• Journal of the Korean Chemical Society
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• v.23 no.4
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• pp.198-205
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• 1979

A valence bond method of calculation of the dipole moments for octahedral $(M(III)0_3S_3)$ type complexes are developed, using $d^2sp^3 $hybrid orbitals of the central metal ions and the single basis set orbital of ligands. (M (III) =V (III), Cr (III), Mn (III), Fe (III), Co (III), Ru (III), Rh (III) and OS (III)). In this method the mixing coefficient of the valence basis sets for the central metal ion with the appropriate ligand orbitals is not required to be the same, differently from the molecular orbital method. The valence bond method is much more easier to calculate the dipole moments for octahedral complexes than the approximate molecular orbital method and the calculated results are also in the range of the experimental vaues.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.6
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• pp.2470-2476
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• 2011

Inherent strain method, a hybrid method of experimental and numerical, is known to be very efficient in predicting the plate deformation due to line heating. For the simulation of deformation using inherent strain method, it is important to determine the magnitude and the region of inherent strain properly. Because the phase of steel transforms differently depending on the actual speed of cooling following line heating, it should be also considered in determining the inherent strain. A heat transfer analysis method including the effects of impinging water jet, film boiling, and radiation is proposed to simulate the water cooling process widely used in shipyards. From the above simulation it is possible to obtain the actual speed of cooling and volume percentage of each phase in the inherent strain region of a line heated steel plate. Based on the material properties calculated from the volume percentage of each phase, it should be possible to predict the plate deformations due to line heating with better precision.

• Proceedings of the Korea Contents Association Conference
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• 2003.05a
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• pp.416-420
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• 2003

In this paper, we implemented a dual-resolution image database system for the fast naked-eye retrieval using interpolation. This system can solve two conventional problems : a blocking noise at zoom-out image in single high resolution method and a big storage to store in simple dual-resolution image database system. The proposed method makes a subsampled image by subsampling a original image, and then a interpolated image of it using interpolation. After that, a hybrid dual-resolution image database is composed based on the differential image between the interpolated image and the original image. Experimental results of simulating through 60 sample images shows that the proposed method is 0.011 second faster than simple high-resolution method in the retrieval time - one is 0.003 second, the other is 0.014 second, respectively. Also, that improves 14.7% more than simple dual-resolution method in the stored size - one is 19,821 byte, the other is 16,910 byte, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.11
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• pp.294-301
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• 2016

Recently, the solar tracker has been used to improve the efficiency of solar energy. Solar tracking technologies are classified into the sensor-based method, the program-based method, and the hybrid method. Solar trackers using an AC motor and CdS sensor are low in cost, but the precision of the positions is low, owing to the inertia of the motor and the scattering of sunlight. To compensate for the low precision, we implement a CdS sensor module and propose an AC motor control method using error value. To evaluate the performance of the solar tracker, we implemented a solar water heater. From the experimental results, the solar tracker can achieve ${\pm}2mm$ accuracy for sun, can satisfy ${\pm}15mm$ as a limited error value, and provides a 32% performance enhancement in KSB8202 criteria.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.581-587
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• 2005

This paper presents a hybrid face recognition method of both the first moment of image and the independent component analysis(ICA) of fixed point(FP) algorithm based on Newton method. First moment is a method for finding centroid of image, which is applied to exclude the needless backgrounds in the face recognitions by shifting to the centroid of face image. FP-ICA is also applied to find a set of independent basis images for the faces, which is a set of statistically independent facial features. The proposed method has been applied to the problem for recognizing the 48 face images(12 persons o 4 scenes) of 64*64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate) than conventional FP-ICA without preprocessing. The city-block has been relatively achieved more an accurate similarity than Euclidean or negative angle.

• Journal of Digital Convergence
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• v.10 no.6
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• pp.297-302
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• 2012

In this paper, we present a object detection and tracking method based on image context analysis. It is robust from the image variations such as complicated background, dynamic movement of the object. Image context analysis is carried out using the hybrid network of k-means and RBF. The proposed object detection employs context-driven adaptive Bayesian framework to relive the effect due to uneven object images. The proposed method used feature vector generator using 2D Haar wavelet transform and the Bayesian discriminant method in order to enhance the speed of learning. The system took less time to learn, and learning in a wide variety of data showed consistent results. After we developed the proposed method was applied to real-world environment. As a result, in the case of the object to detect pass outside expected area or other changes in the uncertain reaction showed that stable. The experimental results show that the proposed approach can achieve superior performance using various data sets to previously methods.

• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.715-720
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• 2005

This paper presents a hybrid recognition method of first moment of face image and principal component analysis(PCA). First moment is applied to reduce the dimension by shifting to the centroid of image, which is to exclude the needless backgrounds in the face recognitions. PCA is implemented by single layer neural network which has a teaming rule of Foldiak algorithm. It has been used as an alternative method for numerical PCA. PCA is to derive an orthonormal basis which directly leads to dimensionality reduction and possibly to feature extraction of face image. The proposed method has been applied to the problems for recognizing the 48 face images(12 Persons $\ast$ 4 scenes) of 64$\ast$64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate). The negative angle has been relatively achieved more an accurate similarity than city-block or Euclidean.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.11
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• pp.957-964
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• 2016

This paper presents numerical investigation on behaviors of the rear cover in the vertical launcher under rocket plume loading by using fluid-structure interaction analysis. The rocket plume loading is modeled by the fully Eulerian method and elasto-plastic behavior of the rear cover is predicted by the total Lagrangian method based on a 9-node planar element. The interface motion and boundary conditions are described by a hybrid particle level-set method within the ghost fluid framework. The present results will be compared with the experimental data in the future.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.6
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• pp.44-51
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• 1999

The HMM-Net is a neural network architecture that implements the computation of output probabilities of a hidden Markov model (HMM). The architecture is developed for the purpose of combining the discriminant power of neural networks with the time-domain modeling capability of HMMs. Criteria of maximum likehood(ML) and minimization of mean squared error(MMSE) are used for learning HMM-Net classifiers. The criterion MMSE is better than ML when initial learning condition is well established. However Ml is more useful one when the condition is incomplete[3]. Therefore we propose an efficient learning method of HMM-Net classifiers using a hybrid criterion(ML/MMSE). In the method, we begin a learning with ML in order to get a stable start-point. After then, we continue the learning with MMSE to search an optimal or near-optimal solution. Experimental results for the isolated numeric digits from /0/ to /9/, a training and testing time-series pattern set, show that the performance of the proposed method is better than the others in the respects of learning and recognition rates.

• Journal of KIISE:Software and Applications
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• v.28 no.11
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• pp.795-813
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• 2001

Sophisticated geometric structure analysis must be preceded to create electronic document from logical components extracted from document image. this paper presents a knowledge-based method for sophisticated geometric structure analysis of technical journal pages. The proposed knowledge base encodes geometric characteristics that are not only common in technical journals but also publication-specific in the form rules. The method takes the hybrid of top-down and bottom-up techniques and consists of two phases: region segmentation and identification. Generally, the result of segmentation process does not have a one-to-one matching with composite layout components. Therefore, the proposed method identifies non-text objects such as image, drawing and table, as well as text objects such as text line and equation by splitting or grouping segmented regions into composite layout components. Experimental results with 372 images scanned from the IEEE Transactions on Pattern Analysis and Machine Intelligence show that the proposed method has performed geometrical structure analysis successfully on more than 99% of the test images, resulting in sophisticated performance compared with previous works.