Abstract: This questionnaire-based study, aimed to measure and
compare the awareness of English reading strategies among EFL
learners at Bangkok University (BU) classified by their gender, field
of study, and English learning experience. Proportional stratified
random sampling was employed to formulate a sample of 380 BU
students. The data were statistically analyzed in terms of the mean
and standard deviation. t-Test analysis was used to find differences in
awareness of reading strategies between two groups (-male and
female- /-science and social-science students). In addition, one-way
analysis of variance (ANOVA) was used to compare reading strategy
awareness among BU students with different lengths of English
learning experience. The results of this study indicated that the
overall awareness of reading strategies of EFL learners at BU was at
a high level (ðÑ = 3.60) and that there was no statistically significant
difference between males and females, and among students who have
different lengths of English learning experience at the significance
level of 0.05. However, significant differences among students
coming from different fields of study were found at the same level of
significance.
Abstract: Self-efficacy, self-reliance, and motivation were
examined in a quasi-experimental study with 178 sophomore
university students. Participants used an interactive cardiovascular
anatomy and physiology CD-ROM, and completed a 15-item
questionnaire. Reliability of the questionnaire was established using
Cronbach-s alpha. Post-tests and course grades were examined using
a t-test, demonstrating no significance. Results of an item-to-item
analysis of the questionnaire showed overall satisfaction with the
teaching methodology and varied results for self-efficacy, selfreliance,
and motivation. Kendall-s Tau was calculated for all items
in the questionnaire.
Abstract: Recommender systems are usually regarded as an
important marketing tool in the e-commerce. They use important
information about users to facilitate accurate recommendation. The
information includes user context such as location, time and interest
for personalization of mobile users. We can easily collect information
about location and time because mobile devices communicate with the
base station of the service provider. However, information about user
interest can-t be easily collected because user interest can not be
captured automatically without user-s approval process. User interest
usually represented as a need. In this study, we classify needs into two
types according to prior research. This study investigates the
usefulness of data mining techniques for classifying user need type for
recommendation systems. We employ several data mining techniques
including artificial neural networks, decision trees, case-based
reasoning, and multivariate discriminant analysis. Experimental
results show that CHAID algorithm outperforms other models for
classifying user need type. This study performs McNemar test to
examine the statistical significance of the differences of classification
results. The results of McNemar test also show that CHAID performs
better than the other models with statistical significance.
Abstract: In the current age, retrieval of relevant information
from massive amount of data is a challenging job. Over the years,
precise and relevant retrieval of information has attained high
significance. There is a growing need in the market to build systems,
which can retrieve multimedia information that precisely meets the
user's current needs. In this paper, we have introduced a framework
for refining query results before showing it to the user, using ambient
intelligence, user profile, group profile, user location, time, day, user
device type and extracted features. A prototypic tool was also
developed to demonstrate the efficiency of the proposed approach.
Abstract: Xanthan gum is a microbial polysaccharide of great
commercial significance. The purpose of this study was to select the
optimum fermentation time for xanthan gum production by
Xanthomonas campestris (NRRL-B-1459) using 10% sugar beet
molasses as a carbon source. The pre-heating of sugar beet molasses
and the supplementation of the medium were investigated in order to
improve xanthan gum production. Maximum xanthan gum
production in fermentation media (9.02 g/l) was observed after 4 days
shaking incubation at 25°C and 240 rpm agitation speed. A solution
of 10% sucrose was used as a control medium. Results indicated that
the optimum period for xanthan gum production in this condition was
4 days.
Abstract: In recent years, everything is trending toward digitalization
and with the rapid development of the Internet technologies,
digital media needs to be transmitted conveniently over the network.
Attacks, misuse or unauthorized access of information is of great
concern today which makes the protection of documents through
digital media a priority problem. This urges us to devise new data
hiding techniques to protect and secure the data of vital significance.
In this respect, steganography often comes to the fore as a tool for
hiding information. Steganography is a process that involves hiding
a message in an appropriate carrier like image or audio. It is of
Greek origin and means "covered or hidden writing". The goal of
steganography is covert communication. Here the carrier can be sent
to a receiver without any one except the authenticated receiver only
knows existence of the information. Considerable amount of work
has been carried out by different researchers on steganography. In this
work the authors propose a novel Steganographic method for hiding
information within the spatial domain of the gray scale image. The
proposed approach works by selecting the embedding pixels using
some mathematical function and then finds the 8 neighborhood of
the each selected pixel and map each bit of the secret message in
each of the neighbor pixel coordinate position in a specified manner.
Before embedding a checking has been done to find out whether the
selected pixel or its neighbor lies at the boundary of the image or not.
This solution is independent of the nature of the data to be hidden
and produces a stego image with minimum degradation.