• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.1
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• pp.253-263
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• 2017

As needs for knowledge on Korean history and the attention of the people are rapidly increasing, various smartphone applications for learning the history have appeared during recent years. These applications provide multiple choice questions to users through their own problem banks. But, since these questions are selected from the fixed set of problems that are stored previously, the learning efficiency of users is inevitably decreased when they use the applications repeatedly. In this paper, we present a question generation system named K-History which generates multiple choice questions in an automatic way using the database on the history of Korea. In addition, we also describe the development of the application Korean History Infinite Challenge as a learning application for Korean history. To develop K-History, we classify typical types of learning problems through various problems based on Korean history learning materials, proposing algorithms to generate problems according to the types found. Through the developed techniques, various learning systems can reduce the cost for creating questions, while increasing the learning efficiency of users.

• Design Convergence Study
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• v.15 no.2
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• pp.347-368
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• 2016

Recently, researches for the word of mouth(WOM) imply that consumers use WOM informations of products in their purchase process. This study suggests methods using opinion mining and visualization to understand consumers' opinion of each goods and each markets. For this study we conduct research that includes developing domain ontology based on reviews confined to "movie" category because people who want to have watching movie refer other's movie reviews recently, and it is analyzed by opinion mining and visualization. It has differences comparing other researches as conducting attribution classification of evaluation factors and comprising verbal dictionary about evaluation factors when we conduct ontology process for analyzing. We want to prove through the result if research method will be valid. Results derived from this study can be largely divided into three. First, This research explains methods of developing domain ontology using keyword extraction and topic modeling. Second, We visualize reviews of each movie to understand overall audiences' opinion about specific movies. Third, We find clusters that consist of products which evaluated similar assessments in accordance with the evaluation results for the product. Case study of this research largely shows three clusters containing 130 movies that are used according to audiences'opinion.

• Design Convergence Study
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• v.16 no.3
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• pp.103-118
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• 2017

It is expected that the integrated control service of the public sector will be increased for the safety of citizens in the future. Therefore, In this study, we analyzed the classification of CCTV control center and the characteristics of interior design. The survey was conducted at eight control centers in Seoul that were constructed since 2007 and analyzed according to the criteria of general matters, services, spatial basic information, spatial structure, and internal structure. The results of the survey are summarized as follows. Based on the results of the study, the Integrated Control Center is a space where the ratio of the physical environment is not high but performs important tasks for the citizens of the city, which are operated 24 hours a day, and security and security. It is characterized by the efficient space allocation for the treatment, the design of the moving line, and the connection according to the urgent work flow. The results of this study are expected to be used as basic data for other integrated control center environment.

• Trans-
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• v.15
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• pp.1-24
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• 2023

This study examines the application of data visualization technology using a clustered data algorithm called 'Tamed Cloud' to virtual spaces and seeks the possibility of implementing it in various types of realistic exhibition contents. To this end, we first attempt to classify virtual reality (VR) exhibition contents starting with COVID-19, and summarize technologies applied. Also, various realistic exhibition contents provide visitors with an opportunity to appreciate the artworks through online and virtual exhibitions. In this trend, virtual reality and augmented reality (AR) technologies have been introduced, allowing visitors to enjoy the artwork more immersively, and the possibility of realistic exhibition content with interaction between the artwork and the user is also being demonstrated. Based on this background, this study examines the history of exhibition contents by dividing them before and after the advent of virtual reality technology, and examines how the clustered algorithm technology called Tamed Cloud was applied to virtual space and implemented as a realistic exhibition content in <70mK> project. By synthesizing all of this, we propose a convergence method of data visualization, virtual reality, and realistic content, and propose it as a new alternative to realistic exhibition content in virtual space.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.189-192
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• 2021

YouTube, the world's largest video sharing platform, is loved by many users in that it provides numerous videos and makes it easy to get helpful information. However, the ratio of like/hate for each video varies according to the subject or upload time, even though they are in the same channel; thus, previous studies try to understand the reason by inspecting some numerical statistics such as the ratio and view count. They can help know how each video is preferred, but there is an explicit limitation to identifying the cause of such preference. Therefore, this study aims to determine the reason that affects the preference through matching between topic words extracted from comments in each video and non-sympathetic types defined in advance. Among the top 10 channels in the field of 'pets' and 'cooking', where outliers occur a lot, the top 10 videos (the threshold of pet: 4.000, the threshold of cooking: 0.723) with the highest ratio were selected. 11,110 comments collected totally, and topics were extracted and matched with non-sympathetic types. The experimental results confirmed that it is possible to predict whether the rate of like/hate would be high or which non-sympathetic type would be by analyzing the comments.

• Korea Science and Art Forum
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• v.20
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• pp.409-419
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• 2015

Service Design Platform which has been developing under the sponsorship of the Ministry of Knowledge Economy is aimed at facilitating service design consultancy to carry out service design projects smoothly online. In the development process in order to verify and improve the usability of the platform, heuristic evaluations by usability experts along with usability test done by user participation are required. This study was conducted for the purpose of deriving appropriate evaluation areas and detailed evaluation indices prior to carrying out the heuristic evaluation. For the study, first, the concept of the service design platform was identified and the features of its component were analyzed. Second, based on literature study of standards which are related to usability evaluation indices, usability evaluation areas and indices were analyzed. Third, in order to establish and verify evaluation areas and indices which are appropriate for the evaluation, Delphi survey was conducted and its validity was verified. Through this study, evaluation indices with 4 evaluation areas and 45 detailed items were derived. Derived evaluation indices was made in the form of checklist and will be utilized for heuristic evaluation by usability experts.

• Korean Journal of Construction Engineering and Management
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• v.24 no.6
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• pp.66-73
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• 2023

The construction industry suffers losses due to failures in demand forecasting due to price fluctuations in construction raw materials, increased user costs due to project cost changes, and lack of forecasting system. Accordingly, it is necessary to improve the accuracy of construction raw material price forecasting. This study aims to predict the price of construction raw materials and verify applicability through the improvement of the Data Refactor technique. In order to improve the accuracy of price prediction of construction raw materials, the existing data refactor classification of low and high frequency and ARIMAX utilization method was improved to frequency-oriented and ARIMA method utilization, so that short-term (3 months in the future) six items such as construction raw materials lumber and cement were improved. ), mid-term (6 months in the future), and long-term (12 months in the future) price forecasts. As a result of the analysis, the predicted value based on the improved Data Refactor technique reduced the error and expanded the variability. Therefore, it is expected that the budget can be managed effectively by predicting the price of construction raw materials more accurately through the Data Refactor technique proposed in this study.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• The Journal of Sustainable Design and Educational Environment Research
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• v.23 no.1
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• pp.1-11
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• 2024

Complex school facilities are being considered to meet increased public demands for culture and welfare in Korea, given the decreasing population. In this context, Gyeongi-do Hwaseong City's E-umteo is recognized as a relatively well-operated school complex. Therefore, this study considered seven E-umteo branches as case studies to examine the operations of educational programs and understand the techniques employed in the spatial configuration of E-umteo. To this end, field observations and interviews with facility operators were conducted. The case analysis results revealed that educational programs could be classified into three types: learning sharing , community communication, and lifelong learning. Furthermore, the learning sharing type was classified into education and physical education while the community communication type was classified into the community and convenience types. Meanwhile, lifelong learning was identified as the most actively used type by differentiating specialized programs. With regard to the spatial composition between the school and the "pitcher," only the connection and independent types were observed, and no integral type was discovered. Therefore, integrated future studies are mandated.

• Information Systems Review
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• v.22 no.3
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• pp.119-142
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• 2020

This study aims to examine the role of IT features as heuristic cues in choosing a content on YouTube. According to the heuristic-systematic model, people tend to rely on heuristic cues when they have to choose and process useful information quickly so that they could save time and reduce demands for thinking. Based on this line of reasoning, this study posits that YouTube users rely on certain IT features as heuristic cues in choosing contents before they actually watch them. Based on the prior literature and interviews with YouTube users, we develop a research model in which social endorsement, self-presentation, and interactivity are identified as potential determinants of users' attitude toward contents, which in turn influence their intention to watch them. To empirically test the research model, we conduct a laboratory experiment and a follow-up survey. The results of data analysis show that social endorsement for the content, YouTube creator's self-presentation, and interactivity have significant and positive effects on their attitude toward the content, leading to their intention to watch it. This study suggests that IT features on YouTube could be wisely utilized to increase the chance that users choose a particular content out of many competing contents when they search certain information on YouTube.