Abstract: Retrieval of the surface reflectance is important in the
remotely sensed data analysis to obtain the atmospheric reflectance or
atmospheric correction. The relationship between visible and mid
infrared reflectance over land was investigated and developed in this
study. The surface reflectances of the two visible bands were
measured using a handheld spectroradiometer collected around
Penang Island. In this study, we use the assumption that the 2.1 μm
band is not affected by aerosol and it is transparent to most aerosol
types (except dust). Therefore the satellite observed signal is the
same as the surface signal in 2.1 μm band. The correlation between
the surface reflectance measured by the spectroradiometer in the blue
and red region and the 2.1 μm observed by the satellite has been
established. We investigate five dates of Landsat TM scenes in this
study. The finding obtained by this study indicates that the surface
reflectance can be retrieved from the 2.1 μm band.
Abstract: The mosques have been appearance in Thailand since
Ayutthaya Kingdom (1350 to 1767 A.D.) Until today, more than 400 years later; there are many styles of art form behind their structure.
This research intended to identify Islamic Art in Thai mosques. A framework was applied using qualitative research methods; Thai
Muslims with dynamic roles in Islamic culture were interviewed. In
addition, a field survey of 40 selected mosques from 175 Thai
mosques was studied. Data analysis will be according to the pattern
of each period. The identification of Islamic Art in Thai Mosques are
1) the image of Thai identity: with Thai traditional art style and Government policy. 2) The image of the Ethnological identity: with
the traditional culture of Asian Muslims in Thailand. 3) The image of
the Nostalgia identity: with Islamic and Arabian conservative style.
4) The image of the Neo Classic identity: with Neo – Classic and
Contemporary art. 5) The image of the new identity: with Post
Modern and Deconstruction art.
Abstract: This study is concerned with pH solution detection
using 2 × 4 flexible sensor array based on a plastic polyethylene
terephthalate (PET) substrate that is coated a conductive layer and a
ruthenium dioxide (RuO2) sensitive membrane with the technologies
of screen-printing and RF sputtering. For data analysis, we also
prepared a dynamic measurement system for acquiring the response
voltage and analyzing the characteristics of the working electrodes
(WEs), such as sensitivity and linearity. In this condition, an array
measurement system was designed to acquire the original signal from
sensor array, and it is based on the method of digital signal processing
(DSP). The DSP modifies the unstable acquisition data to a direct
current (DC) output using the technique of digital filter. Hence, this
sensor array can obtain a satisfactory yield, 62.5%, through the design
measurement and analysis system in our laboratory.
Abstract: This research is aimed to describe the application of robust regression and its advantages over the least square regression method in analyzing financial data. To do this, relationship between earning per share, book value of equity per share and share price as price model and earning per share, annual change of earning per share and return of stock as return model is discussed using both robust and least square regressions, and finally the outcomes are compared. Comparing the results from the robust regression and the least square regression shows that the former can provide the possibility of a better and more realistic analysis owing to eliminating or reducing the contribution of outliers and influential data. Therefore, robust regression is recommended for getting more precise results in financial data analysis.
Abstract: Cytogenetic analysis still remains the gold standard method for prenatal diagnosis of trisomy 21 (Down syndrome, DS). Nevertheless, the conventional cytogenetic analysis needs live cultured cells and is too time-consuming for clinical application. In contrast, molecular methods such as FISH, QF-PCR, MLPA and quantitative Real-time PCR are rapid assays with results available in 24h. In the present study, we have successfully used a novel MGB TaqMan probe-based real time PCR assay for rapid diagnosis of trisomy 21 status in Down syndrome samples. We have also compared the results of this molecular method with corresponding results obtained by the cytogenetic analysis. Blood samples obtained from DS patients (n=25) and normal controls (n=20) were tested by quantitative Real-time PCR in parallel to standard G-banding analysis. Genomic DNA was extracted from peripheral blood lymphocytes. A high precision TaqMan probe quantitative Real-time PCR assay was developed to determine the gene dosage of DSCAM (target gene on 21q22.2) relative to PMP22 (reference gene on 17p11.2). The DSCAM/PMP22 ratio was calculated according to the formula; ratio=2 -ΔΔCT. The quantitative Real-time PCR was able to distinguish between trisomy 21 samples and normal controls with the gene ratios of 1.49±0.13 and 1.03±0.04 respectively (p value
Abstract: Renewable energy systems are becoming a topic of
great interest and investment in the world. In recent years wind
power generation has experienced a very fast development in the
whole world. For planning and successful implementations of good
wind power plant projects, wind potential measurements are
required. In these projects, of great importance is the effective choice
of the micro location for wind potential measurements, installation of
the measurement station with the appropriate measuring equipment,
its maintenance and analysis of the gained data on wind potential
characteristics. In this paper, a wavelet transform has been applied to
analyze the wind speed data in the context of insight in the
characteristics of the wind and the selection of suitable locations that
could be the subject of a wind farm construction. This approach
shows that it can be a useful tool in investigation of wind potential.
Abstract: The OTOP Entrepreneurship that used to create
substantial source of income for local Thai communities are now in a
stage of exigent matters that required assistances from public sectors
due to over Entrepreneurship of duplicative ideas, unable to adjust
costs and prices, lack of innovation, and inadequate of quality
control. Moreover, there is a repetitive problem of middlemen who
constantly corner the OTOP market. Local OTOP producers become
easy preys since they do not know how to add more values, how to
create and maintain their own brand name, and how to create proper
packaging and labeling. The suggested solutions to local OTOP
producers are to adopt modern management techniques, to find
knowhow to add more values to products and to unravel other
marketing problems. The objectives of this research are to study the
prevalent OTOP products management and to discover direction to
manage OTOP products to enhance the effectiveness of OTOP
Entrepreneurship in Nonthaburi Province, Thailand. There were 113
participants in this study. The research tools can be divided into two
parts: First part is done by questionnaire to find responses of the
prevalent OTOP Entrepreneurship management. Second part is the
use of focus group which is conducted to encapsulate ideas and local
wisdom. Data analysis is performed by using frequency, percentage,
mean, and standard deviation as well as the synthesis of several small
group discussions. The findings reveal that 1) Business Resources:
the quality of product is most important and the marketing of product
is least important. 2) Business Management: Leadership is most
important and raw material planning is least important. 3) Business
Readiness: Communication is most important and packaging is least
important. 4) Support from public sector: Certified from the
government is most important and source of raw material is the least
important.
Abstract: Aims for this study: first, to compare the expertise
level in data analysis, communication and information technologies
in undergraduate psychology students. Second, to verify the factor
structure of E-ETICA (Escala de Experticia en Tecnologias de la Informacion, la Comunicacion y el Análisis or Data Analysis,
Communication and Information'Expertise Scale) which had shown
an excellent internal consistency (α= 0.92) as well as a simple factor
structure. Three factors, Complex, Basic Information and
Communications Technologies and E-Searching and Download
Abilities, explains 63% of variance. In the present study, 260
students (119 juniors and 141 seniors) were asked to respond to
ETICA (16 items Likert scale of five points 1: null domain to 5: total
domain). The results show that both junior and senior students report
having very similar expertise level; however, E-ETICA presents a
different factor structure for juniors and four factors explained also
63% of variance: Information E-Searching, Download and Process;
Data analysis; Organization; and Communication technologies.
Abstract: In the end of the day, meteorological data and environmental data becomes widely used such as plant varieties selection system. Variety plant selection for planted area is of almost importance for all crops, including varieties of sugarcane. Since sugarcane have many varieties. Variety plant non selection for planting may not be adapted to the climate or soil conditions for planted area. Poor growth, bloom drop, poor fruit, and low price are to be from varieties which were not recommended for those planted area. This paper presents plant varieties selection system for planted areas in Thailand from meteorological data and environmental data by the use of decision tree techniques. With this software developed as an environmental data analysis tool, it can analyze resulting easier and faster. Our software is a front end of WEKA that provides fundamental data mining functions such as classify, clustering, and analysis functions. It also supports pre-processing, analysis, and decision tree output with exporting result. After that, our software can export and display data result to Google maps API in order to display result and plot plant icons effectively.
Abstract: Temperature, humidity and precipitation in an area,
are parameters proved influential in the climate of that area, and one
should recognize them so that he can determine the climate of that
area. Climate changes are of primary importance in climatology, and
in recent years, have been of great concern to researchers and even
politicians and organizations, for they can play an important role in
social, political and economic activities. Even though the real cause
of climate changes or their stability is not yet fully recognized, they
are a matter of concern to researchers and their importance for
countries has prompted them to investigate climate changes in
different levels, especially in regional, national and continental level.
This issue has less been investigated in our country. However, in
recent years, there have been some researches and conferences on
climate changes. This study is also in line with such researches and
tries to investigate and analyze the trends of climate changes
(temperature and precipitation) in Sefid-roud (the name of a river)
basin. Three parameters of mean annual precipitation, temperature,
and maximum and minimum temperatures in 36 synoptic and
climatology stations in a statistical period of 49 years (1956-2005) in
the stations of Sefid-roud basin were analyzed by Mann-Kendall test.
The results obtained by data analysis show that climate changes are
short term and have a trend. The analysis of mean temperature
revealed that changes have a significantly rising trend, besides the
precipitation has a significantly falling trend.
Abstract: This work aims to explore the factors that have an incidence in reading comprehension process, with different type of texts. In a recent study with 2nd, 3rd and 4th grade children, it was observed that reading comprehension of narrative texts was better than comprehension of expository texts. Nevertheless it seems that not only the type of text but also other textual factors would account for comprehension depending on the cognitive processing demands posed by the text. In order to explore this assumption, three narrative and three expository texts were elaborated with different degree of complexity. A group of 40 fourth grade Spanish-speaking children took part in the study. Children were asked to read the texts and answer orally three literal and three inferential questions for each text. The quantitative and qualitative analysis of children responses showed that children had difficulties in both, narrative and expository texts. The problem was to answer those questions that involved establishing complex relationships among information units that were present in the text or that should be activated from children’s previous knowledge to make an inference. Considering the data analysis, it could be concluded that there is some interaction between the type of text and the cognitive processing load of a specific text.
Abstract: For the past one decade, biclustering has become popular data mining technique not only in the field of biological data analysis but also in other applications like text mining, market data analysis with high-dimensional two-way datasets. Biclustering clusters both rows and columns of a dataset simultaneously, as opposed to traditional clustering which clusters either rows or columns of a dataset. It retrieves subgroups of objects that are similar in one subgroup of variables and different in the remaining variables. Firefly Algorithm (FA) is a recently-proposed metaheuristic inspired by the collective behavior of fireflies. This paper provides a preliminary assessment of discrete version of FA (DFA) while coping with the task of mining coherent and large volume bicluster from web usage dataset. The experiments were conducted on two web usage datasets from public dataset repository whereby the performance of FA was compared with that exhibited by other population-based metaheuristic called binary Particle Swarm Optimization (PSO). The results achieved demonstrate the usefulness of DFA while tackling the biclustering problem.
Abstract: Classification is an interesting problem in functional
data analysis (FDA), because many science and application problems
end up with classification problems, such as recognition, prediction,
control, decision making, management, etc. As the high dimension
and high correlation in functional data (FD), it is a key problem to
extract features from FD whereas keeping its global characters, which
relates to the classification efficiency and precision to heavens. In this
paper, a novel automatic method which combined Genetic Algorithm
(GA) and classification algorithm to extract classification features is
proposed. In this method, the optimal features and classification model
are approached via evolutional study step by step. It is proved by
theory analysis and experiment test that this method has advantages in
improving classification efficiency, precision and robustness whereas
using less features and the dimension of extracted classification
features can be controlled.
Abstract: The purpose of this study was to find out the
effectiveness of neurological impress method and repeated reading
technique on reading fluency of children with learning disabilities.
Thirty primary four pupils in three public primary schools
participated in the study. There were two experimental groups and a
control. This research employed a 3 by 2 factorial matrix and the
participants were taught for one session. Two hypotheses were
formulated to guide the research. T-test was used to analyse the data
gathered, and data analysis revealed that pupils exposed to the two
treatment strategies had improvement in their reading fluency. It was
recommended that the two strategies used in the study can be used to
intervene in reading fluency problems in children with learning
disabilities.
Abstract: One of the main trouble in a steel strip manufacturing
line is the breakage of whatever weld carried out between steel coils,
that are used to produce the continuous strip to be processed. A weld
breakage results in a several hours stop of the manufacturing line. In
this process the damages caused by the breakage must be repaired.
After the reparation and in order to go on with the production it will
be necessary a restarting process of the line. For minimizing this
problem, a human operator must inspect visually and manually each
weld in order to avoid its breakage during the manufacturing process.
The work presented in this paper is based on the Bayesian decision
theory and it presents an approach to detect, on real-time, steel strip
defective welds. This approach is based on quantifying the tradeoffs
between various classification decisions using probability and the
costs that accompany such decisions.
Abstract: We apply a particle tracking technique to track the motion of individual pathogenic Leptospira. We observe and capture images of motile Leptospira by means of CCD and darkfield microscope. Image processing, statistical theories and simulations are used for data analysis. Based on trajectory patterns, mean square displacement, and power spectral density characteristics, we found that the motion modes are most likely to be directed motion mode (70%) and the rest are either normal diffusion or unidentified mode. Our findings may support the fact that why leptospires are very well efficient toward targeting internal tissues as a result of increase in virulence factor.
Abstract: The vehicle fleet of public transportation companies is often equipped with intelligent on-board passenger information systems. A frequently used but time and labor-intensive way for keeping the on-board controllers up-to-date is the manual update using different memory cards (e.g. flash cards) or portable computers. This paper describes a compression algorithm that enables data transmission using low bandwidth wireless radio networks (e.g. GPRS) by minimizing the amount of data traffic. In typical cases it reaches a compression rate of an order of magnitude better than that of the general purpose compressors. Compressed data can be easily expanded by the low-performance controllers, too.
Abstract: This research gathered local wisdom towards career building of people in Kamchanoad Community, Baan Muang sub-district, Baan Dung district, Udon Thani province. Data was collected through in-depth interviews with village headmen, community board, teachers, monks, Kamchanoad forest managers and revered elderly aged over 60 years old. All of these 30 interviewees have resided in Kamchanoad Community for more than 40. Descriptive data analysis result revealed that the most prominent local wisdom of Kamchanoad community is their beliefs and religion. Most people in the community have strongly maintained local tradition, the festival of appeasing Chao Pu Sri Suttho on the middle of the 6th month of Thai lunar calendar which falls on the same day with Vesak Day. 100 percent of the people in this community are Buddhist. They believe that Naga, an entity or being, taking the form of a serpent, named “Sri Suttho” lives in Kamchanoad forest. The local people worship the serpent and ask for blessings. Another local wisdom of this community is Sinh fabric weaving.
Abstract: The problems associated with wind predictions of
WAsP model in complex terrain are already the target of several
studies in the last decade. In this paper, the influence of surrounding
orography on accuracy of wind data analysis of a train is
investigated. For the case study, a site with complex surrounding
orography is considered. This site is located in Manjil, one of the
windiest cities of Iran. For having precise evaluation of wind regime
in the site, one-year wind data measurements from two metrological
masts are used. To validate the obtained results from WAsP, the
cross prediction between each mast is performed. The analysis
reveals that WAsP model can estimate the wind speed behavior
accurately. In addition, results show that this software can be used
for predicting the wind regime in flat sites with complex surrounding
orography.
Abstract: Microarrays have become the effective, broadly used tools in biological and medical research to address a wide range of problems, including classification of disease subtypes and tumors. Many statistical methods are available for analyzing and systematizing these complex data into meaningful information, and one of the main goals in analyzing gene expression data is the detection of samples or genes with similar expression patterns. In this paper, we express and compare the performance of several clustering methods based on data preprocessing including strategies of normalization or noise clearness. We also evaluate each of these clustering methods with validation measures for both simulated data and real gene expression data. Consequently, clustering methods which are common used in microarray data analysis are affected by normalization and degree of noise and clearness for datasets.