• Child Health Nursing Research
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• v.5 no.2
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• pp.151-166
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• 1999

The purposes of this study were to measure the degree of perceived uncertainty, social support & powerlessness, to examine the relationship between the perceived uncertainty, social support & powerlessness and then to find the predictors of powerlessness in mother's of handicapped children. The subjects of this study consist of 102 mothers of handicapped children, registered at rehabilitation & handicapped children school. Data was collected from September 1998 to March 1999. The tools used in this study were Mishel's the Parents' Perception of Uncertainty Scale (28 item, 4 likert scale), Miller's Powerlessness measurement Scale(28 itewt 4 likert scale) & Cohen's Interpersonal Support Evaluation List (40 items, 4 likert scale). Data was analyzed by t-test, ANOVA, Duncan comparison, Pearson Correlation coefficient & Stepwise multiple regression Results of this study are summarized as follows : 1. Mothers perceived their uncertainty to be slightly high(Mn 2.50). The degree of perceived uncertainty by the four components were followed as : lack of clarity(2.69), unpredictability(2.56), ambiguity(2.56) & lack of information(2.46). The degree of perceived uncertainty of the mothers of handicapped children revealed to be influenced significantly by age of children, admission experience, disability types of children. 2. The degree of mothers' powerlessness was measured to be slightly high(Mn 2.14). The degree of perceived powerlessness of the mothers with handicapped children revealed to be influenced significantly by age of children, duration of illness admission experience,8E marital status of the mothers. 3. Mothers perceived their social support to be slightly high(Mn 2.71). The degree of perceived social support revealed to be influenced significantly by sex of children, married state of mothers. 4. Mothers' uncertainty was related positively to the mothers' powerlessness(r=.33, p=.0008). And also mothers' powerlessness was related inversely to social support(r=-.50, p=.0001). But, mothers' uncertainty was not related to social support significantly. 5. To analyze the variables which affect powerlessness, stepwise regression was implemented. As a result, about 61% of the powerlessness were explained by social support, marital status of the mothers and perceived uncertainty. Based upon these results, it is recommended that the nurses, who are caring handicapped children and their families, provide various support programs for them to overcome their difficulties. Also programs which decrease the uncertainty & powerlessness used social support multidimensionally & individually are recommended to be developed.

• Journal of KIISE
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• v.43 no.1
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• pp.87-95
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• 2016

Recently, due to the development of the Internet and electronic devices, there has been an enormous increase in the amount of available knowledge and information. As this growth has proceeded, studies on large-scale ontological reasoning have been actively carried out. In general, a machine learning program or knowledge engineer measures and provides a degree of confidence for each triple in a large ontology. Yet, the collected ontology data contains specific uncertainty and reasoning such data can cause vagueness in reasoning results. In order to solve the uncertainty issue, we propose an RDFS reasoning approach that utilizes confidence values indicating degrees of uncertainty in the collected data. Unlike conventional reasoning approaches that have not taken into account data uncertainty, by using the in-memory based cluster computing framework Spark, our approach computes confidence values in the data inferred through RDFS-based reasoning by applying methods for uncertainty estimating. As a result, the computed confidence values represent the uncertainty in the inferred data. To evaluate our approach, ontology reasoning was carried out over the LUBM standard benchmark data set with addition arbitrary confidence values to ontology triples. Experimental results indicated that the proposed system is capable of running over the largest data set LUBM3000 in 1179 seconds inferring 350K triples.

• 한국신재생에너지학회:학술대회논문집
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• 2005.06a
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• pp.42-46
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• 2005

In spite of fast growing of prediction codes, there is still not negligible uncertainty in their results. This uncertainty affects on the turbine structural design and power production prediction. With the growing size of wind turbine, reducing this uncertainty is becoming one of critical issues for high performance and efficient wind turbine design. In this respect, there are international efforts to evaluate and tune prediction codes of wind turbine. As the reference data for this purpose, field test data is not appropriate because of its uncontrollable wind characteristics and its inherent uncertainty. Wind tunnel can provide controllable wind. For this reason, NREL has done the full scale test of the 10m turbine at NASA-Ames. With this reference data, a blind comparison has been done with participation of 18 organizations with 19 modeling tools. The results were not favorable. In Europe, a similar project is going on. Nine organizations from five countries are participating in the MEXICO project to do full scale wind tunnel tests and calculation with prediction codes. In this study. these two projects were reviewed in respect of wind tunnel test and its contribution. As a conclusion, it is suggested that scale model wind tunnel tests can be a complementary tool to calculation codes which were evaluated worse than expected.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.173-181
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• 2017

As the industries have developed, a myriad of big data have been produced and the inherent uncertainty in the data has also increased accordingly. In this paper, we propose an interval type-2 fuzzy clustering method to deal with the inherent uncertainty in the data and, using this method, design and optimize the fuzzy neural network. Fuzzy rules using the proposed clustering method are designed and carried out the learning process. Genetic algorithms are used as an optimization method and the model parameters are optimally explored. Experiments were performed with two pattern classification, both of the experiments show the superior pattern recognition results. The proposed network will be able to provide a way to deal with the uncertainty increasing.

• Journal of Haehwa Medicine
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• v.6 no.1
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• pp.567-584
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• 1997

Most of cancer therapy consists of surgery, chemotherapy and radiotherapy developed by modern western medicine. Often Korean patients use both modem western and oriental medicine through their cancer life. This study tried out to answer the the question : "What are the experience of a Korean cancer patients who follow oriental medicine after cancer diagnosis?" To answer to that, a micro-ethnographic research method was used. Total 6 patients were observed from March, 1996 to February, 1997. Data were obtained through interview, participant observation, audio-tape recording, field recoding, field note-taking, and ralated documents Using an analytical tool known as "pencil and scissors", the data were analyzed. First, I learned patietnts' accounts for cancer experience following oriental medicine, and I could found that they expereinced "feeling of uncertainty" through cancer life. Second, major argument was searched. : Feeling of uncertainty of cancer patients was extremely increased after cancer diagnosis. Oriental Medicine made cancer patients not only expect to improve general physical condition, but also gave them significnat emotional support to overcome their feeling of uncertanty. Third, I examined how did this argument form meanings in the context of individual life. Modem western mediacal service system could not satisfy cancer patients' informational and emotional need. But oriental medicine contribute to relieve the degree of their feeling of uncertainty. As a result of these understandings, I suggest that modern wetern medicine need to be concerned to feeling of uncertainty of cancer patietns and infomational service, and oriental medicine counsel with cancer patients much more systemically. Also nurses must improve cancer education with more accurate and practical information based on empirical data.

• Nuclear Engineering and Technology
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• v.53 no.9
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• pp.2816-2829
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• 2021

Decay heat residuals of spent nuclear fuel (SNF), i.e., the differences between calculations and measurements, were obtained previously for various spent fuel assemblies (SFA) using the Polaris module of the SCALE code system. In this paper, we compare decay heat residuals to their uncertainties, focusing on four PWRs and four BWRs. Uncertainties in nuclear data and model inputs are propagated stochastically through calculations using the SCALE/Sampler super-sequence. Total uncertainties could not explain the residuals of two SFAs measured at GE-Morris. The combined z-scores for all SFAs measured at the Clab facility could explain the resulting deviations. Nuclear-data-related uncertainties contribute more in the high burnup SFAs. Design and operational uncertainties tend to contribute more to the total uncertainties. Assembly burnup is a relevant variable as it correlates significantly with the SNF decay heat. Additionally, burnup uncertainty is a major contributor to decay heat uncertainty, and assumptions relating to these uncertainties are crucial. Propagation of nuclear data and design and operational uncertainties shows that the analyzed assemblies respond similarly with high correlation. The calculated decay heats are highly correlated in the PWRs and BWRs, whereas lower correlations were observed between decay heats of SFAs that differ in their burnups.

• Journal of the Korea Convergence Society
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• v.5 no.4
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• pp.155-161
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• 2014

We survey the relation of fuzzy entropy measure and similarity measure. Each measure represents features of data uncertainty and certainty between comparative data group. With the help of one-to-one correspondence characteristics, distance measure and similarity measure have been expressed by the complementary characteristics. We construct similarity measure using distance measure, and verification of usefulness is proved. Furthermore analysis of similarity measure from fuzzy entropy measure is also discussed.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1079-1086
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• 2005

Most discussions of single imputation methods and the EM algorithm concern point estimation of population quantities with missing values. A second concern is how to get standard errors of the point estimates obtained from the filled-in data by single imputation methods and EM algorithm. Now we focus on how to estimate standard errors with incorporating the additional uncertainty due to nonresponse. There are some approaches to account for the additional uncertainty. The general two possible approaches are considered. One is the jackknife method of resampling methods. The other is multiple imputation(MI). These two approaches are reviewed and compared through simulation studies.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.2
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• pp.118-126
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• 2014

In this paper, a new method is proposed for the five-degree-of-freedom precision alignment and stitching of three-dimensional surface-profile data sets. The control parameters for correcting thealignment error are calculated from the surface profile data for overlapped areas among the adjacent measuring areas by using the "least squares method" and "maximum lag position of cross correlation function." To ensure the alignment and stitching reliability, the relationships betweenthe alignment uncertainty, overlapped area, and signal-to-noise level of the measured profile data are investigated. Based on the results of this uncertainty analysis, an appropriate size is proposed for the overlapped area according to the specimen's surface texture and noise level.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.521-521
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• 2000

This paper investigates the problem of robust H$_{\infty}$ filter with FIR(Finite Impulse Response) structure for linear continuous time-varying systems with sampled-data measurements. It is assumed that the system is subject to real time-varying uncertainty which is represented by the state-space model having parameter uncertainty. The robust H$_{\infty}$ FIR filter is proposed for the continuous-time linear parameter uncertain systems. It is also derived from the equivalence relationship between the robust linear H$_{\infty}$ FIR filter and the robust linear H$_{\infty}$ filter with sampled-data measurements.