Abstract: Due to increased number of terrorist attacks in recent years, loads induced by explosions need to be incorporated in building designs. For safer performance of a structure, its foundation should have sufficient strength and stability. Therefore, prior to any reconstruction or rehabilitation of a building subjected to blast, it is important to examine adverse effects on the foundation caused by blast induced ground shocks. This paper evaluates the effects of a buried explosion on a pile foundation. It treats the dynamic response of the pile in saturated sand, using explicit dynamic nonlinear finite element software LS-DYNA. The blast induced wave propagation in the soil and the horizontal deformation of pile are presented and the results are discussed. Further, a parametric study is carried out to evaluate the effect of varying the explosive shape on the pile response. This information can be used to evaluate the vulnerability of piled foundations to credible blast events as well as develop guidance for their design.
Abstract: We report the electronic structure and optical
properties of NdF3 compound. Our calculations are based on density
functional theory (DFT) using the full potential linearized augmented
plane wave (FPLAPW) method with the inclusion of spin orbit
coupling. We employed the local spin density approximation (LSDA)
and Coulomb-corrected local spin density approximation, known for
treating the highly correlated 4f electrons properly, is able to
reproduce the correct insulating ground state. We find that the
standard LSDA approach is incapable of correctly describing the
electronic properties of such materials since it positions the f-bands
incorrectly resulting in an incorrect metallic ground state. On the
other hand, LSDA + U approximation, known for treating the highly
correlated 4f electrons properly, is able to reproduce the correct
insulating ground state. Interestingly, however, we do not find any
significant differences in the optical properties calculated using
LSDA, and LSDA + U suggesting that the 4f electrons do not play a
decisive role in the optical properties of these compounds. The
reflectivity for NdF3 compound stays low till 7 eV which is
consistent with their large energy gaps. The calculated energy gaps
are in good agreement with experiments. Our calculated reflectivity
compares well with the experimental data and the results are analyzed
in the light of band to band transitions.
Abstract: We present an explicit expression to estimate driving voltage attenuation through RC networks representation of an ultrahigh- speed image sensor. Elmore delay metric for a fundamental RC chain is employed as the first-order approximation. By application of dimensional analysis to SPICE simulation data, we found a simple expression that significantly improves the accuracy of the approximation. Estimation error of the resultant expression for uniform RC networks is less than 2%. Similarly, another simple closed-form model to estimate 50 % delay through fundamental RC networks is also derived with sufficient accuracy. The framework of this analysis can be extended to address delay or attenuation issues of other VLSI structures.
Abstract: The paper presents an analytical solution for dispersion
of a solute in the peristaltic motion of a micropolar fluid in the
presence of magnetic field and both homogeneous and heterogeneous
chemical reactions. The average effective dispersion coefficient has
been found using Taylor-s limiting condition under long wavelength
approximation. The effects of various relevant parameters on the average
coefficient of dispersion have been studied. The average effective
dispersion coefficient increases with amplitude ratio, cross viscosity
coefficient and heterogeneous chemical reaction rate parameter. But it
decreases with magnetic field parameter and homogeneous chemical
reaction rate parameter. It can be noted that the presence of peristalsis
enhances dispersion of a solute.
Abstract: Traffic congestion has become a major problem in
many countries. One of the main causes of traffic congestion is due
to road merges. Vehicles tend to move slower when they reach the
merging point. In this paper, an enhanced algorithm for traffic
simulation based on the fluid-dynamic algorithm and kinematic wave
theory is proposed. The enhanced algorithm is used to study traffic
congestion at a road merge. This paper also describes the
development of a dynamic traffic simulation tool which is used as a
scenario planning and to forecast traffic congestion level in a certain
time based on defined parameter values. The tool incorporates the
enhanced algorithm as well as the two original algorithms. Output
from the three above mentioned algorithms are measured in terms of
traffic queue length, travel time and the total number of vehicles
passing through the merging point. This paper also suggests an
efficient way of reducing traffic congestion at a road merge by
analyzing the traffic queue length and travel time.
Abstract: In this paper, we propose a supervised method for
color image classification based on a multilevel sigmoidal neural
network (MSNN) model. In this method, images are classified into
five categories, i.e., “Car", “Building", “Mountain", “Farm" and
“Coast". This classification is performed without any segmentation
processes. To verify the learning capabilities of the proposed method,
we compare our MSNN model with the traditional Sigmoidal Neural
Network (SNN) model. Results of comparison have shown that the
MSNN model performs better than the traditional SNN model in the
context of training run time and classification rate. Both color
moments and multi-level wavelets decomposition technique are used
to extract features from images. The proposed method has been
tested on a variety of real and synthetic images.
Abstract: Scale Time Offset Robust Modulation (STORM) [1]–
[3] is a high bandwidth waveform design that adds time-scale
to embedded reference modulations using only time-delay [4]. In
an environment where each user has a specific delay and scale,
identification of the user with the highest signal power and that
user-s phase is facilitated by the STORM processor. Both of these
parameters are required in an efficient multiuser detection algorithm.
In this paper, the STORM modulation approach is evaluated with
a direct sequence spread quadrature phase shift keying (DS-QPSK)
system. A misconception of the STORM time scale modulation is that
a fine temporal resolution is required at the receiver. STORM will
be applied to a QPSK code division multiaccess (CDMA) system
by modifying the spreading codes. Specifically, the in-phase code
will use a typical spreading code, and the quadrature code will
use a time-delayed and time-scaled version of the in-phase code.
Subsequently, the same temporal resolution in the receiver is required
before and after the application of STORM. In this paper, the bit error
performance of STORM in a synchronous CDMA system is evaluated
and compared to theory, and the bit error performance of STORM
incorporated in a single user WCDMA downlink is presented to
demonstrate the applicability of STORM in a modern communication
system.
Abstract: We here propose improved version of elastic graph matching (EGM) as a face detector, called the multi-scale EGM (MS-EGM). In this improvement, Gabor wavelet-based pyramid reduces computational complexity for the feature representation often used in the conventional EGM, but preserving a critical amount of information about an image. The MS-EGM gives us higher detection performance than Viola-Jones object detection algorithm of the AdaBoost Haar-like feature cascade. We also show rapid detection speeds of the MS-EGM, comparable to the Viola-Jones method. We find fruitful benefits in the MS-EGM, in terms of topological feature representation for a face.
Abstract: This paper examines predictability in stock return in
developed and emergingmarkets by testing long memory in stock
returns using wavelet approach. Wavelet-based maximum likelihood
estimator of the fractional integration estimator is superior to the
conventional Hurst exponent and Geweke and Porter-Hudak
estimator in terms of asymptotic properties and mean squared error.
We use 4-year moving windows to estimate the fractional integration
parameter. Evidence suggests that stock return may not be predictable
indeveloped countries of the Asia-Pacificregion. However,
predictability of stock return insome developing countries in this
region such as Indonesia, Malaysia and Philippines may not be ruled
out. Stock return in the Thailand stock market appears to be not
predictable after the political crisis in 2008.
Abstract: This paper proposes new hybrid approaches for face
recognition. Gabor wavelets representation of face images is an
effective approach for both facial action recognition and face
identification. Perform dimensionality reduction and linear
discriminate analysis on the down sampled Gabor wavelet faces can
increase the discriminate ability. Nearest feature space is extended to
various similarity measures. In our experiments, proposed Gabor
wavelet faces combined with extended neural net feature space
classifier shows very good performance, which can achieve 93 %
maximum correct recognition rate on ORL data set without any preprocessing
step.
Abstract: Lossless compression schemes with secure
transmission play a key role in telemedicine applications that helps in
accurate diagnosis and research. Traditional cryptographic algorithms
for data security are not fast enough to process vast amount of data.
Hence a novel Secured lossless compression approach proposed in
this paper is based on reversible integer wavelet transform, EZW
algorithm, new modified runlength coding for character
representation and selective bit scrambling. The use of the lifting
scheme allows generating truly lossless integer-to-integer wavelet
transforms. Images are compressed/decompressed by well-known
EZW algorithm. The proposed modified runlength coding greatly
improves the compression performance and also increases the
security level. This work employs scrambling method which is fast,
simple to implement and it provides security. Lossless compression
ratios and distortion performance of this proposed method are found
to be better than other lossless techniques.
Abstract: Truss spars are used for oil exploitation in deep and ultra-deep water if storage crude oil is not needed. The linear hydrodynamic analysis of truss spar in random sea wave load is necessary for determining the behaviour of truss spar. This understanding is not only important for design of the mooring lines, but also for optimising the truss spar design. In this paper linear hydrodynamic analysis of truss spar is carried out in frequency domain. The hydrodynamic forces are calculated using the modified Morison equation and diffraction theory. Added mass and drag coefficients of truss section computed by transmission matrix and normal acceleration and velocity component acting on each element and for hull section computed by strip theory. The stiffness properties of the truss spar can be separated into two components; hydrostatic stiffness and mooring line stiffness. Then, platform response amplitudes obtained by solved the equation of motion. This equation is non-linear due to viscous damping term therefore linearised by iteration method [1]. Finally computed RAOs and significant response amplitude and results are compared with experimental data.
Abstract: Wavelets have provided the researchers with
significant positive results, by entering the texture defect detection domain. The weak point of wavelets is that they are one-dimensional
by nature so they are not efficient enough to describe and analyze two-dimensional functions. In this paper we present a new method to
detect the defect of texture images by using curvelet transform.
Simulation results of the proposed method on a set of standard
texture images confirm its correctness. Comparing the obtained results indicates the ability of curvelet transform in describing
discontinuity in two-dimensional functions compared to wavelet
transform
Abstract: Structural and UV/Visible optical properties can be
useful to describe a material for the CIGS solar cell active layer,
therefore, this work demonstrates the properties like surface
morphology, X-ray Photoelectron Spectroscopy (XPS) bonding
energy (EB) core level spectra, UV/Visible absorption spectra,
refractive index (n), optical energy band (Eg), reflection spectra for
the Cu25 (In16Ga9) Se40Te10 (CIGST-1) and Cu20 (In14Ga9) Se45Te12
(CIGST-2) chalcogenide compositions. Materials have been
exhibited homogenous surface morphologies, broading /-or diffusion
of bonding energy peaks relative elemental values and a high
UV/Visible absorption tendency in the wave length range 400 nm-
850 nm range with the optical energy band gaps 1.37 and 1.42
respectively. Subsequently, UV/Visible reflectivity property in the
wave length range 250 nm to 320 nm for these materials has also
been discussed.
Abstract: The urban centers within northeastern Brazil are
mainly influenced by the intense rainfalls, which can occur after long
periods of drought, when flood events can be observed during such
events. Thus, this paper aims to study the rainfall frequencies in such
region through the wavelet transform. An application of wavelet
analysis is done with long time series of the total monthly rainfall
amount at the capital cities of northeastern Brazil. The main
frequency components in the time series are studied by the global
wavelet spectrum and the modulation in separated periodicity bands
were done in order to extract additional information, e.g., the 8 and
16 months band was examined by an average of all scales, giving a
measure of the average annual variance versus time, where the
periods with low or high variance could be identified. The important
increases were identified in the average variance for some periods,
e.g. 1947 to 1952 at Teresina city, which can be considered as high
wet periods. Although, the precipitation in those sites showed similar
global wavelet spectra, the wavelet spectra revealed particular
features. This study can be considered an important tool for time
series analysis, which can help the studies concerning flood control,
mainly when they are applied together with rainfall-runoff
simulations.
Abstract: Movable power sources of proton exchange
membrane fuel cells (PEMFC) are the important research done in the
current fuel cells (FC) field. The PEMFC system control influences
the cell performance greatly and it is a control system for industrial
complex problems, due to the imprecision, uncertainty and partial
truth and intrinsic nonlinear characteristics of PEMFCs. In this paper
an adaptive PI control strategy using neural network adaptive Morlet
wavelet for control is proposed. It is based on a single layer feed
forward neural networks with hidden nodes of adaptive morlet
wavelet functions controller and an infinite impulse response (IIR)
recurrent structure. The IIR is combined by cascading to the network
to provide double local structure resulting in improving speed of
learning. The proposed method is applied to a typical 1 KW PEMFC
system and the results show the proposed method has more accuracy
against to MLP (Multi Layer Perceptron) method.
Abstract: In this paper, a wavelet based method is proposed to
identify the constant coefficients of a second order linear system and
is compared with the least squares method. The proposed method
shows improved accuracy of parameter estimation as compared to the
least squares method. Additionally, it has the advantage of smaller
data requirement and storage requirement as compared to the least
squares method.
Abstract: We describe a novel method for removing noise (in wavelet domain) of unknown variance from microarrays. The method is based on the following procedure: We apply 1) Bidimentional Discrete Wavelet Transform (DWT-2D) to the Noisy Microarray, 2) scaling and rounding to the coefficients of the highest subbands (to obtain integer and positive coefficients), 3) bit-slicing to the new highest subbands (to obtain bit-planes), 4) then we apply the Systholic Boolean Orthonormalizer Network (SBON) to the input bit-plane set and we obtain two orthonormal otput bit-plane sets (in a Boolean sense), we project a set on the other one, by means of an AND operation, and then, 5) we apply re-assembling, and, 6) rescaling. Finally, 7) we apply Inverse DWT-2D and reconstruct a microarray from the modified wavelet coefficients. Denoising results compare favorably to the most of methods in use at the moment.
Abstract: We have modeled the effect of a graded band gap
window on the performance of a single junction AlxGa1-xAs/GaAs
solar cell. First, we study the electrical characteristics of a single
junction AlxGa1-xAs/GaAs solar cell, by employing an optimized
structure for this solar cell, we show that grading the band gap of the
window can increase the conversion efficiency of the solar cell by
about 1.5%, and can also improve the quantum efficiency of the solar
cell especially at shorter wavelengths.
Abstract: We investigated statistical performance of Bayesian inference using maximum entropy and MAP estimation for several models which approximated wave-fronts in remote sensing using SAR interferometry. Using Monte Carlo simulation for a set of wave-fronts generated by assumed true prior, we found that the method of maximum entropy realized the optimal performance around the Bayes-optimal conditions by using model of the true prior and the likelihood representing optical measurement due to the interferometer. Also, we found that the MAP estimation regarded as a deterministic limit of maximum entropy almost achieved the same performance as the Bayes-optimal solution for the set of wave-fronts. Then, we clarified that the MAP estimation perfectly carried out phase unwrapping without using prior information, and also that the MAP estimation realized accurate phase unwrapping using conjugate gradient (CG) method, if we assumed the model of the true prior appropriately.