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Prediction of penetration Rate and cost with Artificial Neural Network for Alhafaya Oil Field
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Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered from five drilled wells were involved in modeling process.Approximatlly,85 % of these data were used for training the ANN models, and 15% to assess their accuracy and direction of stability. The results of the simulation showed good matching between the raw data and the predicted values of ROP by Artificial Neural Network (ANN) model. In addition, a good fitness was obtained in the estimation of drilling cost from ANN method when compared to the raw data.

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Publication Date
Sat Apr 09 2022
Journal Name
Engineering, Technology & Applied Science Research
A Semi-Empirical Equation based on the Strut-and-Tie Model for the Shear Strength Prediction of Deep Beams with Multiple Large Web Openings
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The behavior and shear strength of full-scale (T-section) reinforced concrete deep beams, designed according to the strut-and-tie approach of ACI Code-19 specifications, with various large web openings were investigated in this paper. A total of 7 deep beam specimens with identical shear span-to-depth ratios have been tested under mid-span concentrated load applied monotonically until beam failure. The main variables studied were the effects of width and depth of the web openings on deep beam performance. Experimental data results were calibrated with the strut-and-tie approach, adopted by ACI 318-19 code for the design of deep beams. The provided strut-and-tie design model in ACI 318-19 code provision was assessed and found to be u

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Publication Date
Sat Jan 01 2022
Journal Name
Lecture Notes In Electrical Engineering
Handling Mobility with Network Virtualization in IoT WAVE Context
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Realizing robust interconnectivity in a rapidly changing network topology is a challenging issue. This problem is escalating with the existence of constrained devices in a vehicular environment. Several standards have been developed to support reliable communication between vehicular nodes as the IEEE 1609 WAVE stack. Mitigating the impact of security/mobility protocols on limited capability nodes is a crucial aspect. This paper examines the burden of maintaining authenticity service that associated with each handover process in a vehicular network. Accordingly, a network virtualization-based infrastructure is proposed which tackles the overhead of IEEE 1906 WAVE standard on constrained devices existed in vehicular network. The virtualized

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Publication Date
Mon Jul 01 2019
Journal Name
Iop Conference Series: Materials Science And Engineering
Study of different geostatistical methods to model formation porosity (Cast study of Zubair formation in Luhais oil field)
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Abstract<p>This study is concerned with making comparison in using different geostatistical methods for porosity distribution of upper shale member - Zubair formation in Luhais oil field which was chosen to study.</p><p>Kriging, Gaussian random function simulation and sequential Gaussian simulation geostatistical methods were adopted in this study. After preparing all needed data which are contour map, well heads of 12 wells, well tops and porosity from CPI log. Petrel software 2009 was used for porosity distribution of mentioned formation in methods that are showed above. Comparisons were made among these three methods in order to choose the best one, the comparing cri</p> ... Show More
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Publication Date
Tue Jul 01 2025
Journal Name
Ain Shams Engineering Journal
Deep neural networks for speech enhancement and speech recognition: A systematic review
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Publication Date
Tue Jul 01 2025
Journal Name
Ain Shams Engineering Journal
Deep neural networks for speech enhancement and speech recognition: A systematic review
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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Improvement of Traffic Movement for Roads Network in Al-Kadhimiya City Center
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Numerous regions in the city of Baghdad experience the congestion and traffic problems. Due to the religious and economic significance, Al-Kadhimiya city (inside the metropolitan range of Baghdad) was chosen as study area. The data gathering stage was separated into two branches: the questionnaire method which is utilized to estimate the traffic volumes for the chosen roads and field data collection method which included video recording and manual counting for the volumes entering the selected signal intersections. The stage of analysis and evaluation for the seventeen urban roads, one highway, and three intersections was performed by HCS-2000 software.The presented work plots a system for assessing the level of service

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
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In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

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Publication Date
Mon Oct 22 2018
Journal Name
Journal Of Economics And Administrative Sciences
Performance Appraisal of Human Resource Management and Its Effect on Achieving the Organizational Success -A Field Search at the Ministry of Oil-
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The present study addressed "Performance Appraisal of Human Resource Management and Its Effect on Achieving the Organizational Success", for the topics of performance appraisal of human resource management and the organizational success gained an increasing interest being relatively important and modern topics which had a great effect on the future of organizations.

The study aimed at revealing the pattern of appraising the performance of human resource management for the study sample, and whether it was qualified to lead the ministry towards the organizational success, for this purpose two main hypotheses were formulated: 1) there is a positive significant correlation between both variables: performanc

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Implementation of Neural Control for Continuous Stirred Tank Reactor (CSTR)
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In this paper a dynamic behavior and control of  a jacketed continuous stirred tank reactor (CSTR)  is developed using different control strategies, conventional feedback control (PI and PID), and neural network (NARMA-L2, and NN Predictive) control. The dynamic model for CSTR process is described by a first order lag system with dead time.

The optimum tuning of control parameters are found by two different methods; Frequency Analysis Curve method (Bode diagram) and Process Reaction Curve using the mean of Square Error (MSE) method. It is found that the Process Reaction Curve method is better than the Frequency Analysis Curve method and PID feedback controller is better than PI feedback controller.

The results s

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I
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     In this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used:  local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the

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