• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2008.11a
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• pp.150-150
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• 2008

본 연구에서는 Wet chemistry damage가 Nanopatterned p-ohmic electrode에 미치는 영향을 연구하였다. Nanopattern은 Metal clustering을 이용하여, P-GaN와 Ohmic형성에 유리한 Pd을 50$\AA$ 적층한 후 Rapid Thermal Annealing방법으로 $850^{\circ}C$, $N_2$분위기에서 3min열처리를 하여 Pd Clustering mask 를 제작하였다. Wet etching은 $85^{\circ}C$, $H_3PO_4$조건에서 시간에 따라 Sample을 Dipping하는 방법으로 시행하였다 Ohmic test를 위해서 Circular - Transmission line Model 방법을 이용하였으며, Atomic Force Microscopy과 Parameter Analyzer로 Nanopatterned GaN surface위에 형성된 Ni/ Au Contact에서의 전기적 분석과, 표면구조분석을 시행하였다. AFM결과 Wet처리시간에 따라서 Etching형상 및 Etch rate이 영향을 받는 것이 확인되었고, Ohmic test에서 Wet chemistry처리에 의한 Tunneling parameter와 Schottky Barrier Height가 크게 증/감함을 관찰하였다. 이러한 결과들은 Wet처리에 의해서 발생된 Defect가 GaN의 표면과 하부에서 발생되며, Deep acceptor trap 및 transfer거동과 밀접한 관련이 있음을 확인 할 수 있었다. 보다 자세한 Transport 및 Wet chemical처리영향에 관한 형성 Mechanism은 후에 I-V-T, I-V, C-V, AFM결과 들을 활용하여 발표할 예정이다.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.4
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• pp.469-474
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• 2011

This paper presents the intelligent tracking method for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. K-means clustering and TS fuzzy system are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by K-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. While calculating expected value, the non-linearity of the maneuvering target is recognized as linear one by dividing acceleration and the capability of Kalman filter is kept in the filtering process. The error for the non-linearity is compensated by approximated acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.24 no.2
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• pp.71-84
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• 2021

Restoration of DMZ has come up with the discussion on the peaceful use of the DMZ and the conservation plan of the army. In this study, we aim to identify soil characteristics of 108 sites to figure out environmental conditions around the iron fence of DMZ where vegetation has been removed repeatedly. Based on the soil characteristics and climate variables, hierarchy clustering was performed to categorize sites. As a result, we categorized 108 sites into 4 types: middle elevation region, lowland, East coast lowland, other areas. Group of 'other area' is only high in nutrient and clay proportion. Others are in igneous rock and metamorphic rocks with a high proportion of sand and lower nutrients than the optimum range of growth in Korean forest soil. The middle elevation region has a high altitude, low temperature. The east coast lowland has a high temperature in January and low precipitation. The lowland has a low altitude and high temperature. This category provides the environmental condition around the DMZ fence and can be used to select plants for restoration. The restoration project around the DMZ iron fence should satisfy the security of military plans, which means that functional restoration is prior to ecological restoration such as vegetation management under a power line. Additionally, improvement of soil quality and surface stability through restoration projects is required to enhance the resilience of the ecosystem in DMZ.

• Geomechanics and Engineering
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• v.36 no.3
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• pp.205-215
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• 2024

Manually mapping fractures in construction stone mines is challenging, time-consuming, and hazardous. In this method, there is no physical access to all points. In contrast, digital image processing offers a safe, cost-effective, and fast alternative, with the capability to map all joints. In this study, two methods of detecting the trace of discontinuities using image processing in construction stone mines are presented. To achieve this, we employ two modified Hough transform algorithms and the degree of neighborhood technique. Initially, we introduced a method for selecting the best edge detector and smoothing algorithms. Subsequently, the Canny detector and median smoother were identified as the most efficient tools. To trace discontinuities using the mentioned methods, common preprocessing steps were initially applied to the image. Following this, each of the two algorithms followed a distinct approach. The Hough transform algorithm was first applied to the image, and the traces were represented through line drawings. Subsequently, the Hough transform results were refined using fuzzy clustering and reduced clustering algorithms, along with a novel algorithm known as the farthest points' algorithm. Additionally, we developed another algorithm, the degree of neighborhood, tailored for detecting discontinuity traces in construction stones. After completing the common preprocessing steps, the thinning operation was performed on the target image, and the degree of neighborhood for lineament pixels was determined. Subsequently, short lines were removed, and the discontinuities were determined based on the degree of neighborhood. In the final step, we connected lines that were previously separated using the method to be described. The comparison of results demonstrates that image processing is a suitable tool for identifying rock mass discontinuity traces. Finally, a comparison of two images from different construction stone mines presented at the end of this study reveals that in images with fewer traces of discontinuities and a softer texture, both algorithms effectively detect the discontinuity traces.

• The Journal of the Korea Contents Association
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• v.22 no.5
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• pp.15-25
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• 2022

This study aims to identify the family and lineage of a part of a "Fish Tribe Conference" in the section Tokkijeon by utilizing computer literature analysis techniques. First of all, we encode the classification for a pairwise comparison's type of each paragraph to build a corpus, and based on this, we use the Hamming distance to calculate the distance matrix between each classification for a pairwise comparison's. We visualized classification for a pairwise comparison's clustering pattern by applying multidimensional scale method, and hierarchical clustering to explore the characteristics of the 'fish family' line and lineage compared to the existing cluster analysis study on entire paragraphs of "Tokkijeon". As a result, unlike the cluster analysis of the entire paragraph of "Tokkijeon", which consists of six categories, the "Fish Tribe Conference" section has five categories and some classification for a pairwise comparison's accesses. The results of this study are that the relative distance between Yibon was measured and systematic classification was performed in an objective and empirical way by calculation, and the characteristics of the line of the fish family were revealed compared to the analysis of the entire rabbit exhibition.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.82-89
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• 2012

This paper presents the intelligent tracking algorithm for maneuvering target using the positional error compensation of the maneuvering target. The difference between measured point and predict point is separated into acceleration and noise. Fuzzy c-mean clustering and predicted impact point are used to get the optimal acceleration value. The membership function is determined for acceleration and noise which are divided by fuzzy c-means clustering and the characteristics of the maneuvering target is figured out. Divided acceleration and noise are used in the tracking algorithm to compensate computational error. The filtering process in a series of the algorithm which estimates the target value recognize the nonlinear maneuvering target as linear one because the filter recognize only remained noise by extracting acceleration from the positional error. After filtering process, we get the estimates target by compensating extracted acceleration. The proposed system improves the adaptiveness and the robustness by adjusting the parameters in the membership function of fuzzy system. To maximize the effectiveness of the proposed system, we construct the multiple model structure. Procedures of the proposed algorithm can be implemented as an on-line system. Finally, some examples are provided to show the effectiveness of the proposed algorithm.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.3
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• pp.191-210
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• 2023

The purpose of this study is to draw implications through domestic and international best case studies of library programs, and to suggest ways to improve a public library reading programs through analysis based on the 3rd Reading Culture Promotion Basic Plan in line with the changing role of future libraries. there is To this end, first, prior studies were analyzed from various angles to derive clustering standards for library programs. Based on this, programs of various domestic and foreign libraries were analyzed based on clustering criteria. And based on the clustering criteria of library programs and the 13 key tasks under the 4 strategies of the 3rd Reading Culture Promotion Basic Plan, the status of a specific public library reading programs was analyzed. Through this, in consideration of the demand of users in the era of the 4th Industrial Revolution, participatory reading promotion programs are expanded, and in response to the post-COVID-19 era, beyond face-to-face library services, non-face-to-face and non-contact library services are also considered. A development plan was presented. It is expected that this analysis and application attempt will ultimately go beyond the unit library and contribute to improving the public library service in Korea into a library program closely related to the lives of users.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.5
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• pp.28-41
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• 2020

This study selects two linear parks representing each culture and reveals the differences between them using a visitor survey as small data and social media analytics as big data based on the three components of the model of landscape perception. The 606 in Chicago, U.S., and the Gyeongchun Line in Seoul, Korea, are representative parks built on railroads. A total of 505 surveys were collected from these parks. The responses were analyzed using descriptive statistics, principal component analysis, and linear regression. Also, more than 20,000 tweets which mentioned two linear parks respectively were collected. By using those tweets, the authors conducted the clustering analysis and draw the bigram network diagram for identifying and comparing the placeness of each park. The result suggests that more diverse design concept links to less diversity in behavior; that half of the park users use the park as a shortcut; and that same physical exercise provides different benefits depending on the park. Social media analysis showed the 606 is more closely related to the neighborhoods rather than the Gyeongchun Line Forest. The Gyeongchun Line Forest was a more event-related place than the 606.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.5A
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• pp.717-725
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• 2000

Within the last several years, there has been a large number of algorithms developed for face recognition. The majority of these algorithms have been view- and projection-based algorithms. Our definition of projection is not restricted to projecting the image onto an orthogonal basis the definition is expansive and includes a general class of linear transformation of the image pixel values. The class includes correlation, principal component analysis, clustering, gray scale projection, and matching pursuit filters. In this paper, we perform a detailed analysis of this class of algorithms by evaluating them on the FERET database of facial images. In our experiments, a projection-based algorithms consists of three steps. The first step is done off-line and determines the new basis for the images. The bases is either set by the algorithm designer or is learned from a training set. The last two steps are on-line and perform the recognition. The second step projects an image onto the new basis and the third step recognizes a face in an with a nearest neighbor classifier. The classification is performed in the projection space. Most evaluation methods report algorithm performance on a single gallery. This does not fully capture algorithm performance. In our study, we construct set of independent galleries. This allows us to see how individual algorithm performance varies over different galleries. In addition, we report on the relative performance of the algorithms over the different galleries.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.3
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• pp.259-266
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• 2013

An automated cell tracking system is used to automatically analyze and track the changes in cell behavior in time-lapse cell images acquired using a microscope with a cell culture. Clustering is the partial overlapping of neighboring cells in the process of cell change. Separating clusters into individual cells is very important for cell tracking. In this study, we proposed an algorithm for separating clusters by using ellipse fitting based on a direct least square method. We extracted the contours of clusters, divided them into line segments, and then produced their fitted ellipses using a direct least square method for each line segment. All of the fitted ellipses could be used to separate their corresponding clusters. In experiments, our algorithm separated clusters with average precisions of 91% for two overlapping cells, 84% for three overlapping cells, and about 73% for four overlapping cells.