The development of NIRS calibration model as a rapid, precise, robust, and cost-effective method to estimate oil content in ground seeds of worldwide safflower germplasm collection grown under different agro-climatic conditions was the key objective of this research project. The oil content was measured by accelerated solvent extraction method in a total of 328 samples collected across 2004 (16...

Field experiments were conducted in 2005-2006 and 2007-2008 and the data were used tocalibrate and validate yield and biomass of AquaCrop Model for canola (Brassica napus l.). Themodel was calibrated with the first year and then was validated with the second year data. Fivewater stress treatments at different growth stages were performed including fully irrigatedduring whole growing period (I1)...

australian rainfall is related with numerous key climate predictors namely el-nino southern oscillation (enso), indian ocean dipole (iod) and southern annular mode (sam). some studies have tried to discover the effects of these climate predictors on rainfall variability of different parts of australia, particularly western australia, queensland and victoria. nonetheless, clear association betwe...

In order to choose correctly the dimension of calibration model in chemistry, a new simple and effective method named Ž . Monte Carlo cross validation MCCV is introduced in the present work. Unlike leave-one-out procedure commonly used in Ž . chemometrics for cross validation CV , the Monte Carlo cross validation developed in this paper is an asymptotically consistent method in determining the ...

Advanced robot control schemes require an accurate knowledge of the dynamic parameters of the manipulator. This article examines various issues related to robot dynamic calibration, from generation of optimal excitation trajectories to data acquisition and filtering, and experimental inertial and friction parameter estimation. In particular, a new method is developed for the determination of op...

This paper presents a method to optimise the calibration of parameters and land use transition rules of a cellular automata (CA) urban growth model using a self-adaptive genetic algorithm (SAGA). Optimal calibration is achieved through an algorithm that minimises the difference between the simulated and observed urban growth. The model was applied to simulate land use change from non-urban to u...

If its utility function is everywhere increasing and concave, rank−dependent expected utility shares a troubling property with expected utility −− aversion to the same moderate−stakes risk at every wealth level implies an extreme aversion to large−stakes risks. In fact, the problem may be even worse for rank−dependent expected utility, since the moderate−stakes risk need not be actuarially fair...