• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.5
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• pp.251-257
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• 2014

Digital RDA system is retransmit into the opposite direction of the incident signals. Digital RDA system have a disadventage that this system do not signal classification in multipath environment. because multipath signal is shown as vector sum of multipath signal, digital RDA system required complex signal process for multipath signal classification. In this paper, to solve these problem we propose hybrid digital RDA system which combination of the MUSIC algorithm and the digital RDA system. Proposed system has two modes. First mode is digital RDA mode. Secornd mode is digital beamforming mode. Digital RDA mode is used in situations where the less the impact of multipath. Digital beamforming mode is applied to multipath effects is greater. In secornd mode, we find optimal path using MUSIC algorithm. After than the proposed system uses only the optimal path. Through the proposed system in a multipath environment with digital RDA can be used to supplement a disadvantage.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.141-141
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• 2022

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2019.08a
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• pp.184-185
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• 2019

• Korean Journal of Agricultural Science
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• v.47 no.4
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• pp.1097-1107
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• 2020

Assessment of soil carbon stock is essential for climate change mitigation and soil fertility. The digital soil mapping (DSM) is well known as a general technique to estimate the soil carbon stocks and upgrade previous soil maps. The aim of this study is to calculate the soil carbon stock in the top soil layer (0 to 30 cm) in Jeolla Province of South Korea using the DSM technique. To predict spatial carbon stock, we used Cubist, which a data-mining algorithm model base on tree regression. Soil samples (130 in total) were collected from three depths (0 to 10 cm, 10 to 20 cm, 20 to 30 cm) considering spatial distribution in Jeolla Province. These data were randomly divided into two sets for model calibration (70%) and validation (30%). The results showed that clay content, topographic wetness index (TWI), and digital elevation model (DEM) were the most important environmental covariate predictors of soil carbon stock. The predicted average soil carbon density was 3.88 kg·m-2. The R2 value representing the model's performance was 0.6, which was relatively high compared to a previous study. The total soil carbon stocks at a depth of 0 to 30 cm in Jeolla Province were estimated to be about 81 megatons.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.2
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• pp.209-216
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• 2013

In this paper, we design and analyze digital retrodirective array antenna (RDA) system in 60GHz wireless communication for low power consumption and high quality. Digital RDA can automatically make beam toward source without information about the direction of incoming signal, this system is able to do low power communication thanks to increased signal to interference noise ratio (SINR) because making the beam toward source can reduce interference signals. The frequency offset seriously arises when millimetric wave band like 60GHz is used to communicate for high-speed transmission. The proposed system is robustly designed to frequency offset through designing digital phase lock loop in order to solve the problem of frequency offset. In this paper, we analyze the performance of the proposed system according to the number of array antenna and frequency offset. striking space.

• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2014.10a
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• pp.173-181
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• 2014

• Korean Journal of Soil Science and Fertilizer
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• v.49 no.6
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• pp.731-742
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• 2016

Recent technological advance in UAV (Unmanned Aerial Vehicle) technology offers new opportunities for assessing crop situation using UAV imagery. The objective of this study was to assess if reflectance and NDVI derived from consumer-grade cameras mounted on UAVs are useful for crop condition monitoring. This study was conducted using a fixed-wing UAV(Ebee) with Cannon S110 camera from March 2015 to March 2016 in the experiment field of National Institute of Agricultural Sciences. Results were compared with ground-based recordings obtained from consumer-grade cameras and ground multi-spectral sensors. The relationship between raw digital numbers (DNs) of UAV images and measured calibration tarp reflectance was quadratic. Surface (lawn grass, stairs, and soybean cultivation area) reflectance obtained from UAV images was not similar to reflectance measured by ground-based sensors. But NDVI based on UAV imagery was similar to NDVI calculated by ground-based sensors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.86-92
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• 2017

In this study, a model to classify frost occurrence and frost free day was developed using the digital weather forecast data provided by Korea Meteorological Administration (KMA). The minimum temperature, average wind speed, relative humidity, and dew point temperature were identified as the meteorological variables useful for classification frost occurrence and frost-free days. It was found that frost-occurrence date tended to have relatively low values of the minimum temperature, dew point temperature, and average wind speed. On the other hand, relatively humidity on frost-free days was higher than on frost-occurrence dates. Models based on machine learning methods including Artificial Neural Network (ANN), Random Forest(RF), Support Vector Machine(SVM) with those meteorological factors had >70% of accuracy. This results suggested that these models would be useful to predict the occurrence of frost using a digital weather forecast data.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.18-18
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• 2022

Barley has been used for the production of malt in the brewing industry. Malting is the process of preparing barley through partial germination. Malt extract is the most important quality parameter for malt quality. The grain and malt quality parameters of ten Korean malting barley varieties were studied. Malts was prepared using Phoeix automated micro malting system(Phoenix Bio, Australia). Quality analysis of Barley and malt was determined according to European brewery convention(EBC, 1998) and American society of brewing chemists(ASBC, 1997) method. And the hordeins of barley and malt were extracted with 50% isopropyl alcohol(IPA, 2-propanol) of 1% dithiothreitol(DTT). The analysis of hordeins was carried out by ultra-performance liquid chromatography(UPLC). The mean values of 1000-grains weight, assortment rate, protein content, starch content, beta-glucan content, husk rate, germination energy, germination capacity and water sensitivity of grain were 45.8g, 86.8%, 11.9%, 58.0%, 3.8%, 14.0%, 96.2%, 97.2%, 10.0%, respectively. The mean values of protein content, friability, diastatic power, extract, soluble protein, Kolbach index, beta-glucan of malt and wort were 11.3%, 87.6%, 201WK(Windish Kolbach), 79.3%, 4.6%, 41%, 85mg/L, respectively. UPLC analysis of grain and malt hordeins revealed that the amount of hordeins significantly degraded during malting. Also, we could successfully be used to compare hordein polypeptide patterns with malt quality.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.4
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• pp.398-403
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• 2023

Process-based K-cabbage model is based on physiological processes such as photosynthesis and phenology, making it possible to predict crop growth under different climate conditions that have never been experienced before. Current first-stage process-based models can be used to assess climate impact through yield prediction based on climate change scenarios, but no comparison has been performed between big data obtained from the main production area and model prediction so far. The aim of this study was to find out the direction of model improvement when using the current model for yield prediction. For this purpose, model performance evaluation was conducted based on data collected from farmers growing 'Chungwang' cabbage in Taebaek and Samcheok, the main producing areas of Chinese cabbage in highland region. The farms surveyed in this study had different cultivation methods in terms of planting date and soil water and nutrient management. The results showed that the potential biomass estimated using the K-cabbage model exceeded the observed values in all cases. Although predictions and observations at the time of harvest did not show a complete positive correlation due to limitations caused by the use of fresh weight in the model evaluation process (R²=0.74, RMSE=866.4), when fitting the model based on the values 2 weeks before harvest, the growth suitability index was different for each farm. These results are suggested to be due to differences in soil properties and management practices between farms. Therefore, to predict attainable yields taking into account differences in soil and management practices between farms, it is necessary to integrate dynamic soil nutrient and moisture modules into crop models, rather than using arbitrary growth suitability indices in current K-cabbage model.