• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.221-228
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• 2021

This study was conducted to improve the convenience of design of mobile VR devices use in a way binds smart phones. Research on traditional mobile VR devices is insufficient. So the first survey was conducted on users 100 to understand the current status and status of mobile VR devices. As a result, it was found that the satisfaction with the convenience of use was significantly lowered, and countermeasures were needed. Then, a second survey of 30 Heavy Users was conducted to find out specific usability and problems of mobile VR devices. Through this, problems, ease of use, and other opinions of mobile VR devices were found. The survey results were analyzed through the Descriptive Statistics Act, and it was found that improvement was urgent due to low satisfaction with wearing and network. In-depth interviews were conducted with the same respondents. As with the problems derived first, problems such as wearing satisfaction, excessive head weight for long-term use, and lack of content could be found. Based on the previous studies, the focus group interview consisting of 6 experts derived the ease of use evaluation element. It consists of elements that can satisfy the convenience of use of mobile VR devices for creation, wearing satisfaction, network, morphology, learning, and spatiality, and has a total of 26. Using this evaluation elements, it is intended to provide better ease of use to users who will use the mobile VR device.

• Journal of the Korea Computer Graphics Society
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• v.28 no.1
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• pp.1-9
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• 2022

Non-small cell lung cancer (NSCLC) accounts for a high proportion of 85% among all lung cancer and has a significantly higher mortality rate (22.7%) compared to other cancers. Therefore, it is very important to predict the prognosis after surgery in patients with non-small cell lung cancer. In this study, the types of preoperative chest CT image patches for non-small cell lung cancer patients with tumor as a region of interest are diversified into five types according to tumor-related information, and performance of single classifier model, ensemble classifier model with soft-voting method, and ensemble classifier model using 3 input channels for combination of three different patches using pre-trained ResNet and EfficientNet CNN networks are analyzed through misclassification cases and Grad-CAM visualization. As a result of the experiment, the ResNet152 single model and the EfficientNet-b7 single model trained on the peritumoral patch showed accuracy of 87.93% and 81.03%, respectively. In addition, ResNet152 ensemble model using the image, peritumoral, and shape-focused intratumoral patches which were placed in each input channels showed stable performance with an accuracy of 87.93%. Also, EfficientNet-b7 ensemble classifier model with soft-voting method using the image and peritumoral patches showed accuracy of 84.48%.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.1
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• pp.253-275
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• 2022

Niklas Luhmann is one of the most contentious and difficult theorist in sociology but follow-up studies on his theory gradually increase for recent 10 years. The purpose of this study is to observe how follow-up studies use the difficult concepts of Luhmann. Unlike previous studies, this study adopted a keyword rather than an article as the unit of analysis because keywords are linguistic constructs that can make concepts observable. The study analyzed co-occurrence of keywords in 139 articles retrieved from social sciences category in Web of Science DB. The key findings were following: the most important keywords were the name of Luhmann(Niklas Luhmann) and theory(social systems); keywords were grouped into 4 clusters(social systems theory, systems theory, legal system and political system, the significant of Luhmann's theory from the viewpoint of the history of social theory); topic terms were systems theory, communication, Autopoiesis, risk, legal system, functional differentiation, environment, social theory, sociological theory, structural coupling, systems and evolution. The significance of the study is following: the study gives keywords as useful access point for beginners of Luhmann's theory; the study proves that content analysis by keywords network can be applied to trend analysis of difficult theoretical researches.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.947-960
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• 2021

In this study, we examine the AI ethics perception of university students to explore the direction of AI ethics education. For this, 83 students wrote their thoughts about 5 discussion topics on online bulletin board. We analyzed it using language networks, one of the text mining techniques. As a result, 62.5% of students spoke the future of the AI society positively. Second, if there is a self-driving car accident, 39.2% of students thought it is the vehicle owner's responsibility at the current level of autonomous driving. Third, invasion of privacy, abuse of technology, and unbalanced information acquisition were cited as dysfunctions of the development of AI. It was mentioned that ethical education for both AI users and developers is required as a way to minimize malfunctions, and institutional preparations should be carried out in parallel. Fourth, only 19.2% of students showed a positive opinion about a society where face recognition technology is universal. Finally, there was a common opinion that when collecting data including personal information, only the part with the consent should be used. Regarding the use of AI without moral standards, they emphasized the ethical literacy of both users and developers. This study is meaningful in that it provides information necessary to design the contents of artificial intelligence ethics education in liberal arts education.

• Knowledge Management Research
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• v.23 no.2
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• pp.277-299
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• 2022

The massive card transaction data generated in the tourism industry has become an important resource that implies tourist consumption behaviors and patterns. Based on the transaction data, developing a smart service system becomes one of major goals in both tourism businesses and knowledge management system developer communities. However, the lack of rating scores, which is the basis of traditional recommendation techniques, makes it hard for system designers to evaluate a learning process. In addition, other auxiliary factors such as temporal, spatial, and demographic information are needed to increase the performance of a recommendation system; but, gathering those are not easy in the card transaction context. In this paper, we introduce CTDDTR, a novel approach using card transaction data to recommend tourism services. It consists of two main components: i) Temporal preference Embedding (TE) represents tourist groups and services into vectors through Doc2Vec. And ii) Deep tourism Recommendation (DR) integrates the vectors and the auxiliary factors from a tourism RDF (resource description framework) through MLP (multi-layer perceptron) to provide services to tourist groups. In addition, we adopt RFM analysis from the field of knowledge management to generate explicit feedback (i.e., rating scores) used in the DR part. To evaluate CTDDTR, the card transactions data that happened over eight years on Jeju island is used. Experimental results demonstrate that the proposed method is more positive in effectiveness and efficacies.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.8
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• pp.315-324
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• 2022

In this paper, we propose KoEPT, a Transformer-based generative model for automatic math word problems solving. A math word problem written in human language which describes everyday situations in a mathematical form. Math word problem solving requires an artificial intelligence model to understand the implied logic within the problem. Therefore, it is being studied variously across the world to improve the language understanding ability of artificial intelligence. In the case of the Korean language, studies so far have mainly attempted to solve problems by classifying them into templates, but there is a limitation in that these techniques are difficult to apply to datasets with high classification difficulty. To solve this problem, this paper used the KoEPT model which uses 'expression' tokens and pointer networks. To measure the performance of this model, the classification difficulty scores of IL, CC, and ALG514, which are existing Korean mathematical sentence problem datasets, were measured, and then the performance of KoEPT was evaluated using 5-fold cross-validation. For the Korean datasets used for evaluation, KoEPT obtained the state-of-the-art(SOTA) performance with 99.1% in CC, which is comparable to the existing SOTA performance, and 89.3% and 80.5% in IL and ALG514, respectively. In addition, as a result of evaluation, KoEPT showed a relatively improved performance for datasets with high classification difficulty. Through an ablation study, we uncovered that the use of the 'expression' tokens and pointer networks contributed to KoEPT's state of being less affected by classification difficulty while obtaining good performance.

• Journal of the Korea Institute of Building Construction
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• v.22 no.4
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• pp.379-390
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• 2022

While the construction industry is striving to make changes suitable for the 4th industrial revolution era through the introduction of 4th industrial revolution technologies, such change is progressing more slowly than in other industries. Nevertheless, the recent digitization and digital transformation of the construction industry can provide a new paradigm to address and innovate the chronic problems faced by the construction industry. Therefore, in this study, a case study using a data hub and API for use of the data hub, which is essential for digitalization and digital transformation, was conducted, and the efficiency and feasibility of using the data hub and API were considered. When the API system was introduced, it was found that the average budget savings per person was about 23%, and the costbenefit ratio was about 4.4 times higher, indicating that the feasibility of the project was very high. The results and framework of this study can serve as fundamental research data for related research, and provide a worthy case study to promote the introduction of related technologies. This will ultimately contribute to digitalization and digital transformation for smartization of the construction industry.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.3
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• pp.123-155
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• 2022

This study focuses on the management of the news production system in broadcasting companies. This paper concentrates on the process of data registration and metadata management in order to examine whether the currently produced news can have value as a 'public record' in the long term, and whether reliable and accurate information is preserved. In addition, the user experience in the current system is analyzed through in-depth interviews with Ingest Managers, Editors, and Archive Managers, who are closely related to metadata creation compared to other members of the its News Department. Finally, a sustainable metadata quality management method is sought to increase the value of news footage as a 'public record'. In this study, these points can be found out: the metadata of the news agency footage is input manually according to the user's will or working style, that is, the user-friendly metadata input system is insufficient. Accordingly, it can be seen that the quality of the metadata of the news video continues to deteriorate. As an alternative to overcome this, it is found that work flow improvement, system improvement, classification system and metadata improvement plan, etc. are definitely necessary in the short and long term.

• Journal of the Korean Institute of Landscape Architecture
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• v.50 no.5
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• pp.54-68
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• 2022

This study proposes urban development concept and strategies for Garden City, focused on Solaseado, Yeongam Heanam Tourism-Leisure Type Enterprise City in Korea. Understanding that an essential element of a garden is the endless care performed by gardeners, the Garden City development concept suggests applying this idea to making planned cities by cultivating the potential natural landscape of the site in the long run. The meaning of Garden City can be defined in three aspects; an attitude and process of planning a city, a system for constructing the spatial structure of a city, and city branding. A Garden City is a city structured with the spirit of a garden, a city where open space networks become the urban structure, and a city that builds its identity through the landscape, respectively. From this point of view, the research draws development strategies with spatial design examples to embody the Garden City concept in Solaseado by following three steps; establishing the main urban axes, creating city networks through the conjunction of the axes, and categorizing and systematizing open spaces within the city. Consequently, the study shows an alternative urban planning model that extends the concept of a Garden City while maintaining the intrinsic landscape as an urban resource. In addition, the conceptual master plan of Solaseado will structure the urban landscape and park system according to the Garden City strategies.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.43-57
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• 2022

In this paper, we propose a method of analyzing research papers published by researchers belonging to university departments in the field of disaster & safety for the scientometric analysis of the research status in the field of disaster safety. In order to conduct analysis research, the dataset constructed in previous studies was newly improved and utilized. In detail, for research papers of authors belonging to the disaster prevention and safety engineering type department of domestic universities, institution identification, cited journal identification of references, department type classification, disaster safety type classification, researcher major information, KSIC(Korean Standard Industrial Classification) mapping information was reflected in the experimental data. The proposed method has a difference from previous studies in the field of disaster & safety and data set based on related keyword searches. As a result of the analysis, the type and regional distribution of organizations belonging to the department of disaster prevention and safety engineering, the composition of co-authored department types, the researchers' majors, the status of disaster safety types and standard industry classification, the status of citations in academic journals, and major keywords were identified in detail. In addition, various co-occurrence networks were created and visualized for each analysis unit to identify key connections. The research results will be used to identify and recommend major organizations and information by disaster type for the establishment of an intelligent crisis warning system. In order to provide comprehensive and constant analysis information in the future, it is necessary to expand the analysis scope and automate the identification and classification process for data set construction.