• Title/Summary/Keyword: Virtual Process

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A Study on Promoting Performing Art with Robot Actor : Focusing on EveR (로봇 배우를 활용한 공연예술 활성화 방안 연구 : '에버' 중심으로)

  • Lee, Yoo Sun;Kim, Dong Eon
    • (The) Research of the performance art and culture
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    • no.22
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    • pp.371-411
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    • 2011
  • In the twenty first century of rapid cultural change performing art requires new mode of expression based on imaginative power and creativity as well as establishing its own identity. The modern technological environment support this with advanced technology and bring about the expansion of reason from new experience. The introduction of digital media on artistic expression in particular, expands the physical ability of human body which is the main subject of performing art. A virtual body from digital technology is freed from physical boundaries and goes over space and time. It also suggests the possibility of new mode of communication with audience. This study aims at examining the subject of performing art and its digitalized movement focusing on EveR, the world's first professional robot actor. The robot actor which came on stage according to the new expression medium, a digital body, stands in need not only of technological value but also of cultural and artistic application for expression in art. In this endeavor to meet the demand, this study examines the development process and function of 'EveR' the robot actor. Also it searches into the performance of Ever which replaced human being as well as the historical significance of the title:the world's first. To be more specific, there is a example research on two performances:a pansori play "EveR is simply stunning(2009)" and children's play "The Robot Princess and Seven Dwarfs(2009)." Through this example research, it is enabled to anticipate the influence of robot actors on performing arts and to search for the better way of them to evolve. Furthermore, it aims at finding ways to create high value through promoting robot actors to be familiar to the public as well as supporting them to become active cultural contents. The performance with robotic technology is one of the artistic experiment that may cause the change of the future of performing art by actualizing technological imagination together with human body and machinery. As a consequence, it is expected that the meeting of performing art and robotic technology gives positive influence on activating performing art as one of the integrated cultural phenomenon which satisfies the taste of modern era. Moreover, this study may also be the beginning of the expansion of performing art to stretch to diverse field.

Conceptual Model of Establishing Lifestyle (Lifestyle-DEPER [Decision, Execution, Personal Factor, Environment, Resources]) and Lifestyle Intervention Strategies (라이프스타일 형성 모델(Lifestyle-DEPER [Decision, Execution, Personal Factor, Environment, Resources])과 건강을 위한 라이프스타일 중재 전략)

  • Park, Ji-Hyuk;Park, Hae Yean;Hong, Ickpyo;Han, Dae-Sung;Lim, Young-Myoung;Kim, Ah-Ram;Nam, Sanghun;Park, Kang-Hyun;Lim, Seungju;Bae, Suyeong;Jin, Yeonju
    • Therapeutic Science for Rehabilitation
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    • v.12 no.4
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    • pp.9-22
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    • 2023
  • The Lifestyle-DEPER (Decision, Execution, Personal Factors, Environment, Resources) model explains lifestyle formation. Lifestyles are shaped through the decision, execution, and habituation stages. Factors influencing the establishment of a lifestyle are categorized as environmental, resource, and personal. The environment encompasses our surroundings and social, physical, cultural, and virtual environments. Resources refer to what individuals possess, such as health, time, economic, and social resources. Personal factors include competencies, needs, and values. At the lifestyle establishment stage, each of these factors influences a different stage. These collective processes are referred to as events, encompassing both personal and social events. Health-related lifestyle factors include physical activity, nutrition, social relationships, and occupational participation. These are the goals of lifestyle intervention. The intervention strategy based on the Lifestyle-DEPER model, called KEEP (Knowledge, Evaluation, Experience, Plan), is a comprehensive approach to promoting a healthy lifestyle by considering lifestyle formation stages and their influencing factors. This study introduces the Lifestyle-DEPER model and presents a lifestyle intervention strategy (KEEP) to promote health. Further research is required to validate the practicality of the model after applying interventions based on the lifestyle construction model.

Comparison of marginal and internal fit of 3-unit monolithic zirconia fixed partial dentures fabricated from solid working casts and working casts from a removable die system (가철성 다이 시스템으로 제작된 작업 모형과 솔리드 작업 모형 상에서 제작된 지르코니아 3본 고정성 치과 보철물의 변연 및 내면 적합도 비교)

  • Wan-Sun Lee
    • Journal of Dental Rehabilitation and Applied Science
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    • v.40 no.2
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    • pp.72-81
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    • 2024
  • Purpose: This study aimed to assess the marginal and internal fit of 3-unit monolithic zirconia fixed partial dentures (FPDs) fabricated via computer-aided design and computer-aided manufacturing (CAD/CAM) from solid working casts and removable die system. Materials and Methods: The tooth preparation protocol for a zirconia crown was executed on the mandibular right first premolar and mandibular right first molar, with the creation of a reference cast featuring an absent mandibular right second premolar. The reference cast was duplicated using polyvinyl siloxane impression, from which 20 working casts were fabricated following typical dental laboratory procedures. For comparative analysis, 10 FPDs were produced from a removable die system (RD group) and the remaining 10 FPDs from the solid working casts (S group). The casts were digitized using a dental desktop scanner to establish virtual casts and design the FPDs using CAD. The definitive 3-unit monolithic zirconia FPDs were fabricated via a CAM milling process. The seated FPDs on the reference cast underwent digital evaluation for marginal and internal fit. The Mann-Whitney U test was applied for statistical comparison between the two groups (α = 0.05). Results: The RD group showed significantly higher discrepancies in fit for both premolars and molars compared to the S group (P < 0.05), particularly in terms of marginal and occlusal gaps. Color mapping also highlighted more significant deviations in the RD group, especially in the marginal and occlusal regions. Conclusion: The study found that the discrepancies in marginal and occlusal fits of 3-unit monolithic zirconia FPDs were primarily associated with those fabricated using the removable die system. This indicates the significant impact of the fabrication method on the accuracy of FPDs.

Research on Generative AI for Korean Multi-Modal Montage App (한국형 멀티모달 몽타주 앱을 위한 생성형 AI 연구)

  • Lim, Jeounghyun;Cha, Kyung-Ae;Koh, Jaepil;Hong, Won-Kee
    • Journal of Service Research and Studies
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    • v.14 no.1
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    • pp.13-26
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    • 2024
  • Multi-modal generation is the process of generating results based on a variety of information, such as text, images, and audio. With the rapid development of AI technology, there is a growing number of multi-modal based systems that synthesize different types of data to produce results. In this paper, we present an AI system that uses speech and text recognition to describe a person and generate a montage image. While the existing montage generation technology is based on the appearance of Westerners, the montage generation system developed in this paper learns a model based on Korean facial features. Therefore, it is possible to create more accurate and effective Korean montage images based on multi-modal voice and text specific to Korean. Since the developed montage generation app can be utilized as a draft montage, it can dramatically reduce the manual labor of existing montage production personnel. For this purpose, we utilized persona-based virtual person montage data provided by the AI-Hub of the National Information Society Agency. AI-Hub is an AI integration platform aimed at providing a one-stop service by building artificial intelligence learning data necessary for the development of AI technology and services. The image generation system was implemented using VQGAN, a deep learning model used to generate high-resolution images, and the KoDALLE model, a Korean-based image generation model. It can be confirmed that the learned AI model creates a montage image of a face that is very similar to what was described using voice and text. To verify the practicality of the developed montage generation app, 10 testers used it and more than 70% responded that they were satisfied. The montage generator can be used in various fields, such as criminal detection, to describe and image facial features.

Development and evaluation of Pre-Parenthood Education Program for high school students based on Home Economics subject (고등학생을 위한 가정교과 기반 예비부모교육 프로그램 개발 및 평가)

  • Noh, Heui-Yeon;Cho, Jae Soon;Chae, Jung Hyun
    • Journal of Korean Home Economics Education Association
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    • v.29 no.4
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    • pp.161-193
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    • 2017
  • The purpose of this study was to develop and evaluate pre-parenthood education program(PPEP) based on Home Economics(HE) subject for high school students. The development and evaluation of PPEP based on HE subject in this study followed ADDIE model except implementation through 4 processes such as analysis, design, development, and evaluation. First, program development directions were set in three aspects such as 'general development', 'contents', and 'teaching and learning methods'. Themes of the program are 11 in total such as '1. Parenting, what is being a parent', '2. Choosing your spouse, happy marital relationship, the best gift to your children', '3. Pregnancy and birth, a moving meeting with a new life', '4. Taking care of a new born infant for 24 hours', '5. Taking care of infants, relationship with my lovely baby, attachment', '6. Taking care of young children, my child from another planet', '7. Parents and children in healthy family', '8. Parent-child relationship, wise parents to make effective interaction with their children', '9. Parents safety manager at home,', '10. Practice to take care of infants', and '11. Practice of community nurturing support service development'. In particular, learning activities of the program have major characteristics such as 1) utilization of cases including practice problems related to parenting, 2) community exchange activities utilizing learned knowledge and techniques, 3) actual life project activities utilizing learning contents related with parenting, 4) activities inducing positive changes in current life of high school students, and 5) practice activities for the necessities of life such as food, clothing and shelter supporting development of children. Second, the program was developed according to the design. Teaching-learning plans and materials for 17 classes were developed according to 11 themes. The developed plans include class flow and teacher's reference. It starts with receiving a class-related message from a virtual child at the introduction stage and ended with replying to the message by summarizing contents of the class and making a promise as a parent-to-be. That is the basic frame of class flow. Learning materials included various plans and reports necessary for learning activities and they are prepared in details so that they can be play the role of textbooks in regular curriculum. Third, evaluation of developed program was executed by a 5 point Likert scale survey on 13 HE experts on two aspects of program development process and program development results. In the evaluation of development process, mean value was 4.61 and index of content validity was 97.4%. For development results, mean value was 4.37 and index of content validity was 86.9%. These values showed that validity in the development process and results in this study was highly secured and confirmed that PPEP based on HE was appropriate and valid to enhance parent qualifications of high school learners.

A Study on the Improvement of Recommendation Accuracy by Using Category Association Rule Mining (카테고리 연관 규칙 마이닝을 활용한 추천 정확도 향상 기법)

  • Lee, Dongwon
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.27-42
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    • 2020
  • Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.