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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
Tue Jul 15 2025
Journal Name
Smart Innovation, Systems And Technologies
The Role of Artificial Intelligence in Enhancing Translation and Cultural Diversity with Reference English and Arabic Translation
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With the spread of globalization, the need for translators and scholars has grown, as translation is the only process that helps bridge linguistic gaps. Following the emergence of artificial intelligence (AI), a strong competitor has arisen to the translators, sweeping through all scientific and professional fields, including translation sector, with a set of tools that aid in the translation process. The current study aims to investigate the capability of AI tools in translating texts rich in cultural variety from one language to another, specifically focusing on English-Arabic translations, through qualitative analysis to uncover cultural elements in the target language and determine the ability of AI tools to preserve, lose, or alter the

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison between Methods of Laplace Estimators and the Robust Huber for Estimate parameters logistic regression model
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The logistic regression model regarded as the important regression Models ,where of the most interesting subjects in recent studies due to taking character more advanced in the process of statistical analysis .                                                

The ordinary estimating methods is failed in dealing with data that consist of the presence of outlier values and hence on the absence of such that have undesirable effect on the result.    &nbs

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Development an Anomaly Network Intrusion Detection System Using Neural Network
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Most intrusion detection systems are signature based that work similar to anti-virus but they are unable to detect the zero-day attacks. The importance of the anomaly based IDS has raised because of its ability to deal with the unknown attacks. However smart attacks are appeared to compromise the detection ability of the anomaly based IDS. By considering these weak points the proposed
system is developed to overcome them. The proposed system is a development to the well-known payload anomaly detector (PAYL). By
combining two stages with the PAYL detector, it gives good detection ability and acceptable ratio of false positive. The proposed system improve the models recognition ability in the PAYL detector, for a filtered unencrypt

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Enhancement Ear-based Biometric System Using a Modified AdaBoost Method
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          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed

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Publication Date
Wed Feb 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
Supra-Approximation Spaces Using Mixed Degree System in Graph Theory
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This paper is concerned with introducing and studying the o-space by using out degree system (resp. i-space by using in degree system) which are the core concept in this paper. In addition, the m-lower approximations, the m-upper approximations and ospace and i-space. Furthermore, we introduce near supraopen (near supraclosed) d. g.'s. Finally, the supra-lower approximation, supraupper approximation, supra-accuracy are defined and some of its properties are investigated.

Publication Date
Tue Jun 01 2021
Journal Name
Journal Of Engineering Science And Technology
Membrane Fouling Reduction for Reverse Osmosis System Using Zeta Rod
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Reverse osmosis membrane desalination is one of the most significant water treatments that is used to offer freshwater. The aim of this research is to study the effect of controlling the value of the zeta potential on the suspended particles in the water and the proximity of the membrane surfaces in the colloidal solution, to keep the water stable electrically and disperse the colloidal particles. To achieve this aim, the experimental study was conducted in the Sanitary Engineering Laboratory, in the engineering college - University of Baghdad. Two systems were set up, one worked normally and the other worked by using the zeta rod placed before the reverse osmosis membrane. The results showed that the effect of the zeta rod increas

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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Developing of Bacterial Mutagenic Assay System for Detection of Environmental and Food MutagensV – Using Anticancer Drug Cyclophosphamide
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G-system composed of three isolates G3 ( Bacillus),G12 ( Arthrobacter )and G27 ( Brevibacterium) was used to detect the mutagenicity of the anticancer drug, cyclophosphamide (CP) under conditions similar to that used for standard mutagen, Nitrosoguanidine (NTG). The CP effected the survival fraction of isolates after treatment for 15 mins using gradual increasing concentrations, but at less extent comparing to NTG. The mutagenic effect of CP was at higher level than that of NTG when using streptomycin as a genetic marker, but the situation was reversed when using rifampicin resistant as a report marker. The latter effect appeared upon recording the mutagen efficiency (ie., number of induced mutants/microgram of mutagen). Measuring the R

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Publication Date
Tue Sep 30 2025
Journal Name
International Journal On Engineering Applications (irea)
Prediction of Trips Attraction to the Central Business District of Al Nasiriyah City Utilizing an Artificial Neural Network Model
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Estimation of trip attraction and analyzing its main influencing factors are powerful for offering different classifications for business districts and presenting recommendations for improving attractiveness in long term. This is beneficial for designing transportation facilities and infrastructures. The paper presents the prediction of trip attraction using an artificial intelligence technology due to the profits that the technology can possess in shortening time, lowering expenses and saving effort. The new model has utilized six input parameters that have not been considered previously within the area of Nasiriyah city including; age and educational level of the passengers, mode of transport that the passengers use, purpose of the trip,

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Publication Date
Mon May 25 2026
Journal Name
Lettersinbiomathematics
Assessment of Neuromuscular Fatigue in Basketball Players Using Continuous Wavelet Transform Analysis
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The purpose of this paper is to evaluate neuromuscular fatigue among elite basketball players in the Iraqi Basketball League using surface electromyography (sEMG) with the Ultium EMG device and the MR3.18 program, and using the Wavelet analysis application with the Continuous Wavelet Transform (CWT) method. The research sample included six advanced players from the Iraqi Elite League, aged (21.50 ±3.67) years, with a body mass of (80.50 ±11.71) kg, and a height of (189.00 ±7.75) cm. The research sample underwent a physical skill-exertion protocol that simulated the actual playing requirements of basketball, during which the electrical activity of the six selected muscles involved in performing the ski

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Publication Date
Wed Dec 25 2019
Journal Name
Journal Of Engineering
Link Failure Recovery for a Large-Scale Video Surveillance System using a Software-Defined Network
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The software-defined network (SDN) is a new technology that separates the control plane from data ‎plane for the network devices. One of the most significant issues in the video ‎surveillance system is the link failure. When the path failure occurs, the monitoring center cannot receive the ‎video from the cameras. In this paper, two methods are proposed to solve this problem.  The first ‎method uses the Dijkstra algorithm to re-find the path at the source node switch. The second method ‎uses the Dijkstra algorithm to re-find the path at the ingress node switch (or failed link).

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