• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.327-333
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• 2022

Principal component analysis (PCA) is the most widely used technique in dimension reduction, however, it is very sensitive to outliers. A robust version of PCA, called robust PCA, was suggested by two seminal papers by Candès et al. (2011) and Chandrasekaran et al. (2011). The robust PCA is an essential tool in the artificial intelligence such as background detection, face recognition, ranking, and collaborative filtering. Also, the robust PCA receives a lot of attention in statistics in addition to computer science. In this paper, we introduce recent algorithms for the robust PCA and give some illustrative examples.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.28 no.1
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• pp.9-18
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• 2015

In this paper, we verify the optimal topology design for heat conduction problems in steady stated which is obtained numerically using the adjoint design sensitivity analysis(DSA) method. In adjoint variable method(AVM), the already factorized system matrix is utilized to obtain the adjoint solution so that its computation cost is trivial for the sensitivity. For the topology optimization, the design variables are parameterized into normalized bulk material densities. The objective function and constraint are the thermal compliance of the structure and the allowable volume, respectively. For the experimental validation of the optimal topology design, we compare the results with those that have identical volume but designed intuitively using a thermal imaging camera. To manufacture the optimal design, we apply a simple numerical method to convert it into point cloud data and perform CAD modeling using commercial reverse engineering software. Based on the CAD model, we manufacture the optimal topology design by CNC.

• The KIPS Transactions:PartA
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• v.11A no.5
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• pp.383-390
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• 2004

This paper propose a method that controls facial expression of 3D avatar by having the user select a sequence of facial expressions in the space of facial expressions. And we setup its system. The space of expression is created from about 2400 frames consist of motion captured data of facial expressions. To represent the state of each expression, we use the distance matrix that represents the distances between pairs of feature points on the face. The set of distance matrices is used as the space of expressions. But this space is not such a space where one state can go to another state via the straight trajectory between them. We derive trajectories between two states from the captured set of expressions in an approximate manner. First, two states are regarded adjacent if the distance between their distance matrices is below a given threshold. Any two states are considered to have a trajectory between them If there is a sequence of adjacent states between them. It is assumed . that one states goes to another state via the shortest trajectory between them. The shortest trajectories are found by dynamic programming. The space of facial expressions, as the set of distance matrices, is multidimensional. Facial expression of 3D avatar Is controled in real time as the user navigates the space. To help this process, we visualized the space of expressions in 2D space by using the multidimensional scaling(MDS). To see how effective this system is, we had users control facial expressions of 3D avatar by using the system. As a result of that, users estimate that system is very useful to control facial expression of 3D avatar in real-time.

• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.11-20
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• 2007

AAM has been successfully applied to face alignment, but its performance is very sensitive to initial values. In this paper, we propose a face alignment method using progressive AAM. The proposed method consists of two stages; modelling and relation derivation stage and fitting stage. Modelling and relation derivation stage first builds two AAM models; the inner face AAM model and the whole face AAM model and then derive the relation matrix between the inner face AAM model parameter vector and the whole face AAM model parameter vector. The fitting stage is processed progressively in two phases. In the first phase, the proposed method finds the feature parameters for the inner facial feature points of a new face, and then in the second phase it localizes the whole facial feature points of the new face using the initial values estimated utilizing the inner feature parameters obtained in the first phase and the relation matrix obtained in the first stage. Through experiments, it is verified that the proposed progressive AAM-based face alignment method is more robust with respect to pose, and face background than the conventional basic AAM-based face alignment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.2
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• pp.173-182
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• 1993

This paper presents an algorithm to derive the representative unit hydrograph for the real environment of a watershed. For a given watershed, the conventional methods give several different unit hydrographs by storm events. In this study the LP model is somewhat modified based on the previous study by Mays et also as follows: the objective function is designed to minimize the sum of weighted residuals. An additional constraint of moving average is added to prevent the unit hydrograph from the occurence of oscillation which was not active in Mays's paper. Configuration of rainfall matrix was improved to reduce its dimension in accordance with Diskin's review point. In spite of the superiority of LP approach in terms of representativeness, all the methods were very sensitive to the validity of baseflow separation and rainfall-loss. Several methods of the separations for rainfall excesses and direct runoffs were applied and no preferred methods were identified. This is the matter of judgement considering catchment and rainfall characteristics. This algorithm was applied to a real watershed of the Wi stream in the Nak-dong river. Compared with the IHP results by conventional methods, this optimized representative unit hydrograph demonstrated relatively smaller and shorter values in terms of the peak discharge and the basin lag respectively, and the oscillation of its falling limb successfully eliminated owing to the additional constraints of moving averages.

• Water for future
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• v.27 no.1
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• pp.89-99
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• 1994

Flood forecasting in Korea has been based on the off-line parameter estimation method. But recent flood forecasting studies explore on-line recursive parameter estimation algorithms. In this study, a simultaneous adaptive estimation of system states and parameters for rainfall-runoff model is investigated for on-line real-time flood forecasting and parameter estimation. The proposed flood routing system is composed of Flood forecasting in Korea has been based on the off-line parameter estimation method. But recent flood forecasting studies explore on-line recursive parameter estimation algorithms. In this study, a simultaneous adaptive estimation of system states and parameters for rainfall-runoff model is investigated for on-line real-time flood forecasting and parameter estimation. The proposed flood routing system is composed of ø-index in the assessment of effective rainfall and the cascade of nonlinear reservoirs accounting for translation effect in flood routing. To combine the flood routing model with a parameter estimation model, system states and parameters are treated with the extended state-space formulation. Generalized least squares and maximum a posterior estimation algorithms are comparatively examined as estimation techniques for the state-space model. The sensitivity analysis is to investigate the identifiability of the parameters. The index of sensitivity used in this study is the covariance matrix of the estimated parameters.-index in the assessment of effective rainfall and the cascade of nonlinear reservoirs accounting for translation effect in flood routing. To combine the flood routing model with a parameter estimation model, system states and parameters are treated with the extended state-space formulation. Generalized least squares and maximum a posterior estimation algorithms are comparatively examined as estimation techniques for the state-space model. The sensitivity analysis is to investigate the identifiability of the parameters. The index of sensitivity used in this study is the covariance matrix of the estimated parameters.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.6
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• pp.503-513
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• 2005

With the recognition of the importance of computational approach for protein-protein interaction prediction, many techniques have been developed to computationally predict protein-protein interactions. However, few techniques are actually implemented and announced in service form for general users to readily access and use the techniques. In this paper, we design and implement a protein interaction prediction service system based on the domain combination based protein-protein interaction prediction technique, which is known to show superior accuracy to other conventional computational protein-protein interaction prediction methods. In the prediction accuracy test of the method, high sensitivity($77\%$) and specificity($95\%$) are achieved for test protein pairs containing common domains with teaming sets of proteins in a Yeast. The stability of the method is also manifested through the testing over DIP CORE, HMS-PCI, and TAP data. Performance, openness and flexibility are the major design goals and they are achieved by adopting parallel execution techniques, web Services standards, and layered architecture respectively. In this paper, several representative user interfaces of the system are also introduced with comprehensive usage guides.

• Geophysics and Geophysical Exploration
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• v.22 no.1
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• pp.1-11
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• 2019

Well logging technologies are used to measure the physical properties of reservoirs through boreholes. These technologies have been utilized to understand reservoir characteristics, such as porosity, fluid saturation, etc., using equations based on rock physics models. The analysis of well logs is performed by selecting a reliable rock physics model adequate for reservoir conditions or characteristics, comparing the results using the Archie's equation or simandoux method, and determining the most feasible reservoir properties. In this study, we developed a joint inversion algorithm to estimate physical properties in shaly sandstone reservoirs based on the pre-existing algorithm for sandstone reservoirs. For this purpose, we proposed a rock physics model with respect to shale volume, constructed the Jacobian matrix, and performed the sensitivity analysis for understanding the relationship between well-logging data and rock properties. The joint inversion algorithm was implemented by adopting the least-squares method using probabilistic approach. The developed algorithm was applied to the well-logging data obtained from the Colony gas sandstone reservoir. The results were compared with the simandox method and the joint inversion algorithms of sand stone reservoirs.

• Journal of KIISE
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• v.41 no.10
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• pp.799-809
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• 2014

In this paper, we address the problem of computing Pearson correlation coefficients and Spearman's rank correlation coefficients in a secure manner while data providers preserve privacy of their own data in distributed environment. For a data mining or data analysis in the distributed environment, data providers(data owners) need to share their original data with each other. However, the original data may often contain very sensitive information, and thus, data providers do not prefer to disclose their original data for preserving privacy. In this paper, we formally define the secure correlation computation, SCC in short, as the problem of computing correlation coefficients in the distributed computing environment while preserving the data privacy (i.e., not disclosing the sensitive data) of multiple data providers. We then present SCC solutions for Pearson and Spearman's correlation coefficients using secure scalar product. We show the correctness and secure property of the proposed solutions by presenting theorems and proving them formally. We also empirically show that the proposed solutions can be used for practical applications in the performance aspect.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.249-257
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• 2009

The purpose of this study is to find a classification method with high accuracy in regard with sasang constitutional diagnosis. The BMI, blood pressure, pulse wave, and Sasang constitution diagnosed by a specialist was collected from 2848 subjects who were apparently healthy. Through a selective procedure, the data of 1635 subjects was used in the analysis. The results with the classification methods such as the discriminant analysis, regression, decision tree and neural network were compared with the diagnosis of a Sasang constitutional specialist. In result, the discriminant analysis method was hard to qualify the assumption of the equality of covariance matrices within constitutional groups. Moreover, without BMI, the decision tree and neural network methods were very sensitive to the change of the analysis data. Therefore, the Logistic regression and the decision tree is recommended on condition that the decisive factors of constitution are well concerned.