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Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parameters. A databases from one well drilled in carbonate environments were subjected to the predictive methods. Each raw dataset is described by eight parameters including rate of penetration (ROP), true vertical depth (TVD), weight on bit (WOB), bit rotational speed (RPM), torque (TQ), flow rate (Q), equivalent circulating density (ECD), standpipe pressure (SPP), and unconfined compressive strength (UCS). First, both MRA and ANNs are tested as predictive methods. The prediction capacity of each model was also verified by using two-based error metrics: the determination coefficient (R2) and the mean square error (MSE).</p><p>The current results support the evidence that MRA and ANNs are able to be effectively utilize the drilling data, and thus provide accurate ROP prediction. However, more attention to the multiple regression analysis is required where it is implemented for ROP prediction. ANNs appear to be more conservative in predicting ROP than MRA as indicated by a higher value R2 (0.96) and lower value MSE (1.89) of the ANN model. Considering the input parameters, the obtained results showed that TVD, WOB, RPM, SPP, and ECD had the greatest effect on estimated ROP-conditions, followed in decreasing by pump flow rate, drilling torque, and rock strength. Another important point that highlights in this study is that the drilling rate may increase with depth in carbonate rocks because of their heterogeneity. This study presents new models to estimate ROP from other parameters which can help the driller to achieve an optimal drilling rate through monitoring controllable parameters.</p>
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Publication Date
Sun Mar 03 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
Using Information Technology for Comprehensive Analysis and Prediction in Forensic Evidence
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With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

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Publication Date
Fri Sep 16 2022
Journal Name
Sustainability
Intellectual Capital History and Trends: A Bibliometric Analysis Using Scopus Database
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This article aims to provide a bibliometric analysis of intellectual capital research published in the Scopus database from 1956 to 2020 to trace the development of scientific activities that can pave the way for future studies by shedding light on the gaps in the field. The analysis focuses on 638 intellectual capital-related papers published in the Scopus database over 60 years, drawing upon a bibliometric analysis using VOSviewer. This paper highlights the mainstream of the current research in the intellectual capital field, based on the Scopus database, by presenting a detailed bibliometric analysis of the trend and development of intellectual capital research in the past six decades, including journals, authors, countries, inst

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Publication Date
Mon Apr 01 2024
Journal Name
Wasit Journal Of Engineering Sciences
Analysis attackers’ methods with hashing secure password using CSPRNG and PBKDF2
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Using the Internet, nothing is secure and as we are in need of means of protecting our data, the use of passwords has become important in the electronic world. To ensure that there is no hacking and to protect the database that contains important information such as the ID card and banking information, the proposed system stores the username after hashing it using the 256 hash algorithm and strong passwords are saved to repel attackers using one of two methods: -The first method is to add a random salt to the password using the CSPRNG algorithm, then hash it using hash 256 and store it on the website. -The second method is to use the PBKDF2 algorithm, which salts the passwords and extends them (deriving the password) before being ha

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Publication Date
Mon Sep 01 2014
Journal Name
Paripex-indian Journal Of Research
Inundation Map Development by Using HEC-RAS Hydraulic Simulation Modeling from Roseires to Khartoum Cities
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Inundation floodingmap aimedto find outearly warningsto avoidenvironmental damageandhumanin terms of theheight ofthe wave ofwater, speed time arrival, effects of inundation sideanddepth of the water/ distanceand reduce the impact of the flood wave after obtaining the process of collapse of the dam in the lower part of the river to the dam area. The study has been using a numerical model one-dimensional depends on the development of equations (Saint-Venant) so that parts of the river, any river channel main banks of the right and left treated as separate parts, that’s the difference in the characteristics of the hydraulic and engineering, along the line of the flow will take into account in each section of the sections and flow in the riv

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Publication Date
Thu Jun 28 2018
Journal Name
2018 4th International Conference On Computer And Technology Applications (iccta)
Improving accuracy of CADx system by hybrid PCA and backpropagation
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—Medical images have recently played a significant role in the diagnosis and detection of various diseases. Medical imaging can provide a means of direct visualization to observe through the human body and notice the small anatomical change and biological processes associated by different biological and physical parameters. To achieve a more accurate and reliable diagnosis, nowadays, varieties of computer aided detection (CAD) and computer-aided diagnosis (CADx) approaches have been established to help interpretation of the medical images. The CAD has become among the many major research subjects in diagnostic radiology and medical imaging. In this work we study the improvement in accuracy of detection of CAD system when comb

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of Some Methods for Estimating Mixture of Linear Regression Models with Application
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 A mixture model is used to model data that come from more than one component. In recent years, it became an effective tool in drawing inferences about the complex data that we might come across in real life. Moreover, it can represent a tremendous confirmatory tool in classification observations based on similarities amongst them. In this paper, several mixture regression-based methods were conducted under the assumption that the data come from a finite number of components. A comparison of these methods has been made according to their results in estimating component parameters. Also, observation membership has been inferred and assessed for these methods. The results showed that the flexible mixture model outperformed the others

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Regression shrinkage and selection variables via an adaptive elastic net model
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Abstract<p>In this paper, a new method of selection variables is presented to select some essential variables from large datasets. The new model is a modified version of the Elastic Net model. The modified Elastic Net variable selection model has been summarized in an algorithm. It is applied for Leukemia dataset that has 3051 variables (genes) and 72 samples. In reality, working with this kind of dataset is not accessible due to its large size. The modified model is compared to some standard variable selection methods. Perfect classification is achieved by applying the modified Elastic Net model because it has the best performance. All the calculations that have been done for this paper are in </p> ... Show More
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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Mathematical Modeling and Kinetics of Removing Metal Ions from Industrial Wastewater
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The study's objective is to produce Nano Graphene Oxide (GO) before using it for batch adsorption to remove heavy metals (Cadmium Cd+2, Nickel Ni+2, and Vanadium V+5) ions from industrial wastewater. The temperature effect (20-50) °C and initial concentration effect (100-800) mg L-1 on the adsorption process were studied. A simulation aqueous solution of the ions was used to identify the adsorption isotherms, and after the experimental data was collected, the sorption process was studied kinetically and thermodynamically. The Langmuir, Freundlich, and Temkin isotherm models were used to fit the data. The results showed that Cd, Ni, and V ions on the GO adsorbing surface matched the Langmuir model with correlation coefficients (R2)

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Publication Date
Thu Nov 21 2019
Journal Name
Al-kindy College Medical Journal
Magnetic Resonance Venography Findings In A Group Of Patients With Multiple Sclerosis
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Background: Multiple sclerosis is a chronic heterogeneous demyelinating axonal and inflammatory disease involving the Central Nervous System [CNS] white matter with a possibility of gray matter involvement in which the insulating covers of nerve cells in the brain and spinal cord are damaged. This damage disrupts the ability of parts of the nervous system to communicate, resulting in a wide range of signs and symptoms. Cerebral venous insufficiency theory was raised as a possible etiology for the disease at 2008 by Zamboni an Italian cardiothoracic surgeon. This theory was defeated by Multiple Sclerosis[ MS] researchers and scientists who thought that the disease is an autoimmune rather than vascular.

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