Abstract: The objective of this paper is to propose an adaptive multi threshold for image segmentation precisely in object detection. Due to the different types of license plates being used, the requirement of an automatic LPR is rather different for each country. The proposed technique is applied on Malaysian LPR application. It is based on Multi Layer Perceptron trained by back propagation. The proposed adaptive threshold is introduced to find the optimum threshold values. The technique relies on the peak value from the graph of the number object versus specific range of threshold values. The proposed approach has improved the overall performance compared to current optimal threshold techniques. Further improvement on this method is in progress to accommodate real time system specification.
Abstract: In this paper, we have combined some spatial derivatives with the optimised time derivative proposed by Tam and Webb in order to approximate the linear advection equation which is given by = 0. Ôêé Ôêé + Ôêé Ôêé x f t u These spatial derivatives are as follows: a standard 7-point 6 th -order central difference scheme (ST7), a standard 9-point 8 th -order central difference scheme (ST9) and optimised schemes designed by Tam and Webb, Lockard et al., Zingg et al., Zhuang and Chen, Bogey and Bailly. Thus, these seven different spatial derivatives have been coupled with the optimised time derivative to obtain seven different finite-difference schemes to approximate the linear advection equation. We have analysed the variation of the modified wavenumber and group velocity, both with respect to the exact wavenumber for each spatial derivative. The problems considered are the 1-D propagation of a Boxcar function, propagation of an initial disturbance consisting of a sine and Gaussian function and the propagation of a Gaussian profile. It is known that the choice of the cfl number affects the quality of results in terms of dissipation and dispersion characteristics. Based on the numerical experiments solved and numerical methods used to approximate the linear advection equation, it is observed in this work, that the quality of results is dependent on the choice of the cfl number, even for optimised numerical methods. The errors from the numerical results have been quantified into dispersion and dissipation using a technique devised by Takacs. Also, the quantity, Exponential Error for Low Dispersion and Low Dissipation, eeldld has been computed from the numerical results. Moreover, based on this work, it has been found that when the quantity, eeldld can be used as a measure of the total error. In particular, the total error is a minimum when the eeldld is a minimum.
Abstract: The present study is concerned with the effect of
exciting boundary layer on cooling process in a gas-turbine blades.
The cooling process is numerically investigated. Observations show
cooling the first row of moving or stable blades leads to increase
their life-time. Results show that minimum temperature in cooling
line with exciting boundary layer is lower than without exciting.
Using block in cooling line of turbines' blade causes flow pattern and
stability in boundary layer changed that causes increase in heat
transfer coefficient. Results show at the location of block,
temperature of turbines' blade is significantly decreased. The k-ε
turbulence model is used.
Abstract: In this paper the concept of strongly (λM)p - Ces'aro
summability of a sequence of fuzzy numbers and strongly λM- statistically convergent sequences of fuzzy numbers is introduced.
Abstract: An unstructured finite volume numerical model is
presented here for simulating shallow-water flows with wetting and
drying fronts. The model is based on the Green-s theorem in
combination with Chorin-s projection method. A 2nd-order upwind
scheme coupled with a Least Square technique is used to handle
convection terms. An Wetting and drying treatment is used in the
present model to ensures the total mass conservation. To test it-s
capacity and reliability, the present model is used to solve the
Parabolic Bowl problem. We compare our numerical solutions with
the corresponding analytical and existing standard numerical results.
Excellent agreements are found in all the cases.
Abstract: Industrial radiography is a famous technique for the identification and evaluation of discontinuities, or defects, such as cracks, porosity and foreign inclusions found in welded joints. Although this technique has been well developed, improving both the inspection process and operating time, it does suffer from several drawbacks. The poor quality of radiographic images is due to the physical nature of radiography as well as small size of the defects and their poor orientation relatively to the size and thickness of the evaluated parts. Digital image processing techniques allow the interpretation of the image to be automated, avoiding the presence of human operators making the inspection system more reliable, reproducible and faster. This paper describes our attempt to develop and implement digital image processing algorithms for the purpose of automatic defect detection in radiographic images. Because of the complex nature of the considered images, and in order that the detected defect region represents the most accurately possible the real defect, the choice of global and local preprocessing and segmentation methods must be appropriated.
Abstract: This research contribution is drafted to present the
orbit design, orbit propagator and geomagnetic field estimator for the
nanosatellites specifically for the upcoming CUBESAT, ICUBE-1 of
the Institute of Space Technology (IST), Islamabad, Pakistan. The
ICUBE mission is designed for the low earth orbit at the approximate
height of 700KM. The presented research endeavor designs the
Keplarian elements for ICUBE-1 orbit while incorporating the
mission requirements and propagates the orbit using J2 perturbations,
The attitude determination system of the ICUBE-1 consists of
attitude determination sensors like magnetometer and sun sensor. The
Geomagnetic field estimator is developed according to the model of
International Geomagnetic Reference Field (IGRF) for comparing the
magnetic field measurements by the magnetometer for attitude
determination. The output of the propagator namely the Keplarians
position and velocity vectors and the magnetic field vectors are
compared and verified with the same scenario generated in the
Satellite Tool Kit (STK).
Abstract: Segmentation techniques based on Active Contour
Models have been strongly benefited from the use of prior information
during their evolution. Shape prior information is captured from
a training set and is introduced in the optimization procedure to
restrict the evolution into allowable shapes. In this way, the evolution
converges onto regions even with weak boundaries. Although
significant effort has been devoted on different ways of capturing
and analyzing prior information, very little thought has been devoted
on the way of combining image information with prior information.
This paper focuses on a more natural way of incorporating the
prior information in the level set framework. For proof of concept
the method is applied on hippocampus segmentation in T1-MR
images. Hippocampus segmentation is a very challenging task, due
to the multivariate surrounding region and the missing boundary
with the neighboring amygdala, whose intensities are identical. The
proposed method, mimics the human segmentation way and thus
shows enhancements in the segmentation accuracy.
Abstract: The main goal of the present work is to decrease the
computational burden for optimum design of steel frames with
frequency constraints using a new type of neural networks called
Wavelet Neural Network. It is contested to train a suitable neural
network for frequency approximation work as the analysis program.
The combination of wavelet theory and Neural Networks (NN)
has lead to the development of wavelet neural networks.
Wavelet neural networks are feed-forward networks using
wavelet as activation function. Wavelets are mathematical
functions within suitable inner parameters, which help them to
approximate arbitrary functions. WNN was used to predict the
frequency of the structures. In WNN a RAtional function with
Second order Poles (RASP) wavelet was used as a transfer
function. It is shown that the convergence speed was faster
than other neural networks. Also comparisons of WNN with
the embedded Artificial Neural Network (ANN) and with
approximate techniques and also with analytical solutions are
available in the literature.
Abstract: Although services play a crucial role in economy,
service did not gain as much importance as productivity management
in manufacturing. This paper presents key findings from literature
and practice. Based on an initial definition of complex services, seven
productivity concepts are briefly presented and assessed by relevant,
complex service specific criteria. Following the findings a complex
service productivity model is proposed. The novel model comprises
of all specific dimensions of service provision from both, the
provider-s as well as costumer-s perspective. A clear assignment of
identified value drivers and relationships between them is presented.
In order to verify the conceptual service productivity model a case
study from a project engineering department of a chemical plant
development and construction company is presented.
Abstract: Proper management of residues originated from
industrial activities is considered as one of the serious challenges
faced by industrial societies due to their potential hazards to the
environment. Common disposal methods for industrial solid wastes
(ISWs) encompass various combinations of solely management
options, i.e. recycling, incineration, composting, and sanitary
landfilling. Indeed, the procedure used to evaluate and nominate the
best practical methods should be based on environmental, technical,
economical, and social assessments. In this paper an environmentaltechnical
assessment model is developed using analytical network
process (ANP) to facilitate the decision making practice for ISWs
generated at Gilan province, Iran. Using the results of performed
surveys on industrial units located at Gilan, the various groups of
solid wastes in the research area were characterized, and four
different ISW management scenarios were studied. The evaluation
process was conducted using the above-mentioned model in the
Super Decisions software (version 2.0.8) environment. The results
indicates that the best ISW management scenario for Gilan province
is consist of recycling the metal industries residues, composting the
putrescible portion of ISWs, combustion of paper, wood, fabric and
polymeric wastes as well as energy extraction in the incineration
plant, and finally landfilling the rest of the waste stream in addition
with rejected materials from recycling and compost production plants
and ashes from the incineration unit.
Abstract: In cellular networks, limited availability of resources
has to be tapped to its fullest potential. In view of this aspect, a
sophisticated averaging and voting technique has been discussed in
this paper, wherein the radio resources available are utilized to the
fullest value by taking into consideration, several network and radio
parameters which decide on when the handover has to be made and
thereby reducing the load on Base station .The increase in the load
on the Base station might be due to several unnecessary handover
taking place which can be eliminated by making judicious use of the
radio and network parameters.
Abstract: Emergence of smartphones brings to live the concept
of converged devices with the availability of web amenities. Such
trend also challenges the mobile devices manufactures and service
providers in many aspects, such as security on mobile phones,
complex and long time design flow, as well as higher development
cost. Among these aspects, security on mobile phones is getting more
and more attention. Microkernel based virtualization technology will
play a critical role in addressing these challenges and meeting mobile
market needs and preferences, since virtualization provides essential
isolation for security reasons and it allows multiple operating systems
to run on one processor accelerating development and cutting development
cost. However, virtualization benefits do not come for free.
As an additional software layer, it adds some inevitable virtualization
overhead to the system, which may decrease the system performance.
In this paper we evaluate and analyze the virtualization performance
cost of L4 microkernel based virtualization on a competitive mobile
phone by comparing the L4Linux, a para-virtualized Linux on top of
L4 microkernel, with the native Linux performance using lmbench
and a set of typical mobile phone applications.
Abstract: The so-called all-pass filter circuits are commonly
used in the field of signal processing, control and measurement.
Being connected to capacitive loads, these circuits tend to loose their
stability; therefore the elaborate analysis of their dynamic behavior is
necessary. The compensation methods intending to increase the
stability of such circuits are discussed in this paper, including the socalled
lead-lag compensation technique being treated in detail. For
the dynamic modeling, a two-port network model of the all-pass filter
is being derived. The results of the model analysis show, that
effective lead-lag compensation can be achieved, alone by the
optimization of the circuit parameters; therefore the application of
additional electric components are not needed to fulfill the stability
requirement.
Abstract: This paper presents a computational methodology
based on matrix operations for a computer based solution to the
problem of performance analysis of software reliability models
(SRMs). A set of seven comparison criteria have been formulated to
rank various non-homogenous Poisson process software reliability
models proposed during the past 30 years to estimate software
reliability measures such as the number of remaining faults, software
failure rate, and software reliability. Selection of optimal SRM for
use in a particular case has been an area of interest for researchers in
the field of software reliability. Tools and techniques for software
reliability model selection found in the literature cannot be used with
high level of confidence as they use a limited number of model
selection criteria. A real data set of middle size software project from
published papers has been used for demonstration of matrix method.
The result of this study will be a ranking of SRMs based on the
Permanent value of the criteria matrix formed for each model based
on the comparison criteria. The software reliability model with
highest value of the Permanent is ranked at number – 1 and so on.
Abstract: Manufacturing processes demand tight dimensional
tolerances. The paper concerns a transducer for precise measurement
of displacement, based on a camera containing a linescan chip.
When tests were conducted using a track of black and white stripes
with a 2mm pitch, errors in measuring on individual cycle amounted
to 1.75%, suggesting that a precision of 35 microns is achievable.
Abstract: Multiphase flow transport in porous medium is very common and significant in science and engineering applications. For example, in CO2 Storage and Enhanced Oil Recovery processes, CO2 has to be delivered to the pore spaces in reservoirs and aquifers. CO2 storage and enhance oil recovery are actually displacement processes, in which oil or water is displaced by CO2. This displacement is controlled by pore size, chemical and physical properties of pore surfaces and fluids, and also pore wettability. In this study, a technique was developed to measure the pressure profile for driving gas/liquid to displace water in pores. Through this pressure profile, the impact of pore size on the multiphase flow transport and displacement can be analyzed. The other rig developed can be used to measure the static and dynamic pore wettability and investigate the effects of pore size, surface tension, viscosity and chemical structure of liquids on pore wettability.
Abstract: Most routing protocols (DSR, AODV etc.) that have
been designed for wireless adhoc networks incorporate the broadcasting
operation in their route discovery scheme. Probabilistic broadcasting
techniques have been developed to optimize the broadcast operation
which is otherwise very expensive in terms of the redundancy
and the traffic it generates. In this paper we have explored percolation
theory to gain a different perspective on probabilistic broadcasting
schemes which have been actively researched in the recent years.
This theory has helped us estimate the value of broadcast probability
in a wireless adhoc network as a function of the size of the network.
We also show that, operating at those optimal values of broadcast
probability there is at least 25-30% reduction in packet regeneration
during successful broadcasting.
Abstract: The purpose of this study is to present a non invasive
method for the marginal adaptation evaluation in class V composite
restorations. Standardized class V cavities, prepared in human
extracted teeth, were filled with Premise (Kerr) composite. The
specimens were thermo cycled. The interfaces were examined by
Optical Coherence Tomography method (OCT) combined with the
confocal microscopy and fluorescence. The optical configuration
uses two single mode directional couplers with a superluminiscent
diode as the source at 1300 nm. The scanning procedure is similar to
that used in any confocal microscope, where the fast scanning is enface
(line rate) and the depth scanning is much slower (at the frame
rate). Gaps at the interfaces as well as inside the composite resin
materials were identified. OCT has numerous advantages which
justify its use in vivo as well as in vitro in comparison with
conventional techniques.
Abstract: Corporate credit rating prediction using statistical and
artificial intelligence (AI) techniques has been one of the attractive
research topics in the literature. In recent years, multiclass
classification models such as artificial neural network (ANN) or
multiclass support vector machine (MSVM) have become a very
appealing machine learning approaches due to their good
performance. However, most of them have only focused on classifying
samples into nominal categories, thus the unique characteristic of the
credit rating - ordinality - has been seldom considered in their
approaches. This study proposes new types of ANN and MSVM
classifiers, which are named OMANN and OMSVM respectively.
OMANN and OMSVM are designed to extend binary ANN or SVM
classifiers by applying ordinal pairwise partitioning (OPP) strategy.
These models can handle ordinal multiple classes efficiently and
effectively. To validate the usefulness of these two models, we applied
them to the real-world bond rating case. We compared the results of
our models to those of conventional approaches. The experimental
results showed that our proposed models improve classification
accuracy in comparison to typical multiclass classification techniques
with the reduced computation resource.