Yamama Formation is an important sequence in southern Iraq. Petrographic analysis was used to determine and analyze the microfacies and pore types. The diagenetic processes and the impacts on the petrophysical properties of the rocks were also identified. The petrographic identification was based on data of 250 thin sections of cutting and core samples from four wells that were supplied by the Iraqi Oil Exploration Company (O.E.C). The present study focuses on the depositional environment and the microfacies analysis of Yamama Formation. The results revealed several types of microfacies, including peloidal wackestone-packstone, algal wackestone-packstone, bioclastic wackestone-packstone, foraminiferal wackestone, bioclastic wackestone, and mudstone. The latter was divided into two submicrofacies, namely argillaceous lime mudstone and sparse fossiliferous lime mudstone. The study showed that Yamama Formation was deposited through various settings within the carbonate platform; these comprise inner ramp, middle ramp, and outer ramp settings. The inner and middle ramp settings, characterized at the top and middle Formation, have high effective porosity and low clay volume, due to dominant packstone.
Azo dyes like methyl orange (MO) are very toxic components due to their recalcitrant properties which makes their removal from wastewater of textile industries a significant issue. The present study aimed to study their removal by utilizing aluminum and Ni foam (NiF) as anodes besides Fe foam electrodes as cathodes in an electrocoagulation (EC) system. Primary experiments were conducted using two Al anodes, two NiF anodes, or Al-NiF anodes to predict their advantages and drawbacks. It was concluded that the Al-NiF anodes were very effective in removing MO dye without long time of treatment or Ni leaching at in the case of adopting the Al-Al or NiF-NiF anodes, respectively. The structure and surface morphology of the NiF electrode were inves
... Show MoreObjective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using
... Show MoreThe research involves using phenol – formaldehyde (Novolak) resin as matrix for making composite material, while glass fiber type (E) was used as reinforcing materials. The specimen of the composite material is reinforced with (60%) ratio of glass fiber.
The impregnation method is used in test sample preparation, using molding by pressure presses.
All samples were exposure to (Co60) gamma rays of an average energy (2.5)Mev. The total doses were (208, 312 and 728) KGy.
The mechanical tests (bending, bending strength, shear force, impact strength and surface indentation) were performed on un irradiated and irrad
... Show MoreThe current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,
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