• Korea journal of population studies
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• v.16 no.2
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• pp.125-139
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• 1993

Korea has successfully achieved a lowered fertility level owing to the strong population control policy and effective family planning program. Along with fertility decline and decreased number of children in family, average number of household members has decreased and nontraditional households such as one person household and households composed of unrelated individuals have prolifirated, even though the absolute number of them are found minimal in Korea. However in recent years several data and survey results suggest that one person households are gradually in the increasing trend. The study aimed at investigating the real state of one person households in Korea and next analyzing the proportional distribution of one person households by a few socioeconomic characteristics, thus providing basic for eatablishing far-singhted population and social welfare policy in the future. Korea has experienced high growth rate of economy through government-led development plans starting from the 1960s. During the past three decades, Korea has shifted from the agricultural state to the industrialized one. In compliance with the economic growth, urbanization and industrialization have brought about rural-to-urban migration and a great bulk of young population migrated to urban areas, who are seeking for educational and job opportunities. Korean society has also been under drastic change in every aspect of life involving norms, tradition, and attitude, etc. Therefore, in spite of the prejudice on 'living alone' still remaining, young people gradually leave parents and home, and further form nontraditional households in urban areas. Current increase in the number of one person households is partly attributable to the increase in high female educational attainment and female participation in economic activities. As the industrial structure in Korea changes from primary into secondary and tertiary industries, job opportunities for service/sales and manufacturing are opened to young female labor force in the process of industrialization. Contrary to the formation of one person households by young people, the aged single households are composed when children in family leave one by one because of marriage, education, employment. In particular, a higher proportion of aged female single households occur in rural areas due to the mortality difference by sex. Based on the data released form the 1990 Population and Housing Census and National Fertility and Family Health Survey in 1985 and 1991, the study tried to examine the state of one person households in Korea. According to Census data, the number of one person households increased to 1, 021, 000 in 1990, comprising 9.0 percent of total households. And the survey reveal that among total 11, 540 households, 8.0 percent, 923 households, are composed of one person households. Generally, the proportion of female single households is greater than that of male ones, and a big proportion of one person households is concentrated in the 25-34 age bracket in urban areas and 65 years and more in rural areas. It is shown than one person householders in urban areas have higher educational attainment with 59.2 percent high schooling and over in 1991, Job seeking proved to be the main reason for leaving home and forming one person households. The number of young female single households with higher education and economic self-reliance are found nil and the study did not allow to analyze the causal realtionship between female education and employment and one person household formation. However more research and deep analysis on the causal facors on one person household formation using statistical method are believed to be necessary.

• Korean Chemical Engineering Research
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• v.57 no.2
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• pp.274-282
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• 2019

In recent years, big data analysis has been expanded to include automatic control through reinforcement learning as well as prediction through modeling. Research on the utilization of image data is actively carried out in various industrial fields such as chemical, manufacturing, agriculture, and bio-industry. In this paper, we applied NASNet, which is an AutoML reinforced learning algorithm, to DeepU-Net neural network that modified U-Net to improve image semantic segmentation performance. We used BRATS2015 MRI data for performance verification. Simulation results show that DeepU-Net has more performance than the U-Net neural network. In order to improve the image segmentation performance, remove dropouts that are typically applied to neural networks, when the number of kernels and filters obtained through reinforcement learning in DeepU-Net was selected as a hyperparameter of neural network. The results show that the training accuracy is 0.5% and the verification accuracy is 0.3% better than DeepU-Net. The results of this study can be applied to various fields such as MRI brain imaging diagnosis, thermal imaging camera abnormality diagnosis, Nondestructive inspection diagnosis, chemical leakage monitoring, and monitoring forest fire through CCTV.

• Journal of Technologic Dentistry
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• v.37 no.4
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• pp.271-284
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• 2015

Purpose: The purpose of this study was to examine the usage of CAD/CAM, which is one of dental technologist duties, in an effort to look for any possible changes in the usage of CAD/CAM. It's specifically meant to compare the results of this study with those of Lee Jong-do, Park Kwang-Sig(2011)'s study in March, 2011, to determine if there were any changes over the past four years. The selected variables that were investigated were the ownership of CAD/CAM, awareness of it, the route of acquiring the first information on it, the merits and demerits of its usage, usage experience and educational experience about it. Methods: An online survey was conducted on the dental technologists who worked in urban communities including metropolitan cities to find out the usage of CAD/CAM in 2015 from July 15 to 31, 2015, after existing questionnaire items were modified. The collected data were analyzed by IBM SPSS statistics 22.0, and statistical data on frequency, percentage, mean and standard deviation for each item were obtained. To figure out the characteristics of the subjects and the relationship between their occupational characteristics and the usage of CAD/CAM, crosstabs, independent-samples t-test and one-way ANOVA were utilized. As for the usage of CAD/CAM in 2011, the results of Lee Jong-do, Park Kwang-Sig(2011)'s study were selected, and then a comparative analysis was made. The level of significance was all set at .05. Total 250 questionnaires were distributed to them, and 190(76.0%) were returned. After excluding 23 whose answers were uncertain or seemed to lack reliability, total 167(66.8%) were used in final analysis. Results: As a result of analyzing the usage of CAD/CAM that was one of dental technologist duties, there was a great increase in the ownership of CAD/CAM in their workplaces from 2.4 percent in 2011 to 71.7 percent in 2015, and there was an improvement in awareness about it and the necessity of its usage as well. In 2011, the Internet and mass media were the most common route that they got to know about it. They had a strong tendency to acquire related knowledge through education in 2015, and there were some changes in the products that they used or preferred. In both years, the great merit of CAD/CAM was the simplified manufacturing process of restoration, and it had another great advantages in 2015 such as the improved quality of restoration or improved environments for dental technology. Concerning disadvantages, high price was a big problem in 2011. In 2015, not only price but the burden of material costs, frequent breakdown, poor demand among dental clinics and a lack of CAD/CAM professionals were pointed out a lot. In the future, this researcher intends to make research to seek ways of improving CAD/CAM professionals. Conclusion: There was more awareness of CAD/CAM in 2015 than in 2011 when the changes in awareness of it were analyzed, and the finding suggest the necessity of sustained education and concern.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.274-280
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• 2017

The smart-car industry has emerged as the important variable that will decide the future industrial contour of the automotive industry, together with commercialization of electronic vehicles, connected cars, infotainment, telematics, and the autonomous/self-driving car. This study analyzes the strategic position of platform companies and car manufacturers that would determine the future of the smart-car market. The findings of this study show that despite the entry barriers in industrial factors, such as economies of scale, the industrial infrastructure, and global production networks, and technical factors like exclusive head-sector information, car manufacturers may be deprived of their industrial leadership by platform companies with map and user data, big data capabilities, and user interface experience if they lag behind ICT innovation. This insight is based on the emerging importance of software and platforms, and the simplification of car structures, proven by the successful commercialization of electronic vehicles. This study complements existing studies mainly focused on technical aspects of the smart-car industry by examining the strategic dimensions of platform companies and their approach to the future smart-car market by comparing them with existing car manufacturing multinationals.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.87-95
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• 2018

Due to global warming and increased energy costs around the world, interests of energy saving and efficiency have been increased. In particular, forging factories need methods to save energy and increase productivity because of needing amounts of energy uses. To solve the problem, we propose a system, which includes collection, monitoring, and analysis process, to monitor energy uses each facility in realtime based on the IoT devices. This system insists of worksheets management, facility/energy management, realtime monitoring, history search, data analysis through connecting with existed ERP/MES Systems in manufacturing factories. The energy monitoring process is to present used energy collected from IoT devices connected with installed gasmeter and wattmeter each facility. This system provide the change of energy uses, usage fee, energy conversion, and green gas information in realtime on Web and mobile devices. This system will be enhanced with energy saving technology by analyzing constructed big data of energy uses. We can also propose a method to increase productivity by integrating this system with functions of digitalized worksheets and optimized models for production process.

• Korean Journal of Health Education and Promotion
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• v.19 no.3
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• pp.73-85
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• 2002

This study was conducted to examine community residents' knowledge level and related factor on electronic wave in order to provide basic data for development of education and publicity program. 2,000 people, who lived in five big cities and five small and medium cities, were selected ad subjects of this study. The data were collected from May 1, 200 I to August 31, 2001. The results of this study are as follows. According to the average knowledge level of harmful affect of electronic wave on health in general characteristics, female was higher(37.40 ± 5.24 points) than male; ‘forties’ was highest(37.77 ± 5.69 points); ‘married spouse’ was high(36.84 ± 5.59 points); ‘living in small-ta-medium city’ was high(36.84 ± 5.32 points). ‘university graduate’ was highest(37.41 ± 5.32 points) in education level, ‘middle class’ was high(36.61 ± 4.96 points) in economic status, ‘professional technician’ was higher(36.68 ± 6.55 points) than other occupations in occupational type. According to the knowledge level of harmful affect of electronic wave on health in health condition by self-judgment, ‘good health condition’ was highest(36.77 ± 4.99 points). In the case of the knowledge level of those who visited medical institutions for last one year, ‘never visited’ was highest(37.19 ± 5.02 points). In the kind of medical institutions, ‘those who visited general hospital’ was highest(36.58 ± 5.63 points). In the way of knowledge obtainments of electronic wave through education and publicity media, ‘school education’ was highest(37.55 ± 5.19 points). According to the score of awareness level of disease incidence related to electronic wave, allergy and erethism was highest(57.8 points on the basis of 100 points). It appeared in order of leukemia, skin disease or skin cancer, dementia, various cancers, cataract, and brain tumor. The variables which significantly influenced knowledge level of harm of electronic wave were knowledge obtainments of electronic wave, age, economic status, daily TV watching period, sex, period of daily cellular phone use, period of working with computer, and daily VTR watching period. The knowledge of community residents concerning harmful affect of electronic wave on health is needed because people's opportunity of exposing to electronic wave is increasing. Especially, it is the demands of the times to provide information on knowledge of each equipment which generate electronic wave. The government, the product manufacturing companies, related social organizations, and education institutions must make efforts to develop the education program which is needed to make people have right knowledge and attitude.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.23-45
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• 2020

Big data is creating in a wide variety of fields such as medical care, manufacturing, logistics, sales site, SNS, and the dataset characteristics are also diverse. In order to secure the competitiveness of companies, it is necessary to improve decision-making capacity using a classification algorithm. However, most of them do not have sufficient knowledge on what kind of classification algorithm is appropriate for a specific problem area. In other words, determining which classification algorithm is appropriate depending on the characteristics of the dataset was has been a task that required expertise and effort. This is because the relationship between the characteristics of datasets (called meta-features) and the performance of classification algorithms has not been fully understood. Moreover, there has been little research on meta-features reflecting the characteristics of multi-class. Therefore, the purpose of this study is to empirically analyze whether meta-features of multi-class datasets have a significant effect on the performance of classification algorithms. In this study, meta-features of multi-class datasets were identified into two factors, (the data structure and the data complexity,) and seven representative meta-features were selected. Among those, we included the Herfindahl-Hirschman Index (HHI), originally a market concentration measurement index, in the meta-features to replace IR(Imbalanced Ratio). Also, we developed a new index called Reverse ReLU Silhouette Score into the meta-feature set. Among the UCI Machine Learning Repository data, six representative datasets (Balance Scale, PageBlocks, Car Evaluation, User Knowledge-Modeling, Wine Quality(red), Contraceptive Method Choice) were selected. The class of each dataset was classified by using the classification algorithms (KNN, Logistic Regression, Nave Bayes, Random Forest, and SVM) selected in the study. For each dataset, we applied 10-fold cross validation method. 10% to 100% oversampling method is applied for each fold and meta-features of the dataset is measured. The meta-features selected are HHI, Number of Classes, Number of Features, Entropy, Reverse ReLU Silhouette Score, Nonlinearity of Linear Classifier, Hub Score. F1-score was selected as the dependent variable. As a result, the results of this study showed that the six meta-features including Reverse ReLU Silhouette Score and HHI proposed in this study have a significant effect on the classification performance. (1) The meta-features HHI proposed in this study was significant in the classification performance. (2) The number of variables has a significant effect on the classification performance, unlike the number of classes, but it has a positive effect. (3) The number of classes has a negative effect on the performance of classification. (4) Entropy has a significant effect on the performance of classification. (5) The Reverse ReLU Silhouette Score also significantly affects the classification performance at a significant level of 0.01. (6) The nonlinearity of linear classifiers has a significant negative effect on classification performance. In addition, the results of the analysis by the classification algorithms were also consistent. In the regression analysis by classification algorithm, Naïve Bayes algorithm does not have a significant effect on the number of variables unlike other classification algorithms. This study has two theoretical contributions: (1) two new meta-features (HHI, Reverse ReLU Silhouette score) was proved to be significant. (2) The effects of data characteristics on the performance of classification were investigated using meta-features. The practical contribution points (1) can be utilized in the development of classification algorithm recommendation system according to the characteristics of datasets. (2) Many data scientists are often testing by adjusting the parameters of the algorithm to find the optimal algorithm for the situation because the characteristics of the data are different. In this process, excessive waste of resources occurs due to hardware, cost, time, and manpower. This study is expected to be useful for machine learning, data mining researchers, practitioners, and machine learning-based system developers. The composition of this study consists of introduction, related research, research model, experiment, conclusion and discussion.

• The Journal of the Korea Contents Association
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• v.7 no.8
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• pp.102-108
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• 2007

Among culture industry that greet digital generation and is observed 21th century the most representative game industry latest is caught what and more interest degree is rising. 2D and 3D animation accomplish continuous growth and development depending action expression along with development of computer technology, and 2D and 3D animation practical use extent are trend that is widening the area in TV, movie, GAME industry etc. through computer hardware and fast change of software technology. The trend of latest game graphic is trend that the weight is changing from 2D to 3D by 3D game and activation of 3D game character that raise player's immersion stuff and Control in 2D's simplicity manufacturing game balance for one side. This treatise that is reality of 3D game character to classify kind of (Motion Capture) and 3D character animation, form model the sense put. Recognize that is overview and reality of 3D game character first for this about example, and is considered to efficiency is high game industry and digital contents industry hereafter by proposing kind model classification of 3D game character animation, form model classification data and character animation manufacture process that application is possible at fast time and effect in 3D character animation application are big.

• Korean journal of food and cookery science
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• v.20 no.1
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• pp.26-33
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• 2004

The purpose of this study was to investigate the consumption patterns of traditional Korean rice cake among college students. Self administered questionnaires were collected from 512 college students in the Seoul, Kyunggi, Chungchung, Kyungsang, Junla and Gangwondo areas. The data were statistically analysed using frequency analysis, chi-squared and t-tests and a one-way ANOVA. By examining the results of the student's perceptions of traditional Korean rice cake, it was found that most know little, or only a moderate amount, about this type of food. Meanwhile, more than half the students liked traditional Korean rice cake, as this type of food satisfied their need for a traditional Korean taste, while the reason for disliking was that they were more familiar with western-style confectionary. Most students answered that they only ate traditional Korean rice cake on special occasions, such as big holidays or ceremonies for the dead ancestors. Most answered that they bought those foods at conventional markets, the mile in the neighborhood, (Eds note: I dont't understand, do you mean, “within a mile of their neighborhood”\ulcorner) or atbig malls. The factor they considered the most important at the time of purchase was the quality (taste), which demonstrates the need for the development of traditional Korean rice cakes, with new tastes and shapes, which still satisfy the Korean's taste, whilemaintaining the traditional taste. For the questions that asked about the problems faced by the traditional Korean rice cake manufacturing industry, and the reasons for low consumption, the students responded that buying this type of food was difficult as the outlets selling themwere not easy to find. Our results seem to suggest that there are almost no specialty stores for the sale of traditional Korean rice cake compared to the other types of cakes that are scattered all over the country. (Eds note: this is only my opinion, and I maybe wrong, but I would have thought that trying to market traditional Korean rice cakes at local convenience stores, rather than speciality stores, would make them more available to the general public. Their marketing at speciality stores will maintain the status quo, i.e. people will go to the speciality stores to purchase product for holidays and special occasions, whereas they will go to the local convenience stores to buy general everyday snacks etc.)