Thesis

One of the main purposes of remote sensing satellite images is to interpret the observed data and classify features. Satellite image classification plays a major role in the extraction and interpretation of valuable information from massive satellite images.The primary purpose of this research is to classify multi-spectral Thematic Mapper satellite images using supervised classification. Unsupervised (RGB color model) and supervised classification (maximum likelihood method) is adopted to achieve the classification purpose.

Atoms and molecules are the fundamental constituents of materials and they are the main key that can open the door to understand the materials’ structures and dynamics. The goal of a computational atomic and molecular physics is to determine numerical solutions of approximate equations. All measurable properties of the atoms and molecules can be obtained by these solutions.In the present work, accurate treatments for both non-relativistic quantum mechanics and relativistic quantum mechanics have been presented.

          The interacting boson model (IBM) has been used to make a schematic study of (^172-180Hf and ^180-190W) isotopes. For each isotope of Hafnium and Tungsten determined the values of the parameters in the Hamiltonian of IBM-1 and IBM-2, which satisfied the best fit to the experimental data for energy levels. Beside on these values, can extrapolate to isotopes are extrapolated for which no experimental data founded and can make predictions for future experiments.

 The nuclear structure  and electromagnetic transitions of even–even neutronrich 120–148Ba isotopes was studied in the framework of the collective models Interacting Boson Model (IBM-1 and IBM-2) and Dynamic Deformation Model (DDM). The reduced transition probabilities B(E2), B(M1), monopole matrix element )0(E , mixing ratio )1/2( ME  and )2/0( EEX  of these isotopes was calculated. A set of parameters was used in the calculation to approach the values with the measured data.