• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.337-347
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• 2010

Most sample surveys are designed to estimate reliable statistics for the whole population and for some large subpopulations. However, the research for small area estimation have been increasing in recent years because users demand to reliable estimates for smaller subpopulations like small areas or specific domains. In Korea, the Economically Active Population Survey(EAPS) is the main household survey that produces monthly unemployment rates for nationwide and 16 large areas (7 metropolitans and 9 provinces) in Korea. For county level estimation, direct estimators are not reliable because of the small sample sizes. We consider small area estimation of the county level unemployment ratesfrom the sample observations in EAPS. To do this, we use an area level model to "borrow strength" from the auxiliary information, such as administrative data and census data. The proposed method is based on the assumption of normality of the model errors in the area level model. The proposed method is compared with the other alternatives in terms of the estimated mean squared errors.

• Journal of Information Technology Services
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• v.21 no.3
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• pp.63-72
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• 2022

The extinction crisis of local cities, caused by a population density increase phenomenon in capital regions, directly causes the increase of vacant houses in local cities. According to population and housing census, Gunsan-si has continuously shown increasing trend of vacant houses during 2015 to 2019. In particular, since Gunsan-si is the city which suffers from doughnut effect and industrial decline, problems regrading to vacant house seems to exacerbate. This study aims to provide a foundation of a system which can predict and deal with the building that has high risk of becoming vacant house through implementing a data driven vacant house prediction machine learning model. Methodologically, this study analyzes three types of machine learning model by differing the data components. First model is trained based on building register, individual declared land value, house price and socioeconomic data and second model is trained with the same data as first model but with additional POI(Point of Interest) data. Finally, third model is trained with same data as the second model but with excluding water usage and electricity usage data. As a result, second model shows the best performance based on F1-score. Random Forest, Gradient Boosting Machine, XGBoost and LightGBM which are tree ensemble series, show the best performance as a whole. Additionally, the complexity of the model can be reduced through eliminating independent variables that have correlation coefficient between the variables and vacant house status lower than the 0.1 based on absolute value. Finally, this study suggests XGBoost and LightGBM based machine learning model, which can handle missing values, as final vacant house prediction model.

• Asian Journal for Public Opinion Research
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• v.11 no.3
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• pp.257-273
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• 2023

Conducting face-to-face surveys is difficult and cost prohibitive, necessitating a new attempt to build a probability-based panel in South Korea. Since 99.9% of adult Koreans own a mobile phone, mobile phone numbers provide a viable sampling frame. Random digit dialing (RDD) surveys were conducted August-December 2021. Of the 288,056 valid phone numbers dialed, 13,655 respondents between the ages of 19 and 69 completed a phone survey. These respondents were later invited by text message to join a panel; 3,202 of these (23.4% or 1.2% based on the number initially contacted) joined the panel. When compared to official government statistics like resident registration data, the census, or the Social Survey, this new probability-based panel can be said to be representative of the Korean population on the basis of age, gender, location, marital status, and household size after weighting is applied. However, even after weighting, panel members are more educated than the general population, white-collar workers and self-employed people are overrepresented, and blue-collar workers are underrepresented. As of February 2023, this panel has grown to 10,471 participants with plans to continue to invite more panel members in the same way. Based on the comparisons in this paper, we can regard this panel as a cost-effective, probability-based panel that may be used for various kinds of public opinion research, by researchers both within and outside of Korea. As we continue to refine and grow this panel, we hope it will become more widely used by researchers as well as provide a model for those building similar panels in other countries.

• Women's Health Nursing
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• v.28 no.4
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• pp.348-357
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• 2022

Purpose: This study aimed to identify maternal, infant, and perinatal mortality using the national population data of South Korea between 2018 and 2020, and to analyze mortality rates according to characteristics such as age, date of death, and cause of death in each group. This study updates the most recent study using 2009 to 2017 data. Methods: Analyses of maternal, infant, and perinatal mortality were done with data identified through the supplementary investigation system for cases of death from the Census of Population Dynamics data provided by Statistics Korea from 2018 to 2020. Results: Between 2018 and 2020, a total of 99 maternal deaths, 2,427 infant deaths, and 2,408 perinatal deaths were identified from 901,835 live births. The maternal mortality ratio was 11.3 deaths per 100,000 live births in 2018; it decreased to 9.9 in 2019 but increased again to 11.8 in 2020. The maternal mortality ratio increased steeply in women over the age of 40 years. An increasing trend in the maternal mortality ratio was found for complications related to the puerperium and hypertensive disorders. Both infant and perinatal mortality continued to decrease, from 2.8 deaths per 1,000 live births in 2018 to 2.5 in 2020 and from 2.8 in 2018 to 2.5 in 2020, respectively. Conclusion: Overall, the maternal, infant, and perinatal mortality statistics showed improvements. However, more attention should be paid to women over 40 years of age and specific causes of maternal deaths, which should be taken into account in Korea's maternal and child health policies.

• Health Policy and Management
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• v.13 no.2
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• pp.125-143
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• 2003

This study was conducted to estimate the future government budget in medical expenditures using for the low-income handicapped, because medical expenditures to the low-income handicapped is escalating in these days. It became a big problem not only to the central-government but also to the district-government because they have to subsidize a part of co-payment. This study was designed to project the future government budget using structural model. For the short-term projection, the structural model is stronger than the regression model. The data used for this study were the population projection data based on National Census Data(2000) of the National Statistical Office, the data of Ministry of Health & Welfare, and the data of National Health Insurance Corporation from November 2m to June 2001. The results of the study are summarized as follows: The future government budget in medical expenditures using to the low-income handicapped will be 15-18 billion Won in the year 2003, 16-23 billion Won in 2004, 18-30 billion Won in 2005, 19-38 billion Won in 2006 and 21-49 billion Won in 2007. It is predicted that they would be increasing rapidly. Therefore, the government budget in medical expenditures using for the low-income handicapped must be enlarged.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.473-476
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• 2003

Nowaday, Internet is doing the role of a large distributed information service tenter and various information and database servers managing it are in distributed network environment. However, the we have several difficulties in deciding the server to disposal input data depending on data properties. In this paper, we designed server mining mechanism and Intellectual data mining system architecture for the best efficiently dealing with input data pattern by using neural network among the various data in distributed environment. As a result, the new input data pattern could be operated after deciding the destination server according to dynamic binding method implemented by neural network. This mechanism can be applied Datawarehous, telecommunication and load pattern analysis, population census analysis and medical data analysis.

• Journal of Soil and Groundwater Environment
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• v.18 no.2
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• pp.19-26
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• 2013

This study developed the classification of National Soil Quality Monitoring Network (NSQM) and its site selection criteria to meet the recently established purposes of the NSQM. The NSQM were suggested by this study to classify into the six-purposes site groups from the current classification of land uses. The six purposes site groups were 1) intensive observation sites, 2) contaminant loading sites, 3) human activity sites, 4) background sites, 5) river soil sites, and 6) sites near the groundwater quality monitoring wells. Furthermore, this study developed the site selection criteria of NSQM utilizing the accumulated NSQM data, road traffic data, chemical emission data, census, soil information, and the literature related to soil quality variation due to contaminant loads. For selecting suitable sites for NSQM, this study used road traffic, chemical emission, the distance from the contaminant sources, and population information as specific criteria. The suggested site classification and criteria were appled for the current 100 NSQM sites for evaluation. Forty sites were met to the criteria suggested by this study, but sixty sites were not met to the criteria. However, some of the sixty sites also included the obscure sites that their addresses were not apparent to find them.

• The Bulletin of The Korean Astronomical Society
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• v.41 no.2
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• pp.63.2-63.2
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• 2016

One of the well-known problems in the lambda cold dark matter (${\Lambda}CDM$) models is a missing satellite problem. The slope of the mass function of low mass galaxies predicted by ${\Lambda}CDM$ models is much steeper than that based on the luminosity function of dwarf galaxies in the local universe. This implies that the model prediction is an overestimate of low mass galaxies, or that the current census of dwarf galaxies in the local universe may be an underestimate of dwarf galaxies. Previous studies of galaxy luminosity functions to address this problem are based mostly on the sample of galaxies brighter than Mv ~ -10 in the nearby galaxies. In this study we try to search for ultra-faint galaxies (UFDs), which are much fainter than those in the previous studies. We use multi-field HST ACS images of M60 in the archive. M60 is a giant elliptical galaxy located in the east part of the Virgo cluster, and hosts a large population of globular clusters and UCDs. Little is known about the dwarf galaxies in this galaxy. UFDs are much fainter, much smaller, and have lower surface brightness than normal dwarf galaxies so HST images of massive galaxies are an ideal resource. We present preliminary results of this search.

• Journal of the Korean Society of Costume
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• v.13
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• pp.151-159
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• 1989

The purpose of this study is to research into the relationship between the clothing purchase practices of high school girls in Seoul and their social stratification. For the survey of social stratification, the information of the monthly income of the households were extracted from the Annual Report of the City-Household in the Economic Planning Board : as for the occupations of patriarches, the groups of occupations were extracted from the Census of the Population & House in the Economic Planning Board and the types of occupations from the Korea Professional Dictionary in the Labor Ministry. The survey of clothing purchase practices is based on Ryan's Clothing: A Study in Human Behavior. The questionnaires were distributed to the seven girls' high schools in Seoul. The data from 354 respondents was analyzed by Pearsons'r, ANOVA and $x^2$ test. The Results were: 1. There was a significant relationship between clothing purchase practices variables and their social stratification. 2. There were differences in clothing purchase practices variables according to the social stratification. 3. There were significant relationships among the three clothing purchase practices variables.

• Land and Housing Review
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• v.5 no.3
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• pp.193-201
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• 2014

Around 80% of the 63 million people in the UK live in urban areas where demand for affordable housing is highest. Supply of new dwellings is a long way short of demand and with an average annual replacement rate of 0.5% more than 80% of the existing residential housing stock will still be in use by 2050. A high proportion of owner-occupiers, a weak private rental sector and lack of sustainable financing models render England's housing market one of the least responsive in the developed world. As an exploratory research the purpose of this paper is to examine the provision of social housing in the United Kingdom with a particular focus on England, and to set out implications for housing associations delivering sustainable community development. The paper is based on an analysis of historical data series (Census data), current macro-economic data and population projections to 2033. The paper identifies a chronic undersupply of affordable housing in England which is likely to be exacerbated by demographic development, changes in household composition and reduced availability of finance to develop new homes. Based on the housing market trends analysed in this paper opportunities are identified for policy makers to remove barriers to the delivery of new affordable homes and for social housing providers to evolve their business models by taking a wider role in sustainable community development.