• Culinary science and hospitality research
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• v.14 no.2
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• pp.61-72
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• 2008

The purpose of this study was to analyze the difference in preference and property of native local foods among students living in Busan. It concentrated on the students who were majored in food service in five universities in Busan. From September 1st to 30th, 2007, 300 copies of questionnaire were distributed and 260 returned were included in the statistics. The statistics was conducted by frequency analysis, T-test(average deviation verification), technical analysis and one way ANOVA for an accurate result of the study. As a result, it was found that Gayamilmyeon(M=4.42) showed the most preference for 25 native local foods of Busan(sansungmakgeoli, dongraepajeon, steamed carp, catfish soup, corbicula soup, roasted eel, gijang raw hairtail, dongrae mugwort cake, sansung roasted goat, gijangkkomjangeo, steamed frogfish, duck dish, guponoodles, gayamilmyeon, sliced raw fish, molsim hot-pepper fish stew, hairtail stew, anchovy stew, miyeoksulchi, gompi salted dish, salted raw anchovy dish, roasted kkomjaneo, salted sliced persimmon dish, salted bean leave dish, kkasiri soup). On the other hand, it was found that Miyeoksulchi(M=2.66) showed the least preference among them. As a result of the analysis of the difference in demographic characteristics and property of native local foods, it was presented that there was no difference in the statistical analysis by sex but significant difference in taste, quantity, service, price, freshness, sanitation, packing condition and originality, etc by age, department, academic year, type of residence, family member, living period in Busan and monthly spending. It was considered to conduct a more in-depth study to promote native local foods and interest in the food of Busan in university students.

• The Korean Journal of Applied Statistics
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• v.31 no.6
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• pp.825-833
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• 2018

We examined the relationship between the order of signs and the order of vote within parties in electing local district councilors during the 7th nationwide local election held on June 13th, 2018. We analyzed election data for respective cases that include two, three, four candidates within the same party. In most cases, the candidate with sign 'Ga' gained more than other candidates in the same party, showing a need for provisional measures. In addition, a difference in voting tendency was found between in-house voting and early outside voting when there were two candidates in the Democratic Party of Korea as well as for when there were two candidates in the Liberty Korea Party.

• The Korean Journal of Applied Statistics
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• v.22 no.3
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• pp.479-488
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• 2009

The ${\kappa}$-Nearest Neighbors Classification(KNNC) is a popular non-parametric classification method which assigns a fixed number ${\kappa}$ of neighbors to every observation without consideration of the local feature of the each observation. In this paper, we propose an Adaptive Nearest Neighbors Classification(ANNC) as an alternative to KNNC. The proposed ANNC method adapts the number of neighbors according to the local feature of the observation such as density of data. To verify characteristics of ANNC, we compare the number of misclassified observation with KNNC by Monte Carlo study and confirm the potential performance of ANNC method.

• 한국데이터정보과학회:학술대회논문집
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• 2005.04a
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• pp.164-173
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• 2005

Data mining is the method to find useful information for large amounts of data in database. It is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. The decision tree approach is most useful in classification problems and to divide the search space into rectangular regions. Decision tree algorithms are used extensively for data mining in many domains such as retail target marketing, fraud detection, data reduction and variable screening, category merging, etc. We analyze waste database united with local information using decision tree techniques for environmental information. We can use these decision tree outputs for environmental preservation and improvement.

• Communications for Statistical Applications and Methods
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• v.24 no.3
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• pp.271-290
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• 2017

We study a bivariate response regression model with arbitrary marginal distributions and joint distributions using Frank and Clayton's families of copulas. The proposed model is used for fitting dependent bivariate data with explanatory variables using the log-odd log-logistic Weibull distribution. We consider likelihood inferential procedures based on constrained parameters. For different parameter settings and sample sizes, various simulation studies are performed and compared to the performance of the bivariate odd-log-logistic-Weibull regression model. Sensitivity analysis methods (such as local and total influence) are investigated under three perturbation schemes. The methodology is illustrated in a study to assess changes on schoolchildren's oral health-related quality of life (OHRQoL) in a follow-up exam after three years and to evaluate the impact of caries incidence on the OHRQoL of adolescents.

• Communications for Statistical Applications and Methods
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• v.27 no.1
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• pp.129-140
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• 2020

In this paper, we introduce an efficient algorithm for the non-convex penalized multinomial logistic regression that can be uniformly applied to a class of non-convex penalties. The class includes most non-convex penalties such as the smoothly clipped absolute deviation, minimax concave and bridge penalties. The algorithm is developed based on the concave-convex procedure and modified local quadratic approximation algorithm. However, usual quadratic approximation may slow down computational speed since the dimension of the Hessian matrix depends on the number of categories of the output variable. For this issue, we use a uniform bound of the Hessian matrix in the quadratic approximation. The algorithm is available from the R package ncpen developed by the authors. Numerical studies via simulations and real data sets are provided for illustration.

• The Korean Journal of Applied Statistics
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• v.33 no.4
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• pp.499-509
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• 2020

We compared and analyzed the relationship between vote intention, vote expectation, and party approval rate using the 19th Presidential Election and the 7th Nationwide Simultaneous Local Election (Regional Local Government Election) poll data. The case study provides an alternative method of predicting the winner using vote expectation and a party approval rate that can improve the accuracy of election forecasting.

• Journal of the Korean Mathematical Society
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• v.47 no.2
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• pp.385-407
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• 2010

To study the relationship between the levels of chemical pollutants and the number of daily total hospital admissions for respiratory diseases and to find the effect of temperature/relative humidity on the admission number, Wong et al. [17] introduced the varying-coefficient single-index model (VCSIM). As pointed out, it is a popular multivariate nonparametric fitting technique. However, the tests of the model have not been very well developed. In this paper, based on the estimators obtained by the local linear technique, the average method and the one-step back-fitting technique in the VCSIM, the generalized likelihood ratio (GLR) tests for varying-coefficient parts on the VCSIM are established. Under the null hypotheses the new proposed GLR tests follow the $\chi^2$-distribution asymptotically with scale constant and degree of freedom independent of the nuisance parameters, known as Wilks phenomenon. Simulations are conducted to evaluate the test procedure empirically. A real example is used to illustrate the performance of the testing approach.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.116-120
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• 2006

This paper discusses an approach for detecting a new edge in color images. The color image is to be represented by a vector field, and the color image edges are detected as differences in the local vector statistics. This method is based on the calculation for the vector angle between two adjacent pixels. Unlike Euclidean distance in RGB space, the vector angle distinguishes the differences in chromaticity, independent of luminance or intensity. The proposed approach can easily accommodate concepts, such as variable template edge detection, as well as the latest developments in vector order statistics for color image processing. In this paper, it is used not a conventional fixed template operator but a variable template operator The variable template is implemented and experimental results for digital color images are included.

• Journal of IKEEE
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• v.17 no.4
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• pp.478-483
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• 2013

This paper presents an adaptive Retinex algorithm for improving dynamic range of image representation. The proposed Retinex algorithm detects degraded brightness by using skewness and the degraded components are compensated with local statistics. In particular, we propose a new compensation function for dynamic range so that effectinve image representation can be achieved. Experimental results show that the proposed algorithm has the capability to improve the dynamic range with reduction of color degradation.