• 한국정보과학회:학술대회논문집
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• 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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• pp.482-484
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• 1998

Abstract : Multimedia data now one of the widely used information in all the fields as the fast developments of computer techniques have been made. Traditional database systems based on textual information have limitations when applied to multimedia information. This is because simple textual descriptions are ambiguous and inadequate for searching multimedia information for multimedia databases and digital libraries. Thus, especially for image data, which is one of the important multimedia information types, which can retrieve and browse image data on the basis of pictorial queries. Therefore, this paper presents an efficient method for describing texture information in image data.

• 응용통계연구
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• 제21권6호
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• pp.1109-1116
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• 2008

Biplots are the multivariate analogue of scatter plots. They are useful for giving a graphical description of the data matrix, for detecting patterns and for displaying results found by more formal methods of analysis. Nevertheless, when some values are missing in data matrix, most biplots are not directly applicable. In particular, we are interested in the shape variability of principal component biplot which is the most popular in biplots with missing values. For this, we estimate the missing data using the EM algorithm and mean imputation according to missing rates. Even though we estimate missing values of biplot of incomplete data, we have different shapes of biplots according to the imputation methods and missing rates. Therefore we propose a RMS(root mean square) for measuring and comparing the shape variability between the original biplots and the estimated biplots.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.351-356
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• 2011

Some materials show the character of rigid body in low frequency spectrum. The rigid body motions are consisted of translational and rotational motions. Especially, we can get the acceleration or displacement of a random point in the rigid body by analyzing rigid body transfer matrix at the car's engine and power train. Actually it is difficult to measure the acceleration by attaching the sensor inside of the engine and power train. So the hard to predict acceleration data can be achieved attaching the sensor on the outside of the engine and power train by analyzing the data of rigid body motion which the engine is operated using dynamo. Also this paper will show the change of predicted data and accuracy variation by not using all the measured data but a few exceptions of the point number.

• 로봇학회논문지
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• 제3권2호
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• pp.117-122
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• 2008

This paper presents a multi-robot localization based on multidimensional scaling (MDS) in spite of the existence of incomplete and noisy data. While the traditional algorithms for MDS work on the full-rank distance matrix, there might be many missing data in the real world due to occlusions. Moreover, it has no considerations to dealing with the uncertainty due to noisy observations. We propose a robust MDS to handle both the incomplete and noisy data, which is applied to solve the multi-robot localization problem. To deal with the incomplete data, we use the Nystr$\ddot{o}$m approximation which approximates the full distance matrix. To deal with the uncertainty, we formulate a Bayesian framework for MDS which finds the posterior of coordinates of objects by means of statistical inference. We not only verify the performance of MDS-based multi-robot localization by computer simulations, but also implement a real world localization of multi-robot team. Using extensive empirical results, we show that the accuracy of the proposed method is almost similar to that of Monte Carlo Localization(MCL).

• 응용통계연구
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• 제32권3호
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• pp.451-462
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• 2019

문서-용어 빈도행렬은 텍스트 마이닝 분야에서 보편적으로 사용되는 데이터의 한 유형으로, 여러 개체들이 제공하는 문서를 기반으로 만들어진다. 그러나 대다수의 연구자들은 개체 정보에 무게를 두지 않고 여러 문서에서 공통적으로 등장하는 공통용어 중 핵심적인 용어를 효과적으로 찾아내는 방법에 집중하는 경향을 보인다. 공통용어에서 핵심어를 선별할 경우 특정 문서에서만 등장하는 중요한 용어들이 공통용어 선정단계에서부터 배제될 뿐만 아니라 개별 문서들이 갖는 고유한 정보가 누락되는 등의 문제가 야기된다. 본 연구에서는 이러한 문제를 극복할 수 있는 데이터를 근접성 데이터라 정의한다. 그리고 근접성 데이터를 생성할 수 있는 12가지 방법 중 개체 군집화의 관점에서 가장 최적화된 방법을 제안한다. 개체 특성 파악을 위한 군집화 알고리즘으로는 다차원척도법과 K-평균 군집분석을 활용한다.

• 한국멀티미디어학회논문지
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• 제17권8호
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• pp.953-960
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• 2014

In Shamir's (t,n)-threshold based secret image sharing schemes, there exists a problem that the secret image can be reconstructed when an arbitrary attacker becomes aware of t secret image pieces, or t participants are malicious collusion. It is because that utilizes linear combination polynomial arithmetic operation. In order to overcome the problem, we propose a secret image sharing scheme using matrix decomposition and adversary structure. In the proposed scheme, there is no reconstruction of the secret image even when an arbitrary attacker become aware of t secret image pieces. Also, we utilize a simple matrix decomposition operation in order to improve the security of the secret image. In experiments, we show that performances of embedding capacity and image distortion ratio of the proposed scheme are superior to previous schemes.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.595-601
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• 2003

In this paper we propose an on line training method for classification based on least squares support vector machine. Proposed method enables the computation cost to be reduced and the training to be peformed incrementally, With the incremental formulation of an inverse matrix in optimization problem, current information and new input data can be used for building the new inverse matrix for the estimation of the optimal bias and Lagrange multipliers, so the large scale matrix inversion operation can be avoided. Numerical examples are included which indicate the performance of proposed algorithm.

• Journal of Nutrition and Health
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• 제39권8호
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• pp.756-761
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• 2006

Curcumin has been known for its anti-proliferative and apoptotic effects on several cancer cells. We examined the inhibitory effects of curcumin on cancer cell adhesion, motility, invasion and matrix metalloproteinase-9 (MMP-9) activity in MDA-MB-231 human breast cancer cells. MDA-MB-231 cells were cultured with 0, 5, 10 or $20{\mu}M$ of curcumin. Curcumin significantly inhibited the adhesion of cancer cells to the fibronectin at $20{\mu}M$ and suppressed the motility and invasion of cancer cells at all concentrations. Also, the MMP-9 activity was inhibited by curcumin, but MMP-9 protein amounts were not affected. Our data indicate that curcumin inhibits motility, invasion and MMP-9 activity of MDA-MB-231 cells. Therefore, curcumin may contribute to the potential beneficial food component to prevent the cancer metastasis in human breast cancer.

• 응용통계연구
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• 제25권3호
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• pp.531-541
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• 2012

In this study, we consider various methods to estimate the weights of a pairwise comparison matrix in the Analytic Hierarchy Process widely applied in various decision-making fields. This paper uses a data dependent simulation to evaluate the statistical accuracy, minimum violation and minimum norm of the obtaining weight methods from a reciprocal symmetric matrix. No method dominates others in all criteria. Least squares methods perform best in point of mean squared errors; however, the eigenvectors method has an advantage in the minimum norm.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.372-377
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• 2001

Piezoelectric Fiber Composites with Interdigitated Electrodes (PFCIDE) were previously introduced as an alternative to monolithic wafers with conventional electrodes for applications of structural actuation. This paper is an investigation into the performance improvement of piezoelectric fiber composite actuators by changing the matrix material. This paper presents a modified micro-electromechanical model of a piezoelectric fiber/piezopolymer matrix composite actuator with interdigitated electrodes (PFPMIDE). Various concepts from different backgrounds including three-dimensional linear elastic and dielectric theories have been incorporated into the present linear piezoelectric model. The rule of mixture and the modified method to calculate the effective properties of fiber composites are extended to apply to the PFPMIDE model. The new model is validated comparing with available experimental data and other analytical results.