• The Journal of the Korea Contents Association
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• v.10 no.1
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• pp.37-45
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• 2010

WEB or Internet has given mankind an unprecedented experience in indefinite sharing of online content by original means of digitalized information, but it comes to face an empirical issue of unreasonable informational superfluity as well as a practical issue of collapsed dot.com bubble economy in 2001. Instead, a latest networking concept called 'WEB 2.0' or 'Semantic WEB' becomes embodied as a new approach to entities such as end users and content. The concept of WEB 2.0 for creating a platform on the basis of openness and collaboration has made such a technological setting that we can effectively resolve and manage unreasonable data maintenance and interface inherent in Creative Group Thinking System (CGTS), a WEB-based computer-aided idea generation system developed in 2003. Concerning decreased usability and difficulties with data maintenance due to certain issues of CGTS as a part of WEB R&D platform, such as complex display composition and inefficient data processing system, this study seeks to simplify and streamline data structure by means of AJAX and DOM as WEB2.0-based technologies, and integrate interface structure of WEB platform to focus on end users, so that it can improve interface of conventional CGTS for the purpose of realizing end user's participation through improving usability.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.19-30
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• 2018

The main purposes of this study are to analyze the contents and text network of online tourism information. For this purpose, Jeju Island, one of the representative tourist destinations in South Korea is selected as a study site. And this study collects the contents of both JeJu official tourism website and Sina Weibo's personal blogs which is one of the most popular Social Network Systems in China. In addition, this study analyzes this online text information using ROST Content Mining System, one of the Chinese big data mining systems. The results of the content analysis show that the formal website of Jeju includes the nouns related to natural, geographical and physical resources, verbs related to existence of resources, and adjectives related to the beauty, cleanness and convenience of resources mainly. Meanwhile, personal blogs include the nouns of Korean-wave, food, local products, other destinations and shopping, verbs related to activity and feeling in Jeju, and adjectives related to their experiences and feeling mainly. Finally, the results of text network show that there are some strong centrality and network of online tourism information at formal website, but there are weak relationships in personal blogs. The results of this study may be able to contribute to the development of demand-based marketing strategies of tourists destination.

• The Journal of the Korea Contents Association
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• v.18 no.6
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• pp.504-517
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• 2018

The purpose of this study is to analyze the trends and contents of the research related to young children safety published in the domestic KCI and the candidate journals from 2010 to 2017. To analyze this, we selected 75 articles related to safety for young children published in the KCI and candidate journals from 2010 to 2017. A total of 75 papers were analyzed for frequency, percentage and ${\chi}^2$ using the SPSS Win 23.0 program. The main results of this study are as follows: First, the articles related to young children safety were published the most in 2016 and 2017 and related to infant safety were the least. Next, more than half of the research methods were conducted by quantitative research methods. The results of this study are meaningful in that it presents the necessity of safety education by analyzing trends and contents of research related to young children safety in situations where safety accidents for young children are frequent and the importance of young children safety is more emphasized. It is expected that this research will provide basic data on research topics such as disaster safety who need further research.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.2
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• pp.23-35
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• 2007

With the development of semantic web technologies in information retrieval area, the necessity for thesaurus is recently increasing along with internet lexicons. A thesaurus is the combination of classification and a lexicon, and is the topic map of knowledge structure expressing relations among concepts(terms) subject to human knowledge activities such as learning and research using formally organized and controlled index terms for clarifying the context of superordinate and subordinate concepts. However, although thesaurus are regarded as essential tools for controlling and standardizing terms and searching and processing information efficiently, we do not have a Korean thesaurus for geology. To build a thesaurus, we need standardized and well-defined guidelines. The standardized guidelines enable efficient information management and help information users use correct information easily and conveniently. The present study purposed to build a thesaurus system with terms used in geology. For this, First, we surveyed related works for standardizing geological terms in Korea and other countries. Second, we defined geological topics in 15 areas and prepared a classification system(draft) for each topic. Third, based on the geological thesaurus classification system, we created the specification of geological thesaurus. Lastly, we designed and implemented an internet-based geological thesaurus system using the specification.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.583-598
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• 2022

As human-based tunnel inspections are affected by the subjective judgment of the inspector, making continuous history management difficult. There is a lot of deep learning-based automatic crack detection research recently. However, the large public crack datasets used in most studies differ significantly from those in tunnels. Also, additional work is required to build sophisticated crack labels in current tunnel evaluation. Therefore, we present a method to improve crack detection performance by inputting existing datasets into a deep learning model. We evaluate and compare the performance of deep learning models trained by combining existing tunnel datasets, high-quality tunnel datasets, and public crack datasets. As a result, DeepLabv3+ with Cross-Entropy loss function performed best when trained on both public datasets, patchwise classification, and oversampled tunnel datasets. In the future, we expect to contribute to establishing a plan to efficiently utilize the tunnel image acquisition system's data for deep learning model learning.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.6
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• pp.513-524
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• 2022

Recently, detecting damages of civil infrastructures from digital images using deep learning technology became a very popular research topic. In order to adapt those methodologies to the field, it is essential to explain robustness of deep learning models. Our research points out that the existing pixel-based deep learning model evaluation metrics are not sufficient for detecting cracks since cracks have linear appearance, and proposes a new evaluation methodology to explain crack segmentation deep learning model more rationally. Specifically, we design, implement and validate a methodology to generate tolerance buffer alongside skeletonized ground truth data and prediction results to consider overall similarity of topology of the ground truth and the prediction rather than pixel-wise accuracy. We could overcome over-estimation or under-estimation problem of crack segmentation model evaluation through using our methodology, and we expect that our methodology can explain crack segmentation deep learning models better.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.691-704
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• 2021

The development of AI technology has brought about a big change in our lives. The importance of AI and data education is also growing as AI's influence from life to society to the economy grows. In response, the OECD Education Research Report and various domestic information and curriculum studies deal with data literacy and present it as an essential competency. However, the definition of data literacy and the content and scope of the components vary among researchers. Thus, we analyze the semantic similarity of words through Word2Vec deep learning natural language processing methods along with the definitions of key data literacy studies and analysis of word frequency utilized in components, to present objective and comprehensive definition and components. It was revised and supplemented by expert review, and we defined data literacy as the 'basic ability of knowledge construction and communication to collect, analyze, and use data and process it as information for problem solving'. Furthermore we propose the components of each category of knowledge, skills, values and attitudes. We hope that the definition and components of data literacy derived from this study will serve as a good foundation for the systematization and education research of AI education related to students' future competency.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.4
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• pp.253-263
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• 2021

Concrete structures are damaged by aging and external environmental factors. This type of damage is to appear in the form of cracks, to proceed in the form of spalling. Such concrete damage can act as the main cause of reducing the original design bearing capacity of the structure, and negatively affect the stability of the structure. If such damage continues, it may lead to a safety accident in the future, thus proper repair and reinforcement are required. To this end, an accurate and objective condition inspection of the structure must be performed, and for this inspection, a sensor technology capable of detecting damage area is required. For this reason, we propose a deep learning-based image processing algorithm that can detect spalling. To develop this, 298 spalling images were obtained, of which 253 images were used for training, and the remaining 45 images were used for testing. In addition, an improved loss function and data augmentation technique were applied to improve the detection performance. As a result, the detection performance of concrete spalling showed a mean intersection over union of 80.19%. In conclusion, we developed an algorithm to detect concrete spalling through a deep learning-based image processing technique, with an improved loss function and data augmentation technique. This technology is expected to be utilized for accurate inspection and diagnosis of structures in the future.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.302-312
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• 2019

Stamps are the smallest image symbols that can be read in the period, and they include the history, culture, politics, and figures and events of the issuing country. In particular, the stamps of the past presidents include the contemporary history of Korea, and reexamining and reviewing the meaning of the presidential stamps historically has a meaning that can not be overlooked as a researcher who studies the image of political leaders. In this study, the scope of research from the first republic to the fifth republic, where the publicity of political leaders through the advertisement of stamps and placards was high, was conducted and the leader image formation and change process centering on the former presidents Rhee Seungman, Park Jeong Hee, Chun Doo Hwan, Respectively. For the interpretation of the image of political leaders according to the changes of time, the images were classified by using Osgood's Semantic Differential Scale, and the images were analyzed using Saussure's semiotics. The image continues to move and change, and the conclusion that the image of the political leader of the time is not a simple personal image but a social product reflecting the specific age of the era.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.808-823
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• 2021

This study was conducted to explore the experience and its meaning of the elderly residents in long-term care facilities(LTCFs). It is aimed to find the role of family and society for the qualitative care of elderly living in LTCF and to seek social welfare measures. For this purpose, qualitative research data was collected by conducting in-depth interviews and participation observations on 8 elderly residents at 4 LTCFs in Seoul, Incheon, and Gyeonggi Province. The collected data were analyzed using Giorgi's phenomenological research method. The analysis results show that 33 semantic units, 14 subcomponents, and 4 upper components. The 4 upper components showed up as 「Crumbling my existence」, 「The life thrown into an unfamiliar environment」, 「New relationship where discomfort and gratitude coexist」 and 「My life I want to find」. Among them, 「My life I want to find」 was the essence of the living experiences of elderly residents in LTCF. Through this study, it was suggested creating an environment to provide facilities access preparation program for the elderly, developing and activating various family participation programs, providing conditions of Aging in place for the elderly, and developing and activating community resource linkage programs.