• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.6
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• pp.761-768
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• 2009

GPS data acquired at CORS are widely and rapidly used in many application such as information technology industries. In acquisition of GPS data the establishment of standards of reliability and tolerance error range is necessary. This standards is regarded to contain the requirements of selection of using softwares, precise and broadcast ephemeris, duration of data acquisition, and etc. This study focused to present above standards of tolerance error. In long baseline GPS observation network the RMSE analysed in this study resulted little change when data acquired in 6-hour duration, but the less observation duration resulted less accuracy. Especially in 3-hour observation the accuracy of GPS data decreased rapidly. After analyses of data accuracy in the same observation condition using different computer program between academic and commercial purpose software, the RMSE of academic software resulted less than 1cm compared to 3 to 10cm from commercial software. RMSE analysis between precise ephemeris and broadcast ephemeris resulted similar quantity. Therefore this study regarded to present the reliable establishment of standards of error which can be used in required accuracy in GPS data observation.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.68-78
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• 2020

Crop models have been used to predict vegetable crop yield, which would have a considerable economic impact on consumers as well as producers. A small number of models have been developed to estimate growth and yield of vegetables due to limited availability of growth observation data in high-quality. In this study, we aimed to analyze the protocols designed for collection of the observation data for major vegetable crops including cabbage, radish, garlic, onion and pepper. We also designed the protocols suitable for development and verification of a vegetable crop growth model. In particular, different measures were proposed to improve the existing protocol used by Statistics Korea (KOSTAT) and Rural Development Administration (RDA), which would enhance reliability of parameter estimation for the crop model. It would be advantageous to select sampling sites in areas where reliable weather observation data can be obtained because crop models quantify the response of crop growth to given weather conditions. It is recommended to choose multiple sampling sites where climate conditions would differ. It is crucial to collect time series data for comparison between observed and simulated crop growth and yield. A crop model can be developed to predict actual yield rather than attainable yield using data for crop damage caused by diseases and pests as well as weather anomalies. A bigdata platform where the observation data are to be shared would facilitate the development of crop models for vegetable crops.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.32 no.2
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• pp.135-145
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• 2020

Wave observation is widely used to direct observation method for observing the water surface elevation using wave buoy or pressure gauge and remote-sensing wave observation method. The wave buoy and pressure gauge can produce high-quality wave data but have disadvantages of the high risk of damage and loss of the instrument, and high maintenance cost in the offshore area. On the other hand, remote observation method such as radar is easy to maintain by installing the equipment on the land, but the accuracy is somewhat lower than the direct observation method. This study investigates the data quality of MIROS Wave and Current Radar (MWR) installed at Dokdo and improve the data quality of remote wave observation data using the wave buoy (CWB) observation data operated by the Korea Meteorological Administration. We applied and developed the three types of wave data quality control; 1) the combined use (Optimal Filter) of the filter designed by MIROS (Reduce Noise Frequency, Phillips Check, Energy Level Check), 2) Spike Test Algorithm (Spike Test) developed by OOI (Ocean Observatories Initiative) and 3) a new filter (H-Ts QC) using the significant wave height-period relationship. As a result, the wave observation data of MWR using three quality control have some reliability about the significant wave height. On the other hand, there are still some errors in the significant wave period, so improvements are required. Also, since the wave observation data of MWR is different somewhat from the CWB data in high waves of over 3 m, further research such as collection and analysis of long-term remote wave observation data and filter development is necessary.

• Korean Journal of Adult Nursing
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• v.25 no.6
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• pp.655-664
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• 2013

Purpose: This study was undertaken to identify which delirium screening instrument would be more useful in clinical practice. Methods: Data were collected from 118 nurses from six hospitals in five provinces in Korea. For the delirium screening three instruments were compared: NEECHAM Confusion Scale (NEECHAM), Nursing Delirium Screening Scale (Nu-DESC), Delirium Observation Scale (DOS). The MMSE-K was used for concurrent validity. The nurse subjects were surveyed as to the practical clinical value of each instrument. Cronbach's ${\alpha}$ coefficient and Kuder-Richardson 20 were used to confirm the reliability. Results: The range of three scales reliability was .70~.82 and the range of correlation coefficient was .63~.82 with MMSE-K. For sensitivity of NEECHAM, Nu-DESC and DOS was 1.00, 1.00 and 0.81 respectively and specificity NEECHAM, Nu-DESC and DOS was 0.88, 0.89 and 0.89 respectively. Nurses rated the practical use of the DOS scale as significantly easier to use than the NEECHAM and Nu-DESC. Conclusion: NEECHAM, Nu-DESC and DOS scales were acceptable in terms of reliability, validity, sensitivity and specificity. However, nurses rated the DOS scale as easier scale to use and had more relevance to their practice.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.13 no.3
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• pp.510-519
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• 2006

Purpose: To develop and validate a scale suitable and efficient scale for use in clinical practice as to assess pain in premature infants. Method: Pain indicators identified by observation of preform infants. A cohort of preform infants was studied prospectively to determine the construct validity, inter-rater reliability, and internal consistency of the scale. The PIPS uses four indicators of pain: corrected gestational age, heart rate, oxygen saturation, behavioral state. The validation study included 45 premature infants with gestational age of 37 weeks or less. Results: The inter-rater reliability of the PIPS was acceptable, with Pearson correlations ranging from.720 to.970. Internal consistency was high: Cronbach's alpha coefficients ranged from.551 to.653. There was a strong correlation between the PIPS and PIPP scores (each researcher's r=.743, each indicator's r=.914). Although gestational age showed no association between these factors and the sum, the other variables were positively associated with the sum. Time needed to calculate PIPS scores is was less than Premature Infant Pain Profile (PIPP) scores(p<.000). Conclusion: The validation data suggest that the PIPS is appropriate and efficient for assessing pain in premature infants. Further studies are required about to determine appropriate interventions for each pain score on the PIPS.

• Journal of the Korean Society of Safety
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• v.27 no.5
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• pp.148-157
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• 2012

Reliability-based design optimization (RBDO) problem is usually formulated as an optimization problem to minimize an objective function subjected to probabilistic constraint functions which may include deterministic design variables as well as random variables. The challenging task is that, because the probability models of the random variables are often assumed based on limited data, there exists a possibility of selecting inappropriate distribution models and/or model parameters for the random variables, which can often lead to disastrous consequences. In order to select the most appropriate distribution model from the limited observation data as well as model parameters, this study takes into account a set of possible candidate models for the random variables. The suitability of each model is then investigated by employing performance and risk functions. In this regard, this study enables structural design optimization and fitness assessment of the distribution models of the random variables at the same time. As the first paper of a two-part series, this paper describes a new design method considering probability model uncertainties. The robust performance of the proposed method is presented in Part 2. To demonstrate the effectiveness of the proposed method, an example of ten-bar truss structure is considered. The numerical results show that the proposed method can provide the optimal design variables while guaranteeing the most desirable distribution models for the random variables even in case the limited data are only available.

• Journal of the Ergonomics Society of Korea
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• v.35 no.5
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• pp.383-389
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• 2016

Objective: In this paper, work time for the representative fruit crops are collected and analyzed using time-diary method, and the collected data were compared with the directly observed work time using GPS device. Background: There is no consistent conclusion which measurement method for work time is accurate. Most of the research results were collected from the environment other than rural area. Therefore, there is need to review reliability of the measurement methods for the agricultural work which are carried out for a long duration. Method: Top five crops (apple, pear, grape, sweet persimmon, and peach) were selected according to the number of farms and cultivation areas. We let fruit growers fill a work diary during one cropping period. A difference between the work-time that was recorded by the farmers and the direct observed worktime using GPS device were analyzed. Results: Average direct work time for the five fruit crops found to be 7.1% of the total work time. Conclusions and Applications: Reliability was secured by recording the daily work diary at each work stage while aware that direct observation is carried on. Data which are being collected by government institutions are obtained by the memories of the respondents. Therefore, it is needed to try the method adopted by this study in order to collect more accurate data.

• Applied Chemistry for Engineering
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• v.20 no.5
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• pp.511-516
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• 2009

Photodegradation characteristics of polyolefin composites were studied. Thermogravimetric analysis results suggest that the polyolefin blends used in this study have different amounts of talc. The mechanical behaviors of polyolefin blends, which experienced UV-irradiation in accordance with SAE J1960, are investigated using tensile and Izod impact tests. These results show that as the UV-exposure time increases, a significant drop in the elongation at break and impact strength at a low temperature are observed. This may be explained by the decreases in elastic energy derived from the scission of polymer molecular chains and the low density of entanglement after UV- photodegradation. Scanning electron microscopy observations indicate that no crack and surface damage are observed, while the additional talc particles are exposed, on the UV-exposed surfaces. The exposure of talc particles may be responsible for the discoloration of UV-exposed polyolefin blend surface. Observation using Fourier transform infrared spectroscopy (FT-IR) confirms the presence of photodegradation on the surface of UV-exposed polyolefin blend.

• Journal of Coastal Disaster Prevention
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• v.4 no.4
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• pp.189-196
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• 2017

Ocean Research Stations (ORSs) is the ocean platform type observation towers and measured oceanic, atmospheric and environmental data. These station located on the offshore area far from the coast, so they can produce the data without land effect. This study focused to improve the wave data quality of ORS station. The wave observations at ORSs are used by the C-band (5.8 GHz, 5.17 cm) MIROS Wave and Current Radar (MWR). MWR is convenient to maintenance and produce reliability wave data under bad weather conditions. MWR measured significant wave height, peak wave period, peak wave direction and 2D wave spectrum, so it's can provide wave information for researchers and engineers. In order to improve the reliability of MWR wave data, Datawell Waverider Buoy was installed near the one ORS (Socheoncho station) during 7 months and validate the wave data of MWR. This study found that the wave radar tend to be overestimate the low wave height under wind condition. Firstly, this study carried out the wave Quality Control (QC) using wind data, however the quality of wave data was limited. So, this study applied the four filters (Correlation Check, Direction Filter, Reduce White Noise and Phillips Check) of MWR operating software and find that the filters effectively improve the wave data quality. After applying 3 effective filters in combination, the RMSE of significant wave height decreased from 0.81m to 0.23m, by 0.58m and Correlation increased from 0.66 to 0.96, by 0.32, so the reliability of MWR significant wave height was significantly improved.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.366-372
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• 2020

The Army's rocket missile is a one-shot weapon system, which is produced and used for only one mission, and requires high reliability. While reliability analysis with failure data can result in underestimation of the life distribution, reliability analysis with all the non-failure data can result in overestimation of the life distribution. Under or overestimation of the life distribution can lead to cost increase by early disposal or complete observation of all rocket missiles. In order to overcome this problem, the Army suggests the guideline of the number of samples from non-failure data for reliability analysis with failure data. However, the currently used sampling method can generate errors for predicting the failure rate. To solve this problem, this study proposes a new sampling procedure for predicting a future failure rate using non-failure data. The comparison test between the currently used sampling method and the proposed sampling method is conducted and the result shows that the proposed sampling method can predict the future failure rate more accurately.