• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.6
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• pp.41-50
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• 2003

For copyright protection of digital contents, we employ watermarking techniques to embed watermark signals into digital host data. In this paper we propose an adaptive watermarking algorithm for three-dimensional (3-D) mesh models. Watermark signals are inserted into vertex coordinates adaptively according to changes of their position values. While we embed strong watermarks in the areas of large variations, watermarks are weakly inserted in other areas. After we generate triangle strips by traversing the 3-D model and convert the Cartesian coordinates to the spherical coordinate system, we calculate variations of vertex positions along the traversed strips. Then, we insert watermark signals into the vertex coordinates adaptively according to the calculated variations. We demonstrate that imperceptibility of the inserted watermark is significantly improved and show the bit error rate (BER) for robustness.

• Journal of Internet Computing and Services
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• v.15 no.6
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• pp.117-124
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• 2014

Cluttered background is a major obstacle in developing salient object detection and tracking system for mobile device captured natural scene video frames. In this paper we propose a context aware feature vector selection model to provide an efficient noise filtering by machine learning based classifiers. Since the context awareness for feature selection is achieved by searching nearest neighborhoods, known as NP hard problem, we apply a fast approximation method with complexity analysis in details. Separability enhancement in feature vector space by adding the context aware feature subsets is studied rigorously using principal component analysis (PCA). Overall performance enhancement is quantified by the statistical measures in terms of the various machine learning models including MLP, SVM, Naïve Bayesian, CART. Summary of computational costs and performance enhancement is also presented.

• The Korean Journal of Applied Statistics
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• v.30 no.2
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• pp.215-231
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• 2017

The US presidential primaries take place sequentially in different places with a time lag. However, they have not attracted as much attention in terms of modelling as the US presidential election has. This study applied several autologistic models to find the relation between the outcome of the primary election for a Democrat candidate with socioeconomic attributes in consideration of spatial and temporal dependence. According to the result applied to the 2016 election data at the county level, Hillary Clinton was supported by people in counties with high population rates of old age, Black, female and Hispanic. In addition, spatial dependence was observed, representing that people were likely to support the same candidate who was supported from neighboring counties. Positive auto-correlation was also observed in the time-series of the election outcome. Among several autologistic models of this study, the model specifying the effect of Super Tuesday had the best fit.

• Journal of Korea Multimedia Society
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• v.13 no.5
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• pp.651-662
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• 2010

This paper describes a method to identify objects for autonomous navigation of an outdoor mobile robot. To identify objects, the robot recognizes the object from an image taken by moving robot on outdoor environment. As a beginning, this paper presents the candidates for a segment of region to building of artificial object, sky and trees of natural objects. Then we define their characteristics individually. In the process, we segment the regions of the objects included by preprocessing using multiple features. Multiple features are HSI, line segments, context information, hue co-occurrence matrix, principal components and vanishing point. An analysis of building identifies the geometrical properties of building facet such as wall region, windows and entrance. The building as intersection in vertical and horizontal line segment of vanishing point extracts the mesh. The wall region of building detect by merging the mesh of the neighbor parallelograms that have similar colors. The property estimates the number of story and rooms in the same floors by merging skewed parallelograms of the same color. We accomplish the result of image segmentation using multiple features and the geometrical properties analysis of object through experiments.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.44-51
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• 2007

For real-time recognizing of model objects in remote position a new Neural Networks algorithm is proposed. The proposed neural networks technique is the real time computation methods through the inter-node diffusion. In the networks, a node corresponds to a state in the quantized input space. Each node is composed of a processing unit and fixed weights from its neighbor nodes as well as its input terminal. The most reliable algorithm derived for real time recognition of objects, is a dynamic programming based algorithm based on sequence matching techniques that would process the data as it arrives and could therefore provide continuously updated neighbor information estimates. Through several simulation experiments, real time reconstruction of the nonlinear image information is processed. 1-D LIPN hardware has been composed and various experiments with static and dynamic signals have been implemented.

• Proceedings of the Korean Vacuum Society Conference
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• 2000.02a
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• pp.45-45
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• 2000

PDP, FED, 그리고 VFD와 같은 마이크로 전자디스플레이 장치를 제작하기 위한 가장 중요한 기술중에 하나인 패널 내를 고진공으로 만드는 것과 초기의 진공을 유지하는 것이다. PDP 디스플레이는 전면판과 후면판으로 구성되어 있다. 전면판은 ITO전극, 절연체 그리고 MgO보호막으로 구성되어 있으며, 후면판은 어드레스 전극, 반사층, 격벽, 그리고 형광체층이 있다. 기존의 방식은 대기에서 프릿 글라스를 이용하여 두 장의 유리를 봉입하고, 후면판 모서리 부분에 있는 구멍에 배기 글라스 튜브를 붙이고, 튜브를 통해서 배기하고, 플라즈마 가스를 채우고, 최종적으로 tip-off를 한다. 이러한 기존의 방식을 통해서는 배기 컨덕턴스의 한계로 얻을 수 있는 초기 진공도에 한계가 있다. 아울러 두 장의 유리사이는 150$\mu$m 정도의 간격으로 되어 있고, 이웃한 격벽사이는 320$\mu$m 정도의 미세한 공간이 주어지는 구조가 컨덕턴스를 저하시킨다. 이와 같은 초기 진공도의 한계성을 극복하기 위한 연구로서, PDP 패널을 구성하는 두 장의 글라스를 진공 챔버내에서 IR heater를 이용하여 실장하였다. 대개 PbO, ZnO, SiO2,, 그리고 B？로 구성된 프릿 글라스를 대기에서 전면판에 dispensing하고 가소한다. 그리고 프릿 글라스가 형성된 전면판과 후면판을 loading, align 한 다음, 2 10-7torr까지 펌핑한 후 heating, holding 그리고 cooling 공정을 수행하므로 써 두 장의 유리를 실장하였다. 그러나 온도의 non-uniformity, 프릿 성분에 따라서 crack과 기포문제가 진공 실장과정에서 발생하였다. 이와 같은 문제를 개선하기 위해 프릿 글라스의 새로운 조성과 온도 uniformity를 유지하므로써, 프릿 글라스의 기포와 crack 발생없이 재현성 있게 진공 실장하였다. Leak channel 형성유무를 검증하기 위하여 챔버 자체의 펌핑 속도와 제작된 패널의 펌핑 속도를 비교하므로써, leak channel형성 유무를 평가할 수 있는 방법을 이용하였다. 이와 같은 방법을 이용하여, crack 또는 기포가 있는 패널은 leak channel을 형성하여 패널내의 진공을 유지할 수 없음을 검증하였고, crack 또는 기포가 없는 패널은 leak channel없이 패널내의 진공을 유지할 수 있음을 검증하였다. 결과적으로 진공 인-라인 실장시 가장 중요한 요인인 프릿의 변화를 분석하므로써, 고진공을 요구하는 FPD(PDP, FED, VFD)에 적합하게 적용할 수 있으며, 아울러 실장시 진공도를 개선하므로 패널내부의 오염을 최소화하여 디스필레이로서의 효율을 극대화할 수 있을 것이다.

• Journal of the Korean Geographical Society
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• v.41 no.2 s.113
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• pp.188-194
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• 2006

Three-dimensional topological data is essential for 3D modeling and application such as emergency management and 3D network analysis. This paper reviewed current 3D topological data model and developed a method to construct 3D topological node-relation data structure from 2D computer aided design (CAD) data. The method needed two steps with medial axis-transformation and topological node-relation algorithms. Using a medial-axis transformation algorithm, the first step is to extract skeleton from wall data that was drawn polygon or double line in a CAD data. The second step is to build a topological node-relation structure by converting rooms to nodes and the relations between rooms to links. So, links represent adjacency and connectivity between nodes (rooms). As a result, with the conversion method 3D topological data for micro-level sub-unit of each building can be easily constructed from CAD data that are commonly used to design a building as a blueprint.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8C
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• pp.795-802
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• 2003

It is very important to construct statistical model in order to exactly estimate the signal variance from a noisy image. In order to estimate variance, information of neighboring region is used generally. The size of neighbor region is varied according to the regional characteristics of image. More accurate estimation of edge variance is due to smaller region of neighbor, on the other hands, larger region of neighbor is used to estimate the variance of flat region. By using estimated variance of original image, in general, Wiener filter is constructed, and it is applied to the noisy image. In this paper, we propose a new method for determining the range of neighbors to estimate the variance in wavelet domain. Firstly, a significance map is constructed using the parent-child relationship of wavelet domain. Based on the number of the significant wavelet coefficients, the range of neighbors is determined and then the variance of the original signal is estimated using ML(maximum likelihood method. Experimental results show that the proposed method yields better results than conventional methods for image denoising.

• Journal of the Korean Chemical Society
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• v.24 no.3
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• pp.193-200
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• 1980

The crystal structure of N-acetyl-L-cysteine, $C_5H_9NO_3S,$ has been determined from three dimensional photographic intensity data $(CuK{\alpha}$ radiation) by single crystal X-ray diffraction analysis. There is one formula unit in the triclinic unit cell with a = 7.04(3), b = 5.14(2), c = 8.25(3) ${\AA}$, ${\alpha}$ = 106(2), ${\beta}$ = 51(1), ${\gamma}$ = 124(2)$^{\circ}$ and space group P$_1$, The structure was solved by the direct method and refined by the full matrix least-squares method. The final R value is 12.3% for 629 observed reflections. The C-carboxyl group and the N-acetyl group are very neary planar. The molecule appears to form with neighboring molecules a hydrogen bond, $O-H{\cdot}{\cdot}{\cdot}O(3)$ of length 2.59${\AA}$.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.73-82
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• 2005

This paper proposes a multi-level thresholding method using weighted FCM(Fuzzy C-Means) algorithm in color image. FCM algerian determines a more optimal thresholding value than the existing methods and can extend to multi-level thresholding. But FCM algerian is sensitive to noise because it doesn't include spatial information. To solve the problem, we can remove noise by applying a weight based on entropy that is obtained from neighboring pixels to FCM algerian. And we determine the optimal cluster number by using within-class distance in code image based on the clustered pixels of each color component. In the experiments, we show that the proposed method is more tolerant to noise and is more superior than the existing methods.