• Journal of the KSME
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• v.29 no.3
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• pp.306-316
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• 1989

최근 자동차 업계의 CAE 방향을 하드웨어 측면에서 보면, 대용량의 계산능력을 갖춘 슈퍼 컴 퓨터와 자체 계산능력을 갖춘 워크스테이션의 활용이 점차적으로 확대 되어가고 있다. 이것을 배경으로 크래쉬 시뮬레이션, 자동차 전체 시스템의 진동 및 소음해석, 공기역학적 특성을 고 려한 형상 최적화 등이 행해지고 있다. 이와 같은 해석을 원활히 수행하기 위해서 고려되어야 할 사항은 우선 사용 소프트웨어 상호간의 데이터 인터페이스를 충분히 고려한 체계적인 총합 CAE 시스템의 구축이고, 인공지능(artificial intelligence) 언어를 이용하여 사용이 용이한 해석 경 험(knowhow)의 데이터 베이스를 구축하는 것도 바람직하다. 또한 상용 소프트웨어가 지원하지 못하는 분야에 대한 자체 프로그램의 개발도 필요한 것이다.

• Defense and Technology
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• no.7 s.161
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• pp.54-59
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• 1992

주변 안보위협의 변화와 함께 조기경보 및 전장감시 등 정보수집능력의 강화가 절실한 현시점에서, 제2회 조기경보/전장감시 심포지엄이 4월 24일 국과연에서 열렸습니다 발표된 내용중 일부(6편)를 발췌, 개작하여 지난 5월호부터 연재, 소개합니다. 지면과 보안관계상 많은 부분을 삭제하거나 수정하여 게재하게 되었음을 양지해주시기 바랍니다

• Defense and Technology
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• no.8 s.162
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• pp.60-63
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• 1992

주변 안보위협의 변화와 함께 조기경보 및 전장감시 등 정보수집능력이 강화가 절실한 현시점에서, 제2회 조기경보/전장감시 심포지엄이 4월 24일 국과연에서 열렸습니다. 발표된 내용중 일부(6편)를 발췌, 개작하여 지난 5월호부터 연재, 소개합니다. 지면과 보안관계상 많은 부분을 삭제하거나 수정하여 게재하게 되었음을 양지해주시기 바랍니다

• The Journal of the Korea Contents Association
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• v.21 no.4
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• pp.205-219
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• 2021

The present study identified determinants to user acceptance of artificial intelligence(AI)-based news anchor. Our conceptual model included three constructs of ability, benevolence, and integrity to determine whether these three constructs are predictive of trust perceived from AI news anchor. This work further examined the influences of social presence, anthropomorphism, perceived usefulness, understanding as well as trust as immediate determinants to user acceptance. The conceptual model was validated on survey data collected from 513 respondents. A series of scale refinement process was conducted by the examination of data normality, common method bias, structure of latent variables as well as internal consistency. In addition, a confirmatory factor analysis was performed to assess the extent to which the sample data collected from survey study measures the constructs adequately. The results from the analysis of structural equation model indicated that, (1) two constructs of ability and integrity were found to be significantly predictive of perceived trust, and (2) anthropomorphism, perceived usefulness, and trust emerged as significant and positive predictors of user acceptance of AI-based news anchor.

• Journal of the Korea Society for Simulation
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• v.15 no.2
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• pp.1-12
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• 2006

As the needs of intelligent systems increase, there have been diverse approaches that combine artificial intelligence (AI) and simulation in the last decade. RG-DEVS, which is the basis for this paper, embedded AI planning techniques into the simulation modeling methodology of DEVS, in order to specify dynamically a simulation model. However, a hierarchy concept, which is used for various types of problem solving systems. is not included in the planning of RG-DEVS. The hierarchy concept reduces the computational cost of planning by reducing the search space, and also makes it easy to apply the hierarchical process flow of a target system to planning. This paper proposes Hierarchical RG-DEVS (HRG-DEVS) in an attempt to insert hierarchical planning capability into RG-DEVS. For the verification of the proposed modeling methodology, HRG-DEVS is applied to model the block's world problem of ABSTRIPS, which is a classical planning problem.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.229-235
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• 2021

Artificial intelligence technology is influencing across all areas as technology advances and social needs change. Therefore, Korean universities have actively developed and operated classes related to artificial intelligence, and have emphasized the importance of artificial intelligence not only in major education but also in liberal arts education. However, there is a lack of research on the development of educational methods and educational programs because artificial intelligence education in liberal arts is in its early stages. SSI is an education that can apply social and ethical problems related to science to open problems that can creatively and reasonably present solutions. SSI can be applied to make AI education more effective. In this study, an artificial intelligence liberal arts curriculum applied SSI was developed with three purposes: First, it is designed is designed so that students subject to education can access it by considering its characteristics as actors of the intelligent information society. Second, it is designed so that students can experience artificial intelligence programs themselves and deal with science technology and social relevance in depth, focusing on various examples of real life. Third, it is designed and approached so that students can participate and cooperate for the purpose of solving common problems to develop cooperative problem-solving skills.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1137-1144
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• 2022

In this study, an artificial intelligence(AI) was developed to help with facial expression practice in order to express emotions. The developed AI used multimodal inputs consisting of sentences and facial images for deep neural networks (DNNs). The DNNs calculated similarities between the emotions predicted by the sentences and the emotions predicted by facial images. The user practiced facial expressions based on the situation given by sentences, and the AI provided the user with numerical feedback based on the similarity between the emotion predicted by sentence and the emotion predicted by facial expression. ResNet34 structure was trained on FER2013 public data to predict emotions from facial images. To predict emotions in sentences, KoBERT model was trained in transfer learning manner using the conversational speech dataset for emotion classification opened to the public by AIHub. The DNN that predicts emotions from the facial images demonstrated 65% accuracy, which is comparable to human emotional classification ability. The DNN that predicts emotions from the sentences achieved 90% accuracy. The performance of the developed AI was evaluated through experiments with changing facial expressions in which an ordinary person was participated.

• Proceedings of The KACE
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• 2017.08a
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• pp.209-211
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• 2017

기계학습은 인공지능(AI, Artificial Intelligence)의 일종으로 다른 인공지능 알고리즘이 정해진 규칙을 기반으로 주어진 임무(Task)를 해결하는 것과는 달리, 기계학습은 수집된 Data를 기반으로 최적의 솔루션을 학습한 후 미래의 값들을 예측하거나 해석하는 방법을 사용하고 있다. 더욱이 인터넷을 통한 연결성의 확대와 컴퓨터의 연산능력 발전으로 가능하게 된 Big-Data를 기반으로 하고 있어 이전의 인공지능 알고리즘에 비해 월등한 성능을 보여주고 있다. 그러나 기계학습 알고리즘이 Data를 학습할 때 학습 결과를 사람이 해석하기에 너무 복잡하여 사람이 그 내부 구조를 이해하는 것은 사실상 불가능하고, 이에 따라 학습된 기계학습 모델의 단점 또는 한계 등을 알지 못하는 문제가 있다. 본 연구에서는 이러한 블랙박스화된 기계학습 알고리즘의 특성을 이해하기 위해, 기계학습 알고리즘이 특정 입력에 대한 결과를 예측할 때 어떤 입력들로 부터 영향을 많이 받는지 그리고 어떤 입력으로부터 영향을 적게 받는지를 알아보는 방법을 소개하고 기존 연구의 단점을 개선하기 위한 방법을 제시한다.

• Journal of Practical Engineering Education
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• v.12 no.2
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• pp.301-308
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• 2020

There are concerns that the recent surge in multicultural families and the continuation of non-face-to-face education, such as remote classes caused by COVID-19, are causing educational gaps among lower grades in elementary school. In particular, the importance of reading, writing and listening to our language should be established in lower grades of elementary school. Therefore, the research has recently developed contents that can enhance understanding by utilizing highly interested artificial intelligence tools and provide interesting Korean language education through play. In the future, there will be various attempts for artificial intelligence tools to be used in lower-grade elementary school education.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.420-422
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• 2023

본 연구는 웨어러블 디바이스를 활용하여 장애인 재활운동 보조를 위한 AI 기반의 맞춤형 서비스 개발을 소개한다. 해당 서비스는 웨어러블 디바이스를 장착한 상태로 운동 중인 사용자의 심박수, 소모 칼로리, 운동 시간 등의 센서 데이터를 수집 및 관리한다. 사용자 생체 데이터는 클라이언트 서버 간 실시간 통신으로 관리되며, django rest framework 로 구축된 서버에 저장된다. 제안 시스템을 통해 수집된 데이터는 시계열 군집화 분석을 위해 k-means clustering 과 k-shape clustering 을 활용하여 체력 평가의 핵심 지표인 심박수를 분석하였다. 특히, 상대적으로 운동이 어려운 장애인 사용자를 위한 맞춤형 운동능력 분석 및 해석에 대한 정보 제공이 가능하다.