Abstract: Analysis for the generalized thermoelastic Lamb
waves, which propagates in anisotropic thin plates in generalized
thermoelasticity, is presented employing normal mode expansion
method. The displacement and temperature fields are expressed by a
summation of the symmetric and antisymmetric thermoelastic modes
in the surface thermal stresses and thermal gradient free orthotropic
plate, therefore the theory is particularly appropriate for waveform
analyses of Lamb waves in thin anisotropic plates. The transient
waveforms excited by the thermoelastic expansion are analyzed for
an orthotropic thin plate. The obtained results show that the theory
provides a quantitative analysis to characterize anisotropic
thermoelastic stiffness properties of plates by wave detection. Finally
numerical calculations have been presented for a NaF crystal, and the
dispersion curves for the lowest modes of the symmetric and
antisymmetric vibrations are represented graphically at different
values of thermal relaxation time. However, the methods can be used
for other materials as well
Abstract: In recent years, copulas have become very popular in
financial research and actuarial science as they are more flexible in
modelling the co-movements and relationships of risk factors as compared
to the conventional linear correlation coefficient by Pearson.
However, a precise estimation of the copula parameters is vital in
order to correctly capture the (possibly nonlinear) dependence structure
and joint tail events. In this study, we employ two optimization
heuristics, namely Differential Evolution and Threshold Accepting to
tackle the parameter estimation of multivariate t distribution models
in the EML approach. Since the evolutionary optimizer does not rely
on gradient search, the EML approach can be applied to estimation of
more complicated copula models such as high-dimensional copulas.
Our experimental study shows that the proposed method provides
more robust and more accurate estimates as compared to the IFM
approach.
Abstract: In order to calculate the flexural strength of
normal-strength concrete (NSC) beams, the nonlinear actual concrete
stress distribution within the compression zone is normally replaced
by an equivalent rectangular stress block, with two coefficients of α
and β to regulate the intensity and depth of the equivalent stress
respectively. For NSC beams design, α and β are usually assumed
constant as 0.85 and 0.80 in reinforced concrete (RC) codes. From an
earlier investigation of the authors, α is not a constant but significantly
affected by flexural strain gradient, and increases with the increasing
of strain gradient till a maximum value. It indicates that larger
concrete stress can be developed in flexure than that stipulated by
design codes. As an extension and application of the authors- previous
study, the modified equivalent concrete stress block is used here to
produce a series of design charts showing the maximum design limits
of flexural strength and ductility of singly- and doubly- NSC beams,
through which both strength and ductility design limits are improved
by taking into account strain gradient effect.
Abstract: A numerical study on the influence of electroosmotic flow on analyte preconcentration by isotachophoresis ( ITP) is made. We consider that the double layer induced electroosmotic flow ( EOF) counterbalance the electrophoretic velocity and a stationary ITP stacked zones results. We solve the Navier-Stokes equations coupled with the Nernst-Planck equations to determine the local convective velocity and the preconcentration dynamics of ions. Our numerical algorithm is based on a finite volume method along with a secondorder upwind scheme. The present numerical algorithm can capture the the sharp boundaries of step-changes ( plateau mode) or zones of steep gradients ( peak mode) accurately. The convection of ions due to EOF reduces the resolution of the ITP transition zones and produces a dispersion in analyte zones. The role of the electrokinetic parameters which induces dispersion is analyzed. A one-dimensional model for the area-averaged concentrations based on the Taylor-Aristype effective diffusivity is found to be in good agreement with the computed solutions.
Abstract: A self tuning PID control strategy using reinforcement
learning is proposed in this paper to deal with the control of wind
energy conversion systems (WECS). Actor-Critic learning is used to
tune PID parameters in an adaptive way by taking advantage of the
model-free and on-line learning properties of reinforcement learning
effectively. In order to reduce the demand of storage space and to
improve the learning efficiency, a single RBF neural network is used
to approximate the policy function of Actor and the value function of
Critic simultaneously. The inputs of RBF network are the system
error, as well as the first and the second-order differences of error.
The Actor can realize the mapping from the system state to PID
parameters, while the Critic evaluates the outputs of the Actor and
produces TD error. Based on TD error performance index and
gradient descent method, the updating rules of RBF kernel function
and network weights were given. Simulation results show that the
proposed controller is efficient for WECS and it is perfectly
adaptable and strongly robust, which is better than that of a
conventional PID controller.
Abstract: The study of interaction among the grain, moisture,
and the surrounding space (air) is key to understanding the graindrying
process. In Iran, rice (mostly Indica type) is dried by flat
bed type dryer until the final MC reaches to 6 to 8%. The
experiments were conducted to examine the effect of application of
discharge fan with different heights of paddy on the drying
efficiency. Experiments were designed based on two different
configurations of the drying methods; with and without discharge
fan with three different heights of paddy including; 5, 10, and 15
cm. The humid heated air will be going out immediately by the
suction of discharge fan. The drying time is established upon the
average final MC to achieve about 8%. To save energy and reduce
the drying time, the distribution of temperature between layers
should be fast and uniform with minimum difference; otherwise
the difference of MC gradient between layers will be high and will
induce grain breakage. The difference of final MC between layers
in the two methods was 48-73%. The steady state of temperature
between the two methods has saved time in the range of 10-20%,
and the efficiency of temperature distribution increased 17-26% by
the use of discharge fan.
Abstract: The error diffusion method generates worm artifacts,
and weakens the edge of the halftone image when the continuous gray
scale image is reproduced by a binary image. First, to enhance the
edges, we propose the edge-enhancing filter by considering the
quantization error information and gradient of the neighboring pixels.
Furthermore, to remove worm artifacts often appearing in a halftone
image, we add adaptively random noise into the weights of an error
filter.
Abstract: The H.264/AVC standard uses an intra prediction, 9
directional modes for 4x4 luma blocks and 8x8 luma blocks, 4
directional modes for 16x16 macroblock and 8x8 chroma blocks,
respectively. It means that, for a macroblock, it has to perform 736
different RDO calculation before a best RDO modes is determined.
With this Multiple intra-mode prediction, intra coding of H.264/AVC
offers a considerably higher improvement in coding efficiency
compared to other compression standards, but computational
complexity is increased significantly. This paper presents a fast intra
prediction algorithm for H.264/AVC intra prediction based a
characteristic of homogeneity information. In this study, the gradient
prediction method used to predict the homogeneous area and the
quadratic prediction function used to predict the nonhomogeneous
area. Based on the correlation between the homogeneity and block
size, the smaller block is predicted by gradient prediction and
quadratic prediction, so the bigger block is predicted by gradient
prediction. Experimental results are presented to show that the
proposed method reduce the complexity by up to 76.07%
maintaining the similar PSNR quality with about 1.94%bit rate
increase in average.
Abstract: This work presents the highly accurate numerical calculation
of the natural frequencies for functionally graded beams with
simply supported boundary conditions. The Timoshenko first order
shear deformation beam theory and the higher order shear deformation
beam theory of Reddy have been applied to the functionally
graded beams analysis. The material property gradient is assumed
to be in the thickness direction. The Hamilton-s principle is utilized
to obtain the dynamic equations of functionally graded beams. The
influences of the volume fraction index and thickness-to-length ratio
on the fundamental frequencies are discussed. Comparison of the
numerical results for the homogeneous beam with Euler-Bernoulli
beam theory results show that the derived model is satisfactory.
Abstract: Empirical force fields and density functional theory
(DFT) was used to study the binding energies and structures of
methylamine on the surface of activated carbons (ACs). This is a first
step in studying the adsorption of alkyl amines on the surface of
functionalized ACs. The force fields used were Dreiding (DFF),
Universal (UFF) and Compass (CFF) models. The generalized
gradient approximation with Perdew Wang 91 (PW91) functional
was used for DFT calculations. In addition to obtaining the aminecarboxylic
acid adsorption energies, the results were used to establish
reliability of the empirical models for these systems. CFF predicted a
binding energy of -9.227 (kcal/mol) which agreed with PW91 at -
13.17 (kcal/mol), compared to DFF 0 (kcal/mol) and UFF -0.72
(kcal/mol). However, the CFF binding energies for the amine to ester
and ketone disagreed with PW91 results. The structures obtained
from all models agreed with PW91 results.
Abstract: Different variants for buoyancy-affected terms in k-ε turbulence model have been utilized to predict the flow parameters more accurately, and investigate applicability of alternative k-ε turbulence buoyant closures in numerical simulation of a horizontal gravity current. The additional non-isotropic turbulent stress due to buoyancy has been considered in production term, based on Algebraic Stress Model (ASM). In order to account for turbulent scalar fluxes, general gradient diffusion hypothesis has been used along with Boussinesq gradient diffusion hypothesis with a variable turbulent Schmidt number and additional empirical constant c3ε.To simulate buoyant flow domain a 2D vertical numerical model (WISE, Width Integrated Stratified Environments), based on Reynolds- Averaged Navier-Stokes (RANS) equations, has been deployed and the model has been further developed for different k-ε turbulence closures. Results are compared against measured laboratory values of a saline gravity current to explore the efficient turbulence model.
Abstract: The presence of cold air with the convergent
topography of the Lut valley over the valley-s sloping terrain can
generate Low Level Jets (LLJ). Moreover, the valley-parallel
pressure gradients and northerly LLJ are produced as a result of the
large-scale processes. In the numerical study the regional MM5
model was run leading to achieve an appropriate dynamical analysis
of flows in the region for summer and winter. The results of this
study show the presence of summer synoptical systems cause the
formation of north-south pressure gradients in the valley which could
be led to the blowing of winds with the velocity more than 14 ms-1
and vulnerable dust and wind storms lasting more than 120 days.
Whereas the presence of cold air masses in the region in winter,
cause the average speed of LLJs decrease. In this time downslope
flows are noticeable in creating the night LLJs.
Abstract: According to conjugate gradient algorithm, a new consensus protocol algorithm of discrete-time multi-agent systems is presented, which can achieve finite-time consensus. Finally, a numerical example is given to illustrate our theoretical result.
Abstract: ZnO+Ga2O3 functionally graded thin films (FGTFs)
were examined for their potential use as Solar cell and organic light
emitting diodes (OLEDs). FGTF transparent conducting oxides (TCO)
were fabricated by combinatorial RF magnetron sputtering. The
composition gradient was controlled up to 10% by changing the
plasma power of the two sputter guns. A Ga2O3+ZnO graded region
was placed on the top layer of ZnO. The FGTFs showed up to 80%
transmittance. Their surface resistances were reduced to < 10% by
increasing the Ga2O3: pure ZnO ratio in the TCO. The FGTFs- work
functions could be controlled within a range of 0.18 eV. The
controlled work function is a very promising technology because it
reduces the contact resistance between the anode and Hall transport
layers of OLED and solar cell devices.
Abstract: Most neural network (NN) models of human category learning use a gradient-based learning method, which assumes that locally-optimal changes are made to model parameters on each learning trial. This method tends to under predict variability in individual-level cognitive processes. In addition many recent models of human category learning have been criticized for not being able to replicate rapid changes in categorization accuracy and attention processes observed in empirical studies. In this paper we introduce stochastic learning algorithms for NN models of human category learning and show that use of the algorithms can result in (a) rapid changes in accuracy and attention allocation, and (b) different learning trajectories and more realistic variability at the individual-level.
Abstract: In intensity modulated radiation therapy (IMRT)
treatment planning, beam angles are usually preselected on the basis of
experience and intuition. Therefore, getting an appropriate beam
configuration needs a very long time. Based on the present situation,
the paper puts forward beam orientation optimization using ant colony
optimization (ACO). We use ant colony optimization to select the
beam configurations, after getting the beam configuration using
Conjugate Gradient (CG) algorithm to optimize the intensity profiles.
Combining with the information of the effect of pencil beam, we can
get the global optimal solution accelerating. In order to verify the
feasibility of the presented method, a simulated and clinical case was
tested, compared with dose-volume histogram and isodose line
between target area and organ at risk. The results showed that the
effect was improved after optimizing beam configurations. The
optimization approach could make treatment planning meet clinical
requirements more efficiently, so it had extensive application
perspective.
Abstract: This paper proposes a method for speckle reduction in
medical ultrasound imaging while preserving the edges with the
added advantages of adaptive noise filtering and speed. A nonlinear
image diffusion method that incorporates local image parameter,
namely, scatterer density in addition to gradient, to weight the
nonlinear diffusion process, is proposed. The method was tested for
the isotropic case with a contrast detail phantom and varieties of
clinical ultrasound images, and then compared to linear and some
other diffusion enhancement methods. Different diffusion parameters
were tested and tuned to best reduce speckle noise and preserve
edges. The method showed superior performance measured both
quantitatively and qualitatively when incorporating scatterer density
into the diffusivity function. The proposed filter can be used as a
preprocessing step for ultrasound image enhancement before
applying automatic segmentation, automatic volumetric calculations,
or 3D ultrasound volume rendering.
Abstract: There are two common methodologies to verify
signatures: the functional approach and the parametric approach. This
paper presents a new approach for dynamic handwritten signature
verification (HSV) using the Neural Network with verification by the
Conjugate Gradient Neural Network (NN). It is yet another avenue in
the approach to HSV that is found to produce excellent results when
compared with other methods of dynamic. Experimental results show
the system is insensitive to the order of base-classifiers and gets a
high verification ratio.
Abstract: An iterative definition of any n variable mean function is given in this article, which iteratively uses the two-variable form of the corresponding two-variable mean function. This extension method omits recursivity which is an important improvement compared with certain recursive formulas given before by Ando-Li-Mathias, Petz- Temesi. Furthermore it is conjectured here that this iterative algorithm coincides with the solution of the Riemann centroid minimization problem. Certain simulations are given here to compare the convergence rate of the different algorithms given in the literature. These algorithms will be the gradient and the Newton mehod for the Riemann centroid computation.
Abstract: Structural behavior of ring stiffened thick walled
cylinders made of functionally graded materials (FGMs) is
investigated in this paper. Functionally graded materials are inhomogeneous composites which are usually made from a mixture
of metal and ceramic. The gradient compositional variation of the
constituents from one surface to the other provides an elegant solution to the problem of high transverse shear stresses that are
induced when two dissimilar materials with large differences in material properties are bonded. FGM formation of the cylinder is
modeled by power-law exponent and the variation of characteristics is supposed to be in radial direction.
A finite element formulation is derived for the analysis. According to the property variation of the constituent materials in the radial
direction of the wall, it is not convenient to use conventional elements to model and analyze the structure of the stiffened FGM
cylinders. In this paper a new cylindrical super-element is used to model the finite element formulation and analyze the static and
modal behavior of stiffened FGM thick walled cylinders. By using
this super-element the number of elements, which are needed for
modeling, will reduce significantly and the process time is less in comparison with conventional finite element formulations. Results for static and modal analysis are evaluated and verified by
comparison to finite element formulation with conventional
elements. Comparison indicates a good conformity between results.