Abstract: Currently, many types of no-reversible compressed
sound source, represented by MP3 (MPEG Audio Layer-3) are
popular in the world and they are widely used to make the music file
size smaller. The sound data created in this way has less information as
compared to pre-compressed data. The objective of this study is by
analyzing EEG to determine if people can recognize such difference as
differences in sound. A measurement system that can measure and
analyze EEG when a subject listens to music were experimentally
developed. And ten subjects were studied with this system. In this
experiment, a WAVE formatted music data and a MP3 compressed
music data that is made from the WAVE formatted data were
prepared. Each subject was made to hear these music sources at the
same volume. From the results of this experiment, clear differences
were confirmed between two wound sources.
Abstract: The conventional GA combined with a local search
algorithm, such as the 2-OPT, forms a hybrid genetic algorithm(HGA)
for the traveling salesman problem (TSP). However, the geometric
properties which are problem specific knowledge can be used to
improve the search process of the HGA. Some tour segments (edges)
of TSPs are fine while some maybe too long to appear in a short tour.
This knowledge could constrain GAs to work out with fine tour
segments without considering long tour segments as often.
Consequently, a new algorithm is proposed, called intelligent-OPT
hybrid genetic algorithm (IOHGA), to improve the GA and the 2-OPT
algorithm in order to reduce the search time for the optimal solution.
Based on the geometric properties, all the tour segments are assigned
2-level priorities to distinguish between good and bad genes. A
simulation study was conducted to evaluate the performance of the
IOHGA. The experimental results indicate that in general the IOHGA
could obtain near-optimal solutions with less time and better accuracy
than the hybrid genetic algorithm with simulated annealing algorithm
(HGA(SA)).
Abstract: Fossil fuels are the major source to meet the world
energy requirements but its rapidly diminishing rate and adverse
effects on our ecological system are of major concern. Renewable
energy utilization is the need of time to meet the future challenges.
Ocean energy is the one of these promising energy resources. Threefourths
of the earth-s surface is covered by the oceans. This enormous
energy resource is contained in the oceans- waters, the air above the
oceans, and the land beneath them. The renewable energy source of
ocean mainly is contained in waves, ocean current and offshore solar
energy. Very fewer efforts have been made to harness this reliable
and predictable resource. Harnessing of ocean energy needs detail
knowledge of underlying mathematical governing equation and their
analysis. With the advent of extra ordinary computational resources
it is now possible to predict the wave climatology in lab simulation.
Several techniques have been developed mostly stem from numerical
analysis of Navier Stokes equations. This paper presents a brief over
view of such mathematical model and tools to understand and
analyze the wave climatology. Models of 1st, 2nd and 3rd generations
have been developed to estimate the wave characteristics to assess the
power potential. A brief overview of available wave energy
technologies is also given. A novel concept of on-shore wave energy
extraction method is also presented at the end. The concept is based
upon total energy conservation, where energy of wave is transferred
to the flexible converter to increase its kinetic energy. Squeezing
action by the external pressure on the converter body results in
increase velocities at discharge section. High velocity head then can
be used for energy storage or for direct utility of power generation.
This converter utilizes the both potential and kinetic energy of the
waves and designed for on-shore or near-shore application. Increased
wave height at the shore due to shoaling effects increases the
potential energy of the waves which is converted to renewable
energy. This approach will result in economic wave energy
converter due to near shore installation and more dense waves due to
shoaling. Method will be more efficient because of tapping both
potential and kinetic energy of the waves.
Abstract: Text Mining is around applying knowledge discovery
techniques to unstructured text is termed knowledge discovery in text
(KDT), or Text data mining or Text Mining. In decision tree
approach is most useful in classification problem. With this
technique, tree is constructed to model the classification process.
There are two basic steps in the technique: building the tree and
applying the tree to the database. This paper describes a proposed
C5.0 classifier that performs rulesets, cross validation and boosting
for original C5.0 in order to reduce the optimization of error ratio.
The feasibility and the benefits of the proposed approach are
demonstrated by means of medial data set like hypothyroid. It is
shown that, the performance of a classifier on the training cases from
which it was constructed gives a poor estimate by sampling or using a
separate test file, either way, the classifier is evaluated on cases that
were not used to build and evaluate the classifier are both are large. If
the cases in hypothyroid.data and hypothyroid.test were to be
shuffled and divided into a new 2772 case training set and a 1000
case test set, C5.0 might construct a different classifier with a lower
or higher error rate on the test cases. An important feature of see5 is
its ability to classifiers called rulesets. The ruleset has an error rate
0.5 % on the test cases. The standard errors of the means provide an
estimate of the variability of results. One way to get a more reliable
estimate of predictive is by f-fold –cross- validation. The error rate of
a classifier produced from all the cases is estimated as the ratio of the
total number of errors on the hold-out cases to the total number of
cases. The Boost option with x trials instructs See5 to construct up to
x classifiers in this manner. Trials over numerous datasets, large and
small, show that on average 10-classifier boosting reduces the error
rate for test cases by about 25%.
Abstract: In order to meet environmental norms, Indian fuel
policy aims at producing ultra low sulphur diesel (ULSD) in near
future. A catalyst for meeting such requirements has been developed
and kinetics of this catalytic process is being looked into. In the
present investigations, effect of mass transfer on kinetics of ultra deep
hydrodesulphurization (UDHDS) to produce ULSD has been studied
to determine intrinsic kinetics over a pre-sulphided catalyst.
Experiments have been carried out in a continuous flow micro reactor
operated in the temperature range of 330 to 3600C, whsv of 1 hr-1 at a
pressure of 35 bar, and its parameters estimated. Based on the derived
rate expression and estimated parameters optimum operation range
has been determined for this UDHDS catalyst to obtain ULSD
product.
Abstract: Modularized design approach can facilitate the
modeling of complex systems and support behavior analysis and
simulation in an iterative and thus complex engineering process, by
using encapsulated submodels of components and of their interfaces.
Therefore it can improve the design efficiency and simplify the
solving complicated problem. Multi-drivers off-road vehicle is
comparatively complicated. Driving-line is an important core part to a
vehicle; it has a significant contribution to the performance of a
vehicle. Multi-driver off-road vehicles have complex driving-line, so
its performance is heavily dependent on the driving-line. A typical
off-road vehicle-s driving-line system consists of torque converter,
transmission, transfer case and driving-axles, which transfer the
power, generated by the engine and distribute it effectively to the
driving wheels according to the road condition. According to its main
function, this paper puts forward a modularized approach for
designing and evaluation of vehicle-s driving-line. It can be used to
effectively estimate the performance of driving-line during concept
design stage. Through appropriate analysis and assessment method, an
optimal design can be reached. This method has been applied to the
practical vehicle design, it can improve the design efficiency and is
convenient to assess and validate the performance of a vehicle,
especially of multi-drivers off-road vehicle.
Abstract: The aim of this paper is to investigate the
performance of the developed two point block method designed for
two processors for solving directly non stiff large systems of higher
order ordinary differential equations (ODEs). The method calculates
the numerical solution at two points simultaneously and produces
two new equally spaced solution values within a block and it is
possible to assign the computational tasks at each time step to a
single processor. The algorithm of the method was developed in C
language and the parallel computation was done on a parallel shared
memory environment. Numerical results are given to compare the
efficiency of the developed method to the sequential timing. For
large problems, the parallel implementation produced 1.95 speed-up
and 98% efficiency for the two processors.
Abstract: Iran is one of the greatest producers of date in the
world. However due to lack of information about its viscoelastic
properties, much of the production downgraded during harvesting
and postharvesting processes. In this study the effect of temperature
and moisture content of product were investigated on stress
relaxation characteristics. Therefore, the freshly harvested date
(kabkab) at tamar stage were put in controlled environment chamber
to obtain different temperature levels (25, 35, 45, and 55 0C) and
moisture contents (8.5, 8.7, 9.2, 15.3, 20, 32.2 %d.b.). A texture
analyzer TAXT2 (Stable Microsystems, UK) was used to apply
uniaxial compression tests. A chamber capable to control temperature
was designed and fabricated around the plunger of texture analyzer to
control the temperature during the experiment. As a new approach a
CCD camera (A4tech, 30 fps) was mounted on a cylindrical glass
probe to scan and record contact area between date and disk.
Afterwards, pictures were analyzed using image processing toolbox
of Matlab software. Individual date fruit was uniaxially compressed
at speed of 1 mm/s. The constant strain of 30% of thickness of date
was applied to the horizontally oriented fruit. To select a suitable
model for describing stress relaxation of date, experimental data were
fitted with three famous stress relaxation models including the
generalized Maxwell, Nussinovitch, and Pelege. The constant in
mentioned model were determined and correlated with temperature
and moisture content of product using non-linear regression analysis.
It was found that Generalized Maxwell and Nussinovitch models
appropriately describe viscoelastic characteristics of date fruits as
compared to Peleg mode.
Abstract: The ideal sinc filter, ignoring the noise statistics, is often
applied for generating an arbitrary sample of a bandlimited signal by
using the uniformly sampled data. In this article, an optimal interpolator is proposed; it reaches a minimum mean square error (MMSE)
at its output in the presence of noise. The resulting interpolator is
thus a Wiener filter, and both the optimal infinite impulse response
(IIR) and finite impulse response (FIR) filters are presented. The
mean square errors (MSE-s) for the interpolator of different length
impulse responses are obtained by computer simulations; it shows that
the MSE-s of the proposed interpolators with a reasonable length are
improved about 0.4 dB under flat power spectra in noisy environment with signal-to-noise power ratio (SNR) equal 10 dB. As expected,
the results also demonstrate the improvements for the MSE-s with various fractional delays of the optimal interpolator against the ideal
sinc filter under a fixed length impulse response.
Abstract: Dried tomato peel (DTP) was tested in vivo (n=10) in 42 week-old laying hens at rates of 0, 40, 70, 100 and 130g/kg DM feed. Laying hens were fed in group 120 g DM/day/animal for 26 days. After 21 days, feed intake was not affected after DTP incorporation (97% of the offered feed in the five groups). Laying rate was not significantly different after DTP incorporation at 4 and 10% from the control group. Egg yolk resulting from DTP-enriched diets, contained lower amounts of cholesterol (14 to 17mg/g) and triglyceride (188mg/g) compared to the control group (22 and 241 mg/g, respectively) (P
Abstract: In this paper, we investigate a blind channel estimation method for Multi-carrier CDMA systems that use a subspace decomposition technique. This technique exploits the orthogonality property between the noise subspace and the received user codes to obtain channel of each user. In the past we used Singular Value Decomposition (SVD) technique but SVD have most computational complexity so in this paper use a new algorithm called URV Decomposition, which serve as an intermediary between the QR decomposition and SVD, replaced in SVD technique to track the noise space of the received data. Because of the URV decomposition has almost the same estimation performance as the SVD, but has less computational complexity.
Abstract: In this paper, based on the past project cost and time
performance, a model for forecasting project cost performance is
developed. This study presents a probabilistic project control concept
to assure an acceptable forecast of project cost performance. In this
concept project activities are classified into sub-groups entitled
control accounts. Then obtain the Stochastic S-Curve (SS-Curve), for
each sub-group and the project SS-Curve is obtained by summing
sub-groups- SS-Curves. In this model, project cost uncertainties are
considered through Beta distribution functions of the project
activities costs required to complete the project at every selected time
sections through project accomplishment, which are extracted from a
variety of sources. Based on this model, after a percentage of the
project progress, the project performance is measured via Earned
Value Management to adjust the primary cost probability distribution
functions. Then, accordingly the future project cost performance is
predicted by using the Monte-Carlo simulation method.
Abstract: Earthmoving operations are a major part of many
construction projects. Because of the complexity and fast-changing
environment of such operations, the planning and estimating are
crucial on both planning and operational levels. This paper presents
the framework ofa microscopic discrete-event simulation system for
modeling earthmoving operations and conducting productivity
estimations on an operational level.A prototype has been developed
to demonstrate the applicability of the proposed framework, and this
simulation system is presented via a case study based on an actual
earthmoving project. The case study shows that the proposed
simulation model is capable of evaluating alternative operating
strategies and resource utilization at a very detailed level.
Abstract: Rotation or tilt present in an image capture by digital
means can be detected and corrected using Artificial Neural Network
(ANN) for application with a Face Recognition System (FRS). Principal
Component Analysis (PCA) features of faces at different angles
are used to train an ANN which detects the rotation for an input image
and corrected using a set of operations implemented using another
system based on ANN. The work also deals with the recognition
of human faces with features from the foreheads, eyes, nose and
mouths as decision support entities of the system configured using
a Generalized Feed Forward Artificial Neural Network (GFFANN).
These features are combined to provide a reinforced decision for
verification of a person-s identity despite illumination variations. The
complete system performing facial image rotation detection, correction
and recognition using re-enforced decision support provides a
success rate in the higher 90s.
Abstract: Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.
Abstract: The objective this study was to characterize and
develop anthropomorphic liver phantoms in tomography hepatic
procedures for quality control and improvement professionals in
nuclear medicine. For the conformation of the anthropomorphic
phantom was used in plaster and acrylic. We constructed three
phantoms representing processes with liver cirrhosis. The phantoms
were filled with 99mTc diluted with water to obtain the scintigraphic
images. Tomography images were analyzed anterior and posterior
phantom representing a body with a greater degree cirrhotic. It was
noted that the phantoms allow the acquisition of images similar to
real liver with cirrhosis. Simulations of hemangiomas may contribute
to continued professional education of nuclear medicine, on the
question of image acquisition, allowing of the study parameters such
of the matrix, energy window and count statistics.
Abstract: Qk
n has been shown as an alternative to the hypercube
family. For any even integer k ≥ 4 and any integer n ≥ 2, Qk
n is
a bipartite graph. In this paper, we will prove that given any pair of
vertices, w and b, from different partite sets of Qk
n, there exist 2n
internally disjoint paths between w and b, denoted by {Pi | 0 ≤ i ≤ 2n-1}, such that 2n-1
i=0 Pi covers all vertices of Qk
n. The result is
optimal since each vertex of Qk
n has exactly 2n neighbors.
Abstract: Lean manufacturing is a production philosophy made
popular by Toyota Motor Corporation (TMC). It is globally known as
the Toyota Production System (TPS) and has the ultimate aim of
reducing cost by thoroughly eliminating wastes or muda. TPS
embraces the Just-in-time (JIT) manufacturing; achieving cost
reduction through lead time reduction. JIT manufacturing can be
achieved by implementing Pull system in the production.
Furthermore, TPS aims to improve productivity and creating
continuous flow in the production by arranging the machines and
processes in cellular configurations. This is called as Cellular
Manufacturing Systems (CMS). This paper studies on integrating the
CMS with the Pull system to establish a Big Island-Pull system
production for High Mix Low Volume (HMLV) products in an
automotive component industry. The paper will use the build-in JIT
system steps adapted from TMC to create the Pull system production
and also create a shojinka line which, according to takt time, has the
flexibility to adapt to demand changes simply by adding and taking
out manpower. This will lead to optimization in production.
Abstract: Recently research on human wayfinding has focused
mainly on mental representations rather than processes of
wayfinding. The objective of this paper is to demonstrate the
rationality behind applying multi-agent simulation paradigm to the
modeling of rescuer team wayfinding in order to develop
computational theory of perceptual wayfinding in crisis situations
using image schemata and affordances, which explains how people
find a specific destination in an unfamiliar building such as a
hospital. The hypothesis of this paper is that successful navigation is
possible if the agents are able to make the correct decision through
well-defined cues in critical cases, so the design of the building
signage is evaluated through the multi-agent-based simulation. In
addition, a special case of wayfinding in a building, finding one-s
way through three hospitals, is used to demonstrate the model.
Thereby, total rescue time for rescue operation during building fire is
computed. This paper discuses the computed rescue time for various
signage localization and provides experimental result for
optimization of building signage design. Therefore the most
appropriate signage design resulted in the shortest total rescue time in
various situations.
Abstract: In this paper, a new approach is introduced to solve
Blasius equation using parameter identification of a nonlinear
function which is used as approximation function. Bees Algorithm
(BA) is applied in order to find the adjustable parameters of
approximation function regarding minimizing a fitness function
including these parameters (i.e. adjustable parameters). These
parameters are determined how the approximation function has to
satisfy the boundary conditions. In order to demonstrate the
presented method, the obtained results are compared with another
numerical method. Present method can be easily extended to solve a
wide range of problems.