• Title/Summary/Keyword: virtual production

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A Study of 'Hear Me Later' VR Content Production to Improve the Perception of the Visually-Impaired (시각 장애인에 대한 인식 개선을 위한 'Hear me later' VR 콘텐츠 제작 연구)

  • Kang, YeWon;Cho, WonA;Hong, SeungA;Lee, KiHan;Ko, Hyeyoung
    • Journal of the Korea Computer Graphics Society
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    • v.26 no.3
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    • pp.99-109
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    • 2020
  • This study was conducted to improve the education method for improving perception awareness of the visually-impaired. 'Hear me later' was designed and implemented based on VR content that allows the visually-impaired experience in the eyes and environment. The main target is from middle and high school students to adolescents in their twenties. It is consisted of a student, the user's daily life with waking up at home in the morning, going to school, taking classes at school, and disembarking home late in the dark. In addition, 10 quests are placed on each map to induce users' participation and activity. These quests are a daily activity for non-disabled people, but it is an activity to experience uncomfortable activity for visually impaired people. In order to verify the effect of 'Hear me later', 8 participants in their early teens to early 20s' perception of visually impaired people was measured through pre and post evaluation of VR contents experience. In order to verify the effect of'Hear me later', 8 participants in their early teens to early 20s' perception of visually impaired people was measured through pre-post evaluation of VR experiences. As a result, it was found that in the post-evaluation of VR contents experience, the perception of the visually impaired was increased by 30% compared to the pre-evaluation. In particular, misunderstandings and changes in prejudice toward the visually impaired were remarkable. Through this study, the possibility of a VR-based disability experience education program that can freely construct space-time and maximize the experience was verified. In addition, it laid the foundation to expand it to various fields of improvement of the disabled.

Economic Impact of HEMOS-Cloud Services for M&S Support (M&S 지원을 위한 HEMOS-Cloud 서비스의 경제적 효과)

  • Jung, Dae Yong;Seo, Dong Woo;Hwang, Jae Soon;Park, Sung Uk;Kim, Myung Il
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.10
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    • pp.261-268
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    • 2021
  • Cloud computing is a computing paradigm in which users can utilize computing resources in a pay-as-you-go manner. In a cloud system, resources can be dynamically scaled up and down to the user's on-demand so that the total cost of ownership can be reduced. The Modeling and Simulation (M&S) technology is a renowned simulation-based method to obtain engineering analysis and results through CAE software without actual experimental action. In general, M&S technology is utilized in Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Multibody dynamics (MBD), and optimization fields. The work procedure through M&S is divided into pre-processing, analysis, and post-processing steps. The pre/post-processing are GPU-intensive job that consists of 3D modeling jobs via CAE software, whereas analysis is CPU or GPU intensive. Because a general-purpose desktop needs plenty of time to analyze complicated 3D models, CAE software requires a high-end CPU and GPU-based workstation that can work fluently. In other words, for executing M&S, it is absolutely required to utilize high-performance computing resources. To mitigate the cost issue from equipping such tremendous computing resources, we propose HEMOS-Cloud service, an integrated cloud and cluster computing environment. The HEMOS-Cloud service provides CAE software and computing resources to users who want to experience M&S in business sectors or academics. In this paper, the economic ripple effect of HEMOS-Cloud service was analyzed by using industry-related analysis. The estimated results of using the experts-guided coefficients are the production inducement effect of KRW 7.4 billion, the value-added effect of KRW 4.1 billion, and the employment-inducing effect of 50 persons per KRW 1 billion.

Application of Greenhouse Climate Management Model for Educational Simulation Design (교육용 시뮬레이션 설계를 위한 온실 환경 제어 모델의 활용)

  • Yoon, Seungri;Kim, Dongpil;Hwang, Inha;Kim, Jin Hyun;Shin, Minju;Bang, Ji Wong;Jeong, Ho Jeong
    • Journal of Bio-Environment Control
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    • v.31 no.4
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    • pp.485-496
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    • 2022
  • Modern agriculture is being transformed into smart agriculture to maximize production efficiency along with changes in the 4th industrial revolution. However, rural areas in Korea are facing challenges of aging, low fertility, and population outflow, making it difficult to transition to smart agriculture. Among ICT technologies, simulation allows users to observe or experience the results of their choices through imitation or reproduction of reality. The combination of the three-dimension (3D) model and the greenhouse simulator enable a 3D experience by virtual greenhouse for fruits and vegetable cultivation. At the same time, it is possible to visualize the greenhouse under various cultivation or climate conditions. The objective of this study is to apply the greenhouse climate management model for simulation development that can visually see the state of the greenhouse environment under various micrometeorological properties. The numerical solution with the mathematical model provided a dynamic change in the greenhouse environment for a particular greenhouse design. Light intensity, crop transpiration, heating load, ventilation rate, the optimal amount of CO2 enrichment, and daily light integral were calculated with the simulation. The results of this study are being built so that users can be linked through a web page, and software will be designed to reflect the characteristics of cladding materials and greenhouses, cultivation types, and the condition of environmental control facilities for customized environmental control. In addition, environmental information obtained from external meteorological data, as well as recommended standards and set points for each growth stage based on experiments and research, will be provided as optimal environmental factors. This simulation can help growers, students, and researchers to understand the ICT technologies and the changes in the greenhouse microclimate according to the growing conditions.

Utilization of Smart Farms in Open-field Agriculture Based on Digital Twin (디지털 트윈 기반 노지스마트팜 활용방안)

  • Kim, Sukgu
    • Proceedings of the Korean Society of Crop Science Conference
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    • 2023.04a
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    • pp.7-7
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    • 2023
  • Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.

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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.