• Journal of the Society of Cosmetic Scientists of Korea
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• v.33 no.2
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• pp.117-126
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• 2007

This study investigated the effect of the price and brand name on the consumer's evaluation of cosmetics. 363 women from 20's to 50's living in Seoul and the metropolitan area were asked to use and describe the given samples of cosmetic products for one week with different information of price and brand name. The results of this study are as follows: First, the assessment of the facial toner, moisturizer and cream does not show a significant statistical difference between the group of 'renowned' and 'renownless'. Second, the assessment of the facial toner, moisturizer, and cream shows a significant statistical difference between the user groups which received the prior information whether the cosmetics are 'high price' or 'low price'. Third, the assessment of the users' satisfaction of the 3 kinds of cosmetic products mentioned above is influenced by 'renown' an 'price'. Finally, the interaction of the factor 'renown' and 'price' influences on the cosmetics' effectiveness significantly. From this study, it was discovered that the evaluation and the degree of satisfaction on cosmetics were influenced by the price and brand names. This will improve the understanding of consumers' behavior and personal decision-making, which in be the key of marketing strategy.

• 대한공업교육학회지
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• v.41 no.2
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• pp.1-23
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• 2016

This study was conducted to analyze the effect Meister high school students' career maturity with respect to the impact on school maladjustment. Also, this study clarify the relationship. This study purpose is to permanently provide Meister as the basis for the vocational education sector career education needed to faithfully serve as a special purpose high schools. Tools used for the survey is maladaptive measurement tools developed by Leegyumi (2004) and Career maturity measurement tools developed at Korea Research Institute for Vocational Education and Training (2012). Using these tools, a reliability test was conducted. Meister students' career maturity was conducted correlation analysis and multiple regression analysis to analyze the impact of school maladjustment. Independent variables are consisted of career maturity and independence, attitude toward the job, planning, self-understanding, rational decision-making, information retrieval, knowledge of the desired job, career exploration and ready for action. Meister high school student's career maturity according to the students' background variables are little girls was higher than boys, but it was not statistically significant. T-test was conducted to ascertain the career maturity and school maladjustment differences of adaptation groups and maladaptive group in meister school students in background variables. A career maturity and school maladjustment between adaptive and maladaptive population groups showed a statistically significant difference in background variables.

• Korean Journal of Environment and Ecology
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• v.17 no.3
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• pp.285-294
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• 2003

The purpose of this paper is to provide useful knowledge for recreation management in natural park(NP) by evaluating use suitability of recreation resource. We had obtained data through a questionnaire, which surveyed 385 visitors at 6 of the 73 NP in Korea in 2001, based on stratified sampling method. We have analyzed the data using the multiple regression method. We found that 1) in bivariate analysis, the relationships between use suitability and all the recreation resources are fairly high and statistically significant. The higher the degree of recreation resources, the higher the degree of use suitability. 2) in multivariate analysis, topography, social resource(SR), cultural resource(CR), landscape, smell, color and sound(SCS) have been turned out to be statistically significant at one percent level. 3) the direction of relationship between topography, SR, CR, landscape, SCS and use suitability is same. 4) in relative contribution of the use suitability of recreation resource, level of topography has been turned out to have about 1.05, 1.56, 2.16 and 2.70 times more important than that of SCS, SR, landscape, topography, respectively This results will be used for a criterion for recreation resource evaluation and a settlement of management priority and increasing user's satisfaction.

• Food Science and Preservation
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• v.18 no.4
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• pp.527-534
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• 2011

The purpose of this studies was analyzed moisture content, rheology and sensual test of jujube jungkwa by addition of water, sugar, fructose at processing of jujube jungkwa for development the optimization for processing of jujube jungkwa. The changes of moisture contents at process condition of jujube jungkwa were increased by increasing of sugar and water quantity. And moisture contents of jujube jungkwa were increased by high fructose quantity and low sugar quantity, but were decreased by high sugar and fructose quantity. The 'b' values of jujube jungkwa at low sugar quantity were decreased by the increasing of water quantity, but increased at high sugar quantity. The cohesiveness of jujube jungkwa at 0.03 kg of fructose were high by the increasing of sugar quantity, but those at 0.065 kg of fructose were high by the decreasing of sugar quantity. And those at 0.050 kg of fructose were similar without the quantity of sugar. The sweet taste of jujube jungkwa were increased by the increasing of water and fructose quantity. The characteristics of jungkwa at conditions of processing for the best quality of jujube jungkwa were 18-20% of moisture content, 2.0-3.0 of 'b' values, 3.0-3.2 of color scores, and 3.3-3.4 of sweet taste scores. The conditions of processing for the best quality of jujube jungkwa were determined to 0.95-1.04 L of water, 0.052-0.060 kg of fructose at 0.95 kg of sugar.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.126-132
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• 2015

Technology forecasting is about understanding a status of a specific technology in the future, based on the current data of the technology. It is useful when planning technology management strategies. These days, it is common for countries, companies, and researchers to establish R&D directions and strategies by utilizing experts' opinions. However, this qualitative method of technology forecasting is costly and time consuming since it requires to collect a variety of opinions and analysis from many experts. In order to deal with these limitations, quantitative method of technology forecasting is being studied to secure objective forecast result and help R&D decision making process. This paper suggests a methodology of technology forecasting based on quantitative analysis. The methodology consists of data collection, principal component analysis, and technology forecasting by logistic regression, which is one of the data mining techniques. In this research, patent documents related to autonomous vehicle are collected. Then, the texts from patent documents are extracted by text mining technique to construct an appropriate form for analysis. After principal component analysis, logistic regression is performed by using principal component score. On the basis of this result, it is possible to analyze R&D development situation and technology forecasting.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.15-28
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• 2015

As personal devices and pervasive technologies for interacting with networked objects continue to proliferate, there is an unprecedented world of scattered pieces of contextualized information available. However, the explosive growth and variety of information ironically lead users and service providers to make poor decision. In this situation, recommender systems may be a valuable alternative for dealing with these information overload. But they failed to utilize various types of contextual information. In this study, we suggest a methodology for context-aware recommender systems based on the concept of contextual boundary. First, as we suggest contextual boundary-based profiling which reflects contextual data with proper interpretation and structure, we attempt to solve complexity problem in context-aware recommender systems. Second, in neighbor formation with contextual information, our methodology can be expected to solve sparsity and cold-start problem in traditional recommender systems. Finally, we suggest a methodology about context support score-based recommendation generation. Consequently, our methodology can be first step for expanding application of researches on recommender systems. Moreover, as we suggest a flexible model with consideration of new technological development, it will show high performance regardless of their domains. Therefore, we expect that marketers or service providers can easily adopt according to their technical support.

• The Korean Journal of Applied Statistics
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• v.30 no.1
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• pp.41-55
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• 2017

This study predicts the average scores of top 150 PGA golf players on 132 PGA Tour tournaments (2013-2015) using data mining techniques and statistical analysis. This study also aims to predict the Top 10 and Top 25 best players in 4 different playoffs. Linear and nonlinear regression methods were used to predict average scores. Stepwise regression, all best subset, LASSO, ridge regression and principal component regression were used for the linear regression method. Tree, bagging, gradient boosting, neural network, random forests and KNN were used for nonlinear regression method. We found that the average score increases as fairway firmness or green height or average maximum wind speed increases. We also found that the average score decreases as the number of one-putts or scrambling variable or longest driving distance increases. All 11 different models have low prediction error when predicting the average scores of PGA Tournaments in 2015 which is not included in the training set. However, the performances of Bagging and Random Forest models are the best among all models and these two models have the highest prediction accuracy when predicting the Top 10 and Top 25 best players in 4 different playoffs.

• Land and Housing Review
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• v.4 no.3
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• pp.225-234
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• 2013

The indices to choose the object countries for developing overseas industrial park were developed and applied in this paper. The results are showing as follows. First, the Korean enterprises are branched out into total 128 countries as of the first quarter of 2010, and the 13 asian countries including China, Vietnam, Japan, and Hongkong shows the majority of precedence 20 countries among the reported during 1980-2010. Second, the 3 steps of selecting the principal region to branch out, establishing assessment indices and criteria, and choosing strategical target counties were developed to choose the countries for developing overseas industrial park. The 38 of 128 countries were selected where the GDP per capita is lower than Korea, and the local reports of incorporation during 2007-2010 are more than 10 times. Then, the 10 countries were excluded where the minimum wages during 2008-2009 are similar to Korean ($815/month). Consequently, the 28 countries including China, Vietnam, and Cambodia etc. were selected as the major target regions. Third, the indices to choose countries for developing overseas industrial park are classified into 5 categories-investment condition, labor market flexibility, potential market demand, population, changing rate of the reported number of manufacturing industry, and detailed indices for each category were selected, then the weight were given with the consideration of importance. Finally, Indonesia, Mongolia, and Uzbekistan were selected as the strategical target counties where acquire the high score in labor market flexibility and investment condition, relatively undeveloped, and friendly to Korea.

• Information Systems Review
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• v.17 no.3
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• pp.95-111
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• 2015

The recommendation system automatically provides the predicted items which are expected to be purchased by analyzing the previous customer behaviors. This recommendation system has been applied to many e-commerce businesses, and it is generating positive effects on user convenience as well as the company's revenue. However, there are several limitations of the existing recommendation systems. They do not reflect specific criteria for evaluating products or the factors that affect customer buying decisions. Thus, our research proposes a collaborative recommendation model algorithm that utilizes each customer's online product reviews. This study deploys topic modeling method for customer opinion mining. Also, it adopts a kernel-based machine learning concept by selecting kernels explaining individual similarities in accordance with customers' purchase history and online reviews. Our study further applies a multiple kernel learning algorithm to integrate the kernelsinto a combined model for predicting the product ratings, and it verifies its validity with a data set (including purchased item, product rating, and online review) of BestBuy, an online consumer electronics store. This study theoretically implicates by suggesting a new method for the online recommendation system, i.e., a collaborative recommendation method using topic modeling and kernel-based learning.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.7
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• pp.143-152
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• 2015

The 'Quality Competitiveness Index' (QCI) is defined as an quantitative and disinterested indicator that measures and compares the quality of products across the world. The purpose of this study is to suggest the 'Quality Competitiveness Assessment Model' (QCAM) and calculate QCI of a popular UHF RFID Label tag (Global ISO 18000-3C supported) available these days in a global apparel market. The model was based on KS-QEI(Korean Standard-Quality Excellence Index), and was composed with the following 4 evaluation categories, a process capability test, an environmental reliability test, a durability test and a design margin test. The QCI score can be calculated with the following formula, using the weighted arithmetic mean between a score of each evaluation category ($X_1$, $X_2$, $X_3$, $X_4$) and each weight($w_1$, $w_2$, $w_3$, $w_4$). The actual weights was determined by an result of AHP survey to which was conducted for the related Industry-University-Institute experts. The proposed index shows the results of comparisons with global competitor's products as well as the high-quality domestic RFID label tags. In addition, it will play an important role for manufacturers when developing their future products.