abstract the aim of this study is of the effect of structural changes in higher education on changes of output in sistan and baluchestan province using structural decomposition analysis (sda). the input-output tables of this region for the period 2006-2011 have been employed as the database of the model. the structural changes were decomposed into two factors: changes in share of specific secto...

Decomposing 3D building models into architectural elements is an essential step in understanding their 3D structure. Although we focus on landmark buildings, our approach generalizes to arbitrary 3D objects. We formulate the decomposition as a multi-label optimization that identifies individual elements of a landmark. This allows our system to cope with noisy, incomplete, outlier-contaminated 3...

This paper presents an innovative approach to model validation for a structure with significant parameter variations. Model uncertainty of the structural dynamics is quantified with the use of a singular value decomposition technique to extract the principal components of parameter change, and an interval model is generated to represent the system with parameter uncertainty. The coordinate vect...

Proper orthogonal decomposition is a statistical pattern analysis technique for "nding the dominant structures, called the proper orthogonal modes, in an ensemble of spatially distributed data. While the proper orthogonal modes are obtained through a statistical formulation, they can be physically interpreted in the "eld of structural dynamics. The purpose of this paper is thus to provide some ...

We first consider the following inverse eigenvalue problem: givenX ∈ Cn×m and a diagonal matrix Λ ∈ Cm×m, find n×nHermite-HamiltonmatricesK andM such thatKX MXΛ. We then consider an optimal approximation problem: given n × n Hermitian matrices Ka and Ma, find a solution K,M of the above inverse problem such that ‖K−Ka‖ ‖M−Ma‖ min. By using the MoorePenrose generalized inverse and the singular v...