• Journal of Information Processing Systems
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• v.4 no.1
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• pp.27-32
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• 2008

Minimum support and confidence have been used as criteria for generating association rules in all association rule mining algorithms. These criteria have their natural appeals, such as simplicity; few researchers have suspected the quality of generated rules. In this paper, we examine the rules from a more rigorous point of view by conducting statistical tests. Specifically, we use contingency tables and chi-square test to analyze the data. Experimental results show that one third of the association rules derived based on the support and confidence criteria are not significant, that is, the antecedent and consequent of the rules are not correlated. It indicates that minimum support and minimum confidence do not provide adequate discovery of meaningful associations. The chi-square test can be considered as an enhancement or an alternative solution.

• Journal of Engineering Education Research
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• v.25 no.4
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• pp.35-41
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• 2022

In order to enhance basic competencies for freshmen at engineering college, whose learning ability is gradually declining, a new course was developed to review basic mathematics and physics through a process of collecting opinions from fellow professors. Tests in six fields of math and physics with the same problems showed the correct answer rate rose from 24.8% at the beginning of the semester to 59.0% at the end of the semester after operating the course developed. According to the survey, the students' self-evaluated confidence on the basic competencies in 16 fields of math and physics showed a significant increase. Students with high confidence in basic competencies also received high actual grades. General high school graduates' confidence point in basic competencies improved from 54.7 at the beginning to 75.3 points at the end of the semester, while specialized high school graduates' enhanced from 38.3 to 64.0 which is higher than that of general high school graduates at the beginning of the semester.

• Journal of the Korean Home Economics Association
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• v.44 no.9
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• pp.51-59
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• 2006

The role of consumer self-confidence is important in consumer's purchase decision. Nevertheless, the use of self-esteem measures might cause misinformation in the specific situation of the marketing-related point of view. In this study, consumer self-confidence was measured by marketing oriented tools to clarify the dimensions of consumer self-confidence while the influence of consumer self-confidence on clothing satisfaction was also investigated. A total of 325 questionnaires were collected by surveying university students in Seoul and the surrounding metropolitan area using convenient sampling. The data were analysed by factor analysis, ANOVA, t-test, and regression by using SPSSWIN program. The findings of the study were as fellows. First, the consumer self-confidence was composed of 6 sub-scales: information acquisition, personal outcomes decision making, social outcomes decision making, consideration-set formation, persuasion knowledge, and marketplace interfaces. Second, female subjects rated higher on consumer self-confidence than male subjects did in social outcomes decision making and consideration-set formation. Third, higher income was correlated with higher social outcomes decision making and consideration-set formation. Finally, clothing satisfaction was influenced by personal outcomes decision making and information acquisition.

• Journal of Distribution Science
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• v.12 no.2
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• pp.81-93
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• 2014

Purpose - Recent rapid environmental changes in the hospital industry are accelerating the spread of customer satisfaction management. Customers' desires have become diversified and advanced; in the past, customers tended to preferred popularized and standardized care, whereas they now prefer individualized and differentiated care, based on an increase in income. Specifically, this study tries to analyze the mediating effects of factors that affect the configuration portion of customer value and relationship quality (customer trust and relationship commitment) by investigating the impacts and configuration factor of customer value on relationship quality and determining how these factors impact customer loyalty directly or indirectly. Research design, data, and methodology - This study aims to determine the customer value factors that impact the perceptions of dental hospital customers, how these factors impact relationship quality and customer loyalty, and the causal relationship of these factors, and to verify the research model based on previous research. To increase the validity and reliability of the questionnaire, the authors of this study constructed basic questions using measurement tools already verified for reliability and validity in existing studies. In this study, customer value is defined as customers' recognizing value by exchanging goods or services and is measured using a five-point Likert scale using 19 questions about the 4-Ds, such as convenience value, quick service, response value, and trustworthiness. For each question, "very low" was set at 1 point and "very high" at 5 points. Customer trust, relationship commitment, and customer loyalty are also measured using a five-point Likert 5-point scale (1 = very low, 5 = very high) based on previous studies. Results - For customer value, trustworthiness and quick service are shown to have direct significant positive impacts on customer loyalty. For customer value and quality of the relationship (customer confidence and commitment), trustworthiness, response value, confidence value, and quick service are shown to have a significant positive impact on customer truth, in order of impact. For the relationship between customer value and commitment, quick service and response value are shown to have significant positive impact. Customer confidence has a very high positive influence on commitment. For the relationship between the quality of the relationship (customer confidence and commitment) and customer loyalty, customer confidence is shown to have more of an impact than commitment, in terms of a direct influence of customer loyalty. Commitment showed a positive impact on customer loyalty. For the relationship between customer confidence and customer loyalty, commitment showed a mediating effect. Conclusions - Many additional variables could apply; this study focused on customer value, quality of the relationship, and customer loyalty. In particular, there will be significant value in identifying the relationships among customer value, relationship quality, and customer loyalty by using impact factors for customer value; ensuring external validity by expanding denotation and applying the findings to other service industries; and undertaking continuous research. This study has limited generalization potential because the target for this survey was located only in the Seoul area.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.533-537
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• 2005

A Likert scale is an often used questionnaire format. It requests respondents to specify their level of agreement to each of a list of statements. A typical question using a five-point Likert scale might make a statement. The results shows vague values. We have five-point fuzzy membership function by fuzzy valued three-point for the question and fuzzy hypothesis test the membership function by 95% confidence interval.

• Communications for Statistical Applications and Methods
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• v.18 no.4
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• pp.445-455
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• 2011

Although misclassified binary data occur frequently in practice, the statistical methodology available for the data is rather limited. In particular, the interval estimation of population proportion has relied on the classical Wald method. Recently, Lee and Choi (2009) developed a new confidence interval by applying the Agresti-Coull's approach and showed the efficiency of their proposed confidence interval numerically, but a theoretical justification has not been explored yet. Therefore, a Bayesian model for the misclassified binary data is developed to consider the Agresti-Coull confidence interval from a theoretical point of view. It is shown that the Agresti-Coull confidence interval is essentially a Bayesian confidence interval.

• Genomics & Informatics
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• v.18 no.3
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• pp.31.1-31.8
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• 2020

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a global pandemic. No specific therapeutic agents or vaccines for COVID-19 are available, though several antiviral drugs, are under investigation as treatment agents for COVID-19. The use of convalescent plasma transfusion that contain neutralizing antibodies for COVID-19 has become the major focus. This requires mass screening of populations for these antibodies. While several countries started reporting population based antibody rate, its simple point estimate may be misinterpreted without proper estimation of standard error and confidence intervals. In this paper, we review the importance of antibody studies and present the 95% confidence intervals COVID-19 antibody rate for the Korean population using two recently performed antibody tests in Korea. Due to the sparsity of data, the estimation of confidence interval is a big challenge. Thus, we consider several confidence intervals using Asymptotic, Exact and Bayesian estimation methods. In this article, we found that the Wald method gives the narrowest interval among all Asymptotic methods whereas mid p-value gives the narrowest among all Exact methods and Jeffrey's method gives the narrowest from Bayesian method. The most conservative 95% confidence interval estimation shows that as of 00:00 on September 15, 2020, at least 32,602 people were infected but not confirmed in Korea.

• Journal of Korean Society on Water Environment
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• v.26 no.2
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• pp.297-302
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• 2010

It is very important to know mean and confidence interval of water-quality constituents such as BOD for water-quality control and management of rivers and reservoirs effectively. The mean and confidence interval of BOD at Anseong2 and Hwangguji3 sampling stations which are located at the border of local governments in Anseong Stream were estimated and analyzed in this paper using Bootstrap technique which is one of non-parametric statistics. The results of Bootstrap were compared with arithmetic mean, geometric mean, Biweight method mean as a point estimator and distribution mean came from the appropriate probability distribution of Log-normal. In Bootstrap technique 12 data set was randomly selected in each year and 1000 samples was produced to get parameter of population. Visual Basic for Applications (VBA) of Microsoft Excel was utilized in Bootstrap. It was revealed that the Bootstrap technique can be used to explain more rigorously and robustly the achievement or violation of BOD target concentration in Total Maximum Daily Load (TMDL).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.87-91
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• 2004

This paper dealt with FMEA, Which is a method of the analysis to secure safety and confidence coming up to customer's expectation in consideration of the environment of the corporation, the industrial environment, and the functional improvement. And by using FMEA, We showed the example analyzed the confidence of the reduction gear. It was proved by the result of the analysis that the rate of the breakdown which is usually regarded as the first important point to reform can't satisfy the selecting basis to improve. Also the result said that it is not right to depend on only the rate of the failure in making the list of the reform. Through the analysis of the breakdown, FMEA can present the important factors of the reform to improve the confidence of the system. In this study would show the important factors of the improvement in order to product the goods guaranteed confidence through the method of FMEA.

• MALSORI
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• no.63
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• pp.113-124
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• 2007

In this paper, we propose a use of confidence vector as an intermediate input feature for multi-stage based speech recognition architecture to improve recognition accuracy. A multi-stage speech recognition structure is introduced as a method to reduce the computational complexity of the decoding procedure and then accomplish faster speech recognition. Conventional multi-stage speech recognition is usually composed of three stages, acoustic search, lexical search, and acoustic re-scoring. In this paper, we focus on improving the accuracy of the lexical decoding by introducing a confidence vector as an input feature instead of phoneme which was used typically. We take experimental results on 220K Korean Point-of-Interest (POI) domain and the experimental results show that the proposed method contributes on improving accuracy.