One of the problems of the data envelopment analysis traditional models in the multiple form that is the weights corresponding to certain inputs and outputs are considered zero in the calculation of efficiency and this means that not all input and output components are utilized for the evaluation of efficiency, as some are ignored. The above issue causes the efficiency score of the under evalua...

Knowledge on spatial distribution of land cover and land use is extremely important for solving applied problems in many domains such as agriculture/food security, environmental monitoring, and climate change. Geospatial data including satellite imagery play an important role since it can provide regular, consistent and objective information. Identifying geospatial patterns and quantifying chan...

A novel approach to the problem of regression modeling for fuzzy input-output data is introduced.In order to estimate the parameters of the model, a distance on the space of interval-valued quantities is employed.By minimizing the sum of squared errors, a class of regression models is derived based on the interval-valued data obtained from the $alpha$-level sets of fuzzy input-output data.Then,...

Multiple-source data are often collected to provide better information of some underlying construct that is difficult to measure or likely to be missing. In this article, we describe regression-based methods for analyzing multiple-source data in Stata. We use data from the BROMS Cohort Study, a cohort of Swedish adolescents who collected data on body mass index that was self-reported and that w...

Experience in real-world listening situations suggests that listeners, in general, have a great deal of spatial information about multiple concurrent sounds in an auditory scene. Despite this, laboratory data would suggest that listeners should operate quite poorly in such environments. This study employed environmental sounds that would naturally occur in real-world auditory environments and m...