• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.9
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• pp.139-147
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• 2014

In this paper, we present a novel method for simultaneous detection and tracking of multiple objects using dual-layer particle filtering. The proposed dual-layer particle sampling (DLPS) algorithm consists of parent-particles (PP) in the first layer for detecting multiple objects and child-particles (CP) in the second layer for tracking objects. In the first layer, PPs detect persons using a classifier trained by the intersection kernel support vector machine (IKSVM) at each particle under a randomly selected scale. If a certain PP detects a person, it generates CPs, and makes an object model in the detected object region for tracking the detected object. While PPs that have detected objects generate CPs for tracking, the rest of PPs still move for detecting objects. Experimental results show that the proposed method can automatically detect and track multiple objects, and efficiently reduce the processing time using the sampled particles based on motion distribution in video sequences.

• Communications for Statistical Applications and Methods
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• v.23 no.1
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• pp.47-55
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• 2016

Stratified cluster sampling has been widely used for effective parameter estimations due to reductions in time and cost. The probability proportional to size (PPS) sampling method is used when the number of cluster element are significantly different. However, simple random sampling (SRS) is commonly used for simplicity if the number of cluster elements are almost the same. Also it is known that the ratio estimator produces a good performance when the total number of population elements is known. However, the two stage cluster estimator should be used if the total number of elements in population is neither known nor accurate. In this study we suggest a composite estimator by combining the ratio estimator and the two stage cluster estimator to obtain a better estimate under a certain population circumstance. Simulation studies are conducted to compare the superiority of the suggested estimator with two other estimators.

• Communications for Statistical Applications and Methods
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• v.15 no.6
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• pp.883-897
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• 2008

This paper provides correct informations inflecting the present situation using the sample design in population that the National Statistical Office puts in operation of the mining and manufacturing industry statistical survey in 2006. This paper proposes new sampling design which is able to grasp business fluctuations and provide basic data for the rearing policy and management of the material industry and components industry. These sample design are the modified cut-off method and multivariate Neyman allocation using principal components and sampling method is the probability proportional systematic sampling.

• Survey Research
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• v.5 no.1
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• pp.103-130
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• 2004

Main monthly household surveys conducted by Korea National Statistical Office are economically active population survey(EAPS) and household income and expenditure survey(HIES). Samples of these two surveys are redesigned every 5 years based on Census. This paper is about sample redesign of household survey conducted in 2002 based on 2000 Census. Main improvements of 2002 sample redesign are the introduction of rotation sampling system, the expansion of HIES survey area from urban to whole country and the foundation of basement to make small area estimation for the unemployment statistics. Also the number of sample households within a enumeration district(ED) is reduced from 24 to 20. That makes it possible to select more ED samples which provides better precision for EAPS and HIES. To select representative samples for the population, different classification index is used for each metropolitan area and provinces.

• Journal of Integrative Natural Science
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• v.7 no.3
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• pp.208-213
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• 2014

National-wide and/or large scale sample surveys generally use complex sample design. Traditional Pearson chi-square test is not appropriate for the categorical complex sample data. Rao-Scott suggested an adjustment method for Pearson chi-square test, which uses the average of eigenvalues of design matrix of cell probabilities. This study is to compare the efficiency of Rao-Scott first order adjusted test to Wald test for homogeneity between two populations using 2009 Gyeongnam regional education offices's customer satisfaction survey (2009 GREOCSS) data. The 2009 GREOCSS data were collected based on stratified three-stage cluster sampling with probability proportional to size. The empirical results show that the Rao-Scott adjusted test statistic using only the variances of cell probabilities is very close to the Wald test statistic, which uses the covariance matrix of cell probabilities, under the 2009 GREOCSS data based. However it is necessary to be cautious to use the Rao-Scott first order adjusted test statistic in the place of Wald test because its efficiency is decreasing as the relative variance of eigenvalues of the design matrix of cell probabilities is increasing, specially more when the number of degrees of freedom is small.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.669-679
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• 2010

A sample survey design is suggested for the service satisfaction evaluation of regional education offices based on the sample size of 2009 Gyeongnam regional education offices's customer satisfaction survey. The sample design is developed to fit the goal of evaluation of individual regional offices and allocate at least the minimum sample size to each city or county in Gyeongnam to achieve the goal of the survey. The population is stratified according to the regions and the types of schools, and the sample of schools is selected with proportional to the size of classes within each stratum. Finally, each sample student is selected according to two-stage cluster sampling within each sample school. Weighting averages, weighting totals and so on can be evaluated for analysis purposes. Their variance estimates can be evaluated using re-sampling methods like BBR, Jackknife, linearization-substitution methods, which are generally used for the data from a complex sample.

• Journal of the Korean Society of School Health
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• v.22 no.1
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• pp.49-59
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• 2009

Purpose: The aim of this study was to identify the factors related with the intention of smoking abstinence among elementary students in a metropolitan city in Korea. Methods: All the elementary schools in the city were stratified by region, and then schools as a primary sampling units (PSU) were selected by probability proportional to size (PPS) sampling. One class per grade was sampled randomly from 5th and 6th grade in the sampled schools from October to December in 2004. The students completed a standardized self-administered questionnaire anonymously. A total number of 1,712 respondents who did not smoke was included in the final analysis. The dependent variable was an intention of smoking in the future, and it was dichotomized into 'absolutely confident in smoking abstinence' and 'others'. The risk of non-absolute confidence in smoking abstinence was calculated with simple and multiple logistic regression, which were conducted with STATA 9.0 by a design-based analysis considering strata variable, PSU, and sampling weight. Results: In the final model of multiple logistic regression analysis, those who were more likely to have non-absolute confidence in smoking abstinence were male students (OR=2.66, p<0.001); barely attending religious services (OR=3.32, p=0.002) or having no religion (OR=1.95, p=0.027); exposure to environmental tobacco smoke outside home 1${\sim}$2 days per week (OR=1.60, p=0.013); having friends who smoked (OR=1.93, p=0.011); non-absolute confidence in refusing to smoke (OR=5.35, p<0.001); having relatively less negative attitude (OR=2.88, p<0.001), positive attitude (OR=2.35, p<0.001), and indifference (OR=4.05, p=0.034) toward peer smoking; not good relationship with mother (OR=1.52, p=0.016). Conclusion: The factors related with non-absolute confidence in smoking abstinence were coincided with those of smoking among children. The results of this study suggest the smoking prevention education should be applied to the children more actively, especially who are not confident in smoking abstinence in the future.

• Journal of Technology Innovation
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• v.17 no.2
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• pp.1-23
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• 2009

The Survey on the Industrial Research and Development(R&D) is the primary source of information on R&D performed by Korea industrial sector. The results of the survey are used to assess trends in R&D expenditures. Government agencies, corporations, and research organizations use the data to investigate productivity determinants, formulate tax policy, and compare individual company performance with industry averages. Recently, Korea Industrial Technology Association(KOITA) has collected the data by complete enumeration. Koita has, currently, considered sample survey because the number of R&D institutions in industry has been dramatically increased. This study develops survey design for the industrial research and development(R&D) statistics by introducing a sample survey. Companies are divided into 8 groups according to the amount of R&D expenditures and firm size or type. We collect the sample from 24 or 8 sampling strata and compare the results with those of complete enumeration survey. The estimates from 24 sampling strata are not significantly different to the results of complete enumeration survey. We propose the survey design as follows: Companies are divided into 11 groups including the companies of which R&D expenditures are unknown. All large companies are included in the survey and medium and small companies are sampled from 70% and 3%. Simple random sampling (SRS) is applied to the small company partition since they show uniform distribution in R&D expenditures. The independent probability proportionate to size (PPS) sampling procedure may be applied to those companies identified as 'not R&D performers'. When respondents do not provide the requested information, estimates for the missing data are made using imputation algorithms. In the future study, new key variables should be developed in survey questionnaires.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.755-758
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• 2016

Background: There is little information about the objectivity of posttraumatic growth experienced by cancer patients. So, the aim of present study was to investigate the viewpoints of family caregivers regarding posttraumatic growth in cancer patients. Materials and Methods: This descriptive study was conducted in one referral medical center in East Azerbaijan Province in northwest of Iran. 120 primary family caregivers of cancer patients participated with a convenience sampling method. The Posttraumatic Growth Inventory (PTGI) and Perception about Prognosis Scale (PPS) were applied for data collection with analysis performed using SPSS statistical software. Results: Family caregivers believed that their patients had a good prognosis (score 3.95 from 5). The total score of PTGI was 60.7 (SD=18.8) that indicates a moderate level of growth as reported by family caregivers. Conclusions: Family caregivers of cancer patients have incorrect viewpoints about the prognosis of their patients and reported moderate levels of growth. These findings showed that posttraumatic growth among cancer patients is an objective phenomenon.

• Journal of Preventive Medicine and Public Health
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• v.39 no.4
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• pp.317-324
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• 2006

Objectives: This study was conducted to estimate the unbiased smoking prevalence and its standard errors among adolescents in a large city in Korea, by design-based analysis. Methods: All the students in Daegu city were stratified by grade, gender and region, and then schools as primary sampling units (PSU) were selected by probability proportional to size (PPS) sampling. One or two classes were sampled randomly from each grade, from 5th grade in elementary schools to the 3rd grade in high schools. The students anonymously completed a standardized self-administered questionnaire from October to December 2004. The total number of respondents was 8,480 in the final analysis, excluding the third graders in the general high schools because of incomplete sampling. The sampling weight was calculated for each student after post-stratification adjustment, with adjustment being made for the missing cases. The data were analyzed with Stata 8.0 with consideration of PSU, weighting and the strata variables. Results: The smoking prevalence (%) and standard errors for male students from the fifth grade in elementary schools to the second grade in high schools were $0.93{\pm}0.47,\;1.83{\pm}0.74,\;3.16{\pm}1.00,\;5.12{\pm}1.02,\;10.86{\pm}1.13,\;15.63{\pm}2.44\;and\;17.96{\pm}2.67$, and those for the female students were $0.28{\pm}0.28,\;1.17{\pm}0.73,\;3.13{\pm}0.60,\;1.45{\pm}0.58,\;3.94{\pm}0.92,\;8.75{\pm}1.86\;and\;10.04{\pm}1.70$, sequentially. Conclusions: The smoking prevalence from this study was much higher than those from the other conventional studies conducted in Korea. The point estimates and standard errors from the design-based analysis were different from those of the model-based analysis. These findings suggest the importance of design-based analysis to estimate unbiased prevalence and standard errors in complex survey data and this method is recommended to apply to future surveys for determining the smoking prevalence for specific population.