• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.638-643
• /
• 2002

MODIS (MODerate-resolution Imaging Spectroradiometer) onboard the first Earth Observing System (EOS) satellite, Terra, was launched successfully at the end of 1999. The direct broadcast MODIS data has been received and utilized in Korea Meteorological Administration (KMA) since february 2001. This study introduces utilizations of this data, especially for the derivation of sea surface temperature (SST). To produce the MODIS SST operationally, we used a simple cloud mask algorithm and MCSST algorithm. By using a simple cloud mask algorithm and by assumption of NOAA daily SST as a true SST, a new set of MCSST coefficients was derived. And we tried to analyze the current NASA's PFSST and new MCSST algorithms by using the collocated buoy observation data. Although the number of collocated data was limited, both algorithms are highly correlated with the buoy SST, but somewhat bigger bias and RMS difference than we expected. And PFSST uniformly underestimated the SST. Through more analyzing the archived and future-received data, we plan to derive better MCSST coefficients and apply to MODIS data of Aqua that is the second EOS satellite. To use the MODIS standard cloud mask algorithm to get better SST coefficients is going to be prepared.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2022.10a
• /
• pp.81-81
• /
• 2022

Recently, many studies on big data based smart farming have been conducted. Research to quantify morphological characteristics using image data from various crops in smart farming is underway. Rice is one of the most important food crops in the world. Much research has been done to predict and model rice crop yield production. The number of productive tillers per plant is one of the important agronomic traits associated with the grain yield of rice crop. However, modeling the basic growth characteristics of rice requires accurate data measurements. The existing method of measurement by humans is not only labor intensive but also prone to human error. Therefore, conversion to digital data is necessary to obtain accurate and phenotyping quickly. In this study, we present an image-based method to predict leaf number and evaluate tiller number of individual rice crop using YOLOv5 deep learning network. We performed using various network of the YOLOv5 model and compared them to determine higher prediction accuracy. We ako performed data augmentation, a method we use to complement small datasets. Based on the number of leaves and tiller actually measured in rice crop, the number of leaves predicted by the model from the image data and the existing regression equation were used to evaluate the number of tillers using the image data.

• Journal of Intelligence and Information Systems
• /
• v.6 no.1
• /
• pp.73-82
• /
• 2000

This study examined the characteristicso f the knowledge discovery and data mining algorithms to demonstrate how they can be used to predict health outcomes and provide policy information for hypertension management using the Korea Medical Insurance Corporation database. Specifically this study validated the predictive power of data mining algorithms by comparing the performance of logistic regression and two decision tree algorithms CHAID (Chi-squared Automatic Interaction Detection) and C5.0 (a variant of C4.5) since logistic regression has assumed a major position in the healthcare field as a method for predicting or classifying health outcomes based on the specific characteristics of each individual case. This comparison was performed using the test set of 4,588 beneficiaries and the training set of 13,689 beneficiaries that were used to develop the models. On the contrary to the previous study CHAID algorithm performed better than logistic regression in predicting hypertension but C5.0 had the lowest predictive power. In addition CHAID algorithm and association rule also provided the segment characteristics for the risk factors that may be used in developing hypertension management programs. This showed that data mining approach can be a useful analytic tool for predicting and classifying health outcomes data.

• Atmosphere
• /
• v.33 no.1
• /
• pp.33-47
• /
• 2023

In this study, for the application of observation errors to the Korean Integrated Model (KIM) to utilize the Constellation Observing System for Meteorology, Ionosphere & Climate-2 (COSMIC-2) new satellites, the observation errors were diagnosed based on the Desroziers method using the cost function in the process of variational data assimilation. We calculated observation errors for all observational species being utilized for KIM and compared with their relative values. The observation error of the calculated the Global Navigation Satellite System Radio Occultation (GNSS RO) was about six times smaller than that of other satellites. In order to balance with other satellites, we conducted two experiments in which the GNSS RO data expanded by about twice the observation error. The performance of the analysis field was significantly improved in the tropics, where the COSMIC-2 data are more available, and in the Southern Hemisphere, where the influence of GNSS RO data is significantly greater. In particular, the prediction performance of the Southern Hemisphere was improved by doubling the observation error in global region, rather than doubling the COSMIC-2 data only in areas with high density, which seems to have been balanced with other observations.

• Korean Journal of Agricultural Science
• /
• v.46 no.1
• /
• pp.137-149
• /
• 2019

Accurate estimation of reference evapotranspiration (RET) is important to quantify crop evapotranspiration for sustainable water resource management in hydrological, agricultural, and environmental fields. It is estimated by different methods from direct measurements with lysimeters, or by many empirical equations suggested by numerous modeling using local climatic variables. The potential to use some such equations depends on the availability of the necessary meteorological parameters for calculating the RET in specific climatic conditions. The objective of this study was to determine the proper RET equations using limited climatic data and to analyze the temporal and spatial trends of the RET in South Korea. We evaluated the FAO-56 Penman-Monteith equation (FAO-56 PM) by comparing several simple RET equations and observed small fan evaporation. In this study, the modified Penman equation, Hargreaves equation, and FAO Penman-Monteith equation with missing solar radiation (PM-Rs) data were tested to estimate the RET. Nine weather stations were considered with limited climatic data across South Korea from 1973 - 2017, and the RET equations were calculated for each weather station as well as the analysis of the mean error (ME), mean absolute error (MAE), and root mean square error (RMSE). The FAO-56 PM recommended by the Food Agriculture Organization (FAO) showed good performance even though missing solar radiation, relative humidity, and wind speed data and could still be adapted to the limited data conditions. As a result, the RET was increased, and the evapotranspiration rate was increased more in coastal areas than inland.

• Journal of Biosystems Engineering
• /
• v.40 no.3
• /
• pp.284-288
• /
• 2015

Training power tiller operators in safe farming is necessary to avoid farming accidents. With the continuing progress in computational technology, driving simulators have become increasingly popular for conducting such training. Purpose: The objective of this study is to develop mock control devices and data acquisition apparatus for a tiller simulator. Methods: Except for the stand and tail wheel adjusting levers, the mock control devices were developed using a tiller handle assay. The data acquisition apparatus was realized using an embedded data-logging device and LabVIEW, the system design software. Results: The control devices of a real handle assay were successfully mimicked by the mock operator control devices, which used sensors for the relevant measurements. The data from the mock devices were acquired and transmitted to the main computer at intervals of 10 ms via Wi-Fi. Conclusions: The developed mock control devices operate similar to real power tillers and can be utilized in power tiller training simulators.

• Atmosphere
• /
• v.29 no.2
• /
• pp.219-226
• /
• 2019

Generally, the weather forecast system has been run using prescribed ocean condition. As it is widely known that coupling between atmosphere and ocean process produces consistent initial condition at all-time scales to improve forecast skill, there are many trials on the application of data assimilation of coupled model. In this study, we implemented a weakly coupled data assimilation (short for WCDA) system in global NWP model with low horizontal resolution for coupled forecast with uncoupled initialization, following WCDA system at the Met Office. The experiment is carried out for a typhoon evolution forecast in 2017. Air-sea exchange process provides SST cooling and gives a substantial impact on tendency of central pressure changes in the decaying phase of the typhoon, except the underestimated central pressure. Coupled data assimilation is a challenging new area, requiring further work, but it would offer the potential for improving air-sea feedback process on NWP timescales and finally contributing forecast accuracy.

• 한국지구과학회:학술대회논문집
• /
• 2002.02a
• /
• pp.41-41
• /
• 2002

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2019.09a
• /
• pp.103-103
• /
• 2019

• The Journal of Fisheries Business Administration
• /
• v.31 no.1
• /
• pp.55-71
• /
• 2000

Being Changed the international fisheries situation to begin the WTO, it is important to increase the international competition power in fisheries environment to related our country. One of most important work is to build the Fisheries Information Systems(FIS), FIS should give to increase the efficiency of fisheries policies, to share the fisheries informations, and to increase the competitive power of international fisheries environment. On the conclusion, this paper has four expect effects to build the FIS. First, fisheries information will be supplied the clean fisheries policies based on FIS. Second, The Data Warehouse of FIS will be contributed to improve the criterion and statistics of fisheries data. Third, Fisheries Administration will increase the service between fisheries institutes using the FIS. Finally, fisheries administration will use the fisheries data efficiently as integrating the fisheries data into information systems.