• Journal of Photoscience
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• v.4 no.2
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• pp.61-67
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• 1997

The model based on the idea that the p$_y$-orbital of the carbonyl oxygen is responsible to receiving hydrogen was devised for simulation of intramolecular hydrogen transfer. A Monte Carlo method was applied to free rotation of a molecular chain performed by changing the dihedral angles, and a "hit" was defined as the case when the migrating hydrogen comes within the region defined as the p$_y$-orbital and satisfies all the geometrical requirements for abstraction. A set of parameters was employed for defining the region and the requirements; $\tau$ was defined as the angle formed between O...H vector and its projection on the mean plane of the carbonyl group (- 43$\circ$ < $\tau$ < + 43$\circ$), $\Delta$ as the C=O...H angle (90 -15$\circ$ < $\Delta$ < 90 + 15$\circ$), $\theta$ as the O...H - C angle ( 180 - 80$\circ$< 0 < 180 + 80$\circ$), d as the distance from the center of the lobe of the p$_y$-orbital to hydrogen (0 < d < 1.04 ${\AA}$). The minimum value for the distance between carbonyl oxygen (O$_1$) and the migrating hydrogen (H$_i$) and for that between non-bonded atoms except the pair of O$_1$ and H$_i$ were assumed to be 0.52 ${\AA}$ and 1.54 ${\AA}$, respectively. The apphcation of this model to intramolecular $\beta$-, $\gamma$-, $\delta$-, $\epsilon$-, and $\zeta$-hydrogen abstraction in ketones and $\eta$- and $\theta$- proton transfer in oxoesters gave good results reflecting their photochemical behavior. The model was also used for prediction of photoreactivities of 2-(N,N-dibenzylamino)ethyl 2-, 3- and 4-benzoylbenzoate (1a - c). (1a - c).

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.1-10
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• 2001

Neural networks we increasingly being seen as an addition to the statistics toolkit which should be considered alongside both classical and modern statistical methods. Neural networks are usually useful for classification and function estimation. In this paper we concentrate on function estimation using neural networks with weight decay factor The use of weight decay seems both to help the optimization process and to avoid overfitting. In this type of neural networks, the problem to decide the number of hidden nodes, weight decay parameter and iteration number of learning is very important. It is called the optimization of weight decay neural networks. In this paper we propose a automatic optimization based on genetic algorithms. Moreover, we compare the weight decay neural network automatically learned according to automatic optimization with ordinary neural network, projection pursuit regression and support vector machines.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.31 no.4
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• pp.207-213
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• 2018

This paper investigates applicability of Microsoft $Kinect^{(R)}$, RGB-depth camera, to implement a 3D image and spatial information for sensing a target. The relationship between the image of the Kinect camera and the pixel coordinate system is formulated. The calibration of the camera provides the depth and RGB information of the target. The intrinsic parameters are calculated through a checker board experiment and focal length, principal point, and distortion coefficient are obtained. The extrinsic parameters regarding the relationship between the two Kinect cameras consist of rotational matrix and translational vector. The spatial images of 2D projection space are converted to a 3D images, resulting on spatial information on the basis of the depth and RGB information. The measurement is verified through comparison with the length and location of the 2D images of the target structure.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.141-146
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• 2017

In this paper, a gradient magnitude hardware architecture based on hardware folding design method is proposed for low power image feature extraction. For the hardware complexity reduction, the projection vector chracteristic of gradient magnitude is applied. The proposed hardware architecture can be implemented with the small degradation of the gradient magnitude data quality. The FPGA implementation result shows the 41% of logic elements and 62% embedded multiplier savings compared with previous work using Altera Cyclone VI (EP4CE115F29C7N) FPGA and Quartus II v16.0 environment.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2991-3007
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• 2022

Two dimensional locality preserving projections (2D-LPP) is an improved algorithm of 2D image to solve the small sample size (SSS) problems which locality preserving projections (LPP) meets. It's able to find the low dimension manifold mapping that not only preserves local information but also detects manifold embedded in original data spaces. However, 2D-LPP is simple and elegant. So, inspired by the comparison experiments between two dimensional linear discriminant analysis (2D-LDA) and linear discriminant analysis (LDA) which indicated that matrix based methods don't always perform better even when training samples are limited, we surmise 2D-LPP may meet the same limitation as 2D-LDA and propose a novel matrix exponential method to enhance the performance of 2D-LPP. 2D-MELPP is equivalent to employing distance diffusion mapping to transform original images into a new space, and margins between labels are broadened, which is beneficial for solving classification problems. Nonetheless, the computational time complexity of 2D-MELPP is extremely high. In this paper, we replace some of matrix multiplications with multiple multiplications to save the memory cost and provide an efficient way for solving 2D-MELPP. We test it on public databases: random 3D data set, ORL, AR face database and Polyu Palmprint database and compare it with other 2D methods like 2D-LDA, 2D-LPP and 1D methods like LPP and exponential locality preserving projections (ELPP), finding it outperforms than others in recognition accuracy. We also compare different dimensions of projection vector and record the cost time on the ORL, AR face database and Polyu Palmprint database. The experiment results above proves that our advanced algorithm has a better performance on 3 independent public databases.

• The Journal of Engineering Geology
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• v.23 no.1
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• pp.47-55
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• 2013

To analyze lateral displacement of excavation walls exposed during the construction of Subway Line 1 in the Daegu region, inclinometer measurement data for sites D4, D5, and Y6 are investigated from the perspective of engineering geology. The study area, in the Banyawol Formation, Hayang Group, Gyeongsang Supergroup, is in the lower part of bedrock of andesitic volcanics, calcareous shale, sandstone, hornfels, and felsite dykes that are unconformably overlain by soil. The rock mass around the D4 site is classified as RMR-V grade and the maximum lateral displacement of 101.39 mm, toward N34W, was measured at a bedding-parallel fault, at a depth of 12 m. The rock mass around the D5 site is classified as RMR-IV grade and the maximum lateral displacement of 55.17 mm, toward the south, was measured at a lithologic contact between shale and felsite, at a depth of 14 m. The rock mass around the Y6 site is classified as RMR-III grade and the maximum lateral displacement of 12.65 mm, toward S52W, was measured at an unconformity between the soil and underlying bedrocks, at a depth of 7 m. The directions of lateral displacement in the excavation walls are vector sums of the directions perpendicular to the excavation wall and horizontally parallel to the excavation wall. Lateral displacement graphs according to depth in the soil profile show curvilinear trajectories, whereas those in bedrock show straight and rapid-displacement trajectories.

• The Journal of Information Technology
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• v.7 no.2
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• pp.93-104
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• 2004

Sports scene is characterized by large amount of global motion due to pan and zoom of camera motion, and includes many small objects moving independently. Some short period of sports games is thrilling to televiewers, and important to producers. At the same time that kinds of scenes exhibit exceptionally dynamic motions and it is very difficult to analyze the motions with conventional algorithms. In this thesis, several algorithms are proposed for global motion analysis on these dynamic scenes. It is shown that proposed algorithms worked well for motion compensation and panorama synthesis. When cascading the inter frame motions, accumulated errors are unavoidable. In order to minimize these errors, interpolation method of motion vectors is introduced. Affined transform or perspective projection transform is regarded as a square matrix, which can be factorized into small amount of motion vectors. To solve factorization problem, we preposed the adaptation of Newton Raphson method into vector and matrix form, which is also computationally efficient. Combining multi frame motion estimation and the corresponding interpolation in hierarchical manner enhancement algorithm of motion parameters is proposed, which is suitable for motion compensation and panorama synthesis. The proposed algorithms are suitable for special effect rendering for broadcast system, video indexing, tracking in complex scenes, and other fields requiring global motion estimation.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.117-124
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• 2007

This paper describes methodology that enables animators to create the facial expression animations and to control the facial expressions in real-time by reusing motion capture datas. In order to achieve this, we fix a facial expression state expression method to express facial states based on facial motion data. In addition, by distributing facial expressions into intuitive space using LLE algorithm, it is possible to create the animations or to control the expressions in real-time from facial expression space using user interface. In this paper, approximately 2400 facial expression frames are used to generate facial expression space. In addition, by navigating facial expression space projected on the 2-dimensional plane, it is possible to create the animations or to control the expressions of 3-dimensional avatars in real-time by selecting a series of expressions from facial expression space. In order to distribute approximately 2400 facial expression data into intuitional space, there is need to represents the state of each expressions from facial expression frames. In order to achieve this, the distance matrix that presents the distances between pairs of feature points on the faces, is used. In order to distribute this datas, LLE algorithm is used for visualization in 2-dimensional plane. Animators are told to control facial expressions or to create animations when using the user interface of this system. This paper evaluates the results of the experiment.

• Tunnel and Underground Space
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• v.13 no.6
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• pp.486-494
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• 2003

When the orientations of joints are measured on a rock exposure, there are frequent cases that are difficult to approach by the surveyor to the target joints or to set up scanlines on the slope. In this study, to complement such limit and weak points, a new algorithm was developed to interpret joint orientation from analyzing the images of rock slope. As a method of arranging the multiple images of a rock slope, the multistage convergent photographing system was introduced to overcome the limitation of photographing direction which existing method such as parallel stereophotogrammetric system has and to cover the range of image measurement, which is the overlapping area between the image pair, to a maximum extent. To determine camera parameters in the perspective projection equation that are the main elements of the analysis method, a new method was developed introducing three ground control points and single ground guide point. This method could be considered to be very simple compared with other existing methods using a number of ground control points and complicated analysis process. So the global coordinates of a specific point on a rock slope could be analyzed with this new method. The orientation of a joint could be calculated using the normal vector of the joint surface which can be derived from the global coordinates of several points on the joint surface analyzed from the images.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.9
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• pp.361-368
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• 2014

The LPR(License plate recognition) system has been developed to efficient control for complex traffic environment and currently be used in many places. However, because of light, noise, background changes, environmental changes, damaged plate, it only works limited environment, so it is difficult to use in real-time. This paper presents a heuristic segmentation algorithm for robust to noise and illumination changes and introduce a real-time license plate recognition system using it. In first step, We detect the plate utilized Haar-like feature and Adaboost. This method is possible to rapid detection used integral image and cascade structure. Second step, we determine the type of license plate with adaptive histogram equalization, bilateral filtering for denoise and segment accurate character based on adaptive threshold, pixel projection and associated with the prior knowledge. The last step is character recognition that used histogram of oriented gradients (HOG) and multi-layer perceptron(MLP) for number recognition and support vector machine(SVM) for number and Korean character classifier respectively. The experimental results show license plate detection rate of 94.29%, license plate false alarm rate of 2.94%. In character segmentation method, character hit rate is 97.23% and character false alarm rate is 1.37%. And in character recognition, the average character recognition rate is 98.38%. Total average running time in our proposed method is 140ms. It is possible to be real-time system with efficiency and robustness.