• The Korean Journal of Applied Statistics
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• v.11 no.1
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• pp.141-150
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• 1998

In this paper, we developed one-stage cluster randomized response model for obtaining quantitative data by using the Greenberg et al. model(1971) when the population was made up of sensitive quantitative clusters. We obtained the minimum variance by calculating the cluster's size and the optimum number of sample clusters under the some given constant cost. We compared the efficiency of our model with the Greenberg et al. model by simple random sampling.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1468-1480
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• 1999

In database systems, join operations are the most complex and time consuming ones which limit performance of such system. Many parallel join algorithms have been proposed for the systems. However, they did not consider data skew, such as attribute value skew (AVS) and join product skew (JPS). In the skewness environments, performance of framework for a uniform load distribution and an efficient parallel join algorithm using the framework to handle AVS and JPS. In our algorithm, we estimate data distributions of input and output relations of join operations using the sampling methodology and evaluate join cost for the estimated data distributions. Finally, using the histogram equalization method we distribute data among nodes to achieve good load balancing among nodes in the local joining phase. For performance comparison, we present simulation model of our algorithm and other join algorithms and present the result of some simulation experiments. The results indicate that our algorithm outperforms other algorithms in the skewed case.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.3
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• pp.1832-1843
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• 2015

Recently, since the "Capital Market Consolidation Act" has been effective in 2009, the competition among the securities companies in Korean security market has been fierce. Thus, securities business lately are needed by the market environmental requirements rapidly changed for various strategies. The purpose of this study was to identify the effect of corporate attribute, employee attribute, financial product attribute securities on customer satisfaction, trust with the firm, and usage intention. As the subjects I selected the customer of securities in Seoul in 2014 and conducted survey with questionnaires. Among total 400, I chose 378 as the valid sample by convenience sampling. For the data process, I used SPSS 20.0 I verified the perspective hypotheses after testing reliability and validity of fit by the data process. The results are as following. First, it was shown that the sub-factors of corporate attribute, employee attribute, financial product attribute in securities as ethics, innovation, size, kind, professionalism, ethics, profitability and diversity had significant effect on usage intention. Second, the study confirms that reliability and satisfaction influences customer loyalty as moderate variable. The industrial and academic significance of this study is that it may serve as a useful base date to understand customer behavior and draw new strategies in a financial management environment.

• Journal of the Korean Society of Clothing and Textiles
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• v.17 no.1
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• pp.3-10
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• 1993

This study intends to provide a beneficial foundation which can aid our understanding of how a clothing consumer group can be classified according to the clothing buying motives, and what differences are there about the importances store image attribute among them and how consumer's preferences to the store image are shown differently among them and ultimately, some concrete data which can be useful in establishing efficient store image strategies for clothing stores. 484 subjects were gathered through convenience sampling method and, for data analysis, cronbach' ${\alpha}$, frequency, percentage, mean, ${\chi}^2$-text, t-test, ANOVA, Duncan Multiple Range Test, Factor Analysis, Cluster Analysis were conducted. the results are as follows; 1. three kind of factors in the clothing buying motives were determined for analysis of consumers group and by which it was revealed as to be significant for us to classify them three subdivisions; those of fashion pursuit group, self display group, financial utilitarian group. 2. Importance on store image attribute was revealed that Ewha students regarded quality, price, more important factors than others. 3. Store image preferences show significantly when concerned with quality, price, fashion, impression and age of store personnel, convenience for exchanging and returning goods, credit, delivery and repair, mailing of catalogue and discount coupon, bightness of store among consumer groups.

• The Korean Journal of Community Living Science
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• v.22 no.3
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• pp.327-339
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• 2011

This study aims to investigate relationships between benefit sought and selection attributes of green tea consumers. For data collection, a total of 595 copies of questionnaires were collected by convenience sampling in the Seoul and Gyeonggi-do area. The data were analyzed by using SPSS 15.0. The factor analysis identified four dimensions of the benefit sought : health benefit, sensory, sociality, and self-esteem. Six dimensions of selection attributes were identified as manufacturing, design, sensory appeal, recommendation, utility and brand. The results of the canonical correlation analysis indicated that health benefit, sensory, sociality of benefit sought and manufacturing, design, sensory appeal, recommendation, utility, brand of selection attributes were highly correlated, and the self-esteem of benefit sought and recommendation of selection attribute were highly correlated. This means it is important to place an emphasis on safety production, package design, sensory characteristics, product description, utility and brand for consumers who seek health benefit, flavor and sociality. It is also important to place an emphasis on product description for consumers who pursue self-esteem benefits. Green tea marketers should consider benefit sought aspects as the most important factors affecting selection attributes on green tea purchasing.

• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1322-1329
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• 2023

This study attempted to verify how the selection attribute affects customer satisfaction and participation intention to provide basic data for the efficient operation strategy of domestic futsal fields. Therefore, people who used domestic futsal fields were selected as samples, and convenience sampling methods were used. The final analysis used 271 copies of data. The data processing was conducted with the SPSS (ver. 21.0) program, which conducted frequency analysis, factor analysis and reliability analysis, correlation analysis, simple and multiple regression analysis. First, the results of the study showed that domestic futsal field selection attributes had a significant impact on customer satisfaction in the order of service, convenience, price, and facility. Second, customer satisfaction had a significant effect on participation intention. Third, the optional attributes had a significant impact on participation intention in the order of facility, service, convenience, and price. Summarizing the above results, it is believed that domestic futsal courts need to provide facilities and services that allow consumers to enjoy futsal games more conveniently and safely.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.10
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• pp.5015-5038
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• 2018

In this paper, a novel spectral-spatial joint sparse representation algorithm for hyperspectral image classification is proposed based on multi-layer superpixels in various scales. Superpixels of various scales can provide complete yet redundant correlated information of the class attribute for test pixels. Therefore, we design a joint sparse model for a test pixel by sampling similar pixels from its corresponding superpixels combinations. Firstly, multi-layer superpixels are extracted on the false color image of the HSI data by principal components analysis model. Secondly, a group of discriminative sampling pixels are exploited as reconstruction matrix of test pixel which can be jointly represented by the structured dictionary and recovered sparse coefficients. Thirdly, the orthogonal matching pursuit strategy is employed for estimating sparse vector for the test pixel. In each iteration, the approximation can be computed from the dictionary and corresponding sparse vector. Finally, the class label of test pixel can be directly determined with minimum reconstruction error between the reconstruction matrix and its approximation. The advantages of this algorithm lie in the development of complete neighborhood and homogeneous pixels to share a common sparsity pattern, and it is able to achieve more flexible joint sparse coding of spectral-spatial information. Experimental results on three real hyperspectral datasets show that the proposed joint sparse model can achieve better performance than a series of excellent sparse classification methods and superpixels-based classification methods.

• Industrial Engineering and Management Systems
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• v.15 no.3
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• pp.231-238
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• 2016

Traditional acceptance sampling plans have focused on the proportion of nonconforming items as an attribute criterion for quality. In today's modern quality management under high quality production environments, the reduction of the deviation from a target value in a quality characteristic has become the most important purpose. In consequence, various inspection plans for the purpose of reducing the deviation from the target value in the quality characteristic have been investigated. In this case, a concept of the quality loss evaluated by the deviation from the target value has been accepted as the variable evaluation criterion of quality. Further, some quality measures based on the quality loss have been devised; e.g. the process loss and the process capability index. Then, as one of inspection plans based on the quality loss, the rigorous design procedure for the variable sampling plan having desired operating characteristics (VS-OC plan) indexed by the quality loss has been proposed by Yen and Chang in 2009. By the way, since the estimator of the quality loss obeys the non-central chi-square distribution, the rigorous design procedure for the VS-OC plan indexed by the quality loss is complicated. In particular, the rigorous design procedure for the VS-OC plan requires a large number of the repetitive and complicated numerical calculation about the non-central chi-square distribution. On the other hand, an approximate design procedure for the VS-OC plan has been proposed before the proposal of the above rigorous design procedure. The approximate design procedure for the VS-OC plan has been constructed by combining Patnaik approximation relating the non-central chi-square distribution to the central chi-square distribution and Wilson-Hilferty approximation relating the central chi-square distribution to the standard normal distribution. Then, the approximate design procedure has been devised as a convenient procedure without complicated and repetitive numerical calculations. In this study, through some comparisons between the rigorous and approximate design procedures, the applicability of the approximate design procedure has been confirmed.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.89-96
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• 2016

By reviewing preceding studies of big data and spatial big data, spatial big data was defined as one part of big data, which spatialize location information and systematize time series data. Spatial big data, as one part of big data, should not be separated with big data and application methods within the system is to be examined. Therefore in this study, services that spatial big data is required to provide were suggested. Spatial big data must be available of various spatial analysis and is in need of services that considers present and future spatial information. Not only should spatial big data be able to detect time series changes in location, but also analyze various type of big data using attribute information of spatial data. To successfully provide the requirements of spatial big data and link various type of big data with spatial big data, methods of forming sample points and extracting attribute information were proposed in this study. The increasing application of spatial information related to big data is expected to attribute to the development of spatial data industry and technological advancement.

• Journal of Digital Contents Society
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• v.16 no.2
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• pp.283-290
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• 2015

This study focused on SNS use of Chinese students who are studying in Korea. Communication media like SNS is strongly related with socialization of foreigners. Thus, it is expected to verify relationship between current SNS use tendency of Chinese students and their settlement in Korea based on analysis on the factor influencing SNS use of Chines students. For the study on the factor influencing to SNS use of Chinese students in Korea TAM model was used as a research frame. Based on TAM theory technological attribute, individual attribute and social attribute were taken out as independent variables. Perceived ease of use and perceived usefulness are applied as mediator variables. In research conclusion, some hypotheses are adopted the same as existing theory, but some hypotheses for example service quality and individual attribute are rejected as variables which influence positively to mediator variable perceived easy of use. For the next research more various variables and nationwide sampling will be needed. Based on this research it is expected to be analysed correlation between foreigners settlement in Korea and communication media like SNS.