• Journal of People, Plants, and Environment
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• v.23 no.3
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• pp.267-276
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• 2020

Background and objective: Agro-healing is crucial with urban farming in the domestic. It is beyond the conventional agriculture. This study was carried out to assess the 2010s researches on domestic agro-healing and predict the future direction of agro-healing development. Methods: Among the articles published from 2010 to 2018, we collected some articles by searching keywords including agro-healing, garden activity, gardening, horticultural activity, horticultural program, horticultural therapy, plant effect, plant environment, plant growing program, plant impact, social gardening, urban agriculture and vegetable garden activity, selected 83 articles that were evaluated in advance, and analyzed by frequency analysis, t-test, and one-way ANOVA with SPSS 20.0. Results: Agro-healing journal articles were published the most in 2010, and have declined since then. In the classification according to the academic society, most of the journal articles were published by the Society for People, Plants, and Environment. The main targets of domestic agro-healing related to activities and programs were preschoolers, children and adolescents, accounting for 52.4% of the total. By the characteristics of the subjects, agro-healing programs and studies were conducted with special participants who needed special care compared to the general participants. The dependent variables were classified into six areas according to their attributes and the share of psychological and emotional areas was highest (42.6%) among them. In terms of the composition of the program, the share of those with 9-12 sessions was highest (36.7%) and the share of those with more than 20 participants was also highest (39.8%). Conclusion: It is recommended to operate agro-healing programs or industries focusing on the socially disadvantaged including those who have special needs or the underprivileged, but in order to create income for farms and expand the demand for agro-healing, it will be necessary to spread the perception that anyone without any physical or emotional issue can be the targets of and experience agro-healing. To meet the different needs of targets of agro-healing, it will be necessary to conduct objective and practical studies on broader areas and in the process the healing functions of agriculture and the strength of agro-healing needs to be further highlighted.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.53-62
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• 2019

In recent years, South Korean has made a globally acknowledged achievement in movie industry. In terms of Art, films produced in South Korea obtained lots of awards in international movie festivals; in the business field, Korean movies are swiftly occupying the Asian or even the world film market. Extraordinary films with good reputations and high box office records are frequently launched and induced to a trend, which then forms into a cultural phenomenon and attributes to an important, major force in the so-called "Hallyu" culture. This, in part, benefits from the massive support of Korean government's cultural policies, and is also a product of the high degree of cultural consciousness of Korean movie producers. The Korean cultures, customs, and the underlying cultural elements of the East, that are presented in these movies, satisfy the audience and appeal their fondness. The Princess and the Matchmaker is a South Korean period romantic comedy film directed by Hong Chang-pyo and starred Shim Eun-kyung and Lee Seung-gi. The movie was presented on Feb 28th, 2018. It tells a story of Seo Do-yoon, the most proficient saju (fortune-teller) expert of the Joseon Era who selected a husband for Princess Song-Hwa based on her "fortune eight letters" (specifically, the time, day, month and year of her and her husbands' birth, normally in eight letters), in a hope of alleviating the rage of people following years of drought, and thus to resolve a national crisis. This paper takes The Princess and the Matchmaker as an example, from the aspects of cultural state, system, behavior and mentality, to analyze the traditional customs such as "fortune eight letters", "marriage by match" and the cultural concepts behind these phenomena, in order to explore the ways and methods of traditional culture in the modern cultural and artistic form of film.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.7
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• pp.295-302
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• 2023

Software requirements written in natural language may have different meanings from the stakeholders' viewpoint. When designing an architecture based on quality attributes, it is necessary to accurately classify quality attribute requirements because the efficient design is possible only when appropriate architectural tactics for each quality attribute are selected. As a result, although many natural language processing models have been studied for the classification of requirements, which is a high-cost task, few topics improve classification performance with the imbalanced quality attribute datasets. In this study, we first show that the classification model can automatically classify the Korean requirement dataset through experiments. Based on these results, we explain that data augmentation through EDA(Easy Data Augmentation) techniques and undersampling strategies can improve the imbalance of quality attribute datasets, and show that they are effective in classifying requirements. The results improved by 5.24%p on F1-score, indicating that handling imbalanced data helps classify Korean requirements of classification models. Furthermore, detailed experiments of EDA illustrate operations that help improve classification performance.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.11-26
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• 2023

This study aimed to empirically analyze the effect of Korean companies' FDI(Foreign Direct Investment) on their financial performances, particularly divided into profitability, stability, growth and activity, while comparing distinct financial performances between SMEs(small and medium-sized enterprises) and large enterprises whose corporate attributes are different from each other. As research subjects, this study selected FDI Korean companies from the directory of oversea-expanded companies of KOTRA(Korea Trade-Investment Promotion Agency) and used financial data from a total of 409 companies(136 SMEs and 273 large enterprises) with complete financial data for the first five years after the initial investment out of all the financial data from 1990 to 2021. The analysis results can be summarized as follows; In the profitability sector, FDI had positive effects on ROA(Return on Assets) and ROS(Return on Sales) of SMEs, while having negative effects on those of large enterprises to the contrary. In the stability sector, FDI had no statistical significance for SMEs, while having significantly negative effect on LEV(Debt to Equity Ratio) of large enterprises. In the growth sector, FDI had significantly negative effect on AGR(Asset Growth) of SMEs, but showed no significant results for large enterprises. In the activity sector, FDI showed no statistical significance for SMEs, while having positive effects on ATR(Asset Turnover Ratio) and FATA(Fixed Asset Turnover Ratio) of large enterprises. In conclusion, it was found that when having made FDI, SMEs and large enterprises showed different financial performances from each other in terms of profitability, stability, growth and activity.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.1
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• pp.29-40
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• 2024

Recently, the technology of autonomous driving, one of the core of the fourth industrial revolution, is developing, but sensor-based autonomous driving is showing limitations, such as accidents in unexpected situations, To compensate for this, HD-map is being used as a core infrastructure for autonomous driving, and interest in the public and private sectors is increasing, and various studies and technology developments are being conducted to secure the latest and accuracy of HD-map. Currently, NGII will be newly built in urban areas and major roads across the country, including the metropolitan area, where self-driving cars are expected to run, and is working to minimize data error rates through quality verification. Therefore, this study analyzes the spatial relationship of reference objects in the attribute structuring process for rapid and accurate renewal and production of HD-map under construction by NGII, By applying the attribute input automation methodology of the reference object in which spatial relations are established using the library of open source-based PyQGIS, target sites were selected for each road type, such as high-speed national highways, general national highways, and C-ITS demonstration sections. Using the attribute automation tool developed in this study, it took about 2 to 5 minutes for each target location to automatically input the attributes of the spatial relationship reference object, As a result of automation of attribute input for reference objects, attribute input accuracy of 86.4% for high-speed national highways, 79.7% for general national highways, 82.4% for C-ITS, and 82.8% on average were secured.

• Informatization Policy
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• v.31 no.3
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• pp.48-71
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• 2024

In the modern era of digital sophistication, effective public administration warrants a citizen-centric approach that not only anticipates the needs of public service users but also comprehends their behaviors in undertaking proactive measures to deliver public services as needed. This study adopts a typological perspective by viewing e-government users as distinct consumer groups with individualized demands, behavioral tendencies, and perceptual attributes. Utilizing data from a 2021 survey on e-government service utilization, a two-step cluster analysis was conducted to delineate user typology through an empirical study. The analysis incorporated variables such as the purpose of using e-government, selected e-government channels, subjective perceptions of technological risk, and personal innovativeness. Accordingly, e-government users were classified into five distinct typological groups labeled "Unilateral Active Users Geared to Social Media," "Versatile Power Users," "Unilateral Pragmatic Active Users," "Occasional Passive Users," and "Minimal Users." This typological differentiation of e-government user groups is intended to help identify unique user demands and characteristics so as to facilitate the delivery of tailored e-government services and informed policy decisions catering to the diverse needs of users.

• Science of Emotion and Sensibility
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• v.15 no.2
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• pp.297-306
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• 2012

In this study we investigated emotional characteristics of various whites which have slightly different nuances to suggest guidelines that help designers to select appropriate colors when designing white based products. The study involved three different procedures. In experiment 1, we selected 20 emotional words through a survey (N=30) among 60 words, which we picked from literature review that was thought to be appropriate to evaluate product colors. In experiment 2, we evaluated the emotional characteristics of 13 basic colors from the I.R.I Hue & Tone 120 system (N=30) using previously selected emotional words, to find relative emotional positions of white in comparison to other colors. Based on the ratings, factor analysis was conducted and consequently four factors were extracted: flamboyant, elegant, clear, and soft. Accordingly, the emotional characteristics of the 13 colors were profiled and compared with those of white. Finally, in experiment 3, we conducted an evaluation of emotional characteristics on 25 whites with different nuances facilitating the four factors obtained in experiment 2. The color stimuli used in experiments were measured in terms of CIE 1976 $L^*a^*b^*$, and regression analysis was performed in order to predict the emotional characteristics through the L, a, and b values of a color, as long as that is perceived as a white. Throughout three empirical studies, we observed three overruling tendencies : First, there are four important factors when evaluating product color - flamboyant, elegance, clearness and softness; second, white is dominantly the most elegant in comparison to other colors; third, the emotional factors of the study were affected by some combinations of attributes of colors rather than by all three-hue, saturation and brightness. In addition, the equations derived from the regression analysis in experiment 3, it is expected that designers may predict the emotional distinction between nuances of white.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.129-142
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• 2016

Customer product reviews have become one of the important factors for purchase decision makings. Customers believe that reviews written by others who have already had an experience with the product offer more reliable information than that provided by sellers. However, there are too many products and reviews, the advantage of e-commerce can be overwhelmed by increasing search costs. Reading all of the reviews to find out the pros and cons of a certain product can be exhausting. To help users find the most useful information about products without much difficulty, e-commerce companies try to provide various ways for customers to write and rate product reviews. To assist potential customers, online stores have devised various ways to provide useful customer reviews. Different methods have been developed to classify and recommend useful reviews to customers, primarily using feedback provided by customers about the helpfulness of reviews. Most shopping websites provide customer reviews and offer the following information: the average preference of a product, the number of customers who have participated in preference voting, and preference distribution. Most information on the helpfulness of product reviews is collected through a voting system. Amazon.com asks customers whether a review on a certain product is helpful, and it places the most helpful favorable and the most helpful critical review at the top of the list of product reviews. Some companies also predict the usefulness of a review based on certain attributes including length, author(s), and the words used, publishing only reviews that are likely to be useful. Text mining approaches have been used for classifying useful reviews in advance. To apply a text mining approach based on all reviews for a product, we need to build a term-document matrix. We have to extract all words from reviews and build a matrix with the number of occurrences of a term in a review. Since there are many reviews, the size of term-document matrix is so large. It caused difficulties to apply text mining algorithms with the large term-document matrix. Thus, researchers need to delete some terms in terms of sparsity since sparse words have little effects on classifications or predictions. The purpose of this study is to suggest a better way of building term-document matrix by deleting useless terms for review classification. In this study, we propose neutrality index to select words to be deleted. Many words still appear in both classifications - useful and not useful - and these words have little or negative effects on classification performances. Thus, we defined these words as neutral terms and deleted neutral terms which are appeared in both classifications similarly. After deleting sparse words, we selected words to be deleted in terms of neutrality. We tested our approach with Amazon.com's review data from five different product categories: Cellphones & Accessories, Movies & TV program, Automotive, CDs & Vinyl, Clothing, Shoes & Jewelry. We used reviews which got greater than four votes by users and 60% of the ratio of useful votes among total votes is the threshold to classify useful and not-useful reviews. We randomly selected 1,500 useful reviews and 1,500 not-useful reviews for each product category. And then we applied Information Gain and Support Vector Machine algorithms to classify the reviews and compared the classification performances in terms of precision, recall, and F-measure. Though the performances vary according to product categories and data sets, deleting terms with sparsity and neutrality showed the best performances in terms of F-measure for the two classification algorithms. However, deleting terms with sparsity only showed the best performances in terms of Recall for Information Gain and using all terms showed the best performances in terms of precision for SVM. Thus, it needs to be careful for selecting term deleting methods and classification algorithms based on data sets.

• Journal of agricultural medicine and community health
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• v.29 no.1
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• pp.1-14
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• 2004

Objectives: We investigated the factors related to health examination behaviors, sociodemographic aspects and lifestyles of elderly persons with different social backgrounds, and compared sexual and regional differences in urban and rural elderlies. Methods: The total study subjects(464 individuals) from urban(236) and rural areas(228), recruited by a stratified cluster random sampling were interviewed and examined about their sociodemographic profiles, daily lifestyles, subjective health status, conditions concerning use of medical resources, hearing acuity, visual acuity and ADL(activity of daily living), and whether they receive health examination or not. For statistical analysis, Chi-square test was used for sexual and regional comparisons among the groups who have been given a health examination and the one who have not. Results: In urban areas, the rate of having underwent health examination was 54.5% in men and 46.9% in women, and in rural areas, it was 59.8% in men and 42.7% in women, showing its higher rate in men than in women in both areas. For regional differences between the group who have taken a health examination and the one who have not, there was a significant difference in terms of age, family pattern, current job, monthly household income, owning a house, drinking status, eating habit, subjective health status, whether they have taken outpatient medical service for the recent 3 months or not, anxiety for the health, and IADL conditions according to whether the community is rural or urban. In multiple regressions, the influential factors on the health examination behaviors were selected such as having their own house, their family doctor, amnesia, urinary incontinence and chronic disease in urban districts. But in rural districts, the variables were selected such as having or not of their family doctor, urinary incontinence, anxiety for the health, educational level, their own house and chronic disease. Conclusions: It is suggested that the approach to the health examination of an older patient requires substantial consideration of highly variable individual sociodemographic characteristics involving regional attributes as well as their daily life styles, subjective health status, status of performing health examination, physical health status and ADL conditions.