• 한국철도학회논문집
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• 제6권4호
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• pp.221-231
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• 2003

Most rail system related simulators currently used are designed to simulate only one discipline system. This obviously assumes the other discipline systems are running regularly not being affected by the system being simulated. In this paper a multi discipline simulator is proposed and its design concept is presented. A multi discipline simulator is the simulator in which major subsystems with different technical discipline are simulated simultaneously. The advantage of the simulator is in that it makes it possible to analyze the systems behavior while other discipline system vary. With this we can identify the possible multi-discipline problems and even find their solutions. A proto type simulator has been developed using object oriented programming. Object concept was judged best suitable to model the various multi-discipline self-controlling railway subsystems. It was applied to the target system, which is under development by the Korea Railroad Research Institute. The test results shows it is very useful in designn verification. It could also be a good tool in research and development work to improve the system.

• 제어로봇시스템학회논문지
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• 제11권5호
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• pp.398-405
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• 2005

The intelligent robots that will be needed in the near future are human-friendly robots that are able to coexist with humans and support humans effectively. To realize this, robots need to recognize their position and posture in known environment as well as unknown environment. Moreover, it is necessary for their localization to occur naturally. It is desirable for a robot to estimate of his position by solving uncertainty for mobile robot navigation, as one of the best important problems. In this paper, we describe a method for the localization of a mobile robot using image information of a moving object. This method combines the observed position from dead-reckoning sensors and the estimated position from the images captured by a fixed camera to localize a mobile robot. Using a priori known path of a moving object in the world coordinates and a perspective camera model, we derive the geometric constraint equations which represent the relation between image frame coordinates for a moving object and the estimated robot's position. Also, the control method is proposed to estimate position and direction between the walking human and the mobile robot, and the Kalman filter scheme is used for the estimation of the mobile robot localization. And its performance is verified by the computer simulation and the experiment.

• 영어영문학
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• 제58권4호
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• pp.783-807
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• 2012

This study compares and contrasts Freud's "work of mourning" which mostly appears in his memorable essay "Mourning and Melancholia" and Derrida's theory of mourning which appears in various works such as MEMOIRES for Paul de Man, The Work of Mourning, and others. Freud maintains that the mourner begins to sever emotional ties to the lost object through a labor of memory and eventually completes the work of mourning. It is a "testing of reality" that motivates the mourner to begin to relinquish emotional attachment to the lost object. Derrida, however, challenges Freudian work of mourning by saying that true mourning lies in "respecting the Otherness of the Other." Derrida suggests that Freud's "normal work of mourning" is "unjust betrayal" of the lost object because it "kills" and "devours" the other and thereby makes it part of the self. So he proposes that work of mourning has "to fail in order to succeed": "success fails" and "failure succeeds." There is an enormous, even epistemological, chasm between Freud who states that mourning, "however painful it may be, comes to a spontaneous end" and Derrida who states that "mourning is interminable. Inconsolable. Irreconcilable." and "I mourn Therefore I am." The former is the voice of "testing of reality" and common sense whereas the latter is that of utopian ethical vision. Yet neither seems to get the upper hand and they are kind of forced to maintain an ongoing dialogue with each other, for true mourning seems to lie somewhere in between.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1315-1318
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• 2003

In this paper, a neural network based approach using a self-organizing feature map is proposed for the segmentation of X ray images. A number of algorithms based on such approaches as histogram analysis, region growing, edge detection and pixel classification have been proposed for segmentation of general images. However, few approaches have been applied to X ray image segmentation because of blur of the X ray image and vagueness of its edge, which are inherent properties of X ray images. To this end, we develop a new model based on the neural network to detect objects in a given X ray image. The new model utilizes Mumford-Shah functional incorporating with a modified adaptive SOFM. Although Mumford-Shah model is an active contour model not based on the gradient of the image for finding edges in image, it has some limitation to accurately represent object images. To avoid this criticism, we utilize an adaptive self organizing feature map developed earlier by the authors.[1] It's learning rule is derived from Mumford-Shah energy function and the boundary of blurred and vague X ray image. The evolution of the neural network is shown to well segment and represent. To demonstrate the performance of the proposed method, segmentation of an industrial part is solved and the experimental results are discussed in detail.

• 정보처리학회논문지B
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• 제15B권5호
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• pp.407-412
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• 2008

잡음이 심한 배경을 가진 영상 내부의 영역 분할 처리 과정은 해결하기 매우 어려운 문제로 인식되어 왔다. 그에 따라 이 문제를 해결하기 위한 기초적 방법론에 관한 연구 및 주어진 문제에 따라 실제적 적용을 위한 다양한 노력이 있어왔다. 본 논문에서는 영상 분할을 위한 새로운 접근법을 제시하는 것을 목적으로 하였다. 새로운 방법론으로서 기존의 관심 객체 분할의 반대인 배경 영역 분할이라는 새로운 관점을 연구의 중심으로 하였다. 기반 이론으로는 승자 독식 원리의 자기 학습 이론 알고리즘에서 특징 선택을 위한 자기 조직화를 분석하고 이를 문제 해결에 적용하였다. 실제적 영상 데이터를 통한 실험을 통해 배경 영역 분할을 적용한 영상 분할은 효과적으로 수행될 수 있음을 실험 결과로 제시해 보였다.

• 컴퓨터교육학회논문지
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• 제11권2호
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• pp.79-87
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• 2008

자기조절학습은 학습자 스스로가 학습에 참여하여 학습효율을 높일 수 있는 대안으로 제시되고 있다. 본 연구에서는 이러닝 시스템에 자기조절학습을 적용하였으며, 학습자가 능동적으로 학습에 참여함으로서 학습효과를 높이기 위한 방법으로 학습자 스스로가 학습객체를 선택할 수 있도록 하였다. 또한 학습 비즈니스로직은 개발의 효율성과 운용성을 위하여 웹 서비스로 구현하였다. 본 연구의 적용으로서, 비슷한 학습수준을 가지는 학습집단에 대하여 시험된 결과 제안된 방법에 의한 학습이 더 좋은 학습효과를 가져왔다.

• 한국생활과학회지
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• 제18권3호
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• pp.641-656
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• 2009

The purpose of this study was to compare Chinese-Korean adolescents' with Korean adolescents's academic achievement motivation, parental expectation, teacher expectation, self-efficacy. The object is 492 students in the middle school 2th and high school 2th grade who are from Chinese-Korean school and Korean school in Seoul and Incheon. The major results of findings were as follows: First, Chinese-Korean adolescents were more high than academic achievement motivation in Korean adolescents. Second, juniors in middle school were more positive than parental expectation in high school. Third, Chinese-Korean adolescents were more positive than teacher expectation in Korean adolescents, and juniors in middle school are more positive than ones in high school. Forth, Chinese-Korean adolescents were more high than self-efficacy in Korean adolescents.

• 디지털융복합연구
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• 제13권2호
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• pp.361-369
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• 2015

이 연구는 사격선수의 성취목표성향과 자기관리 및 인지된 운동수행이 어떠한 관계를 형성하고 있는지를 구조방정식모형을 통해 실증적으로 검증하는데 목적이 있다. 연구대상은 대한사격연맹에 2014년 등록된 대학 사격선수 112명을 선정하였다. 자료처리는 SPSS 16.0과 AMOS 7.0 프로그램을 활용하였으며, 연구의 목적에 부합하도록 빈도분석, 탐색적요인분석, 확인적요인분석, 상관분석, 구조방정식모형분석을 실시하여 다음과 같은 연구결과를 얻었다. 첫째, 성취목표성향 하위요인인 과제지향성은 자기관리에 정(+)적인 영향을 미치는 것으로 나타났다. 둘째, 성취 목표성향 하위요인인 과제지향성과 자아지향성은 인지된 운동수행에 정(+)적인 영향을 미치는 것으로 나타났다. 셋째, 자기관리는 인지된 운동수행에 정(+)적인 영향을 미치는 것으로 나타났다.

• 산업기술연구
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• 제21권B호
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• pp.91-98
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• 2001

In this paper, center detection and motion analysis of a moving object are studied. Kohonen's self-organizing neural network models are used for the moving objects tracking and time delay neural networks are used for dynamic characteristic analysis. Instead of objects brightness, neuron projections by Kohonen Networks are used. The motion of target objects can be analyzed by using the differential neuron image between the two projections. The differential neuron image which is made by two consecutive neuron projections is used for center detection and moving objects tracking. The two differential neuron images which are made by three consecutive neuron projections are used for the moving trajectory estimation. It is possible to distinguish 8 directions of a moving trajectory with two frames and 16 directions with three frames.

• 한국측량학회지
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• 제35권4호
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• pp.303-312
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• 2017

This paper indirectly created high density point cloud data using unmanned aerial vehicle image. Then, we tried to suggest new concept of classification technique where particular objects from point cloud data can be selectively classified. For this, we established the classification technique that can be used as search factor in classifying color information in point cloud data. Then, using suggested classification technique, we implemented object classification and analyzed classification accuracy by relative comparison with self-created proof resource. As a result, the possibility of point cloud data classification was observable using the image's information. Furthermore, it was possible to classify particular object's point cloud data in high classification accuracy.