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...

This paper reviews and compares two methods for fault detection and isolation in a stochastic setting, assuming additive faults on input and output signals and stochastic unmeasurable disturbances. The first method is the parity space approach, analyzed in a stochastic setting. This leads to Kalman filter like residual generators, but with a FIR filter rather than an IIR filter as for the Kalma...

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...

Traditional mixed livestock cereal- and pasture-based sheep farming systems in Europe are threatened by intensification and specialisation processes. However, the intensification process does not always yield improved economic results or efficiency. This study involved a group of farmers that raised an autochthonous sheep breed (Ojinegra de Teruel) in an unfavourable area of North-East Spain. T...

The relationship between pests and natural enemies using multivariate analysis on cotton in different spacing has not been documented yet. Using multivariate approaches is possible to optimize strategies to control Aphis gossypii at different crop spacings because the possibility of a better use of the aphid sampling strategies as well as the conservation and release of its natural enemies. The...

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...