This work implements the face recognition system based on two stages, the first stage is feature extraction stage and the second stage is the classification stage. The feature extraction stage consists of Self-Organizing Maps (SOM) in a hierarchical format in conjunction with Gabor Filters and local image sampling. Different types of SOM’s were used and a comparison between the results from these SOM’s was given.

The next stage is the classification stage, and consists of self-organizing map neural network; the goal of this stage is to find the similar image to the input image. The proposal method algorithm implemented by using C++ packages, this work is successful classifier for a face database consist of 20

The research discusses the obstacles that faced the Iraqi strategic performance in achieving sustainable development after the election of the first Iraqi government in 2005 and the most important strategies to overcome these obstacles.

In The Name of Allah Most Gracious Most Merciful

The reason for choosing this topic was:

First: It is my great love for the Prophet Muhammad, may God’s prayers and peace be upon him, his family, his companions, his followers, the followers of their followers, and the scholars after them until the Day of Judgment.

Secondly: Showing a great jurisprudential figure who has contributed by speaking about important jurisprudential issues in the life of this nation, and bringing out this immortal book to put it in the hands of scholars, so I chose a figure from the followers (may God be pleased with them all).

Third: The study of the jurisprudence of the companions

The zeolite's textural properties have a significant effect on zeolite's effectiveness in the different industrial processes. This research aimed to study the textual properties of the NaX and FeX zeolites using the nitrogen adsorption-desorption technique at a constant low temperature. According to the International Union of Pure and Applied Chemistry, the adsorption-desorption isotherm showed that the studied materials were mixed kinds I/II isotherms and H3 type hysteresis. The Brunauer-Emmett-Teller isotherm was the best model to describe the nitrogen adsorption-desorption better than the Langmuir and Freundlich isotherms. The obtained adsorption capacity and Brunauer-Emmett-Teller surface area values for NaX were greater than FeX. Ac

In the theoretical part, removal of direct yellow 8 (DY8) from water solution was accomplished using Bentonite Clay as an adsorbent. Under batch adsorption, the adsorption was observed as a function of contact time, adsorbent dosage, pH, and temperature. The equilibrium data were fitted with the Langmuir and Freundlich adsorption models, and the linear regression coefficient R2 was used to determine the best fitting isotherm model. thermodynamic parameters of the ongoing adsorption mechanism, such as Gibb's free energy, enthalpy, and entropy, have also been measured. The batch method was also used for the kinetic calculations, and the day's adsorption assumes first-order rate kinetics. The kinetic studies also show that the intrapar

IR, MIR, UV – Visible spectra have been studied for Cobalt chloride molecule (CoCl2. 6H2O) compound, In wide range spectra (40000 – 410) cm-1 specially MIR range. Assignment were achieved for the fundamental vibrational bands of (CoCl2 . 6H2O ) to symmetry stretching ?1 (?^+) Anti – symmetry stretching ?3(?^+), these bands are non-degenerate , and the bending band is ?2(?) is doubly degenerate thought they have activity in IR and Raman , which explain the weakness in symmetry of this molecule, the fundamental bands for the molecule are centered at the following wave numbers (615, 685, 795, 1115, 1340, 1375, 1616.35, 2091, 2386, 2410, 3364) cm-1 which are corresponding to wave lengths (16260, 14598, 12578, 8968, 7462, 7272, 6186,

In data mining, classification is a form of data analysis that can be used to extract models describing important data classes. Two of the well known algorithms used in data mining classification are Backpropagation Neural Network (BNN) and Naïve Bayesian (NB). This paper investigates the performance of these two classification methods using the Car Evaluation dataset. Two models were built for both algorithms and the results were compared. Our experimental results indicated that the BNN classifier yield higher accuracy as compared to the NB classifier but it is less efficient because it is time-consuming and difficult to analyze due to its black-box implementation.