• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.205-212
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• 2019

Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only object types, their positions and attributes, but also three-dimensional spatial relationships between them, An 3D scene graph can be viewed as a prior knowledge base describing the given environment within that the agent will be deployed later. Therefore, 3D scene graphs can be used in many useful applications, such as visual question answering (VQA) and service robots. This proposed 3D scene graph generation model consists of four sub-networks: object detection network (ObjNet), attribute prediction network (AttNet), transfer network (TransNet), relationship prediction network (RelNet). Conducting several experiments with 3D simulated indoor environments provided by AI2-THOR, we confirmed that the proposed model shows high performance.

• Journal of The Korean Association For Science Education
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• v.37 no.6
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• pp.1037-1049
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• 2017

The purpose of this study is to explore how the flow of discourse move and their reasoning process in dialogic argumentation during group modeling on excretion. Five groups of three to four students in the second grade of a middle school participated in the modeling practice of a Gifted Center. Analysis was conducted on argumentation during the modeling activity in which students should explain how the waste product (ammonia) leaves the body. It was found that there was a sequential argumentative process-tentative consensus, solving the uncertainty, and consensus. There were several discourse moves - 'claim' and 'counterclaim' in the stage of tentative consensus, 'query' and 'clarification of meaning' in the stage of solving the uncertainty, and 'change of claim' in the stage of consensus. Students participated in the dialogic argumentation by constructing argument collaboratively for reaching a consensus. Critical questioning in the stage of solving the uncertainty and reasoning in the stage of consensus were the impact factors of dialogic argumentation. By answering the critical questions, students changed their claims or suggested new claims by defending or rebutting previous claims. Students justified group claims with diverse argumentation scheme and scientific reasoning to reach a group consensus. These findings have implication for science educators who want to adopt dialogic argumentation in science classes.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.219-240
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• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.3
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• pp.160-165
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• 2023

In this study, we propose an SNS sentence writing assistance system that utilizes YOLO and GPT to assist users in writing texts with images, such as SNS. We utilize the YOLO model to extract objects from images inserted during writing, and also extract meta-information such as GPS information and creation time information, and use them as prompt values for GPT. To use the YOLO model, we trained it on form image data, and the mAP score of the model is about 0.25 on average. GPT was trained on 1,000 blog text data with the topic of 'restaurant reviews', and the model trained in this study was used to generate sentences with two types of keywords extracted from the images. A survey was conducted to evaluate the practicality of the generated sentences, and a closed-ended survey was conducted to clearly analyze the survey results. There were three evaluation items for the questionnaire by providing the inserted image and keyword sentences. The results showed that the keywords in the images generated meaningful sentences. Through this study, we found that the accuracy of image-based sentence generation depends on the relationship between image keywords and GPT learning contents.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.254-264
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• 2009

The purpose of this study was to develop a performance measurement factor of Balanced Scorecard(BSC) for health-care organization. We did also the research to evaluate the validity and reliability of these indicators. Fifty six health-care organizations are participated in a survey questionnaires. This questionnaires consists of 53-questions, which are the performance evaluation indicators designed by researcher, which are based on the Norton and Kaplan's BSC-Framework. Exploratory and confirmatory factor analysis was carried out and Analytical Hierarchy Process (AHP) was applied to analyze the weight and significances of each factor. Factor analysis of the BSC resulted in 11 major measurement factors (Eigenvalue >1.0). The AHP analysis showed the list of the hospital BSC measurement factors and its KPI(Key Performance Indicator) weighted by its significance priorities. The recommendable degree of reliability and validity of these BSC factors suggests that these factors are adequate for performance measurements of the health-care organizations in Korea.

• Journal of the Korean earth science society
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• v.28 no.3
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• pp.266-276
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• 2007

This purpose of this study was to analyze high school students' alternative conceptions and understanding levels about rocks, crust, plate tectonics and interior of the Earth. Data were collected through surveys, drawing assignments, and interviews. A total of 158 high school students in the first grade were involved in this study. The results showed that students have lots of major alternative conceptions which are meaning and forming process of rock, distinction of continental crust and ocean crust, formation and disappearance of ocean crust, movement of plate, continental drift, activities of volcano and earthquake. Physical and chemical characteristics, including mantle and core state could be found through analyzing from drawings.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.177-184
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• 2007

The purpose of this study is to develop tool that makes students and teachers generate the music therapy system of type as they want by using existing several web-based component technologies. This study develops tool that can generate psychological testing system and users can select image(visual expression) that represents best their psychological state and after some stage can listen the most adequate music in that situation and it can be used as a music therapy too. This tool makes be possible for developer to input and arrange question types and stages, images that can show images connected with them and to offer skill that let them hear adequate music after deciding psychological state. This system development will be able to approach the contents development which is various from education field effectively in order.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.5
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• pp.1052-1059
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• 2009

Health care has become one of the paramount issues of the 21st century as governments and individuals grapples the complex problems associated with contemporary medical care such as cost, affordability, and shifting demographic trends. The purpose of this study was to develop the critical success factors of medical tourism for health-care organizations and to measure the wights of these factors. For this purpose, we gathered the data from doctors, travelling agencies and scholars. about the success factors of medical tourism. Exploratory and confirmatory factor analysis was carried out to determine the factors as the Critical Success Factors of medical tourism. We did also the research to evaluate the validity and reliability of these factors. After that the Analytical Hierarchy Process (AHP) was applied to analyze the weight and significances among these factors. Factor analysis resulted in 15 major factors (Eigenvalue > 1.0). The AHP analysis showed the list of Critical Success Factors weighted by its significance priorities. The recommendable degree of reliability and validity suggests that these factors could be the valuable refences for the policy making process of the medical tourism in Korea.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.339-346
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• 2017

There is increasing interest in text analysis based on unstructured data such as articles and comments, questions and answers. This is because they can be used to identify, evaluate, predict, and recommend features from unstructured text data, which is the opinion of people. The same holds true for TEL, where the MOOC service has evolved to automate debating, questioning and answering services based on the teaching-learning support system in order to generate question topics and to automatically classify the topics relevant to new questions based on question and answer data accumulated in the system. Therefore, in this study, we propose topic modeling using LDA to automatically classify new query topics. The proposed method enables the generation of a dictionary of question topics and the automatic classification of topics relevant to new questions. Experimentation showed high automatic classification of over 0.7 in some queries. The more new queries were included in the various topics, the better the automatic classification results.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.157-162
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• 2019

This thesis analyzed the intermediation and correlation of positive humor style and negative humor style through an entertainment program broadcasted on SBS. For the theoretical background, the Humor Style Questionnaire(HSQ) developed by Martin et al., was selected. As the research methods, first, after classifying the types of humor style of members of , this study analyzed how the positive humor style and negative humor style would intermediate the formation of humor, and also the correlation of humor style of members. The types of positive humor style and negative humor style shown in were balanced in 4:4, which was classified in accordance with age, career experience, and power. The mediation of humor formation occurred at the point where humors confronted. The humor style had the correlation with twist.