Abstract: Data on 657 lactation from 163 Maltese goat,
collected over a 5-year period were analyzed by a mixed model to
estimate the variance components for heritability. The considered
lactation traits were: milk yield (MY) and lactation length (LL). Year,
parity and type of birth (single or twin) were significant sources of
variation for lactation length; on the other hand milk yield was
significantly influenced only by the year. The average MY was
352.34 kg and the average LL was 230 days. Estimates of heritability
were 0.21 and 0.15 for MY and LL respectively. These values
suggest there is low correlation between genotype and phenotype so
it may be difficult to evaluate animals directly on phenotype. So, the
genetic improvement of this breed may be quite slow without the
support of progeny test aimed to select Maltese breeders.
Abstract: Steel made pipelines with different diameters are used
for transmitting oil and gas which in many cases are buried in soil
under the sea bed or immersed in sea water. External corrosion of
pipes is an important form of deterioration due to the aggressive
environment of sea water. Corrosion normally results in pits. Hence,
using the finite element method, namely ABAQUS software, this
paper estimates the amount of pressure capacity reduction of a pipecontaining
a semi-elliptical pitting corrosion and the rate of corrosion
during the pipeline life of 25 years.
Abstract: In this paper, the concepts of dichotomous logistic
regression (DLR) with leave-one-out (L-O-O) were discussed. To
illustrate this, the L-O-O was run to determine the importance of the
simulation conditions for robust test of spread procedures with good
Type I error rates. The resultant model was then evaluated. The
discussions included 1) assessment of the accuracy of the model, and
2) parameter estimates. These were presented and illustrated by
modeling the relationship between the dichotomous dependent
variable (Type I error rates) with a set of independent variables (the
simulation conditions). The base SAS software containing PROC
LOGISTIC and DATA step functions can be making used to do the
DLR analysis.
Abstract: In this paper, an H1-Galerkin mixed finite element method is discussed for the coupled Burgers equations. The optimal error estimates of the semi-discrete and fully discrete schemes of the coupled Burgers equation are derived.
Abstract: Synchronization is a difficult problem in CDMA
satellite communications. Due to the influence of additive noise and
fading in the mobile channel, it is not easy to keep up with the
attenuation and offset. This paper considers a recently proposed
approach to solve the problem of synchronization chaotic Chen
system in CDMA satellite communication in the presence of constant
attenuation and offset. An analytic algorithm that provides closed
form channel and carrier offset estimates is presented. The principle
of this approach is based on adding a compensation block before the
receiver to compensate the distortion of the imperfect channel by
using genetic algorithm.
The resultants presented, show that the receiver is able to recover
rapidly the synchronization with the transmitter.
Abstract: Self-sensing estimates the air gap within an electro
magnetic path by analyzing the bearing coil current and/or voltage
waveform. The self-sensing concept presented in this paper has been
developed within the research project “Active Magnetic Bearings
with Supreme Reliability" and is used for position sensor fault
detection.
Within this new concept gap calculation is carried out by an alldigital
analysis of the digitized coil current and voltage waveform.
For analysis those time periods within the PWM period are used,
which give the best results. Additionally, the concept allows the
digital compensation of nonlinearities, for example magnetic
saturation, without degrading signal quality. This increases the
accuracy and robustness of the air gap estimation and additionally
reduces phase delays.
Beneath an overview about the developed concept first
measurement results are presented which show the potential of this
all-digital self-sensing concept.
Abstract: Complex statistical analysis of stresses in concrete
slab of the real type of rigid pavement is performed. The
computational model of the pavement is designed as a spatial (3D) model, is based on a nonlinear variant of the finite element method
that respects the structural nonlinearity, enables to model different arrangement of joints, and the entire model can be loaded by the
thermal load. Interaction of adjacent slabs in joints and contact of the slab and the subsequent layer are modeled with help of special
contact elements. Four concrete slabs separated by transverse and
longitudinal joints and the additional subgrade layers and soil to the depth of about 3m are modeled. The thickness of individual layers,
physical and mechanical properties of materials, characteristics of
joints, and the temperature of the upper and lower surface of slabs are supposed to be random variables. The modern simulation technique
Updated Latin Hypercube Sampling with 20 simulations is used for statistical analysis. As results, the estimates of basic statistics of the
principal stresses s1 and s3 in 53 points on the upper and lower surface of the slabs are obtained.
Abstract: A study was conducted to formally characterize
notebook computer performance under various environmental and
usage conditions. Software was developed to collect data from the
operating system of the computer. An experiment was conducted to
evaluate the performance parameters- variations, trends, and
correlations, as well as the extreme value they can attain in various
usage and environmental conditions. An automated software script
was written to simulate user activity. The variability of each
performance parameter was addressed by establishing the empirical
relationship between performance parameters. These equations were
presented as baseline estimates for performance parameters, which
can be used to detect system deviations from normal operation and
for prognostic assessment. The effect of environmental factors,
including different power sources, ambient temperatures, humidity,
and usage, on performance parameters of notebooks was studied.
Abstract: The motivation for adaptive modulation and coding is
to adjust the method of transmission to ensure that the maximum
efficiency is achieved over the link at all times. The receiver
estimates the channel quality and reports it back to the transmitter.
The transmitter then maps the reported quality into a link mode. This
mapping however, is not a one-to-one mapping. In this paper we
investigate a method for selecting the proper modulation scheme.
This method can dynamically adapt the mapping of the Signal-to-
Noise Ratio (SNR) into a link mode. It enables the use of the right
modulation scheme irrespective of changes in the channel conditions
by incorporating errors in the received data. We propose a Markov
model for this method, and use it to derive the average switching
thresholds and the average throughput. We show that the average
throughput of this method outperforms the conventional threshold
method.
Abstract: The aim of this paper is to emphasize and alleviate the effect of phase noise due to imperfect local oscillators on the performances of a Multi-Carrier CDMA system. After the cancellation of Common Phase Error (CPE), an iterative approach is introduced which iteratively estimates Inter-Carrier Interference (ICI) components in the frequency domain and cancels their contribution in the time domain. Simulation are conducted in order to investigate the achievable performances for several parameters, such as the spreading factor, the modulation order, the phase noise power and the transmission Signal-to-Noise Ratio.
Abstract: The problem of Small Area Estimation (SAE) is complex because of various information sources and insufficient data. In this paper, an approach for SAE is presented for decision-making at national, regional and local level. We propose an Empirical Best Linear Unbiased Predictor (EBLUP) as an estimator in order to combine several information sources to evaluate various indicators. First, we present the urban audit project and its environmental, social and economic indicators. Secondly, we propose an approach for decision making in order to estimate indicators. An application is used to validate the theoretical proposal. Finally, a decision support system is presented based on open-source environment.
Abstract: We deal with the numerical solution of time-dependent convection-diffusion-reaction equations. We combine the local projection stabilization method for the space discretization with two different time discretization schemes: the continuous Galerkin-Petrov (cGP) method and the discontinuous Galerkin (dG) method of polynomial of degree k. We establish the optimal error estimates and present numerical results which shows that the cGP(k) and dG(k)- methods are accurate of order k +1, respectively, in the whole time interval. Moreover, the cGP(k)-method is superconvergent of order 2k and dG(k)-method is of order 2k +1 at the discrete time points. Furthermore, the dependence of the results on the choice of the stabilization parameter are discussed and compared.
Abstract: The density estimates considered in this paper comprise
a base density and an adjustment component consisting of a linear
combination of orthogonal polynomials. It is shown that, in the
context of density approximation, the coefficients of the linear combination
can be determined either from a moment-matching technique
or a weighted least-squares approach. A kernel representation of
the corresponding density estimates is obtained. Additionally, two
refinements of the Kronmal-Tarter stopping criterion are proposed
for determining the degree of the polynomial adjustment. By way of
illustration, the density estimation methodology advocated herein is
applied to two data sets.
Abstract: In this paper, the C1-conforming finite element method is analyzed for a class of nonlinear fourth-order hyperbolic partial differential equation. Some a priori bounds are derived using Lyapunov functional, and existence, uniqueness and regularity for the weak solutions are proved. Optimal error estimates are derived for both semidiscrete and fully discrete schemes.
Abstract: In this paper, we consider the problem for identifying the unknown source in the Poisson equation. A modified Tikhonov regularization method is presented to deal with illposedness of the problem and error estimates are obtained with an a priori strategy and an a posteriori choice rule to find the regularization parameter. Numerical examples show that the proposed method is effective and stable.
Abstract: Data from 1731 Gentile di Puglia lambs, sired by 65 rams over a 5-year period were analyzed by a mixed model to estimate the variance components for heritability. The considered growth traits were: birth weight (BW), weight at 30 days of age (W30) and average daily gain from birth to 30 days of age (DG). Year of birth, sex of lamb, type of birth (single or twin), dam age at lambing and farm were significant sources of variation for all the considered growth traits. The average lamb weights were 3.85±0.16 kg at birth, 9.57±0.91 kg at 30 days of age and the average daily gain was 191±14 g. Estimates of heritability were 0.33±0.05, 0.41±0.06 and 0.16±0.05 respectively for the same traits. These values suggest there is a good opportunity to improve Gentile di Puglia lambs by selecting animals for growth traits.
Abstract: This work presents a fusion of Log Gabor Wavelet
(LGW) and Maximum a Posteriori (MAP) estimator as a speech
enhancement tool for acoustical background noise reduction. The
probability density function (pdf) of the speech spectral amplitude is
approximated by a Generalized Laplacian Distribution (GLD).
Compared to earlier estimators the proposed method estimates the
underlying statistical model more accurately by appropriately
choosing the model parameters of GLD. Experimental results show
that the proposed estimator yields a higher improvement in
Segmental Signal-to-Noise Ratio (S-SNR) and lower Log-Spectral
Distortion (LSD) in two different noisy environments compared to
other estimators.
Abstract: A free-trade agreement is found to increase Thailand-s
agricultural imports from New Zealand, despite the short span of
time for which the agreement has been operational. The finding is
described by autoregressive estimates that correct for possible unit
roots in the data. The agreement-s effect upon imports is also
estimated while considering an error-correction model of imports
against gross domestic product.
Abstract: Dengue disease is an infectious vector-borne viral
disease that is commonly found in tropical and sub-tropical regions,
especially in urban and semi-urban areas, around the world and
including Malaysia. There is no currently available vaccine or
chemotherapy for the prevention or treatment of dengue disease.
Therefore prevention and treatment of the disease depend on vector
surveillance and control measures. Disease risk mapping has been
recognized as an important tool in the prevention and control
strategies for diseases. The choice of statistical model used for
relative risk estimation is important as a good model will
subsequently produce a good disease risk map. Therefore, the aim of
this study is to estimate the relative risk for dengue disease based
initially on the most common statistic used in disease mapping called
Standardized Morbidity Ratio (SMR) and one of the earliest
applications of Bayesian methodology called Poisson-gamma model.
This paper begins by providing a review of the SMR method, which
we then apply to dengue data of Perak, Malaysia. We then fit an
extension of the SMR method, which is the Poisson-gamma model.
Both results are displayed and compared using graph, tables and
maps. Results of the analysis shows that the latter method gives a
better relative risk estimates compared with using the SMR. The
Poisson-gamma model has been demonstrated can overcome the
problem of SMR when there is no observed dengue cases in certain
regions. However, covariate adjustment in this model is difficult and
there is no possibility for allowing spatial correlation between risks in
adjacent areas. The drawbacks of this model have motivated many
researchers to propose other alternative methods for estimating the
risk.