• Proceedings of the Korea Water Resources Association Conference
• /
• 2022.05a
• /
• pp.329-329
• /
• 2022

Accurate characterization of terrestrial precipitation variation from high spatial resolution satellite sensors is beneficial for urban hydrology and microscale agriculture modeling, as well as natural disasters (e.g., urban flooding) early warning. However, the widely-used top-down approach for precipitation retrieval from microwave satellites is limited in several hydrological and agricultural applications due to their coarse spatial resolution. In this research, we aim to apply a novel bottom-up method, the parameterized SM2RAIN, where precipitation can be estimated from soil moisture signals based on an inversion of water balance model, to generate high spatial resolution terrestrial precipitation estimates at 0.01º grid (roughly 1-km) from the C-band SAR Sentinel-1. This product was then tested against a common reanalysis-based precipitation data and a domestic rain gauge network from the Korean Meteorological Administration (KMA) over central South Korea, since a clear difference between climatic types (coasts and mainlands) and land covers (croplands and mixed forests) was reported in this area. The results showed that seasonal precipitation variability strongly affected the SM2RAIN performances, and the product derived from separated parameters (rainy and non-rainy seasons) outperformed that estimated considering the entire year. In addition, the product retrieved over the mainland mixed forest region showed slightly superior performance compared to that over the coastal cropland region, suggesting that the 6-day time resolution of S1 data is suitable for capturing the stable precipitation pattern in mainland mixed forests rather than the highly variable precipitation pattern in coastal croplands. Future studies suggest comparing this product to the traditional top-down products, as well as evaluating their integration for enhancing high spatial resolution precipitation over entire South Korea.

• Clinical Nutrition Research
• /
• v.12 no.2
• /
• pp.126-137
• /
• 2023

Hemodialysis (HD) patients face a common problem of malnutrition due to poor appetite. This study aims to verify the appetite alteration model for malnutrition in HD patients through quantitative data and the International Classification of Functioning, Disability, and Health (ICF) framework. This study uses the Mixed Method-Grounded Theory (MMGT) method to explore various factors and processes affecting malnutrition in HD patients, create a suitable treatment model, and validate it systematically by combining qualitative and quantitative data and procedures. The demographics and medical histories of 14 patients were collected. Based on the theory, the research design is based on expansion and confirmation sequence. The usefulness and cut-off points of the creatinine index (CI) guidelines for malnutrition in HD patients were linked to significant categories of GT and the domain of ICF. The retrospective CIs for 3 months revealed patients with 3 different levels of appetite status at nutrition assessment and 2 levels of uremic removal. In the same way, different levels of dry mouth, functional support, self-efficacy, and self-management were analyzed. Poor appetite, degree of dryness, and degree of taste change negatively affected CI, while self-management, uremic removal, functional support, and self-efficacy positively affected CI. This study identified and validated the essential components of appetite alteration in HD patients. These MM-GT methods can guide the selection of outcome measurements and facilitate the perspective of a holistic approach to self-management and intervention.

• Journal of Korean Academy of Nursing
• /
• v.46 no.4
• /
• pp.501-513
• /
• 2016

Purpose: The current challenges faced by nurses in providing high quality and evidence-based practice (EBP) supported care require profound changes in nursing education. To understand the changes needed to strengthen EBP education, the researchers examined EBP self-efficacy, course needs, barriers, and facilitators for academic faculty and clinical nurse preceptors to teach EBP in undergraduate nursing curricula. Methods: For this study, mixed-method approach was used with survey data collected from 73 academic faculty members from 54 universities. Further, 17 clinical nurse preceptors in three academic hospitals provided qualitative data for exploration of barriers and facilitators to teaching EBP. Data analysis used SPSS/WIN 21.0 and content analysis. Results: Quantitative data showed that although the overall level of self-efficacy among faculty was moderate, the implementation levels were relatively low. Most faculty members agreed with the need to integrate EBP courses into undergraduate nursing curricula. The qualitative data showed that the barriers to teaching EBP were lack of knowledge, skill, and initial investment for teaching EBP; hierarchical, rules-oriented nursing culture; potential learner overloads in processing EBP; limited research dissemination and application. Facilitators were identified as the importance of EBP to the profession of nursing; collaboration in schools and hospitals; and continuing education in teaching/utilizing EBP. Conclusion: The findings indicate that for successful integration of EBP ni nursing education there is a need for faculty training and integrated EBP courses.

• Journal of Environmental Impact Assessment
• /
• v.20 no.4
• /
• pp.523-538
• /
• 2011

This study analyzes the changes in the surface area of each forest cover, based on temperature data analysis and satellite imagery as the basic methods for the impact assessment of climate change on regional units. Furthermore, future changes in the forest cover are predicted using the double exponential smoothing method. The results of the study have shown an overall increase in annual mean temperature in the studied region since 1990, and an especially increased rate in winter and autumn compared to other seasons. The multi-temporal analysis of the changes in the forest cover using satellite images showed a large decrease of coniferous forests, and a continual increase in deciduous forests and mixed forests. Such changes are attributed to the increase in annual mean temperature of the studied regions. The analysis of changes in the surface area of each forest cover using the statistical data displayed similar tendencies as that of the forest cover categorizing results from the satellite images. Accordingly, rapid changes in forest cover following the increase of temperature in the studied regions could be expected. The results of the study of the forest cover surface using the double exponential smoothing method predict a continual decrease in coniferous forests until 2050. On the contrary, deciduous forests and mixed forests are predicted to show continually increasing tendencies. Deciduous forests have been predicted to increase the most in the future. With these results, the data on forest cover can be usefully applied as the main index for climate change. Further qualitative results are expected to be deduced from these data in the future, compared to the analyses of the relationship between tree species of forest and climate factors.

• Journal of the Korean Data and Information Science Society
• /
• v.21 no.6
• /
• pp.1289-1303
• /
• 2010

The need for statistical process control to check the performance of a process is becoming more important in chemical and pharmaceutical industries. This study illustrates the method to determine whether a process is in control and how to produce and interpret control charts. In the experiment, a stream of green dyed water and a stream of pure water were continuously mixed in the process. The concentration of the dye solution was measured before and after the mixer via a spectrophotometer. The in-line mixer provided benefits to the dye and water mixture but not for the stock dye solution. The control charts were analyzed, and the pre-mixer process was in control for both the stock and mixed solutions. The R and X-bar charts showed virtually all of the points within control limits, and there were no patterns in the X-bar charts to suggest nonrandom data. However, the post-mixer process was shown to be out of control. While the R charts showed variability within the control limits, the X-bar charts were out of control and showed a steady increase in values, suggesting that the data was nonrandom. This steady increase in dye concentration was due to discontinuous, non-steady state flow. To improve the experiment in the future, a mixer could be inserted into the stock dye tank. The mixer would ensure that the dye concentration of the stock solution is more uniform prior to entering the pre-mixer ow cell. Overall, this would create a better standard to judge the water and dye mixture data against as well.

• The Korean Journal of Applied Statistics
• /
• v.34 no.5
• /
• pp.697-710
• /
• 2021

Relative error prediction is preferred over ordinary prediction methods when relative/percentile errors are regarded as important, especially in econometrics, software engineering and government official statistics. The relative error prediction techniques have been developed in linear/nonlinear regression, nonparametric regression using kernel regression smoother, and stationary time series models. However, random effect models have not been used in relative error prediction. The purpose of this article is to extend relative error prediction to some of generalized linear mixed model (GLMM) with panel data, which is the random effect models based on gamma, lognormal, or inverse gaussian distribution. For better understanding, the real auto insurance data is used to predict the claim size, and the best predictor and the best relative error predictor are comparatively illustrated.

• The Journal of Korean Academic Society of Nursing Education
• /
• v.27 no.3
• /
• pp.227-239
• /
• 2021

Purpose: This study used an exploratory sequential approach (mixed methods) design to explore essential meaning through comparing and analyzing the experiences of nursing students in virtual simulation practice and high fidelity simulation practice education in parallel. Methods: The study participants were 20 nursing students, and data were collected through focus group meetings from July 17 to August 5, 2020, and via online quantitative data from November 10 to November 15, 2020. The qualitative data were analyzed using Giorgi's phenomenological method, and the quantitative data were analyzed using descriptive statistics, the Mann-Whitney U test, Kruskal-Wallis H test analysis of variance and Spearman's ρ correlation. Results: The comparison between the two simulation training experiences was shown in five contextual structures, as follows: (1) reflection of the clinical field, (2) thinking theorem vs. thinking expansion, (3) individual-centered learning vs. team-centered learning, (4) attitudes toward participating in practical training, (5) metacognition of personal competency as a prospective nurse, and (6) revisiting the method of practice training. There was a positive correlation between satisfaction with the practice and the clinical judgment ability of high fidelity simulation, which was statistically significant (r=.47, p=.036). Conclusion: Comparing the experiences between virtual simulation practice training and high fidelity simulation practice training, which has increased in demand due to the Coronavirus Disease-2019 pandemic, is meaningful as it provides practical data for introspection and reflection on in-campus clinical education.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.6
• /
• pp.136-148
• /
• 1996

In this paper, we analyze the traffic characteristics in microcell and macrocell overlaid PCS system which process voice and dta calls separately each others. in this system, data calls are delayed in queue when all of channels are occupied, while voice calls are bolcked in that case. For this, we calculated inter-microcell handoff area dwelling time distribution and handoff area dwelling time distribution between microcell and macrocell. We analyze traffic performance using this results. We used M/M/C/K model, and analyzed traffic performance of macrocell with handoff area variation of microcell.

• Journal of the Korean Data and Information Science Society
• /
• v.7 no.1
• /
• pp.87-92
• /
• 1996

A regression model with nested erroe structure is considered. The regression model includes two error terms that are independent and normally distributed with zero means and constant variances. This error structure of the model gives correlated response variables. The distributions of variance components in the regression model with nested error structure are dervied by using theorems for quadratic forms.

• Journal of the Korean Data and Information Science Society
• /
• v.14 no.1
• /
• pp.131-141
• /
• 2003

In this paper, we prove that multi-variate fuzzy polynomials are universal approximators for multi-variate fuzzy functions which are the extension principle of continuous real-valued function under $T_W-based$ fuzzy arithmetic operations for a distance measure that Buckley et al.(1999) used. We also consider a class of fuzzy polynomial regression model. A mixed non-linear programming approach is used to derive the satisfying solution.