• Journal of Institute of Control, Robotics and Systems
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• v.13 no.1
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• pp.46-51
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• 2007

In this paper, we propose a new data clustering method using local probability and hypothesis theory. To cluster the test data set we analyze the local area of the test data set using local probability distribution and decide the candidate class of the data set using mean standard deviation and variance etc. To decide each class of the test data, statistical hypothesis theory is applied to the decided candidate class of the test data set. For evaluating, the proposed classification method is compared to the conventional fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm. The simulation results show more accuracy than results of fuzzy c-mean method, k-means algorithm and Discriminator analysis algorithm.

• International Journal of Naval Architecture and Ocean Engineering
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• v.5 no.1
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• pp.1-20
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• 2013

In the present paper, the sloshing resistance performance of a huge-size LNG carrier's insulation system is evaluated by the fluid-structure interaction (FSI) analysis. To do this, the global-local analysis which is based on the arbitrary Lagrangian-Eulerian (ALE) method is adopted to accurately calculate the structural behavior induced by internal LNG sloshing of a KC-1 type LNG carrier insulation system. During the global analysis, the sloshing flow and hydrodynamic pressure of internal LNG are analyzed by postulating the flexible insulation system as a rigid body. In addition, during the local analysis, the local hydroelastic response of the LNG carrier insulation system is computed by solving the local hydroelastic model where the entire and flexible insulation system is adopted and the numerical analysis results of the global analysis such as initial and boundary conditions are implemented into the local finite element model. The proposed novel analysis techniques can potentially be used to evaluate the structural integrity of LNG carrier insulation systems.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.233-240
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• 2024

We analyzed the effect of local college students' economic activities on the local economy. The analysis method was an industry-related analysis based on data obtained from a survey. As a result of the analysis, local university students were found to be sensitive to price when consuming due to insufficient living infrastructure around local universities. In addition, as a result of analyzing the impact of local college students' consumption expenditures on the local economy, especially local income, using a regional industry correlation table, the total income generated was KRW 130.6 billion (direct and indirect income effects KRW 90.9 billion, induced income effects KRW 39.6 billion), and the number of people induced to be employed was KRW 130.6 billion. It was estimated that there were 2,145 people per year. We examined the effect of local college students' economic activities on the local economy through quantitative analysis. This is a contribution point of the study as evidence supporting the maintenance and necessity of local universities, and suggests that the government and local governments should take active interest and efforts in fostering local universities.

• Smart Structures and Systems
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• v.24 no.5
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• pp.597-606
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• 2019

Damage detection based on dynamic characteristics of a structure is one of important roles in structural damage identification. It is difficult to detect local structural damage using traditional dynamic experimental methods due to a limited number of sensors used in an experiment. In this work, a non-contact test stand of fan blades is established, and a full-field noncontact test method, combined with three-dimensional digital image correlation, Bayesian operational modal analysis, and damage indices, is used to detect local damage of a fan blade under ambient excitation without use of baseline information before structural damage. The methodology is applied to detect invisible local damage on the fan blade. Such a method has a seemingly high potential as an alternative to detect local damage of blades with complex high-precision surfaces under extreme working conditions because it is a noncontact test method and can be used under ambient excitation without human participation.

• Korean Management Science Review
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• v.22 no.1
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• pp.1-13
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• 2005

This paper proposed a quantitative evaluation method to measure the operational effectiveness of the local military manpower administrations. The proposed method compared the relative operational effectiveness level for 12 local military manpower administrations in Korea.. The method used the IDEA (imprecise Data Envelopment Analysis) model which Is able to measure relative operational effectiveness level, and also used two input variables (labor cost, operational cost) and three output variables (number of military applicants, number of civil application approved & processed, management accuracy level). Through the model output analysis, we presented the relative effectiveness scores, the reason for non-effectiveness, and the relationship between non-effective ness level and input/output variables for each local military manpower administration. We also presented a few recommendations how to improve the effectiveness level on particular local military manpower administration.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.228-234
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• 2002

This paper proposes a real-time application of rationalized Haar transform which is based on the local rationalized Haar transform, local operational matrix and local delay operational matrix. This approach let a general sampling time be used by introducing a scaling factor. In the existing method of orthogonal functions, a major disadvantage is that process signals need to be recorded prior to obtaining their expansions. This paper proposes a novel method of rationalized Haar transform to overcome this shortcoming. And the proposed method is suitable for the analysis of linear systems. The proposed method is expected to the applicable to the adaptive control which demanded to the real-time applications.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.81-86
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• 2012

In this paper, we proposed a new design methodology of a pattern classification rule based on the local linear discriminant analysis expanded from the generic linear discriminant analysis which is used in the local area divided from the whole input space. There are two ways such as k-Means clustering method and the differential evolutionary algorithm to partition the whole input space into the several local areas. K-Means clustering method is the one of the unsupervised clustering methods and the differential evolutionary algorithm is the one of the optimization algorithms. In addition, the experimental application covers a comparative analysis including several previously commonly encountered methods.

• Communications for Statistical Applications and Methods
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• v.6 no.1
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• pp.43-52
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• 1999

The local influence method is adapted to quadratic discriminant analysis for the identification of influential observations affecting the estimation of probability density function probabilities and log odds. The method allows a simultaneous perturbation on all observations so that it can identify multiple influential observations. The proposed method is applied to a real data set and satisfactory result is obtained.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.3
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• pp.54-60
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• 2010

The local appearance-based method is one of the face recognition methods that divides face image into small areas and extracts features from each area of face image using statistical analysis. It collects classification results of each area and decides identity of a face image using a voting scheme by integrating classification results of each area of a face image. The conventional local appearance-based method divides face images into small pieces and uses all the pieces in recognition process. In this paper, we propose a local appearance-based method that makes use of only the relatively important facial components. The proposed method detects the facial components such as eyes, nose and mouth that differs much from person to person. In doing so, the proposed method detects exact locations of facial components using support vector machines (SVM). Based on the detected facial components, a number of small images that contain the facial parts are constructed. Then it extracts features from each facial component image using principal components analysis (PCA). We compared the performance of the proposed method to those of the conventional methods. The results show that the proposed method outperforms the conventional local appearance-based method while preserving the advantages of the conventional local appearance-based method.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.5
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• pp.118-126
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• 1996

In object analysis by image processing, finding lines plays a universal role. And these lines can be easily found by detecting ridges and valleys in digital gray scale images. In this paper, a new method of detecting ridges and valleys by using local min/max operations was presented. This method detects ridges and valleys of desired width by using erosion and dilation properties of local min/max operations, and requires no information of ridge or valley direction. Therefore the method is efficient and computationally simple in comparision with the conventional analytical method.