In this paper, the topic of forecasting the changes in the value of Iraqi crude oil exports for the period from 2019 to 2025, using the Markov transitional series based on the data of the time series for the period from January 2011 to November 2018, is real data obtained from the published data of the Central Agency Of the Iraqi statistics and the Iraqi Ministry of Oil that the results reached indicate stability in the value of crude oil exports according to the data analyzed and listed in the annex to the research.

Keywords: Using Markov chains

      Data mining has the most important role in healthcare for discovering hidden relationships in big datasets, especially in breast cancer diagnostics, which is the most popular cause of death in the world. In this paper two algorithms are applied that are decision tree and K-Nearest Neighbour for diagnosing Breast Cancer Grad in order to reduce its risk on patients. In decision tree with feature selection, the Gini index gives an accuracy of %87.83, while with entropy, the feature selection gives an accuracy of %86.77. In both cases, Age appeared as the  most effective parameter, particularly when Age<49.5. Whereas  Ki67  appeared as a second effective parameter. Furthermore, K- Nearest Neighbor is based on the minimu

In digital images, protecting sensitive visual information against unauthorized access is considered a critical issue; robust encryption methods are the best solution to preserve such information. This paper introduces a model designed to enhance the performance of the Tiny Encryption Algorithm (TEA) in encrypting images. Two approaches have been suggested for the image cipher process as a preprocessing step before applying the Tiny Encryption Algorithm (TEA). The step mentioned earlier aims to de-correlate and weaken adjacent pixel values as a preparation process before the encryption process. The first approach suggests an Affine transformation for image encryption at two layers, utilizing two different key sets for each layer. Th

Efficient and cost-effective drilling of directional wells necessitates the implementation of best drilling practices and advanced techniques to optimize drilling operations. Failure to adequately consider drilling risks can result in inefficient drilling operations and non-productive time (NPT). Although advanced drilling techniques may be expensive, they offer promising technical solutions for mitigating drilling risks. This paper aims to demonstrate the effectiveness of advanced drilling techniques in mitigating risks and improving drilling operations when compared to conventional drilling techniques. Specifically, the advanced drilling techniques employed in Buzurgan Oil Field, including vertical drilling with mud motor, managed pres

The aim of the present research is to investigate the effecting of pH parameter on the feasibility of lead removal from simulated wastewater using an electrochemical system. Electrocoagulation method is one of electrochemical technology which is used widely to treat industrial wastewater. Parameters affecting this operation, such as initial metal concentration, applied current, stirrer speed, and contact time of electroprocessing were taken as 155ppm, 1.5 Ampere, 150 rpm, 60 minutes respectively. While pH of the simulated wastewater was in the range of  2 to 12 in the experiments. It was found from the results that pH is an important parameter affecting lead removal operation. The best value of pH parameter is appro

Microalgae have been increasingly used for wastewater treatment due to their capacity to assimilate nutrients. Samples of wastewater were taken from the Erbil wastewater channel near Dhahibha village in northern Iraq. The microalga Coelastrella sp. was used in three doses (0.2, 1, and 2g. l^-1) in this experiment for 21 days, samples were periodically (every 3 days) analyzed for physicochemical parameters such as pH, EC, Phosphate, Nitrate, and BOD₅, in addition to, Chlorophyll a concentration. Results showed that the highest dose 2g.l^-1 was the most effective dose for removing nutrients, confirmed by significant differences (p≤0.05) between all doses. The highest removal percentage was

Assessing the accuracy of classification algorithms is paramount as it provides insights into reliability and effectiveness in solving real-world problems. Accuracy examination is essential in any remote sensing-based classification practice, given that classification maps consistently include misclassified pixels and classification misconceptions. In this study, two imaginary satellites for Duhok province, Iraq, were captured at regular intervals, and the photos were analyzed using spatial analysis tools to provide supervised classifications. Some processes were conducted to enhance the categorization, like smoothing. The classification results indicate that Duhok province is divided into four classes: vegetation cover, buildings,

This paper aims to study the biosorption for removal of lead, cadmium, copper and arsenic ions using algae as a biosorbent. A series of experiments were carried out to obtain the breakthrough data in a fluidized bed reactor. The minimum fluidization velocities of beds were found to be 2.27 and 3.64 mm/s for mish sizes of 0.4-0.6 and 0.6-1 mm diameters, respectively. An ideal plug flow model has been adopted to characterize the fluidized bed reactor. This model has been solved numerically using MATLAB version 6.5. The results showed a well fitting with the experimental data. Different operating conditions were varied: static bed height, superficial velocity and particle diameter. The breakthrough curves were plotted for each metal. Pb2+ s