• Journal of the Korea Convergence Society
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• v.10 no.8
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• pp.291-298
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• 2019

The purpose of this study is to analyze the effect of beauty interest on the satisfaction of mask pack use and repurchase. This study analyzed data from 305 copies of the questionnaire on SPSS. The analysis was done using the v21 statistical package program. The results of the analysis showed that the sub-factors of beauty interest had a statistically significant positive (+) effect on the mask-pack satisfaction level, and the sub-factors of mask-pack satisfaction level had a positive effect on repurchase intention. As a result of this study, the higher the consumers' beauty interest, the more important the satisfaction of using the mask pack, and accordingly, the intention to repurchase was increased. Through this study, we can expect successful marketing effects if the mask pack sales company understands the needs of consumers and uses them as marketing elements.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.246-256
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• 2022

Recently, parents and teachers consider physical education as a minor subject for students in elementary and secondary schools. Physical education performance has become increasingly significant as parents and schools pay more attention to physical schooling. The sports mining with distribution analysis model considers different factors, including the games, comments, conversations, and connection made on numerous sports interests. Using different machine learning/deep learning approach, children's athletic and academic interests can be tracked over the course of their academic lives. There have been a number of studies that have focused on predicting the success of students in higher education. Sports interest prediction research at the secondary level is uncommon, but the secondary level is often used as a benchmark to describe students' educational development at higher levels. An Automated Student Interest Prediction on Sports Mining using DL Based Bi-directional Long Short-Term Memory model (BiLSTM) is presented in this article. Pre-processing of data, interest classification, and parameter tweaking are all the essential operations of the proposed model. Initially, data augmentation is used to expand the dataset's size. Secondly, a BiLSTM model is used to predict and classify user interests. Adagrad optimizer is employed for hyperparameter optimization. In order to test the model's performance, a dataset is used and the results are analysed using precision, recall, accuracy and F-measure. The proposed model achieved 95% accuracy on 400^th instances, where the existing techniques achieved 93.20% accuracy for the same. The proposed model achieved 95% of accuracy and precision for 60%-40% data, where the existing models achieved 93% for accuracy and precision.

• Korean Journal of Culture and Social Issue
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• v.16 no.3
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• pp.289-310
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• 2010

The purpose of this study was to examine how political interest, political ideologies, and information-searching goals influence the amount of information voters search, the ways in which people search for information about political candidates, and the type of information they select. The results showed that the participants under accuracy goal searched much more information and the participants under the high level of interest were not affected by conservative ideology, but the participants with the low level of interest were influenced by the liberal ideology and viewed substantially more information. And most of participants had the attribute-centered searching pattern. The social policies were accessed most, however, the information about party and personal background of a candidate were found least.

• Journal of The Korean Association For Science Education
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• v.38 no.2
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• pp.113-122
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• 2018

The purpose of this study is to investigate the effects of the educational context variables on students' science achievement and interest in TIMSS 2015. TIMSS 2015 science data and questionnaire results were used to fit the Hierarchical Linear Model (HLM) in this study. According to the results, books at home, parents' level of education, and students' views on science lessons have significant influence on science achievement of above-high level 4th-grade students, and books at home on below-intermediate level 4th-grade students. Books at home, students' views on science lessons, and school composition by student economic background have significant influence on science achievement of above-high level 8th-grade students, and books at home and students' views on science lessons on science achievement of below-Intermediate level 8th-grade students. In all grade levels, books at home, and students' views on science lessons have significant influence on science achievement and interest. Discussed in the conclusion are ways to improve science teaching and learning including offering systematic reading programs for all students, reinforcement of student-participation in science classes, connecting science hands-on activities with science concepts for below-Intermediate level elementary students, and so on.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.434-445
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• 2009

Content-based image retrieval(CBIR) is the retrieval technique which uses the contents of images. However, in contrast to text data, multimedia data are ambiguous and there is a big difference between system's low-level representation and human's high-level concept. So it doesn't always mean that near points in the vector space are similar to user. We call this the semantic-gap problem. Due to this problem, performance of image retrieval is not good. To solve this problem, the relevance feedback(RF) which uses user's feedback information is used. But existing RF doesn't consider user's region-of-interest(ROI), and therefore, irrelevant regions are used in computing new query points. Because the system doesn't know user's ROI, RF is proceeded in the image-level. We propose a new ROI RF method which guides a user to select ROI from relevant images for the retrieval of complex satellite image, and this improves the accuracy of the image retrieval by computing more accurate query points in this paper. Also we propose a pruning technique which improves the accuracy of the image retrieval by using images not selected by the user in this paper. Experiments show the efficiency of the proposed ROI RF and the pruning technique.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.41 no.2
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• pp.11-18
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• 2023

This study aims to distinguish what can be used in consideration of the national situation with Korea for Chinese Scenic and Historic Interest Areas, and the results are as follows; First, the Chinese Scenic and Historic Interest Areas expanded to the existing scenic cruise culture, travel, and tourism culture in the process of the influx of Western culture in the modern and contemporary era, and became popular as a travel destination. Accordingly, the Chinese government developed the tourism industry around the scenic sites, and thanks to the development of transportation and communication, the Scenic and Historic Interest Areas has become an important national heritage. This influenced the establishment of the system related to Scenic and Historic Interest Areas, and today, it is operated around the Scenic and Historic Interest Areas ordinance. Second, the designation of the Scenic and Historic Interest Areas is divided into the size of the site according to the area, and the process of selecting the Scenic and Historic Interest Areas classification, rating evaluation, and comprehensive value evaluation according to evaluation indicators and rating standards is carried out. Accordingly, according to the results of the classification, it is subdivided from the national level to the Scenic and Historic Interest Areas at the local level. Third, the central government is in charge of managing and supervising Scenic and Historic Interest Areas across the country, and the local government's construction department is in charge of supervising Scenic and Historic Interest Areas in the region. The management organization of Scenic and Historic Interest Areas established by local governments above the county level has a system that actually protects, utilizes, and manages Scenic and Historic Interest Areas. In addition, 14 detailed indicators are used to monitor Scenic and Historic Interest Areas. Based on these results, considering the application of the domestic scenic site policy, the method of developing the policy that has established the system from the perspective of the utilization of the people is worth considering. On the other hand, the evaluation of the designation and management system through the setting of various indicators has limitations in that it is difficult to secure objectivity in impressing or evaluating the landscape. Therefore, rather than blindly introducing quantified evaluation, it seems that guidance and promotion on how to expand consensus on scenic values and enjoy heritage should be prioritized.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.810-813
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• 2004

Indexing and Retrieving images from large and varied collections using image content as a key is a challenging and important problem in computer vision application. In this paper, a color Content-based Image Retrieval (CBIR) system using hierarchical Region of Interest (ROI) query and indexing is presented. During indexing process, First, The ROIs on every image in the image database are extracted using a region-based image segmentation technique, The JSEG approach is selected to handle this problem in order to create color-texture regions. Then, Color features in form of histogram and correlogram are then extracted from each segmented regions. Finally, The features are stored in the database as the key to retrieve the relevant images. As in the retrieval system, users are allowed to select ROI directly over the sample or user's submission image and the query process then focuses on the content of the selected ROI in order to find those images containing similar regions from the database. The hierarchical region-of-interest query is performed to retrieve the similar images. Two-level search is exploited in this paper. In the first level, the most important regions, usually the large regions at the center of user's query, are used to retrieve images having similar regions using static search. This ensures that we can retrieve all the images having the most important regions. In the second level, all the remaining regions in user's query are used to search from all the retrieved images obtained from the first level. The experimental results using the indexing technique show good retrieval performance over a variety of image collections, also great reduction in the amount of searching time.

• The Journal of the Korea Contents Association
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• v.12 no.5
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• pp.113-124
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• 2012

The purpose of this study was to investigate young children's response to technological components in dramatic activities relying on robot projector based augmented reality. The participants of this study were 16 five-year-old children. Young children's response to the technological components was collected by interviews asking 1) the level of understanding and interest in robot technology and 2) the level of understanding and interest in augmented reality technology. The result of this study showed that most of children playing the role of actors as well as audiences were likely to understand and get interested in the robot and augmented realty technology. This study would support the feasibility of employing the robot projector based augmented reality contents to dramatic activities in early childhood settings.

• Journal of Korean Dental Hygiene Science
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• v.5 no.2
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• pp.35-44
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• 2022

Background: This study was aimed at investigating the perception of social network service (SNS) users regarding dental office visits and determining the proportion of dental SNS users among general SNS users. Methods: We surveyed 177 adults using SNSs. Dental SNS characteristics were classified into information provision, interaction, recency, reliability, and interest, and the recognition level of each area was surveyed on a 5-point scale. The total number of items was 17, including three information provision, three interaction, four recency, four reliability, and three interest items. Results: Among the five domains, the recognition level was the highest for reliability (3.51 points) and the lowest for interest (2.94 points). Among the 17 items, the recognition level was the highest for "Educational information provided by dental SNS is valuable" at 3.60 points, "Dental SNS educational video is useful for information sharing and dental knowledge improvement" at 3.53 points, and "The perceived educational information of dental SNS is reliable" at 3.51 points. Participants in their 20s and 30s had higher scores for being up-to-date (3.33 and 2.88 points, respectively) and reliability (3.59 and 3.09 points, respectively) than those in their 40s or older. The recognition level of all areas of dental SNS characteristics was significantly higher for experienced dental SNS users than for nonexperienced ones. Conclusions: The results of this study suggested that dental institutions should consider ways to utilize SNS for patient management and education and that dental SNS-related contents should contain educational and reliable information to help SNS users manage their oral health.

• Journal of Korean Academy of Nursing Administration
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• v.20 no.3
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• pp.342-352
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• 2014

Purpose: The purpose of this study was to identify how political interest, efficacy and media usage influence political participation in hospital nurses. Methods: Participants were 286 nurses, who were informed of the study purpose and agreed to participate. Data were collected during November and December, 2012 using a questionnaire on political interest, political efficacy, media usage and political participation. Data were analyzed using t-test, ANOVA, Scheff$\acute{e}$'s test, Pearson Correlation Coefficients, and Multiple Stepwise Regression. Results: Scores for political participation and political interest was average. The score for political efficacy was higher than average. Political participation was significantly different by education level, job career, position, and intention to vote in the election for the 18th President. Political participation had a moderate positive correlation with political interest (r=.50, p<.001), political efficacy (r=.32, p<.001) and media usage (r=.14, p=.022). Political interest (${\beta}$=.43) was the factor most influential on political participation, explaining 25% of the variance. A total of 32% of political participation was explained by political interest, political efficacy, and TV news or SNS for media use. Conclusion: The results suggest that it is necessary to develop strategies to promote political interest and political efficacy for hospital nurses to improve political participation.