This research aims to clarify the advantages of using the regression method as analytical procedure in the tax audit to reducing the examination cost , time, effort, human and material resources, and represents an applied study in the General Commission of taxes. In order to achieve its objectives the research has used in the theoretical side the descriptive approach (analytical), and in the practical side regression method has been applied to the research sample represented by the soft drinks company that is subject to the tax settlement for the year 2014, where the value of sales has been verified by using the regression method without conductinga comprehensive examination. The most important results of the research indicate that the r

   The present research was conducted to synthesis Y-Zeolite by sol-gel technique using MWCNT (multiwalled carbon nanotubes) as crystallization medium to get a narrow range of particle size distribution with small average size compared with ordinary methods. The phase pattern, chemical structure, particle size, and surface area were detected by XRD, FTIR, BET and AFM, respectively. Results shown that the average size of Zeolite with and without using MWCNT were (92.39) nm and (55.17) nm respectively .Particle size range reduced from (150-55) nm to (130-30) nm. The surface area enhanced to be (558) m²/g with slightly large pore volume (0.231) km³/g was obtained. Meanwhile, degree of crystallization decrease

A total of 37 Staphylococcus epidermidis isolates, isolated from corneal scraping of patients with bacterial keratitis and 20 isolates from healthy eyes (as control) (all isolates, isolated from, Ibn Al- Haietham eye hospital / Baghdad), were tested for slime production, 52.63% of all isolates were positive-slime production (23 isolates from patients and 7 isolates from controls). It was found that positive-slime producing S. epidermidis were exhibited a high resistance to antibiotics as compared to negative-slime producing isolates.

The purpose of this preliminary study is to verify the possibility of using Iraqi Zahdi date palm biomass as a resource for biogas production, methane in particular using thermophilic anaerobic digestion with waste water treatment activated sludge. Moreover, is to investigate the influence of extra nutrients addition to the digestion mixture. Biogas was captured in sealed jars with remote sensing modules connected to computer with integrated program to record the gas pressure continuously. A total gas pressure with 67% Methane was produced from date pulp waste fermentation with a yield of 0.57 Lit for each gram volatile solid of substrate. Addition of 1% yeast extract solution as nutrient increased Methane yield in liters by 5.9%. This i

This study investigates the digestion of cow dung (CD) for biogas production at laboratory scales. The study was carried out through anaerobic fermentation using cow dung as substrate. The digester was operated at ambient temperatures of 39.5 °C for a period of 10 days. The effect of iron powder in controlling the production of hydrogen sulfide (H2S) has been tested. The optimum concentration of iron powder was 4g/L with the highest biogas production. A Q – swatch Nd:YAG laser has been used to mix and homogenize the components of one of the six digesters and accelerate digestion. At the end of digestion, all digestions effluent was subjected to 5 laser pulses with 250mJ/pules to dispose waste biomass.

В статье рассматривается вопрос об использовании мультимедийных средств для оптимизации процесса формирования коммуникативной компетенции  в иракской аудитории с привлечением компьютерных технологий. Статья посвящена  использованию мультимедийных технологий  и  различных  приемов формирования интереса к русскому языку. Включение в процесс обучения коммуникативно-значимого, аутентичн

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m