Abstract: Malay Folk Literature in early childhood education
served as an important agent in child development that involved
emotional, thinking and language aspects. Up to this moment not
much research has been carried out in Malaysia particularly in the
teaching and learning aspects nor has there been an effort to publish
“big books." Hence this article will discuss the stance taken by
university undergraduate students, teachers and parents in evaluating
Malay Folk Literature in early childhood education to be used as big
books. The data collated and analyzed were taken from 646
respondents comprising 347 undergraduates and 299 teachers. Results
of the study indicated that Malay Folk Literature can be absorbed into
teaching and learning for early childhood with a mean of 4.25 while it
can be in big books with a mean of 4.14. Meanwhile the highest mean
value required for placing Malay Folk Literature genre as big books in
early childhood education rests on exemplary stories for
undergraduates with mean of 4.47; animal fables for teachers with a
mean of 4.38. The lowest mean value of 3.57 is given to lipurlara
stories. The most popular Malay Folk Literature found suitable for
early children is Sang Kancil and the Crocodile, followed by Bawang
Putih Bawang Merah. Pak Padir, Legends of Mahsuri, Origin of
Malacca, and Origin of Rainbow are among the popular stories as
well. Overall the undergraduates show a positive attitude toward all
the items compared to teachers. The t-test analysis has revealed a non
significant relationship between the undergraduate students and
teachers with all the items for the teaching and learning of Malay Folk
Literature.
Abstract: This paper compares six approaches of object serialization
from qualitative and quantitative aspects. Those are object
serialization in Java, IDL, XStream, Protocol Buffers, Apache Avro,
and MessagePack. Using each approach, a common example is
serialized to a file and the size of the file is measured. The qualitative
comparison works are investigated in the way of checking whether
schema definition is required or not, whether schema compiler is
required or not, whether serialization is based on ascii or binary, and
which programming languages are supported. It is clear that there
is no best solution. Each solution makes good in the context it was
developed.
Abstract: Recently, lots of researchers are attracted to retrieving
multimedia database by using some impression words and their values.
Ikezoe-s research is one of the representatives and uses eight pairs of
opposite impression words. We had modified its retrieval interface and
proposed '2D-RIB' in the previous work. The aim of the present paper
is to improve his/her satisfaction level to the retrieval result in the
2D-RIB. Our method is to extend the 2D-RIB. One of our extensions is
to define and introduce the following two measures: 'melody
goodness' and 'general acceptance'. Another extension is three types
of customization menus. The result of evaluation using a pilot system
is as follows. Both of these two measures 'melody goodness'
and -general acceptance- can contribute to the improvement.
Moreover, it is effective if we introduce the customization menu
which enables a retrieval person to reduce the strictness level of
retrieval condition in an impression pair based on his/her need.
Abstract: Coherent and incoherent scattering cross section measurements have been carried out using a HPGe detector on elements in the range of Z = 13 - 50 using 241Am gamma rays. The cross sections have been derived by comparing the net count rate obtained from the Compton peak of aluminium with the corresponding peak of the target. The measured cross sections for the coherent and incoherent processes are compared with theoretical values and earlier reported values. Our results are in agreement with the theoretical values.
Abstract: The link between Gröbner basis and linear algebra was
described by Lazard [4,5] where he realized the Gr¨obner basis
computation could be archived by applying Gaussian elimination over
Macaulay-s matrix .
In this paper, we indicate how same technique may be used to
SAGBI- Gröbner basis computations in invariant rings.
Abstract: Naïve Bayes classifiers are simple probabilistic
classifiers. Classification extracts patterns by using data file with a set
of labeled training examples and is currently one of the most
significant areas in data mining. However, Naïve Bayes assumes the
independence among the features. Structural learning among the
features thus helps in the classification problem. In this study, the use
of structural learning in Bayesian Network is proposed to be applied
where there are relationships between the features when using the
Naïve Bayes. The improvement in the classification using structural
learning is shown if there exist relationship between the features or
when they are not independent.
Abstract: Microstrip lines, widely used for good reason, are
broadband in frequency and provide circuits that are compact and
light in weight. They are generally economical to produce since they
are readily adaptable to hybrid and monolithic integrated circuit (IC)
fabrication technologies at RF and microwave frequencies. Although,
the existing EM simulation models used for the synthesis and
analysis of microstrip lines are reasonably accurate, they are
computationally intensive and time consuming. Neural networks
recently gained attention as fast and flexible vehicles to microwave
modeling, simulation and optimization. After learning and
abstracting from microwave data, through a process called training,
neural network models are used during microwave design to provide
instant answers to the task learned.This paper presents simple and
accurate ANN models for the synthesis and analysis of Microstrip
lines to more accurately compute the characteristic parameters and
the physical dimensions respectively for the required design
specifications.
Abstract: Avionic software architecture has transit from a
federated avionics architecture to an integrated modular avionics
(IMA) .ARINC 653 (Avionics Application Standard Software Interface) is a software specification for space and time partitioning in
Safety-critical avionics Real-time operating systems. Methods to transform the abstract avionics application logic function to the
executable model have been brought up, however with less
consideration about the code generating input and output model specific for ARINC 653 platform and inner-task synchronous dynamic
interaction order sequence. In this paper, we proposed an
AADL-based model-driven design methodology to fulfill the purpose
to automatically generating Cµ executable model on ARINC 653 platform from the ARINC653 architecture which defined as AADL653 in order to facilitate the development of the avionics software constructed on ARINC653 OS. This paper presents the
mapping rules between the AADL653 elements and the elements in
Cµ language, and define the code generating rules , designs an automatic C µ code generator .Then, we use a case to illustrate our
approach. Finally, we give the related work and future research directions.
Abstract: This study on “The relationship between human
resource practices and Firm Performance is a speculative
investigation research. The purpose of this research are (1) to provide
and to understand of HRM history and current HR practices in the
Philippines (2) to examine the extent of HRM practice among its
Philippine firms effectively; (3) to investigate the relationship
between HRM practice and firm performance in the Philippines. The
survey was done to 233 companies in the Philippines. The
questionnaire is divided into three parts a) to gathers information on
the profile of respondent, b) to measures the extent to which human
resource practices are being practiced in their organization c) to
measure the organizations performance as perceived by human
resource managers and top executives as compared with their
competitors in the same industry. As a result an interesting finding
was that almost 50 percent of firm performance is affected by the
extent of implementation of HR practices in the firm. These results
show that HR practices that are in line with the organization’s
strategic goals are important for future performance.
Abstract: Experiments were carried out at the Latvia State
Institute of Fruit-Growing in 2011. Fresh-cut minimally processed
apple and pear mixed salad were packed by passive modified
atmosphere (MAP) in PP containers, which were hermetically sealed
by breathable conventional BOPP PropafreshTM P2GAF, and Amcor
Agrifresh films. Biodegradable NatureFlexTM NVS INNOVIA Films
and VC999 BioPack PLA films coated with a barrier of pure silicon
oxide (SiOx) were used to compare the fresh-cut produce quality
with this packed in conventional packaging films. Samples were cold
stored at temperature +4.0±0.5 °C up to 10 days. The quality of salad
was evaluated by physicochemical properties – weight losses,
moisture, firmness, the effect of packaging modes on the colour,
dynamics in headspace atmosphere concentration (CO2 and O2),
titratable acidity values, as well as by microbiological contamination
(yeasts, moulds and total bacteria count) of salads, analyzing before
packaging and after 2, 4, 6, 8, and 10 storage days.
Abstract: Psoriasis is a chronic inflammatory skin condition
which affects 2-3% of population around the world. Psoriasis Area
and Severity Index (PASI) is a gold standard to assess psoriasis
severity as well as the treatment efficacy. Although a gold standard,
PASI is rarely used because it is tedious and complex. In practice,
PASI score is determined subjectively by dermatologists, therefore
inter and intra variations of assessment are possible to happen even
among expert dermatologists. This research develops an algorithm to
assess psoriasis lesion for PASI scoring objectively. Focus of this
research is thickness assessment as one of PASI four parameters
beside area, erythema and scaliness. Psoriasis lesion thickness is
measured by averaging the total elevation from lesion base to lesion
surface. Thickness values of 122 3D images taken from 39 patients
are grouped into 4 PASI thickness score using K-means clustering.
Validation on lesion base construction is performed using twelve
body curvature models and show good result with coefficient of
determinant (R2) is equal to 1.
Abstract: Several studies have been carried out, using various techniques, including neural networks, to discriminate vigilance states in humans from electroencephalographic (EEG) signals, but we are still far from results satisfactorily useable results. The work presented in this paper aims at improving this status with regards to 2 aspects. Firstly, we introduce an original procedure made of the association of two neural networks, a self organizing map (SOM) and a learning vector quantization (LVQ), that allows to automatically detect artefacted states and to separate the different levels of vigilance which is a major breakthrough in the field of vigilance. Lastly and more importantly, our study has been oriented toward real-worked situation and the resulting model can be easily implemented as a wearable device. It benefits from restricted computational and memory requirements and data access is very limited in time. Furthermore, some ongoing works demonstrate that this work should shortly results in the design and conception of a non invasive electronic wearable device.
Abstract: Many research works are carried out on the analysis of
traces in a digital learning environment. These studies produce large
volumes of usage tracks from the various actions performed by a
user. However, to exploit these data, compare and improve
performance, several issues are raised. To remedy this, several works
deal with this problem seen recently. This research studied a series of
questions about format and description of the data to be shared. Our
goal is to share thoughts on these issues by presenting our experience
in the analysis of trace-based log files, comparing several approaches
used in automatic classification applied to e-learning platforms.
Finally, the obtained results are discussed.
Abstract: One of the essential sectors of Myanmar economy is
agriculture which is sensitive to climate variation. The most
important climatic element which impacts on agriculture sector is
rainfall. Thus rainfall prediction becomes an important issue in
agriculture country. Multi variables polynomial regression (MPR)
provides an effective way to describe complex nonlinear input output
relationships so that an outcome variable can be predicted from the
other or others. In this paper, the modeling of monthly rainfall
prediction over Myanmar is described in detail by applying the
polynomial regression equation. The proposed model results are
compared to the results produced by multiple linear regression model
(MLR). Experiments indicate that the prediction model based on
MPR has higher accuracy than using MLR.
Abstract: This paper presents a new function expansion method for finding traveling wave solutions of a nonlinear equations and calls it the G G -expansion method, given by Wang et al recently. As an application of this new method, we study the well-known Sawada-Kotera-Kadomtsev-Petviashivili equation and Bogoyavlensky-Konoplechenko equation. With two new expansions, general types of soliton solutions and periodic solutions for these two equations are obtained.
Abstract: This paper describes the evolution of strategies to
evaluate ePortfolios in an online Master-s of Education (M.Ed.)
degree in Instructional Technology. The ePortfolios are required as a
culminating activity for students in the program. By using Web 2.0
tools to develop the ePortfolios, students are able to showcase their
technical skills, integrate national standards, demonstrate their
professional understandings, and reflect on their individual learning.
Faculty have created assessment strategies to evaluate student
achievement of these skills. To further develop ePortfolios as a tool
promoting authentic learning, faculty are moving toward integrating
transparency as part of the evaluation process.
Abstract: The objective of this paper is to review and assess the
methodological issues and problems in marketing research, data and
knowledge mining in Turkey. As a summary, academic marketing
research publications in Turkey have significant problems. The most
vital problem seems to be related with modeling. Most of the
publications had major weaknesses in modeling. There were also,
serious problems regarding measurement and scaling, sampling and
analyses. Analyses myopia seems to be the most important problem
for young academia in Turkey. Another very important finding is the
lack of publications on data and knowledge mining in the academic
world.
Abstract: To study the effect of suitable methods for
propagation of True Potato Seed (TPS) progenies, transplant and
selection of the best progenies, a factorial experiment base on a
randomized complete block design was carried out in the research
field of Sahneh region, Kermanshah, Iran during 2009-2010. Five
selective progenies from CIP (International Potato Center) including
CIP.994013, CIP.994002, CIP.994014, CIP.888006, and
CIP.994001 and two transplant preparation methods (Paper pot
preparation for mechanical cultivation and preparation in transplant
trays for manual cultivation) were studied in three replications.
Results showed that different progenies had no significant effect on
plant height (cm) and tuber yield (t ha-1), whereas had a significant
effect on number of tubers per unit area (m2). There was significant
difference between transplant preparation methods for plant height
and tuber yield. The interaction effect of progenies and transplant
preparation method was not significant for these traits. CIP.888006
progeny and paper pot preparation method produced the highest
tuber yields. Also CIP.994002 and CIP.994014 progenies considered
as the best progenies under paper pot preparation method due to high
yields.
Abstract: Text document categorization involves large amount
of data or features. The high dimensionality of features is a
troublesome and can affect the performance of the classification.
Therefore, feature selection is strongly considered as one of the
crucial part in text document categorization. Selecting the best
features to represent documents can reduce the dimensionality of
feature space hence increase the performance. There were many
approaches has been implemented by various researchers to
overcome this problem. This paper proposed a novel hybrid approach
for feature selection in text document categorization based on Ant
Colony Optimization (ACO) and Information Gain (IG). We also
presented state-of-the-art algorithms by several other researchers.
Abstract: This paper presents the development of a wavelet
based algorithm, for distinguishing between magnetizing inrush
currents and power system fault currents, which is quite adequate,
reliable, fast and computationally efficient tool. The proposed
technique consists of a preprocessing unit based on discrete wavelet
transform (DWT) in combination with an artificial neural network
(ANN) for detecting and classifying fault currents. The DWT acts as
an extractor of distinctive features in the input signals at the relay
location. This information is then fed into an ANN for classifying
fault and magnetizing inrush conditions. A 220/55/55 V, 50Hz
laboratory transformer connected to a 380 V power system were
simulated using ATP-EMTP. The DWT was implemented by using
Matlab and Coiflet mother wavelet was used to analyze primary
currents and generate training data. The simulated results presented
clearly show that the proposed technique can accurately discriminate
between magnetizing inrush and fault currents in transformer
protection.