two different methods of bayesian segmentation algorithm were used with different band combinations. sequential maximum a posteriori (smap) is a bayesian image segmentation algorithm which unlike the traditional maximum likelihood (ml) classification attempts to improve accuracy by taking contextual information into account, rather than classifying pixels separately. landsat 7 etm+ data with pa...

Sequential learning techniques, such as auto-context, that applies the output of an intermediate classifier as contextual features for its subsequent classifier has shown impressive performance for semantic segmentation. We show that these methods can be interpreted as an approximation technique derived from a Bayesian formulation. To improve the effectiveness of applying this approximation tec...

XML queries employ regular path expressions to find structural patterns within XML documents. The operation of structural join is a crucial part of XML query processing. Existing approaches reduce complex join expressions to several binary structural joins. It implies generation of superfluous intermediate data. In this paper, we propose a new structural join algorithm, called sequence join alg...

Current explanations for private consumption’s diminished role in China focus on the expansion of exports and investments. Using structural path analysis, we find additional contributing factors. First, growth patterns during 1997-2007 favoured sectors with low production multipliers. Secondly, income multipliers fell in most sectors, especially in fast growing sectors and partly due to urbaniz...

this paper is about discrete sensitivity analysis. a triangular bending element with constant moment and six degrees of freedom is used. the required derivatives for sensitivity analysis are calculated explicitly. these formulations, finite element method and sequential linear programming are utilized to find shape optimization of plate bending structures. the numerical examples, which show the...

Path problems can be solved in many ways, by sequential, parallel, general or specialized algorithms 2, 4, 6 . In 8 we have proposed a fairly general distributed algorithm which can be implemented on a network of computers and can be applied to all types of path problems. In 7 we have also studied optimized versions of the same algorithm that are faster but applicable only to certain classes of...

This paper examines the connection between path independence and transitive rationalization of a choice function in a general domain where a choice function may not include all possible non-empty subsets of the universal set. Describing a sequential choice procedure, this paper shows that the requirement of path independence of a choice function is equivalent to Richter's Congruence Axiom and t...

Recent research has shown the benefits of using K -means clustering in task allocation to robots. However, there is little evaluation of other clustering techniques. In this paper we compare K -means clustering to single-linkage clustering and consider the effects of straight line and true path distance metrics in cluster formation. Our empirical results show single-linkage clustering with a tr...

Many high dimensional optimization problems can be reformulated into a problem of finding theoptimal state path under an equivalent space model setting. In this article, we present general emulation strategy for developing whose likelihood function (or posterior distribution) shares the same landscape as objective original problem. Then solution is optimal that maximizes or distribution emulate...