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Estimating Pitting Corrosion Depth and Density on Carbon Steel (C-4130) using Artificial Neural Networks
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The purpose of this research is to investigate the impact of corrosive environment (corrosive ferric chloride of 1, 2, 5, 6% wt. at room temperature), immersion period of (48, 72, 96, 120, 144 hours), and surface roughness on pitting corrosion characteristics and use the data to build an artificial neural network and test its ability to predict the depth and intensity of pitting corrosion in a variety of conditions. Pit density and depth were calculated using a pitting corrosion test on carbon steel (C-4130). Pitting corrosion experimental tests were used to develop artificial neural network (ANN) models for predicting pitting corrosion characteristics. It was found that artificial neural network models were shown to be quite effective; the results were validated by the experimental agreement with those acquired from laboratory tests. Specifically, the correlation coefficient, R = 0.9944.

 

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Publication Date
Sun Aug 06 2023
Journal Name
Journal Of Economics And Administrative Sciences
Probit and Improved Probit Transform-Based Kernel Estimator for Copula Density
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Copula modeling is widely used in modern statistics. The boundary bias problem is one of the problems faced when estimating by nonparametric methods, as kernel estimators are the most common in nonparametric estimation. In this paper, the copula density function was estimated using the probit transformation nonparametric method in order to get rid of the boundary bias problem that the kernel estimators suffer from. Using simulation for three nonparametric methods to estimate the copula density function and we proposed a new method that is better than the rest of the methods by five types of copulas with different sample sizes and different levels of correlation between the copula variables and the different parameters for the function. The

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Using Artificial Intelligence in Analyzing Historical Documents: The Egyptian Libyan Border as a Model (1911–1951)
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Publication Date
Tue Mar 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Semi-parametric regression function estimation for environmental pollution with measurement error using artificial flower pollination algorithm
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Artificial Intelligence Algorithms have been used in recent years in many scientific fields. We suggest employing flower pollination algorithm in the environmental field to find the best estimate of the semi-parametric regression function with measurement errors in the explanatory variables and the dependent variable, where measurement errors appear frequently in fields such as chemistry, biological sciences, medicine, and epidemiological studies, rather than an exact measurement. We estimate the regression function of the semi-parametric model by estimating the parametric model and estimating the non-parametric model, the parametric model is estimated by using an instrumental variables method (Wald method, Bartlett’s method, and Durbin

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Publication Date
Fri Jan 01 2021
Journal Name
Environmental Pollution
Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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Publication Date
Tue Sep 12 2017
Journal Name
Nucl Sci Tech
Investigating the influence of gamma ray energies and steel fiber on attenuation properties of reactive powder concrete
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Publication Date
Tue Sep 12 2017
Journal Name
Nuclear Science And Techniques
Investigating the influence of gamma ray energies and steel fiber on attenuation properties of reactive powder concrete
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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Automated Stand-alone Surgical Safety Evaluation for Laparoscopic Cholecystectomy (LC) using Convolutional Neural Network and Constrained Local Models (CNN-CLM)
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In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

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Publication Date
Tue Feb 01 2022
Journal Name
Journal Of Physics And Chemistry Of Solids
Effect of Sr/Mg co-substitution on corrosion resistance properties of hydroxyapatite coated on Ti–6Al–4V dental alloys
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This study assessed the effect of co-substitution of strontium (Sr) and magnesium (Mg) ions into the hydroxyapatite (HA) coating which was deposited on Ti–6Al–4V dental alloys by an electrochemical deposition process. The deposited layers were examined using energy-dispersive X-ray spectroscopy, scanning electron microscopy, Fourier transform infrared spectroscopy, atomic force microscopy and X-ray diffraction. The corrosion behavior of Ti–6Al–4V alloys in an artificial saliva environment was studied through potentiodynamic polarization technique and electrochemical impedance spectroscopy. The results indicated that the substituted Sr and Mg ions in HA improved the HA coating, where the protection efficiency percentage (PE%) for Ti

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Publication Date
Tue Sep 01 2020
Journal Name
Key Engineering Materials
Push-Out Test of Steel-Concrete-Steel Composite Section for Pre-Installation and Post-Installation Techniques of Shear Connectors
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Composite steel-concrete sections have a broad benefit through increasing structural strength as well as minimizing the self-loads. All past researches were concerned with pre-installed shear connectors (PRSC) in the manufacturing of composite sections. A new fabrication technique for steel-concrete-steel composite sections were presented in the current study by the post-installation shear connectors (POSC) passed-through an embedded polymerizing vinyl chloride (PVC) pipes. The performance of normal strength concrete prisms with a specified strength of 32 MPa connected to square steel tubes (SST) was investigated. Six specimens were fabricated in both methodologies, PRSC and POSC were experimentally tested by Push-out test. The spac

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Publication Date
Fri Feb 13 1998
Journal Name
المجلة العراقية للاحياء المجهرية
EFFECT OF SALTS CONCENTRATIONS AND CARBON SOURCES ON THE GROWTH OF EXTREMELY HALOPHILIC BACTERIA, GENUS Halobacterium
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ABSTRACT The isolation and characterization of (27) isolate of extreme halophilic bacteria was performed ninteen isolate belonged to the genus Halobacterium which included Hb.halobium. Hb. salinarium, Hb. volcanii. Growth curve and generation time in logarthmic phase was measured and found to be (12.8hr±0.32), (11.2hr±0.2), (9.8hr±0.87), respectivaly. Effect of various concentrations of NaCl, KCI, NH4Cl and MgSO4.7H2O was studied, NaCl was essential for the rod shape rapid growth Rat and pigmentation. Less than 1% concentration caused lysis of bacteria. Yeast extract was the best carbone source as compared with glucose and casamino acid.