a procedure for an efficient recovering of reflectance spectra of acrylic paint samples from cie tristimulus color values is described. by fixing a certain criteria based on color difference value, the proposed technique preliminarily selects a series of suitable samples from a main dataset containing the reflectance values of a series of different acrylic paint samples, based on the color spec...

medicinal plant species constitute a considerable part of the flora in iran and play a major role in the composition of plant communities. therefore, it is necessary to recognize the factors leading to the establishment and distribution of vegetation. for data sampling (2012), land units were specified. the plot size was determined using minimal area method and number of plots was determined by...

We examine eight different techniques for developing visual representations in machine vision tasks. In particular we compare different versions of principal component and independent component analysis in combination with stepwise regression methods for variable selection. We found that local methods, based on the statistics of image patches, consistently outperformed global methods based on t...

Advances in data collection and storage have tremendously increased the presence of functional data, whose graphical representations are curves, images or shapes. As a new area of statistics, functional data analysis extends existing methodologies and theories from the realms of functional analysis, generalized linear model, multivariate data analysis, nonparametric statistics, regression model...

Case study of manufacturing of crystalline drug substance was used to see the application of Principal component analysis. Principal Component Analysis (PCA) is one of the multivariate methods of analysis and has been used widely with large multidimensional data sets. PCA involves a mathematical procedure that transforms a number of possible correlated variables into a smaller number of uncorre...

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...