Data Envelopment analysis is a nonparametric method used to evaluate the performance of profit and non-profit organizations. It assumes that the input and output variables are known a priori. In each environment, there exists a huge number of input and output variables, and all the variables will serve as either input or output variable. If there exist a large number of input and output variabl...

The purpose of this study is to provide an efficient method for the selection input–output indicators in data envelopment analysis (DEA) approach, order improve discriminatory power DEA evaluation process and performance homogeneous decision-making units (DMUs) presence negative values data. For purpose, Shannon entropy technique used as one most important methods determining weight indicators....

The exciting study by Steele et al. is the first to use non-negative matrix factorization to quantify electromyography (EMG) muscle synergies during gait in children with cerebral palsy (CP). The identification of fewer synergies during gait in adults with stroke and the relationship of lower synergy number to greater functional limitations are of great interest in neurorehabilitation. So I com...

abstract aims: one of the consequences of taking ground water into surface is changing its chemical quality, specially increasing the concentration of dissolved salts. this research was performed in order to analyze growth possibility of heterotrophic bacteria in the membrane of active desalination plants in kashan city, iran. instrument & methods: this descriptive cross-sectional study was don...

the sources of output growth of iranian agriculture over the years 1986-2001 has been examined, using a decomposition method within the input-output (io) framework. the three comparable io tables of 1986, 1991, and 2001 have been employed as the main data sources. output changes from a demand side perspective, and decomposition of the growth of output into components attributable to consumption...