• Journal of KIISE
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• v.45 no.3
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• pp.288-293
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• 2018

There have recently been several studies investigating how to apply a privacy preserving technique to publish data. Differential privacy can protect personal information regardless of an attacker's background knowledge by adding probabilistic noise to the original data. To perform differentially private k-means clustering, the existing algorithm builds a differentially private histogram and performs the k-means clustering. Since it constructs an equi-width histogram without considering the distribution of data, there are many buckets to which noise should be added. We propose a k-means clustering algorithm using a quad-tree that captures the distribution of data by using a small number of buckets. Our experiments show that the proposed algorithm shows better performance than the existing algorithm.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.633-641
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• 2008

This study introduces the method of detecting and restoring occlusion areas by using epipolar algorithm and K-means classification algorithm for true ortho-photo generation. In the past, the techniques of detecting occlusion areas are using the reference images or information of buildings. But, in this study the occlusion areas can be automatically detected by using DTM data and exterior orientation parameters. The detected occlusion areas can be restored by using anther images or the computed values which are determined in K-means classification algorithm. In addition, this method takes advantages of applying epipolar algorithm in order to find same location in overlapping areas among images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.550-554
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• 1995

The present paper deals with the dynamic stability and vibration suppression of a cantilevered flexible pipe with a concetrated mass under an internal fluid flow. The equations of motion are derived by energy expressions using Hamilton's pronciple, and some analytical results using Galerkin's method are presented. Finally, the vibration suppression technique by means of an internal fluid flow is demonstrated experimentally.

• Proceedings of the KIEE Conference
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• 2007.04a
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• pp.207-209
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• 2007

In this paper, we introduce a genetic optimization of fuzzy set-fuzzy model using successive tuning method to carry out the model identification of complex and nonlinear systems. To identity we use genetic alrogithrt1 (GA) sand C-Means clustering. GA is used for determination the number of input, the seleced input variables, the number of membership function, and the conclusion inference type. Information Granules (IG) with the aid of C-Means clustering algorithm help determine the initial paramters of fuzzy model such as the initial apexes of the, membership functions in the premise part and the initial values of polyminial functions in the consequence part of the fuzzy rules. The overall design arises as a hybrid structural and parametric optimization. Genetic algorithms and C-Means clustering are used to generate the structurally as well as parametrically optimized fuzzy model. To identify the structure and estimate parameters of the fuzzy model we introduce the successive tuning method with variant generation-based evolution by means of GA. Numerical example is included to evaluate the performance of the proposed model.

• Journal of Information Technology Services
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• v.16 no.2
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• pp.97-110
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• 2017

Due to development of IT, various Internet services via the non-face-to-face are increasing rapidly. In the past, the resident registration numbers (RRN) was used a mean of personal identification, but the use of RRN is prohibited by the relevant laws, and the personal identification services using alternative means are activated. According to the prohibition policy of RRN, i-PIN service appeared as an alternative means to identify a person. However, the user's knowledge-based i-PIN service continues to cause fraudulent issuance, account hijacking, and fraud attempts due to hacking accidents. Due to these problems, the usage rate of i-PIN service which performs a nationwide free personal identification service, is rapidly decreasing. Therefore, this paper proposes a technical safety enhancement method for security enhancement in the i-PIN-based personal identification service. In order to strengthen the security of i-PIN, this paper analyzes the encryption key exposure, key exchange and i-PIN authentication model problems of i-PIN and suggests countermeasures. Through the proposed paper, the i-PIN can be expected to be used more effectively as a substitution of RRN by suggesting measures to enhance the safety of personal identification information. Secured personal identification services will enable safer online non-face-to-face transactions. By securing the technical, institutional, and administrative safety of the i-PIN service, the usage rate will gradually increase.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.403-406
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• 1999

Among the compression methods of moving picture information, a motion estimation method is used to remove time-repeating. The Block Matching Algorithm in motion estimation methods is the commonest one. In recent days, it is required the more advanced high quality in many image processing fields, for example HDTV, etc. Therefore, we have to accomplish not by means of Partial Search Algorithm, but by means of Full Search Algorithm in Block Matching Algorithm. In this paper, it is suggested a structure that reduce total calculation quantity and size, because the structure using Bit Plane select and use only 3bit of 8bit luminance signal.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.289-292
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• 2001

This paper investigates a RBF equalizer (RBFE) reducing a center Estimating Speed. One of method for RBF center estimation is using k-means clustering. The performance of RBFE is depends on the estimation ability of the RBF center. We Propose a RBF Equalizer using modified k-means clustering algorithm (MKMC) to speed up channel estimation and to reduce complexity of calculation. Computer simulations are included to illustrate the analytical results. It is shown that a discussed method improves about 1 dB via less training data.

• International journal of advanced smart convergence
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• v.2 no.1
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• pp.12-17
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• 2013

This paper introduces the fuzzy scatter partition-based fuzzy inference system to construct the model for nonlinear process to analyze nonlinear characteristics. The fuzzy rules of fuzzy inference systems are generated by partitioning the input space in the scatter form using Fuzzy C-Means (FCM) clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the parameters of the consequence part are estimated by least square errors. The proposed model is evaluated with the performance using the data widely used in nonlinear process. Finally, this paper shows that the proposed model has the good result for high-dimension nonlinear process.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.126-132
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• 2000

This paper presents a facial expression recognition based on Gabor wavelets that uses a fuzzy C-means(FCM) clustering algorithm and neural network. Features of facial expressions are extracted to two steps. In the first step, Gabor wavelet representation can provide edges extraction of major face components using the average value of the image's 2-D Gabor wavelet coefficient histogram. In the next step, we extract sparse features of facial expressions from the extracted edge information using FCM clustering algorithm. The result of facial expression recognition is compared with dimensional values of internal stated derived from semantic ratings of words related to emotion. The dimensional model can recognize not only six facial expressions related to Ekman's basic emotions, but also expressions of various internal states.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.27 no.12
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• pp.877-882
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• 2014

It has been confirmed that the inner defect of transformer and the perfect diagnosis for aging are closely related to safe electric power transmission system and that the detection of accident and diagnosis technique turn out to be very important issues. Since electric power machinery consists of various kinds of components, however, it is very difficult to make a diagnosis for aging by one parameter. Thus, diagnosis for aging is feasible only through the combination of various parameters. Recently, various expert systems have been developed and applied to diagnosis for aging, but they are not yet reliable enough to apply to the real system. In this paper, XLPE which is ultra high voltage cable insulator material were chosen to investigate the influence of void on insulator material using partial discharge. Obtained data have been processed by PRPD (phased resolved partial discharge) distribution function and K-means. And statistical and cluster distribution of partial discharge have been analysed and investigated.