determined by the local
truncation error (LTE). Numerical results are provided to support the
enhancement of method applied.
Abstract: This paper tests the level of market integration between Malaysia and Singapore stock markets with the world market. Kalman Filter (KF) methodology is used on the International Capital Asset Pricing Model (ICAPM) and the pricing errors estimated within the framework of ICAPM are used as a measure of market integration or segmentation. The advantage of the KF technique is that it allows for time-varying coefficients in estimating ICAPM and hence able to capture the varying degree of market integration. Empirical results show clear evidence of varying degree of market integration for both case of Malaysia and Singapore. Furthermore, the results show that the changes in the level of market integration are found to coincide with certain economic events that have taken placed. The findings certainly provide evidence on the practicability of the KF technique to estimate stock markets integration. In the comparison between Malaysia and Singapore stock market, the result shows that the trends of the market integration indices for Malaysia and Singapore look similar through time but the magnitude is notably different with the Malaysia stock market showing greater degree of market integration. Finally, significant evidence of varying degree of market integration shows the inappropriate use of OLS in estimating the level of market integration.
Abstract: Speckle noise affects all coherent imaging systems
including medical ultrasound. In medical images, noise suppression
is a particularly delicate and difficult task. A tradeoff between noise
reduction and the preservation of actual image features has to be made
in a way that enhances the diagnostically relevant image content.
Even though wavelets have been extensively used for denoising
speckle images, we have found that denoising using contourlets gives
much better performance in terms of SNR, PSNR, MSE, variance and
correlation coefficient. The objective of the paper is to determine the
number of levels of Laplacian pyramidal decomposition, the number
of directional decompositions to perform on each pyramidal level and
thresholding schemes which yields optimal despeckling of medical
ultrasound images, in particular. The proposed method consists of the
log transformed original ultrasound image being subjected to contourlet
transform, to obtain contourlet coefficients. The transformed
image is denoised by applying thresholding techniques on individual
band pass sub bands using a Bayes shrinkage rule. We quantify the
achieved performance improvement.