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: 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: 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: 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: This paper presents a new technique for detection of
human faces within color images. The approach relies on image
segmentation based on skin color, features extracted from the two-dimensional
discrete cosine transform (DCT), and self-organizing
maps (SOM). After candidate skin regions are extracted, feature
vectors are constructed using DCT coefficients computed from those
regions. A supervised SOM training session is used to cluster feature
vectors into groups, and to assign “face" or “non-face" labels to those
clusters. Evaluation was performed using a new image database of
286 images, containing 1027 faces. After training, our detection
technique achieved a detection rate of 77.94% during subsequent
tests, with a false positive rate of 5.14%. To our knowledge, the
proposed technique is the first to combine DCT-based feature
extraction with a SOM for detecting human faces within color
images. It is also one of a few attempts to combine a feature-invariant
approach, such as color-based skin segmentation, together with
appearance-based face detection. The main advantage of the new
technique is its low computational requirements, in terms of both
processing speed and memory utilization.
Abstract: This paper presents a new adaptive DMC controller
that improves the controller performance in case of plant-model
mismatch. The new controller monitors the plant measured output,
compares it with the model output and calculates weights applied to
the controller move. Simulations show that the new controller can
help improve control performance and avoid instability in case of
severe model mismatches.
Abstract: This paper presents an integrated model that
automatically measures the change of rivers, damage area of bridge
surroundings, and change of vegetation. The proposed model is on the
basis of a neurofuzzy mechanism enhanced by SOM optimization
algorithm, and also includes three functions to deal with river imagery.
High resolution imagery from FORMOSAT-2 satellite taken before
and after the invasion period is adopted. By randomly selecting a
bridge out of 129 destroyed bridges, the recognition results show that
the average width has increased 66%. The ruined segment of the
bridge is located exactly at the most scour region. The vegetation
coverage has also reduced to nearly 90% of the original. The results
yielded from the proposed model demonstrate a pinpoint accuracy rate
at 99.94%. This study brings up a successful tool not only for
large-scale damage assessment but for precise measurement to
disasters.
Abstract: This paper aims to study decomposition behavior in
pyrolytic environment of four lignocellulosic biomass (oil palm shell,
oil palm frond, rice husk and paddy straw), and two commercial
components of biomass (pure cellulose and lignin), performed in a
thermogravimetry analyzer (TGA). The unit which consists of a
microbalance and a furnace flowed with 100 cc (STP) min-1 Nitrogen,
N2 as inert. Heating rate was set at 20⁰C min-1 and temperature
started from 50 to 900⁰C. Hydrogen gas production during the
pyrolysis was observed using Agilent Gas Chromatography Analyzer
7890A. Oil palm shell, oil palm frond, paddy straw and rice husk
were found to be reactive enough in a pyrolytic environment of up to
900°C since pyrolysis of these biomass starts at temperature as low as
200°C and maximum value of weight loss is achieved at about
500°C. Since there was not much different in the cellulose,
hemicelluloses and lignin fractions between oil palm shell, oil palm
frond, paddy straw and rice husk, the T-50 and R-50 values obtained
are almost similar. H2 productions started rapidly at this temperature
as well due to the decompositions of biomass inside the TGA.
Biomass with more lignin content such as oil palm shell was found to
have longer duration of H2 production compared to materials of high
cellulose and hemicelluloses contents.
Abstract: In this paper, we consider nested sliding mode control of SISO nonlinear systems, perturbed by bounded matched and unmatched uncertainties. The systems are assumed to be in strict-feedback form. A step wise procedure is introduced to obtain the controller. In each step, a continuous sliding mode controller is designed as virtual control law. Then the next step sliding surface is defined by using this virtual controller. These sliding surfaces are selected as nonlinear static functions of the system states. Finally in the last step, smooth static state feedback control law is determined such that the output reaches the desired set-point while the system is forced arbitrary close to the intersection of sliding surfaces and the states remain bounded.
Abstract: The present study attempted to improve the Mercury
(Hg) sorption capacity of kanuma volcanic ash soil (KVAS) by
impregnating the cupper (Cu). Impregnation was executed by 1 and
5% Cu powder and sorption characterization of optimum Hg
removing Cu impregnated KVAS was performed under different
operational conditions, contact time, solution pH, sorbent dosage and
Hg concentration using the batch operation studies. The 1% Cu
impregnated KVAS pronounced optimum improvement (79%) in
removing Hg from water compare to control. The present
investigation determined the equilibrium state of maximum Hg
adsorption at 6 h contact period. The adsorption revealed a pH
dependent response and pH 3.5 showed maximum sorption capacity
of Hg. Freundlich isotherm model is well fitted with the experimental
data than that of Langmuir isotherm. It can be concluded that the Cu
impregnation improves the Hg sorption capacity of KVAS and 1%
Cu impregnated KVAS could be employed as cost-effective
adsorbent media for treating Hg contaminated water.
Abstract: The study of piezoelectric material in the past was in
T-Domain form; however, no one has studied piezoelectric material in the S-Domain form. This paper will present the piezoelectric material in the transfer function or S-Domain model. S-Domain is a
well known mathematical model, used for analyzing the stability of the material and determining the stability limits. By using S-Domain
in testing stability of piezoelectric material, it will provide a new tool for the scientific world to study this material in various forms.
Abstract: This paper deals with the problem of thermal and
mechanical shocks, which rising during operation, mostly at
interrupted cut. Here will be solved their impact on the cutting edge
tool life, the impact of coating technology on resistance to shocks
and experimental determination of tool life in heating flame.
Resistance of removable cutting edges against thermal and
mechanical shock is an important indicator of quality as well as its
abrasion resistance. Breach of the edge or its crumble may occur due
to cyclic loading. We can observe it not only during the interrupted
cutting (milling, turning areas abandoned hole or slot), but also in
continuous cutting. This is due to the volatility of cutting force on
cutting. Frequency of the volatility in this case depends on the type
of rising chips (chip size element). For difficult-to-machine materials
such as austenitic steel particularly happened at higher cutting speeds
for the localization of plastic deformation in the shear plane and for
the inception of separate elements substantially continuous chips.
This leads to variations of cutting forces substantially greater than for
other types of steel.
Abstract: In this paper, we consider the control of time delay system
by Proportional-Integral (PI) controller. By Using the Hermite-
Biehler theorem, which is applicable to quasi-polynomials, we seek
a stability region of the controller for first order delay systems. The
essence of this work resides in the extension of this approach to
second order delay system, in the determination of its stability region
and the computation of the PI optimum parameters. We have used
the genetic algorithms to lead the complexity of the optimization
problem.
Abstract: The Neuro-Fuzzy hybridization scheme has become
of research interest in pattern classification over the past decade. The
present paper proposes a novel Modified Adaptive Fuzzy Inference
Engine (MAFIE) for pattern classification. A modified Apriori
algorithm technique is utilized to reduce a minimal set of decision
rules based on input output data sets. A TSK type fuzzy inference
system is constructed by the automatic generation of membership
functions and rules by the fuzzy c-means clustering and Apriori
algorithm technique, respectively. The generated adaptive fuzzy
inference engine is adjusted by the least-squares fit and a conjugate
gradient descent algorithm towards better performance with a
minimal set of rules. The proposed MAFIE is able to reduce the
number of rules which increases exponentially when more input
variables are involved. The performance of the proposed MAFIE is
compared with other existing applications of pattern classification
schemes using Fisher-s Iris and Wisconsin breast cancer data sets and
shown to be very competitive.
Abstract: This paper explores the scalability issues associated
with solving the Named Entity Recognition (NER) problem using
Support Vector Machines (SVM) and high-dimensional features. The
performance results of a set of experiments conducted using binary
and multi-class SVM with increasing training data sizes are
examined. The NER domain chosen for these experiments is the
biomedical publications domain, especially selected due to its
importance and inherent challenges. A simple machine learning
approach is used that eliminates prior language knowledge such as
part-of-speech or noun phrase tagging thereby allowing for its
applicability across languages. No domain-specific knowledge is
included. The accuracy measures achieved are comparable to those
obtained using more complex approaches, which constitutes a
motivation to investigate ways to improve the scalability of multiclass
SVM in order to make the solution more practical and useable.
Improving training time of multi-class SVM would make support
vector machines a more viable and practical machine learning
solution for real-world problems with large datasets. An initial
prototype results in great improvement of the training time at the
expense of memory requirements.
Abstract: In this paper, the application of sliding-mode control to a permanent-magnet synchronous motor (PMSM) is presented. The control design is based on a generic mathematical model of the motor. Some dynamics of the motor and of the power amplification stage remain unmodelled. This model uncertainty is estimated in realtime. The estimation is based on the differentiation of measured signals using the ideas of robust exact differentiator (RED). The control law is implemented on an industrial servo drive. Simulations and experimental results are presented and compared to the same control strategy without uncertainty estimation. It turns out that the proposed concept is superior to the same control strategy without uncertainty estimation especially in the case of non-smooth reference signals.
Abstract: Mostly the real life signals are time varying in nature. For proper characterization of such signals, time-frequency representation is required. The STFT (short-time Fourier transform) is a classical tool used for this purpose. The limitation of the STFT is its fixed time-frequency resolution. Thus, an enhanced version of the STFT, which is based on the cross-level sampling, is devised. It can adapt the sampling frequency and the window function length by following the input signal local variations. Therefore, it provides an adaptive resolution time-frequency representation of the input. The computational complexity of the proposed STFT is deduced and compared to the classical one. The results show a significant gain of the computational efficiency and hence of the processing power. The processing error of the proposed technique is also discussed.
Abstract: This study investigates the in-situ regeneration of deactivated Pt-Pd catalyst in a laboratory-scale catalysis reactor. Different regeneration conditions are tested and the activity and characteristics of regenerated catalysts are analyzed. Experimental results show that the conversion efficiencies of C3H6 by different regenerated Pt-Pd catalysts were significantly improved from 77%, 55% and 41% to 86%, 98% and 99%, respectively. The best regeneration conditions was 52ppm ozone, 500oC, and 10min. Regeneration temperature has more influences than ozone concentration and regeneration time. With the comparisons of characteristics of deactivated catalyst and regenerated catalyst, the major poison species (carbon, metals, chloride, and sulfate) on the spent catalysts can be effectively removed by ozone regeneration.
Abstract: Fecal sterol has been proposed as a chemical indicator
of human fecal pollution even when fecal coliform populations have
diminished due to water chlorination or toxic effects of industrial
effluents. This paper describes an improved derivatization procedure
for simultaneous determination of four fecal sterols including
coprostanol, epicholestanol, cholesterol and cholestanol using gas
chromatography-mass spectrometry (GC-MS), via optimization study
on silylation procedures using N-O-bis
(trimethylsilyl)-trifluoroacetamide (BSTFA), and
N-(tert-butyldimethylsilyl)-N-methyltrifluoroacetamide
(MTBSTFA), which lead to the formation of trimethylsilyl (TMS) and
tert-butyldimethylsilyl (TBS) derivatives, respectively. Two
derivatization processes of injection-port derivatization and water bath
derivatization (60 oC, 1h) were inspected and compared. Furthermore,
the methylation procedure at 25 oC for 2h with
trimethylsilydiazomethane (TMSD) for fecal sterols analysis was also
studied. It was found that most of TMS derivatives demonstrated the
highest sensitivities, followed by methylated derivatives. For BSTFA
or MTBSTFA derivatization processes, the simple injection-port
derivatization process could achieve the same efficiency as that in the
tedious water bath derivatization procedure.
Abstract: For the past thirty years the Malaysian economy has been said to contribute well to the progress of the nations. However, the intensification of global economy activity and the extensive use of Information Communication Technologies (ICTs) in recent years are challenging government-s effort to further develop Malaysian society. The competition posed by the low wage economies such as China and Vietnam have made the government realise the importance of engaging in high-skill and high technology industries. It is hoped this will be the basis of attracting more foreign direct investment (FDI) in order to help the country to compete in globalised world. Using Vision 2020 as it targeted vision, the government has decided to engage in the use of ICTs and introduce many policies pertaining to it. Mainly based on the secondary analysis approach, the findings show that policy pertaining to ICTs in Malaysia contributes to economic growth, but the consequences of this have resulted in greater division within society. Although some of the divisions such as gender and ethnicity are narrowing down, the gap in important areas such as regions and class differences is becoming wider. The widespread use of ICTs might contribute to the further establishment of democracy in Malaysia, but the increasing number of foreign entities such as FDI and foreign workers, cultural hybridisation and to some extent cultural domination are contributing to neocolonialism in Malaysia. This has obvious consequences for the government-s effort to create a Malaysian national identity. An important finding of this work is that there are contradictions within ICT policy between the effort to develop the economy and society.