Feature extraction is a very important preprocessing step for classification of hyperspectral images. The linear discriminant analysis (LDA) method fails to work in small sample size situations. Moreover, LDA has poor efficiency for non-Gaussian data. LDA is optimized by a global criterion. Thus, it is not sufficiently flexible to cope with the multi-modal distributed data. We propose a new fea...

efficient mode shape extraction of fluid-structure systems is of particular interest in engineering. an efficient modified version of unsymmetric lanczos method is proposed in this paper. the original unsymmetric lanczos method was applied to general form of unsymmetric matrices, while the proposed method is developed particularly for the fluid-structure matrices. the method provides us with si...

The applications of machine learning and data analysis are rapidly increases. In such kind of applications multimedia data is compared for storage. In addition of that during retrieval and search a significant amount of resources are consumed by these methods. Nowadays various applications are available that claim to extract the accurate information from such colored image databases with less c...

The effects and influences of various operational parameters on the efficiency of mixer-settlers are thoroughly studied in this paper. One of the most important factors in designing a mixer-settler is to obtain an optimum operational extraction and overall efficiency. These two factors are dependent on various parameters such as impeller shape, size and speed of impeller, baffle size, residence...

Improvement of light extraction efficiency of InGaN light emitting diodes (LEDs) using polydimethylsiloxane (PDMS) concave microstructures arrays was demonstrated. The size effect of the concave microstructures on the light extraction efficiency of III-Nitride LEDs was studied. Depending on the size of the concave microstructures, ray tracing simulations show that the use of PDMS concave micros...