Abstract: Encrypted messages sending frequently draws the attention
of third parties, perhaps causing attempts to break and
reveal the original messages. Steganography is introduced to hide
the existence of the communication by concealing a secret message
in an appropriate carrier like text, image, audio or video. Quantum
steganography where the sender (Alice) embeds her steganographic
information into the cover and sends it to the receiver (Bob) over a
communication channel. Alice and Bob share an algorithm and hide
quantum information in the cover. An eavesdropper (Eve) without
access to the algorithm can-t find out the existence of the quantum
message. In this paper, a text quantum steganography technique based
on the use of indefinite articles (a) or (an) in conjunction with the nonspecific
or non-particular nouns in English language and quantum
gate truth table have been proposed. The authors also introduced a
new code representation technique (SSCE - Secret Steganography
Code for Embedding) at both ends in order to achieve high level of
security. Before the embedding operation each character of the secret
message has been converted to SSCE Value and then embeds to cover
text. Finally stego text is formed and transmits to the receiver side.
At the receiver side different reverse operation has been carried out
to get back the original information.
Abstract: Practicum placements are an critical factor for student teachers on Education Programs. How can student teachers become professionals? This study was to investigate problems, weakness and obstacles of practicum placements and develop guidelines for partnership in the practicum placements. In response to this issue, a partnership concept was implemented for developing student teachers into professionals. Data were collected through questionnaires on attitude toward problems, weaknesses, and obstacles of practicum placements of student teachers in Rajabhat universities and included focus group interviews. The research revealed that learning management, classroom management, curriculum, assessment and evaluation, classroom action research, and teacher demeanor are the important factors affecting the professional development of Education Program student teachers. Learning management plan and classroom management concerning instructional design, teaching technique, instructional media, and student behavior management are another important aspects influencing the professional development for student teachers.
Abstract: Medical image modalities such as computed
tomography (CT), magnetic resonance imaging (MRI), ultrasound
(US), X-ray are adapted to diagnose disease. These modalities
provide flexible means of reviewing anatomical cross-sections and
physiological state in different parts of the human body. The raw
medical images have a huge file size and need large storage
requirements. So it should be such a way to reduce the size of those
image files to be valid for telemedicine applications. Thus the image
compression is a key factor to reduce the bit rate for transmission or
storage while maintaining an acceptable reproduction quality, but it is
natural to rise the question of how much an image can be compressed
and still preserve sufficient information for a given clinical
application. Many techniques for achieving data compression have
been introduced. In this study, three different MRI modalities which
are Brain, Spine and Knee have been compressed and reconstructed
using wavelet transform. Subjective and objective evaluation has
been done to investigate the clinical information quality of the
compressed images. For the objective evaluation, the results show
that the PSNR which indicates the quality of the reconstructed image
is ranging from (21.95 dB to 30.80 dB, 27.25 dB to 35.75 dB, and
26.93 dB to 34.93 dB) for Brain, Spine, and Knee respectively. For
the subjective evaluation test, the results show that the compression
ratio of 40:1 was acceptable for brain image, whereas for spine and
knee images 50:1 was acceptable.
Abstract: Rainfall data at fine resolution and knowledge of its
characteristics plays a major role in the efficient design and operation
of agricultural, telecommunication, runoff and erosion control as well
as water quality control systems. The paper is aimed to study the
statistical distribution of hourly rainfall depth for 12 representative
stations spread across Peninsular Malaysia. Hourly rainfall data of 10
to 22 years period were collected and its statistical characteristics
were estimated. Three probability distributions namely, Generalized
Pareto, Exponential and Gamma distributions were proposed to
model the hourly rainfall depth, and three goodness-of-fit tests,
namely, Kolmogorov-Sminov, Anderson-Darling and Chi-Squared
tests were used to evaluate their fitness. Result indicates that the east
cost of the Peninsular receives higher depth of rainfall as compared
to west coast. However, the rainfall frequency is found to be
irregular. Also result from the goodness-of-fit tests show that all the
three models fit the rainfall data at 1% level of significance.
However, Generalized Pareto fits better than Exponential and
Gamma distributions and is therefore recommended as the best fit.
Abstract: Based on 276 responses from academic staff in an
evaluation of an online learning environment (OLE), this paper
identifies those elements of the OLE that were most used and valued
by staff, those elements of the OLE that staff most wanted to see
improved, and those factors that most contributed to staff perceptions
that the use of the OLE enhanced their teaching. The most used and
valued elements were core functions, including accessing unit
information, accessing lecture/tutorial/lab notes, and reading online
discussions. The elements identified as most needing attention related
to online assessment: submitting assignments, managing assessment
items, and receiving feedback on assignments. Staff felt that using the
OLE enhanced their teaching when they were satisfied that their
students were able to access and use their learning materials, and
when they were satisfied with the professional development they
received and were confident with their ability to teach with the OLE.
Abstract: Extraction of laccase produced by L. polychrous in an
aqueous two-phase system, composed of polyethylene glycol and
phosphate salt at pH 7.0 and 250C was investigated. The effect of
PEG molecular weight, PEG concentration and phosphate
concentration was determined. Laccase preferentially partitioned to
the top phase. Good extraction of laccase to the top phase was
observed with PEG 4000. The optimum system was found in the
system containing 12% w/w PEG 4000 and 16% w/w phosphate salt
with KE of 88.3, purification factor of 3.0-fold and 99.1% yield.
Some properties of the enzyme such as thermal stability, effect of
heavy metal ions and kinetic constants were also presented in this
work. The thermal stability decreased sharply with high temperature
above 60 0C. The enzyme was inhibited by Cd2+, Pb2+, Zn2+ and
Cu2+. The Vmax and Km values of the enzyme were 74.70
μmol/min/ml and 9.066 mM respectively.
Abstract: Friction-stir welding has received a huge interest in the last few years. The many advantages of this promising process have led researchers to present different theoretical and experimental explanation of the process. The way to quantitatively and qualitatively control the different parameters of the friction-stir welding process has not been paved. In this study, a refined energybased model that estimates the energy generated due to friction and plastic deformation is presented. The effect of the plastic deformation at low energy levels is significant and hence a scale factor is introduced to control its effect. The predicted heat energy and the obtained maximum temperature using our model are compared to the theoretical and experimental results available in the literature and a good agreement is obtained. The model is applied to AA6000 and AA7000 series.
Abstract: Tumor classification is a key area of research in the
field of bioinformatics. Microarray technology is commonly used in
the study of disease diagnosis using gene expression levels. The
main drawback of gene expression data is that it contains thousands
of genes and a very few samples. Feature selection methods are used
to select the informative genes from the microarray. These methods
considerably improve the classification accuracy. In the proposed
method, Genetic Algorithm (GA) is used for effective feature
selection. Informative genes are identified based on the T-Statistics,
Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate
solutions of GA are obtained from top-m informative genes. The
classification accuracy of k-Nearest Neighbor (kNN) method is used
as the fitness function for GA. In this work, kNN and Support Vector
Machine (SVM) are used as the classifiers. The experimental results
show that the proposed work is suitable for effective feature
selection. With the help of the selected genes, GA-kNN method
achieves 100% accuracy in 4 datasets and GA-SVM method
achieves in 5 out of 10 datasets. The GA with kNN and SVM
methods are demonstrated to be an accurate method for microarray
based tumor classification.
Abstract: Without uncertainty by applying external loads on
beams, bending is created. The created bending in I-beams, puts one
of the flanges in tension and the other one in compression. With increasing of bending, compression flange buckled and beam in out
of its plane direction twisted, this twisting well-known as Lateral Torsional Buckling. Providing bending moment varieties along the
beam, the critical moment is greater than the case its under pure bending. In other words, the value of bending gradient coefficient is
always greater than unite. In this article by the use of " ANSYS 10.0" software near 80 3-D finite element models developed for the
propose of analyzing beams` lateral torsional buckling and surveying influence of slenderness on beams' bending gradient coefficient.
Results show that, presented Cb coefficient via AISC is not correct for some of beams and value of this coefficient is smaller than what proposed by AISC. Therefore instead of using a constant Cb for each
case of loading , a function with two criterion for calculation of Cb coefficient for some cases is proposed.
Abstract: Starting with an analysis of the financial and
operational indicators that can be found in the specialised literature,
this study aims to contribute to improvements in the performance
measurement systems used when the unit of analysis is the
manufacturing plant. For this a search was done in the highest impact
Journals of Production and Operations Management and
Management Accounting , with the aim of determining the financial
and operational indicators used to evaluate performance when
Advanced Production Practices have been implemented, more
specifically when the practices implemented are Total Quality
Management, JIT/Lean Manufacturing and Total Productive
Maintenance. This has enabled us to obtain a classification of the two
types of indicators based on how much each is used. For the financial
indicators we have also prepared a proposal that can be adapted to
manufacturing plants- accounting features. In the near future we will
propose a model that links practices implementation with financial
and operational indicators and these two last with each other. We aim
to will test this model empirically with the data obtained in the High
Performance Manufacturing Project.
Abstract: This paper mainly investigates the environmental and
economic impacts of worldwide use of electric vehicles. It can be
concluded that governments have good reason to promote the use of
electric vehicles. First, the global vehicles population is evaluated with
the help of grey forecasting model and the amount of oil saving is
estimated through approximate calculation. After that, based on the
game theory, the amount and types of electricity generation needed by
electronic vehicles are established. Finally, some conclusions on the
government-s attitudes are drawn.
Abstract: Simulation is a very powerful method used for highperformance
and high-quality design in distributed system, and now
maybe the only one, considering the heterogeneity, complexity and
cost of distributed systems. In Grid environments, foe example, it is
hard and even impossible to perform scheduler performance
evaluation in a repeatable and controllable manner as resources and
users are distributed across multiple organizations with their own
policies. In addition, Grid test-beds are limited and creating an
adequately-sized test-bed is expensive and time consuming.
Scalability, reliability and fault-tolerance become important
requirements for distributed systems in order to support distributed
computation. A distributed system with such characteristics is called
dependable. Large environments, like Cloud, offer unique
advantages, such as low cost, dependability and satisfy QoS for all
users. Resource management in large environments address
performant scheduling algorithm guided by QoS constrains. This
paper presents the performance evaluation of scheduling heuristics
guided by different optimization criteria. The algorithms for
distributed scheduling are analyzed in order to satisfy users
constrains considering in the same time independent capabilities of
resources. This analysis acts like a profiling step for algorithm
calibration. The performance evaluation is based on simulation. The
simulator is MONARC, a powerful tool for large scale distributed
systems simulation. The novelty of this paper consists in synthetic
analysis results that offer guidelines for scheduler service
configuration and sustain the empirical-based decision. The results
could be used in decisions regarding optimizations to existing Grid
DAG Scheduling and for selecting the proper algorithm for DAG
scheduling in various actual situations.
Abstract: It has become crucial over the years for nations to
improve their credit scoring methods and techniques in light of the
increasing volatility of the global economy. Statistical methods or
tools have been the favoured means for this; however artificial
intelligence or soft computing based techniques are becoming
increasingly preferred due to their proficient and precise nature and
relative simplicity. This work presents a comparison between Support
Vector Machines and Artificial Neural Networks two popular soft
computing models when applied to credit scoring. Amidst the
different criteria-s that can be used for comparisons; accuracy,
computational complexity and processing times are the selected
criteria used to evaluate both models. Furthermore the German credit
scoring dataset which is a real world dataset is used to train and test
both developed models. Experimental results obtained from our study
suggest that although both soft computing models could be used with
a high degree of accuracy, Artificial Neural Networks deliver better
results than Support Vector Machines.
Abstract: This paper is concerned with propagation of thermoelastic longitudinal vibrations of an infinite circular cylinder, in the context of the linear theory of generalized thermoelasticity with two relaxation time parameters (Green and Lindsay theory). Three displacement potential functions are introduced to uncouple the equations of motion. The frequency equation, by using the traction free boundary conditions, is given in the form of a determinant involving Bessel functions. The roots of the frequency equation give the value of the characteristic circular frequency as function of the wave number. These roots, which correspond to various modes, are numerically computed and presented graphically for different values of the thermal relaxation times. It is found that the influences of the thermal relaxation times on the amplitudes of the elastic and thermal waves are remarkable. Also, it is shown in this study that the propagation of thermoelastic longitudinal vibrations based on the generalized thermoelasticity can differ significantly compared with the results under the classical formulation. A comparison of the results for the case with no thermal effects shows well agreement with some of the corresponding earlier results.
Abstract: This paper presents a Reliability-Based Topology
Optimization (RBTO) based on Evolutionary Structural Optimization
(ESO). An actual design involves uncertain conditions such as
material property, operational load and dimensional variation.
Deterministic Topology Optimization (DTO) is obtained without
considering of the uncertainties related to the uncertainty parameters.
However, RBTO involves evaluation of probabilistic constraints,
which can be done in two different ways, the reliability index
approach (RIA) and the performance measure approach (PMA). Limit
state function is approximated using Monte Carlo Simulation and
Central Composite Design for reliability analysis. ESO, one of the
topology optimization techniques, is adopted for topology
optimization. Numerical examples are presented to compare the DTO
with RBTO.
Abstract: Today, advantage of biotechnology especially in environmental issues compared to other technologies is irrefragable. Kimia Gharb Gostar Industries Company, as a largest producer of citric acid in Middle East, applies biotechnology for this goal. Citrogypsum is a by–product of citric acid production and it considered as a valid residuum of this company. At this paper summary of acid citric production and condition of Citrogypsum production in company were introduced in addition to defmition of Citrogypsum production and its applications in world. According to these information and evaluation of present conditions about Iran needing to Citrogypsum, the best priority was introduced and emphasized on strategy selection and proper programming for self-sufficiency. The Delphi technique was used to elicit expert opinions about criteria for evaluating the usages. The criteria identified by the experts were profitability, capacity of production, the degree of investment, marketable, production ease and time production. The Analytical Hierarchy Process (ARP) and Expert Choice software were used to compare the alternatives on the criteria derived from the Delphi process.
Abstract: With the rapid growth and development of information and communication technology, the Internet has played a definite and irreplaceable role in people-s social lives in Taiwan like in other countries. In July 2008, on a general social website, an unexpected phenomenon was noticed – that there were more than one hundred users who started forming clubs voluntarily and having face-to-face gatherings for specific purposes. In this study, it-s argued whether or not teenagers- social contact on the Internet is involved in their life context, and tried to reveal the teenagers- social preferences, values, and needs, which merge with and influence teenagers- social activities. Therefore, the study conducts multiple user experience research methods, which include practical observations and qualitative analysis by contextual inquiries and in-depth interviews. Based on the findings, several design implications for software related to social interactions and cultural inheritance are offered. It is concluded that the inherent values of a social behaviors might be a key issue in developing computer-mediated communication or interaction designs in the future.
Abstract: To model the human visual system (HVS) in the region of interest, we propose a new objective metric evaluation adapted to wavelet foveation-based image compression quality measurement, which exploits a foveation setup filter implementation technique in the DWT domain, based especially on the point and region of fixation of the human eye. This model is then used to predict the visible divergences between an original and compressed image with respect to this region field and yields an adapted and local measure error by removing all peripheral errors. The technique, which we call foveation wavelet visible difference prediction (FWVDP), is demonstrated on a number of noisy images all of which have the same local peak signal to noise ratio (PSNR), but visibly different errors. We show that the FWVDP reliably predicts the fixation areas of interest where error is masked, due to high image contrast, and the areas where the error is visible, due to low image contrast. The paper also suggests ways in which the FWVDP can be used to determine a visually optimal quantization strategy for foveation-based wavelet coefficients and to produce a quantitative local measure of image quality.
Abstract: In face recognition, feature extraction techniques
attempts to search for appropriate representation of the data. However,
when the feature dimension is larger than the samples size, it brings
performance degradation. Hence, we propose a method called
Normalization Discriminant Independent Component Analysis
(NDICA). The input data will be regularized to obtain the most
reliable features from the data and processed using Independent
Component Analysis (ICA). The proposed method is evaluated on
three face databases, Olivetti Research Ltd (ORL), Face Recognition
Technology (FERET) and Face Recognition Grand Challenge
(FRGC). NDICA showed it effectiveness compared with other
unsupervised and supervised techniques.
Abstract: Glutathione S-transferase was purified from human
erythrocytes and effects of some polyphenols were investigated on
the enzyme activity. The purification procedure was performed on
Glutathione-Agarose affinity chromatography after preparation of
erythrocytes hemolysate with a yield of 81%. The purified enzyme
showed a single band on the SDS-PAGE. The effects of some
poliphenolic compounds such as catechin, dopa, dopamine, progallol
and catechol were examined on the in vitro GST activity. Catechin
was determined to be inhibitor for the enzyme, but others were not
effective on the enzyme as inhibitors or activators. IC50 value -the
concentration of inhibitor which reduces enzyme activity by 50%-
was estimated to be 10 mM. Ki constants were also calculated as 6.38
± 0,70 mM with GSH substrate, and 3.86 ± 0,78 mM with CDNB
substrate using the equations of graphs for the inhibitor, and its
inhibition type was determined as non-competitive.