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Geomechanical Modeling and Artificial Neural Network Technique for Predicting Breakout Failure in Nasiriyah Oilfield
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Wellbore instability is one of the major issues observed throughout the drilling operation. Various wellbore instability issues may occur during drilling operations, including tight holes, borehole collapse, stuck pipe, and shale caving. Rock failure criteria are important in geomechanical analysis since they predict shear and tensile failures. A suitable failure criterion must match the rock failure, which a caliper log can detect to estimate the optimal mud weight. Lack of data makes certain wells' caliper logs unavailable. This makes it difficult to validate the performance of each failure criterion. This paper proposes an approach for predicting the breakout zones in the Nasiriyah oil field using an artificial neural network. It also presents the optimal mud weight window for this field, which can be used to optimise the mud weights to minimise the wellbore instability issues. The results showed that an artificial neural network is a powerful tool for determining the breakout zones using the input data. The obtaining root mean square error and the determination coefficient were respectively 0.0082 and 0.959, by which the 1D MEM gave a high match between the predicted wellbore instabilities using the Mogi-failure criterion and the predicted breakout using the ANN model. Most borehole enlargements occur due to formation shear failures because of using low mud weights during drilling. The conclusion clarify the1.35 g/cc is the optimal mud weights for drilling new wells in this field of interest with fewer drilling issues.

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Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
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Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

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Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
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Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

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Publication Date
Tue Oct 10 2023
Journal Name
2023 3rd International Conference On Emerging Smart Technologies And Applications (esmarta)
Perceived Trust of Stakeholders: Predicting the Use of COBIT 2019 to Reduce Information Asymmetry
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Perceived Trust of Stakeholders: Predicting the Use of COBIT 2019 to Reduce Information Asymmetry

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Reservoir permeability prediction based artificial intelligence techniques
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   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

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Publication Date
Sun Jan 02 2011
Journal Name
Al-khwarizmi Engineering Journal
Biomechanical Concept Design of Artificial Human Hand
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This work is focused on the design parameters and activity of artificial human finger for seven grips. At first, obtained the ideal kinematics of human fingers motion by analyzing the grips video which were recorded using a single digital camera recorder fitted on a tripod in sagital plane while the hand is moving. Special motion analysis software (Dartfish) the finger joint angles were studied using the video recording. Then the seven grips were modeled using static torque analysis, which calculates the amount of torque applied on the fingers joint grip depending on the results of the kinematic analysis. The last step of the work was to design the actuator (Muscle Wire) of artificial finger for the seven grips in a simple design approac

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Diagnosis of Diabetes Using Artificial Intelligence Programs
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Scientific development has occupied a prominent place in the field of diagnosis, far from traditional procedures. Scientific progress and the development of cities have imposed diseases that have spread due to this development, perhaps the most prominent of which is diabetes for accurate diagnosis without examining blood samples and using image analysis by comparing two images of the affected person for no less than a period. Less than ten years ago they used artificial intelligence programs to analyze and prove the validity of this study by collecting samples of infected people and healthy people using one of the Python program libraries, which is (Open-CV) specialized in measuring changes to the human face, through which we can infer the

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Publication Date
Thu Jan 01 2009
Journal Name
Computer And Information Science 2009
The Stochastic Network Calculus Methodology
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Home Computer and Information Science 2009 Chapter The Stochastic Network Calculus Methodology Deah J. Kadhim, Saba Q. Jobbar, Wei Liu & Wenqing Cheng Chapter 568 Accesses 1 Citations Part of the Studies in Computational Intelligence book series (SCI,volume 208) Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad

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Publication Date
Wed Jun 01 2022
Journal Name
Iranian Journal Of Chemistry And Chemical Engineering
The Thermal Pre-processing Technique of the Bio-waste for Contaminated Water Treatment: Histological and Experimental Study
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The current study suggested a thermal treatment as a necessary proactive step in improving the adsorption capacity of bio-waste for contaminants removal in wastewater. This approach was based on the experimental and histological investigation of biowaste pods shell. This investigation showed that these shells compose of parenchyma cells that store secondary metabolites compounds produced from cells were exhibited in present study. The results also reported that these compounds are extracted directly from the cells as soon as they are exposed to an aqueous solution, hampering their use as an adsorbent material. The increase in the weight of bio-waste adsorbent at unit liquid volume increases the production of secondary metabolites compounds

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Publication Date
Tue Jan 01 2013
Journal Name
Journal Of The College Of Basic Education
Study the spectral reflectance and factor affecting they for the dominate land cover by using remote sensing technique in Abu-Gharib projection
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Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.

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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Study the Spectral reflectance and factor affecting they for the dominate land cover by using remote sensing technique in Abu-Gharib projection.
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Image of landsate-7 taken by thematic mapper was used and classified using supervised method. Results of supervised classification indicated presence of nine land cover classes. Salt-soils class shows the highest reflectance value while water bodies' class shows the lowest values. Also the results indicated that soil properties show different effects on reflectance. There was a high significant positive relation of carbonate, gypsum, electric conductivity and silt content, while there was a week positive relation with sand and negative relation with organic matter, water content, bulk density and cataion exchange capacity.

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