• Journal of the Korea Computer Graphics Society
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• v.22 no.3
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• pp.53-61
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• 2016

In this paper, we propose an algorithm for generating lightning paths, which are more realistic than those of random tree based algorithm and faster than a physically based simulation algorithm. Our approach utilizes physically based Dielectric Breakdown Method (DBM) and approximates the electric potential field dramatically to generate the lightning path. We also show a guide path method for the lightning to avoid obstacles in a complex scene. Finally, our method renders fast and realistic lightning by considering physical characteristics for the thickness and brightness of the lightning stream. Our result of the lightning path shares similarity to natural phenomenon by having about 1.56 fractal dimensions, and we can generate the lightning path faster than a previous physically based algorithm. On the other hand, our method is difficult to apply on the real-time games yet, but our approach can be improved by performing the path generation algorithm with GPU in future.

• Korean Journal of Soil Science and Fertilizer
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• v.40 no.3
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• pp.189-195
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• 2007

Using fractal dimensionality theory proposed by Riew and Sposito (1991), we attempted to analyze quantitatively the characteristics of porous distribution for built-in soils in the mini-lysimeter and artificial seed-bed media. The 2" stainless core soil samples were taken from lysimeter soils. Artificial seed-bed media were compacted in the acrylic core filled with raw materials consisted of cocopeat, zeolite and perlite. N (Constant number of partitioned group size smaller media volumes) and r (Self-similarity ratio) parameters consisting of fractal dimension D=log(N)/log(1/r) were obtained by Excel Programme using the Riew and Sposito's fractal model. The pore distribution of tested media was screened in pore size and its occurring frequency. The results reveal that the distribution range of pores is wider in the lysimeter soils than in the seed-bed media, while average size of pores in the media is smaller in lysimeter core soils than in seed-bed media.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9C
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• pp.922-929
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• 2005

In this paper, we propose the MRS p:Ittern classification techniques by the fusion scheme based on the SpPCA and MLP. A conventional PCA teclulique for the dimension reduction has the problem that it can't find a optimal transformation matrix if the property of input data is nonlinear. To overcome this drawback we extract features by the SpPCA technique which use the local patterns rather than whole patterns. In a next classification step, individual classifier based on MLP calculates the similarity of each class for local features. Finally, MRS patterns is classified by the fusion scheme to effectively combine the individual information. As the simulation results to verify the effectiveness, the proposed method showed more improved classification results than conventional methods.

• Journal of KIISE
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• v.44 no.7
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• pp.692-702
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• 2017

Face detection using the LBP based feature descriptor has issues in that it can not represent spatial information between facial shape and facial components such as eyes, nose and mouth. To address these issues, in previous research, a facial image was divided into a number of square sub-regions. However, since the sub-regions are divided into different numbers and sizes, the division criteria of the sub-region suitable for the database used in the experiment is ambiguous, the dimension of the LBP histogram increases in proportion to the number of sub-regions and as the number of sub-regions increases, the sensitivity to facial orientation rotation increases significantly. In this paper, we present a novel facial region segmentation method that can solve in-plane rotation issues associated with LBP based feature descriptors and the number of dimensions of feature descriptors. As a result, the proposed method showed detection accuracy of 99.0278% from a single facial image rotated in orientation.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.3
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• pp.297-303
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• 2009

In this paper, we propose the biomedical spectral pattern classification techniques by the fusion scheme based on the SpPCA and MLP in extended feature space. A conventional PCA technique for the dimension reduction has the problem that it can't find an optimal transformation matrix if the property of input data is nonlinear. To overcome this drawback, we extract features by the SpPCA technique in extended space which use the local patterns rather than whole patterns. In the classification step, individual classifier based on MLP calculates the similarity of each class for local features. Finally, biomedical spectral patterns is classified by the fusion scheme to effectively combine the individual information. As the simulation results to verify the effectiveness, the proposed method showed more improved classification results than conventional methods.

• Nuclear Engineering and Technology
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• v.48 no.5
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• pp.1184-1191
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• 2016

This paper introduces the development of a transient monitoring system to detect the early stage of a transient, to identify the type of the transient scenario, and to inform an operator with the remaining time to turbine trip when there is no operator's relevant control. This study focused on the transients originating from a secondary system in nuclear power plants (NPPs), because the secondary system was recognized to be a more dominant factor to make unplanned turbine-generator trips which can ultimately result in reactor trips. In order to make the proposed methodology practical forward, all the transient scenarios registered in a simulator of a 1,000 MWe pressurized water reactor were archived in the transient pattern database. The transient patterns show plant behavior until turbine-generator trip when there is no operator's intervention. Meanwhile, the operating data periodically captured from a plant computer is compared with an individual transient pattern in the database and a highly matched section among the transient patterns enables isolation of the type of transient and prediction of the expected remaining time to trip. The transient pattern database consists of hundreds of variables, so it is difficult to speedily compare patterns and to draw a conclusion in a timely manner. The transient pattern database and the operating data are, therefore, converted into a smaller dimension using the principal component analysis (PCA). This paper describes the process of constructing the transient pattern database, dealing with principal components, and optimizing similarity measures.

• Journal of Korean Elementary Science Education
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• v.22 no.1
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• pp.109-120
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• 2003

The purpose of this study is to observe, to analyze of the preservice teachers' naive theories about the change of season. And it is to find a instruction strategy which can solve problem about this. The general idea about the change of season is observed by the 3 methods which are simply explaining with words, explaining with pictures and models. The author is to find the similarity. difference and relationship which the preservice teachers have about the general idea about the change of season. The important changable primary factors, which can effect to the general Idea formation, are naturally dragged out through the observation of preservice teachers participation. For this study, 4 first year preservice teachers of one of national university of education are used. Before the interview. the author tries to form rapport with the preservice teachers. Experiment materials, pencil. paper, camcorder, digital recorder and interview note were used for the study with reflection of them just way they are. As the result of the interview. all of 4 preservice teachers had not being understand the concept about the change of season and the three ways of explanation methods were not matched each other, so it is revealed that the general Idea of the change of season, which the preservice teachers have, is not strongly formed. In spite of the repeated study of the change of season from elementary school to university, it has many problem about recognition of the general idea about the change of season which pre-elementary teachers have. Therefore it is needed to improve the experiment in elementary science text book and naive theories by the activity which is explaining the change of season in three dimension space. to prevent the naive theories which the preservice teachers may have.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.2
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• pp.99-105
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• 2017

Generally, stereo matching methods are used to estimate depth information based on color and spatial similarity. However, most depth estimation methods suffer from the occlusion region because occlusion regions cause inaccurate depth information. Moreover, they do not consider the temporal dimension when estimating the disparity. In this paper, we propose a temporal stereo matching method, considering occlusion and disregarding inaccurate temporal depth information. First, we apply a global stereo matching algorithm to estimate the depth information, we segment the image to occlusion and non-occlusion regions. After occlusion detection, we fill the occluded region with a reasonable disparity value that are obtained from neighboring pixels of the current pixel. Then, we apply a temporal disparity estimation method using the reliable information. Experimental results show that our method detects more accurate occlusion regions, compared to a conventional method. The proposed method increases the temporal consistency of estimated disparity maps and outperforms per-frame methods in noisy images.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.229-234
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• 2005

This study was carried out to analyze the effect of wind load on the stability of a 50ton container crane using wind tunnel test and provide a container crane designer with data which can be used in a wind resistance design of a container crane assuming that a wind load at 75m/s wind velocity is applied on a container crane. Data acquisition conditions for this experiment were established in accordance with the similarity. The scale of a container crane dimension, wind velocity and time were chosen as 1/200, 1/13.3 and 1/15. And this experiment was implemented in an Effect type atmospheric boundary-layer wind tunnel with $11.52m^2$ cross-section area. Each directional drag and overturning moment coefficients were investigated and uplift forces at each supporting point due to the wind load were analyzed.