Preferred Language
Articles
/
ijcpe-916
Comparison of Estimation Sonic Shear Wave Time Using Empirical Correlations and Artificial Neural Network
...Show More Authors

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data that was adopted by the ANN study was used here where it is comprised of 1922 measured points of SSW and the other nine parameters of Gamma Ray, Compressional Sonic, Caliper, Neutron Log, Density Log, Deep Resistivity, Azimuth Angle, Inclination Angle, and True Vertical Depth from one Iraqi directional well. Three existing empirical correlations are based only on Compressional Sonic Wave Time (CSW) for predicting SSW. In the same way of developing previous correlations, a fourth empirical correlation was developed by using all measured data points of SSW and CSW. A comparison demonstrated that utilizing ANN was better for SSW predicting with a higher R2 equal to 0.966 and lower other statistical coefficients than utilizing four empirical correlations, where correlations of Carroll, Freund, Brocher, and developed fourth had R2 equal to 0.7826, 0.7636, 0.6764, and 0.8016, respectively, with other statistical parameters that show the new developed correlation best than the other three existing. The use of ANN or new developed correlation in future SSW calculations is relevant to decision makers due to a number of limitations and target SSW accuracy.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Thu Oct 01 2020
Journal Name
Biochemical & Cellular Archives
RAPID SPECTROPHOTOMETRIC ESTIMATION OF TRACE AMOUNTS OF MEFENAMIC ACID BASED DISPERSIVE LIQUID-LIQUID MICROEXTRACTION OF IN PHARMACEUTICAL PREPARATIONS.
...Show More Authors

A dispersive liquid-liquid microextraction combines with UV-V is spectrophotometry for the preconcentration and determination of Mefenamic acid in pharmaceutical preparation was developed and introduced. The proposed method is based on the formation of charge transfer complexation between mefenamic acid and chloranil as an n-electron donor and a p-acceptor, respectively to form a violet chromogen complex measured at 542 nm. The important parameters affecting the efficiency of DLLME were evaluated and optimized. Under the optimum conditions, the calibration graphs of standard and drug, were ranged 0.03-10 µg mL-1. The limits of detection, quantification and Sandell's sensitivity were calculated. Good recoveries of MAF Std. and drug at 0.05,

... Show More
Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Sum Rate Maximization Versus MSE Minimization in FDD Massive MIMO Systems With Short Coherence Time
...Show More Authors

View Publication
Scopus (11)
Crossref (11)
Scopus Clarivate Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Ieee Transactions On Human-machine Systems
Myoelectric Control With Fixed Convolution-Based Time-Domain Feature Extraction: Exploring the Spatio–Temporal Interaction
...Show More Authors

View Publication
Scopus (36)
Crossref (36)
Scopus Clarivate Crossref
Publication Date
Mon Sep 07 2026
Journal Name
Twms Journal Of Applied And Engineering Mathematics
THE QUANTILE GARCH-DISTRIBUTED LAG (QGDL) FRAMEWORK: A UNIFIED MODEL FOR HIGH-VOLATILITY TIME SERIES
...Show More Authors

TWMS Journal of Applied and Engineering Mathematics | Volume: 16 Issue: 9

View Publication Preview PDF
Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
...Show More Authors

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

... Show More
View Publication
Crossref
Publication Date
Mon Dec 01 2025
Journal Name
Sensors And Actuators A: Physical
IoT based hybrid optical-wireless microstructured optical fiber sensor network for cadmium ions detection
...Show More Authors

View Publication
Scopus (1)
Crossref (1)
Scopus Crossref
Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Engineering
Deterioration Model for Sewer Network Asset Management in Baghdad City (case study Zeppelin line)
...Show More Authors

Asset management involves efficient planning of economic and technical performance characteristics of infrastructure systems. Managing a sewer network requires various types of activities so the network can be able to achieve a certain level of performance. During the lifetime of the network various components will start to deteriorate leading to bad performance and can damage the infrastructure. The main objective of this research is to develop deterioration models to provide an assessment tool for determining the serviceability of the sewer networks in Baghdad city the Zeppelin line was selected as a case study, as well as to give top management authorities the appropriate decision making. Different modeling techniques

... Show More
View Publication Preview PDF
Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Functionalized multi-walled carbon nanotubes network sensor for NO2 gas detection at room temperature
...Show More Authors

View Publication
Scopus (7)
Crossref (7)
Scopus Clarivate Crossref
Publication Date
Tue Oct 20 2026
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Modified LASS Method Suggestion as an additional Penalty on Principal Components Estimation – with Application-
...Show More Authors

This research deals with a shrinking method concernes with the principal components similar to that one which used in the multiple regression “Least Absolute Shrinkage and Selection: LASS”. The goal here is to make an uncorrelated linear combinations from only a subset of explanatory variables that may have a multicollinearity problem instead taking the whole number say, (K) of them. This shrinkage will force some coefficients to equal zero, after making some restriction on them by some "tuning parameter" say, (t) which balances the bias and variance amount from side, and doesn't exceed the acceptable percent explained variance of these components. This had been shown by MSE criterion in the regression case and the percent explained v

... Show More
View Publication Preview PDF
Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
Comparison of Properties of Various Heat Storage Fluids used with Evacuated Tube of Solar Water Heater
...Show More Authors

The aim of this work was to capture solar radiation and convert it into solar thermal energy by using a storage material and the heat transfer fluid like oil and water and comparison between them, we used the evacuated tube as a receiver for solar radiation, The results showed that the oil better than water as storage material and the heat transfer fluid and the effective thermal conductivity material and good for power level, rates and durations of charge and discharge cycles.

View Publication Preview PDF
Crossref