• Journal of Digital Convergence
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• v.16 no.2
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• pp.479-488
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• 2018

To develop and test validity and reliability of Korean version of the Student Perception of Patient Safety Knowledge, Skills, Attitudes to assess applicability for nursing students. Survey data were collected from convenience sample of 425 fourth year nursing students who enrolled in four universities. Data were evaluated using item analysis, content validity, exploratory factor analysis, and Cronbach's alpha. The attitudes scale was eliminated since item-total correlations were less than .3, on the final Korean Version Scales. The attitudes subscale needs further refinement before implementation. The finding out this study demonstrate that the knowledge and skills scales showed satisfactory validity and reliability. It is useful to evaluate nursing students during educational preparation and in practice.

• Journal of Ocean Engineering and Technology
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• v.32 no.4
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• pp.244-252
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• 2018

This paper provides quantification of the effects of the turbulence model and grid refinement on the analysis of tip vortex flows by using the RANS(Reynolds averaged Navier-Stokes) method. Numerical simulations of the tip vortex flows of the NACA $66_2$-415 elliptic hydrofoil were conducted, and two turbulence models for RANS closure were tested, i.e., the Realizable $k-{\varepsilon}$ model and the Reynolds stress transport model. Numerical results were compared with available experimental data, and it was shown that the data for the Reynolds stress transport model that were computed on the finest grid system had better agreement in reproducing the development and propagation of the tip vortex. The Realizable $k-{\varepsilon}$ model overestimated the turbulence level in the vortex core and showed a diffusive behavior of the tip vortex. The tip vortex cavitation on the hydrofoil and its trajectory also showed good agreement between the current numerical results that were obtained using the Reynolds stress transport model and the results observed in the experiment.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.437-443
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• 2016

Purpose of this study was to develop a self-care program for patients with asthma and test its effects on self-efficacy, compliance, Quality of Life. One group pretest and posttest design was used to test the effects of the intervention. Sixteen asthma patients were recruited conveniently from C university hospital. Date were collected from February 1st to Spring 30th, 2011. Self-care program was composed asthma related education and demonstration of usage of MID & PEFR. The data were analyzed using Wilcoxon signed Rank test by SPSS 18.0. There was a significant increased in self-efficacy(Z=-3.26, p=.001), compliance(Z=-3.52, p<.001), QOL(Z=-3.41, p=.001). Based on data, we recommened the refinement of the intervention in the following areas for future studies: duration, research design, sample size.

• Journal of muscle and joint health
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• v.10 no.1
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• pp.44-53
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• 2003

Purpose : This study was to identify Korean terms appropriate for a new scale using pain terms to assess the pain of the arthritis patients. Method : This study was conducted by secondary analysis of two previous studies, one from Kim's data (1994) and the other from Lee and Choi's(1988). The subjects were 482 patients with arthralgia. Data were analyzed by SPSS Win 11.0, for frequencies, percentages, and means. Results : Five pain groups were sorted out from the sensory pain category, three in the affective pain category, and two in the miscellaneous pain category by selecting groups of pain terms expressed more than 50% by all subjects. Local inflammatory repeated pain terms, simple irritative pain terms, superficial pressure pain terms, traction pain terms, and peripheral nerve terms were included in the sensory pain category, fatigue-related pain terms, digestion-related terms, and suffering-related terms in the affective category, and dull pain terms and body cavity pressure pain category. Among five sample groups terms selected by more than 3 groups with more than 30% of patients were dugumhada, sikungorinda, wooksinwooksinhada, nurudusi apuda, and dangginda in the sensory pain category; nogonhage apuda, gobukhada, and jajungsurupge apuda in the affecte pain category; and buctjockgigunhada and manjimyon apuda in the miscellaneous pain category. Conclusion : Ten pain groups were tentatively selected out of 20 pain groups; 10 pain terms composed of 1 pain term from each group were selected out of 90 pain terms from thesecondarydataofarthriticpainpatients. Implications More detailed clinical studies are needed for the refinement of the scale.

• Journal of the Korean Data and Information Science Society
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• v.24 no.4
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• pp.701-712
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• 2013

The e-learning industry status survey statistic provides information about the actual conditions of supply and demand of the e-learning industries. NIPA (National IT Industry Promotion Agency) has published the annual report of the survey results since 2004. Due to the 9th version of the KSIC (Korean standard industrial classification) revised in 2008, a refinement of the sampling design for the survey becomes necessary, especially that for the business demand sector. This article, based on the 9th revision of the KSIC, constructs a stratification of the target population used for the e-learning industry status survey on the business demand sector. Classification of strata in the business population is based on the industrial type and employment scale of business. Under the stratified population, we design a sampling scheme by using the power allocation method that enables us to satisfy a target coefficient of variation of each industrial stratum. In order to secure an accurate survey results based on the proposed sampling design, we consider the problem of calculating the design weights, derivation of parameter estimators, and formulas of their standard errors.

• Smart Structures and Systems
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• v.15 no.3
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• pp.665-682
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• 2015

Structural identification or St-Id is 'the parametric correlation of structural response characteristics predicted by a mathematical model with analogous characteristics derived from experimental measurements'. This paper describes a St-Id exercise on Humber Bridge that adopted a novel two-stage approach to first calibrate and then validate a mathematical model. This model was then used to predict effects of wind and temperature loads on global static deformation that would be practically impossible to observe. The first stage of the process was an ambient vibration survey in 2008 that used operational modal analysis to estimate a set of modes classified as vertical, torsional or lateral. In the more recent second stage a finite element model (FEM) was developed with an appropriate level of refinement to provide a corresponding set of modal properties. A series of manual adjustments to modal parameters such as cable tension and bearing stiffness resulted in a FEM that produced excellent correspondence for vertical and torsional modes, along with correspondence for the lower frequency lateral modes. In the third stage traffic, wind and temperature data along with deformation measurements from a sparse structural health monitoring system installed in 2011 were compared with equivalent predictions from the partially validated FEM. The match of static response between FEM and SHM data proved good enough for the FEM to be used to predict the un-measurable global deformed shape of the bridge due to vehicle and temperature effects but the FEM had limited capability to reproduce static effects of wind. In addition the FEM was used to show internal forces due to a heavy vehicle to to estimate the worst-case bearing movements under extreme combinations of wind, traffic and temperature loads. The paper shows that in this case, but with limitations, such a two-stage FEM calibration/validation process can be an effective tool for performance prognosis.

• Journal of Korea Water Resources Association
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• v.51 no.10
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• pp.853-862
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• 2018

An adaptive cut-cell grid based 2D inundation analysis model, K-Flood, is developed in this study. Cut cell grid method divides a grid into a flow area and a non-flow area depending the characteristics of the flows. With adaptive mesh refinement technique cut cell method can represent complex flow area using relatively small number of cells. In recent years, the urban inundation modeling using high resolution and fine quality data is increasing to achieve more accurate flood analysis or flood forecasting. K-Flood has potential to simulate such complex urban inundation using efficient grid generation technique. A finite volume numerical scheme of second order accuracy for space and time was applied. For verification of K-Flood, 1) shockwave reflex simulation by circular cylinder, 2) urban flood experiment simulation, 3) Malpasset dam collapse simulation are performed and the results are compared with observed data and previous simulation results.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.419-426
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• 2022

In this paper, we propose a method to improve the accuracy of 3D human pose estimation model in various move motions. Existing human pose estimation models have some problems of jitter, inversion, swap, miss that cause miss coordinates when estimating human poses. These problems cause low accuracy of pose estimation models to detect exact coordinates of human poses. We propose a method that consists of detection and correction methods to handle with these problems. Deep learning-based outlier detection method detects outlier of human pose coordinates in move motion effectively and rule-based correction method corrects the outlier according to a simple rule. We have shown that the proposed method is effective in various motions with the experiments using 2D golf swing motion data and have shown the possibility of expansion from 2D to 3D coordinates.

• Journal of Preventive Medicine and Public Health
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• v.55 no.2
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• pp.134-143
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• 2022

Objectives: Many governments have imposed-and are still imposing-mobility restrictions to contain the coronavirus disease 2019 (COVID-19) pandemic. However, there is no consensus on whether policy-induced reductions of human mobility effectively reduce the effective reproduction number (Rt) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Several studies based on country-restricted data reported conflicting trends in the change of the SARS-CoV-2 Rt following mobility restrictions. The objective of this study was to examine, at the global scale, the existence of regional specificities in the correlations between Rt and human mobility. Methods: We computed the Rt of SARS-CoV-2 using data on worldwide infection cases reported by the Johns Hopkins University, and analyzed the correlation between Rt and mobility indicators from the Google COVID-19 Community Mobility Reports in 125 countries, as well as states/regions within the United States, using the Pearson correlation test, linear modeling, and quadratic modeling. Results: The correlation analysis identified countries where Rt negatively correlated with residential mobility, as expected by policymakers, but also countries where Rt positively correlated with residential mobility and countries with more complex correlation patterns. The correlations between Rt and residential mobility were non-linear in many countries, indicating an optimal level above which increasing residential mobility is counterproductive. Conclusions: Our results indicate that, in order to effectively reduce viral circulation, mobility restriction measures must be tailored by region, considering local cultural determinants and social behaviors. We believe that our results have the potential to guide differential refinement of mobility restriction policies at a country/regional resolution.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.162-171
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• 2020

The purpose of this study is to examine the social perception of disaster safety education for young children based on Textom big data and to explore the direction of young children's disaster safety education. Researchers collected and analyzed online text data using the keywords 'young children+disaster+safety education' from portal websites from 2014 to 2017. The raw data were then subjected to first and second data refinement process. Based on the frequency analysis results, 50 keywords were selected, and the selected keywords were converted into matrix data for network analysis. The results of the study are: first, the most frequently appeared keyword together with young children's disaster safety education was 'education', followed by 'experience', 'kindergarten', 'prevention', and 'school.' Second, keywords with high centrality in the analysis of centrality also were 'education', 'experience', and 'prevention'. In addition, keywords like 'prevention', 'life', and 'evacuation' appear higher in connection-centricity than frequency ranking, which means that the degree of connection between the words is high. These results suggest that young children need education in during early childhood in order to improve their disaster safety skills, and disaster safety education should be accomplished through 'prevention' and 'experience' in early childhood education institutions.