• Korea journal of population studies
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• v.26 no.2
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• pp.111-145
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• 2003

This paper attempts to explore recent socio-demographic changes of the ethnic Korean population in Yanbian autonomous prefecture. Due to rapid decrease in the level of fertility and population ageing, Korean minority society in China has been in a process of profound transition after the introduction of the market economy and establishment of diplomatic relations between South Korea and China. The changes in demographic behaviors and in the structure of population appear to be much faster among Koreans than Hans. Results from the 2000 population census reveal that the Korean population in Yanbian, where ethnic Koreans are most densely populated in China, has been in a decreasing trends in absolute numbers and in its proportion to the total population. The growing tendency of regional mobility for work and for marriage, rapid expansion of residential areas, serious crisis of ethnic schools of Korean community, and weakening social integration and ethnic identification of Koreans in Yanbian are discussed in this study. It is expected that socio-demographic transition of Korean society in Yanbian will be even more drastic over the coming decades. The rapid changes in demographic behaviors and in the structure of population has major consequences and implications for every sphere of human life, and will present enormous challenges for the status of Korean minority society in China. Along with various statistical data on Yanbian, micro-level data as well as published reports from the 1990 Chinese population census for Yanbian and the 2000 Chinese population census are analyzed in this study. In addition to sex ratios and age ratios, various indices are calculated to analyze the characteristics and accuracy of the data from the 1990 and 2000 population censuses of China.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.464-469
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• 2013

After city of Busan has been entered to the aging society in 2000, the city has the highest aging rate among 7 representative cities in 2011. Moreover, while entire population and number of average household are decreasing, over 65 years old of elderly population is rapidly increasing. So, it is possible to enter the super-aged society, where aging rate would be about 20% after 2020. The purpose of this study is that older housing-related analysis is consisted of dong-unit, and this led microscopic analysis has become necessary. Surveys from 2000 through 2010, census aggregate (output area) unit of spatial analysis was conducted. Take advantages of this, aging population and area, soaring area, high-density areas, such as the region of interest were primary extracted, and microscopic location and spatial distribution patterns were analyzed. Upon analysis, aging population is concentrated in the city and adjacent area, the highlands, and 10 years of increasing rate was more than 30 times in certain aggregate. Regarding the characteristic of these areas, the original city center, Busan, especially concentrated and intensified in aging population. Also, 2000 to 2010, the overall distribution pattern of Busan has identified aging population that is increasingly being distributed. This is the result, which is confronted with previous research result. Entering a super aged-society for the future is accordance with migration of social costs and improve the quality of life of elderly. And this could be the basic information to use the spatial dimension for the corresponding.

• Journal of Korea Port Economic Association
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• v.34 no.4
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• pp.53-68
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• 2018

This paper analyzes comparatively business performance indicators and determinants of small and medium sized shipping logistics companies in Korea, using 2015 economic census data. For this purpose, this study estimates various business performance indicators according to 2015 small and medium sized companies classification standards, including operating income to sales and gross value-added to sales. In addition, this study analyzes determinants of business performance using generalized least squares models. The results indicate that average sales, operating income and value-added, sales and operating income per worker, operating income to sales, and material cost to sales of large sized companies are higher than those of small and medium sized companies. The business performance indicators differ by industry and size. Moreover, the determinants of business performance are analyzed in terms of the unemployment rate (-), number of employees (-), sales (+), labor cost ratio (+), and labor cost per employee (-) and the impacts of the individual explanatory variables based on elasticity are different. Finally, this quantitative information could be used to improve the business performance of domestic shipping logistics companies.

• Korean Journal of Ichthyology
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• v.34 no.1
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• pp.44-56
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• 2022

Fish fauna was observed off the coast of Busan (Cheongsapo) and Ulsan (Bangeojin) using underwater visual census from November 2016 to October 2017. A total of 1,486 individuals of 25 species in Cheongsapo and 3,859 individuals of 31 species were identified in Bangeojin. Dominant species in the number of individuals were Trachurus japonicus (20.9%), Halichoeres tenuispinis (12.6%), and Chromis notata (11.9%) in Cheongsapo, Siganus fuscescens (42.0%), Pempheris japonica (8.4%), and Chromis notata (8.0%) in Bangeojin. There was no significant difference in the species composition of Cheongsapo and Bangeojin but spring vs. summer, spring vs. autumn, summer vs. winter, autumn vs. winter showed a significant difference. Contribution species of seasonal differences were commonly high rates by Halichoeres tenuispinis and Parajulis poecilepterus. Of the total 38 species, 17 (44.7%) temperate, 6 (15.8%) tropical, and 15 (39.5%) subtropical species observed coastal waters off Cheongsapo and Bangeojin.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.21-29
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• 2023

In this paper, we propose an AI-based system for automatically classifying industry and occupation codes in the population census. The accurate classification of industry and occupation codes is crucial for informing policy decisions, allocating resources, and conducting research. However, this task has traditionally been performed by human coders, which is time-consuming, resource-intensive, and prone to errors. Our system represents a significant improvement over the existing rule-based system used by the statistics agency, which relies on user-entered data for code classification. In this paper, we trained and evaluated several models, and developed an ensemble model that achieved an 86.76% match accuracy in industry and 81.84% in occupation, outperforming the best individual model. Additionally, we propose process improvement work based on the classification probability results of the model. Our proposed method utilizes an ensemble model that combines transfer learning techniques with pre-trained models. In this paper, we demonstrate the potential for AI-based systems to improve the accuracy and efficiency of population census data classification. By automating this process with AI, we can achieve more accurate and consistent results while reducing the workload on agency staff.

• Asian Journal of Turfgrass Science
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• v.9 no.2
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• pp.131-136
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• 1995

The herb, shrub, understory and canopy strata, which arbitrarily delineated by size classes, were sampled separately. The former one were sampled by the pin-point quadrat method. And remaining three by size quadrats, diversity (H= =$\Sigma$ Pi log Pi) of of each stratum was estimated for each set of census data. Species diversity within a stratum was independent of sample plot size above a minimum cumulative area. Diversity based on plotless and plot samples could he determined by the same equation, and by pooling the data needed to estimate diversity of each stratum.

• 대한예방의학회:학술대회논문집
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• 2004.10a
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• pp.46.2-47
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• 2004

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.107-108
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• 2015

In this project, all available databases of molecular and gas-dust clouds in the Galaxy were cross-identified by taking into account available properties, including position, angular dimensions, velocity, density, temperature and mass. An initial list of about 7000 entries was condensed into a cross-identified all-sky catalogue containing molecular and gas-dust clouds. Some relationships were studied between the main physical features of clouds. Finally, we prepared a complex observing program and address future work for filling in the gaps.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.781-790
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• 1999

In this paper we consider estimation of cancer incidence rates for local areas. The raw estimates usually are based on small sample sizes and hence are usually unreliable. A hierarchical Bayes generalized linear model is used which connects the local areas thereby enabling one to 'borrow strength' Random effects with pairwise difference priors model the spatial structure in the data. The methods are applied to cancer incidence estimation for census tracts in a certain region of the state of New York.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.91-96
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• 2015

In this study, we introduce robust face recognition system with illumination variation realized with the aid of CT preprocessing method. As preprocessing algorithm, Census Transform(CT) algorithm is used to extract locally facial features under unilluminated condition. The dimension reduction of the preprocessed data is carried out by using $(2D)^2$PCA which is the extended type of PCA. Feature data extracted through dimension algorithm is used as the inputs of proposed radial basis function neural networks. The hidden layer of the radial basis function neural networks(RBFNN) is built up by fuzzy c-means(FCM) clustering algorithm and the connection weights of the networks are described as the coefficients of linear polynomial function. The essential design parameters (including the number of inputs and fuzzification coefficient) of the proposed networks are optimized by means of artificial bee colony(ABC) algorithm. This study is experimented with both Yale Face database B and CMU PIE database to evaluate the performance of the proposed system.