• 전기학회논문지
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• 제57권3호
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• pp.344-353
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• 2008

To apply the appropriate new grounding system to domestic power system, safety has to be guaranteed under the given circumstances. It is not possible to decide the safety of grounding systems by the experimental test because safety experiments directly relate to the human life and the installed electric machines. Therefore, the computer simulation program to decide the safety of grounding systems based on the IEC standard systems, has to be developed. This paper proposes the computer simulation based method to decide the safety of grounding system with the concepts of touch voltage, step voltage, human resistivity, and applied electric current according to the several conditions of human body located in the corresponding grounding systems. The proposed method is implemented by Matlab/Simulink and Visual C++ programming tools for its visualization.

• 한국멀티미디어학회논문지
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• 제7권12호
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• pp.1692-1699
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• 2004

Many researchers have developed various techniques for detection of human faces in ordinary still images. Face detection is the first imperative step of human face recognition systems. The two main problems of human face detection are how to cutoff the running time and how to reduce the number of false positives. In this paper, we present frontal and near-frontal face detection algorithm in still gray images using a thick edge image and neural network. We have devised a new filter that gets the thick edge image. Our overall scheme for face detection consists of two main phases. In the first phase we describe how to create the thick edge image using the filter and search for face candidates using a whole face detector. It is very helpful in removing plenty of windows with non-faces. The second phase verifies for detecting human faces using component-based eye detectors and the whole face detector. The experimental results show that our algorithm can reduce the running time and the number of false positives.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 합동 추계학술대회 논문집 정보 및 제어부문
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• pp.184-186
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• 2001

This paper describes a method of human sensibility evaluation for pleasant and unpleasant environments. Conditions of the environment are room temperature and humidity. Changing the conditions, 10-channel EEG signals for 4 subjects are collected. Linear predictor coefficients of the recorded EEGs are extracted as the feature parameter of human sensibility. A neural network-based human sensibility estimation algorithm is developed. The developed algorithm showed good performance in the pleasantness evaluation. The neural network output produced accurate states of pleasantness sensibility. Subject-independent test showed similar results with subject-dependent test.

• 대한인간공학회지
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• 제14권2호
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• pp.33-39
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• 1995

The inverse Kinematics can be used for representing the motion of human body model. In order to find the final figure of the human body model with given target position, we can uwe the formula x=J .THETA. , where J is the Jacobian matrix of x=f( .THETA.), of the Inverse Kinematics. In this formula, f has so complicated form that it is difficult to calcuate the Jacobian matrix J by expanding all formulae exactly. In this paper, a numerical method that calculates the Jacobian matrix is proosed. The simulation results obtained by using the simple human model reprsent that the proposed. The simulation results obtained by using the simple human model represent that the proposed method is useful for generating the final figure of the body model.

• 한국정보디스플레이학회:학술대회논문집
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• 한국정보디스플레이학회 2009년도 9th International Meeting on Information Display
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• pp.1550-1553
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• 2009

We studied the human visual performance with PDP and LCD to clarify the relationships between viewer preference and chromatic adaption. In this paper, optical performance of the display is measured mechanically based on standard. The human visual performance about the display color image quality trough optical process is represented numerically based on CIECAM02. By comparing these results with the result of the questionnaire, performance of the display can be evaluated in detail.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 1999년도 KOBA 방송기술 워크샵 KOBA Broadcasting Technology Workshop
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• pp.11-14
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• 1999

The forthcoming century will be the "era of cyber society" . In a virtual environment, a cyber character plays the role of an agent for the human being. In this paper, we introduce active researches of industries, universities, and research institutes in Korea. After Adam Soft Inc. presented a cyber singer,“Adam”, a few cyber characters have succeeded commercially through Internet, TV, CF, movies and etc. Some universities had their own characters to make fundamental researches in the fields of modeling, motion control, and VR. Research institutes have been funded recently to a cyber character related researches. This paper briefly reviews the recent research works, and future trends in Korea. in Korea.

• International Journal of Computer Science & Network Security
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• 제22권6호
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• pp.97-108
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• 2022

The video-assisted human action recognition [1] field is one of the most active ones in computer vision research. Since the depth data [2] obtained by Kinect cameras has more benefits than traditional RGB data, research on human action detection has recently increased because of the Kinect camera. We conducted a systematic study of strategies for recognizing human activity based on deep data in this article. All methods are grouped into deep map tactics and skeleton tactics. A comparison of some of the more traditional strategies is also covered. We then examined the specifics of different depth behavior databases and provided a straightforward distinction between them. We address the advantages and disadvantages of depth and skeleton-based techniques in this discussion.

• International Journal of Computer Science & Network Security
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• 제23권3호
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• pp.144-150
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• 2023

With progressive advancements in Man-made consciousness (computer based intelligence) and Profound Learning (DL), contributing altogether to Normal Language Handling (NLP), the precision and nature of Machine Interpretation (MT) has worked on complex. There is a discussion, but that its no time like the present the human interpretation became immaterial or excess. All things considered, human flaws are consistently dealt with by its own creations. With the utilization of brain networks in machine interpretation, its been as of late guaranteed that keen frameworks can now decipher at standard with human interpreters. In any case, simulated intelligence is as yet not without any trace of issues related with handling of a language, let be the intricacies and complexities common of interpretation. Then, at that point, comes the innate predispositions while planning smart frameworks. How we plan these frameworks relies upon what our identity is, subsequently setting in a one-sided perspective and social encounters. Given the variety of language designs and societies they address, their taking care of by keen machines, even with profound learning abilities, with human proficiency looks exceptionally far-fetched, at any rate, for the time being.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2023년도 제35회 한글 및 한국어 정보처리 학술대회
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• pp.672-676
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• 2023

지식 추적 (knowledge tacing)은 주어진 학습자의 과거 문제 해결 기록을 기반으로 학습자의 지식 습득 정도를 파악하여 목표 문제에 대한 정답 여부를 예측하는 것을 목표로 한다. 이전 연구에서는 이진 분류 기반의 모델을 사용하여 정답 유무만 예측하였기 때문에 학습자의 답변에 존재하는 정보를 활용하지 못한다. 최근 연구에서는 이를 생성 태스크로 변환하여 컴퓨터과학 분야에서 프로그래밍 질문에 대한 지식 추정을 수행하는 open-ended knowledge tracing (OKT)이 제안되었다. 하지만 최적의 OKT 모델에 대한 연구는 진행되지 않았으며 따라서 본 논문에서는 시간에 따라 변화하는 학습자의 지식 상태에 따라 답변 생성을 조정하는 새로운 OKT 방법론을 제안한다. 실험을 본 논문에서 제안하는 방법론의 우수성과 효율성을 증명한다.

• 한국정보과학회 언어공학연구회:학술대회논문집(한글 및 한국어 정보처리)
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• 한국정보과학회언어공학연구회 2023년도 제35회 한글 및 한국어 정보처리 학술대회
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• pp.726-729
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• 2023

본 논문에서는 대화 중 발화에서 페르소나 트리플을 추출하는 방법을 연구한다. 발화 문장과 그에 해당하는 트리플 쌍을 활용하여 발화 문장 혹은 페르소나 문장이 주어졌을 때 그로부터 페르소나 트리플을 추출하도록 모델을 멀티 태스크 러닝 방식으로 학습시킨다. 모델은 인코더-디코더 구조를 갖는 사전학습 언어모델 BART [1]와 T5 [2]를 활용하며 relation 추출과 tail 추출의 두 가지 태스크를 각각 인코더, 디코더 위에 head를 추가하여 학습한다. Relation 추출은 분류로, tail 추출은 생성 문제로 접근하도록 하여 최종적으로 head, relation, tail의 구조를 갖는 페르소나 트리플을 추출하도록 한다. 실험에서는 BART와 T5를 활용하여 각 태스크에 대해 다른 학습 가중치를 두어 훈련시켰고, 두 모델 모두 relation과 tail을 추출하는 태스크 정확도에 있어서 90% 이상의 높은 점수를 보임을 확인했다.