• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.1
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• pp.64-70
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• 2009

This study is to analyze the impact of automotive body with computer simulation. The total deformation, equivalent strain and strain and principal stress are analyzed respectively in case of front, rear and side impacts. The maximum total deformation of side impact is more than 6 times as large as that of rear impact. The maximum equivalent strain or stress of side impact is more than 4 times as large as that of rear impact. These deformation, strain and stress of front impact are a little more than those of rear impact. The maximum principal stress of side impact is more than 4.5 times as large as that of rear impact. This stress of front impact is a little more than that of rear impact.

• Journal of KIEE
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• v.11 no.1
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• pp.1-7
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• 2001

Various methods for blind source separation (BSS) are based on independent component analysis (ICA) which can be viewed as a nonlinear extension of principal component analysis (PCA). Most existing ICA methods require certain nonlinear functions (which leads to higher-order statistics) depending on the probability distributions of sources, whereas PCA is a linear learning method based on second-order statistics. In this paper we show that the PCA can be applied to the task of BBS, provided that source are spatially uncorrelated but temporally correlated. Since the resulting method is based on only second-order statistics, it avoids the nonlinear function and is able to separate mixtures of several colored Gaussian sources, in contrast to the conventional ICA methods.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.483-494
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• 2012

Many recent events, such as terrorist attacks, exposed defects in most sophisticated security systems. Therefore, it is necessary to improve security data systems based on the body or behavioral characteristics, often called biometrics. Together with the growing interest in the development of human and computer interface and biometric identification, human face recognition has become an active research area. Face recognition appears to offer several advantages over other biometric methods. Nowadays, Principal Component Analysis (PCA) has been widely adopted for the face recognition algorithm. Yet still, PCA has limitations such as poor discriminatory power and large computational load. This paper proposes a novel algorithm for face recognition using a mid band frequency component of partial information which is used for PCA representation. Because the human face has even symmetry, half of a face is sufficient for face recognition. This partial information saves storage and computation time. In comparison with the traditional use of PCA, the proposed method gives better recognition accuracy and discriminatory power. Furthermore, the proposed method reduces the computational load and storage significantly.

• Bulletin of the Society of Naval Architects of Korea
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• v.24 no.2
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• pp.20-28
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• 1987

In general, preliminary hull form design is performed by changing a parent hull form using a computer to satisfy given requirements, e.g., principal dimensions, displacement, $L_{CB}$, and etc. Principal dimensions, $C_b,\;L_{CB}$ and midship sections are the only parameters to be modified in the traditional hull form variation methods available for preliminary design. In this paper, a method is presented in which local cross sections as well as principal dimensions and midship sections are modified according to design requirements. The method gives hydrostatic curves of modified hull form simultaneously. An optimization technique to satisfy the constraints of hydrostatic characteristics such as maximizing KM as a design requirement is also considered.

• Journal of Broadcast Engineering
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• v.21 no.1
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• pp.60-65
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• 2016

This paper introduces the non-local means (NLM) algorithm for image denoising, and also introduces an improved algorithm which is based on the principal component analysis (PCA). To do the PCA, a covariance matrix of a given image should be evaluated first. If we let the size of neighborhood patches of the NLM S × S², and let the number of pixels Q, a matrix multiplication of the size S² × Q is required to compute a covariance matrix. According to the characteristic of images, such computation is inefficient. Therefore, this paper proposes an efficient method to compute the covariance matrix by sampling the pixels. After sampling, the covariance matrix can be computed with matrices of the size S² × floor (Width/l) × (Height/l).

• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.11-18
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• 2009

This paper proposes the way of improving learning speed in Levenberg-Marquardt algorithm using the principal submatrix of Jacobian matrix. The Levenberg-Marquardt learning uses Jacobian matrix for Hessian matrix to get the second derivative of an error function. To make the Jacobian matrix an invertible matrix. the Levenberg-Marquardt learning must increase or decrease ${\mu}$ and recalculate the inverse matrix of the Jacobian matrix due to these changes of ${\mu}$. Therefore, to have the proper ${\mu}$, we create the principal submatrix of Jacobian matrix and set the ${\mu}$ as the eigenvalues sum of the principal submatrix. which can make learning speed improve without calculating an additional inverse matrix. We also showed that our method was able to improve learning speed in both a generalized XOR problem and a handwritten digit recognition problem.

• Elastomers and Composites
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• v.38 no.4
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• pp.354-362
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• 2003

The use of a petaloid design for the bottom of carbonated poly(ethylene terephthalate)(PET) bottles is widely spread. This study investigated the causes of bottom cracks. The tensile yield stress variations of PET according to the crystallinity and stretch ratio were examined, then the stretch ratio and strength in the bottom area of a blown bottle were analyzed. A crack test was also performed to observe the cracking phenomena. The distribution of the effective stress and maximum principal stress were both examined using computer simulation to seek the influence of the bottom design on crack. It was concluded that the bottom cracks occurred because of inadequate material strength due to the insufficient stretching of PET, plus the coarse design of a petaloid bottom. The stretch ratio at the bottom during bottle blowing should be higher than the strain hardening point of PET to produce enhanced mechanical strength. The cracks in the bottom of the PET bottles occurred through crazing below the yield stress. The maximum principal stress was higher in the valleys of the petaloid bottom than in the rest bottom area, and the maximum principal stress had a strong effect on the cracks.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.121-130
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• 2012

This paper proposes an intuitive real-time robot control system using human body movement. Recently, it has been developed that motion generation for humanoid robots with reflecting human body movement, which is measured by a motion capture. However, in the existing studies about robot control system by human body movement, the detailed structure information of a robot, for example, degrees of freedom, the range of motion and forms, must be examined in order to calculate inverse kinematics. In this study, we have proposed Associative Motion Generation as humanoid robot motion generation method which does not need the detailed structure information. The associative motion generation system is composed of two neural networks: nonlinear principal component analysis and Jordan recurrent neural network, and the associative motion is generated with the following three steps. First, the system learns the correspondence relationship between an indication and a motion using training data. Second, associative values are extracted for associating a new motion from an unfamiliar indication using nonlinear principal component analysis. Last, the robot generates a new motion through calculation by Jordan recurrent neural network using the associative values. In this paper, we propose a real-time humanoid robot control system based on Associative Motion Generation, that enables user to control motion intuitively by human body movement. Through the task processing and subjective evaluation experiments, we confirmed the effective usability and affective evaluations of the proposed system.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.07a
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• pp.235-235
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• 2004

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3701-3720
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• 2015

A system for the recognition of machine printed Arabic script is proposed. The Arabic script is shared by three languages i.e., Arabic, Urdu and Farsi. The three languages have a descent amount of vocabulary in common, thus compounding the problems for identification. Therefore, in an ideal scenario not only the script has to be differentiated from other scripts but also the language of the script has to be recognized. The recognition process involves the segregation of Arabic scripted documents from Latin, Han and other scripted documents using horizontal and vertical projection profiles, and the identification of the language. Identification mainly involves extracting connected components, which are subjected to Principle Component Analysis (PCA) transformation for extracting uncorrelated features. Later the traditional K-Nearest Neighbours (KNN) algorithm is used for recognition. Experiments were carried out by varying the number of principal components and connected components to be extracted per document to find a combination of both that would give the optimal accuracy. An accuracy of 100% is achieved for connected components >=18 and Principal components equals to 15. This proposed system would play a vital role in automatic archiving of multilingual documents and the selection of the appropriate Arabic script in multi lingual Optical Character Recognition (OCR) systems.