• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.5
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• pp.161-172
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• 2018

This paper proposed the robot vision control method to track a moving rigid body target using the vision system model that can actively control camera parameters even if the relative position between the camera and the robot and the focal length and posture of the camera change. The proposed robotic vision control scheme uses a batch method that uses all the vision data acquired from each moving point of the robot. To process all acquired data, this robot vision control scheme is divided into two cases. One is to give an equal weight for all acquired data, the other is to give weighting for the recent data acquired near the target. Finally, using the two proposed robot vision control schemes, experiments were performed to estimate the positions of a moving rigid body target whose spatial positions are unknown but only the vision data values are known. The efficiency of each control scheme is evaluated by comparing the accuracy through the experimental results of each control scheme.

• Journal of the Korea institute for structural maintenance and inspection
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• v.12 no.5
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• pp.179-189
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• 2008

The object of this study is to develope a program with proposed numerical techniques for an optimal seismic control of structures using active tendon systems. Ricatti closed-loop algorithm has been applied to control the active tendon systems with time-delay problem. The optimal control is formulated as an optimization problem which is finding optimal weighting matrices by minimizing the quadratic performance index by SUMT. In order to find the optimal location of active tendons in structures, controllability index has been introduced. From numerical examples, the current optimal control technique with optimal location of tendons was suitable to control the seismic response of structures.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.3
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• pp.27-36
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• 2004

Detection and recognition of human faces in images can be considered as an important aspect for applications that involve interaction between human and computer. In this paper, we propose a face recognition method using eigenfaces and fuzzy neural networks. The Principal Components Analysis (PCA) is one of the most successful technique that have been used to recognize faces in images. In this technique the eigenvectors (eigenfaces) and eigenvalues of an image is extracted from a covariance matrix which is constructed form image database. Face recognition is Performed by projecting an unknown image into the subspace spanned by the eigenfaces and by comparing its position in the face space with the positions of known indivisuals. Based on this technique, we propose a new algorithm for face recognition consisting of 5 steps including preprocessing, eigenfaces generation, design of fuzzy membership function, training of neural network, and recognition. First, each face image in the face database is preprocessed and eigenfaces are created. Fuzzy membership degrees are assigned to 135 eigenface weights, and these membership degrees are then inputted to a neural network to be trained. After training, the output value of the neural network is intupreted as the degree of face closeness to each face in the training database.

• Journal of KIISE:Software and Applications
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• v.33 no.12
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• pp.1090-1102
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• 2006

This paper suggests a new algorithm for detecting the plagiarism among a set of source codes, constrained to be functionally equivalent, such are submitted for a programming assignment or for a programming contest problem. The typical algorithms largely exploited up to now are based on Greedy-String Tiling, which seeks for a perfect match of substrings, and analysis of similarity between strings based on the local alignment of the two strings. This paper introduces a new method for detecting the similar interval of the given programs based on an adaptive similarity matrix, each entry of which is the logarithm of the probabilities of the keywords based on the frequencies of them in the given set of programs. We experimented this method using a set of programs submitted for more than 10 real programming contests. According to the experimental results, we can find several advantages of this method compared to the previous one which uses fixed similarity matrix(+1 for match, -1 for mismatch, -2 for gap) and also can find that the adaptive similarity matrix can be used for detecting various plagiarism cases.

• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.549-558
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• 2007

Collaborative filtering systems have problems when users rate items and the rated results depend on their feelings, as there is a possibility that the results include noise. The method proposed in this paper optimizes the matrix by excluding irrelevant ratings as information for recommendations from a user-item matrix using dispersion. It reduces the noise that results from predicting preferences based on original user ratings by inflecting the information for items and users on the matrix. The method excludes the ratings values of the utmost limits using a percentile to supply the defects of coefficient of variance and composes a weighted user-item matrix by combining the user coefficient of variance with the median of ratings for items. Finally, the preferences of the active user are predicted based on the weighted matrix. A large database of user ratings for movies from the MovieLens recommender system is used, and the performance is evaluated. The proposed method is shown to outperform earlier methods significantly.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.162-170
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• 2015

Commute time embedding involves computing the spectral decomposition of the graph Laplacian. It requires the computational burden proportional to $o(n^3)$, not suitable for large scale dataset. Many methods have been proposed to accelerate the computational time, which usually employ the Nystr${\ddot{o}}$m methods to approximate the spectral decomposition of the reduced graph Laplacian. They suffer from the lost of information by dint of sampling process. This paper proposes to reduce the errors by approximating the spectral decomposition of the graph Laplacian using that of the affinity matrix. However, this can not be applied as the data size increases, because it also requires spectral decomposition. Another method called approximate commute time embedding is implemented, which does not require spectral decomposition. The performance of the proposed algorithms is analyzed by computing the commute time on the patch graph.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.253-256
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• 1997

This paper proposes a control strategy of position and force control in the same direction based on hybrid position/force control. In order to control position and force in the same direction, a weighting matrix is introduced instead of a selection matrix suggested by Raibert and Craig. The major part of the controller output comes from the position controller when a position control error is large, from the force controller when a position control error is large. The proposed algorithm is implemented by the simulation and experiment focusing on the peg-in-hole task where friction exist significantly and is not constant. It also adopts and event control scheme for more efficient performance.

• Journal of the Korean Society for Precision Engineering
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• v.25 no.2
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• pp.72-79
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• 2008

In the redundant actuation system which has more actuators than a system's mobility, there are various method to determine actuated torques because those are not determined uniquely. This paper presents a torque distribution method using weighted-pseudoinverse to optimize the maximum torque of various actuated inputs of the redundant system. The various weighting factor of weighted-pseudoinverse is studied to reduce maximum actuated torque. This method is experimentally applied to 3RRR parallel robot, which shows that presented method can efficiently reduce the maximum actuated torque.

• Proceedings of the KIEE Conference
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• 2000.11d
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• pp.758-760
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• 2000

본 논문에서는 기구적으로 여유자유도를 갖는 로봇 매니퓰레이터 시스템을 대상으로 하여, 로봇 랜드가 주어진 제적을 추종할 수 있는 관절 토크를 유도하기 위한 동적제어 식을 새로이 구성하고, 동적제어식을 만족하는 관절 토크 해들 중에 국소적으로 토크의 크기를 최적화하는 해를 사용하는 최적토크제어를 제안한다. 최적토크를 구하는 문제에 있어 관절 토크에 가중치 행렬을 적용하여 각 관절 토크의 최대 크기의 비를 반영할 수 있도록 한다. 또한, 로봇 핸드 자코비안-관성 역행렬의 영공간에서 나타나는 영공간 관절 속도를 정의하고 이러한 영공간 관절속도가 최적토크제어에서는 로봇 시스템을 불안정하게 할 수 있다는 것을 보인다. 최적토크 제어의 이러한 문제를 해결하기 위하여 영공간 관절 속도를 제거하기 위한 소산토크를 유도하고, 최적토크제어식에 소산토크를 추가하는 방법을 제안한다. 평면형 3-자유도 로봇을 대상으로 한 모의실험을 통해 제안된 제어 방법의 우수성을 검증하고 그 결과를 분석한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.1827-1830
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• 2002

단백질 모티프(motif)란 유사한 기능을 가진 여러 단백질 서열에서 공통적으로 발견되는 패턴으로서 단백질의 기능을 예측하는 단서로 활용된다. 현재 Prosite, Pfam 등의 데이터베이스에서 정규식(regular expression), 가중치 행렬(weighted matrix), 은닉 마코프 모델(hidden Markov model)의 형태로 4천여종 이상의 모티프가 등록되어 있다. 본 논문에서는 연관성 탐사 기법을 적용하여 Hits 데이터로부터 상당히 높은 연관성을 갖는 모티프 집단을 밝히고, 실제 자연현상에서 자주 나타나는 연관성을 교차타당성 (cross-validation) 기법을 통해 입증하였다. 이렇게 밝혀진 단백질 모티프간 연관성을 트라이 탐색 기법을 통해 웹으로 제공함으로써 단백질의 기능유추에 쉽게 접근하고자 한다.