Abstract: The recent trend in field oriented control (FOC) is towards the use of sensorless techniques that avoid the use of speed sensor and flux sensor. Sensors are replaced by estimators or observers to minimise the cost and increase the reliability. In this paper an anlyse of perfomance of a MRAS used in sensorless control of induction motors and sensitvity to machine parameters change are studied.
Abstract: The experimental thermal performance of two heat
exchangers in closed-wet cooling tower (CWCT) was investigated in
this study. The test sections are heat exchangers which have multi path
that is used as the entrance of cooling water and are consisting of
bare-type copper tubes between 15.88mm and 19.05mm. The process
fluids are the cooling water that flows from top part of heat exchanger
to bottom side in the inner side of tube, and spray water that flows
gravitational direction in the outer side of it. Air contacts its outer side
of that as it counterflows. Heat and mass transfer coefficients and
cooling capacity were calculated with variations of process fluids,
multi path and different diameter tubes to figure out the performance
of characteristics of CWCT.
The main results were summarized as follows: The results show this
experiment is reliable with values of heat and mass transfer
coefficients comparing to values of correlations. Heat and mass
transfer coefficients and cooling capacity of two paths are higher than
these with one path using 15.88 and 19.05mm tubes. Cooling capacity
per unit volume with 15.88mm tube using one and two paths are
higher than 19.05mm tube due to increase of surface area per unit
volume.
Abstract: The purpose of this study is to derive optimal shapes of
a body located in viscous flows by the finite element method using the
acoustic velocity and the four-step explicit scheme. The formulation
is based on an optimal control theory in which a performance function
of the fluid force is introduced. The performance function should be
minimized satisfying the state equation. This problem can be transformed
into the minimization problem without constraint conditions
by using the adjoint equation with adjoint variables corresponding to
the state equation. The performance function is defined by the drag
and lift forces acting on the body. The weighted gradient method
is applied as a minimization technique, the Galerkin finite element
method is used as a spatial discretization and the four-step explicit
scheme is used as a temporal discretization to solve the state equation
and the adjoint equation. As the interpolation, the orthogonal basis
bubble function for velocity and the linear function for pressure
are employed. In case that the orthogonal basis bubble function is
used, the mass matrix can be diagonalized without any artificial
centralization. The shape optimization is performed by the presented
method.
Abstract: The aim of this study was to examine the dynamics of functional composition of a non flooded Amazonian forest in response to drought stress in terms of diameter growth, recruitment and mortality. The survey was carried out in the continuous forest of the Biological dynamics of forest fragments project 90 km outside the city of Manaus, state of Amazonas Brazil. All stems >10 cm dbh where identified to species level and monitored in 18 one hectare permanent sample plots from 1981 to 2004.For statistical analysis all species where aggregated in three ecological guilds. Two distinct drought events occurred in 1983 and 1997. Results showed that more early successional species performed better than later successional ones. Response was significant for both events but for the 1997 event this was more pronounced possibly because of the fact that the event was in the middle of the dry rather than the wet period as was the 1983 one.
Abstract: School experiences, family bonding and self-concept
had always been a crucial factor in influencing all aspects of a
student-s development. The purpose of this study is to develop and to
validate a priori model of self-concept among students. The study
was tested empirically using Structural Equation Modeling (SEM)
and Confirmatory Factor Analysis (CFA) to validate the structural
model. To address these concerns, 1167 students were randomly
selected and utilized the Cognitive Psycho-Social University of
Malaya instrument (2009).Resulted demonstrated there is indirect
effect from family bonding to self-concept through school
experiences among secondary school students as a mediator. Besides
school experiences, there is a direct effect from family bonding to
self-concept and family bonding to school experiences among
students.
Abstract: Linear cryptanalysis methods are rarely used to improve the security of chaotic stream ciphers. In this paper, we apply linear cryptanalysis to a chaotic stream cipher which was designed by strictly using the basic design criterion of cryptosystem – confusion and diffusion. We show that this well-designed chaos-based stream cipher is still insecure against distinguishing attack. This distinguishing attack promotes the further improvement of the cipher.
Abstract: In this article the influence of higher frequency effects
in addition to a special damper design on the electrical behavior of a
synchronous generator main exciter machine is investigated. On the
one hand these machines are often highly stressed by harmonics from
the bridge rectifier thus facing additional eddy current losses. On the
other hand the switching may cause the excitation of dangerous
voltage peaks in resonant circuits formed by the diodes of the
rectifier and the commutation reactance of the machine. Therefore
modern rotating exciters are treated like synchronous generators
usually modeled with a second order equivalent circuit. Hence the
well known Standstill Frequency Response Test (SSFR) method is
applied to a test machine in order to determine parameters for the
simulation. With these results it is clearly shown that higher
frequencies have a strong impact on the conventional equivalent
circuit model. Because of increasing field displacement effects in the
stranded armature winding the sub-transient reactance is even smaller
than the armature leakage at high frequencies. As a matter of fact this
prevents the algorithm to find an equivalent scheme. This issue is
finally solved using Laplace transfer functions fully describing the
transient behavior at the model ports.
Abstract: Traditional principal components analysis (PCA)
techniques for face recognition are based on batch-mode training
using a pre-available image set. Real world applications require that
the training set be dynamic of evolving nature where within the
framework of continuous learning, new training images are
continuously added to the original set; this would trigger a costly
continuous re-computation of the eigen space representation via
repeating an entire batch-based training that includes the old and new
images. Incremental PCA methods allow adding new images and
updating the PCA representation. In this paper, two incremental
PCA approaches, CCIPCA and IPCA, are examined and compared.
Besides, different learning and testing strategies are proposed and
applied to the two algorithms. The results suggest that batch PCA is
inferior to both incremental approaches, and that all CCIPCAs are
practically equivalent.
Abstract: Permeability reduction induced by asphaltene
precipitation during gas injection is one of the serious problems in
the oil industry. This problem can lead to formation damage and
decrease the oil production rate. In this work, Malaysian light oil
sample has been used to investigate the effect CO2 injection and
Water Alternating Gas (WAG) injection on permeability reduction.
In this work, dynamic core flooding experiments were conducted to
study the effect of CO2 and WAG injection on the amount of
asphaltene precipitated. Core properties after displacement were
inspected for any permeability reduction to study the effect of
asphaltene precipitation on rock properties.
The results showed that WAG injection gave less asphaltene
precipitation and formation damage compared to CO2 injection. The
study suggested that WAG injection can be one of the important
factors of managing asphaltene precipitation.
Abstract: Recent research on seeds of bio-diesel plants like
Jatropha curcas, constituting 40-50% bio-crude oil indicates its
potential as one of the most promising alternatives to conventional
sources of energy. Also, limited studies on utilization of de-oiled cake
have revealed that Jatropha bio-waste has good potential to be used as
organic fertilizers produced via aerobic and anaerobic treatment.
However, their commercial exploitation has not yet been possible. The
present study aims at developing appropriate bio-processes and
formulations utilizing Jatropha seed cake as organic fertilizer, for
improving the growth of Polianthes tuberose L. (Tuberose). Pot
experiments were carried out by growing tuberose plants on soil
treated with composted formulations of Jatropha de-oiled cake, Farm
Yard Manure (FYM) and inorganic fertilizers were also blended in
soil. The treatment was carried out through soil amendment as well as
foliar spray. The growth and morphological parameters were
monitored for entire crop cycle.
The growth Length and number of leaves, spike length, rachis
length, number of bulb per plant and earliness of sprouting of bulb and
yield enhancement were comparable to that achieved under inorganic
fertilizer. Furthermore, performance of inorganic fertilizer also showed
an improvement when blended with composted bio-waste. These
findings would open new avenues for Jatropha based bio-wastes to be
composted and used as organic fertilizers for commercial floriculture.
Abstract: Cosmic showers, from their places of origin in space,
after entering earth generate secondary particles called Extensive Air
Shower (EAS). Detection and analysis of EAS and similar High
Energy Particle Showers involve a plethora of experimental setups
with certain constraints for which soft-computational tools like
Artificial Neural Network (ANN)s can be adopted. The optimality
of ANN classifiers can be enhanced further by the use of Multiple
Classifier System (MCS) and certain data - dimension reduction
techniques. This work describes the performance of certain data
dimension reduction techniques like Principal Component Analysis
(PCA), Independent Component Analysis (ICA) and Self Organizing
Map (SOM) approximators for application with an MCS formed
using Multi Layer Perceptron (MLP), Recurrent Neural Network
(RNN) and Probabilistic Neural Network (PNN). The data inputs are
obtained from an array of detectors placed in a circular arrangement
resembling a practical detector grid which have a higher dimension
and greater correlation among themselves. The PCA, ICA and SOM
blocks reduce the correlation and generate a form suitable for real
time practical applications for prediction of primary energy and
location of EAS from density values captured using detectors in a
circular grid.
Abstract: Nowadays, ontologies are the only widely accepted paradigm for the management of sharable and reusable knowledge in a way that allows its automatic interpretation. They are collaboratively created across the Web and used to index, search and annotate documents. The vast majority of the ontology based approaches, however, focus on indexing texts at document level. Recently, with the advances in ontological engineering, it became clear that information indexing can largely benefit from the use of general purpose ontologies which aid the indexing of documents at word level. This paper presents a concept indexing algorithm, which adds ontology information to words and phrases and allows full text to be searched, browsed and analyzed at different levels of abstraction. This algorithm uses a general purpose ontology, OntoRo, and an ontologically tagged corpus, OntoCorp, both developed for the purpose of this research. OntoRo and OntoCorp are used in a two-stage supervised machine learning process aimed at generating ontology tagging rules. The first experimental tests show a tagging accuracy of 78.91% which is encouraging in terms of the further improvement of the algorithm.
Abstract: The fixed partial dentures are mainly used in the frontal
part of the dental arch because of their great esthetics. There are
several factors that are associated with the stress state created in
ceramic restorations, including: thickness of ceramic layers,
mechanical properties of the materials, elastic modulus of the
supporting substrate material, direction, magnitude and frequency of
applied load, size and location of occlusal contact areas, residual
stresses induced by processing or pores, restoration-cement
interfacial defects and environmental defects. The purpose of this
study is to evaluate the capability of Polarization Sensitive Optical
Coherence Tomography (PSOCT) in detection and analysis of
possible material defects in metal-ceramic and integral ceramic fixed
partial dentures. As a conclusion, it is important to have a non
invasive method to investigate fixed partial prostheses before their
insertion in the oral cavity in order to satisfy the high stress
requirements and the esthetic function.
Abstract: This paper reports on the enhanced photoluminescence
(PL) of nanocomposites through the layered structuring of phosphor
and quantum dot (QD). Green phosphor of Sr2SiO4:Eu, red QDs of
CdSe/CdS/CdZnS/ZnS core-multishell, and thermo-curable resin
were used for this study. Two kinds of composite (layered and mixed)
were prepared, and the schemes for optical energy transfer between
QD and phosphor were suggested and investigated based on PL decay
characteristics. It was found that the layered structure is more effective
than the mixed one in the respects of PL intensity, PL decay and
thermal loss. When this layered nanocomposite (QDs on phosphor) is
used to make white light emitting diode (LED), the brightness is
increased by 37 %, and the color rendering index (CRI) value is raised
to 88.4 compared to the mixed case of 80.4.
Abstract: Discrimination between different classes of environmental
sounds is the goal of our work. The use of a sound recognition
system can offer concrete potentialities for surveillance and
security applications. The first paper contribution to this research
field is represented by a thorough investigation of the applicability
of state-of-the-art audio features in the domain of environmental
sound recognition. Additionally, a set of novel features obtained by
combining the basic parameters is introduced. The quality of the
features investigated is evaluated by a HMM-based classifier to which
a great interest was done. In fact, we propose to use a Multi-Style
training system based on HMMs: one recognizer is trained on a
database including different levels of background noises and is used
as a universal recognizer for every environment. In order to enhance
the system robustness by reducing the environmental variability, we
explore different adaptation algorithms including Maximum Likelihood
Linear Regression (MLLR), Maximum A Posteriori (MAP)
and the MAP/MLLR algorithm that combines MAP and MLLR.
Experimental evaluation shows that a rather good recognition rate
can be reached, even under important noise degradation conditions
when the system is fed by the convenient set of features.
Abstract: The influence of twist arrangement on the temperature
distribution in an annular diffuser fitted with twisted rectangular hub
is investigated. Different pitches (Y = 120 mm, 100 mm, 80 mm, and
60 mm) for the twist arrangements are simulated to be compared. The
geometry of the annular diffuser and the inlet condition for the hub
arrangements are kept constant. The result reveals that using twisted
rectangular hub insert with different pitches will force the
temperature to distribute in a circular direction. However,
temperature distribution will be enhanced with the length pitch
increases.
Abstract: Previous studies on political budget cycles (PBCs)
implicitly assume the executive has full discretion power over fiscal
policy, neglecting the role of checks and balances of the legislature.
This paper goes beyond traditional PBCs models and sheds light on
the case study of Japan, South Korea, and Taiwan over the 1988-2007
periods. Based on the results, we find no evidence of electoral impacts
on the public expenditures in South Korean and Taiwan's
congressional elections. We also noted that PBCs are found on
Taiwan-s government expenditures during our sample periods.
Furthermore, the results also show that Japan-s legislature has a
significant checks and balances on government-s expenditures.
However, empirical results show that the legislature veto player in
Taiwan neither has effect on the reduction of public expenditures, nor
has the moderating effect over Taiwan-s political budget cycles, albeit
that they are statistically insignificant.We suggest that the existence of
PBCs in Taiwan is due to a weaker systemof checks and balances. Our
conjecture is that Taiwan either has no legislative veto player or has
observed low compliance to the law during the time period examined
in our study.
Abstract: In recent years, fast neural networks for object/face detection have been introduced based on cross correlation in the frequency domain between the input matrix and the hidden weights of neural networks. In our previous papers [3,4], fast neural networks for certain code detection was introduced. It was proved in [10] that for fast neural networks to give the same correct results as conventional neural networks, both the weights of neural networks and the input matrix must be symmetric. This condition made those fast neural networks slower than conventional neural networks. Another symmetric form for the input matrix was introduced in [1-9] to speed up the operation of these fast neural networks. Here, corrections for the cross correlation equations (given in [13,15,16]) to compensate for the symmetry condition are presented. After these corrections, it is proved mathematically that the number of computation steps required for fast neural networks is less than that needed by classical neural networks. Furthermore, there is no need for converting the input data into symmetric form. Moreover, such new idea is applied to increase the speed of neural networks in case of processing complex values. Simulation results after these corrections using MATLAB confirm the theoretical computations.
Abstract: In this paper, we present a maintenance model of a
two-unit series system with economic dependence. Unit#1 which is
considered to be more expensive and more important, is subject to
condition monitoring (CM) at equidistant, discrete time epochs and
unit#2, which is not subject to CM has a general lifetime distribution.
The multivariate observation vectors obtained through condition
monitoring carry partial information about the hidden state of unit#1,
which can be in a healthy or a warning state while operating. Only the
failure state is assumed to be observable for both units. The objective
is to find an optimal opportunistic maintenance policy minimizing
the long-run expected average cost per unit time. The problem
is formulated and solved in the partially observable semi-Markov
decision process framework. An effective computational algorithm
for finding the optimal policy and the minimum average cost is
developed, illustrated by a numerical example.
Abstract: This paper presents a study on the thermodynamics
and transport properties of hot potassium carbonate aqueous system
(HPC) using electrolyte non-random two liquid, (ELECNRTL)
model. The operation conditions are varied to determine the system
liquid phase stability range at the standard and critical conditions. A
case study involving 30 wt% K2CO3, H2O standard system at
pressure of 1 bar and temperature range from 280.15 to 366.15 K has
been studied. The estimated solubility index, viscosity, water
activity, and density which obtained from the simulation showed a
good agreement with the experimental work. Furthermore, the
saturation temperature of the solution has been estimated.