• Journal of the Korean Society of Earth Science Education
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• v.11 no.2
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• pp.145-157
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• 2018

The purpose of this study is to analyze the research trends in domestic related to gifted counseling by utilizing Sementic analysis methods. For papers of gifted education in korea, KCI(Korea Citation Index) rated journals were selected 83 pieces published in journals were collected and the Sementic Network Analysis(SNA) way was utilizing for keyword frequency and Centrality Network Analysis throughout a variety of research articles using krkwic and Ucinet6.0. The results are as follows. first, the analysis appeared that the trends of paper keywords from highest frequency of appearance keyword in papers focused on four keywords: perfectionism, career, counseling, and the science gifted. second, Analysis of annual trends from 2001 to June 2018 showed that the top keywords were as follows: the gifted underachievers, the perfectionism, the gifted students of Science, and the science gifted students. the rising keywords were perfectionism, twice-exceptional students, and gifted parents, and the keywords of gifted students and general students showed a tendency to decrease. Consequently, gifted counseling research should be done from various perspectives.

• Journal of the Korean Society of Earth Science Education
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• v.11 no.3
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• pp.212-223
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• 2018

The purpose of this study is to investigate the perception of elementary students' 'global environment'. The research method used the Sementic Network Analysis method of the global environment elements which appeared in the students' explanation about the picture and the picture that emerged about the 'global environment'. The results of the study are as follows. First, as a result of analyzing the students' explanation of the pictures along with the pictures of the students, the elementary students were perceived negatively about the global environment such as 'environmental pollution', 'global warming' and 'trash problem'. Second, as a result of analyzing the image of the global environment expressed in the picture, there were many images expressed from a everyday viewpoint rather than a macroscopic viewpoint, and there was a tendency to express the earth personified. In addition, the picture expressing the clean earth environment expressed the most trees with natural environment elements and expressed the healthy earth with various natural elements such as sea, mountain, and land. Third, as a result of analyzing the difference of perception of global environment by grade, it was found that the difference of perception of global environment by grade was not much different.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.97-111
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• 2016

In the creative economy paradigm, motivation of the opportunity based startup is a continuous concern to policy-makers. Recently, bigdata anlalytics challenge traditional methods by providing efficient ways to identify social trend and hidden issues in the public sector. In this study the authors introduce a case study using social bigdata analytics for conducting policy analysis. A semantic network analysis was employed using textual data from social media including online news, blog, and private bulletin board which create buzz on the startup business. Results indicates that each media has been forming different discourses regarding government's policy on the startup business. Furthermore, semantic network structures from private bulletin board reveal unexpected social burden that hiders opening a startup, which has not been found in the traditional survey nor experts interview. Based on these results, the authors found the feasibility of using social bigdata analysis for policy-making. Methodological and practical implications are discussed.

• Journal of the Korean Society of Earth Science Education
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• v.9 no.1
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• pp.65-87
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• 2016

The purpose of this study is to examine Korean journals related to science education in order to analyze research trends into Nature of science in Korea. The subject of the study is the level of Korean Citation Index (KCI-listed, KCI listing candidates), that can be searched by the key phrase, "Nature of science" in Korean language through the RISS service. In this study, the Descriptive Statistical Analysis Method is utilized to discover the number of research articles, classifying them by year and by journal. Also, the Sementic Network Analysis was conducted to Word Cloud Analysis the frequency of key words, Centrality Analysis, co-occurrence and Cluster Dendrogram Analysis throughout a variety of research articles. The results show that 91 research papers were published in 25 journals from 1991 to 2015. Specifically, the 2 major journals published more than 50% of the total papers. In relation to research fields., In addition, key phrases, such as 'Analysis', 'recognition', 'lessons', 'science textbook', 'History of Science' and 'influence' are the most frequently used among the research studies. Finally, there are small language networks that appear concurrently as below: [Nature of science - high school student - recognize], [Explicit - lesson - effect], [elementary school - science textbook - analysis]. Research topic have been gradually diversified. However, many studies still put their focus on analysis and research aspects, and there have been little research on the Teaching and learning methods.

• Journal of IKEEE
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• v.27 no.4
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• pp.456-463
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• 2023

In this paper, we introduce the SSResUNet network model, which integrates the SPADE structure with the U-Net network model for accurate land cover classification using high-resolution satellite imagery without requiring user intervention. The proposed network possesses the advantage of preserving the spatial characteristics inherent in satellite imagery, rendering it a robust classification model even in intricate environments. Experimental results, obtained through training on KOMPSAT-3A satellite images, exhibit superior performance compared to conventional U-Net and U-Net++ models, showcasing an average Intersection over Union (IoU) of 76.10 and a Dice coefficient of 86.22.

• Proceedings of the Korean Society for Information Management Conference
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• 2018.08a
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• pp.133-138
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• 2018

본 연구는 언어네트워크 분석기법을 활용하여 언론보도자료에 나타난 대통령기록물과 관련된 사회적 이슈를 분석하였다. 분석결과를 통해 대통령기록물 관련 이슈의 발생 현황 및 이슈의 구성요소를 파악할 수 있었으며, 대통령기록물 관련 이슈에 대한 시사점 파악 및 관련 연구의 기초자료를 제공하는 것을 목적으로 한다. 이를 위하여 국내 주요 언론사 중 하나인 조선일보를 대상으로, 주제어인"대통령기록물"을 포함하는 관련 기사를 수집하였다. 총 780건의 수집된 보도자료를 대상으로 언어네트워크 분석을 수행하였으며, 분석결과에 대한 시각화를 진행하였다.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.105-115
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• 2022

This study compares the perspectives of experts and the public on the 2015 revised curriculum. To do this, research papers and newspaper articles were collected from October 2013 to May 2020. During this period, 1152 research papers and 692 newspaper articles were collected, and semantic network analysis was performed. As a result of the study, the educational expert group showed great interest in the core concept of the development of the revised curriculum focused on the abstract concept, while the public focused on the practical problems and consequences of the revision rather than the development of the revised curriculum itself. These results not only show the gap between the perspectives of the educational expert group and the public but also raise the need for effective communication to bridge the gap.

• Journal of Ginseng Culture
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• v.4
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• pp.13-37
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• 2022

Even before recorded history, the Korean people took ginseng. Later, poetry passed down from China developed into a literary style in which intellectuals from the Silla, Goryeo, and Joseon Dynasties expressed their thoughts concisely. The aim of this paper is to find Korean poems related to ginseng and to look for their semantic network. To this end, "Korea Classical DB ", produced by the Institute for the Translation of Korean Classics, was searched to find ginseng poems. As the result of a search in November 2021, two poems from the Three Kingdoms Period, two poems from the Goryeo Dynasty, and 23 poems from the Joseon Dynasty were searched. An examination of these poems found that the first ginseng poem was "Goryeoinsamchan," which was sung by people in Goguryeo around the 6th century. Ginseng poetry during the Goryeo Dynasty is represented by Anchuk's poem. Anchuk sang about the harmful effects of ginseng tributes from a realistic point of view. Ginseng poetry in the Joseon Dynasty is represented by Seo Geo-jeong in the early period and Jeong Yakyong in the late period. Seo Geo-jeong's ginseng poem is a romantic poem that praises the mysterious pharmacological effects of ginseng. A poem called "Ginseng" by Yongjae Seonghyeon is also a romantic poem that praises the mysterious medicinal benefits of ginseng. As a scholar of Realist Confucianism, Dasan Jeong Yak-yong wrote very practical ginseng poems. Dasan left five ginseng poems, the largest number written by one poet. Dasan tried ginseng farming himself and emerged from the experience as a poet. The story of the failure and success of his ginseng farming was described in his poems. At that time, ginseng farming was widespread throughout the country due to the depletion of natural ginseng and the development of ginseng farming techniques after the reign of King Jeongjo. Since the early 19th century, ginseng farming had been prevalent on a large scale in the Gaeseong region, and small-scale farming had also been carried out in other regions. What is unusual is Kim Jin-soo's poem. At that time, in Tong Ren Tang, Beijing (the capital of the Qing Dynasty), ginseng from Joseon sold well under the "Songak Sansam" brand. Kim Jin-Soo wrote about this brand of ginseng in his poem. In 1900, Maecheon Hwanghyeon also created a ginseng poem, written in Chinese characters. Thus, the semantic network of Korean ginseng poems is identified as follows: 1) Ginseng poetry in the spirit of the people - Emerging gentry in the Goryeo Dynasty (Anchuk). 2) Romantic ginseng poetry - Government School in the early Joseon Dynasty (Seo Geo-jeong, Seonghyeon, etc.). 3) Practical ginseng poetry - Realist School in the late Joseon Dynasty (Jeong Yak-yong, Kim Jin-soo, Hwang Hyun, etc.). This semantic network was extracted while examining the development of Korean ginseng poems.

• Journal of the Korean Society of Earth Science Education
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• v.10 no.3
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• pp.290-307
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• 2017

The purpose of this study is to analyze the research trends related to qualitative research on science education, to provide basic data of qualitative research on science education and to select the direction of follow-up research. The subject of the study is the level of Korean Citation Index (KCI-listed, KCI listing candidates), that can be searched by the key phrase, 'qualitative research', 'science education' in Korean language through the RISS service. In this study, the Descriptive Statistical Analysis Method is utilized to discover the number of research articles, classifying them by year and by journal. Also, the Sementic Network Analysis was conducted to the frequency of key words, Centrality Analysis throughout a variety of research articles using krkwic and Ucinet6.0. The results show that first, 138 research papers were published in 14 journals from 2005 to 2017. Second,, the analysis showed the highest frequency of appearance keyword in each article, 'elementary school teacher', 'gifted student', 'science teacher', 'class' were higher than others. third, according to the results of the whole Network Analysis, 'Analysis', 'elementary school', 'class' were analyzed as a highly influential node. And 'Comparison', 'inquiry', 'recognition', 'gifted students' were not close to the center of network. Fourth, keywords that appear in all sections are analysis, gifted students, and elementary school students, and can be analyzed continuously based on studies, lessons or recognition, and characteristics. Based on the results of this study, we explored the past and present of the study subjects related to the study of science education quality and discussed future direction of study.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.57-65
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• 2021

We propose a novel method to detect abnormal data of specific symptoms using deep learning in air pollution measurement system. Existing methods generally detect abnomal data by classifying data showing unusual patterns different from the existing time series data. However, these approaches have limitations in detecting specific symptoms. In this paper, we use DeepLab V3+ model mainly used for foreground segmentation of images, whose structure has been changed to handle one-dimensional data. Instead of images, the model receives time-series data from multiple sensors and can detect data showing specific symptoms. In addition, we improve model's performance by reducing the complexity of noisy form time series data by using 'piecewise aggregation approximation'. Through the experimental results, it can be confirmed that anomaly data detection can be performed successfully.