Two field experiments were conducted at two different texture sites. The first site of the fields of AlMed-hateya Agriculture Division / Babil Governorate. The second site of the fields of Al-Nouriah Research Station / Ministry of Agriculture, the factors of the study in the two sites included several factors. The first factor includes two irrigation systems: sprinkler irrigation and surface irrigation. The second factor is the method of cultivation which includes the method of cultivation with basin and furrowing. The third factor is the type of the cultivated crop which includes a local variety (Fajr 3) and a hybrid variety (Drakma). The actual water consumption for the sprinkler irrigation system reached (587.13 and 637.62) mm season-1 f

A two-year study (harvest years 2019 and 2020) was conducted to investigate the effect of a commercially available biofertilizer, in combination with variable nitrogen (N) rate, on bread baking quality and agronomic traits in hard winter wheat grown in conventional (CONV) and organic (ORG) farming systems in Kentucky, USA. The hard red winter wheat cultivar ‘Vision 45’ was used with three N rates (44, 89.6 and 134.5 kg/ha as Low, Med and High, respectively) and three biofertilizer spray regimes (no spray, one spray and two sprays). All traits measured were significantly affected by the agricultural production system (CONV or ORG) and N rate, although trends in their interactions were inconsistent between years. In Y2, yield was

Several correlations have been proposed for bubble point pressure, however, the correlations could not predict bubble point pressure accurately over the wide range of operating conditions. This study presents Artificial Neural Network (ANN) model for predicting the bubble point pressure especially for oil fields in Iraq. The most affecting parameters were used as the input layer to the network. Those were reservoir temperature, oil gravity, solution gas-oil ratio and gas relative density. The model was developed using 104 real data points collected from Iraqi reservoirs. The data was divided into two groups: the first was used to train the ANN model, and the second was used to test the model to evaluate their accuracy and trend stability

In the literature, several correlations have been proposed for hold-up prediction in rotating disk contactor. However,
these correlations fail to predict hold-up over wide range of conditions. Based on a databank of around 611
measurements collected from the open literature, a correlation for hold up was derived using Artificial Neiral Network
(ANN) modeling. The dispersed phase hold up was found to be a function of six parameters: N, vc , vd , Dr , c d m / m ,
s . Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 6.52%
and Standard Deviation (SD) 9.21%. A comparison with selected correlations in the literature showed that the
developed ANN correlation noticeably

Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

The matter of handwritten text recognition is as yet a major challenge to mainstream researchers. A few ways deal with this challenge have been endeavored in the most recent years, for the most part concentrating on the English pre-printed or handwritten characters space. Consequently, the need to effort a research concerning to Arabic texts handwritten recognition. The Arabic handwriting presents unique technical difficulties because it is cursive, right to left in writing and the letters convert its shapes and structures when it is putted at initial, middle, isolation or at the end of words. In this study, the Arabic text recognition is developed and designed to recognize image of Arabic text/characters. The proposed model gets a single l

This study focuses on how tax administrations in Iraq use Artificial Intelligence (AI) techniques to monitor tax evasion for individuals and companies to achieve Tax Compliance (TC). AI was measured through four dimensions: Advanced Data Analytics Techniques (ADAT), Explainable AI (EAI), Machine learning (ML), and Robotic Process Automation (RPA). At the same time, TC was measured through registration, accounting, and tax payment stages. We relied on the questionnaire form to measure the variables. A sample of employees in the General Tax Authority in Iraq was selected, and a questionnaire was distributed to 132 people. The results indicated that the dimensions of AI affect achieving TC at all stages. This study provides evidence of using A

This study aims to reveal the role of one of the artificial intelligence (AI) techniques, “ChatGPT,” in improving the educational process by following it as a teaching method for the subject of automatic analysis for students of the Chemistry Department and the subject of computer security for students of the Computer Science Department, from the fourth stage at the College of Education for Pure Science (Ibn Al-Haitham), and its impact on their computational thinking to have a good educational environment. The experimental approach was used, and the research samples were chosen intentionally by the research community. Research tools were prepared, which included a scale for CT that included 12 items and the achievement test in b

Cutting forces are important factors for determining machine serviceability and product quality. Factors such as speed feed, depth of cut and tool noise radius affect on surface roughness and cutting forces in turning operation. The artificial neural network model was used to predict cutting forces with related to inputs including cutting speed (m/min), feed rate (mm/rev), depth of cut (mm) and work piece hardness (Map). The outputs of the ANN model are the machined cutting force parameters, the neural network showed that all (outputs) of all components of the processing force cutting force FT (N), feed force FA (N) and radial force FR (N) perfect accordance with the experimental data. Twenty-five samp