• KDI Journal of Economic Policy
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• v.31 no.1
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• pp.207-237
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• 2009

One of the main problems in Korea's public assistance program, the NBLS (National Basic Livelihood Security), is that the loophole of welfare system is continuously growing. Living wage program is the largest sub-program of the NBLS, and the most important determinant of amount of living wage for each beneficiary is the level of reported income. Therefore, accurate and effective income detection is essential in improving policy effects and furthermore reducing the leakage of wage expenditure as beneficiaries always have an incentive to underreport their income. Since most of them do not pay income tax, the welfare authority should exert an independent effort to effectively detect their income. Considering that living wage is a special kind of income tax of which marginal tax rate is -1, one can apply a classical theory of tax evasion to understand illegal or excessive receipt of living wage caused by income underreporting. Utilizing a classical theory given by Alingham and Sandmo (1972), this paper provides a theoretical analysis of the optimal income reporting of the beneficiary. Then an optimization problem is constructed from the government's viewpoint to derive optimal income detecting device (auditing). This paper proves that cut-off discriminated auditing outperforms random auditing and cut-off auditing which implies if the government assigns a positive audit probability to every reported income less than a certain level and the probability is inversely proportional to the level of reported income, it can minimize underreporting and then gradually reduce the leakage of wage expenditure.

• Food Science of Animal Resources
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• v.41 no.6
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• pp.936-949
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• 2021

This study discriminated fatty acid profile and flavor characteristics of Beijing You Chicken (BYC) as a precious local breed and Dwarf Beijing You Chicken (DBYC) eggs. Fatty acid profile and flavor characteristics were analyzed to identify differences between BYC and DBYC eggs. Four classification algorithms were used to build classification models. Arachidic acid, oleic acid (OA), eicosatrienoic acid, docosapentaenoic acid (DPA), hexadecenoic acid, monounsaturated fatty acids (MUFA), polyunsaturated fatty acids (PUFA), unsaturated fatty acids (UFA) and 35 volatile compounds had significant differences in fatty acids and volatile compounds by gas chromatography-mass spectrometry (GC-MS) (p<0.05). For fatty acid data, k-nearest neighbor (KNN) and support vector machine (SVM) got 91.7% classification accuracy. SPME-GC-MS data failed in classification models. For electronic nose data, classification accuracy of KNN, linear discriminant analysis (LDA), SVM and decision tree was all 100%. The overall results indicated that BYC and DBYC eggs could be discriminated based on electronic nose with suitable classification algorithms. This research compared the differentiation of the fatty acid profile and volatile compounds of various egg yolks. The results could be applied to evaluate egg nutrition and distinguish avian eggs.

• Food Science and Biotechnology
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• v.17 no.5
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• pp.1016-1020
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• 2008

Parameters of soluble solids, amino acids, catechins, and color difference of 24 green tea samples from China and Korea were determined. The levels of soluble solids, amino acids, total catechins, and infusion lightness in tea samples from Korea were higher than those from China. Concentrations of epigallocatechin galate and epigallocatechin in teas from China were higher than tea samples from Korea. Geographical origin of teas from the 2 countries was discriminated using parameters of infusion lightness, gallocatechin, and total catechins and applying principal component analysis.

• Fashion & Textile Research Journal
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• v.6 no.3
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• pp.321-328
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• 2004

The purpose of this study were to investigate the differences of shopping value, promotional affects and product characteristics between buyers and non-buyers, and to examine the most influenced variable on purchasing behaviors of fashion products in CATV home-shopping. We collected data from 595 consumers related to CATV home-shopping in Busan. Data were analyzed by factor analysis, t-test, ${\chi}^2$-test and discriminant analysis. Results showed that there are significant differences between buyers and non-buyers of shopping value demographic characteristics, promotional affects and product characteristics. Especially, shopping value perceived by consumers(e.g., practical value and hedonic value) and product characteristics(e.g., response of others) discriminated whether consumers purchased the fashion products of CATV home-shopping or not. We discussed the implications of results to encourage the purchasing behavior of fashion products in CATV home-shopping.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.4
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• pp.51-58
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• 2016

In the area of hotel and tourism sector, various research are analyzed using big data. Big data is being generated by any digital devices around us all the times. All the digital process and social media exchange produces the big data. In this paper, we analyzed the de-identification method of big data to use the personal information of hotel guests. Through the analysis of these big data, hotel can provide differentiated and diverse services to hotel guests and can improve the service and support the marketing of hotels. If the hotel wants to use the information of the guest, the private data should be de-identified. There are several de-identification methods of personal information such as pseudonymisation, aggregation, data reduction, data suppression and data masking. Using the comparison of these methods, the pseudonymisation is discriminated to the suitable methods for the analysis of information for the hotel guest. Also, among the pseudonymisation methods, the t-closeness was analyzed to the secure and efficient method for the de-identification of personal information in hotel.

• Proceedings of the KIEE Conference
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• 2000.07c
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• pp.1951-1953
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• 2000

Partial Discharge is non-disruptive discharge, which can be discriminated to 3 kinds as firstly, internal discharge which is caused by internal voids inside of insulator, secondly, surface discharge which occurs from the surface of insulator and finally, corona discharge which is from the surface of an electrode. In this thesis, three kinds of defects are artificially made to the inside and the surface of the epoxy resine busing with internal voltage detection sensor, which is practically equipped into SF6 gas insulated switchgear for 22.9kV distribution line, so that discrimination of three kinds of PD signals by means of phi-q-n pattern analysis method was performed.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.1045-1048
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• 2000

This paper presents the application of the wavelet transform analysis and the neural network method to the phonocardiogram (PCG) signal. Heart sound is a acoustic signal generated by cardiac valves, myocardium and blood flow and is a very complex and nonstationary signal composed of many source. Heart sound can be discriminated normal heart sound and heart murmur. Murmurs have broader frequency bandwidth than the normal ones and can occur at random position of cardiac cycle. In this paper, we classified the group of heart sound as normal heart sound(NO), pre-systolic murmur(PS), early systolic murmur(ES), late systolic murmur(LS), early diastolic murmur(ED). And we used the wavelet transform to shorten artifacts and strengthen the low level signal. The ANN system was trained and tested with the back- propagation algorithm from a large data set of examples-normal and abnormal signals classified by expert. The best ANN configuration occurred with 15 hidden layer neurons. We can get the accuracy of 85.6% by using the proposed algorithm.

• Korean Journal of Food Science and Technology
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• v.37 no.5
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• pp.856-860
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• 2005

Electronic-nose system was used to discriminate commercial sesame oils (A-F) extracted from imported seeds. Response (delta $R_{gas}/R_{air}$) of sensors gained from electronic nose was analyzed by principal component analysis (PCA). Flavor pattern of sesame oil A was similar to those of sesame oils B, C, and D. Sesame oils blended with corn oil at the ratio of 95:5, 90:10 and 80:20% (sesame oil/corn oil, w/w) could be discriminated from ouch genuine sesame oil.

• Journal of Life Science
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• v.16 no.4
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• pp.672-675
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• 2006

In order to determine the morphological variations of the Japanese swimming crab, Charybdis japonica, we conducted morphological analysis of five populations that are relatively abundant in Korea and Japan. Abdominal sternite for individuals of the Tean population showed significantly short when compared to those of other populations. Principal component analysis demonstrated that morphological differentiation was due to differences (A/Q, B/M, D/P, F/O, J/K), and effectively discriminated each others. The first two components accounted for 40.9% and 60.7% of the variation, respectively. The dendrogram showed three distinct groups, Tokyo population, Taean population, and the other populations.

• Journal of Environmental Science International
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• v.16 no.11
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• pp.1301-1312
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• 2007

The objective of this study is to propose a critical storm duration forecasting model on storm runoff in small river basin. The critical storm duration data of 582 sub-basin which introduced disaster impact assessment report on the National Emergency Management Agency during the period from 2004 to 2007 were collected, analyzed and studied. The stepwise multiple regression method are used to establish critical storm duration forecasting models(Linear and exponential type). The results of multiple regression analysis discriminated the linear type more than exponential type. The results of multiple linear regression analysis between the critical storm duration and 5 basin characteristics parameters such as basin area, main stream length, average slope of main stream, shape factor and CN showed more than 0.75 of correlation in terms of the multi correlation coefficient.