• The Journal of the Acoustical Society of Korea
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• v.16 no.3
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• pp.81-85
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• 1997

In this paper, a recursive estimation algorithm for FIR systems is proposed using the 3rd and 4th order cumulants. To obtain the Overdetermined Recursive Instrumental Variable(ORIV) method type algorithm, we transform the 3'th and 4'th order cumulant relationship to a certain matrix form which is consist of only output data. From the matrix form, we induce the proposed algorithm procedure following the ORIV method. The proposed algorithm provides improved estimation accuracy with smaller data and can be applied to a time varying system as well. In addition, it reduces the estimation error due to the additive Gaussian noise compared to conventional 2'rd order based algorithms since it only uses higher than 2'rd order cumulant. Simulation results are presented to compare the performance with other HOS-based algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.4
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• pp.639-644
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• 2002

Nonlinear filters which are utilized rank-order information and temporal-order information, have many proposed, in order to restore nonstationary signals which are corrupted by additive noise. In this paper, we propose a data-dependent LWOS filter whose coefficients change based on local statistics. LWOS(Linear Combination of Weighted Order Statistics) filters［1］which also utilized two informations, and have properties of efficient impulsive and nonimpulsive noise attenuation and sufficiently details and edges preservation. DD-LWOS filters can remove non-impulsive oises while preserving signal details. DD-LWOS2 filter gets more better performance than DD-LWOS filter when input image corrupted by additive noise which includes Impulsive noise components.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.20 no.44
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• pp.123-128
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• 1997

A data base design framework for predictive a preventive-maintenance system is presented in this paper in order to effectively control machines and reduce accident rates in the workplace. The data base is designed to meet general management requirements to evaluate different maintenance strategies. There are seven data files: the equipment list maintenace pesonnel, maintenance history, maintenance specification, spare part, maintenance equipment, and maintenance schedules. Each data base file has several record based upon data acquisition.

• Journal of the Korean Data and Information Science Society
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• v.9 no.2
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• pp.165-172
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• 1998

This paper considers a linear regression model with censored data where each error term follows a multivariate normal distribution. In this paper we consider the diffuse prior distribution for parameters of the linear regression model. With censored data we derive the full conditional densities for parameters of a multiple regression model in order to obtain the marginal posterior densities of the relevant parameters through the Gibbs Sampler, which was proposed by Geman and Geman(1984) and utilized by Gelfand and Smith(1990) with statistical viewpoint.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.749-750
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• 2008

It is often required to display 3-D data onto a 2-D screen and to examine and verify validity of data. LIDAR data is a good example. They represent 3-D spatial information in text format. However, it is very difficult to examine data on a 2-D screen. A 3-D data viewing system has been implemented and tested in order to solve the problem.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1999.10a
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• pp.444-451
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• 1999

The purpose of this study is to Propose data models for central database in integrated system for structural design building. In order to efficiently express data related to structure, I analyzed the structure design process and classified data considering design step. 1 used an object-oriented modeling methodology for logical data model and relational modeling for physical data model. Based on this model, we will develop an integration system with several applications for structure design. Each application will communicate through the central database.

• Journal of the Korean Data and Information Science Society
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• v.15 no.2
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• pp.297-306
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• 2004

It is usual that multivariate data analysis produces related (small number of) artificial variates for data reduction. Among them, refer to MDS(multidimensional scaling), MDPREF(multidimensional preference analysis), CDA(canonical discriminant analysis), CCA(canonical correlation analysis) and FA(factor analysis). Varimax rotation of artificial variables which is originally invented in FA for easy interpretations is applied to diverse multivariate techniques mentioned above. Real data analysisis is performed in order to manifest that rotation improves interpretations of artificial variables.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1539-1547
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• 2014

In this paper we apply the autoregressive process to the nonlinear quantile regression in order to infer nonlinear quantile regression models for the autocorrelated data. We propose a kernel method for the autoregressive data which estimates the nonlinear quantile regression function by kernel machines. Artificial and real examples are provided to indicate the usefulness of the proposed method for the estimation of quantile regression function in the presence of autocorrelation between data.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.213-223
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• 2009

In geoid modelling field, it is very important the GPS/leveling data because it could be check-out the accuracy of gravimetric geoid and computed the hybrid geoid. In this study, GPS surveying was accomplished in the test area including mountainous area to improve the GPS/leveling data density in Korea. And the geometric geoidal heights was calculated using the GPS/leveling data in the test area and the accuracy of the geoidal heights was analyzed. For this study, GPS surveying was accomplished on the 211 1st and 2nd order benchmarks in Gyeongbuk province and 198 GPS/leveling data were achieved after both baseline analysis and network adjustment. Geometric geoidal heights were calculated using these 198 GPS/leveling data and the accuracy analysis was done by comparison with the geoidal heights from EGM2008 geopotential model. The results showed that the bias and standard deviation computed from 190 GPS/leveling data after gross removal was -0.185$\pm$0.079m. And also, the accuracy analyses according to the benchmark order, baseline length, and altitude were accomplished.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.595-601
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• 2014

With the advent of the Smart information-communication era, the number of data has increased exponentially. Accordingly, figuring out and analyzing in which area and circumstance the data has been created becomes one of the factors for prompt actions. In this paper identifies how to analyze the data by implementing a route from the lowest module to highest one in an inverse order for the part judgement for the particular data. The script first identifies cluster analisys, paralizes the analysis using the sum of each factors of the cluster with the tree structure, and finally transpose the answer into number. Also, it is designed to place priority on particular answer, thereafter, draws the wanted answer real-time.