• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.159-168
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• 2008

Since the term structure of interest rates (TSIR) has longitudinal data, we should consider as input variables both time left to maturity and time simultaneously to get a more useful and more efficient function estimation. However, since the resulting data set becomes very large, we need to develop a fast and reliable estimation method for large data set. Furthermore, it tends to overestimate TSIR because data are correlated. To solve these problems we propose a mixture of weighted least squares support vector machines. We recognize that the estimate is well smoothed and well explains effects of the third stock market crash in USA through applying the proposed method to the US Treasury bonds data.

• The International Journal of Costume Culture
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• v.12 no.1
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• pp.38-51
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• 2009

The goal of this study is to define the types of the lifestyles of senior consumers and identify the differences in the properties of apparel products and the apparel attitudes. To collect the data for this study, questionnaires for the research were distributed from November 20, 2006 to December 15, 2006 to those over 50 living in Seoul, Pusanand Kyunggi and 302 questionnaires were used for the data analysis. The results of the study are as follows. First, six factors were extracted which were "Pursuit of Self-development", "Pursuit of Active Life", "Pursuit of Material", "Pursuit of Diversity", "Pursuit of Family-oriented" and "Pursuit of Recreational Life" after factor analysis of lifestyles recognized by the senior consumers that participated in this study. Second, the lifestyles of the senior consumers were categorized into "Consumption-oriented Type", "Personal Satisfaction-oriented Type", "Family Weighted Type" and "Recreation-oriented Type." Third, three factors were extracted which were "Symbolical Property", "Functional Property" and "Customer Support Property" after conducting the factor analysis on the properties of apparel products. Fourth, significant differences were shown in apparel properties by the lifestyle types of senior consumers in the symbolical property and the customer support property. The "symbolical property" was shown highest in "recreation-oriented type" and lowest in the "family weighted type." The customer support property was shown highest in the "family weighted type" and lowest in the "recreation-oriented type", showing the opposite result. Fifth, significant differences were shown in apparel attitudes by the lifestyle types of senior consumers in "Fashion Innovativeness", "Apparel Involvement" and "Apparel Necessity." The "fashion innovativeness" was shown highest in the "recreation-oriented type" and lowest in the "family weighted type." The apparel involvement and the necessity for apparel for senior citizens was shown high in the "recreation-oriented type" and this showed that the senior consumers valuing recreation also value fashion, have high apparel involvement and feel the necessity for apparel for senior citizens.

• Journal of Communications and Networks
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• v.11 no.2
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• pp.122-133
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• 2009

As wireless spectrum resources become more scarce while some portions of frequency bands suffer from low utilization, the design of cognitive radio (CR) has recently been urged, which allows opportunistic usage of licensed bands for secondary users without interference with primary users. Spectrum sensing is fundamental for a secondary user to find a specific available spectrum hole. Cooperative spectrum sensing is more accurate and more widely used since it obtains helpful reports from nodes in different locations. However, if some nodes are compromised and report false sensing data to the fusion center on purpose, the accuracy of decisions made by the fusion center can be heavily impaired. Weighted sequential probability ratio test (WSPRT), based on a credit evaluation system to restrict damage caused by malicious nodes, was proposed to address such a spectrum sensing data falsification (SSDF) attack at the price of introducing four times more sampling numbers. In this paper, we propose two new schemes, named enhanced weighted sequential probability ratio test (EWSPRT) and enhanced weighted sequential zero/one test (EWSZOT), which are robust against SSDF attack. By incorporating a new weight module and a new test module, both schemes have much less sampling numbers than WSPRT. Simulation results show that when holding comparable error rates, the numbers of EWSPRT and EWSZOT are 40% and 75% lower than WSPRT, respectively. We also provide theoretical analysis models to support the performance improvement estimates of the new schemes.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.3
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• pp.163-172
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• 2016

Electric load forecasting is essential for effective power system planning and operation. Complex and nonlinear relationships exist between the electric loads and their exogenous factors. In addition, time-series load data has non-stationary characteristics, such as trend, seasonality and anomalous day effects, making it difficult to predict the future loads. This paper proposes a locally-weighted polynomial neural network (LWPNN), which is a combination of a polynomial neural network (PNN) and locally-weighted regression (LWR) for daily shortterm peak load forecasting. Model over-fitting problems can be prevented effectively because PNN has an automatic structure identification mechanism for nonlinear system modeling. LWR applied to optimize the regression coefficients of LWPNN only uses the locally-weighted learning data points located in the neighborhood of the current query point instead of using all data points. LWPNN is very effective and suitable for predicting an electric load series with nonlinear and non-stationary characteristics. To confirm the effectiveness, the proposed LWPNN, standard PNN, support vector regression and artificial neural network are applied to a real world daily peak load dataset in Korea. The proposed LWPNN shows significantly good prediction accuracy compared to the other methods.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.347-350
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• 2002

In the input buffer switch system, VOQ(Virtual Output Queue) archives 100% throughput. The VOQ with the systolic architecture maintains an uniform performance regardless of a number of Packet class and output port, so that it doesn't have a limitation of scalability. In spite of these advantages, the systolic architecture VOQ is difficult to change sorting order In this paper, we Proposed a systolic architecture VOQ which support weighted round robin(WRR) algorithm to provide with flow control service.

• Journal of the Korean Data and Information Science Society
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• v.21 no.2
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• pp.309-316
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• 2010

Support vector quantile regression (SVQR) is capable of providing more complete description of the linear and nonlinear relationships among response and input variables. In this paper we propose a weighted SVQR for the longitudinal data. Furthermore, we introduce the generalized approximate cross validation function to select the hyperparameters which affect the performance of SVQR. Experimental results are the presented, which illustrate the performance of the proposed SVQR.

• Communications for Statistical Applications and Methods
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• v.17 no.3
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• pp.451-457
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• 2010

This paper considers the problem of nonparametric deconvolution density estimation when sample observa-tions are contaminated by double exponentially distributed errors. Three different deconvolution density estima-tors are introduced: a weighted kernel density estimator, a kernel density estimator based on the support vector regression method in a RKHS, and a classical kernel density estimator. The performance of these deconvolution density estimators is compared by means of a simulation study.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.931-939
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• 2014

In this paper we propose the iteratively reweighted least squares procedure to solve the quadratic programming problem of support vector expectile regression with an asymmetrically weighted squares loss function. The proposed procedure enables us to select the appropriate hyperparameters easily by using the generalized cross validation function. Through numerical studies on the artificial and the real data sets we show the effectiveness of the proposed method on the estimation performances.

• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.505-508
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• 2003

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.417-426
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• 2018

An alternative developmental toxicity test using mouse embryonic stem cell derived embryoid bodies has been developed. This alternative method is not to administer chemicals to animals, but to treat chemicals with cells. This study suggests the use of Discriminant Analysis, Support Vector Machine, Artificial Neural Network and k-Nearest Neighbor. Algorithm performance was compared with accuracy and a weighted Cohen's kappa coefficient. In application, various classification techniques were applied to cytotoxicity data to classify drug toxicity and compare the results.