• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1173-1176
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• 1996

Multilayer feedforward networks may be applied to identify the deterministic relationship between input and output data. When the results from the network require a high level of assurance, considering of the stochastic relationship between the data may be very important. The variance is one of the useful parameters to represent the stochastic relationship. This paper presents a new algorithm for a multilayer feedforward network to learn the variance of dispersed data without preliminary calculation of variance. In this paper, the network with this learning algorithm is named as a variance learning neural network(VALEAN). Computer simulation examples are utilized for the demonstration and the evaluation of VALEAN.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.6
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• pp.121-127
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• 1997

Multilayer feedforward networks may be applied to identify the deterministic relationship between input and output data. When the results from the network require a high level of assurance, consideration of the stochastic relationship between the input and output data may be very important. Variance is one of the effective parameters to deal with the stochastic relationship. This paper presents a new algroithm for a multilayer feedforward network to learn the variance of dispersed data without preliminary calculation of variance. In this paper, the network with this learning algorithm is named as a variance learning neural network(VALEAN). Computer simulation examples are utilized for the demonstration and the evaluation of VALEAN.

• Journal of the Korean Data and Information Science Society
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• v.8 no.1
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• pp.41-48
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• 1997

We construct the empirical Bayes(EB) confidence intervals that attain a specified level of EB coverage for the unknown scale parameter in the Weibull distribution with the known shape parameter under the type II censored data. Our general approach is to use an EB bootstrap samples introduced by Larid and Louis(1987). Also, we compare the coverage probability and the expected interval length for these bootstrap intervals with those of the naive intervals through Monte Carlo simulation.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.22-25
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• 2003

It is usually difficult for a single user to have all the essential knowledge on various Rapid Prototyping processes and techniques. It is therefore necessary to capture knowledge and experience of users of expert level into a decision-support system which provides quicker and more interactive way to select proper RP process and/or machine. rather than reading reports on benchmarking studies and comparing tables and graphs. In this paper two algorithms are presented, which may be used in such a decision-support system. together with its applications. The one is an extended PRES(Project Evaluation and Selection) algorithm which applies weighting factors of each attribute. The other is a LCE(Linear Confidence Equation) algorithm which is proposed to apply user's input requirements as well as weighting factors.

• Communications for Statistical Applications and Methods
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• v.21 no.2
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• pp.193-200
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• 2014

It was recognized by some researchers that the disturbance variance in a censored regression model is frequently underestimated by the maximum likelihood method. This underestimation has implications for the estimation of marginal effects and asymptotic standard errors. For instance, the actual coverage probability of the confidence interval based on a maximum likelihood estimate can be significantly smaller than the nominal confidence level; consequently, a Bayesian estimation is considered to overcome this difficulty. The behaviors of the maximum likelihood and Bayesian estimators of disturbance variance are examined in a fixed effects panel regression model with a limited dependent variable, which is known to have the incidental parameter problem. Behavior under random effect assumption is also investigated.

• Journal of Korean Academy of Nursing
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• v.45 no.6
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• pp.846-856
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• 2015

Purpose: The focus of this study was on symptom management to predict quality of life among individuals with heart failure. The theoretical model was constructed based on situation-specific theory of heart failure self-care and literature review. Methods: For participants, 241 outpatients at a university hospital were invited to the study from May 19 to July 30, 2014. Data were collected with structured questionnaires and analyzed using SPSSWIN and AMOS 20.0. Results: The goodness of fit index for the hypothetical model was .93, incremental fit index, .90, and comparative fit index, .90. As the outcomes satisfied the recommended level, the hypothetical model appeared to fit the data. Seven of the eight hypotheses selected for the hypothetical model were statistically significant. The predictors of symptom management, symptom management confidence and social support together explained 32% of the variance in quality of life. The 28% of variance in symptom management was explained by symptom recognition, heart failure knowledge and symptom management confidence. The 4% of variance in symptom management confidence was explained by social support. Conclusion: The hypothetical model of this study was confirmed to be adequate in explaining and predicting quality of life among patients with heart failure through symptom management. Effective strategies to improve quality of life among patients with heart failure should focus on symptom management. Symptom management can be enhanced by providing educational programs, encouraging social support and confidence, consequently improving quality of life among this population.

• The Journal of Korean Academic Society of Nursing Education
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• v.23 no.4
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• pp.409-418
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• 2017

Purpose: Ineffective communication between healthcare professionals leads to medical errors and puts patients at risk of harm. The aim of this study was to examine the effects of interdisciplinary communication training in simulated settings on self-confidence in communication, observed communication behavior, and technical skill performances of nursing students. Methods: A repeated measures design with one group was conducted. Data was collected from 92 nursing students through a self-administered questionnaire and an observed behavior checklist. Data analysis was performed using descriptive statistics, a paired t-test, the Wilcoxon signed rank test, the Friedmann test, a Repeated Measures ANOVA, and the Spearman correlation coefficient. Results: Self-confidence in communication, observed Identification-Situation-Background-Assessment-Recommendation-Read Back communication behavior, and technical skill performances of nursing students were significantly improved. In observed communication behavior, the performance of Assessment and Read Back communication significantly improved. However, communication of Background, Assessment, and Recommendation did not improve to a satisfactory level. Observed communication behavior was not correlated with the overall technical skill performance. Conclusion: These results indicate that interdisciplinary communication training in simulated settings was effective in improving nursing students' confidence and communication skills with physicians. Longitudinal studies with larger samples are recommended in order to verify the effects of interdisciplinary communication training on clinical outcomes as well as communication competence.

• ETRI Journal
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• v.29 no.3
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• pp.336-352
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• 2007

Sequential pattern mining has become an essential task with broad applications. Most sequential pattern mining algorithms use a minimum support threshold to prune the combinatorial search space. This strategy provides basic pruning; however, it cannot mine correlated sequential patterns with similar support and/or weight levels. If the minimum support is low, many spurious patterns having items with different support levels are found; if the minimum support is high, meaningful sequential patterns with low support levels may be missed. We present a new algorithm, weighted interesting sequential (WIS) pattern mining based on a pattern growth method in which new measures, sequential s-confidence and w-confidence, are suggested. Using these measures, weighted interesting sequential patterns with similar levels of support and/or weight are mined. The WIS algorithm gives a balance between the measures of support and weight, and considers correlation between items within sequential patterns. A performance analysis shows that WIS is efficient and scalable in weighted sequential pattern mining.

• Korean Journal of Health Education and Promotion
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• v.25 no.4
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• pp.43-54
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• 2008

Objectives: To identify the willingness of laypersons to perform the cardiopulmonary resuscitation(CPR), we analyzed their characteristics of socio-economic status and health-medical conditions associated with their willingness. Methods: Based on a health survey of Incheon Metropolitan City adults(N=5,114), tests of the differences between a group with willingness to perform CPR(=1,531) and a group with non-willingness to perform CPR(=3,583), and a logistic regression analysis of two groups were executed on socio-economic status-gender, age, marital stats, education level, jobs, and monthly household income-and health-medical conditions-CPR-related self-confidence, CPR education, chronic diseases, accident experience, EMS(emergency medical service) experience, and health status. Results: The rate of the willingness group was 29.9%, which was relatively lower than other developed countries. There were statistically significant differences between the willingness group with the non-willingness group on gender, age, jobs, CPR-related self-confidence, CPR education, and so on. Furthermore, Gender, age, students or armed forces among jobs, CPR-related self-confidence, and CPR education were statistically significant influential factors on the willingness to perform CPR. Conclusion: This study indicated that there was considerable variation in socio-economic status and health-medical conditions associated with willingness to perform CPR in Incheon. The CPR education aimed at increasing CPR-related self-confidence and correcting inaccurate perceptions of CPR attitudes would promote its use in response to out-of-hospital cardiac arrest.