• Korean Security Journal
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• no.39
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• pp.217-239
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• 2014

The purpose of this study is to compare with three juvenile delinquency theories on adolescents' status offenses including Hirschi's social bonding theory, Agnew's general strain theory, and Akers' social learning theory. The data derived from a sample of 2,337 middle school students taken from National Youth Policy Institute in 2011-2012. Multiple OLS regression analysis revealed that variables from social learning theory were strongly supported as an explanation for adolescents' status offenses, while variables from general strain theory were not supported. The social learning model explained 12.0% of the variance in adolescents' status offenses. However, general strain variables explained 2.6% of the variance in the dependant variable and 6.2% of the variance in adolescents' status offenses were explained by the social bonding variables. The present research made important contributions the further utilization of social learning in investigating many of the damaging forms of social deviance which exist in our society.

• Korean Journal of Child Studies
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• v.36 no.6
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• pp.1-21
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• 2015

This study was aimed at examining the paths through which family socioeconomic status as indicated by family income and parental education influenced preschool-aged children's socioemotional and cognitive development through the mediating role of parental warmth and the home learning environment. The study made use of data from 1,080 families who participated in the 5th wave of the Panel Study on Korean Children, when their children were approximately 4 years of age. Structural equation modeling analysis revealed that the models, including both parental warmth and the home learning environment did not fit the data well. The effects of warmth on social competence and cognitive development were not statistically significant. The modified models, using the home learning environment as a mediator between family SES and child's developmental outcomes showed that higher level of family income and parental education predicted a more cognitively stimulating home environment, which in turn, predicted a child's greater levels of social competence and positive cognitive development. The social competence of preschool-aged children again significantly predicted their cognitive development. The mediating effects of the home learning environment were statistically supported.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.1-18
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• 2017

Recently, identification of the extremely stressed condition of children is an essential skill for real-time recognition of a dangerous situation because incidents of children have been dramatically increased. In this paper, therefore, we present a model based on machine learning techniques for stress status identification of a child by using bio-signals such as voice and heart rate that are major factors for presenting a child's emotion. In addition, a smart band for collecting such bio-signals and a mobile application for monitoring child's stress status are also suggested. Specifically, the proposed method utilizes stress patterns of children that are obtained in advance for the purpose of training stress status identification model. Then, the model is used to predict the current stress status for a child and is designed based on conventional machine learning algorithms. The experiment results conducted by using a real-world dataset showed that the possibility of automated detection of a child's stress status with a satisfactory level of accuracy. Furthermore, the research results are expected to be used for preventing child's dangerous situations.

• Journal of the Korean Society of Costume
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• v.67 no.4
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• pp.116-130
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• 2017

The aim of this study is to investigate the general status, operating status, and the satisfaction level of participating textile-clothing companies involved in the Work and Learning Dual System in Daegu. The general status and operating status of the participating companies are as follows. As of March 2016, 34 of the 43 companies in Daegu participated in this survey, and they were divided into three areas of textile: weaving, dyeing & finishing, and apparel manufacturing. The breakdown is as follows: 14 dyeing & finishing companies (41.2%), 13 apparel manufacturing companies (38.2%), and 7 textile weaving companies (23.6%). The results of the survey showed that 91.2% of the companies decided to participate in the system to cultivate their employees into experts in the field. The satisfaction rate of the theoretical education and training institutions was 3.88 out of 5 points. In particular, the satisfaction rate of the textile weaving companies was as high as 4.29, and the satisfaction level of the dyeing & finishing companies was higher than the average of 3.71. The overall satisfaction rate for the work-related paradigm was 3.97 out of 5 points. The results of this survey can be used to conclude that the Work and Learning Dual System is operating as it was intended to be by the government.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.55 no.5
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• pp.638-644
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• 2022

The measurement of morphological features is essential in aquaculture, fish industry and the management of fishery resources. The measurement of fish requires a large investment of manpower and time. To save time and labor for fish measurement, automated and reliable measurement methods have been developed. Automation was achieved by applying computer vision and machine learning techniques. Recently, machine learning methods based on deep learning have been used for most automatic fish measurement studies. Here, we review the current status of automatic fish measurement with traditional computer vision methods and deep learning-based methods.

• Journal of Technologic Dentistry
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• v.45 no.1
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• pp.21-29
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• 2023

Purpose: This study attempted to collect basic data to improve the basic repair ability of university freshmen in a world where the usage of advanced medical devices related to computer programs is now common. Methods: The collected data from 280 university freshmen enrolled in nursing, dental, and health degrees or computer and engineering degrees at K university of Gangwon-do were analyzed using the t-test, ANOVA, correlation analysis, and linear regression analysis using the IBM SPSS Statistics ver. 21.0 (IBM). Results: The mathematical learning status and the detailed factors of basic mathematical ability had a positive (+) correlation. The factors of basic mathematical ability, psychology of learning (p<0.001), method of learning (p<0.001), and propensity to learn (p<0.05) were found to be statistically significant, and the model's explanatory power was 40.0%. Conclusion: As a result of this study and considering that advanced medical devices such as computer-aided design/computer-aided manufacturing and three-dimensional printers are becoming more common and up-to-date in clinical settings, it is determined that nursing and dental health students require education to improve their repair skills.

• Korean Journal of Artificial Intelligence
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• v.6 no.2
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• pp.23-27
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• 2018

Korea has a high proportion of self-employment. Many of them start the food business since it does not require high-techs and it is possible to start the business relatively easily compared to many others in business categories. However, the closure rate of the business is also high due to excessive competition and market saturation. Cafés and restaurants are examples of food business where the business analysis is highly important. However, for most of the people who want to start their own business, it is difficult to conduct systematic business analysis such as trade area analysis or to find information for business analysis. Therefore, in this paper, we predicted business status with simple information using Microsoft Azure Machine Learning Studio program. Experimental results showed higher performance than the number of attributes, and it is expected that this artificial intelligence model will be helpful to those who are self-employed because it can easily predict the business status. The results showed that the overall accuracy was over 60 % and the performance was high compared to the number of attributes. If this model is used, those who prepare for self-employment who are not experts in the business analysis will be able to predict the business status of stores in Seoul with simple attributes.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.701-712
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• 2013

The e-learning industry status survey statistic provides information about the actual conditions of supply and demand of the e-learning industries. NIPA (National IT Industry Promotion Agency) has published the annual report of the survey results since 2004. Due to the 9th version of the KSIC (Korean standard industrial classification) revised in 2008, a refinement of the sampling design for the survey becomes necessary, especially that for the business demand sector. This article, based on the 9th revision of the KSIC, constructs a stratification of the target population used for the e-learning industry status survey on the business demand sector. Classification of strata in the business population is based on the industrial type and employment scale of business. Under the stratified population, we design a sampling scheme by using the power allocation method that enables us to satisfy a target coefficient of variation of each industrial stratum. In order to secure an accurate survey results based on the proposed sampling design, we consider the problem of calculating the design weights, derivation of parameter estimators, and formulas of their standard errors.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.263-266
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• 2019

In this paper, we suggest an activity and health monitoring system to observe the status of the dogs in real time. We also propose a k-days algorithm which helps monitoring pet health status using classified activity data from a machine learning approach. One of the best machine learning algorithm is used for the classification activity of dogs. Dog health status is acquired by comparing current activity calculation with passed k-days activities average. It is considered as a good, warning and bad health status for differences between current and k-days summarized moving average (SMA) > 30, SMA between 30 and 50, and SMA < 50, respectively.

• The Journal of Korean Academic Society of Nursing Education
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• v.12 no.1
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• pp.21-27
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• 2006

Purpose: This is a descriptive study to identify the relationship of quality of life and learning style of the elderly. Method: 106 elderly persons living in Seoul were surveyed using a questionnaire to identify their demographic characteristics, learning styles, and perceived quality of life. Results: 17% of the respondents were in the low quality of life (QOL). The QOL showed significantly different according to learning styles, gender, current health status, perceived level of current life happiness, and monthly pocket money. The highest average score of QOL was found in the Assimilator group, and the lowest average score was found in the Diverger group. Conclusions: Among the four categories significantly related to QOL, the case of learning style and current health status are the categories by which nurses can intervene to improve QOL. Thus, nurses should emphasize the relationship to improve the clients' QOL. Since the scores of QOL were high for the Assimilator and Accomodator groups, nurse should identify the learning style of the elderly as soon as possible and then help those who are under-developed, to further develop Assimilator and Accomodator learning styles.