t is the purpose of this paper to contribute to the discussion initiated bywachter about the parallelism between principal component (pc) and atypological grade of membership (gom) analysis. the author testedempirically the close relationship between both analysis in a lowdimensional framework comprising up to nine dichotomous variables and twotypologies. our contribution to the subject is also...

as widespread deserts is located in west and southwest of iran plateau, dust storms form due to west andsouthwest systems over syria or iraq as well as arabian peninsula. these systems severely affect west and southwestregions. sometimes the fine dusts transmit to central, north east, and east regions. in this study for investigating dustysynoptical patterns, meteorological data at 5 synoptic s...

background: in order to check the practicality of classification of universities of medical sciences (umss) based on their infrastructures, and scientific contributions, this study explored the most appropriate indicators to measure the size and productivity of umss. methods: in the first phase, we approached a group of experts who had a deep experience in the management of umss and in the mini...

The principle of dimensionality reduction with PCA is the representation of the dataset ‘X’in terms of eigenvectors ei ∈ RN  of its covariance matrix. The eigenvectors oriented in the direction with the maximum variance of X in RN carry the most      relevant information of X. These eigenvectors are called principal components [8]. Ass...

q-mode hierarchical cluster (hca) and principal component analysis (pca) were simultaneously applied to groundwater hydrochemical data from the three times in 2004: june, september, and december, along the ain azel aquifer, algeria, to extract principal factors corresponding to the different sources of variation in the hydrochemistry, with the objective of defining the main controls on the h...

targeted extension for heterogeneous farming systems is a challenge in developing countries. farm type identification and characterization based on estimates of income from different farm components allows simplifying diversity in farming systems. use of multivariate statistical techniques, such as principal component analysis (pca) and cluster analysis (ca), help in such farm typology delineat...

classical lbp such as complexity and high dimensions of feature vectors that make it necessary to apply dimension reduction processes. in this paper, we introduce an improved lbp algorithm to solve these problems that utilizes fast pca algorithm for reduction of vector dimensions of extracted features. in other words, proffer method (fast pca+lbp) is an improved lbp algorithm that is extracted ...

the karnafully is one of the most important rivers due to its profound influence on water chemistry and sediment characteristics. the present study intended to assess the quality of water and sediment from intertidal zone of this river in respect to the pollution index. seasonal water and sediment samples were collected during four seasons (monsoon, post-monsoon, winter, and pre-monsoon) of 201...