3 resultados para Region growing algorithms
em University of Queensland eSpace - Australia
Resumo:
Sequence diversity in the coat protein coding region of Australian strains of Johnsongrass mosaic virus (JGMV) was investigated. Field isolates were sampled during a seven year period from Johnsongrass, sorghum and corn across the northern grain growing region. The 23 isolates were found to have greater than 94% nucleotide and amino acid sequence identity. The Australian isolates and two strains from the U.S.A. had about 90% nucleotide sequence identity and were between 19 and 30% different in the N-terminus of the coat protein. Two amino acid residues were found in the core region of the coat protein in isolates obtained from sorghum having the Krish gene for JGMV resistance that differed from those found in isolates from other hosts which did not have this single dominant resistance gene. These amino acid changes may have been responsible for overcoming the resistance conferred by the Krish gene for JGMV resistance in sorghum. The identification of these variable regions was essential for the development of durable pathogen-derived resistance to JGMV in sorghum.
Resumo:
Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.