• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.165-181
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• 2010

This paper presents some chain ratio-type estimators for estimating finite population variance using two auxiliary variables in two phase sampling set up. The expressions for biases and mean squared errors of the suggested c1asses of estimators are given. Asymptotic optimum estimators(AOE's) in each class are identified with their approximate mean squared error formulae. The theoretical and empirical properties of the suggested classes of estimators are investigated. In the simulation study, we took a real dataset related to pulmonary disease available on the CD with the book by Rosner, (2005).

• Structural Engineering and Mechanics
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• v.32 no.1
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• pp.55-69
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• 2009

A quasi ideal importance sampling simulation method combined in the conditional expectation is proposed for the structural reliability estimation. The quasi ideal importance sampling joint probability density function (p.d.f.) is so composed on the basis of the ideal importance sampling concept as to be proportional to the conditional failure probability multiplied by the p.d.f. of the sampling variables. The respective marginal p.d.f.s of the ideal importance sampling joint p.d.f. are determined numerically by the simulations and partly by the piecewise integrations. The quasi ideal importance sampling simulations combined in the conditional expectation are executed to estimate the failure probabilities of structures with multiple failure surfaces and it is shown that the proposed method gives accurate estimations efficiently.

• Journal of the Korean Data and Information Science Society
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• v.23 no.4
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• pp.677-682
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• 2012

There are lots of sampling design which is determined for sample survey in various fields. Especially, it is important problem for clinical data because basic characteristic variables by group which consist of experiment group and control group in population should be reflect to sample. Therefore, frequencies, center scales and dispersion scales of variables by group in population should be similar in sample. But usual sampling design is very complicate so it is difficult to use in practice for researcher. In this paper, we consider the sampling method using simulation. We applied the proposed method to colon cancer data from a hospital. We compare basic characteristic variables between population and sample with mean, frequency and statistic hypothesis test.

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.4
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• pp.602-607
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• 1993

Concept of the comfort and fitness becomes a major concern in the basic function of the ready-made clothes. This research was performed to classify and characterize Korean adult males anthropometrically. Sample size was 1290 subjects and their age range was from 19 to 54 years old. Sampling was carried out by the stratified sampling method. 75 variables in total were applied to classify the bodytypes. Data were analyzed by the multivariate method, especially factor and cluster analysis. The high factor loading items extracted by factor analysis were based to determine the variables of the cluster analysis for the similar bodytypes respectively. In the part of the lower body, 14 variables from the data were applied to classify the bodytypes of lower part by Ward's minimum variance method. The group fanning a cluster were subdivided into 5 sets by cross-tabulation extracted by the hierarchical cluster analysis. Type 3 and 4 in lower body were composed of the majority of 53.1% of the subjects. The Korean adult males had relatively well-balanced in lower body.

• 한국데이터정보과학회:학술대회논문집
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• 2004.04a
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• pp.39-50
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• 2004

The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud dection, data reduction and variable screening, category merging, etc. CHAID(Chi-square Automatic Interaction Detector) uses the chi-squired statistic to determine splitting and is an exploratory method used to study the relationship between a dependent variable and a series of predictor variables. In this paper we propose CHAID algorithm by cube-based proportional sampling and explore CHAID algorithm in view of accuracy and speed by the number of variables.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.803-816
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• 2004

The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud dection, data reduction and variable screening, category merging, etc. CHAID uses the chi-squired statistic to determine splitting and is an exploratory method used to study the relationship between a dependent variable and a series of predictor variables. In this paper we propose CHAID algorithm by cube-based proportional sampling and explore CHAID algorithm in view of accuracy and speed by the number of variables.

• Journal of Korean Institute of Industrial Engineers
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• v.30 no.3
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• pp.205-212
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• 2004

This paper proposes the variables repetitive group sampling plan where the quality characteristic following normal distribution has upper or lower specification limit. The problem is formulated as a non-linear programming problem where the objective function to minimize is the average sample number and the constraints are related to lot acceptance probabilities at acceptable quality level (AQL) and limiting quality level (LQL) under the operating characteristic curve. Sampling plan tables are constructed for the selection of parameters indexed by AQL and LQL in the cases of known standard deviation and unknown standard deviation. It is shown that the proposed sampling plan significantly reduces the average sample number as compared with the single or the double sampling plan.

• Journal of the Korean Society of Safety
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• v.11 no.4
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• pp.72-78
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• 1996

The breakthrough curves of a sampling tube were studied to predict the service life of a respirator cartridge for organic vapors. The fixed bed adsorption model was applied to respirator cartridge and it's variables were calculated from tile experiment of sampling tube. By the experiment and simulation, it was possible to predict the service life of a respirator cartridge, however, not adequate at low $CCl_4$ concentration less than 700ppm and at high air humidify. The breakthrough curves of sampling tube were irregular compare to that of respirator cartridge due to .packing density.

• Journal of Korea Water Resources Association
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• v.44 no.4
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• pp.295-304
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• 2011

For effective water quality management, it is necessary to secure reliable water quality information. There are many variables that need to be included in a comprehensive practical monitoring network : representative sampling locations, suitable sampling frequencies, water quality variable selection, and budgetary and logistical constraints are examples, especially sampling location is considered to be the most important issues. Until now, monitoring network design for water quality management was set according to the qualitative judgments, which is a problem of representativeness. In this paper, we propose network design system for optimal water quality monitoring using the scientific statistical techniques. Network design system is made based on the SAS program of version 9.2 and configured with simple input system and user friendly outputs considering the convenience of users. It applies to Excel data format for ease to use and all data of sampling location is distinguished to sheet base. In this system, time plots, dendrogram, and scatter plots are shown as follows: Time plots of water quality variables are graphed for identifying variables to classify sampling locations significantly. Similarities of sampling locations are calculated using euclidean distances of principal component variables and dimension coordinate of multidimensional scaling method are calculated and dendrogram by clustering analysis is represented and used for users to choose an appropriate number of clusters. Scatter plots of principle component variables are shown for clustering information with sampling locations and representative location.

• Journal of Environmental Health Sciences
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• v.25 no.3
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• pp.36-43
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• 1999

The present study was performed to investigate biodegradation rate of dichlorvos and methidathion. In the biodegradation test of two pesticides by the modified river die-away method from June 17 to August 22, 1998, the biodegradation rate constants and half-life were determined in Nakdong(A) and Kumho River(B). Biodegradation rate of dichlorvos was 4.51% in A sampling point, 6.88% in B sampling point after 7 days. Biodegradation rate constants and half-life of dichlorvos were 0.0066 and 105 days in A sampling point, 0.0102 and 67.9 days in B sampling point, respectively. Biodegradation rate of methidathion was 23% in A sampling point, 36% in B sampling point after 7 days. Biodegradation rate constants and half-life of methidathion were 0.0377 and 18.4 days in A sampling point, 0.0641 and 10.8 days in B sampling point, respectively. Biodegradation rate of methidathion was faster than that of dichlorvos. This suggested that the difference in biodegradation of pesticides was due to difference in the water quality and standard plate counts in the Nackdong and Kumho Rivers. The result of correlation analysis between biodegradation rate constants of the pesticides and water quality(DO, BOD, SS, ABS, NH$_3$-N, and NO$_3$-N) showed significant correlation with BOD, SS and NH$_3$-N at the 5% significant level. A significant linear equation was obtained from regression analysis at the 5% significant level, whereas, dependent variables were BOD, SS and NH$_3$-N, and the biodegradation rate constant was independent variable. It is suggested that dichlorvos will be mainly degraded by hydrolysis, and for methidathion was both hydrolysis and biodegradation. A significant QSAR equation was obtained from regression analysis at the 10% significant level, whereas, dependent variable is biodegradation rate constants of BPMC, chlorothalonil, dichlorvos and methidathion, vapor pressures, partition coefficients and water solubilities of the pesticides are independent variables. Also, a significant linear equation was obtained from regression analysis at the 1% significant level, whereas, dependent variable is biodegradation rate constants of BPMC, chlorothalonil, dichlorvos and methidathion, hydrolysis rate constants of the pesticides are independent variables. It is suggested that the pesticides will be degraded by main degradation factor when the pesticides was affected both hydrolysis and biodegradation.