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Limits between the Cosmological Parameters from Strong Lensing Observations for Generalized Isothermal Models
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This paper including a gravitational lens time delays study for a general family of lensing potentials, the popular singular isothermal elliptical potential (SIEP), and singular isothermal elliptical density distribution (SIED) but allows general angular structure. At first section there is an introduction for the selected observations from the gravitationally lensed systems. Then section two shows that the time delays for singular isothermal elliptical potential (SIEP) and singular isothermal elliptical density distributions (SIED) have a remarkably simple and elegant form, and that the result for Hubble constant estimations actually holds for a general family of potentials by combining the analytic results with data for the time delay and by using the models of distances.

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Publication Date
Thu Mar 31 2022
Journal Name
Iraqi Geological Journal
Development of Artificial Intelligence Models for Estimating Rate of Penetration in East Baghdad Field, Middle Iraq
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It is well known that the rate of penetration is a key function for drilling engineers since it is directly related to the final well cost, thus reducing the non-productive time is a target of interest for all oil companies by optimizing the drilling processes or drilling parameters. These drilling parameters include mechanical (RPM, WOB, flow rate, SPP, torque and hook load) and travel transit time. The big challenge prediction is the complex interconnection between the drilling parameters so artificial intelligence techniques have been conducted in this study to predict ROP using operational drilling parameters and formation characteristics. In the current study, three AI techniques have been used which are neural network, fuzzy i

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development a Statistical Relationship between Compressional Wave Velocity and Petrophysical Properties from Logs Data for JERIBE Formation ASMARI Reservoir in FAUQI Oil Field
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   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, and

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Publication Date
Thu Sep 30 2021
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Development a Statistical Relationship between Compressional Wave Velocity and Petrophysical Properties from Logs Data for JERIBE Formation ASMARI Reservoir in FAUQI Oil Field
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   The Compressional-wave (Vp) data are useful for reservoir exploration, drilling operations, stimulation, hydraulic fracturing employment, and development plans for a specific reservoir. Due to the different nature and behavior of the influencing parameters, more complex nonlinearity exists for Vp modeling purposes. In this study, a statistical relationship between compressional wave velocity and petrophysical parameters was developed from wireline log data for Jeribe formation in Fauqi oil field south Est Iraq, which is studied using single and multiple linear regressions. The model concentrated on predicting compressional wave velocity from petrophysical parameters and any pair of shear waves velocity, porosity, density, a

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of some methods for estimating the parameters of the binary logistic regression model using the genetic algorithm with practical application
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Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Terramechanics
Interaction of a rigid beam resting on a strong granular layer overlying weak granular soil: Multi-methodological investigations
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In the geotechnical and terramechanical engineering applications, precise understandings are yet to be established on the off-road structures interacting with complex soil profiles. Several theoretical and experimental approaches have been used to measure the ultimate bearing capacity of the layered soil, but with a significant level of differences depending on the failure mechanisms assumed. Furthermore, local displacement fields in layered soils are not yet studied well. Here, the bearing capacity of a dense sand layer overlying loose sand beneath a rigid beam is studied under the plain-strain condition. The study employs using digital particle image velocimetry (DPIV) and finite element method (FEM) simulations. In the FEM, an experiment

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Publication Date
Wed Jan 01 2020
Journal Name
Biochemical & Cellular Archives
CORRELATION STUDY BETWEEN METHIONINE SYNTHASE, CYSTATHIONINE B SYNTHASE WITH CLASSIC PARAMETERS AFTER TREATED WITH JANUVIA IN IRAQI DIABETIC PATIENT'S TYPE 2 AND COMPLICATION.
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This study was aimed to examined effect of Januvia treatment on methionine synthases Meth and cystathionine B- synthase (CBS) in Iraqi patients type2 without treated and another group who taken Januvia treated in addition to diabetic patients with complication without treated with Januvia Also, to found the relationship between these parameters with BMI, FBS, HbA1C and Insulin levels. Firstly, the blood sampling date for this research between December and February 2019 - 2020. Blood sampling was withdrawn from 8:00 to 10:00 in the case of fasting of all substances . five milliliters of venous blood were collected by means of an antecubital venipuncture divided into two parts, one of which (2ml) was put in a tube containing anticoagulant fac

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Publication Date
Sat Feb 14 2026
Journal Name
Philosophy Journal
Philosophy of Civilization Read and critique and analysis of the selected models
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Publication Date
Thu Mar 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Comparison study of Information Criteria to determine the order of Autoregressive models
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بهذا البحث نقارن معاييرالمعلومات التقليدية (AIC , SIC, HQ , FPE ) مع معيارمعلومات الانحراف المحور (MDIC) المستعملة لتحديد رتبة انموذج الانحدارالذاتي (AR) للعملية التي تولد البيانات,باستعمال المحاكاة وذلك بتوليد بيانات من عدة نماذج للأنحدارالذاتي,عندما خضوع حد الخطأ للتوزيع الطبيعي بقيم مختلفة لمعلماته

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Publication Date
Fri Dec 31 2021
Journal Name
Political Sciences Journal
Role of the executive in federal experiences: a study of selected models
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Receipt date:06/23/2020 accepted date:7/15/2020 Publication date:12/31/2021

Creative Commons License This work is licensed under a Creative Commons Attribution 4.0 International License

The executive authority differs from one country to another, as it differs from a federal state to another according to the nature of the applied political systems, so this research focused on federal states according to their political systems, then going into the details of the executive authority and its role In the federal states by referring to the four federal experiments

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Publication Date
Tue Jul 01 2025
Journal Name
Mastering The Minds Of Machines
The Impact of Transfer Learning and Pre-trained Models on Model Performance
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