Abstract: In this paper a simple watermarking method for
color images is proposed. The proposed method is based on
watermark embedding for the histograms of the HSV planes
using visual cryptography watermarking. The method has
been proved to be robust for various image processing
operations such as filtering, compression, additive noise, and
various geometrical attacks such as rotation, scaling, cropping,
flipping, and shearing.
Abstract: Segmentation in ultrasound images is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, a segmentation scheme using fuzzy c-means (FCM) clustering incorporating both intensity and texture information of images is proposed to extract breast lesions in ultrasound images. Firstly, the nonlinear structure tensor, which can facilitate to refine the edges detected by intensity, is used to extract speckle texture. And then, a spatial FCM clustering is applied on the image feature space for segmentation. In the experiments with simulated and clinical ultrasound images, the spatial FCM clustering with both intensity and texture information gets more accurate results than the conventional FCM or spatial FCM without texture information.
Abstract: This paper deals with the synthesis of fuzzy state feedback controller of induction motor with optimal performance. First, the Takagi-Sugeno (T-S) fuzzy model is employed to approximate a non linear system in the synchronous d-q frame rotating with electromagnetic field-oriented. Next, a fuzzy controller is designed to stabilise the induction motor and guaranteed a minimum disturbance attenuation level for the closed-loop system. The gains of fuzzy control are obtained by solving a set of Linear Matrix Inequality (LMI). Finally, simulation results are given to demonstrate the controller-s effectiveness.
Abstract: The aim of this research is to develop a fast and
reliable surveillance system based on a personal digital assistant
(PDA) device. This is to extend the capability of the device to detect
moving objects which is already available in personal computers.
Secondly, to compare the performance between Background
subtraction (BS) and Temporal Frame Differencing (TFD) techniques
for PDA platform as to which is more suitable. In order to reduce
noise and to prepare frames for the moving object detection part,
each frame is first converted to a gray-scale representation and then
smoothed using a Gaussian low pass filter. Two moving object
detection schemes i.e., BS and TFD have been analyzed. The
background frame is updated by using Infinite Impulse Response
(IIR) filter so that the background frame is adapted to the varying
illuminate conditions and geometry settings. In order to reduce the
effect of noise pixels resulting from frame differencing
morphological filters erosion and dilation are applied. In this
research, it has been found that TFD technique is more suitable for
motion detection purpose than the BS in term of speed. On average
TFD is approximately 170 ms faster than the BS technique
Abstract: Building life cycle will never be excused from the existence of defects and deterioration. They are common problems in building, existed in newly build or in aged building. Buildings constructed from wood are indeed affected by its agent and serious defects and damages can reduce values to a building. In repair works, it is important to identify the causes and repair techniques that best suites with the condition. This paper reviews the conservation of traditional timber mosque in Malaysia comprises the concept, principles and approaches of mosque conservation in general. As in conservation practice, wood in historic building can be conserved by using various restoration and conservation techniques which this can be grouped as Fully and Partial Replacement, Mechanical Reinforcement, Consolidation by Impregnation and Reinforcement, Removing Paint and also Preservation of Wood and Control Insect Invasion, as to prolong and extended the function of a timber in a building. It resulted that the common techniques adopted in timber mosque conservation are from the conventional ways and the understanding of the repair technique requires the use of only preserve wood to prevent the future immature defects.
Abstract: Traditional wind tunnel models are meticulously machined from metal in a process that can take several months. While very precise, the manufacturing process is too slow to assess a new design's feasibility quickly. Rapid prototyping technology makes this concurrent study of air vehicle concepts via computer simulation and in the wind tunnel possible. This paper described the Affects layer thickness models product with rapid prototyping on Aerodynamic Coefficients for Constructed wind tunnel testing models. Three models were evaluated. The first model was a 0.05mm layer thickness and Horizontal plane 0.1μm (Ra) second model was a 0.125mm layer thickness and Horizontal plane 0.22μm (Ra) third model was a 0.15mm layer thickness and Horizontal plane 4.6μm (Ra). These models were fabricated from somos 18420 by a stereolithography (SLA). A wing-body-tail configuration was chosen for the actual study. Testing covered the Mach range of Mach 0.3 to Mach 0.9 at an angle-of-attack range of -2° to +12° at zero sideslip. Coefficients of normal force, axial force, pitching moment, and lift over drag are shown at each of these Mach numbers. Results from this study show that layer thickness does have an effect on the aerodynamic characteristics in general; the data differ between the three models by fewer than 5%. The layer thickness does have more effect on the aerodynamic characteristics when Mach number is decreased and had most effect on the aerodynamic characteristics of axial force and its derivative coefficients.
Abstract: In this paper we have suggested a new system for egovernment.
In this method a government can design a precise and
perfect system to control people and organizations by using five
major documents. These documents contain the important
information of each member of a society and help all organizations to
do their informatics tasks through them. This information would be
available by only a national code and a secure program would
support it. The suggested system can give a good awareness to the
society and help it be managed correctly.
Abstract: ECG contains very important clinical information about the cardiac activities of the heart. Often the ECG signal needs to be captured for a long period of time in order to identify abnormalities in certain situations. Such signal apart of a large volume often is characterised by low quality due to the noise and other influences. In order to extract features in the ECG signal with time-varying characteristics at first need to be preprocessed with the best parameters. Also, it is useful to identify specific parts of the long lasting signal which have certain abnormalities and to direct the practitioner to those parts of the signal. In this work we present a method based on wavelet transform, standard deviation and variable threshold which achieves 100% accuracy in identifying the ECG signal peaks and heartbeat as well as identifying the standard deviation, providing a quick reference to abnormalities.
Abstract: A new fast correlation algorithm for calibrating the
wavelength of Optical Spectrum Analyzers (OSAs) was introduced
in [1]. The minima of acetylene gas spectra were measured and
correlated with saved theoretical data [2]. So it is possible to find the
correct wavelength calibration data using a noisy reference spectrum.
First tests showed good algorithmic performance for gas line spectra
with high noise. In this article extensive performance tests were made
to validate the noise resistance of this algorithm. The filter and
correlation parameters of the algorithm were optimized for improved
noise performance. With these parameters the performance of this
wavelength calibration was simulated to predict the resulting
wavelength error in real OSA systems. Long term simulations were
made to evaluate the performance of the algorithm over the lifetime
of a real OSA.
Abstract: Speckled images arise when coherent microwave,
optical, and acoustic imaging techniques are used to image an object, surface or scene. Examples of coherent imaging systems include synthetic aperture radar, laser imaging systems, imaging sonar
systems, and medical ultrasound systems. Speckle noise is a form of object or target induced noise that results when the surface of the object is Rayleigh rough compared to the wavelength of the illuminating radiation. Detection and estimation in images corrupted
by speckle noise is complicated by the nature of the noise and is not
as straightforward as detection and estimation in additive noise. In
this work, we derive stochastic models for speckle noise, with an emphasis on speckle as it arises in medical ultrasound images. The
motivation for this work is the problem of segmentation and tissue classification using ultrasound imaging. Modeling of speckle in this
context involves partially developed speckle model where an underlying Poisson point process modulates a Gram-Charlier series
of Laguerre weighted exponential functions, resulting in a doubly
stochastic filtered Poisson point process. The statistical distribution of partially developed speckle is derived in a closed canonical form.
It is observed that as the mean number of scatterers in a resolution cell is increased, the probability density function approaches an
exponential distribution. This is consistent with fully developed speckle noise as demonstrated by the Central Limit theorem.
Abstract: The psychological well-being of a family is a subjective matter for evaluation, all the more when it involves the element of religions, whether Islam, Christianity, Buddhism or Hinduism. Each of these religions emphasises similar values and morals on family psychological well-being. This comparative study is specifically to determine the role of religion on family psychological well-being in Pekan district, Pahang, Malaysia. The study adopts a quantitative and qualitative mixed method design and considers a total of 412 samples of parents and children for the quantitative study, and 21 samples for the qualitative study. The quantitative study uses simple random sampling, whereas the qualitative sampling is purposive. The instrument for quantitative study is Ryff’s Psychological Well-being Scale and the qualitative study involves the construction of a guidelines protocol for in-depth interviews of respondents. The quantitative study uses the SPSS version .19 with One Way Anova, and the qualitative analysis is manual based on transcripts with specific codes and themes. The results show nonsignificance, that is, no significant difference among religions in all family psychological well-being constructs in the comparison of Islam, Christianity, Buddhism and Hinduism, thereby accepting a null hypothesis and rejecting an alternative hypothesis. The qualitative study supports the quantitative study, that is, all 21 respondents explain that no difference exists in psychological wellbeing in the comparison of teachings in all the religious mentioned. These implications may be used as guidelines for government and non-government bodies in considering religion as an important element in family psychological well-being in the long run.
Abstract: Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.
Abstract: The method described in this paper deals with the problems of T-wave detection in an ECG. Determining the position of a T-wave is complicated due to the low amplitude, the ambiguous and changing form of the complex. A wavelet transform approach handles these complications therefore a method based on this concept was developed. In this way we developed a detection method that is able to detect T-waves with a sensitivity of 93% and a correct-detection ratio of 93% even with a serious amount of baseline drift and noise.
Abstract: Facial expression analysis plays a significant role for
human computer interaction. Automatic analysis of human facial
expression is still a challenging problem with many applications. In
this paper, we propose neuro-fuzzy based automatic facial expression
recognition system to recognize the human facial expressions like
happy, fear, sad, angry, disgust and surprise. Initially facial image is
segmented into three regions from which the uniform Local Binary
Pattern (LBP) texture features distributions are extracted and
represented as a histogram descriptor. The facial expressions are
recognized using Multiple Adaptive Neuro Fuzzy Inference System
(MANFIS). The proposed system designed and tested with JAFFE
face database. The proposed model reports 94.29% of classification
accuracy.
Abstract: One of the important applications of gas turbines is
their utilization for heat recovery steam generator in combine-cycle technology. Exhaust flow and energy are two key parameters for
determining heat recovery steam generator performance which are mainly determined by the main gas turbine components performance
data. For this reason a method was developed for determining the
exhaust energy in the new edition of ASME PTC22. The result of this investigation shows that the method of standard has considerable
error. Therefore in this paper a new method is presented for modifying of the performance calculation. The modified method is
based on exhaust gas constituent analysis and combustion calculations. The case study presented here by two kind of General
Electric gas turbine design data for validation of methodologies. The
result shows that the modified method is more precise than the ASME PTC22 method. The exhaust flow calculation deviation from
design data is 1.5-2 % by ASME PTC22 method so that the deviation regarding with modified method is 0.3-0.5%. Based on precision of
analyzer instruments, the method can be suitable alternative for gas
turbine standard performance test. In advance two methods are
proposed based on known and unknown fuel in modified method procedure. The result of this paper shows that the difference between
the two methods is below than %0.02. In according to reasonable esult of the second procedure (unknown fuel composition), the
method can be applied to performance evaluation of gas turbine, so that the measuring cost and data gathering should be reduced.
Abstract: Starting from the basic pillars of the supportability
analysis this paper queries its characteristics in LCI (Life Cycle
Integration) environment. The research methodology contents a
review of modern logistics engineering literature with the objective to
collect and synthesize the knowledge relating to standards of
supportability design in e-logistics environment. The results show
that LCI framework has properties which are in fully compatibility
with the requirement of simultaneous logistics support and productservice
bundle design. The proposed approach is a contribution to the
more comprehensive and efficient supportability design process.
Also, contributions are reflected through a greater consistency of
collected data, automated creation of reports suitable for different
analysis, as well as the possibility of their customization according
with customer needs. In addition to this, convenience of this approach
is its practical use in real time. In a broader sense, LCI allows
integration of enterprises on a worldwide basis facilitating electronic
business.
Abstract: A numerical method is proposed to calculate damping
properties for sound-proof structures involving elastic body,
viscoelastic body, and porous media. For elastic and viscoelastic body
displacement is modeled using conventional finite elements including
complex modulus of elasticity. Both effective density and bulk
modulus have complex quantities to represent damped sound fields in
the porous media. Particle displacement in the porous media is
discretised using finite element method. Displacement vectors as
common unknown variables are solved under coupled condition
between elastic body, viscoelastic body and porous media. Further,
explicit expressions of modal loss factor for the mixed structures are
derived using asymptotic method. Eigenvalue analysis and frequency
responded were calculated for automotive test panel laminated
viscoelastic and porous structures using this technique, the results
almost agreed with the experimental results.
Abstract: This paper presents the automated methods employed
for extracting craniofacial landmarks in white light images as part of
a registration framework designed to support three neurosurgical
procedures. The intraoperative space is characterised by white light
stereo imaging while the preoperative plan is performed on CT scans.
The registration aims at aligning these two modalities to provide a
calibrated environment to enable image-guided solutions. The
neurosurgical procedures can then be carried out by mapping the
entry and target points from CT space onto the patient-s space. The
registration basis adopted consists of natural landmarks (eye corner
and ear tragus). A 5mm accuracy is deemed sufficient for these three
procedures and the validity of the selected registration basis in
achieving this accuracy has been assessed by simulation studies. The
registration protocol is briefly described, followed by a presentation
of the automated techniques developed for the extraction of the
craniofacial features and results obtained from tests on the AR and
FERET databases. Since the three targeted neurosurgical procedures
are routinely used for head injury management, the effect of
bruised/swollen faces on the automated algorithms is assessed. A
user-interactive method is proposed to deal with such unpredictable
circumstances.
Abstract: Recognizing human action from videos is an active
field of research in computer vision and pattern recognition. Human
activity recognition has many potential applications such as video
surveillance, human machine interaction, sport videos retrieval and
robot navigation. Actually, local descriptors and bag of visuals words
models achieve state-of-the-art performance for human action
recognition. The main challenge in features description is how to
represent efficiently the local motion information. Most of the
previous works focus on the extension of 2D local descriptors on 3D
ones to describe local information around every interest point. In this
paper, we propose a new spatio-temporal descriptor based on a spacetime
description of moving points. Our description is focused on an
Accordion representation of video which is well-suited to recognize
human action from 2D local descriptors without the need to 3D
extensions. We use the bag of words approach to represent videos.
We quantify 2D local descriptor describing both temporal and spatial
features with a good compromise between computational complexity
and action recognition rates. We have reached impressive results on
publicly available action data set
Abstract: Tehran, one of the heavily-populated capitals, is
severely suffering from increasing air pollution. To show a
documented trend of such pollutants during last years, plane tree
species (Platanus orientalis) were suited to be studied as indicators,
for the species have been planted throughout the city many years
ago. Two areas (Saadatabad and Narmak districts) allotting different
contents of crowed and highly-traffic routs but the same ecological
characteristics were selected. Twelve sample individuals were cored
twice perpendicularly in each area. Tree-rings of each core were
measured by a binocular microscope and separated annually for the
last 25 years. Two heavy metals including Cd and Pb accompanied
by a mineral element (Ca) were analyzed using Hatch method. Treerings
analysis of the two areas showed different groups in term of
physiologically ability as the growths were plunged during the last
10 years in Saadatabad district and showed a slight decrease in the
same period for another studying area. In direct contrast to
decreasing growth trend in Saadatabad, all three mentioned elements
increased sharply during last 25 years in the same area. When it came
to Narmak district, the trend was completely different with
Saadatabad. There were some fluctuations in absorbing trace
elements like tree-rings widths were, yet calcium showed an upward
trend all the last 25 years. The results of the study proved the
possibility of using tree species of each region to monitor its air
pollution trends of the past, hence to depict a pollution assessment of
a populated city for last years and then to make appropriate decisions
for the future as it is well-known what the trend is. On the other
hand, risen values of calcium (as the stress-indicator element)
accompanied by increased trace elements suggests non-sustainable
state of the trees.