• Journal of Engineering Education Research
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• v.18 no.6
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• pp.64-69
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• 2015

A video-work story analysis system based on emotional state measurement includes a content provision unit which provides story content of a video-work, a display unit which displays content provided by the content provision unit, an emotional state measurement unit which measures a tense-relaxed emotional state of a viewer viewing the displayed story content, a story pattern analysis unit which analyzes the tense-relaxed emotional state measured from the emotional state measurement unit according to a scene in the story content provided by the content provision unit, and a story pattern display unit which prints out an analysis result or displays the analysis result as an image. The emotional state measurement unit measures a tense or relaxed emotional state through one or more analyses among a brainwave analysis, a vital sign analysis, or an ocular state analysis. A writer may obtain support in an additional scenario modification work, and an investor may obtain support in making a decision through the above description. Furthermore, the video-work story analysis system and analysis method based on emotional state measurement may extract a particular pattern with respect to a change in an emotional state of a viewer, compile statistics, and analyze a correlation between a story and an emotional state.

• The Korean Journal of Applied Statistics
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• v.15 no.1
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• pp.73-84
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• 2002

Linear regression models with inequality constraints on the coefficients are frequently used in economic models due to sign or order constraints on the coefficients. In this paper, we propose a Bayesian approach to selecting significant explanatory variables in linear regression models with inequality constraints on the coefficients. Bayesian variable selection requires computation of posterior probability of each candidate model. We propose a method which computes all the necessary posterior model probabilities simultaneously. In specific, we obtain posterior samples form the most general model via Gibbs sampling algorithm (Gelfand and Smith, 1990) and compute the posterior probabilities by using the samples. A real example is given to illustrate the method.

• Journal of Korean Clinical Nursing Research
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• v.21 no.1
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• pp.105-115
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• 2015

Purpose: This descriptive correlational study was intended to analyze the relationship among menopausal symptoms. competency of self-care agency and social support in middle-aged women. Methods: Participants in the study were 140 women who were 45-60 years of old. Data were collected using structured questionnaires and analyzed using descriptive statistics., t-test, ANOVA, $Scheff{\grave{e}}^{\prime}s$ test and Pearson correlation coefficients. Results: The frequency and discomfort of menopausal symptom were low, but the mean discomfort score were higher than frequency score. Middle-aged women with lower competency of self care experienced more frequent menopausal symptoms (t=-0.28, p=.001) and more discomfort (t=-0.24, p=.004). However, There was no significant difference in menopausal symptoms according to social support. Conclusion: Nursing interventions to enhance competency of self-care agency in middle-aged women are required in order to reduce the discomfort of menopausal symptoms.

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.4
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• pp.628-638
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• 2014

Purpose: This study identifies the relation among the essentials of fundamental nursing skills performance (EFNSP), work capability and stress from work experienced by new clinical nurses. Method: This is a cross-sectional descriptive study with a self-reported questionnaire. The subjects were 224 new clinical nurses employed by general hospitals having more than 400 beds. The data, collected from February 10 to March 7, 2014, were analyzed using descriptive statistics, t-tests, ANCOVA, Pearson's correlation analysis and hierarchical linear regression. Results: The highest frequency of EFNSP of new clinical nurses was vital sign measurement (4.74, ${\pm}.89$) and the lowest frequency of performance was Basic CPR & defibrillator application (1.81, ${\pm}.94$). There were significant positive correlations between frequency and confidence of EFNSP (r=.64, p<.001), frequency and work capability (r=.34, p<.001), and confidence of EFNSP and work capability (r=.48, p<.001), but negative correlation stress from work and work capability (r=-.17, p=.009). General characteristics, stress from work, frequency and confidence in EFNSP and stress from work explain 25.1% of work capability. Conclusion: This result suggests the importance of EFNSP education in nursing schools and availability of opportunities to practice EFNSP during the post-graduation waiting period until assignment to a hospital.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.1
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• pp.118-123
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• 2015

There have been various studies on measurements of flood risk and forecasting models. For river and dam region, PDF and FVI has been proposed for measurement of flood risk and regression models have been applied for forecasting model. For Bo region unlikely river or dam region, flood risk would unexpectedly increase due to outgoing water to keep water amount under the designated risk level even the drain system could hardly manage the water amount. GFI and general linear model was proposed for flood risk measurement and forecasting model. In this paper, FVI with the consideration of duration on GFI was proposed for flood risk measurement at Bo region. General linear model was applied to the empirical data from Bo region of Nadong river to derive the forecasting model of FVI at three different values of Base High Level, 2m, 2.5m and 3m. The significant predictor variables on the target variable, FVI were as follows: ground water level based on sea level with negative effect, difference between ground altitude of ground water and river level with negative effect, and difference between ground water level and river level after Bo water being filled with positive sign for quantitative variables. And for qualitative variable, effective soil depth and ground soil type were significant for FVI.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.635-641
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• 2021

This article analyzes the factors affecting income inequality in Vietnam, with data from 63 provinces and cities collected from the Vietnam Household Living Standards Survey of the General Statistics Office of Vietnam from 2010 to 2018. The article will firstly build a research model to identify factors affecting income inequality. Then, it uses the Generalized Method of Moments (GMM) method to evaluate the effect of factors on income inequality in Vietnam. The empirical estimate result shows that, in the period from 2010 to 2018, the factors such as the proportion of the working employees, income per capita, and inflation have positive effects on the Gini coefficient. That is, when these factors increase, there will be negative effects on improving income inequality in Vietnam. Conversely, when the factors such as the proportion of the literate adults, the proportion of the urban population, and population density increase they will have a positive impact on improving income inequality in Vietnam during this period. The estimated coefficients satisfied the sign expectation except the proportion of the literate adults. It means that, in Vietnam, the increase and more equilibrium in educational attainment balance the distribution of income and bring an improvement in income inequality.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.1-13
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• 2022

This paper empirically explores the predicting ability of the newly proposed smooth transition (ST) time-varying combining forecast methods. The proposed method allows the "weight" of combining forecasts to change gradually over time through its unique feature of transition variables. Stock market returns from 7 countries were applied to Ad Hoc models, the well-known Generalized Autoregressive Conditional Heteroskedasticity (GARCH) family models, and the Smooth Transition Exponential Smoothing (STES) models. Of the individual models, GJRGARCH and STES-E&AE emerged as the best models and thereby were chosen for constructing the combined forecast models where a total of nine ST combining methods were developed. The robustness of the ST combining forecasts is also validated by the Diebold-Mariano (DM) test. The post-sample forecasting performance shows that ST combining forecast methods outperformed all the individual models and fixed weight combining models. This study contributes in two ways: 1) the ST combining methods statistically outperformed all the individual forecast methods and the existing traditional combining methods using simple averaging and Bates & Granger method. 2) trading volume as a transition variable in ST methods was superior to other individual models as well as the ST models with single sign or size of past shocks as transition variables.

• Journal of information and communication convergence engineering
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• v.20 no.3
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• pp.204-211
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• 2022

This study evaluated the completeness of patient care report (PCR). A retrospective quality analysis was conducted using raw data of 122,140 EMS activity reports prepared by paramedics in Gyeonggi-do from April 1 to May 31, 2021. In all, 67,830 cases of normal transfers were statistically analyzed using IBM SPSS Statistics version 22, and statistical significance was set at p<0.5. The 119EMT_2 certificate was omitted in 50,037 (73.8%) cases, followed by time-related items in 1,227 (1.8%) cases. In the primary assessment of vital signs, systolic blood pressure was omitted and erroneous in 1,218 (1.9%) and 1,129 (1.8%) cases, respectively. In the secondary assessment, the completeness of all vital sign items was approximately 70%. Advanced emergency care and online medical control (OLMC) reporting showed discrepancies in all items. As the severity of the patient's condition increased, the errors in the Patient care report (PCR) also increased, at a significant level (p= .00). Paramedics must be aware of the importance of completing the activity report.

• Journal of the Korean Data and Information Science Society
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• v.28 no.3
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• pp.493-504
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• 2017

We often observe count data that exhibit over-dispersion, originating from too many zeros, and under-dispersion, originating from too few zeros. To handle this types of problems, the zero-altered distribution model is designed by Ghosh and Kim in 2007. Their model can control both over-dispersion and under-dispersion with a single parameter, which had been impossible ever. The dispersion type depends on the sign of the parameter ${\delta}$ in zero-altered distribution. In this study, we demonstrate the role of the dispersion type parameter ${\delta}$ through the data of the number of births in Korea. Employing both the chi-square statistic and the Kolmogorov statistic for goodness-of-fit, we also explained any difference between the theoretical distribution and the observed one that exhibits either over-dispersion or under-dispersion. Finally this study shows whether the test statistics for goodness-of-fit show any similarity with the role of the dispersion type parameter ${\delta}$ or not.

• Korean Journal of Radiology
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• v.21 no.9
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• pp.1055-1064
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• 2020

Objective: To assess the incremental prognostic value of coronary computed tomography angiography (CCTA) in comparison to a clinical risk model (Framingham risk score, FRS) and coronary artery calcium score (CACS) for future cardiac events in ischemic stroke patients without chest pain. Materials and Methods: This retrospective study included 1418 patients with acute stroke who had no previous cardiac disease and underwent CCTA, including CACS. Stenosis degree and plaque types (high-risk, non-calcified, mixed, or calcified plaques) were assessed as CCTA variables. High-risk plaque was defined when at least two of the following characteristics were observed: low-density plaque, positive remodeling, spotty calcification, or napkin-ring sign. We compared the incremental prognostic value of CCTA for major adverse cardiovascular events (MACE) over CACS and FRS. Results: The prevalence of any plaque and obstructive coronary artery disease (CAD) (stenosis ≥ 50%) were 70.7% and 30.2%, respectively. During the median follow-up period of 48 months, 108 patients (7.6%) experienced MACE. Increasing FRS, CACS, and stenosis degree were positively associated with MACE (all p < 0.05). Patients with high-risk plaque type showed the highest incidence of MACE, followed by non-calcified, mixed, and calcified plaque, respectively (log-rank p < 0.001). Among the prediction models for MACE, adding stenosis degree to FRS showed better discrimination and risk reclassification compared to FRS or the FRS + CACS model (all p < 0.05). Furthermore, incorporating plaque type in the prediction model significantly improved reclassification (integrated discrimination improvement, 0.08; p = 0.023) and showed the highest discrimination index (C-statistics, 0.85). However, the addition of CACS on CCTA with FRS did not add to the prediction ability for MACE (p > 0.05). Conclusion: Assessment of stenosis degree and plaque type using CCTA provided additional prognostic value over CACS and FRS to risk stratify stroke patients without prior history of CAD better.