• Journal of Korea Water Resources Association
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• v.46 no.11
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• pp.1041-1052
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• 2013

In this study, we estimate parameters of a distributed hydrologic model, GRM (grid based rainfall-runoff model), using a model-independent parameter estimation tool, PEST. We implement auto calibration of model parameters such as initial soil moisture, multipliers of overland roughness and soil hydraulic conductivity in the Geumho River Catchment and the Gamcheon Catchment using radar rainfall estimates and ground-observed rainfall represented by Thiessen interpolation. Automatic calibration is performed by GRM-MP (multiple projects), a modified version of GRM without GUI (graphic user interface) implementation, and "Parallel PEST" to improve estimation efficiency. Although ground rainfall shows similar or higher cumulative amount compared to radar rainfall in the areal average, high spatial variation is found only in radar rainfall. In terms of accuracy of hydrologic simulations, radar rainfall is equivalent or superior to ground rainfall. In the case of radar rainfall, the estimated multiplier of soil hydraulic conductivity is lower than 1, which may be affected by high rainfall intensity of radar rainfall. Other parameters such as initial soil moisture and the multiplier of overland roughness do not show consistent trends in the calibration results. Overall, calibrated parameters show different patterns in radar and ground rainfall, which should be carefully considered in the rainfall-runoff modelling applications using radar rainfall.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.50-53
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• 2016

Image processing techniques play an increasingly important role in many aspects of our daily life. For example, it has been shown to improve agricultural productivity in a number of ways such as plant pest detecting or fruit grading. However, massive quantities of images generated in real-time through multi-devices such as remote sensors during monitoring plant growth lead to the challenges of big data. Meanwhile, most current image processing systems are designed for small-scale and local computation, and they do not scale well to handle big data problems with their large requirements for computational resources and storage. In this paper, we have proposed an IPABigData (Image Processing Algorithm BigData) platform which provides algorithms to support large-scale image processing in agriculture based on Hadoop framework. Hadoop provides a parallel computation model MapReduce and Hadoop distributed file system (HDFS) module. It can also handle parallel pipelines, which are frequently used in image processing. In our experiment, we show that our platform outperforms traditional system in a scenario of image segmentation.

• International Journal of Industrial Entomology and Biomaterials
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• v.3 no.2
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• pp.169-175
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• 2001

A synthetic juvenoid, R394 (Ethyl 9-cyclohexyl-3, 7-dimethyl-2, 4-nonadienoate) which is known to be a strong pest control agent was administered to silkworm, Bombyx mori L. in minute quantity for improving the silk yield. Based on the result of an earlier preliminary screening, three concentrations of the compound, viz., 0.1563, 0.3125, 31.25 nl/ml were prepared in the form of an emulsion and administered topically as a single dose, to separate batches of $5^{th}$ instar silkworm at 24, 48, 72 and 96 hrs to determine the required concentration and critical time of application for an economically favourable response. Two popular commercial silkworm hybrids, PM ${\times}$ NB4D2 (multivoltine${\times}$bivoltine) and KA${\times}$NB4D2 (bivoltine$\times$bivoltine) were subjected to the experiment. The medium and absolute control were maintained in parallel to compare the results. The results showed that 0.3125 nl/ml was the best concentration of the compound and 72 hrs of $5^{th}$instar was the most favourable age for its administration to get the maximum improvement in the commercial traits. The possible role of exogenous juvenoids in eliciting favourable response in silkworm which ultimately leads to improvement in the commercial traits is discussed.

• Archives of design research
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• v.20 no.1 s.69
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• pp.5-20
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• 2007

The aim of this research is to find out the flows of mega-trends and design trends by analyzing the factors that influence trend and design trends in the late 20th century. Moreover, it is to forecast and recommend design color trends by evaluating color trends in design trends for the near future. Secondary and primary research were used in parallel. In the late 20th century, mega-trends were analyzed from secondary research based on PEST. Design trends were analyzed from case studies in fashion, space, product and visual design. On this basis, design color trends were analyzed. Also, color trends were forecast for the near future. The results are as follows. Firstly, the main trends in the late 20th century were 'female thinking', 'back to the nature' and 'heaven of peace'. Second, main design trends in the 1970s were modernism, post-modernism and high-tech. In the 1980s, with those of the 1970s, ecology was introduced In the late 1980s. In the 1990s, modernism rose again and ecology had an influence. The trends of 'female thinking' and 'back to the nature' controled the design in the early 2000s. Third, design colors in the late 20th century changed from Red to Purple Blue. Tones changed from 'grayish' to 'dull' Finally, it was forecast that Purple Blue, Yellow Red and Green colors with 'grayish', 'dull' and 'deep' tones were going to be used mainly in the near future. Also, achromatic colors with female and warm nuances would be reflected in design parts. This research will be very useful in that it has built a concrete database reflected on design trends forecasting in the near future by organizing academically a methodology to identify trends reflected on design and identifying relation between mega-trends and design trends based on analyzing factors that influence trend.