• Transactions of the Korean Society of Mechanical Engineers A
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• v.22 no.1
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• pp.132-141
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• 1998

A parallel version of sheet forming analysis program was developed. This version is compatible with any parallel computers which support MPI that is one of the most recent and popular message passing libraries. For this purpose, SERI-SFA, a vector version which runs on Cray Y-MP C90, a sequential vector computer, was used as a source code. For the sake of the effectiveness of the work, the parallelization was focused on the selected part after checking the rank of CPU consumed from the exemplary calculation on Cray Y-MP C90. The subroutines associated with contact algorithm was selected as targe parts. For this work, MPI was used as a message passing library. For the performance verification, an oil pan and an S-rail forming simulation were carried out. The performance check was carried out by the kernel and total CPU time along with theoretical performance using Amdahl's Law. The results showed some performance improvement within the limit of the selective paralellization.

• Journal of the Korean Society for Nondestructive Testing
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• v.13 no.2
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• pp.11-19
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• 1993

It is very essential to get the accurate classification of defects in primary pressure vessel weld for the safety of nuclear power plant. The signal analysis using the digital signal processing and pattern recognition is performed to classify UT defects extracting feature vector from ultrasonic signals. The minimum distance classifier and the maximum likelihood classifier based on statistics were applied in this experiment to discriminate ultrasonics data obtained form both the training specimens (slit, hole) and the testing specimens(crack, slag). The classification rate was measured using pattern classifier. Results of this study show the promise in solving the many flaw classification problems that exist today.

• Journal of the Korean Society for Nondestructive Testing
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• v.25 no.5
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• pp.384-390
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• 2005

In the numerical analysis of En (eddy current testing) using 3-dimensional FEM (finite element method), MVP (magnetic vector potential) and electric scalar potential are used as variables in conductor region. Three dimensional modeling makes number of unknowns increase, and the degree of freedom of variables also makes number of unknowns increase. Because of this reason, modified UP is used to reduce the number of unknowns. Gauge condition is enforced artificially on existing FEM formulations to insure the uniqueness of MVP. So in this paper the effects of these FEM formulation procedures on ECT are investigated and the appropriate FEM formulation is suggested for accurate ECT simulation.

• Journal of The Korean Digital Architecture Interior Association
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• v.12 no.1
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• pp.61-70
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• 2012

A construction project is very costly and takes a long time to make investment and yield profit. For this reason, financial institutions are cautious about financing construction projects. Meanwhile, a construction company needs financing from financial institutions to cover a large expense of a construction project. Thus, there is likely to be a close correlation between financing conditions and business operation of a construction company. To examine the relationship, variables were identified that are related to insolvency of a construction company and changes in financing conditions. The analysis period is between the second quarter of 2001 and the fourth quarter of 2010. Data was retrieved from TS2000 established by Korea Listed Companies Association (KLCA), Statistics Office, and Construction Economy Research Institute of Korea (CERIK). In terms of methodology, VECM (Vector Error Correction Model) was used to analyze dynamic relationship between changes in financing conditions and insolvency of a construction company based on the identified variables. The hypothesis was that changes in financing conditions would significantly affect business of a construction company, but, the analysis did not find a close relation between the two factors. However, it was shown that poor business of a construction company affects financing conditions adversely.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.6
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• pp.487-490
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• 2001

In this paper, we realize a system that moves a cursor with a finger using the circular pattern vector algorithm that in one of the image analysis algorithms. To apply this algorithm, we use central point of the biggest circle among the various circles that recognize the image of the hand , and find out the pointing finger by looking for the distance of the outline of the hand from the central point. The horizontal direction of the cursor on the display is controlled by converting the direction of the pointing finger to the analysis of the plane corrdinate. Because of setting up only one camera of the upper, the middle and the lower discretely. On account of the discrete movement of the cursor of the vertical direction, we move th cursor to the objective, which the user wants. by expanding the local are to the whole area.

• The Journal of the Korea Contents Association
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• v.6 no.9
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• pp.50-59
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• 2006

This paper proposes an automatic video monitoring system and its application to emergency detection by analyzing human behavior using neural network. The object area is identified by subtracting the statistically constructed background image from the input image. The identified object area then is transformed to the feature vector. Neural network has been adapted for analyzing the human behavior using the feature vector, and is designed to classify the behavior in rather simple numerical calculation. The system proposed in this paper is able to classify the three human behavior: stand, faint, and squat. Experiment results shows that the proposed algorithm is very efficient and useful in detecting the emergency situation.

• ETRI Journal
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• v.32 no.5
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• pp.784-794
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• 2010

Automatic facial expression recognition has many potential applications in different areas of human computer interaction. However, they are not yet fully realized due to the lack of an effective facial feature descriptor. In this paper, we present a new appearance-based feature descriptor, the local directional pattern (LDP), to represent facial geometry and analyze its performance in expression recognition. An LDP feature is obtained by computing the edge response values in 8 directions at each pixel and encoding them into an 8 bit binary number using the relative strength of these edge responses. The LDP descriptor, a distribution of LDP codes within an image or image patch, is used to describe each expression image. The effectiveness of dimensionality reduction techniques, such as principal component analysis and AdaBoost, is also analyzed in terms of computational cost saving and classification accuracy. Two well-known machine learning methods, template matching and support vector machine, are used for classification using the Cohn-Kanade and Japanese female facial expression databases. Better classification accuracy shows the superiority of LDP descriptor against other appearance-based feature descriptors.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2511-2520
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• 2018

In this study, Multi-Radial Basis Function Support Vector Machine (Multi-RBF SVM) classifier is introduced based on a composite kernel function. In the proposed multi-RBF support vector machine classifier, the input space is divided into several local subsets considered for extremely nonlinear classification tasks. Each local subset is expressed as nonlinear classification subspace and mapped into feature space by using kernel function. The composite kernel function employs the dual RBF structure. By capturing the nonlinear distribution knowledge of local subsets, the training data is mapped into higher feature space, then Multi-SVM classifier is realized by using the composite kernel function through optimization procedure similar to conventional SVM classifier. The original training data set is partitioned by using some unsupervised learning methods such as clustering methods. In this study, three types of clustering method are considered such as Affinity propagation (AP), Hard C-Mean (HCM) and Iterative Self-Organizing Data Analysis Technique Algorithm (ISODATA). Experimental results on benchmark machine learning datasets show that the proposed method improves the classification performance efficiently.

• The Plant Pathology Journal
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• v.22 no.4
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• pp.386-390
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• 2006

Extensive research of the Potato virus X(PVX) has been performed in in vitro transcription system using the bacteriophage T7 promoter. We constructed an efficient T-DNA based binary vector, pSNU1, and modified vectors carrying PVX replicons. The suitability of the construct to transiently express PVX RNA using Agrobacterium tumefaciens was tested by analysis of infectivity in plants. The expressed PVX RNA was infectous and systemically spread in three plant species including Nicotiana benthamiana, N. tabacum cv. Xanthi-nc, and Capsicum annuum cv. Chilsungcho. The PVX full length construct, pSPVXp31, was caused severe mosaic symptoms on N. benthamiana, severe necrotic lesions on C. annuum while milder symptoms and delayed mosaic symptoms were appeared on the systemic leaves on N. tabaccum. RT-PCR analysis confirmed the presence of PVX RNAs on both inoculated and systemic leaves in all three plant species tested. Our results indicated that PVX replicons were efficiently expressed PVX RNA in at least three tested species. Further investigation win be needed to elucidate the mechanism of PVX replication, translation, movement and assembly/disassembly processes.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.588-593
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• 2007

Fiber reinforced polymer(FRP) composite decks are new to bridge applications and hence not much literature exists on their structural mechanical behavior. As there are many differences between numerical displacements through static analysis of the primary model and experimental displacements through static load tests, system identification (SI)techniques such as Neural Networks (NN) and support vector machines (SVM) utilized in the optimization of the FE model. During the process of identification, displacements were used as input while stiffness as outputs. Through the comparison of numerical displacements after SI and experimental displacements, it can note that NN and SVM would be effective SI methods in modeling an FRP deck. Moreover, two methods such as response surface method and iteration were proposed to optimize the estimated stiffness. Finally, the results were compared through the mean square error (MSE) of the differences between numerical displacements and experimental displacements at 6 points.