fundamental formulation
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Author(s):  
A. Olfati ◽  
M. Rahimi ◽  
M. Ravanshadnia

Debris treatment after earthquake is very important matter especially after large-scale disasters. Efficient debris treatment is leading to faster reconstruction. Particularly, this article examines fuzziness in debris treatment planning. The problem reduces to a standard transport problem by fundamental formulation. A fuzzy debris transport problem for supply and demand formulated fuzzy constraints. A problem-solving algorithm by referring numerical example demonstrates an irrelevant approach. Realistic debris transport planning can be defined by using the recommended method.


2013 ◽  
Vol 80 (5) ◽  
Author(s):  
Lifeng Ma ◽  
Alexander M. Korsunsky ◽  
Robert M. McMeeking

In this paper the problem of transformation toughening in anisotropic solids is addressed in the framework of Stroh formalism. The fundamental solutions for a transformed strain nucleus located in an infinite anisotropic elastic plane are derived first. Furthermore, the solution for the interaction of a crack tip with a residual strain nucleus is obtained. On the basis of these expressions, fundamental formulations are presented for the toughening arising from transformations using the Green's function method. Finally, a representative example is studied to demonstrate the relevance of the fundamental formulation.


2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
S. Y. Chen ◽  
Hanyang Tong ◽  
Carlo Cattani

Markov random field (MRF) is a widely used probabilistic model for expressing interaction of different events. One of the most successful applications is to solve image labeling problems in computer vision. This paper provides a survey of recent advances in this field. We give the background, basic concepts, and fundamental formulation of MRF. Two distinct kinds of discrete optimization methods, that is, belief propagation and graph cut, are discussed. We further focus on the solutions of two classical vision problems, that is, stereo and binary image segmentation using MRF model.


2009 ◽  
Vol 45 (8) ◽  
pp. 1014-1023 ◽  
Author(s):  
Shu-Wei Chang ◽  
Shun Lien Chuang

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