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Indoor Semantic Data Dection and Indoor Spatial Data Update through Artificial Intelligence and Augmented Reality Technology

  • Kwon, Sun
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.1170-1178
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    • 2022
  • Indoor POI data, an essential component of indoor spatial data, has attribute information of a specific place in the room and is the most critical information necessary for the user. Currently, indoor POI data is manually updated by direct investigation, which is expensive and time-consuming. Recently, research on updating POI using the attribute information of indoor photographs has been advanced to overcome these problems. However, the range of use, such as using only photographs with text information, is limited. Therefore, in this study, and to improvement this, I proposed a new method to update indoor POI data using a smartphone camera. In the proposed method, the POI name is obtained by classifying the indoor scene's photograph into artificial intelligence technology CNN and matching the location criteria to indoor spatial data through AR technology. As a result of creating and experimenting with a prototype application to evaluate the proposed method, it was possible to update POI data that reflects the real world with high accuracy. Therefore, the results of this study can be used as a complement or substitute for the existing methodologies that have been advanced mainly by direct research.

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Analysis of media trends related to spent nuclear fuel treatment technology using text mining techniques (텍스트마이닝 기법을 활용한 사용후핵연료 건식처리기술 관련 언론 동향 분석)

  • Jeong, Ji-Song;Kim, Ho-Dong
    • Journal of Intelligence and Information Systems
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    • v.27 no.2
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    • pp.33-54
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    • 2021
  • With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.

An Analysis of Types and Sources of Background Knowledges of Elementary Preservice Teachers' Questions about Astronomy Contents in Elementary Science Text Books (초등 과학교과서 천문 내용에 대한 예비교사들의 질문의 배경지식 유형과 출처 분석)

  • Lee, Myeong-Je
    • Journal of Korean Elementary Science Education
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    • v.35 no.2
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    • pp.194-204
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    • 2016
  • The purpose of this study is to find out the relationship between types and sources of background knowledges of elementary preteachers' questions about astronomy contents in the elementary science text books. Data were extracted from the preteachers' classes established in a university of education. The results are as follows. First, right background knowledges of questions were found in about 58% questions, wrong background knowledges 15%, and no background knowledges 26%. Second, it was found that 'school' as a source of background knowledges was found in 29% questions, 'friend' 21%, 'internet' 14%, 'book reading' 12%, 'others' 9%, 'TV' 7%, 'institute' 4%. In case of the type that right background knowledges have casual relation or correlation with question contents, 'book reading' and 'TV' sources rate increased, but 'internet' and 'others' decreased when compared to total questions. In the type which background knowledges are right and did not have casual relation or correlation with question contents, 'internet' source rate increased and 'friend' decreased. In case of the type that wrong background knowledges do not have casual relation or correlation with question contents, 'friend' and 'TV' sources rate increased, but 'school' and 'book reading' decreased. The type which background knowledges are right and did not have casual relation or correlation with question contents, 'internet' source rate increased and 'friend' decreased. In case of the type of no background knowledges, 'TV' and 'institute' source rate increased, but 'internet' and 'book reading' decreased. Third, the questions in 'Earth and Moon' unit have little background knowledges. The questions in 'solar system and stars' have background knowledges with no relation to the questions. Especially, in the unit 'changes of seasons', right background knowledges were found in more than half questions, but the contents of questions and background knowledges were not connected scientifically.

A Study on the Research Trends in the Area of Geospatial-Information Using Text-mining Technique Focused on National R&D Reports and Theses (텍스트마이닝 기술을 이용한 공간정보 분야의 연구 동향에 관한 고찰 -국가연구개발사업 보고서 및 논문을 중심으로-)

  • Lim, Si Yeong;Yi, Mi Sook;Jin, Gi Ho;Shin, Dong Bin
    • Spatial Information Research
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    • v.22 no.4
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    • pp.11-20
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    • 2014
  • This study aims to provide information about the research-trends in the area of Geospatial Information using text-mining methods. We derived the National R&D Reports and papers from NDSL(National Discovery for Science Leaders) site. And then we preprocessed their key-words and classified those in separable sectors. We investigated the appearance rates and changes of key-words for R&D reports and papers. As a result, we conformed that the researches concerning applications are increasing, while the researches dealing with systems are decreasing. Especially, with in the framework of the keyword, '3D-GIS', 'sensor' and 'service' xcept ITS are emerging. It could be helpful to investigate research items later.

Mass Media and Social Media Agenda Analysis Using Text Mining : focused on '5-day Rotation Mask Distribution System' (텍스트 마이닝을 활용한 매스 미디어와 소셜 미디어 의제 분석 : '마스크 5부제'를 중심으로)

  • Lee, Sae-Mi;Ryu, Seung-Eui;Ahn, Soonjae
    • The Journal of the Korea Contents Association
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    • v.20 no.6
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    • pp.460-469
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    • 2020
  • This study analyzes online news articles and cafe articles on the '5-day Rotation Mask Distribution System', which is emerging as a recent issue due to the COVID-19 incident, to identify the mass media and social media agendas containing media and public reactions. This study figured out the difference between mass media and social media. For analysis, we collected 2,096 full text articles from Naver and 1,840 posts from Naver Cafe, and conducted word frequency analysis, word cloud, and LDA topic modeling analysis through data preprocessing and refinement. As a result of analysis, social media showed real-life topics such as 'family members' purchase', 'the postponement of school opening', ' mask usage', and 'mask purchase', reflecting the characteristics of personal media. Social media was found to play a role of exchanging personal opinions, emotions, and information rather than delivering information. With the application of the research method applied to this study, social issues can be publicized through various media analysis and used as a reference in the process of establishing a policy agenda that evolves into a government agenda.

The Creation of Dental Radiology Multimedia Electronic Textbook (멀티미디어기술을 이용한 치과방사선학 전자 교과서 제작에 관한 연구)

  • Kim Eun-Kyung;Cha Sang-Yun;Han Won-Jeong;Hong Byeong-Hee
    • Imaging Science in Dentistry
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    • v.30 no.1
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    • pp.55-62
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    • 2000
  • Purpose: This study was performed to develop the electronic textbook (CD-rom title) about preclinical practice of oral and maxillofacial radiology, using multimedia technology with interactive environment. Materials and Methods: After comparing the three authoring methods of multimedia, i.e. programming language, multimedia authoring tool and web authoring tool, we determined the web authoring tool as an authoring method of our electronic textbook. Intel Pentium II 350 MHz IBM-compatible personal computer with 128 Megabyte RAM, Umax Powerlook flatbed scanner with transparency unit, Olympus Camedia l400L digital camera, ESS 1686 sound card, Sony 8 mm Handycam, PC Vision 97 pro capture board, Namo web editor 3.0, Photoshop 3.0, ThumbNailer, RealPlayer 7 basic and RealProducer G2 were used for creating the text document, diagram, figure, X-ray image, video and sound files. We made use of javascripts for tree menu structure, moving text bar, link button and spread list menu and image map etc. After creating all files and hyperlinking them, we burned out the CD-rom title with all of the above multimedia data, Netscape communicator and plug in program as a prototype. Results and Conclusions : We developed the dental radiology electronic textbook which has 9 chapters and consists of 155 text documents, 26 figures, 150 X-ray image files, 20 video files, 20 sound files and 50 questions with answers. We expect that this CD-rom title can be used at the intranet and internet environments and continuous updates will be performed easily.

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An Analysis on the Operational state of Distance Universities' Electronic Libraries through the Life-long Education Law (평생교육법령하의 원격대학 전자도서관의 운영 실태 분석)

  • Lee Jong-Moon
    • Journal of Korean Library and Information Science Society
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    • v.36 no.4
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    • pp.99-113
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    • 2005
  • The purpose of this research is to analyze the operational state of Distance universities' electronic libraries through the Lifelong Education Law, and to find out the related problems. The main investigational focus was on the operational methodologies of the libraries and the usage levels of the full-text service. The data were collected through accessing the URLs of 17 Distance universities authorized till 2005. The result is that every university is operating their libraries either on their own $(17.7\%)$ or by using the links to the external libraries $(82.4\%)$. However, only $(35.3\%)$ of the surveyed universities provide the full-text service available on the Internet. Thus, in order to establish the fourth generation Distance university based on the Internet and Web, it is urgently needed to improve the construction and operation standards of electronic libraries in the Lifelong Education Law.

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Neural Predictive Coding for Text Compression Using GPGPU (GPGPU를 활용한 인공신경망 예측기반 텍스트 압축기법)

  • Kim, Jaeju;Han, Hwansoo
    • KIISE Transactions on Computing Practices
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    • v.22 no.3
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    • pp.127-132
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    • 2016
  • Several methods have been proposed to apply artificial neural networks to text compression in the past. However, the networks and targets are both limited to the small size due to hardware capability in the past. Modern GPUs have much better calculation capability than CPUs in an order of magnitude now, even though CPUs have become faster. It becomes possible now to train greater and complex neural networks in a shorter time. This paper proposed a method to transform the distribution of original data with a probabilistic neural predictor. Experiments were performed on a feedforward neural network and a recurrent neural network with gated-recurrent units. The recurrent neural network model outperformed feedforward network in compression rate and prediction accuracy.

Linking Findings from Text Analyses to Online Sales Strategies (온라인상의 기업 및 소비자 텍스트 분석과 이를 활용한 온라인 매출 증진 전략)

  • Kim, Jeeyeon;Jo, Wooyong;Choi, Jeonghye;Chung, Yerim
    • Journal of the Korean Operations Research and Management Science Society
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    • v.41 no.2
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    • pp.81-100
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    • 2016
  • Much effort has been exerted to analyze online texts and understand how empirical results can help improve sales performance. In this research, we aim to extend this stream of research by decomposing online texts based on text sources, namely, companies and consumers. To be specific, we investigate how online texts driven by companies differ from those generated by consumers, and the extent to which both types of online texts have different effects on online sales. We obtained sales data from one of the biggest game publishers and merged them with online texts provided by companies using news articles and those created by consumers in user communities. The empirical analyses yield the following findings. Word visualization and topic analyses show that firms and consumers generate different contexts. Specifically, companies spread word to promote their own events whereas consumers produce online words to share winning strategies. Moreover, online sales are influenced by consumer-generated community topics whereas firm-driven topics in news articles have little to no effect. These findings suggest that companies should focus more on online texts generated by consumers rather than spreading their own words. Moreover, online sales strategies should take advantage of specific topics that have been proven to increase online sales. In particular, these findings give startup companies and small business owners in variety of industries the advantage when they use the online channel for distribution and as a marketing platform.

Trend Analysis of News Articles Regarding Sungnyemun Gate using Text Mining (텍스트마이닝을 활용한 숭례문 관련 기사의 트렌드 분석)

  • Kim, Min-Jeong;Kim, Chul Joo
    • The Journal of the Korea Contents Association
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    • v.17 no.3
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    • pp.474-485
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    • 2017
  • Sungnyemun Gate, Korea's National Treasure No.1, was destroyed by fire on February 10, 2008 and has been re-opened to the public again as of May 4, 2013 after a reconstruction work. Sungnyemun Gate become a national issue and draw public attention to be a major topic on news or research. In this research, text mining and association rule mining techniques were used on keyword of newspaper articles related to Sungnyemun Gate as a cultural heritage from 2002 to 2016 to find major keywords and keyword association rule. Next, we analyzed some typical and specific keywords that appear frequently and partially depending on before and after the fire and newpaper companies. Through this research, the trends and keywords of newspapers articles related to Sungnyemun Gate could be understood, and this research can be used as fundamental data about Sungnyemun Gate to information producer and consumer.