Grass genomes differ greatly in chromosome number, ploidy level, and size. Despite these differences, very good conservation of the marker order (collinearity) was found at the genetic map level between the different grass genomes. Collinearity is particularly good between rice chromosome 1 and the group 3 chromosomes in the Triticeae. We have used this collinearity to saturate the leaf rust re...

Since the online measurement of melt index (MI) of polyethylene is difficult, a virtual sensor model is desirable. However, a polyethylene process usually produces products with multiple grades. The relations between process and quality variables are highly nonlinear. In addition, a virtual sensor model in the real plant process with many inputs has to deal with the collinearity and the time-va...

The natural complexity of ecological communities regularly lures ecologists to collect elaborate data sets in which confounding factors are often present. Although multiple regression is commonly used in such cases to test the individual effects of many explanatory variables on a continuous response, the inherent collinearity (multicollinearity) of confounded explanatory variables encumbers ana...

ÐDetermining the rigid transformation relating 2D images to known 3D geometry is a classical problem in photogrammetry and computer vision. Heretofore, the best methods for solving the problem have relied on iterative optimization methods which cannot be proven to converge and/or which do not effectively account for the orthonormal structure of rotation matrices. We show that the pose estimatio...

This paper presents an effective recognition method based on perceptual organization of low level features detected in an image. The method uses a dynamic programming (DP) based formulation to represent various line groups such as convex, concave, and more complex patterns consisting of convex and concave shapes. The essential features of perceptual organization such as endpoint proximity, coll...

the latest known source of multicollinearity, a nonorthogonality of two or more explanatory variables in multiple regression models, is high leverage points. Interpreting a fitted regression model may become impossible by the influential impacts of multicollinearity. In this paper, we attempt to investigate the impact of different sample sizes as one of the main causing factors of high leverage...

This report consists of two independent parts. The first is entitled "Non-maximum suppression of gradient magnitudes makes them easier to threshold"; it shows that, besides reducing thick responses to thin, the application of non-maximum suppression to digital gradient magnitudes also improves the form of the edge response histogram, making the choice of thresholds easier. In the second, entitl...