In this paper a decoder of binary BCH code is implemented using a PIC microcontroller for code length n=127 bits with multiple error correction capability, the results are presented for correcting errors up to 13 errors. The Berkelam-Massey decoding algorithm was chosen for its efficiency. The microcontroller PIC18f45k22 was chosen for the implementation and programmed using assembly language to achieve highest performance. This makes the BCH decoder implementable as a low cost module that can be used as a part of larger systems. The performance evaluation is presented in terms of total number of instructions and the bit rate.

         In this study some generic commercial products of Atorvastatin tablets were evaluated by dissolution test in acid medium by comparing with that of parent drug Lipitor of Pfizer Company. Some of solubilizing agents were studied in formulation  of Atorvastatin tablet including;  surface active agent  and PEG 6000 .The most effective factor was the  use of PEG6000 in formulation of Atorvastatin tablet which improved the dissolution and the results of dissolution profile of formulated tablet in this work  was bioequivalent to that of Lipitor .The quantitative analysis of this work was performed by using reversed phase liquid chromatography and a proper mixture of &nbsp

Different solvents (light naphtha, n-heptane, and n-hexane) are used to treat Iraqi Atmospheric oil residue by the deasphalting process. Oil residue from Al-Dura refinery with specific gravity 0.9705, API 14.9, and 0.5 wt. % sulfur content was used. Deasphalting oil (DAO) was examined on a laboratory scale by using solvents with different operation conditions (temperature, concentration of solvent, solvent to oil ratio, and duration time). This study investigates the effects of these parameters on asphaltene yield. The results show that an increase in temperature for all solvents increases the extraction of asphaltene yield. The higher reduction in asphaltene content is obtained with hexane solvent at operating conditions of (90 °C, 4/1

يقترح هذا البحث طريقة جديدة لتقدير دالة كثافة الرابطة باستخدام تحليل المويجات كطريقة لامعلمية، من أجل الحصول على نتائج أكثر دقة وخالية من مشكلة تاثيرات الحدود التي تعاني منها طرائق التقدير اللامعلمية. اذ تعد طريقة المويجات طريقة اوتماتيكية للتعامل مع تاثيرات الحدود وذلك لانها لا تأخذ بنظر الاعتبار إذا كانت السلسلة الزمنية مستقرة او غير مستقرة. ولتقدير دالة كثافة الرابطة تم استعمال المحاكاة لتوليد البي

In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

For desulfurization of naphtha, NaY zeolite was prepared from Dewekhala kaolin clay (Al-Anbar region). For the prepared zeolite adsorbent, x-ray diffraction, sodium content, silica to alumina ratio, surface area, bulk density and crushing strength were determined. From the x-ray diffraction of the prepared NaY zeolite and by a comparison with the standard NaY zeolite, it was found that the prepared adsorbent in this work has approximately the same crystal structure as the standard. Adsorption process was done in a laboratory unit at 25

In this article, the high accuracy and effectiveness of forecasting global gold prices are verified using a hybrid machine learning algorithm incorporating an Adaptive Neuro-Fuzzy Inference System (ANFIS) model with Particle Swarm Optimization (PSO) and Gray Wolf Optimizer (GWO). The hybrid approach had successes that enabled it to be a good strategy for practical use. The ARIMA-ANFIS hybrid methodology was used to forecast global gold prices. The ARIMA model is implemented on real data, and then its nonlinear residuals are predicted by ANFIS, ANFIS-PSO, and ANFIS-GWO. The results indicate that hybrid models improve the accuracy of single ARIMA and ANFIS models in forecasting. Finally, a comparison was made between the hybrid foreca