Abstract: The quantitative determination of several trace
elements (Cr, As, Se, Cd, Hg, Pb) existing as inorganic impurities in
some oriental herb-products such as Lingzhi Mushroom capsules,
Philamin powder, etc using ICP-MS has been studied. Various
instrumental parameters such as power, gas flow rate, sample depth, as
well as the concentration of nitric acid and thick background due to
high concentration of possible interferences on the determination of
these above-mentioned elements was investigated and the optimum
working conditions of the sample measurement on ICP-MS
(Agilent-7500a) were reported. Appropriate isotope internal standards
were also used to improve the accuracy of mercury determination.
Optimal parameters for sampling digestion were also investigated. The
recovery of analytical procedure was examined by using a Certified
Reference Material (IAEA-CRM 359). The recommended procedure
was then applied for the quantitative determination of Cr, As, Se, Cd,
Hg, Pb in Lingzhi Mushroom capsule, and Philamine powder samples.
The reproducibility of sample measurement (average value between
94 and 102%) and the uncertainty of analytical data (less than 20%)
are acceptable.
Abstract: Large scale climate signals and their teleconnections can influence hydro-meteorological variables on a local scale. Several extreme flow and timing measures, including high flow and low flow measures, from 62 hydrometric stations in Canada are investigated to detect possible linkages with several large scale climate indices. The streamflow data used in this study are derived from the Canadian Reference Hydrometric Basin Network and are characterized by relatively pristine and stable land-use conditions with a minimum of 40 years of record. A composite analysis approach was used to identify linkages between extreme flow and timing measures and climate indices. The approach involves determining the 10 highest and 10 lowest values of various climate indices from the data record. Extreme flow and timing measures for each station were examined for the years associated with the 10 largest values and the years associated with the 10 smallest values. In each case, a re-sampling approach was applied to determine if the 10 values of extreme flow measures differed significantly from the series mean. Results indicate that several stations are impacted by the large scale climate indices considered in this study. The results allow the determination of any relationship between stations that exhibit a statistically significant trend and stations for which the extreme measures exhibit a linkage with the climate indices.
Abstract: There is no doubt that Internet technology is widely used by hotels and its demand is constantly booming. Hotels have largely adopted website information services through using different interactive tools, dimensions and attributes to achieve excellence in functionality and usability but these do not necessary equate with website effectiveness. One way to investigate the effectiveness of hotel website is from the perspective ofe-consumers. This exploratory research is to investigate the perceived importance of websites effectiveness of some selected independent small and medium-sized hotels (SMHs) located in Dubai, United Arab Emirates, from the perspective of Omanie-consumers by using non-random sampling method. From 400 questionnaire addressed to respondents in 27 organizations in Muscat the capital city of Oman, 173 are valid. Findings of this study assist SMHs management in Dubai with the reallocation of their resources and efforts in order to supportebusiness development and to sustain a competitive advantage.
Abstract: Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noise-free data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using an averaging methodology of bagging and boosting ensembles with 10 sub-learners in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy.
Abstract: In inspection and workpiece localization, sampling point data is an important issue. Since the devices for sampling only sample discrete points, not the completely surface, sampling size and location of the points will be taken into consideration. In this paper a method is presented for determining the sampled points size and location for achieving efficient sampling. Firstly, uncertainty analysis of the localization parameters is investigated. A localization uncertainty model is developed to predict the uncertainty of the localization process. Using this model the minimum size of the sampled points is predicted. Secondly, based on the algebra theory an eigenvalue-optimal optimization is proposed. Then a freeform surface is used in the simulation. The proposed optimization is implemented. The simulation result shows its effectivity.
Abstract: The purpose of this study was to suggest some optimal
waterfront scales around small rivers by reviewing domestic and
foreign survey reports about concept and relevant systems of the
ecological cities, analyzing the data collected from a survey about
scales and facilities of waterfront green zones around small rivers. The
questionnaire survey was conducted by sampling professional
designers, developers, the citizens living in the GunpoSanbon district
covered by no river system and the citizens living in such districts
covered by a river system. The question items were about need, uses,
scale and facilities of waterfront in common, and about satisfaction
with waterfront in case of citizen groups. In short, most of the subjects
in 5 groups preferred 10~20 wide waterfront green zone. And it is
judged that the results of this study about uses and facilities of the
waterfront green zone and its scales would provide for some basic data
useful to future waterfront green zone and urban development plans.
Abstract: In this paper, we suggest new product-type estimators for the population mean of the variable of interest exploiting the first or the third quartile of the auxiliary variable. We obtain mean square error equations and the bias for the estimators. We study the properties of these estimators using simple random sampling (SRS) and ranked set sampling (RSS) methods. It is found that, SRS and RSS produce approximately unbiased estimators of the population mean. However, the RSS estimators are more efficient than those obtained using SRS based on the same number of measured units for all values of the correlation coefficient.
Abstract: Time series analysis often requires data that represents
the evolution of an observed variable in equidistant time steps. In
order to collect this data sampling is applied. While continuous
signals may be sampled, analyzed and reconstructed applying
Shannon-s sampling theorem, time-discrete signals have to be dealt
with differently. In this article we consider the discrete-event
simulation (DES) of job-shop-systems and study the effects of
different sampling rates on data quality regarding completeness and
accuracy of reconstructed inventory evolutions. At this we discuss
deterministic as well as non-deterministic behavior of system
variables. Error curves are deployed to illustrate and discuss the
sampling rate-s impact and to derive recommendations for its wellfounded
choice.
Abstract: Support vector machines (SVMs) are considered to be
the best machine learning algorithms for minimizing the predictive
probability of misclassification. However, their drawback is that for
large data sets the computation of the optimal decision boundary is a
time consuming function of the size of the training set. Hence several
methods have been proposed to speed up the SVM algorithm. Here
three methods used to speed up the computation of the SVM
classifiers are compared experimentally using a musical genre
classification problem. The simplest method pre-selects a random
sample of the data before the application of the SVM algorithm. Two
additional methods use proximity graphs to pre-select data that are
near the decision boundary. One uses k-Nearest Neighbor graphs and
the other Relative Neighborhood Graphs to accomplish the task.
Abstract: In this paper, we consider a new particle filter inspired
by biological evolution. In the standard particle filter, a resampling
scheme is used to decrease the degeneracy phenomenon and improve
estimation performance. Unfortunately, however, it could cause the
undesired the particle deprivation problem, as well. In order to
overcome this problem of the particle filter, we propose a novel
filtering method called the genetic filter. In the proposed filter, we
embed the genetic algorithm into the particle filter and overcome the
problems of the standard particle filter. The validity of the proposed
method is demonstrated by computer simulation.
Abstract: The objective of this research is to study the people’s level of participation in activities of the community, their satisfaction towards the community, the attachment they have to the community, factors that influence the attachment, as well as the characteristics of the relationships of military families’ of the Royal Guards community of Dusit District. The method used was non-probability sampling by quota sampling according to people’s age. The determined age group was 18 years or older.
One set of a sample group was done per family. The questionnaires were conducted by 287 people. Snowball sampling was also used by interviewing people of the community, starting from the Royal Guards Community’s leader, then by 20 of the community’s well-respected persons. The data was analyzed by using descriptive statistics, such as arithmetic mean and standard deviation, as well as by inferential statistics, such as Independent - Samples T test (T-test), One-Way ANOVA (F-test), Chi-Square. Descriptive analysis according to the structure of the interview content was also used. The results of the research is that the participation of the population in the Royal Guards Community in various activities is at a medium level, with the average participation level during Mother’s and Father’s Days. The people’s general level of satisfaction towards the premises of the Royal Guards Community is at the highest level.
The people were most satisfied with the transportation within the community and in contacting with people from outside the premises. The access to the community is convenient and there are various entrances. The attachment of the people to the Royal Guards Community in general and by each category is at a high level. The feeling that the community is their home rated the highest average. Factors that influence the attachment of the people of the Royal Guards Community are age, status, profession, income, length of stay in the community, membership of social groups, having neighbors they feel close and familiar with, and as well as the benefits they receive from the community. In addition, it was found that people that participate in activities have a high level of positive relationship towards the attachment of the people to the Royal Guards Community. The satisfaction of the community has a very high level of positive relationship with the attachment of the people to the Royal Guards Community.
The characteristics of the attachment of military families’ is that they live in big houses that everyone has to protect and care for, starting from the leader of the family as well as all members. Therefore, they all love the community they live in. The characteristics that show the participation of activities within the community and the high level of satisfaction towards the premises of the community will enable the people to be more attached to the community. The people feel that everyone is close neighbors within the community, as if they are one big family.
Abstract: Abstract–Indoor air (VOCs) samples were collected
simultaneously from variety of indoors (e.g. living rooms, baby-s
rooms) and outdoor environments which were voluntarily selected
from the houses in which pregnant residents live throughout Ankara.
This is the first comprehensive study done in Turkey starting from
prenatal period and continued till the babies had one year old. VOCs
levels were measured over 76 homes. Air samples were collected in
Tenax TA sorbent filled tubes with active sampling method and
analyzed with Thermal Desorber and Gas Chromatography/Mass
spectrometry (TD-GC/MS). At the first sampling period in the baby-s
rooms maximum concentration of toluene was measured about
240.77μg.m-3 and in the living rooms maximum concentration of
naphthalene was 180.24μg.m-3. At the second sampling period in the
baby-s rooms maximum concentration of toluene was measured
about 144.97μg.m-3 and in the living rooms maximum concentration
of naphthalene was 247.89μg.m-3. Concentration of TVOCs in the
first period was generally higher than the second period.
Abstract: Contamination of heavy metals in tin tailings has
caused an interest in the scientific approach of their remediation. One
of the approaches is through phytoremediation, which is using tree
species to extract the heavy metals from the contaminated soils. Tin
tailings comprise of slime and sand tailings. This paper reports only
on the finding of the four timber species namely Acacia mangium,
Hopea odorata, Intsia palembanica and Swietenia macrophylla on
the removal of cadmium (Cd) and lead (Pb) from the slime tailings.
The methods employed for sampling and soil analysis are established
methods. Six trees of each species were randomly selected from a
0.25 ha plot for extraction and determination of their heavy metals.
The soil samples were systematically collected according to 5 x 5 m
grid from each plot. Results showed that the concentration of heavy
metals in soils and trees varied according to species. Higher
concentration of heavy metals was found in the stem than the
primary roots of all the species. A. Mangium accumulated the highest
total amount of Pb per hectare basis.
Abstract: The rangelands, as one of the largest dynamic biomes
in the world, have very capabilities. Regulation of greenhouse gases
in the Earth's atmosphere, particularly carbon dioxide as the main
these gases, is one of these cases. The attention to rangeland, as
cheep and reachable resources to sequestrate the carbon dioxide,
increases after the Industrial Revolution. Rangelands comprise the
large parts of Iran as a steppic area. Rudshur (Saveh), as area index of
steppic area, was selected under three sites include long-term
exclosure, medium-term exclosure, and grazable area in order to the
capable of carbon dioxide’s sequestration of dominated species.
Canopy cover’s percentage of two dominated species (Artemisia
sieberi Besser & Stipa barbata Desf) was determined via establishing
of random 1 square meter plot. The sampling of above and below
ground biomass style was obtained by complete random. After
determination of ash percentage in the laboratory; conversion ratio of
plant biomass to organic carbon was calculated by ignition method.
Results of the paired t-test showed that the amount of carbon
sequestration in above ground and underground biomass of Artemisia
sieberi Besser & Stipa barbata Desf is different in three regions. It,
of course, hasn’t any difference between under and surface ground’s
biomass of Artemisia sieberi Besser in long-term exclosure. The
independent t-test results indicate differences between underground
biomass corresponding each other in the studied sites. Carbon
sequestration in the Stipa barbata Desf was totally more than
Artemisia sieberi Besser. Altogether, the average sequestration of the
long-term exclosure was 5.842gr/m², the medium-term exclosure was
4.115gr/m², and grazable area was 5.975gr/m² so that there isn’t
valuable statistical difference in term of total amount of carbon
sequestration to three sites.
Abstract: It is important to predict yield in semiconductor test process in order to increase yield. In this study, yield prediction means finding out defective die, wafer or lot effectively. Semiconductor test process consists of some test steps and each test includes various test items. In other world, test data has a big and complicated characteristic. It also is disproportionably distributed as the number of data belonging to FAIL class is extremely low. For yield prediction, general data mining techniques have a limitation without any data preprocessing due to eigen properties of test data. Therefore, this study proposes an under-sampling method using support vector machine (SVM) to eliminate an imbalanced characteristic. For evaluating a performance, randomly under-sampling method is compared with the proposed method using actual semiconductor test data. As a result, sampling method using SVM is effective in generating robust model for yield prediction.
Abstract: Several works regarding facial recognition have dealt with methods which identify isolated characteristics of the face or with templates which encompass several regions of it. In this paper a new technique which approaches the problem holistically dispensing with the need to identify geometrical characteristics or regions of the face is introduced. The characterization of a face is achieved by randomly sampling selected attributes of the pixels of its image. From this information we construct a set of data, which correspond to the values of low frequencies, gradient, entropy and another several characteristics of pixel of the image. Generating a set of “p" variables. The multivariate data set with different polynomials minimizing the data fitness error in the minimax sense (L∞ - Norm) is approximated. With the use of a Genetic Algorithm (GA) it is able to circumvent the problem of dimensionality inherent to higher degree polynomial approximations. The GA yields the degree and values of a set of coefficients of the polynomials approximating of the image of a face. By finding a family of characteristic polynomials from several variables (pixel characteristics) for each face (say Fi ) in the data base through a resampling process the system in use, is trained. A face (say F ) is recognized by finding its characteristic polynomials and using an AdaBoost Classifier from F -s polynomials to each of the Fi -s polynomials. The winner is the polynomial family closer to F -s corresponding to target face in data base.
Abstract: The research aims to study the quality of surface water
for consumer in Samut Songkram province. Water sample were
collected from 217 sampling sites conclude 72 sampling sites in
Amphawa, 67 sampling sites in Bangkhonthee and 65 sampling sites
in Muang. Water sample were collected in December 2011 for
winter, March 2012 for summer and August 2012 for rainy season.
From the investigation of surface water quality in Mae Klong
River, main and tributaries canals in Samut Songkram province, we
found that water quality meet the type III of surface water quality
standard issued by the National Environmental Quality Act B.E.
1992. Seasonal variations of pH, Temperature, nitrate, lead and
cadmium have statistical differences between 3 seasons.
Abstract: The problem on the conservation programme of the Royal Thai Navy Sea Turtle Nursery, Phang-nga Province, Thailand is high mortality rate of juvenile green sea turtle (Cheloniamydas) on nursing period. So, during May to October 2012, postmortem examinations of juvenile green sea turtle were performed to determine the causes of dead. Fresh tissues of postmortem of 15 juvenile green sea turtles (1-3 months old) were investigated using paraffin section technique. The results showed normal ultrastructure of all tissue organs. These instances reviewed the health and stability of the environments in which juvenile green sea turtles live and concern for the survival rate. The present article also provides guidance for a review of the biology, guidelines for appropriate postmortem tissue, normal histology and sampling collection and procedures. The data also provides information for conservation of this endangered species in term of acknowledging and encouraging people to protect the animals and their habitats in nature.
Abstract: Linear approximation of point spread function (PSF) is a new method for determining subpixel translations between images. The problem with the actual algorithm is the inability of determining translations larger than 1 pixel. In this paper a multiresolution technique is proposed to deal with the problem. Its performance is evaluated by comparison with two other well known registration method. In the proposed technique the images are downsampled in order to have a wider view. Progressively decreasing the downsampling rate up to the initial resolution and using linear approximation technique at each step, the algorithm is able to determine translations of several pixels in subpixel levels.
Abstract: The purposes of this study are to study political
information exposure, politicians- perceptions, political attitudes and
political participations among people in Bangkok Metropolitan Area.
The sample consisted of 420 which were selected by using accidental sampling method. Questionnaires were administered to all of the
respondents to obtain the data for this research. T-test, one-way ANOVA and Pearson-s correlation coefficient were used to analyze the data. The findings are as follows: The difference in gender,
education, income and occupation has significantly effect upon political information exposures. The difference in age, income has
significantly effect upon politicians- perceptions. The difference in income has significantly effect upon political attitudes. The
difference in gender, income and occupation has significantly effect
upon political participations. There were a significantly relations between political information exposures, political attitudes, political
participations and between politicians- perceptions, political attitudes and political participations.