• Korean Journal of Agricultural and Forest Meteorology
• /
• v.22 no.4
• /
• pp.340-345
• /
• 2020

In this study, we developed the quality control and assurance method of measurement data of SPAR (Soil-Plant-Atmosphere-Research) system, a climate change research facility, for the first time. It was found that the precise processing of CO2 flux data among many observations were sig nificantly important to increase the accuracy of canopy photosynthesis measurements in the SPAR system. The collected raw CO2 flux data should first be removed error and missing data and then replaced with estimated data according to photosynthetic lig ht response curve model. Comparing the correlation between cumulative net assimilation and soybean biomass, the quality control and assurance of the raw CO2 flux data showed an improved effect on canopy photosynthesis evaluation by increasing the coefficient of determination (R2) and lowering the root mean square error (RMSE). These data processing methods are expected to be usefully applied to the development of crop growth model using SPAR system.

• East Asian Journal of Business Economics (EAJBE)
• /
• v.4 no.1
• /
• pp.5-15
• /
• 2016

With vigorous development of global network community, smart phones and mobile devices, enterprises can rapidly collect various kinds of data from internal and external environments. How to discover valuable information and transform it into new business opportunities from big data which grow rapidly is an extremely important issue for current enterprises. This study treats Company S as the subject and tries to find the factors of big data application in enterprises by a modified Decision Making Trial and Evaluation Laboratory (DEMATEL) and perceived benefits - perceived barriers relation matrix as reference for big data application and management of managers or marketing personnel in other organizations or related industry.

• 한국데이터정보과학회:학술대회논문집
• /
• 2003.10a
• /
• pp.75-92
• /
• 2003

• Proceedings of the PSK Conference
• /
• 2001.04a
• /
• pp.156.2-156.2
• /
• 2001

• Proceedings of the KSRS Conference
• /
• 2003.11a
• /
• pp.1371-1373
• /
• 2003

The importance of Fundamental Geographical Information Framework for Digital City (FGFDC) is analysed, it provides all city agencies and units with uniform geographic references. Six kind of data are chosen as the core data sets of a FGDC, a web-based distributed mechanism is constructed to promote data sharing among different agencies. Elementary functional requirements of FGDC are analyzed, so that it can serve as a common distributed urban GIS. A practical FGFDC is developed for Yangzhou Development Administrative Region, and an 3D visualization system is developed within this framework.

• Journal of The Korean Society of Agricultural Engineers
• /
• v.62 no.5
• /
• pp.85-91
• /
• 2020

In order to calculate the Crop Water Stress Index (CWSI), it is necessary to collect weather data (air temperature, humidity, wind speed and solar radiation) and canopy temperature. However, it is not always available to have necessary data sets for CWSI calculation. Therefore, this study was aimed to develop an easy and simple CWSI equation (CWSI_EE) using only two data, air and canopy temperatures. Infrared sensors and weather sensors were installed on apple and peach trees and nearby a study area and every ten-minute data were collected from June to October in 2018 and 2019, respectively. A relationship between air-canopy temperature difference and CWSI was statistically analyzed and used to develop CWSI_EE using the three dimensional Gaussian model. The performance of CWSI_EE against original CWSI showed R² and NSE to 0.780 and 0.710 for apple trees and R² and NSE to 0.884 and 0.866 for peach trees. This study found that the level of crop water stress could be easily calculated using CWSI_EE with only air and canopy temperature data.

• Atmosphere
• /
• v.34 no.1
• /
• pp.23-34
• /
• 2024

The Korea Meteorological Administration has improved medium-range weather forecasts by implementing post-processing methods to minimize numerical model errors. In this study, we employ a statistical correction technique known as the minimum continuous ranked probability score (CRPS) to refine medium-range forecast guidance. This technique quantifies the similarity between the predicted values and the observed cumulative distribution function of the Unified Model Ensemble Prediction System for Global (UM EPSG). We evaluated the performance of the medium-range forecast guidance for surface air temperature and relative humidity, noting significant enhancements in seasonal bias and root mean squared error compared to observations. Notably, compared to the existing the medium-range forecast guidance, temperature forecasts exhibit 17.5% improvement in summer and 21.5% improvement in winter. Humidity forecasts also show 12% improvement in summer and 23% improvement in winter. The results indicate that utilizing the minimum CRPS for medium-range forecast guidance provide more reliable and improved performance than UM EPSG.

• The Korean Journal of Health Service Management
• /
• v.10 no.3
• /
• pp.63-74
• /
• 2016

Objectives : There is a need to develop a data quality management algorithm to improve the quality of healthcare data using a data quality management system. In this study, we developed a data quality control algorithms associated with diseases related to hypertension in patients with diabetes mellitus. Methods : To make a data quality algorithm, we extracted the 2011 and 2012 discharge damage survey data from diabetes mellitus patients. Derived variables were created using the primary diagnosis, diagnostic unit, primary surgery and treatment, minor surgery and treatment items. Results : Significant factors in diabetes mellitus patients with hypertension were sex, age, ischemic heart disease, and diagnostic ultrasound of the heart. Depending on the decision tree results, we found four groups with extreme values for diabetes accompanying hypertension patients. Conclusions : There is a need to check the actual data contained in the Outlier (extreme value) groups to improve the quality of the data.

• Atmosphere
• /
• v.17 no.4
• /
• pp.435-453
• /
• 2007

KEOP (Korea Enhanced Observing Period)-2004 intensive summer observation was carried out from 20 June to 5 July 2004 over the Southwestern part of the Korean peninsula. In this study, the effects of KEOP-2004 intensive observation data on the simulation of precipitation system are investigated using KLAPS (Korea Local Analysis and Prediction System) and PSU/NCAR MM5. Three precipitation cases during the intensive observation are selected for detailed analysis. In addition to the control experiments using the traditional data for its initial and boundary conditions, two sensitivity experiments using KEOP data with and without Jindo radar are performed. Although it is hard to find a clear and consistent improvement in the verification score (threat score), it is found that the KEOP data play a role in improving the position and intensity of the simulated precipitation system. The experiments started at 00 and 12 UTC show more positive effect than those of 06 and 18 UTC. The effect of Jindo radar is dependent on the case. It plays a significant role in the heavy rain cases related to a mesoscale low over Changma front and the landing of a Typhoon. KEOP data produce more strong difference in the 06/18 UTC experiments than in 00/12 UTC, but give more positive effects in 00/12 UTC experiments. One of the possible explanations for this is that : KEOP data could properly correct the atmosphere around them when there are certain amounts of data, while gives excessive effect to the atmospheric field when there are few data. CRA analysis supports this reasoning. According to the CRA (Contiguous Rain Area) analysis, KEOP data in 00/12 UTC experiments improve only the surrounding area, resulting in essentially same precipitation system so the effects remain only in each convective cell rather than the system itself. On the other hand, KEOP data modify the precipitation system itself in 06/18 UTC experiments. Therefore the effects become amplified with time integration.

• Journal of Korean Critical Care Nursing
• /
• v.14 no.3
• /
• pp.62-72
• /
• 2021

Purpose : This study aimed to identify factors influencing clinical nurses' intention to report medication administration errors. Methods : This cross-sectional study collected data from 121 nurses in charge of administering medication at a university hospital in Korea using structured questionnaires. Data were analyzed using descriptive statistics, independent t-test, one-way ANOVA, Pearson's correlation coefficient, and multiple linear regression. Results : Participants' mean age was 26.90±3.99 years, and 89.3% were women. Their mean clinical career duration was 3.88±4.26 years. The average levels of patient safety culture, attitude toward reporting medication administration errors, and intention to report medication administration errors were 7.51 out of 10, 3.36 out of 5, and 4.85 out of 6, respectively. The multiple regression analysis results indicated that the statistically significant influencing factors were patient safety culture (𝛽=.21, p =.018) and attitude toward reporting medication administration errors (𝛽=.22, p =.015). Conclusion : To improve the intention to report medication administration errors among clinical nurses, a patient safety culture must be established, along with an education provision for improving their attitudes toward reporting such administration errors.