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kRhqLJQBVTCNdQwChgOI
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
Thu Mar 01 2007
Journal Name
Al-khwarizmi Engineering Journal
The Inverse Solution Of Dexterous Robot By Using Neural Networks
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The inverse kinematics of redundant manipulators has infinite solutions by using conventional methods, so that, this work presents applicability of intelligent tool (artificial neural network ANN) for finding one desired solution from these solutions. The inverse analysis and trajectory planning of a three link redundant planar robot have been studied in this work using a proposed dual neural networks model (DNNM), which shows a predictable time decreasing in the training session. The effect of the number of the training sets on the DNNM output and the number of NN layers have been studied. Several trajectories have been implemented using point to point trajectory planning algorithm with DNNM and the result shows good accuracy of the end

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Publication Date
Mon Jan 01 2024
Journal Name
Aims Mathematics
Solving quaternion nonsymmetric algebraic Riccati equations through zeroing neural networks
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<abstract><p>Many variations of the algebraic Riccati equation (ARE) have been used to study nonlinear system stability in the control domain in great detail. Taking the quaternion nonsymmetric ARE (QNARE) as a generalized version of ARE, the time-varying QNARE (TQNARE) is introduced. This brings us to the main objective of this work: finding the TQNARE solution. The zeroing neural network (ZNN) technique, which has demonstrated a high degree of effectiveness in handling time-varying problems, is used to do this. Specifically, the TQNARE can be solved using the high order ZNN (HZNN) design, which is a member of the family of ZNN models that correlate to hyperpower iterative techniques. As a result, a novel

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Publication Date
Tue Jan 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Facial Emotion Recognition from Videos Using Deep Convolutional Neural Networks
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Its well known that understanding human facial expressions is a key component in understanding emotions and finds broad applications in the field of human-computer interaction (HCI), has been a long-standing issue. In this paper, we shed light on the utilisation of a deep convolutional neural network (DCNN) for facial emotion recognition from videos using the TensorFlow machine-learning library from Google. This work was applied to ten emotions from the Amsterdam Dynamic Facial Expression Set-Bath Intensity Variations (ADFES-BIV) dataset and tested using two datasets.

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Publication Date
Tue Jun 01 2021
Journal Name
2021 Ieee/cvf Conference On Computer Vision And Pattern Recognition Workshops (cvprw)
Alps: Adaptive Quantization of Deep Neural Networks with GeneraLized PositS
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Publication Date
Tue Mar 16 2021
Journal Name
2021 4th International Conference On Energy Conservation And Efficiency (icece)
Finite Element Modeling Of Finned Double-Pass Solar Air Heaters
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Publication Date
Sun Jan 08 2017
Journal Name
International Journal Of Information Technology And Computer Science
Adaptive Modeling of Urban Dynamics during Armada Event using CDRs
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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Analytical Performance Modeling of InP-InGaAs Hetero-junction Avalanche Photodiode
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In this study, an analytical model depending on experimental results for InPInGaAs
avalanche photodiode at low bias was presented and the characteristics of
gain for this photodiode were determined directly by the impulse response. The
model have considered the most important mechanisms contributing the
photocurrent, they are trapping, photogeneration in the undepleted region and
charge-carriers velocity due to the built-in electrical field. Also, the bandwidth
was determined as a function to the total gain of photodiode and it was mainly
determined by diffusion and trapping processes at low gain regarding to the multilayer
structure considered in this study

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Improving Building Information Modeling (BIM) Implementation throughout the Construction Industry
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Building Information Modeling (BIM) is extensively used in the construction industry due to its benefits throughout the Project Life Cycle (PLC). BIM can simulate buildings throughout PLC, detect and resolve problems, and improve building visualization that contributes to the representation of actual project details in the construction stage. BIM contributes to project management promotion by detecting problems that lead to conflicts, cost overruns, and time delays. This work aims to implement an effective BIM for the Iraqi construction projects’ life cycle. The methodology used is a literature review to collect the most important factors contributing to the success of BIM implementation, interview the team of the Cent

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI)
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This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

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Publication Date
Mon Dec 01 2025
Journal Name
Journal Of University Of Anbar For Pure Science
Mobile ad hoc network wireless security: problems, solutions, and application: state-of-the-art
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