• Journal of Global Scholars of Marketing Science
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• v.19 no.2
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• pp.17-26
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• 2009

As the lifestyle of consumers changes and the need for various products increases, new products are being developed in the market. Each household owns various home appliances which are purchased through the choice of a decision maker. These appliances include not only large-sized products such as TV, refrigerator, and washing machine, but also small-sized products such as microwave oven and air cleaner. There exists latent correlation among possession of home appliances, even though they are purchased independently. The purpose of this research is to analyze the effect of demographic factors on the purchase and possession of each home appliances, and to derive some relationships among various appliances. To achieve this purpose, the present status on the possession of each home appliances are investigated through consumer survey data on the electric and energy product. And a multivariate probit(MVP) model is applied for the empirical analysis. From the estimation results, some appliances show a substitutive or complementary pattern as expected, while others which look apparently unrelated have correlation by co-incidence. This research has several advantages compared to previous literatures on home appliances. First, this research focuses on the various products which are purchased by each household, while previous researches such as Matsukawa and Ito(1998) and Yoon(2007) focus just on a particular product. Second, the methodology of this research can consider a choice process of each product and correlation among products simultaneously. Lastly, this research can analyze not only a substitutive or complementary relationship in the same category, but also the correlation among products in the different categories. As the data on the possession of home appliances in each household has a characteristic of multiple choice, not a single choice, a MVP model are used for the empirical analysis. A MVP model is derived from a random utility model, and has an advantage compared to a multinomial logit model in that correlation among error terms can be derive(Manchanda et al., 1999; Edwards and Allenby, 2003). It is assumed that the error term has a normal distribution with zero mean and variance-covariance matrix ${\Omega}$. Hence, the sign and value of correlation coefficients means the relationship between two alternatives(Manchanda et al., 1999). This research uses the data of 'TEMEP Household ICT/Energy Survey (THIES) 2008' which is conducted by Technology Management, Economics and Policy Program in Seoul National University. The empirical analysis of this research is accomplished in two steps. First, a MVP model with demographic variables is estimated to analyze the effect of the characteristics of household on the purchase of each home appliances. In this research, some variables such as education level, region, size of family, average income, type of house are considered. Second, a MVP model excluding demographic variables is estimated to analyze the correlation among each home appliances. According to the estimation results of variance-covariance matrix, each households tend to own some appliances such as washing machine-refrigerator-cleaner-microwave oven, and air conditioner-dish washer-washing machine and so on. On the other hand, several products such as analog braun tube TV-digital braun tube TV and desktop PC-portable PC show a substitutive pattern. Lastly, the correlation map of home appliances are derived using multi-dimensional scaling(MDS) method based on the result of variance-covariance matrix. This research can provide significant implications for the firm's marketing strategies such as bundling, pricing, display and so on. In addition, this research can provide significant information for the development of convergence products and related technologies. A convergence product can decrease its market uncertainty, if two products which consumers tend to purchase together are integrated into it. The results of this research are more meaningful because it is based on the possession status of each household through the survey data.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.365-371
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• 2011

Most recently issued paper money includes security patterns that can be only identified by ultra violet (UV) illuminations. We propose an automatic extraction method of UV patterns for paper money inspection systems. The image acquired by camera and UV illumination is transformed to input data through preprocessing. And then, the Gaussian mixture model (GMM) and split-and-merge expectation maximization (SMEM) algorithm are applied to segment the image represented by input data. In order to extract the UV pattern from the segmented image, we develop a criterion using the area of covariance vector and the weight value. The experimental results on various paper money are presented to verify the usefulness of the proposed method.

• Atmosphere
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• v.29 no.4
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• pp.355-365
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• 2019

Based on in-situ monitoring data produced by National Institute of Meteorological Sciences, we evaluated the performance of Joint UK Land Environment Simulator (JULES) on the surface energy balance for rice-paddy and cropland in Korea with the operational ancillary data used for Unified Model (UM) Local Data Assimilation and Prediction System (LDAPS) (CTL) and the high-resolution ancillary data from external sources (EXP). For these experiments, we employed the one-year (March 2015~February 2016) observations of eddy-covariance fluxes and soil moisture contents from a double-cropping rice-paddy in BoSeong and a cropland in AnDong. On the rice-paddy site the model performed better in the CTL experiment except for the sensible heat flux, and the latent heat flux was underestimated in both of experiments which can be inferred that the model represents flood-irrigated surface poorly. On the cropland site the model performance of the EXP experiment was worse than that of CTL experiment related to unrealistic surface type fractions. The pattern of the modeled soil moisture was similar to the observation but more variable in time. Our results shed a light on that 1) the improvement of land scheme for the flood-irrigated rice-paddy and 2) the construction of appropriate high-resolution ancillary data should be considered in the future research.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.36 no.6
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• pp.646-653
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• 2003

Investigations were made on the population structure, sex ratio, growth, and recruitment patterns of Leptochela sydniensis in the southwestern coastal areas of Korea, between May 2000 and December 2001. Spawning period, fecundity, brood loss, reproductive output, and size at sexual maturity also were examined. The results of the sex ratio showed that females were more numerous than males during the overall study period. Parameters of growth were estimated using the modified von Bertalanffy growth function (VBGF) model incorporating seasonal variation into growth. Females grew somewhat faster and reached a larger size than males $(L\infty=12.80\;mm\;CL\;and\;K=0.70\;yr^{-1}\;or\;females,\and\;L\infty=12.08\;mm\;CL\;and\;K=0.69\;yr^{-1}$ for males). The structure of recruitment patterns obtained by the FiSAT program indicated one normally distributed group. Based on the occurrence of ovigerous females and the gonadosomatic index (GSI), the main spawning season was from June to August. Analysis of covariance indicated that brood loss was not observed during the incubation period. The size at which $50\%$ of females are mature is estimated as 5.48 mm CL.

• Journal of Korean Academy of Nursing
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• v.30 no.1
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• pp.148-159
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• 2000

The purpose of this study was to test the theoretical model designed to explain juvenile delinquency by media violence. Data were collected through questionnaire survey over a period of 3 months. Subjects served for this study consisted of 537 adolescents including 217 delinquent adolescents and 320 student adolescents in Korea, sampled from Korean student population and delinquent adolescent population confined in juvenile correctional institutions, using proportional stratified random sampling method. In this study, exogeneous variable was family dynamic environment and endogeneous variables were character of adolescent including need satisfaction/ frustration, sociability, antisocial personality tendency, complaints of psychosomatic symptoms and depressive trend, juvenile delinquent behavior and media violence themes including the extent of interest in and exposure and modelling impulsiveness and modelling to media violence themes. A total of 18 instruments were used to operationalized concepts in this model. A validation study indicated that internal consistencies for the 18 instruments which the researcher used were reliable. The one month test-retest correlation for these instruments ranged from 0.54 to 0.88. Statistical methods employed were descriptive statistics and covariance structural modelling. In summarized conclusion, it was found that media violence served as the most contributor to juvenile delinquency by direct effect of 0.64(t=10.18). That is, as the adolescents have to be the higher extent of interest in and exposure and modelling impulsiveness and modelling to media violence themes, they will show the more frequency of delinquent behavior. The single most powerful contributor by total effect of 0.73(t=7.90) (direct effect=0.19, indirect effect=0.54) to the development of delinquent behavior identified in this study was a construct defining family dynamic environment. That is, as the adolescents had to be more unstable family dynamic environment, they became more frustrated to their psychological need, and revealed the more maladaptive personality pattern, consequently they behaved the higher misconducts such as juvenile delinquency through media violence.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.519-527
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• 2003

Speech is much influenced by the existence of outliers which are introduced by such an unexpected happenings as additive background noise, change of speaker's utterance pattern and voice detection errors. These kinds of outliers may result in severe degradation of speaker recognition performance. In this paper, we proposed the GMM based on robust principal component analysis (RPCA-GMM) using M-estimation to solve the problems of both ouliers and high dimensionality of training feature vectors in speaker identification. Firstly, a new feature vector with reduced dimension is obtained by robust PCA obtained from M-estimation. The robust PCA transforms the original dimensional feature vector onto the reduced dimensional linear subspace that is spanned by the leading eigenvectors of the covariance matrix of feature vector. Secondly, the GMM with diagonal covariance matrix is obtained from these transformed feature vectors. We peformed speaker identification experiments to show the effectiveness of the proposed method. We compared the proposed method (RPCA-GMM) with transformed feature vectors to the PCA and the conventional GMM with diagonal matrix. Whenever the portion of outliers increases by every 2%, the proposed method maintains almost same speaker identification rate with 0.03% of little degradation, while the conventional GMM and the PCA shows much degradation of that by 0.65% and 0.55%, respectively This means that our method is more robust to the existence of outlier.

• Journal of the Korean Geographical Society
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• v.49 no.5
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• pp.761-778
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• 2014

There has been relatively little study to model price for commercial property because of its low transaction volume in the market. Despite of this thin market character, this paper tried to estimate prices for commercial lots as accurate as possible. We constructed a model whose components consist of mean structure(global trend), exponential covariance function and a pure error term, and applied it to actual sales price data of Seoul. We explicitly took account of spatial autocorrelation of land price by utilizing a kriging technique, a representative method of spatial interpolation, because the land price of commercial lots has feature of differential price forming pattern depending on submarkets they belong to. In addition, we chose to apply a bayesian kriging to overcome data scarcity by incorporating experts' knowledge into prior probability distribution. The chosen model's excellent performance was verified by the result from validation data. We confirmed that the excellence of the model is attributed to incorporating both autocorexperts' knowledge and spatial autocorrelation in the model construction. This paper is differentiated from previous studies in the sense that it applied the bayesian kriging technique to estimate price for commercial lots and explicitly combined experts' knowledge with data. It is expected that the result of this paper would provide a useful guide for the circumstances under which property price has to be estimated reliably based on sparse transaction data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.10
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• pp.7126-7137
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• 2015

This study explored the quality of nursing services in relation to a nurse's psychosocial factors (type A behavior pattern, self-esteem, locus of control, and anxiety), job stress, and fatigue. This study targeted 503 nurses who currently work at six different general hospitals in Daejeon city, The data was collected by self-administered questionnaire which was surveyed from April 1 to June 30, 2014. As the result of analysis of covariance, psychosocial factors affect the quality of nursing services more than job stress or fatigue. In addition to that, as parts of psychosocial factors, high self-esteem and low fatigue, job stress, and anxiety increase the quality of nursing services. The research above implies that the quality of nursing services of nurses who work at the general hospital has a correlation with not only the psychosocial factors but also job stress, and fatigue.

• Korean Journal of Social Welfare
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• v.36
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• pp.199-228
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• 1998

This study is designed to find out the determinants of dual-earner wives' needs for family-supportive services. For this purpose, a hypothetical model which explains the relationships among 6 stressors, role overload, stress and needs for 4 family-supportive services is developed. Using the data collected by purposive sampling from 234 professional women and 208 blue-collar women living in Chinju and Sacheon, the hypothetical model developed in this study was tested. In order to examine occupational class differences, a model for professionals and another model for blue-collars were developed separately and compared. For data analysis, a covariance structure analysis was used. The best-fitting model for professional women (df=141, GFI=0.928, CFI=0.965) and the model for blue collar women (df=141, GFI=0.902, CFI=0.912) were found. As a result of comparing two models, 9 common relationships were found:l)Greater dissatisfaction with child care service increases role overload; 2)Longer work hours increases role overload; 3) Higher level of role overload increases stress; 4)Higher level of stress increase needs for leaves; 5)Older child increases needs for flexible work pattern; 6)Younger child increases needs for finalcial assistance for child care fee; 7)needs for financial assistance for child care increases needs for on-site child care services; 8)needs for on-site child care services increases needs for leaves; 9)needs for leaves increases needs for flexible work pattern. With the exception of these 9 common relationships, the analyses revealed substantial differences between professional and blue-collar dual-earner wives. Based on the common and differential needs between 2 groups of wives, the effective ways to provide family-supportive services according to the needs of individual dual-earner wives who are in different familial, financial, and work conditions were suggested.

• Management & Information Systems Review
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• v.32 no.4
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• pp.189-207
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• 2013

Using high-frequency data for 2 years, this study investigates intraday lead-lag relationship between stock index and stock index futures markets in Korea and China. We found that there are some differences in price discovery and volatility transmission between Korea and China after the stock index futures markets was introduced. Following Stoll-Whaley(1990) and Chan(1992), the multiple regression is estimated to examine the lead-lag patterns between the two markets by Newey-West's(1987) heteroskedasticity and autocorrelation consistent covariance matrix(HAC matrix). Empirical results of KOSPI 200 shows that the futures market leads the cash market and weak evidence that the cash market leads the futures market. New market information disseminates in the futures market before the stock market with index arbitrageurs then stepping in quickly to bring the cost-of-carry relation back into alignment. The regression tests for the conditional volatility which is estimated using EGARCH model do not show that there is a clear pattern of the futures market leading the stock market in terms of the volatility even though controlling nonsynchronous trading effects. This implies that information in price innovations that originate in the futures market is transmitted to the volatility of the cash market. Empirical results of CSI 300 shows that the cash market is found to play a more dominant role in the price discovery process after the Chinese index started a sharp decline immediately after the stock index futures were introduced. The new stock index futures markets does not function well in its price discovery performance at its infancy stage, apparently due to high barriers to entry into this emerging futures markets. Based on EGAECH model, the results uncover strong bi-directional dependence in the intraday volatility of both markets.