• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.151-154
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• 2021

Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study was analyzed for 21 papers in the March 2021 among the journals of the Korea Institute of Information and Communication Engineering. In the final analysis results, the most frequently mentioned keyword was "Data", which ranked first 305 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.326-327
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• 2021

Newly, big data utilization has been widely interested in a wide variety of industrial fields. Big data analysis is the process of discovering meaningful new correlations, patterns, and trends in large volumes of data stored in data stores and creating new value. Thus, most big data analysis technology methods include data mining, machine learning, natural language processing, and pattern recognition used in existing statistical computer science. Also, using the R language, a big data tool, we can express analysis results through various visualization functions using pre-processing text data. The data used in this study were analyzed for 29 papers in a specific journal. In the final analysis results, the most frequently mentioned keyword was "Research", which ranked first 743 times. Therefore, based on the results of the analysis, the limitations of the study and theoretical implications are suggested.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.117-125
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• 2024

In this paper, implement and propose an Active Electronically Scanned Array (AESA) radar integration analysis system which specialized for radar development by using heterogeneous media. Most analysis systems are used to analyze and improve the cause of defects, so they help the test easier. However, previous log analysis systems that operate only based on text are not intuitive and difficult to find the information user want at once if there is a lot of log information. so when an equipment defect occurs, there are limitations in analyzing the cause of defect. Therefore, the analysis system in this paper utilizes heterogeneous media. The media defined in this paper refers to recording text-based data, displaying data as image or video and visualizing data. The proposed analysis system classifies and stores data that transmitted and received between radar devices, radar target detection and Tracking algorithm data, etc. also displays and visualizes radar operation results and equipment defect information in real time. With this analysis system, it can quickly provide information what user want and assistance in developing high quality radar.

• Journal of the Korean Society of Costume
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• v.54 no.3
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• pp.87-97
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• 2004

패션잡지에 실린 패션 및 뷰티 관련 상품의 광고들은 현시대의 미의 이상을 제시하고, 상품소비를 통해 이를 성취할 수 있음을 제안함으로써 신체와 관련한 미적 상징성을 보여준다. 본 연구의 목적은 신체수정을 위한 상품의 특성과 상징적 의미를 확인하는 데 있으며, 이를 위해 여성잡지 Vogue와 남성잡지 GQ 광고 중 화장품과 바디케어 용품 광고를 선정하여, 이를 신체의 특성, 즉 색상, 볼륨과 비율, 형태와 구조, 텍스쳐, 향의 측면에서 구분하여 조사하였다. 그 결과, Vogue와 GQ 모두 다양한 종류의 신체수정을 위한 상품광고를 선보이고 있었으며, 상대적으로 Vogue가 GQ보다 더 많은 양과 종류의 상품 광고를 보이고 있었다. 신체의 특성에 따른 상품의 비중을 보면, Vogue는 신체의 색상과 관련한 시각적인 면이 높게 나타났고. 반면, GQ는 신체의 골격과 형태미, 볼륨과 비율, 그리고 향과 같은 덜 시각적인 면에서의 상품비중이 높았으며, 텍스쳐와 관련한 상품은 비슷한 비율로 나타났다. 이들 상품광고의 텍스트와 이미지에서 보이는 특성은 다기능성. 자연성, 개별성으로 구분할 수 있으며, 세계적 미의 추구, 젊음과 건강 이데올로기, 젠더 무경계화라는 상징적 의미를 내포하고 있다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.161-164
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• 2022

게임 산업은 기술의 발전과 비대면 서비스 수요 증가로 해마다 발전하고 있다. 본 연구는 사용자들의 수요를 조사하기 위하여 대중성이 가장 높은 온라인 게임 플랫폼에서 이용 시간이 많은 게임 정보를 확인하였다. HTML 파싱(parsing) 라이브러리를 통해 해당 게임들의 리뷰를 크롤링하여 엑셀 파일로 데이터베이스화하였고, 자연어 처리 라이브러리를 활용하여 데이터를 정제하였다. 총 5개 장르에 대하여 분석한 결과 각 장르에 해당하는 대표적인 키워드를 확인할 수 있었다. 취득한 키워드는 범용 시각화 패키지를 활용하여 워드 클라우드 형태로 한눈에 알아볼 수 있도록 시각화하였다.

• Journal of Korean Society of Archives and Records Management
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• v.23 no.4
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• pp.73-89
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• 2023

This study aims to analyze the frequency of keywords used in Korean abstracts, which are unstructured text data in the domestic record management research field, using text mining techniques to identify domestic record management research trends through distance analysis between keywords. To this end, 1,157 keywords of 77,578 journals were visualized by extracting 1,157 articles from 7 journal types (28 types) searched by major category (complex study) and middle category (literature informatics) from the institutional statistics (registered site, candidate site) of the Korean Citation Index (KCI). Analysis of t-Distributed Stochastic Neighbor Embedding (t-SNE) and Scattertext using Word2vec was performed. As a result of the analysis, first, it was confirmed that keywords such as "record management" (889 times), "analysis" (888 times), "archive" (742 times), "record" (562 times), and "utilization" (449 times) were treated as significant topics by researchers. Second, Word2vec analysis generated vector representations between keywords, and similarity distances were investigated and visualized using t-SNE and Scattertext. In the visualization results, the research area for record management was divided into two groups, with keywords such as "archiving," "national record management," "standardization," "official documents," and "record management systems" occurring frequently in the first group (past). On the other hand, keywords such as "community," "data," "record information service," "online," and "digital archives" in the second group (current) were garnering substantial focus.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1111-1120
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• 2022

Image Capturing is a matter of viewing images and describing images in language. The problem is an important problem that can be solved by keeping, understanding, and bringing together two areas of image processing and natural language processing. In addition, by automatically recognizing and describing images in text, images can be converted into text and then into speech for visually impaired people to help them understand their surroundings, and important issues such as image search, art therapy, sports commentary, and real-time traffic information commentary. So far, the image captioning research approach focuses solely on recognizing and texturing images. However, various environments in reality must be considered for practical use, as well as being able to provide image descriptions for the intended purpose. In this work, we limit the universally available Korean and English image captioning models and text generation techniques for the purpose of image captioning.

• The Journal of the Korea Contents Association
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• v.15 no.2
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• pp.86-100
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• 2015

Through advances driven by the Internet and the Smart Revolution, the amount and types of data generated by users have increased and diversified respectively. There is now a new concept at the center of attention, which is Big Data for assessing enormous amount of data and enjoying new values therefrom. In particular, efforts are required to analyze narratives within video clips and to study how to visualize such narratives in order to search contents stored in the Big Data. As part of the research efforts, this paper analyzes dialogues exchanged among characters and offers an interface named "Character-net" developed for modelling narratives. The interface Character-net can extract characters by analyzing narrative videos and also model the relationships between characters, both in the automatic manner. This signifies a possibility of a tool that can visualize a narrative based on an approach different from those used in existing studies. However, its drawbacks have been observed in terms of limited applications and difficulty in grasping a narrative's features at a glace. It was assumed that Character-net could be improved with the introduction of information design. Against the backdrop, the paper first provides a brief explanation of visualization design found in the data information design area and investigates research cases focused on the visualization of narratives present in videos. Next, key ideas of Character-net and its technical differences from existing studies have been introduced, followed by methods suggested for its potential improvements with the help of design-side solutions.

• Archives of design research
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• v.20 no.1 s.69
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• pp.219-228
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• 2007

Printing advertisement is aggregate of commercial information communication text consisted of image sign and language sign. This means that verbal tabor through visual stimulation and character is mixed and passes information through picture. Typography is process that visualize verbal appeal in printing advertisement. Therefore study about typography is very important for a visual expression element in printing advertisement. Typography expression of Korean printing advertisement accomplished fast qualitative growth after 2000 flowing the 1990s. This study makes that typography expression propensity of Korean printing advertisement after 2000 of changed of expression structure, changed of expression rule, changed of expression method etc. Accordingly, extracted each three analysis bases. And this study presented expansive direction of typography expression of printing advertising in case studies.

• Journal of the Korean Chemical Society
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• v.66 no.5
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• pp.376-389
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• 2022

The purpose of this study was to investigate the effects of implementing semantic mapping reading strategy in the science class on high school students' science text reading ability. 3^rd grade students of science core high school in a small and medium-sized city participated in this study for a semester. Texts with socio-scientific issues and chemistry subjects were used to implement semantic mapping reading strategy in the science class. To investigate the changes in students' science text reading ability, experimental group students participated in the pre-reading and post-science reading ability tests and the results were analyzed. The results of this study showed that the mean of the science reading ability test score of experimental group was significantly higher than that of the comparison group. We found that drawing a semantic mapping before solving a reading task made it easier for students to find information and infer meaning from text. It can be seen that students also recognize that the semantic mapping is helpful in understanding the text because it is easy to understand the relationship between concepts by visualizing the content of the text, and can connect their background knowledge with the text content.