Abstract: Functionalities and control behavior are both primary
requirements in design of a complex system. Automata theory plays
an important role in modeling behavior of a system. Z is an ideal
notation which is used for describing state space of a system and then
defining operations over it. Consequently, an integration of automata
and Z will be an effective tool for increasing modeling power for a
complex system. Further, nondeterministic finite automata (NFA)
may have different implementations and therefore it is needed to
verify the transformation from diagrams to a code. If we describe
formal specification of an NFA before implementing it, then
confidence over transformation can be increased. In this paper, we
have given a procedure for integrating NFA and Z. Complement of a
special type of NFA is defined. Then union of two NFAs is
formalized after defining their complements. Finally, formal
construction of intersection of NFAs is described. The specification
of this relationship is analyzed and validated using Z/EVES tool.
Abstract: There have been numerous implementations of
security system using biometric, especially for identification and
verification cases. An example of pattern used in biometric is the iris
pattern in human eye. The iris pattern is considered unique for each
person. The use of iris pattern poses problems in encoding the human
iris.
In this research, an efficient iris recognition method is proposed.
In the proposed method the iris segmentation is based on the
observation that the pupil has lower intensity than the iris, and the
iris has lower intensity than the sclera. By detecting the boundary
between the pupil and the iris and the boundary between the iris and
the sclera, the iris area can be separated from pupil and sclera. A step
is taken to reduce the effect of eyelashes and specular reflection of
pupil. Then the four levels Coiflet wavelet transform is applied to the
extracted iris image. The modified Hamming distance is employed to
measure the similarity between two irises.
This research yields the identification success rate of 84.25% for
the CASIA version 1.0 database. The method gives an accuracy of
77.78% for the left eyes of MMU 1 database and 86.67% for the
right eyes. The time required for the encoding process, from the
segmentation until the iris code is generated, is 0.7096 seconds.
These results show that the accuracy and speed of the method is
better than many other methods.
Abstract: This research project aims to investigate difference in
relative rates concerning phosphoryl transfer relevant to biological
catalysis of DNA and RNA in the pH-independent reactions.
Activated Models of DNA and RNA for alkyl-aryl phosphate diesters
(with 4-nitrophenyl as a good leaving group) have successfully been
prepared to gather kinetic parameters. Eyring plots for the pH–
independent hydrolysis of 1 and 2 were established at different
temperatures in the range 100–160 °C. These measurements have
been used to provide a better estimate for the difference in relative
rates between the reactivity of DNA and RNA cleavage. Eyring plot
gave an extrapolated rate of kH2O = 1 × 10-10 s -1 for 1 (RNA model)
and 2 (DNA model) at 25°C. Comparing the reactivity of RNA
model and DNA model shows that the difference in relative rates in
the pH-independent reactions is surprisingly very similar at 25°. This
allows us to obtain chemical insights into how biological catalysts
such as enzymes may have evolved to perform their current
functions.
Abstract: Phase locked loops in 10 Gb/s and faster data links are
low phase noise devices. Characterization of their phase jitter
transfer functions is difficult because the intrinsic noise of the PLLs
is comparable to the phase noise of the reference clock signal. The
problem is solved by using a linear model to account for the intrinsic
noise. This study also introduces a novel technique for measuring the
transfer function. It involves the use of the reference clock as a
source of wideband excitation, in contrast to the commonly used
sinusoidal excitations at discrete frequencies. The data reported here
include the intrinsic noise of a PLL for 10 Gb/s links and the jitter
transfer function of a PLL for 12.8 Gb/s links. The measured transfer
function suggests that the PLL responded like a second order linear
system to a low noise reference clock.
Abstract: In this study, the problem of discriminating between interictal epileptic and non- epileptic pathological EEG cases, which present episodic loss of consciousness, investigated. We verify the accuracy of the feature extraction method of autocross-correlated coefficients which extracted and studied in previous study. For this purpose we used in one hand a suitable constructed artificial supervised LVQ1 neural network and in other a cross-correlation technique. To enforce the above verification we used a statistical procedure which based on a chi- square control. The classification and the statistical results showed that the proposed feature extraction is a significant accurate method for diagnostic discrimination cases between interictal and non-interictal EEG events and specifically the classification procedure showed that the LVQ neural method is superior than the cross-correlation one.
Abstract: In order to achieve competitive advantage and better
performance of firm, supply chain management (SCM) strategy
should support and drive forward business strategy. It means that
supply chain should be aligned with business strategy, at the same
time supply chain (SC) managers need to use appropriate information
system (IS) solution to support their strategy, which would lead to
stay competitive. There are different kinds of IS strategies which
enable managers to meet the SC requirement by selecting the best IS
strategy. Therefore, it is important to align IS strategies and practices
with SC strategies and practices, which could help us to plan for an
IS application that supports and enhances a SCMS. In this study,
aligning IS with SC in strategy level is considered. The main aim of
this paper is to align the various IS strategies with SCM strategies
and demonstrate their impact on SC and firm performance.
Abstract: The purpose of this research aims to discover the
knowledge for analysis student motivation behavior on e-Learning
based on Data Mining Techniques, in case of the Information
Technology for Communication and Learning Course at Suan
Sunandha Rajabhat University. The data mining techniques was
applied in this research including association rules, classification
techniques. The results showed that using data mining technique can
indicate the important variables that influence the student motivation
behavior on e-Learning.
Abstract: Due to its capability to resist jamming signals, chirp
spread spectrum (CSS) technique has attracted much attention in
the area of wireless communications. However, there has been little
rigorous analysis for the performance of the CSS communication
system in jamming environments. In this paper, we present analytic
results on the performance of a CSS system by deriving symbol
error rate (SER) expressions for a CSS M-ary phase shift keying
(MPSK) system in the presence of broadband and tone jamming
signals, respectively. The numerical results show that the empirical
SER closely agrees with the analytic result.
Abstract: The growing interest on national heritage
preservation has led to intensive efforts on digital documentation of
cultural heritage knowledge. Encapsulated within this effort is the
focus on ontology development that will help facilitate the
organization and retrieval of the knowledge. Ontologies surrounding
cultural heritage domain are related to archives, museum and library
information such as archaeology, artifacts, paintings, etc. The growth
in number and size of ontologies indicates the well acceptance of its
semantic enrichment in many emerging applications. Nowadays,
there are many heritage information systems available for access.
Among others is community-based e-museum designed to support the
digital cultural heritage preservation. This work extends previous
effort of developing the Traditional Malay Textile (TMT) Knowledge
Model where the model is designed with the intention of auxiliary
mapping with CIDOC CRM. Due to its internal constraints, the
model needs to be transformed in advance. This paper addresses the
issue by reviewing the previous harmonization works with CIDOC
CRM as exemplars in refining the facets in the model particularly
involving TMT-Artifact class. The result is an extensible model
which could lead to a common view for automated mapping with
CIDOC CRM. Hence, it promotes integration and exchange of
textile information especially batik-related between communities in
e-museum applications.
Abstract: This paper presents a new method for estimating the nonstationary
noise power spectral density given a noisy signal. The
method is based on averaging the noisy speech power spectrum using
time and frequency dependent smoothing factors. These factors are
adjusted based on signal-presence probability in individual frequency
bins. Signal presence is determined by computing the ratio of the
noisy speech power spectrum to its local minimum, which is updated
continuously by averaging past values of the noisy speech power
spectra with a look-ahead factor. This method adapts very quickly to
highly non-stationary noise environments. The proposed method
achieves significant improvements over a system that uses voice
activity detector (VAD) in noise estimation.
Abstract: The study aims to investigate the impact on board and
audit committee characteristics and firm performance before and
after the revision of MCCG (2007) on GLCs over the period 2005-2010. We used Return on Assets (ROA) as a proxy for firm performance. The data consists of two groups; data collected before
and after the amendments of MCCG (2007). Findings show that
boards of directors with accounting / finance qualifications (BEXP)
are statistically significant with performance for period before the amendments. As for audit committee members with accounting or
finance qualifications (ACEXP), correlation results indicate a
negative association and non-significant results for the years before
amendments. However, the years after the amendments show
positive relationship with highly significant correlations (1%) to ROA. This indicates that the amendments of MCCG 2007 on the
audit committee members- literacy in accounting have impacted the governance structures and performance of GLCs.
Abstract: In aircraft applications, according to the nature of
electrical equipment its location may be in unpressurized area or very
close to the engine; thus, the environmental conditions may change
from atmospheric pressure to less than 100 mbar, and the temperature
may be higher than the ambient one as in most real working
conditions of electrical equipment. Then, the classical Paschen curve
has to be replotted since these parameters may affect the discharge
ignition voltage. In this paper, we firstly investigate the domain of
validity of two corrective expressions on the Paschen-s law found in
the literature, in case of changing the air environment and known as
Peek and Dunbar corrections. Results show that these corrections are
no longer valid for combined variation of temperature and pressure.
After that, a new empirical expression for breakdown voltage is
proposed and is validated in the case of combined variations of
temperature and pressure.
Abstract: This paper presents performance analysis of the
Evolutionary Programming-Artificial Neural Network (EPANN)
based technique to optimize the architecture and training parameters
of a one-hidden layer feedforward ANN model for the prediction of
energy output from a grid connected photovoltaic system. The ANN
utilizes solar radiation and ambient temperature as its inputs while the
output is the total watt-hour energy produced from the grid-connected
PV system. EP is used to optimize the regression performance of the
ANN model by determining the optimum values for the number of
nodes in the hidden layer as well as the optimal momentum rate and
learning rate for the training. The EPANN model is tested using two
types of transfer function for the hidden layer, namely the tangent
sigmoid and logarithmic sigmoid. The best transfer function, neural
topology and learning parameters were selected based on the highest
regression performance obtained during the ANN training and testing
process. It is observed that the best transfer function configuration for
the prediction model is [logarithmic sigmoid, purely linear].
Abstract: This paper has two main ideas. Firstly, it describes Evans and Wurster-s concepts “the trade-off between reach and richness", and relates them to the impact of technology on the virtual markets. Authors Evans and Wurster see the transfer of information as a 'trade'off between richness and reach-. Reach refers to the number of people who share particular information, with Richness ['Rich'] being a more complex concept combining: bandwidth, customization, interactivity, reliability, security and currency. Traditional shopping limits the number of shops the shopper is able to visit due to time and other cost constraints; the time spent traveling consequently leaves the shopper with less time to evaluate the product. The paper concludes that although the Web provides Reach, offering Richness and the sense of community required for creating and sustaining relationships with potential clients could be difficult.
Abstract: Data gathering is an essential operation in wireless
sensor network applications. So it requires energy efficiency
techniques to increase the lifetime of the network. Similarly,
clustering is also an effective technique to improve the energy
efficiency and network lifetime of wireless sensor networks. In this
paper, an energy efficient cluster formation protocol is proposed with
the objective of achieving low energy dissipation and latency without
sacrificing application specific quality. The objective is achieved by
applying randomized, adaptive, self-configuring cluster formation
and localized control for data transfers. It involves application -
specific data processing, such as data aggregation or compression.
The cluster formation algorithm allows each node to make
independent decisions, so as to generate good clusters as the end.
Simulation results show that the proposed protocol utilizes minimum
energy and latency for cluster formation, there by reducing the
overhead of the protocol.
Abstract: In elliptic curve theory, number of rational points on
elliptic curves and determination of these points is a fairly important
problem. Let p be a prime and Fp be a finite field and k ∈ Fp. It
is well known that which points the curve y2 = x3 + kx has and
the number of rational points of on Fp. Consider the circle family
x2 + y2 = r2. It can be interesting to determine common points of
these two curve families and to find the number of these common
points. In this work we study this problem.
Abstract: Drought is one of the most damaging climate-related
hazards, it is generally considered as a prolonged absence of
precipitation. This normal and recurring climate phenomenon had
plagued civilization throughout history because of the negative
impacts on economical, environmental and social sectors. Drought
characteristics are thus recognized as important factors in water
resources planning and management. The purpose of this study is to
detect the changes in drought frequency, persistence and severity
in the Ruhr river basin. The frequency of drought events was
calculated using the Standardized Precipitation Index (SPI). Used
data are daily precipitation records from seven meteorological
stations covering the period 1961-2007. The main benefit of the
application of this index is its versatility, only rainfall data is required
to deliver five major dimensions of a drought : duration, intensity,
severity, magnitude, and frequency. Furthermore, drought can be
calculated in different time steps. In this study SPI was calculated for
1, 3, 6, 9, 12, and 24 months. Several drought events were detected
in the covered period, these events contain mild, moderate and severe
droughts. Also positive and negative trends in the SPI values were
observed.
Abstract: In order to characterize the soy protein hydrolysate obtained in this study, gel chromatography on Sephadex G-25 was used to perform the separation of the peptide mixture and electrophoresis in SDS-polyacrylamide gel has been employed. Protein hydrolysate gave high antioxidant activities, but didn't give any antimicrobial activities. The antioxidant activities of protein hydrolysate was in the same trend of peptide content which gave high antioxidant activities and high peptide content between fractions 15 to 50. With increasing peptide concentrations, the scavenging effect on DPPH radical increased until about 70%, thereafter reaching a plateau. In compare to different concentrations of BHA, which exhibited higher activity (90%), soybean protein hydrolysate exhibited high antioxidant activities (70%) at a concentration of 1.45 mg/ml at fraction 25. Electrophoresis analysis indicated that, low- MW hydrolysate fractions (F1) appeared, on average, to have higher DPPH scavenging activities than high-MW fractions. These results revealed that soybean peptides probably contain substances that were proton donors and could react with free radicals to convert them to stable diamagnetic molecules.
Abstract: The potential of entomopathogenic nematodes in suppressing T. squalida population on cauliflower from transplanting to harvest was evaluated. Significant reductions in plant infestation percentage and population density (/m2) were recorded throughout the plantation seasons, 2011 and 2012 before and after spraying the plants. The percent reduction in numbers/m2 was the highest in March for the treatments with Heterorhabditis indica Behera and Heterorhabditis bacteriophora Giza during the plantation season 2011, while at the plantation season 2012, the reduction in population density was the highest in January for Heterorhabditis Indica Behera and in February for H . bacteriophora Giza treatments. In a comparison test with conventional insecticides Hostathion and Lannate, there were no significant differences in control measures resulting from treatments with H. indica Behera, H. bacteriophora Giza and Lannate. At the plantation season is 2012. Also, the treatments reduced the economic threshold of T. squalida on cauliflower in this experiment as compared with before and after spraying with both the two entomopathogenic nematodes at both seasons 2011 and 2012. This means an increase in the marketability of heads harvested as a consequence of monthly treatments.
Abstract: This paper presents an on-going research work on the
implementation of feature-based machining via macro programming.
Repetitive machining features such as holes, slots, pockets etc can
readily be encapsulated in macros. Each macro consists of methods
on how to machine the shape as defined by the feature. The macro
programming technique comprises of a main program and
subprograms. The main program allows user to select several
subprograms that contain features and define their important
parameters. With macros, complex machining routines can be
implemented easily and no post processor is required. A case study
on machining of a part that comprised of planar face, hole and pocket
features using the macro programming technique was carried out. It
is envisaged that the macro programming technique can be extended
to other feature-based machining fields such as the newly developed
STEP-NC domain.