Abstract: Mammography is the most effective procedure for an
early diagnosis of the breast cancer. Nowadays, people are trying to
find a way or method to support as much as possible to the
radiologists in diagnosis process. The most popular way is now being
developed is using Computer-Aided Detection (CAD) system to
process the digital mammograms and prompt the suspicious region to
radiologist. In this paper, an automated CAD system for detection
and classification of massive lesions in mammographic images is
presented. The system consists of three processing steps: Regions-Of-
Interest detection, feature extraction and classification. Our CAD
system was evaluated on Mini-MIAS database consisting 322
digitalized mammograms. The CAD system-s performance is
evaluated using Receiver Operating Characteristics (ROC) and Freeresponse
ROC (FROC) curves. The archived results are 3.47 false
positives per image (FPpI) and sensitivity of 85%.
Abstract: Osteoarthritis (OA) is the most prevalent and far common debilitating form of arthritis which can be defined as a degenerative condition affecting synovial joint. Patients suffering from osteoarthritis often complain of dull ache pain on movement.
Physical agents can fight the painful process when correctly indicated and used such as heat or cold therapy Aim. This study was carried out to: Compare the effect of cold, warm and contrast therapy on controlling knee osteoarthritis associated problems. Setting: The study was carried out in orthopedic outpatient clinics of Menoufia University and teaching Hospitals, Egypt. Sample: A convenient sample of 60 adult patients with unilateral knee osteoarthritis. Tools: three tools were utilized to collect the data. Tool I : An interviewing questionnaire. It comprised of three parts covering sociodemographic data, medical data and adverse effects of the treatment protocol. Tool II : Knee Injury and Osteoarthritis Outcome Score (KOOS) It consists of five main parts. Tool II1 : 0-10 Numeric pain rating scale. Results: reveled that the total knee symptoms score was decreased from moderate symptoms pre intervention to mild symptoms after warm and contrast method of therapy, but the contrast therapy had significant effect in reducing the knee symptoms and pain than the other symptoms. Conclusions: all of the three
methods of therapy resulted in improvement in all knee symptoms and pain but the most appropriate protocol of treatment to relive symptoms and pain was contrast therapy.
Abstract: The solitary wave solution of the quadratic nonlinear Schrdinger equation is determined by the iterative method called Petviashvili method. This solution is also used for the initial condition for the time evolution to study the stability analysis. The spectral method is applied for the time evolution.
Abstract: Economic dispatch problem is an optimization problem where objective function is highly non linear, non-convex, non-differentiable and may have multiple local minima. Therefore, classical optimization methods may not converge or get trapped to any local minima. This paper presents a comparative study of four different evolutionary algorithms i.e. genetic algorithm, bacteria foraging optimization, ant colony optimization and particle swarm optimization for solving the economic dispatch problem. All the methods are tested on IEEE 30 bus test system. Simulation results are presented to show the comparative performance of these methods.
Abstract: We show that Chebyshev Polynomials are a practical representation of computable functions on the computable reals. The paper presents error estimates for common operations and demonstrates that Chebyshev Polynomial methods would be more efficient than Taylor Series methods for evaluation of transcendental functions.
Abstract: The aim of this work is to determine the supersonic
nozzle profiles used in propulsion, for the launchers or embarked
with the satellites. This design has as a role firstly, to give a
important propulsion, i.e. with uniform and parallel flow at exit,
secondly to find a short length profiles without modification of the
flow in the nozzle. The first elaborate program is used to determine
the profile of divergent by using the characteristics method for an
axisymmetric flow. The second program is conceived by using the
finite volume method to determine and test the profile found
connected to a convergent.
Abstract: Face detection and recognition has many applications
in a variety of fields such as security system, videoconferencing and
identification. Face classification is currently implemented in
software. A hardware implementation allows real-time processing,
but has higher cost and time to-market.
The objective of this work is to implement a classifier based on
neural networks MLP (Multi-layer Perceptron) for face detection.
The MLP is used to classify face and non-face patterns. The systm is
described using C language on a P4 (2.4 Ghz) to extract weight
values. Then a Hardware implementation is achieved using VHDL
based Methodology. We target Xilinx FPGA as the implementation
support.
Abstract: Real-time object tracking is a problem which involves extraction of critical information from complex and uncertain imagedata. In this paper, we present a comprehensive methodology to design an artificial neural network (ANN) for a real-time object tracking application. The object, which is tracked for the purpose of demonstration, is a specific airplane. However, the proposed ANN can be trained to track any other object of interest. The ANN has been simulated and tested on the training and testing datasets, as well as on a real-time streaming video. The tracking error is analyzed with post-regression analysis tool, which finds the correlation among the calculated coordinates and the correct coordinates of the object in the image. The encouraging results from the computer simulation and analysis show that the proposed ANN architecture is a good candidate solution to a real-time object tracking problem.
Abstract: A good green building design project, designers should consider not only energy consumption, but also healthy and comfortable needs of inhabitants. In recent years, the Taiwan government paid attentions on both carbon reduction and indoor air quality issues, which be presented in the legislation of Building Codes and other regulations. Taiwan located in hot and humid climates, dampness in buildings leads to significant microbial pollution and building damage. This means that the high temperature and humidity present a serious indoor air quality issue. The interactions between vapor transfers and energy fluxes are essential for the whole building Heat Air and Moisture (HAM) response. However, a simulation tool with short calculation time, property accuracy and interface is needed for practical building design processes. In this research, we consider the vapor transfer phenomenon of building materials as well as temperature and humidity and energy consumption in a building space. The simulation bases on the EMPD method, which was performed by EnergyPlus, a simulation tool developed by DOE, to simulate the indoor moisture variation in a one-zone residential unit based on the Effective Moisture Penetration Depth Method, which is more suitable for practical building design processes.
Abstract: Linear approximation of point spread function (PSF) is a new method for determining subpixel translations between images. The problem with the actual algorithm is the inability of determining translations larger than 1 pixel. In this paper a multiresolution technique is proposed to deal with the problem. Its performance is evaluated by comparison with two other well known registration method. In the proposed technique the images are downsampled in order to have a wider view. Progressively decreasing the downsampling rate up to the initial resolution and using linear approximation technique at each step, the algorithm is able to determine translations of several pixels in subpixel levels.
Abstract: The performance of a sucrose-based H2 production in
a completely stirred tank reactor (CSTR) was modeled by neural
network back-propagation (BP) algorithm. The H2 production was
monitored over a period of 450 days at 35±1 ºC. The proposed model
predicts H2 production rates based on hydraulic retention time
(HRT), recycle ratio, sucrose concentration and degradation, biomass
concentrations, pH, alkalinity, oxidation-reduction potential (ORP),
acids and alcohols concentrations. Artificial neural networks (ANNs)
have an ability to capture non-linear information very efficiently. In
this study, a predictive controller was proposed for management and
operation of large scale H2-fermenting systems. The relevant control
strategies can be activated by this method. BP based ANNs modeling
results was very successful and an excellent match was obtained
between the measured and the predicted rates. The efficient H2
production and system control can be provided by predictive control
method combined with the robust BP based ANN modeling tool.
Abstract: The scientific community has invested a great deal of effort in the fields of discrete wavelet transform in the last few decades. Discrete wavelet transform (DWT) associated with the vector quantization has been proved to be a very useful tool for the compression of image. However, the DWT is very computationally intensive process requiring innovative and computationally efficient method to obtain the image compression. The concurrent transformation of the image can be an important solution to this problem. This paper proposes a model of concurrent DWT for image compression. Additionally, the formal verification of the model has also been performed. Here the Symbolic Model Verifier (SMV) has been used as the formal verification tool. The system has been modeled in SMV and some properties have been verified formally.
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: One of the main research methods in humanistic studies is the collection and process of data through questionnaires. This paper reports our experiences of localizing and adapting the phpESP package of electronic surveys, which led to a friendly on-line questionnaire environment offered through our department web site. After presenting the characteristics of this environment, we identify the expected benefits and present a questionnaire carried out through both the traditional and electronic way. We present the respondents' feedback and then we report the researchers' opinions.Finally, we propose ideas we intend to implement in order to further assist and enhance the research based on this web accessed,electronic questionnaire environment.
Abstract: Restarted GMRES methods augmented with approximate eigenvectors are widely used for solving large sparse linear systems. Recently a new scheme of augmenting with error approximations is proposed. The main aim of this paper is to develop a restarted GMRES method augmented with the combination of harmonic Ritz vectors and error approximations. We demonstrate that the resulted combination method can gain the advantages of two approaches: (i) effectively deflate the small eigenvalues in magnitude that may hamper the convergence of the method and (ii) partially recover the global optimality lost due to restarting. The effectiveness and efficiency of the new method are demonstrated through various numerical examples.
Abstract: In this paper a fast motion estimation method for
H.264/AVC named Triplet Search Motion Estimation (TS-ME) is
proposed. Similar to some of the traditional fast motion estimation
methods and their improved proposals which restrict the search points
only to some selected candidates to decrease the computation
complexity, proposed algorithm separate the motion search process to
several steps but with some new features. First, proposed algorithm try
to search the real motion area using proposed triplet patterns instead of
some selected search points to avoid dropping into the local minimum.
Then, in the localized motion area a novel 3-step motion search
algorithm is performed. Proposed search patterns are categorized into
three rings on the basis of the distance from the search center. These
three rings are adaptively selected by referencing the surrounding
motion vectors to early terminate the motion search process. On the
other hand, computation reduction for sub pixel motion search is also
discussed considering the appearance probability of the sub pixel
motion vector. From the simulation results, motion estimation speed
improved by a factor of up to 38 when using proposed algorithm than
that of the reference software of H.264/AVC with ignorable picture
quality loss.
Abstract: The colors of the human skin represent a special
category of colors, because they are distinctive from the colors of
other natural objects. This category is found as a cluster in color
spaces, and the skin color variations between people are mostly due
to differences in the intensity. Besides, the face detection based on
skin color detection is a faster method as compared to other
techniques. In this work, we present a system to track faces by
carrying out skin color detection in four different color spaces: HSI,
YCbCr, YES and RGB. Once some skin color regions have been
detected for each color space, we label each and get some
characteristics such as size and position. We are supposing that a face
is located in one the detected regions. Next, we compare and employ
a polling strategy between labeled regions to determine the final
region where the face effectively has been detected and located.
Abstract: Double-diffusive natural convection in an open top
square cavity and heated from the side is studied numerically.
Constant temperatures and concentration are imposed along the right
and left walls while the heat balance at the surface is assumed to obey
Newton-s law of cooling. The finite difference method is used to
solve the dimensionless governing equations. The numerical results
are reported for the effect of Marangoni number, Biot number and
Prandtl number on the contours of streamlines, temperature and
concentration. The predicted results for the average Nusselt number
and Sherwood number are presented for various parametric
conditions. The parameters involved are as follows; the thermal
Marangoni number, 0 ≤ MaT ≤1000 , the solutal Marangoni number,
0 1000 c ≤ Ma ≤ , the Biot number, 0 ≤ Bi ≤ 6 , Grashof number,
5 Gr = 10 and aspect ratio 1. The study focused on both flows; thermal
dominated, N = 0.8 , and compositional dominated, N = 1.3 .
Abstract: This analysis investigates the distortion of flow
measurement and the increase of cavitation along orifice
flowmeter. The analysis using the numerical method (CFD)
validated the distortion of flow measurement through the inlet
velocity profile considering the convergence and grid
dependency. Realizable k-e model was selected and y+ was
about 50 in this numerical analysis. This analysis also estimated
the vulnerability of cavitation effect due to inlet velocity profile.
The investigation concludes that inclined inlet velocity profile
could vary the pressure which was measured at pressure tab
near pipe wall and it led to distort the pressure values ranged
from -3.8% to 5.3% near the orifice plate and to make the
increase of cavitation. The investigation recommends that the
fully developed inlet velocity flow is beneficial to accurate flow
measurement in orifice flowmeter.
Abstract: Carbon nanotubes (CNTs) possess unique structural,
mechanical, thermal and electronic properties, and have been
proposed to be used for applications in many fields. However, to
reach the full potential of the CNTs, many problems still need to be
solved, including the development of an easy and effective
purification procedure, since synthesized CNTs contain impurities,
such as amorphous carbon, carbon nanoparticles and metal particles.
Different purification methods yield different CNT characteristics
and may be suitable for the production of different types of CNTs. In
this study, the effect of different purification chemicals on carbon
nanotube quality was investigated. CNTs were firstly synthesized by
chemical vapor deposition (CVD) of acetylene (C2H2) on a
magnesium oxide (MgO) powder impregnated with an iron nitrate
(Fe(NO3)3·9H2O) solution. The synthesis parameters were selected
as: the synthesis temperature of 800°C, the iron content in the
precursor of 5% and the synthesis time of 30 min. The liquid phase
oxidation method was applied for the purification of the synthesized
CNT materials. Three different acid chemicals (HNO3, H2SO4, and
HCl) were used in the removal of the metal catalysts from the
synthesized CNT material to investigate the possible effects of each
acid solution to the purification step. Purification experiments were
carried out at two different temperatures (75 and 120 °C), two
different acid concentrations (3 and 6 M) and for three different time
intervals (6, 8 and 15 h). A 30% H2O2 : 3M HCl (1:1 v%) solution
was also used in the purification step to remove both the metal
catalysts and the amorphous carbon. The purifications using this
solution were performed at the temperature of 75°C for 8 hours.
Purification efficiencies at different conditions were evaluated by
thermogravimetric analysis. Thermal and electrical properties of
CNTs were also determined. It was found that the obtained electrical
conductivity values for the carbon nanotubes were typical for organic
semiconductor materials and thermal stabilities were changed
depending on the purification chemicals.