• Journal of the Korean Data and Information Science Society
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• v.25 no.2
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• pp.365-371
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• 2014

Association rule of the well-studied techniques in data mining is the exploratory data analysis for understanding the relevance among the items in a huge database. This method has been used to find the relationship between each set of items based on the interestingness measures such as support, confidence, lift, similarity measures, etc. By typical association rule technique, we generate association rule that satisfy minimum support and confidence values. Support and confidence are the most frequently used, but they have the drawback that they can not determine the direction of the association because they have always positive values. In this paper, we compared support, basic confidence, and three kinds of confidence measures useful for classification model building to overcome this problem. The result confirmed that the causal confirmed confidence was the best confidence in view of the association mining because it showed more precisely the direction of association.

• Journal of Convergence for Information Technology
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• v.12 no.4
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• pp.231-238
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• 2022

This study aims to investigate the effect of college students' major satisfaction on career decision-making self-efficacy and job confidence. The research method was used for analysis by surveying 335 two-year college students majoring in beauty in Seoul and Gyeonggi-do. The collected data were analyzed for frequency analysis, factor analysis, reliability analysis, and correlation between career decision-making self-efficacy and job confidence using SPSS 26.0, and multiple regression analysis was conducted to confirm the effect between each variable. As a result of the study, first, a statistically significant positive (+) correlation between college students' major satisfaction was confirmed between career decision-making self-efficacy and job confidence. Second, as the effect of major satisfaction on self-efficacy, statistically significant effects were confirmed in self-evaluation, problem-solving, and goal selection. Fifth, it was confirmed that major satisfaction had a statistically significant effect on job confidence. Fourth, it was confirmed that career decision-making self-efficacy had a statistically significant effect on job confidence.

• Structural Engineering and Mechanics
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• v.13 no.2
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• pp.117-134
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• 2002

This paper presents a computational method for a confidence region of identified parameters which are affected by measurement noise and error contained in prescribed parameters. The method is based on sensitivities of the identified parameters with respect to model parameter error and measurement noise along with the law of error propagation. By conducting numerical experiments on simple models, it is confirmed that the confidence region coincides well with the results of numerical experiments. Furthermore, the optimum arrangement of sensor locations is evaluated when uncertainty exists in prescribed parameters, based on the concept that square sum of coefficients of variations of identified results attains minimum. Good agreement of the theoretical results with those of numerical simulation confirmed validity of the theory.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.8
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• pp.533-542
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• 2020

This study estimates the nature of the relationship of entrepreneurship and business confidence on youth unemployment in the Philippines over the 2001-2017 period. The paper employed a range of cointegrating regression models, namely, autoregressive distributed lag (ARDL) bounds testing approach, Johansen-Juselius (JJ) and Engle-Granger (EG) cointegration models, dynamic OLS, fully modified OLS, and canonical cointegrating regression (CCR) estimation techniques. The Granger causality based on error correction model (ECM) was also performed to determine the causal link of entrepreneurship and business confidence on youth unemployment. The ARDL bounds testing approach, Johansen-Juselius (JJ) and Engle-Granger (EG) cointegration models confirmed the existence of long-run equilibrium relationship of entrepreneurship and business confidence on youth unemployment. The long-run coefficients from JJ and dynamic OLS show significant long-run and positive relationship of entrepreneurship and business confidence on youth unemployment. While results of the long-run coefficients from fully modified OLS and canonical cointegrating regression (CCR) found that only entrepreneurship has significant and positive relationship with youth unemployment in the long-run. The Granger causality based on error correction model (ECM) estimates show evidence of long-run causal relationship of entrepreneurship and business confidence on youth unemployment. In the short-run, increases in entrepreneurship and business confidence causes youth unemployment to decrease.

• 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.

• The Journal of Korean Academic Society of Nursing Education
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• v.29 no.2
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• pp.180-189
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• 2023

Purpose: The purpose of this study is to confirm the relationship between nursing students' nursing professionalism and ethical decision-making confidence, and to clarify the mediating effect of moral sensitivity which has a mutual influence on nursing professionalism and ethical decision-making confidence. Methods: The data collection for this study was conducted from January 23 to February 1, 2021 with junior and senior nursing students enrolled in five nursing departments in two regions. The data collected in this study were analyzed using the IBM SPSS statistics version 23.0 program. Results: Through this study, it was found that nursing professionalism (β=.47) and moral sensitivity (β=.32) acted as important influencing factors on the ethical decision-making confidence of nursing students, with an explanatory power of 31.2%. In addition, it was confirmed that there was a partial mediating effect of moral sensitivity in the relationship between the nursing professionalism and ethical decision-making confidence of nursing students, and the mediating effect coefficient of moral sensitivity was .16. Conclusion: Based on the results of the study, it is suggested to prepare a plan to increase ethical decision-making confidence and moral sensitivity when planning interventions to improve nursing professionalism in nursing students.

• Management & Information Systems Review
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• v.34 no.1
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• pp.1-20
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• 2015

This study analyses the relationship with the feature of the web usability and Social commerce. Therefore, this research tries to investigate the relationship about in which the characteristic of the web-site usability is connected through the confidence about the Social commerce site to the re-purchase. The existing research that the information system and Electronic commerce relates is considered and the usability factor about the Social commerce site tries to be drawn and these try to verify on the relationship with the trust building of the user about the Social commerce site and purchasing intention through the positive research. The result is follows. First, the visual property of the Social commerce site was confirmed to have the descriptive ability noted to the confidence. Second, it was confirmed to have the descriptive ability that information characteristic about the Social commerce site notes to the confidence. Third, it was confirmed to have the descriptive ability that relative characteristic about the Social commerce site notes to the confidence. The importance of the web-site usuability has preferentially to be considered in being put through this research and building the confidence of the social commerce user could be known. When running with the social commerce site design, this is determined because it can become the useful standard.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.857-868
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• 2014

Data mining is the representative analysis methodology in the era of big data, and is the process to analyze a massive volume database and summarize it into meaningful information. Association rule technique finds the relationship among several items in huge database using the interestingness measures such as support, confidence, lift, etc. But these interestingness measures cannot be used to establish a causality relationship between antecedent and consequent item sets. Moreover, we can not know association direction by them. This paper propose causally confirmed association thresholds to compensate for these problems, and then check the three conditions of interestingness measures. The comparative studies with basic association thresholds, causal association thresholds, and causally confirmed association thresholds are shown by simulation studies. The results show that causally confirmed association thresholds are better than basic and causal association thresholds.

• Genomics & Informatics
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• v.18 no.4
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• pp.45.1-45.5
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• 2020

With the ongoing rise of coronavirus disease 2019 (COVID-19) pandemic across the globe, interests in COVID-19 antibody testing, also known as a serology test has grown, as a way to measure how far the infection has spread in the population and to identify individuals who may be immune. Recently, many countries reported their population based antibody titer study results. South Korea recently reported their third antibody formation rate, where it divided the study between the general population and the young male youths in their early twenties. As previously stated, these simple point estimates may be misinterpreted without proper estimation of standard error and confidence intervals. In this article, we provide an updated 95% confidence intervals for COVID-19 antibody formation rate for the Korean population using asymptotic, exact and Bayesian statistical estimation methods. As before, 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 November 23, 2020, at least 69,524 people were infected but not confirmed. It also shows that more positive cases were found among the young male in their twenties (0.22%), three times that of the general public (0.051%). This thereby calls for the quarantine authorities' need to strengthen quarantine managements for the early twenties in order to find the hidden infected people in the population.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.311-324
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• 2022

In this paper, we adjusted the feedback and learning materials for each learning based on ARCS motivation which applied DEVS methodology. We designed the ARCS professor-student model that expresses the continuous change in the student's attitude toward the class according to the student's attention, relevance, confidence, and satisfaction. It was applied to computational thinking and data analysis classes Based on the designed model. Before and after class, the students were asked the same question and then analyzed for each part of the ARCS. It was observed that students' perceptions of Attention, Relevance, and Satisfaction were improved except for Confidence. we observed that the students themselves felt that they lacked a lot of confidence compared to other ARS through the analysis. Although, Confidence showed a 13.5% improvement after class but it was about 33% lower than the average of other ARS. However, when it was observed that students' self-confidence was 30% lower than other motivational factors it was confirmed that the part that leads C to a similar level in other ARS is necessary.