Abstract: In these days, multimedia data is transmitted and
processed in compressed format. Due to the decoding procedure and
filtering for edge detection, the feature extraction process of MPEG-7
Edge Histogram Descriptor is time-consuming as well as
computationally expensive. To improve efficiency of compressed
image retrieval, we propose a new edge histogram generation
algorithm in DCT domain in this paper. Using the edge information
provided by only two AC coefficients of DCT coefficients, we can get
edge directions and strengths directly in DCT domain. The
experimental results demonstrate that our system has good
performance in terms of retrieval efficiency and effectiveness.
Abstract: Thermal conductivity is an important characteristic of
a nanofluid in laminar flow heat transfer. This paper presents an
improved model for the prediction of the effective thermal
conductivity of nanofluids based on dimensionless groups. The
model expresses the thermal conductivity of a nanofluid as a function
of the thermal conductivity of the solid and liquid, their volume
fractions and particle size. The proposed model includes a parameter
which accounts for the interfacial shell, brownian motion, and
aggregation of particle. The validation of the model is verified by
applying the results obtained by the experiments of Tio2-water and
Al2o3-water nanofluids.
Abstract: Pressure wave velocity in a hydraulic system was
determined using piezo pressure sensors without removing fluid from
the system. The measurements were carried out in a low pressure
range (0.2 – 6 bar) and the results were compared with the results of
other studies. This method is not as accurate as measurement with
separate measurement equipment, but the fluid is in the actual
machine the whole time and the effect of air is taken into
consideration if air is present in the system. The amount of air is
estimated by calculations and comparisons between other studies.
This measurement equipment can also be installed in an existing
machine and it can be programmed so that it measures in real time.
Thus, it could be used e.g. to control dampers.
Abstract: The tubes in an Ammonia primary reformer furnace
operate close to the limits of materials technology in terms of the
stress induced as a result of very high temperatures, combined with
large differential pressures across the tube wall. Operation at tube
wall temperatures significantly above design can result in a rapid
increase in the number of tube failures, since tube life is very
sensitive to the absolute operating temperature of the tube. Clearly it
is important to measure tube wall temperatures accurately in order to
prevent premature tube failure by overheating.. In the present study,
the catalyst tubes in an Ammonia primary reformer has been modeled
taking into consideration heat, mass and momentum transfer as well
as reformer characteristics.. The investigations concern the effects of
tube characteristics and superficial tube wall temperatures on of the
percentage of heat flux, unconverted methane and production of
Hydrogen for various values of steam to carbon ratios. The results
show the impact of catalyst tubes length and diameters on the
performance of operating parameters in ammonia primary reformers.
Abstract: A two-parameter fatigue model explicitly accounting for the cyclic as well as the mean stress was used to fit static and fatigue data available in literature concerning carbon fiber reinforced composite laminates subjected tension-tension fatigue. The model confirms the strength–life equal rank assumption and predicts reasonably the probability of failure under cyclic loading. The model parameters were found by best fitting procedures and required a minimum of experimental tests.
Abstract: In this study, a vibration analysis was carried out of
symmetric angle-ply laminated composite plates with and without
square hole when subjected to compressive loads, numerically. A
buckling analysis is also performed to determine the buckling load of
laminated plates. For each fibre orientation, the compression load is
taken equal to 50% of the corresponding buckling load. In the
analysis, finite element method (FEM) was applied to perform
parametric studies, the effects of degree of orthotropy and stacking
sequence upon the fundamental frequencies and buckling loads are
discussed. The results show that the presence of a constant
compressive load tends to reduce uniformly the natural frequencies
for materials which have a low degree of orthotropy. However, this
reduction becomes non-uniform for materials with a higher degree of
orthotropy.
Abstract: In this paper we present a Feed-Foward Neural
Networks Autoregressive (FFNN-AR) model with genetic algorithms
training optimization in order to predict the gross domestic product
growth of six countries. Specifically we propose a kind of weighted
regression, which can be used for econometric purposes, where the
initial inputs are multiplied by the neural networks final optimum
weights from input-hidden layer of the training process. The
forecasts are compared with those of the ordinary autoregressive
model and we conclude that the proposed regression-s forecasting
results outperform significant those of autoregressive model.
Moreover this technique can be used in Autoregressive-Moving
Average models, with and without exogenous inputs, as also the
training process with genetics algorithms optimization can be
replaced by the error back-propagation algorithm.
Abstract: loss of feedwater accident is one of the frequently sever accidents in steam boiler facilities. It threatens the system structural integrity and generates serious hazards and economic loses. The safety analysis of the thermal installations, based extensively on the numeric simulation. The simulation analysis using realistic computer codes like Relap5/Mod3.2 will help understand steam boiler thermal-hydraulic behavior during normal and abnormal conditions. In this study, we are interested on the evaluation of the radiant steam boiler assessment and response to loss-of-feedwater accident. Pressure, temperature and flow rate profiles are presented in various steam boiler system components. The obtained results demonstrate the importance and capability of the Relap5/Mod3.2 code in the thermal-hydraulic analysis of the steam boiler facilities.
Abstract: This paper presents a new methodology to select test
cases from regression test suites. The selection strategy is based on
analyzing the dynamic behavior of the applications that written in
any programming language. Methods based on dynamic analysis are
more safe and efficient. We design a technique that combine the code
based technique and model based technique, to allow comparing the
object oriented of an application that written in any programming
language. We have developed a prototype tool that detect changes
and select test cases from test suite.
Abstract: There are several approaches in trying to solve the
Quantitative 1Structure-Activity Relationship (QSAR) problem.
These approaches are based either on statistical methods or on
predictive data mining. Among the statistical methods, one should
consider regression analysis, pattern recognition (such as cluster
analysis, factor analysis and principal components analysis) or partial
least squares. Predictive data mining techniques use either neural
networks, or genetic programming, or neuro-fuzzy knowledge. These
approaches have a low explanatory capability or non at all. This
paper attempts to establish a new approach in solving QSAR
problems using descriptive data mining. This way, the relationship
between the chemical properties and the activity of a substance
would be comprehensibly modeled.
Abstract: In this research, a systematic investigation was carried out to determine the optimum conditions of HDS reactor. Moreover, a suitable model was developed for a rigorous RTO (real time optimization) loop of HDS (Hydro desulfurization) process. A systematic experimental series was designed based on CCD (Central Composite design) and carried out in the related pilot plant to tune the develop model. The designed variables in the experiments were Temperature, LHSV and pressure. However, the hydrogen over fresh feed ratio was remained constant. The ranges of these variables were respectively equal to 320-380ºC, 1- 21/hr and 50-55 bar. a power law kinetic model was also developed for our further research in the future .The rate order and activation energy , power of reactant concentration and frequency factor of this model was respectively equal to 1.4, 92.66 kJ/mol and k0=2.7*109 .
Abstract: The noteworthy point in the advancement of Brain Machine Interface (BMI) research is the ability to accurately extract features of the brain signals and to classify them into targeted control action with the easiest procedures since the expected beneficiaries are of disabled. In this paper, a new feature extraction method using the combination of adaptive band pass filters and adaptive autoregressive (AAR) modelling is proposed and applied to the classification of right and left motor imagery signals extracted from the brain. The introduction of the adaptive bandpass filter improves the characterization process of the autocorrelation functions of the AAR models, as it enhances and strengthens the EEG signal, which is noisy and stochastic in nature. The experimental results on the Graz BCI data set have shown that by implementing the proposed feature extraction method, a LDA and SVM classifier outperforms other AAR approaches of the BCI 2003 competition in terms of the mutual information, the competition criterion, or misclassification rate.
Abstract: Restoration of endodontically treated teeth is a
common problem in dentistry, related to the fractures occurring in
such teeth and to concentration of forces little information regarding
variation of basic preparation guidelines in stress distribution has
been available. To date, there is still no agreement in the literature
about which material or technique can optimally restore
endodontically treated teeth. The aim of the present study was to
evaluate the influence of the core height and restoration materials on
corono-radicular restored upper first premolar. The first step of the
study was to achieve 3D models in order to analyze teeth, dowel and
core restorations and overlying full ceramic crowns. The FEM model
was obtained by importing the solid model into ANSYS finite
element analysis software. An occlusal load of 100 N was conducted,
and stresses occurring in the restorations, and teeth structures were
calculated. Numerical simulations provide a biomechanical
explanation for stress distribution in prosthetic restored teeth. Within
the limitations of the present study, it was found that the core height
has no important influence on the stress generated in coronoradicular
restored premolars. It can be drawn that the cervical regions
of the teeth and restorations were subjected to the highest stress
concentrations.
Abstract: Diagnostic and detection of the arterial stiffness is
very important; which gives indication of the associated increased risk of cardiovascular diseases. To make a cheap and easy method for general screening technique to avoid the future cardiovascular
complexes , due to the rising of the arterial stiffness ; a proposed algorithm depending on photoplethysmogram to be used. The
photoplethysmograph signals would be processed in MATLAB. The
signal will be filtered, baseline wandering removed, peaks and
valleys detected and normalization of the signals should be achieved
.The area under the catacrotic phase of the photoplethysmogram
pulse curve is calculated using trapezoidal algorithm ; then will used
in cooperation with other parameters such as age, height, blood
pressure in neural network for arterial stiffness detection. The Neural
network were implemented with sensitivity of 80%, accuracy 85%
and specificity of 90% were got from the patients data. It is
concluded that neural network can detect the arterial STIFFNESS
depending on risk factor parameters.
Abstract: In this paper, the estimation of the stress-strength
parameter R = P(Y < X), when X and Y are independent and both
are Lomax distributions with the common scale parameters but
different shape parameters is studied. The maximum likelihood
estimator of R is derived. Assuming that the common scale parameter
is known, the bayes estimator and exact confidence interval of R are
discussed. Simulation study to investigate performance of the
different proposed methods has been carried out.
Abstract: This paper describes a simulation model for analyzing artificial emotion injected to design the game characters. Most of the game storyboard is interactive in nature and the virtual characters of the game are equipped with an individual personality and dynamic emotion value which is similar to real life emotion and behavior. The uncertainty in real expression, mood and behavior is also exhibited in game paradigm and this is focused in the present paper through a fuzzy logic based agent and storyboard. Subsequently, a pheromone distribution or labeling is presented mimicking the behavior of social insects.
Abstract: In this paper we are to find the optimum
multiwavelet for compression of electrocardiogram (ECG)
signals. At present, it is not well known which multiwavelet is
the best choice for optimum compression of ECG. In this
work, we examine different multiwavelets on 24 sets of ECG
data with entirely different characteristics, selected from MITBIH
database. For assessing the functionality of the different
multiwavelets in compressing ECG signals, in addition to
known factors such as Compression Ratio (CR), Percent Root
Difference (PRD), Distortion (D), Root Mean Square Error
(RMSE) in compression literature, we also employed the
Cross Correlation (CC) criterion for studying the
morphological relations between the reconstructed and the
original ECG signal and Signal to reconstruction Noise Ratio
(SNR). The simulation results show that the cardbal2 by the
means of identity (Id) prefiltering method to be the best
effective transformation.
Abstract: Heavy rains are one of the features of arid and semi
arid climates which result in flood. This kind of rainfall originates
from environmental and synoptic conditions. Mediterranean cyclones
are the major factor in heavy rainfall in Iran, but these cyclones do
not happen in some parts of Iran such as Southern and Southeastern
areas. In this study, it has been tried to pinpoint the synoptic reasons
of heavy rainfall in Isfahan through the analysis of the relationship
between this rainfall in Isfahan and atmospheric system over Iran and
the areas around it. The findings of this study show that the major
factor have is the arrival of Sudanese low pressure system in this
region from the southwest, of course if the ascent local conditions
such as heat occur, the heaviest rains happen in Isfahan. In fact this
kind of rainfall in Isfahan has a Sudanese origin and if it is
accompanied by Mediterranean system, heavier rain falls.
Abstract: In this paper, a second order autoregressive (AR)
model is proposed to discriminate alcoholics using single trial
gamma band Visual Evoked Potential (VEP) signals using 3 different
classifiers: Simplified Fuzzy ARTMAP (SFA) neural network (NN),
Multilayer-perceptron-backpropagation (MLP-BP) NN and Linear
Discriminant (LD). Electroencephalogram (EEG) signals were
recorded from alcoholic and control subjects during the presentation
of visuals from Snodgrass and Vanderwart picture set. Single trial
VEP signals were extracted from EEG signals using Elliptic filtering
in the gamma band spectral range. A second order AR model was
used as gamma band VEP exhibits pseudo-periodic behaviour and
second order AR is optimal to represent this behaviour. This
circumvents the requirement of having to use some criteria to choose
the correct order. The averaged discrimination errors of 2.6%, 2.8%
and 11.9% were given by LD, MLP-BP and SFA classifiers. The
high LD discrimination results show the validity of the proposed
method to discriminate between alcoholic subjects.
Abstract: Displacement measurement was conducted on compact normal and shear specimens made of acrylic homogeneous material subjected to mixed-mode loading by digital image correlation. The intelligent hybrid method proposed by Nishioka et al. was applied to the stress-strain analysis near the crack tip. The accuracy of stress-intensity factor at the free surface was discussed from the viewpoint of both the experiment and 3-D finite element analysis. The surface images before and after deformation were taken by a CMOS camera, and we developed the system which enabled the real time stress analysis based on digital image correlation and inverse problem analysis. The great portion of processing time of this system was spent on displacement analysis. Then, we tried improvement in speed of this portion. In the case of cracked body, it is also possible to evaluate fracture mechanics parameters such as the J integral, the strain energy release rate, and the stress-intensity factor of mixed-mode. The 9-points elliptic paraboloid approximation could not analyze the displacement of submicron order with high accuracy. The analysis accuracy of displacement was improved considerably by introducing the Newton-Raphson method in consideration of deformation of a subset. The stress-intensity factor was evaluated with high accuracy of less than 1% of the error.