Abstract: Heart sound is an acoustic signal and many techniques
used nowadays for human recognition tasks borrow speech recognition
techniques. One popular choice for feature extraction of accoustic
signals is the Mel Frequency Cepstral Coefficients (MFCC) which
maps the signal onto a non-linear Mel-Scale that mimics the human
hearing. However the Mel-Scale is almost linear in the frequency
region of heart sounds and thus should produce similar results with
the standard cepstral coefficients (CC). In this paper, MFCC is
investigated to see if it produces superior results for PCG based
human identification system compared to CC. Results show that the
MFCC system is still superior to CC despite linear filter-banks in
the lower frequency range, giving up to 95% correct recognition rate
for MFCC and 90% for CC. Further experiments show that the high
recognition rate is due to the implementation of filter-banks and not
from Mel-Scaling.
Abstract: Revolutions Applications such as telecommunications, hands-free communications, recording, etc. which need at least one microphone, the signal is usually infected by noise and echo. The important application is the speech enhancement, which is done to remove suppressed noises and echoes taken by a microphone, beside preferred speech. Accordingly, the microphone signal has to be cleaned using digital signal processing DSP tools before it is played out, transmitted, or stored. Engineers have so far tried different approaches to improving the speech by get back the desired speech signal from the noisy observations. Especially Mobile communication, so in this paper will do reconstruction of the speech signal, observed in additive background noise, using the Kalman filter technique to estimate the parameters of the Autoregressive Process (AR) in the state space model and the output speech signal obtained by the MATLAB. The accurate estimation by Kalman filter on speech would enhance and reduce the noise then compare and discuss the results between actual values and estimated values which produce the reconstructed signals.
Abstract: A property-s selling price is described as the result of
sequential bargaining between a buyer and a seller in an environment
of asymmetric information. Hedonic housing prices are estimated
based upon 17,333 records of New Zealand residential properties
sold during the years 2006 and 2007.
Abstract: In this study, the transesterification of palm oil with methanol for biodiesel production was studied by using CaO–ZnO as a heterogeneous base catalyst prepared by incipient-wetness impregnation (IWI) and co-precipitation (CP) methods. The reaction parameters considered were molar ratio of methanol to oil, amount of catalyst, reaction temperature, and reaction time. The optimum conditions–15:1 molar ratio of methanol to oil, a catalyst amount of 6 wt%, reaction temperature of 60 °C, and reaction time of 8 h–were observed. The effects of Ca loading, calcination temperature, and catalyst preparation on the catalytic performance were studied. The fresh and spent catalysts were characterized by several techniques, including XRD, TPR, and XRF.
Abstract: This paper presents a procedure for estimating VAR
using Sequential Discounting VAR (SDVAR) algorithm for online
model learning to detect fraudulent acts using the telecommunications
call detailed records (CDR). The volatility of the VAR is observed
allowing for non-linearity, outliers and change points based on the
works of [1]. This paper extends their procedure from univariate
to multivariate time series. A simulation and a case study for
detecting telecommunications fraud using CDR illustrate the use of
the algorithm in the bivariate setting.
Abstract: Motion detection is very important in image
processing. One way of detecting motion is using optical flow.
Optical flow cannot be computed locally, since only one independent
measurement is available from the image sequence at a point, while
the flow velocity has two components. A second constraint is needed.
The method used for finding the optical flow in this project is
assuming that the apparent velocity of the brightness pattern varies
smoothly almost everywhere in the image. This technique is later
used in developing software for motion detection which has the
capability to carry out four types of motion detection. The motion
detection software presented in this project also can highlight motion
region, count motion level as well as counting object numbers. Many
objects such as vehicles and human from video streams can be
recognized by applying optical flow technique.
Abstract: Agricultural residue such as oil palm fronds (OPF) is
cheap, widespread and available throughout the year. Hemicelluloses
extracted from OPF can be hydrolyzed to their monomers and used in
production of xylooligosaccharides (XOs). The objective of the
present study was to optimize the enzymatic hydrolysis process of
OPF hemicellulose by varying pH, temperature, enzyme and substrate
concentration for production of XOs. Hemicelluloses was extracted
from OPF by using 3 M potassium hydroxide (KOH) at temperature of
40°C for 4 hrs and stirred at 400 rpm. The hemicellulose was then
hydrolyzed using Trichoderma longibrachiatum xylanase at different
pH, temperature, enzyme and substrate concentration. XOs were
characterized based on reducing sugar determination. The optimum
conditions to produced XOs from OPF hemicellulose was obtained at
pH 4.6, temperature of 40°C , enzyme concentration of 2 U/mL and
2% substrate concentration. The results established the suitability of
oil palm fronds as raw material for production of XOs.
Abstract: The objective of the research was to study of foot
anthropometry of children aged 7-12 years in the South of Thailand Thirty-three dimensions were measured on 305 male and 295 female
subjects with 3 age ranges (7-12 years old). The instrumentation consists of four types of anthropometer, digital vernier caliper, digital
height gauge and measuring tape. The mean values and standard
deviations of average age, height, and weight of the male subjects were 9.52(±1.70) years, 137.80(±11.55) cm, and 37.57(±11.65) kg.
Female average age, height, and weight subjects were 9.53(±1.70) years, 137.88(±11.55) cm, and 34.90(±11.57) kg respectively. The
comparison of the 33 comparison measured anthropometric. Between
male and female subjects were sexual differences in size on women in almost all areas of significance (p
Abstract: Extended Kalman Filter (EKF) is probably the most
widely used estimation algorithm for nonlinear systems. However,
not only it has difficulties arising from linearization but also many
times it becomes numerically unstable because of computer round off
errors that occur in the process of its implementation. To overcome
linearization limitations, the unscented transformation (UT) was
developed as a method to propagate mean and covariance
information through nonlinear transformations. Kalman filter that
uses UT for calculation of the first two statistical moments is called
Unscented Kalman Filter (UKF). Square-root form of UKF (SRUKF)
developed by Rudolph van der Merwe and Eric Wan to
achieve numerical stability and guarantee positive semi-definiteness
of the Kalman filter covariances. This paper develops another
implementation of SR-UKF for sequential update measurement
equation, and also derives a new UD covariance factorization filter
for the implementation of UKF. This filter is equivalent to UKF but
is computationally more efficient.
Abstract: We present a low frequency watermarking method
adaptive to image content. The image content is analyzed and
properties of HVS are exploited to generate a visual mask of the
same size as the approximation image. Using this mask we embed the
watermark in the approximation image without degrading the image
quality. Watermark detection is performed without using the original
image. Experimental results show that the proposed watermarking
method is robust against most common image processing operations,
which can be easily implemented and usually do not degrade the
image quality.
Abstract: In this paper, a neural tree (NT) classifier having a
simple perceptron at each node is considered. A new concept for
making a balanced tree is applied in the learning algorithm of the
tree. At each node, if the perceptron classification is not accurate and
unbalanced, then it is replaced by a new perceptron. This separates
the training set in such a way that almost the equal number of patterns
fall into each of the classes. Moreover, each perceptron is trained only
for the classes which are present at respective node and ignore other
classes. Splitting nodes are employed into the neural tree architecture
to divide the training set when the current perceptron node repeats
the same classification of the parent node. A new error function based
on the depth of the tree is introduced to reduce the computational
time for the training of a perceptron. Experiments are performed to
check the efficiency and encouraging results are obtained in terms of
accuracy and computational costs.
Abstract: Majority of researches conducted on Iranian urban
development plans indicate that they have been almost unsuccessful
in terms of draft, execution and goal achievement. Lack or shortage
of essential statistics and information can be listed as an important
reason of the failure of these plans. Lack of figures and information
has turned into an obvious part of the country-s statistics officials.
This problem has made urban planner themselves to embark on
physical surveys including real estate and land pricing, population
and economic census of the city. Apart from the problems facing
urban developers, the possibility of errors is high in such surveys.
In the present article, applying the interview technique, it has
been mentioned that utilizing multipurpose cadastre system as a land
information system is essential for urban development plans in Iran.
It can minimize or even remove the failures facing urban
development plans.
Abstract: The recent global financial problem urges government
to play role in stimulating the economy due to the fact that private
sector has little ability to purchase during the recession. A concerned
question is whether the increased government spending crowds out
private consumption and whether it helps stimulate the economy. If
the government spending policy is effective; the private consumption
is expected to increase and can compensate the recent extra
government expense. In this study, the government spending is
categorized into government consumption spending and government
capital spending. The study firstly examines consumer consumption
along the line with the demand function in microeconomic theory.
Three categories of private consumption are used in the study. Those
are food consumption, non food consumption, and services
consumption. The dynamic Almost Ideal Demand System of the three
categories of the private consumption is estimated using the Vector
Error Correction Mechanism model. The estimated model indicates
the substituting effects (negative impacts) of the government
consumption spending on budget shares of private non food
consumption and of the government capital spending on budget share
of private food consumption, respectively. Nevertheless the result
does not necessarily indicate whether the negative effects of changes
in the budget shares of the non food and the food consumption means
fallen total private consumption. Microeconomic consumer demand
analysis clearly indicates changes in component structure of
aggregate expenditure in the economy as a result of the government
spending policy. The macroeconomic concept of aggregate demand
comprising consumption, investment, government spending (the
government consumption spending and the government capital
spending), export, and import are used to estimate for their
relationship using the Vector Error Correction Mechanism model.
The macroeconomic study found no effect of the government capital
spending on either the private consumption or the growth of GDP
while the government consumption spending has negative effect on
the growth of GDP. Therefore no crowding out effect of the
government spending is found on the private consumption but it is
ineffective and even inefficient expenditure as found reducing growth
of the GDP in the context of Thailand.
Abstract: In this research, CaO-ZnO catalysts (with various
Ca:Zn atomic ratios of 1:5, 1:3, 1:1, and 3:1) prepared by incipientwetness
impregnation (IWI) and co-precipitation (CP) methods were
used as a catalyst in the transesterification of palm oil with methanol
for biodiesel production. The catalysts were characterized by several
techniques, including BET method, CO2-TPD, and Hemmett
Indicator. The effects of precursor concentration, and calcination
temperature on the catalytic performance were studied under reaction
conditions of a 15:1 methanol to oil molar ratio, 6 wt% catalyst,
reaction temperature of 60°C, and reaction time of 8 h. At Ca:Zn
atomic ratio of 1:3 gave the highest FAME value owing to a basic
properties and surface area of the prepared catalyst.
Abstract: One of the most important requirements for the
operation and planning activities of an electrical utility is the
prediction of load for the next hour to several days out, known as
short term load forecasting. This paper presents the development of
an artificial neural network based short-term load forecasting model.
The model can forecast daily load profiles with a load time of one
day for next 24 hours. In this method can divide days of year with
using average temperature. Groups make according linearity rate of
curve. Ultimate forecast for each group obtain with considering
weekday and weekend. This paper investigates effects of temperature
and humidity on consuming curve. For forecasting load curve of
holidays at first forecast pick and valley and then the neural network
forecast is re-shaped with the new data. The ANN-based load models
are trained using hourly historical. Load data and daily historical
max/min temperature and humidity data. The results of testing the
system on data from Yazd utility are reported.
Abstract: Although the World Wide Web is considered the
largest source of information there exists nowadays, due to its
inherent dynamic characteristics, the task of finding useful and
qualified information can become a very frustrating experience. This
study presents a research on the information mining systems in the
Web; and proposes an implementation of these systems by means of
components that can be built using the technology of Web services.
This implies that they can encompass features offered by a services
oriented architecture (SOA) and specific components may be used by
other tools, independent of platforms or programming languages.
Hence, the main objective of this work is to provide an architecture
to Web mining systems, divided into stages, where each step is a
component that will incorporate the characteristics of SOA. The
separation of these steps was designed based upon the existing
literature. Interesting results were obtained and are shown here.
Abstract: The present paper discusses the basic concepts and the underlying principles of Multi-Agent Systems (MAS) along with an interdisciplinary exploitation of these principles. It has been found that they have been utilized for lots of research and studies on various systems spanning across diverse engineering and scientific realms showing the need of development of a proper generalized framework. Such framework has been developed for the Multi-Agent Systems and it has been generalized keeping in mind the diverse areas where they find application. All the related aspects have been categorized and a general definition has been given where ever possible.
Abstract: The energy consumption and delay in read/write
operation of conventional SRAM is investigated analytically as well
as by simulation. Explicit analytical expressions for the energy
consumption and delay in read and write operation as a function of
device parameters and supply voltage are derived. The expressions are
useful in predicting the effect of parameter changes on the energy
consumption and speed as well as in optimizing the design of
conventional SRAM. HSPICE simulation in standard 0.25μm CMOS
technology confirms precision of analytical expressions derived from
this paper.
Abstract: Stochastic modeling of network traffic is an area of
significant research activity for current and future broadband
communication networks. Multimedia traffic is statistically
characterized by a bursty variable bit rate (VBR) profile. In this
paper, we develop an improved model for uniform activity level
video sources in ATM using a doubly stochastic autoregressive
model driven by an underlying spatial point process. We then
examine a number of burstiness metrics such as the peak-to-average
ratio (PAR), the temporal autocovariance function (ACF) and the
traffic measurements histogram. We found that the former measure is
most suitable for capturing the burstiness of single scene video
traffic. In the last phase of this work, we analyse statistical
multiplexing of several constant scene video sources. This proved,
expectedly, to be advantageous with respect to reducing the
burstiness of the traffic, as long as the sources are statistically
independent. We observed that the burstiness was rapidly
diminishing, with the largest gain occuring when only around 5
sources are multiplexed. The novel model used in this paper for
characterizing uniform activity video was thus found to be an
accurate model.
Abstract: This research simulates one of the natural phenomena,
the ocean wave. Our goal is to be able to simulate the ocean wave at
real-time rate with the water surface interacting with objects. The
wave in this research is calm and smooth caused by the force of the
wind above the ocean surface. In order to make the simulation of the
wave real-time, the implementation of the GPU and the
multithreading techniques are used here. Based on the fact that the
new generation CPUs, for personal computers, have multi cores, they
are useful for the multithread. This technique utilizes more than one
core at a time. This simulation is programmed by C language with
OpenGL. To make the simulation of the wave look more realistic, we
applied an OpenGL technique called cube mapping (environmental
mapping) to make water surface reflective and more realistic.