• Korean Journal of Social Welfare
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• v.56 no.3
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• pp.303-325
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• 2004

This study investigated subtypes of men who batter, and explored the differences among them. It was based on 217 subjects from all around the nation who received legal punishment. In the analysis of the typology, we specifically tested whether the Holtzworth-Munroe and Stuart proposed typology was verified. The results of the cluster analysis revealed support for their theoretical distinction for three types of abusers. These results imply that Holtzworth-Munroe and Stuart's batterer typology is applicable to Korean batterers to some degree. Type 1 men demonstrated the lowest levels of physical and psychological abuse toward their wives and were the least likely to have had a history of child abuse or alcohol problems. These men had lower MCMI scores and did not show any extraordinary personality traits. Men in this category were violent only against their wives, had relatively liberal sex role attitudes and had the most satisfaction in their intimate relationships. Type 2 men were violent only at home, using a moderate level of violence. These men had very high levels of dependency on others and showed a borderline, avoident or passive-aggressive personality. The amount of alcohol consumption was similar to Type 1, but scores of jealousy, self-esteem, and attitudinal variables were similar to Type 3 men. They lacked assertiveness skills and reported the least marital satisfaction. Type 3 men used the most severe violence and were violent both inside and outside the home. These men showed signs of antisocial and aggressive personality. They had experienced frequent physical abuse during childhood, were the most likely to abuse alcohol and had lower self-control. Type 3 were the most traditional in their views of women's roles and had attitudes supporting violence. Based upon the study findings, practical implications of enhancing treatment efficacy were considered.

• Journal of the Korean Society of Clothing and Textiles
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• v.32 no.6
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• pp.890-901
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• 2008

This study explores an initial framework for online product categorization by examining the relationships among Internet motivations, buying tendencies, and online purchase intentions for product categories. A total of 217 usable questionnaires were obtained from respondents in a southwestern state in the United States. A path model using a correlation matrix with maximum likelihood was estimated using LISREL 8.53. Findings indicated that Internet motivations consisted of four factors: Diversion, Economic, Information, and Social motivations. In addition, online products were classified into three categories based on purchase intentions: Sensory, Cognitive, and Search products. Estimated path model showed that diversion and economic motivations affected impulse buying tendency, whereas economic, information and social motivations influenced planned buying tendency in the online context. Also, the buying tendencies were significantly related to online purchase intentions for the product categories. Purchase intentions for sensory products were more strongly affected by impulse buying tendency, whereas purchase intentions for cognitive and search products were more strongly affected by planned buying tendency. Theoretical and managerial implications were discussed for devising an appropriate e-market strategy for specific product categories.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.91-107
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• 2012

As the Internet becomes more popular, many people use it to communicate. With the increasing number of personal homepages, blogs, and social network services, people often expose their personal information online. Although the necessity of those services cannot be denied, we should be concerned about the negative aspects such as personal information leakage. Because it is impossible to review all of the past records posted by all of the people, an automatic personal information detection method is strongly required. This study proposes a method to detect or classify online documents that contain personal information by analyzing features that are common to personal information related documents and learning that information based on the Na$\ddot{i}$ve Bayes algorithm. To select the document classification algorithm, the Na$\ddot{i}$ve Bayes classification algorithm was compared with the Vector Space classification algorithm. The result showed that Na$\ddot{i}$ve Bayes reveals more excellent precision, recall, F-measure, and accuracy than Vector Space does. However, the measurement level of the Na$\ddot{i}$ve Bayes classification algorithm is still insufficient to apply to the real world. Lewis, a learning algorithm researcher, states that it is important to improve the quality of category features while applying learning algorithms to some specific domain. He proposes a way to incrementally add features that are dependent on related documents and in a step-wise manner. In another experiment, the algorithm learns the additional dependent features thereby reducing the noise of the features. As a result, the latter experiment shows better performance in terms of measurement than the former experiment does.

• Korean Journal of Family Social Work
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• no.54
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• pp.107-153
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• 2016

The purpose of this study was to explore the marriage decision-making process and experience of the 'Older women-Younger men couple' and presenting a substantive theory to explain the decision-making process that married women experience of 'Older women-Younger men couple'. This in-depth interviews were conducted 11 female people among 32-48 years of 'Older women-Younger men couple.' Analysis of the data was applied to the "grounded theory" method of Qualitative research methods suggested by Strauss and Corbin(1998). Research questions of this study is that what is the experience of the marriage decision-making process to 'Older women-Younger men couple?'. After analyzing the data to the grounded theory method 75 concepts and 29 sub-categories, 14 categories were derived. Older women experienced a central phenomenon of 'ambivalence of love and anxiety'.'Older women-Younger men couple's marriage decision-making process of the women had to 'step adjustment', 'acceptable level', 'Step enacted', and 'Older women-Younger men couple's core category of married women in the decision-making process' was 'Intimacy based on the trust each other beyond the prejudices of the differences'. This study is meant by presenting the basic data provided professional counseling intervention measures for 'Older women-Younger men' couple by collectively Understanding the decision-making process of Older women-Younger men couple married.

• Korean Journal of Plant Resources
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• v.35 no.4
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• pp.471-501
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• 2022

This study was carried out on 455 forest wetlands of south Korea for which an inventory was established through value evaluation and grade. Correlation analysis was conducted to find out the correlation between the types and grades of forest wetlands and 23 evaluation factors in four categories: vegetation and landscape, material circulation and hydraulics·hydrology, humanities and social landscape, and disturbance level. Through the improvement of types and grades of forest wetlands, it is possible to secure basic data that can be used in setting up conservation measures by preparing standards necessary for future forest wetland conservation and restoration, and to found a systematic monitoring system. First, between the type of forest wetland and size and accessibility showed a positive correlation, but the remaining items were analyzed to have negative or no correlation. In particular, it was found that there was no negative correlation or no correlation with the grades of forest wetland. Moreover, it was found that there was a very strong negative correlation with the weighted four category items. Thus, it is judged that improvement is necessary because there is an error in the weight or adjust the evaluation criteria of the value evaluation item, add an item that can increase objectivity. Especially, in the case of forest wetlands, the ecosystem service function due to biodiversity is the largest, so evaluation items should be improved in consideration of this. Therefore, it can be divided into five categories: uniqueness and rarity (15%), wildlife habitat (15%), vegetation and landscape (35%), material cycle·hydraulic hydrology (30%), and humanities and social landscape (5%). It will be possible to propose weights that can increase effectiveness.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Korean Association of Arts Management
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• no.52
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• pp.5-37
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• 2019

Despite a copious volume of work on the relationship between social class and cultural consumption, scholars have paid scant attention to the increasingly apparent observation that a vast majority of the population exhibits indifference toward fine arts regardless of one's socio-economic status. Much of the prior literature on cultural consumption has treated the public's indifference to fine arts not as a distinct analytical category that deserves an explanation of its own, but simply as the opposite of "likes" or the act of consumption, let alone being disentangled from the concept of "dislikes" in taste-formation and consumption behavior. In this paper, we suggest that the seemingly increasing trend toward indifference to fine arts, especially among those who are part of the well-educated and economically well-off, merits close scholarly attention on its own term. As an initial step toward this endeavor, we explore the factors behind indifference toward fine arts among Korean middle-class, using the ground theory method. Our interview findings reveal that much of indifference toward fine arts is attributable to the lack of tastes in fine arts and artistic competence. Our results suggest that research drawing on Bourdieu's theory and Peterson's omnivore hypothesis needs to be further revised through an in-depth investigation of the institutional and societal contexts where art education takes place in Korea. We discuss the implications of our findings for policy-making in the cultural and artistic sphere.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.3
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• pp.166-178
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• 2023

This study aims to introduce and assess CNN Deep Learning methods to analyze visual landscape images on social media with embedded user perceptions and experiences. This study analyzed visual landscape images by focusing on a healing place. For the study, seven adjectives related to healing were selected through text mining and consideration of previous studies. Subsequently, 50 evaluators were recruited to build a Deep Learning image. Evaluators were asked to collect three images most suitable for 'healing', 'healing landscape', and 'healing place' on portal sites. The collected images were refined and a data augmentation process was applied to build a CNN model. After that, 15,097 images of 'healing' and 'healing landscape' on portal sites were collected and classified to analyze the visual landscape of a healing place. As a result of the study, 'quiet' was the highest in the category except 'other' and 'indoor' with 2,093 (22%), followed by 'open', 'joyful', 'comfortable', 'clean', 'natural', and 'beautiful'. It was found through research that CNN Deep Learning is an analysis method that can derive results from visual landscape image analysis. It also suggested that it is one way to supplement the existing visual landscape analysis method, and suggests in-depth and diverse visual landscape analysis in the future by establishing a landscape image learning dataset.

• Korean Journal of Culture and Social Issue
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• v.24 no.3
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• pp.491-518
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• 2018

The purpose of this study was to compare with qualitative research articles on the grandparents' parenting experiences of grandchildren between those with primary responsibility and those with partial responsibility in Korean Journals since 2000. For the purpose of the study, this study analyzed research of 43 qualitative research articles(19 grandfamilies, 24 custodial grandparents), with respect to their objectives, basic annual trends, methodology, subject, category of content. The major findings are as follows. Firstly, the annual number of articles of grandfamilies are on an decreasing trend, while those of custodial grandparents are on an increasing trend. Secondly, the phenomenology and interview are frequently used in research of the two types of family. Thirdly, 6~10 participants were the most frequent number of participation in all of the family. However, demographics, caring circumstances, physical circumstances were significantly different in two types of family. Fourthly, caring categories of contents(the meaning, positive factor, conflict factor and resolution of conflicts) were also similar, while these were significant diffent in specific psychological experiences in all of the family. Based on the findings of this comparative study, suggestions for pratical services and implication for future study were proposed.

• Korean Journal of Culture and Social Issue
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• v.20 no.3
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• pp.205-233
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• 2014

This study aims to identify work conflicts in Korean socio-cultural context by applying grounded theory. Survey has been conducted through in-depth interviews with 11 different employees from various occupational categories. Data collected from the survey were then analyzed based on the grounded theory of Strauss and Corbin (1998), thus resulted in a paradigm model consisting of 31 categories, 63 subcategories, and 100 concepts by open coding. Axial coding was then conducted and the results were as follows. The causal condition was the 'character of an opponent'. Contextual conditions which affect the causal condition were 'situational characteristics', 'character of an opponent', 'character of oneself', and their 'mutuality'. 'Negative feeling' was the central phenomena of work conflict and action/interaction strategies were verified to be 'avoidance', 'expression', 'effort toward solving problems' and 'increasing conflict'. Intervening conditions were 'interrelation', 'intervention', and 'group/task characteristics'. The consequences were organized as 'conflict continuance', 'personnel change' and 'positive effect'. Through selective coding, 'managing with the conflict' was derived as core-category and three different types of management were classified. Ultimately, this study shows how employees work in Korea experience the work conflicts and what kinds of socio-cultural factors have influence on the work conflicts, which can supplement previous inadequate empirical research. Also, this study can provide implications and suggestions as a fundamental integrated model for the future empirical research on work conflicts.