Abstract: We present new finite element methods for Helmholtz and Maxwell equations on general three-dimensional polyhedral meshes, based on domain decomposition with boundary elements on the surfaces of the polyhedral volume elements. The methods use the lowest-order polynomial spaces and produce sparse, symmetric linear systems despite the use of boundary elements. Moreover, piecewise constant coefficients are admissible. The resulting approximation on the element surfaces can be extended throughout the domain via representation formulas. Numerical experiments confirm that the convergence behavior on tetrahedral meshes is comparable to that of standard finite element methods, and equally good performance is attained on more general meshes.
Abstract: The overall objective of this paper is to retrieve soil
surfaces parameters namely, roughness and soil moisture related to
the dielectric constant by inverting the radar backscattered signal
from natural soil surfaces.
Because the classical description of roughness using statistical
parameters like the correlation length doesn't lead to satisfactory
results to predict radar backscattering, we used a multi-scale
roughness description using the wavelet transform and the Mallat
algorithm. In this description, the surface is considered as a
superposition of a finite number of one-dimensional Gaussian
processes each having a spatial scale. A second step in this study
consisted in adapting a direct model simulating radar backscattering
namely the small perturbation model to this multi-scale surface
description. We investigated the impact of this description on radar
backscattering through a sensitivity analysis of backscattering
coefficient to the multi-scale roughness parameters.
To perform the inversion of the small perturbation multi-scale
scattering model (MLS SPM) we used a multi-layer neural network
architecture trained by backpropagation learning rule. The inversion
leads to satisfactory results with a relative uncertainty of 8%.
Abstract: From the perspective of industrial structure
coordination and based on an explicit definition for the connotation of
industrial structure coordination, the synergetic coefficients are used
to measure the coordination degree between three industries' input
structure and output structure, and then the efficacy function method is
employed to comprehensively evaluate the level of China-s industrial
structure optimization. It is showed that Chinese industrial structure
presented a "v-shaped" variation tendency between 1996 and 2008,
and its industrial structure adjustment got obvious achievements after
2003, with the industrial structure optimization level increasing
continuously. However in 2009, the level of China-s industrial
structure optimization declined sharply due to the decreasing
contribution degree of value added structure and energy structure
coordination and the lower coordination degree of value added
structure and capital structure.
Abstract: Solution of some practical problems is reduced to the
solution of the integro-differential equations. But for the numerical
solution of such equations basically quadrature methods or its
combination with multistep or one-step methods are used. The
quadrature methods basically is applied to calculation of the integral
participating in right hand side of integro-differential equations. As
this integral is of Volterra type, it is obvious that at replacement with
its integrated sum the upper limit of the sum depends on a current
point in which values of the integral are defined. Thus we receive the
integrated sum with variable boundary, to work with is hardly.
Therefore multistep method with the constant coefficients, which is
free from noted lack and gives the way for finding it-s coefficients is
present.
Abstract: The Wind Turbine Modeling in Wind Energy Conversion System (WECS) using Doubly-Fed Induction Generator (DFIG) PI Controller based design is presented. To study about the variable wind speed. The PI controller performs responding to the dynamic performance. The objective is to study the characteristic of wind turbine and finding the optimum wind speed suitable for wind turbine performance. This system will allow the specification setting (2.5MW). The output active power also corresponding same the input is given. And the reactive power produced by the wind turbine is regulated at 0 Mvar. Variable wind speed is optimum for drive train performance at 12.5 m/s (at maximum power coefficient point) from the simulation of DFIG by Simulink is described.
Abstract: The purposes of this research are 1) to study English language learning strategies used by the fourth-year students majoring in English and Business English, 2) to study the English language learning strategies which have an affect on English learning achievement, and 3) to compare the English language learning strategies used by the students majoring in English and Business English. The population and sampling comprise of 139 university students of the Suan Sunandha Rajabhat University. Research instruments are language learning strategies questionnaire which was constructed by the researcher and improved on by three experts and the transcripts that show the results of English learning achievement. The questionnaire includes 1) Language Practice Strategy 2)Memory Strategy 3) Communication Strategy 4)Making an Intelligent Guess or Compensation Strategy 5) Self-discipline in Learning Management Strategy 6) Affective Strategy 7)Self-Monitoring Strategy 8) Self-studySkill Strategy. Statistics used in the study are mean, standard deviation, T-test and One Way ANOVA, Pearson product moment correlation coefficient and Regression Analysis. The results of the findings reveal that the English language learning strategies most frequently used by the students are affective strategy, making an intelligent guess or compensation strategy, self-studyskill strategy and self-monitoring strategy respectively. The aspect of making an intelligent guess or compensation strategy had the most significant affect on English learning achievement. It is found that the English language learning strategies mostly used by the Business English major students and moderately used by the English major students. Their language practice strategies uses were significantly different at the 0.05 level and their communication strategies uses were significantly different at the 0.01 level. In addition, it is found that the poor students and the fair ones most frequently used affective strategy while the good ones most frequently used making an intelligent guess or compensation strategy. KeywordsEnglish language, language learning strategies, English learning achievement, and students majoring in English, Business English. Pranee Pathomchaiwat is an Assistant Professor in Business English Program, Suan Sunandha Rajabhat University, Bangkok, Thailand (e-mail: [email protected]).
Abstract: Particulate reinforced metal matrix composites
(MMCs) are potential materials for various applications due to their
advantageous of physical and mechanical properties. This paper
presents a study on the performance of stir cast Al2O3 SiC reinforced
metal matrix composite materials. The results indicate that the
composite materials exhibit improved physical and mechanical
properties, such as, low coefficient of thermal expansion, high
ultimate tensile strength, high impact strength, and hardness. It has
been found that with the increase of weight percentage of
reinforcement particles in the aluminium metal matrix, the new
material exhibits lower wear rate against abrasive wearing. Being
extremely lighter than the conventional gray cast iron material, the
Al-Al2O3 and Al-SiC composites could be potential green materials
for applications in the automobile industry, for instance, in making
car disc brake rotors.
Abstract: In this paper, the sum of squares in linear regression is
reduced to sum of squares in semi-parametric regression. We
indicated that different sums of squares in the linear regression are
similar to various deviance statements in semi-parametric regression.
In addition to, coefficient of the determination derived in linear
regression model is easily generalized to coefficient of the
determination of the semi-parametric regression model. Then, it is
made an application in order to support the theory of the linear
regression and semi-parametric regression. In this way, study is
supported with a simulated data example.
Abstract: Flow around a flat tube is studied numerically. Reynolds number is defined base on equivalent circular tube and it is varied in range of 100 to 300. Equations are solved by using finite volume method and results are presented in form of drag and lift coefficient. Results show that drag coefficient of flat tube is up to 66% lower than circular tube with equivalent diameter. In addition, by increasing l/D from 1 to 2, the drag coefficient of flat tube is decreased about 14-27%.
Abstract: To improve the efficiency of parametric studies or
tests planning the method is proposed, that takes into account all input parameters, but only a few simulation runs are performed to
assess the relative importance of each input parameter. For K input
parameters with N input values the total number of possible combinations of input values equals NK. To limit the number of runs,
only some (totally N) of possible combinations are taken into account. The sampling procedure Updated Latin Hypercube
Sampling is used to choose the optimal combinations. To measure the
relative importance of each input parameter, the Spearman rank
correlation coefficient is proposed. The sensitivity and the influence
of all parameters are analyzed within one procedure and the key
parameters with the largest influence are immediately identified.
Abstract: The relationships between Proteolysis and soluble
calcium levels with hardness of cheese texture were investigated in
Iranian UF white cheese during 90 d ripening. Cheeses were sampled
in interior and exterior. Results showed that levels of proteolysis,
soluble calcium and hardness of cheese texture changed significantly
(p< 0.05) over ripening. Levels of proteolysis and hardness were
significantly (p< 0.05) different in interior and exterior zones of
cheeses. External zones of cheeses became softer and had higher
levels of proteolysis compared to internal zones during ripening. The
highest correlation coefficient (r2= 0.979; p
Abstract: A numerical simulation of vortex-induced vibration of
a 2-dimensional elastic circular cylinder with two degree of freedom
under the uniform flow is calculated when Reynolds is 200.
2-dimensional incompressible Navier-Stokes equations are solved
with the space-time finite element method, the equation of the cylinder
motion is solved with the new explicit integral method and the mesh
renew is achieved by the spring moving mesh technology. Considering
vortex-induced vibration with the low reduced damping parameter, the
variety trends of the lift coefficient, the drag coefficient, the
displacement of cylinder are analyzed under different oscillating
frequencies of cylinder. The phenomena of locked-in, beat and
phases-witch were captured successfully. The evolution of vortex
shedding from the cylinder with time is discussed. There are very
similar trends in characteristics between the results of the one degree
of freedom cylinder model and that of the two degree of freedom
cylinder model. The streamwise vibrations have a certain effect on the
lateral vibrations and their characteristics.
Abstract: Segmentation of a color image composed of different
kinds of regions can be a hard problem, namely to compute for an
exact texture fields. The decision of the optimum number of
segmentation areas in an image when it contains similar and/or un
stationary texture fields. A novel neighborhood-based segmentation
approach is proposed. A genetic algorithm is used in the proposed
segment-pass optimization process. In this pass, an energy function,
which is defined based on Markov Random Fields, is minimized. In
this paper we use an adaptive threshold estimation method for image
thresholding in the wavelet domain based on the generalized
Gaussian distribution (GGD) modeling of sub band coefficients. This
method called Normal Shrink is computationally more efficient and
adaptive because the parameters required for estimating the threshold
depend on sub band data energy that used in the pre-stage of
segmentation. A quad tree is employed to implement the multi
resolution framework, which enables the use of different strategies at
different resolution levels, and hence, the computation can be
accelerated. The experimental results using the proposed
segmentation approach are very encouraging.
Abstract: The binary phase-only filter digital watermarking
embeds the phase information of the discrete Fourier transform of the
image into the corresponding magnitudes for better image authentication.
The paper proposed an approach of how to implement watermark
embedding by quantizing the magnitude, with discussing how to
regulate the quantization steps based on the frequencies of the magnitude
coefficients of the embedded watermark, and how to embed the
watermark at low frequency quantization. The theoretical analysis and
simulation results show that algorithm flexibility, security, watermark
imperceptibility and detection performance of the binary phase-only
filter digital watermarking can be effectively improved with quantization
based watermark embedding, and the robustness against JPEG
compression will also be increased to some extent.
Abstract: Simultaneous determination of multicomponents of phenol, resorcinol and catechol with a chemometric technique a PCranking artificial neural network (PCranking-ANN) algorithm is reported in this study. Based on the data correlation coefficient method, 3 representative PCs are selected from the scores of original UV spectral data (35 PCs) as the original input patterns for ANN to build a neural network model. The results obtained by iterating 8000 .The RMSEP for phenol, resorcinol and catechol with PCranking- ANN were 0.6680, 0.0766 and 0.1033, respectively. Calibration matrices were 0.50-21.0, 0.50-15.1 and 0.50-20.0 μg ml-1 for phenol, resorcinol and catechol, respectively. The proposed method was successfully applied for the determination of phenol, resorcinol and catechol in synthetic and water samples.
Abstract: As the network based technologies become
omnipresent, demands to secure networks/systems against threat
increase. One of the effective ways to achieve higher security is
through the use of intrusion detection systems (IDS), which are a
software tool to detect anomalous in the computer or network. In this
paper, an IDS has been developed using an improved machine
learning based algorithm, Locally Linear Neuro Fuzzy Model
(LLNF) for classification whereas this model is originally used for
system identification. A key technical challenge in IDS and LLNF
learning is the curse of high dimensionality. Therefore a feature
selection phase is proposed which is applicable to any IDS. While
investigating the use of three feature selection algorithms, in this
model, it is shown that adding feature selection phase reduces
computational complexity of our model. Feature selection algorithms
require the use of a feature goodness measure. The use of both a
linear and a non-linear measure - linear correlation coefficient and
mutual information- is investigated respectively
Abstract: The purpose of this study is to investigate the capacity
of natural Turkish zeolite for NH4-N removal from landfill leachate.
The effects of modification and initial concentration on the removal
of NH4-N from leachate were also investigated. The kinetics of
adsorption of NH4-N has been discussed using three kinetic models,
i.e., the pseudo-second order model, the Elovich equation, the
intraparticle diffuion model. Kinetic parameters and correlation
coefficients were determined. Equilibrium isotherms for the
adsorption of NH4-N were analyzed by Langmuir, Freundlich and
Tempkin isotherm models. Langmuir isotherm model was found to
best represent the data for NH4-N.
Abstract: In this paper, we show that the stability can not be
achieved with current stabilizing MPC methods for some unstable
processes. Hence we present a new method for stabilizing these
processes. The main idea is to use a new time varying weighted cost
function for traditional GPC. This stabilizes the closed loop system
without adding soft or hard constraint in optimization problem. By
studying different examples it is shown that using the proposed
method, the closed-loop stability of unstable nonminimum phase
process is achieved.
Abstract: Gabor-based face representation has achieved enormous success in face recognition. This paper addresses a novel algorithm for face recognition using neural networks trained by Gabor features. The system is commenced on convolving a face image with a series of Gabor filter coefficients at different scales and orientations. Two novel contributions of this paper are: scaling of rms contrast and introduction of fuzzily skewed filter. The neural network employed for face recognition is based on the multilayer perceptron (MLP) architecture with backpropagation algorithm and incorporates the convolution filter response of Gabor jet. The effectiveness of the algorithm has been justified over a face database with images captured at different illumination conditions.
Abstract: The flow filed around a flatted-roof compound has
been investigated by means of 2D and 3D numerical simulations. A
constant wind velocity profile, based both on the maximum reference
wind speed in the building site (peak gust speed worked out for a 50-
year return period) and on the local roughness coefficient, has been
simulated in order to determine the wind-induced loads on top of the
roof. After determining the influence of the incoming wind directions
on the induced roof loads, a 2D analysis of the most severe load
condition has been performed, achieving a numerical quantification
of the expected wind-induced forces on the PV panels on top of the
roof.