• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.5
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• pp.66-72
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• 1997

In this paper, we propose a method improving the accuracy of th eregistration coefficients calculated form two range images considering the measurement error. The employed range finder is based on triangulation and the depth measurement error is described with an error covariance matrix, which is based on thesensitivity of the range measurements. Experimental results demonstrate that the registration coefficients obtained with the proposed method are better than the results when the measurment errors are neglected.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.6 no.2
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• pp.28-33
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• 1988

The objective of this work is to study the sue of precise triangulation nets by matrix analysis in adjusting coordinates. Results of this work show that matrix analysis has many advantages, namely in terms of accuracy and efficiency. In addition to this, comparison of adjusted vlues by two different methods, a Rigorous Method and an Approximate Method, show that differences in adjusted coordinates are 1-2 mm within the mean square error. This proves that the Approximate Method has sufficient accuracy in the practical application.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.6
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• pp.608-613
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• 2006

Any input acceleration that bends RLG dithering axis causes flexure error, which is a source of the noncommutative error that can not be compensated by simply using integrated gyro sensor output. This paper introduces noncommutative error equations that define attitude errors caused by flexure errors. In this paper, flexure error is classified as sensor level error if the sensing axis coincides with the dithering axis and as system level error if the two axes do not coincide. The relationship between gyro output and the rotation vector is introduced and is used to define the coordinate transformation matrix and angular motion. Equations are derived for both sensor level and system level flexure error analysis. These equations show that RLG based INS attitude error caused by flexure is directly proportional to time, amount of input acceleration and the dynamic frequency of the vehicle.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.2
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• pp.99-112
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• 2013

This paper presents a subspace system identification for estimating the stiffness matrix and flexural rigidities of a shear building. System matrices are estimated by LQ decomposition and singular value decomposition from an input-output Hankel matrix. The estimated system matrices are converted into a real coordinate through similarity transformation, and the stiffness matrix is estimated from the system matrices. The accuracy and the stability of an estimated stiffness matrix depend on the size of the associated Hankel matrix. The estimation error curve of the stiffness matrix is obtained with respect to the size of a Hankel matrix using a prior finite element model of a shear building. The sizes of the Hankel matrix, which are consistent with a target accuracy level, are chosen through this curve. Among these candidate sizes of the Hankel matrix, more proper one can be determined considering the computational cost of subspace identification. The stiffness matrix and flexural rigidities are estimated using the Hankel matrix with the candidate sizes. The validity of the proposed method is demonstrated through the numerical example of a five-story shear building model with and without damage.

• The Journal of Korea Robotics Society
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• v.12 no.1
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• pp.42-54
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• 2017

Using an inverse of the geometric Jacobian matrix is one of the most popular ways to control robot manipulators, because the Jacobian matrix contains the relationship between joint space velocities and operational space velocities. However, the control algorithm based on Jacobian matrix has algorithmic singularities: The robot manipulator becomes unstable when the Jacobian matrix loses rank. To solve this problem, various methods such as damped and filtered inverse have been proposed, but comparative studies to evaluate the performance of these algorithms are insufficient. Thus, this paper deals with a comparative analysis of six representative singularity avoidance algorithms: Damped Pseudo Inverse, Error Damped Pseudo Inverse, Scaled Jacobian Transpose, Selectively Damped Inverse, Filtered Inverse, and Task Transition Method. Especially, these algorithms are verified through computer simulations with a virtual model of a humanoid robot, THORMANG, in order to evaluate tracking error, computational time, and multiple task performance. With the experimental results, this paper contains a deep discussion about the effectiveness and limitations of each algorithm.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1359-1371
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• 2020

In transmitting and receiving such a large amount of data, reliable data communication is crucial for normal operation of a device and to prevent abnormal operations caused by errors. Therefore, in this paper, it is assumed that an error correction code (ECC) that can detect and correct errors by itself is used in an environment where massive data is sequentially received. Because an embedded system has limited resources, such as a low-performance processor or a small memory, it requires efficient operation of applications. In this paper, we propose using an accelerated ECC-decoding technique with a graphics processing unit (GPU) built into the embedded system when receiving a large amount of data. In the matrix-vector multiplication that forms the Hamming code used as a function of the ECC operation, the matrix is expressed in compressed sparse row (CSR) format, and a sparse matrix-vector product is used. The multiplication operation is performed in the kernel of the GPU, and we also accelerate the Hamming code computation so that the ECC operation can be performed in parallel. The proposed technique is implemented with CUDA on a GPU-embedded target board, NVIDIA Jetson TX2, and compared with execution time of the CPU.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.8
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• pp.89-96
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• 2015

Human visual system has chromatic adaptation to determine the color of an object regardless of illumination, whereas digital camera records illumination and reflectance together, giving the color appearance of the scene varied under different illumination. NMFsc(nonnegative matrix factorization with sparseness constraint) was recently introduced to estimate original object color by using sparseness constraint. In NMFsc, low sparseness constraint is used to estimate illumination and high sparseness constraint is used to estimate reflectance. However, NMFsc has an illumination estimation error for images with large uniform area, which is considered as dominant chromaticity. To overcome the defects of NMFsc, illumination estimation via nonnegative matrix factorization with dominant chromaticity image is proposed. First, image is converted to chromaticity color space and analyzed by chromaticity histogram. Chromaticity histogram segments the original image into similar chromaticity images. A segmented region with the lowest standard deviation is determined as dominant chromaticity region. Next, dominant chromaticity is removed in the original image. Then, illumination estimation using nonnegative matrix factorization is performed on the image without dominant chromaticity. To evaluate the proposed method, experimental results are analyzed by average angular error in the real world dataset and it has shown that the proposed method with 5.5 average angular error achieve better illuminant estimation over the previous method with 5.7 average angular error.

• Science of Emotion and Sensibility
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• v.17 no.2
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• pp.91-100
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• 2014

This study was to examine how visual angle of matrix corresponding to the physical properties of P300 speller and eye gaze corresponding to the user's personal characteristics influence on the accuracy of P300. Visual angle of the matrix was operated as the distance between the user and the matrix and three groups were composed: 60 cm group, 100 cm groups, and 150 cm group. Eye gaze methods was consisted three conditions. Head moving condition was putting eye gaze using head, pupil moving condition was moving pupil with the head fixed, while the eye fixed condition is to fix the eye gaze at the center of the matrix. The results showed that there was significant difference in the accuracy of P300 speller according to the eye gaze method. The accuracy of the head moving condition was higher than the accuracy of pupil moving conditions, accuracy of pupil moving conditions was higher than the accuracy of the eye fixed conditions. However, the effect of visual angle of matrix and interaction effect were not significant. When P300 amplitude of target character was measured depending on how you stare at the target character, P300 amplitude of the head moving condition was greater than P300 amplitude of the pupil moving condition. There was no significant difference in the error distribution in head moving condition and pupil moving condition, while there was a significant difference between two eye gaze conditions and fixed gaze condition. The error was located at the neighboring characters of the target character in head moving condition and pupil moving condition, while the error was relatively distributed widely in fixed eye condition, error was occurred with high rate in characters far away from the center of matrix.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.70-75
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• 1993

The performance of the BEWE(Bearing Estimation Without Eigendecomposition) algorithm depends on the sensor outputs which are selected to construct the projection matrix. In this paper, we construct the covariance matrix of the bearing estimates for two targets and propose the criterion to select the sensor outputs which minimize the covariance matrix. The computer simulation conforms that the estimation error is smallest when the sensor outputs are selected based on the proposed criterion.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.559-564
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• 1993

Nonlinear equation of motion of the flexible manipulator are derived by the Lagrangian method in symbolic form to better understand the structure of the dynamic model. The resulting equations of motion have a structure which is useful to reduce the number of terms calculated, to check correctness, or to extend the model to high order. A manipulator with a flexible 4 bar link mechanism is a constrained system whose equations are sensitive to numerical integration error. This constrained system is solved using the null space matrix of the constraint Jacobian matrix. Singular value decomposition is a stable algorithm to find the null space matrix.