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: A novel idea presented in this paper is to combine
multihop routing with single-frequency networks (SFNs) for a
broadcasting scenario. An SFN is a set of multiple nodes that transmit
the same data simultaneously, resulting in transmitter macrodiversity.
Two of the most important performance factors of multihop
networks, node reachability and routing robustness, are analyzed.
Simulation results show that our proposed SFN-D routing algorithm
improves the node reachability by 37 percentage points as compared
to non-SFN multihop routing. It shows a diversity gain of 3.7 dB,
meaning that 3.7 dB lower transmission powers are required for the
same reachability. Even better results are possible for larger
networks. If an important node becomes inactive, this algorithm can
find new routes that a non-SFN scheme would not be able to find.
Thus, two of the major problems in multihopping are addressed;
achieving robust routing as well as improving node reachability or
reducing transmission power.
Abstract: In this paper, we propose a dynamic TDMA slot
reservation (DTSR) protocol for cognitive radio ad hoc networks.
Quality of Service (QoS) guarantee plays a critically important role
in such networks. We consider the problem of providing QoS
guarantee to users as well as to maintain the most efficient use of
scarce bandwidth resources. According to one hop neighboring
information and the bandwidth requirement, our proposed protocol
dynamically changes the frame length and the transmission schedule.
A dynamic frame length expansion and shrinking scheme that
controls the excessive increase of unassigned slots has been
proposed. This method efficiently utilizes the channel bandwidth by
assigning unused slots to new neighboring nodes and increasing the
frame length when the number of slots in the frame is insufficient to
support the neighboring nodes. It also shrinks the frame length when
half of the slots in the frame of a node are empty. An efficient slot
reservation protocol not only guarantees successful data
transmissions without collisions but also enhance channel spatial
reuse to maximize the system throughput. Our proposed scheme,
which provides both QoS guarantee and efficient resource utilization,
be employed to optimize the channel spatial reuse and maximize the
system throughput. Extensive simulation results show that the
proposed mechanism achieves desirable performance in multichannel
multi-rate cognitive radio ad hoc networks.
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: In the Equivalent Transformation (ET) computation
model, a program is constructed by the successive accumulation of
ET rules. A method by meta-computation by which a correct ET
rule is generated has been proposed. Although the method covers a
broad range in the generation of ET rules, all important ET rules
are not necessarily generated. Generation of more ET rules can be
achieved by supplementing generation methods which are specialized
for important ET rules. A Specialization-by-Equation (Speq) rule is
one of those important rules. A Speq rule describes a procedure in
which two variables included in an atom conjunction are equalized
due to predicate constraints. In this paper, we propose an algorithm
that systematically and recursively generate Speq rules and discuss
its effectiveness in the synthesis of ET programs. A Speq rule is
generated based on proof of a logical formula consisting of given
atom set and dis-equality. The proof is carried out by utilizing some
ET rules and the ultimately obtained rules in generating Speq rules.
Abstract: The purpose of this study is to investiagte the use of
the ecommerce website in Indonesia as a developing country. The
ecommerce website has been identified having the significant impact
on business activities in particular solving the geographical problem
for islanded countries likes Indonesia. Again, website is identified as
a crucial marketing tool. This study presents the effect of quality and
features on the use and user satisfaction employing ecommerce
websites. Survey method for 115 undergraduate students of
Management Department in Andalas University who are attending
Management Information Systems (SIM) class have been
undertaken. The data obtained is analyzed using Structural Equation
Modeling (SEM) using SmartPLS program. This result found that
quality of system and information, feature as well satisfaction
influencing the use ecommerce website in Indonesia contexts.
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: Indian subcontinent has a plethora of traditional
medicine systems that provide promising solutions to lifestyle
disorders in an 'all natural way'. Spices and oilseeds hold
prominence in Indian cuisine hence the focus of the current study
was to evaluate the bioactive molecules from Linum usitatissinum
(LU), Lepidium sativum (LS), Nigella sativa (NS) and Guizotia
abyssinica (GA) seeds. The seeds were characterized for functional
lipids like omega-3 fatty acid, antioxidant capacity, phenolic
compounds, dietary fiber and anti-nutritional factors. Analysis of the
seeds revealed LU and LS to be a rich source of α-linolenic acid
(41.85 ± 0.33%, 26.71 ± 0.63%), an omega 3 fatty acid (using
GCMS). While studying antioxidant potential NS seeds demonstrated
highest antioxidant ability (61.68 ± 0.21 TEAC/ 100 gm DW) due to
the presence of phenolics and terpenes as assayed by the Mass
spectral analysis. When screened for anti-nutritional factor
cyanogenic glycoside, LS seeds showed content as high as 1674 ± 54
mg HCN / kg. GA is a probable good source of a stable vegetable oil
(SFA: PUFA 1:2.3). The seeds showed diversified bioactive profile
and hence further studies to use different bio molecules in tandem for
the development of a possible 'nutraceutical cocktail' have been
initiated..
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: 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: 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: This paper presents a implementation of an object tracking system in a video sequence. This object tracking is an important task in many vision applications. The main steps in video analysis are two: detection of interesting moving objects and tracking of such objects from frame to frame. In a similar vein, most tracking algorithms use pre-specified methods for preprocessing. In our work, we have implemented several object tracking algorithms (Meanshift, Camshift, Kalman filter) with different preprocessing methods. Then, we have evaluated the performance of these algorithms for different video sequences. The obtained results have shown good performances according to the degree of applicability and evaluation criteria.
Abstract: In this paper, application of artificial neural networks
in typical disease diagnosis has been investigated. The real procedure
of medical diagnosis which usually is employed by physicians was
analyzed and converted to a machine implementable format. Then
after selecting some symptoms of eight different diseases, a data set
contains the information of a few hundreds cases was configured and
applied to a MLP neural network. The results of the experiments and
also the advantages of using a fuzzy approach were discussed as
well. Outcomes suggest the role of effective symptoms selection and
the advantages of data fuzzificaton on a neural networks-based
automatic medical diagnosis system.
Abstract: The most common domestic birds live in Turkey are: crows (Corvus corone), pigeons (Columba livia), sparrows (Passer domesticus), starlings (Sturnus vulgaris) and blackbirds (Turdus merula). These birds give damage to the agricultural areas and make dirty the human life areas. In order to send away these birds, some different materials and methods such as chemicals, treatments, colored lights, flash and audible scarers are used. It is possible to see many studies about chemical methods in the literatures. However there is not enough works regarding audible bird scarers are reported in the literature. Therefore, a solar powered bird scarer was designed, manufactured and tested in this experimental investigation. Firstly, to understand the sensitive level of these domestic birds against to the audible scarer, many series preliminary studies were conducted. These studies showed that crows are the most resistant against to the audible bird scarer when compared with pigeons, sparrows, starlings and blackbirds. Therefore the solar powered audible bird scarer was tested on crows. The scarer was tested about one month during April- May, 2007. 18 different common known predators- sounds (voices or calls) of domestic birds from Falcon (Falco eleonorae), Falcon (Buteo lagopus), Eagle (Aquila chrysaetos), Montagu-s harrier (Circus pygargus) and Owl (Glaucidium passerinum) were selected for test of the scarer. It was seen from the results that the reaction of the birds was changed depending on the predators- sound type, camouflage of the scarer, sound quality and volume, loudspeaker play and pause periods in one application. In addition, it was also seen that the sound from Falcon (Buteo lagopus) was most effective on crows and the scarer was enough efficient.
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: Radio Frequency Identification (RFID) system is
looked upon as one of the top ten important technologies in the 20th
century and find its applications in many fields such as car industry.
The intelligent cars are one important part of this industry and always
try to find new and satisfied intelligent cars. The purpose of this
paper is to introduce an intelligent car with the based of RFID. By
storing the moving control commands such as turn right, turn left,
speed up and speed down etc. into the RFID tags beforehand and
sticking the tags on the tracks Car can read the moving control
commands from the tags and accomplish the proper actions.
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.