• Journal of The Korean Society of Agricultural Engineers
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• v.55 no.4
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• pp.55-63
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• 2013

This study investigates the trends and uncertainty of the impacts of climate change on paddy rice production in the Geumho river basin. The Long Ashton Research Station stochastic Weather Generator (LARS-WG) was used to derive future climate data for the Geumho river basin from 15 General Circulation models (GCMs) for 3 Special Report on Emissions Scenarios (SRES) (A2, A1B and B1) included in the Intergovernmental Panel on Climate Change (IPCC) 4th assessment report. The Food and Agricultural Organization (FAO) AquaCrop, a water-driven crop model, was statistically calibrated for the 1982 to 2010 climate. The index of agreement (IoA), prediction efficiency ($R^2$), percent bias (PBIAS), root mean square error (RMSE) and a visual technique were used to evaluate the adjusted AquaCrop simulated yield values. The adjusted simulated yields showed RMSE, NSE, IoA and PBIAS of 0.40, 0.26, 0.76 and 0.59 respectively. The 5, 9 and 15 year central moving averages showed $R^2$ of 0.78, 0.90 and 0.96 respectively after adjustment. AquaCrop was run for the 2020s (2011-2030), 2050s (2046-2065) and 2090s (2080-2099). Climate change projections for Geumho river basin generally indicate a hotter and wetter future climate with maximum increase in the annual temperature of $4.5^{\circ}C$ in the 2090s A1B, as well as maximum increase in the rainfall of 45 % in the 2090s A2. The means (and ranges) of paddy rice yields are projected to increase by 21 % (17-25 %), 34 % (27-42 %) and 43 % (31-54 %) for the 2020s, 2050s and 2090s, respectively. The A1B shows the largest rice yield uncertainty in all time slices with standard deviation of 0.148, 0.189 and $0.173t{\cdot}ha^{-1}$ for the 2020s, 2050s and 2090s, respectively.

• The Journal of Korean Institute of Next Generation Computing
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• v.14 no.6
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• pp.44-56
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• 2018

Researches on military weapons are actively studied to improve national defense power of each country. The military weapon system is being used not only as a weapon but also as a reconnaissance and surveillance device for places where it is difficult for people to access. If such a weapon system becomes an object of attack, military data that is important to national security can be leaked. Furthermore, if a device is taken, it can be used as a terrorist tool to threaten its own country. So, security of military devices is necessarily required. In order to enhance the security of a weapon system such as drone, it is necessary to form a chain of trust(CoT) that gives trustworthiness to the overall process of the system from the power on until application is executed. In this paper, by analyzing the trusted computing-based boot technology, we derive trusted boot technology components and classify them based on hardware dependence/independence. We expect our classification of hardware dependence/independence to be applied to the trusted boot technology of our self-development ultraprecision weapon system to improve the defense capability in our military.