• Journal of the Korea Society of Computer and Information
• /
• v.27 no.9
• /
• pp.1-12
• /
• 2022

Traditional methods of measuring corneal ulcers were difficult to present objective basis for diagnosis because of the subjective judgment of the medical staff through photographs taken with special equipment. In this paper, we propose a method to detect the ulcer area on a pixel basis in corneal ulcer images using a semantic segmentation model. In order to solve this problem, we performed the experiment to detect the ulcer area based on the DeepLab model which has the highest performance in semantic segmentation model. For the experiment, the training and test data were selected and the backbone network of DeepLab model which set as Xception and ResNet, respectively were evaluated and compared the performances. We used Dice similarity coefficient and IoU value as an indicator to evaluate the performances. Experimental results show that when 'crop & resized' images are added to the dataset, it segment the ulcer area with an average accuracy about 93% of Dice similarity coefficient on the DeepLab model with ResNet101 as the backbone network. This study shows that the semantic segmentation model used for object detection also has an ability to make significant results when classifying objects with irregular shapes such as corneal ulcers. Ultimately, we will perform the extension of datasets and experiment with adaptive learning methods through future studies so that they can be implemented in real medical diagnosis environment.

• The Journal of the Korea Contents Association
• /
• v.15 no.7
• /
• pp.578-590
• /
• 2015

This paper investigated how high school students perceive on nuclear power applying semantic network analysis. The total number of 250 high school students in 6 metropolitan areas responded to the survey. Results indicate that the word which most frequently appeared is 'Nuclear plant' (87 times) following by 'Japan' (71 times), 'Danger'(59 times), 'Fukushima' (59 times), 'Radioactivity' (56 times), 'Energy' (47 times), 'Youngkwang' (37 times), 'Electricity' (30times), 'Chernobyl' (29 times), 'Explosion' (25 times). For students in higher acceptance level of nuclear 'Radioactivity' (25 times) was most frequently showed up following by 'Fukushima' (23 times), 'Energy' (21 times), 'Japan' (21 times), Nuclear plant' (20 times), 'Danger' (17 times), 'Youngkwang' (16 times). For student in lower acceptance level of nuclear, the word of 'Nuclear plant' (40 times) most frequently appeared following by 'Japan' (31 times)', 'Danger' (29 times), 'Fukushima' (23 times), 'Radioactivity' (17 times), 'Energy' (16 times), 'Youngkwang' (16 times), 'Chernobyl' (15 times).

• Journal of the Korean BIBLIA Society for library and Information Science
• /
• v.28 no.3
• /
• pp.217-240
• /
• 2017

The purpose of this study was to investigate the semantic network analysis to understand image contents and to examine the degree to which words, word clusters contributed to the formation of semantic map within image contents. For this research, from 1993 until 2016 the field of the image contents were collected for a total of 2,624 cases papers. The word appeared in Title analyzed the social network by using the R program of Big Data. The results were as follows: First, The field of image contents is based on researches related to 'image', 'media' and 'contents'. Second, there is a three-step flow ('education' -> 'media' -> 'contents') of research in the field of image contents. Third, researches related to 'broadcasting', 'digital', 'technology', and 'production' were continuously carried out. Finally, There were new research subjects for each regime.

• Journal of the Korean earth science society
• /
• v.34 no.7
• /
• pp.711-726
• /
• 2013

The purpose of this study was to investigate how congruently the learning objectives of Earth Science I textbooks match the 2009 revised Earth Science curriculum. For this purpose, we classified the learning objectives of curriculum and textbooks were into three factors including ability, cross-cutting concepts, and behavioral verbs. The text data were analyzed using the semantic network analysis method. The results are as follows. The learning objectives of textbooks with regard to ability factors mainly emphasized the cognitive and affective domain. In addition, the ability of inquiry performance was emphasized in the learning objective of the curriculum. The textbooks used various sub-frame of cross-cutting concepts in comparison with the curriculum. Both textbooks and curriculum used the term 'comprehension' the most as behavioral verbs. However, most behavioral verbs just remained at the level of cognitive system.

• KIISE Transactions on Computing Practices
• /
• v.22 no.2
• /
• pp.107-112
• /
• 2016

The Sejong Electronic(machine-readable) Dictionary, developed by the 21st century Sejong Plan, contains systematically organized information on Korean words. It helps to solve problems encountered in the electronic formatting of the still-commonly-used hard-copy dictionary. The Sejong Electronic Dictionary, however has a limitation relate to sentence structure and selection-restricted nouns. This paper discuses the limitations of word-sense disambiguation(WSD) that uses subcategorization information suggested by the Sejong Electronic Dictionary and generalized selection-restricted nouns from the Korean Lexico-semantic network. An alternative method that utilized semi-supervised learning, the chi-square test and some other means to make WSD decisions is presented herein.

• Journal of Digital Contents Society
• /
• v.18 no.5
• /
• pp.911-921
• /
• 2017

The purpose of this study was to investigate the semantic network analysis to understand image contents and to examine the degree to which words, word clusters contributed to the formation of semantic map within image contents. For this research, from 1993 until 2016 the field of the image contents were collected for a total of 2,624 cases papers. The word appeared in Title analyzed the social network by using the R program of Big Data. The results were as follows: First, Research on 'education' in the field of image contents has decreased. Second, the role of 'media' in the field of image contents is changing. Finally, It is a change in the status of 'contents' in the field of image contents.

• Human Ecology Research
• /
• v.58 no.4
• /
• pp.613-633
• /
• 2020

This study identifies consumers' perceived benefits and costs when using Samsung Health (a healthcare app) based on consumer reviews from Google Play Store's app and social media discourse. We examine the differences in the benefits and the costs of Samsung Health using these two sources of data. We conducted text frequency analysis, clustering analysis, and semantic network analysis using R programming. The major findings are as follows. First, consumers experience benefits and costs on several functions of the app, such as step counting, device interlocking, information acquisition, and competition with global consumers. Second, the results of semantic network analysis showed that there were eight benefit factors and three cost factors. We also found that the three costs correspond to the benefits, indicating that some consumers gained benefits from certain functions while others gained costs from the same functions. Third, the comparison between consumer app review and social media discourse showed that the former is appropriate to assess the performance of app functions, while the latter is appropriate to examine how the app is used in daily life and how consumers feel about it. The current study suggests managerial implications to healthcare app service providers regarding what they should strengthen and improve to enhance consumers' satisfaction. It also suggests some implications from the two media, which can be mutually complementary, for researchers who study consumer opinions.

• KIISE Transactions on Computing Practices
• /
• v.21 no.7
• /
• pp.500-505
• /
• 2015

The Sejong Electronic(machine readable) Dictionary, which was developed by the 21 century Sejong Plan, contains a systematic of immanence information of Korean words. It helps in solving the problem of electronical presentation of a general text dictionary commonly used. Word sense disambiguation problems can also be solved using the specific information available in the Sejong Electronic Dictionary. However, the Sejong Electronic Dictionary has a limitation of suggesting structure of sentences and selection-restricted nouns. In this paper, we discuss limitations of word sense disambiguation by using subcategorization information as suggested by the Sejong Electronic Dictionary and generalize selection-restricted noun of argument using Korean Lexico-semantic network.

• (The) Research of the performance art and culture
• /
• no.37
• /
• pp.437-464
• /
• 2018

This study used semantic network analysis to understand the academic identity and characteristics of the society of korean performance art and culture and to grasp the trend of the research. For this purpose, this study analyze the research trend of korean performance art and culture related papers based on 455 whole articles in the Journal of The Society of Korean Performance Art and Culture by the Korean Performance Art and Culture Association from 2000 to 2017. Through this research, the trends of The Society of Korean Performance Art and Culture in the period of time were identified, and the phenomenon of the performance culture field and the future development direction were suggested.

• The Journal of Korean Association of Computer Education
• /
• v.22 no.4
• /
• pp.21-34
• /
• 2019

SW education is being implemented in all the school due to the application of the 2015 Curriculum. The purpose of SW education is to improve Computational Thinking by using Unplugged Activities, Educational Programming Language, and Physical Computing. Among them, 73 domestic and 85 overseas researches related to 'Unplugged Activities' were compared and analyzed using semantic network analysis techniques. As a result, the research on 'Unplugged Activities' has been started from 1998, and the research has started in Korea since 2006. As the CT is recognized as a core competence for the future society in line with the 4th Industrial Revolution, researches have been rapidly increasing in both the domestic and overseas countries since 2016. In Korean studies, it was analyzed that many main words related to the elemental factors such as 'unplugged activity', 'robot utilization', 'educational programming language' were found. This suggests that future research should move toward research for the promotion of 'CT' which is the purpose of computer science.