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Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites in Baghdad city were used. 70% of these results were used to train the prediction ANN models and the rest were equally divided to test and validate the ANN models. The performance of the developed models was examined using the correlation coefficient R. The final models have demonstrated that the ANN has capability for acceptable prediction of compression index and compression ratio. Two equations were proposed to estimate compression index using the connecting weights algorithm, and good agreements with test results were achieved.

 

 

 

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Publication Date
Fri Jan 01 2016
Journal Name
Ieee Access
Towards an Applicability of Current Network Forensics for Cloud Networks: A SWOT Analysis
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In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

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Publication Date
Fri Jul 01 2022
Journal Name
Journal Of Engineering
Using Water Quality Index to Assess Drinking Water For AL-Muthana Project
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The water quality index is the most common mathematical way of monitoring water characteristics due to the reasons for the water parameters to identify the type of water and the validity of its use, whether for drinking, agricultural, or industrial purposes. The water arithmetic indicator method was used to evaluate the drinking water of the Al-Muthana project, where the design capacity was (40000) m3/day, and it consists of traditional units used to treat raw water. Based on the water parameters (Turb, TDS, TH, SO4, NO2, NO3, Cl, Mg, and Ca), the evaluation results were that the quality of drinking water is within the second category of the requirements of the WHO (86.658%) and the first category of the standard has not been met du

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Publication Date
Fri May 18 2018
Journal Name
International Journal Of Advanced Biological Research
CALCULATION THE AIR POLLUTION TOLERANCE INDEX OF EUCALYPTUS PLANT IN BAGHDAD CITY
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Air pollution from various sources is one of the most serious environmental problems, especially after pollutants are deposited on the surface of the soil and leaves of the plants and then transferred to the rest of the plant and entering food chains. The present study was conducted to determine the effects of air pollution on different biochemical parameters in Eucalyptus sp. and calculation the Air Pollution Tolerance Index. The selected plant leaves were collected from five sites, four of them within the city of Baghdad, namely Al-Jadriya, Al-Andlous, Al-Doura and close to the private generators to represent the urban areas and Abu Ghraib site to represent the rural area. The leaves were taken on a seasonal basis for the period from Octo

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Intelligent Engineering And Systems
Generalized Joint Subcarrier-Time Index Modulation Aided Differential Chaos Shift Keying System
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Publication Date
Tue Oct 30 2018
Journal Name
Https://www.researchgate.net/journal/civil-engineering-journal-2476-3055
Developing Water Quality Index to Assess the Quality of the Drinking Water
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In the present study, an attempt has been to develop a new water quality index (WQI) method that depends on the Iraqi specifications for drinking water (IQS 417, 2009)  to assess the validity of the Euphrates River for drinking by classifying the quality of the river water at different stations along its entire reach inside the Iraqi lands. The proposed classifications by this method are: Excellent, Good, Acceptable, Poor, and Very poor. Eight water quality parameters have been selected to represent the quality of the river water these are: Ion Hydrogen Concentration (pH), Calcium (Ca), Magnesium (Mg), Sodium (Na), Chloride (Cl), Sulphate (SO_4), Nitrate (NO_3), and Total Dissolved Solids (TDS). The variation of the water quality p

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Publication Date
Wed Apr 02 2014
Journal Name
Iraqi Journal Of Physics
The evaluation of left ventricle stiffness index in patients suffering from hypertension
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Many diseases can produce cardiac overload, of these disease hypertension, valve disease congenital anomaly in addition to many other disease. One of the most common diseases causing left ventricle overload is hypertension. A long term hypertension can cause myocardium hypertrophy leading to changes in the cardiac contractility and reduced efficiency. The investigations were carried out using conventional echocardiography techniques in addition to the tissue Doppler imaging (TDI) from which many noninvasive measurements can be readily obtained. The study has involved the effect of hypertension on the myocardium stiffness index through the measurement of early diastolic filling (E) and the early velocity of lateral mitral annulus (E

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Publication Date
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
The evaluation of left ventricle stiffness index in patients suffering from hypertension
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Many diseases can produce cardiac overload, of these disease hypertension, valve disease congenital anomaly in addition to many other disease. One of the most common diseases causing left ventricle overload is hypertension. A long term hypertension can cause myocardium hypertrophy leading to changes in the cardiac contractility and reduced efficiency. The investigations were carried out using conventional echocardiography techniques in addition to the tissue Doppler imaging (TDI) from which many noninvasive measurements can be readily obtained. The study has involved the effect of hypertension on the myocardium stiffness index through the measurement of early diastolic filling (E) and the early velocity of lateral mitral annulus (Ea

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Publication Date
Fri Jul 01 2022
Journal Name
Journal Of Engineering
Using Water Quality Index to Assess Drinking Water For AL-Muthana Project
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The water quality index is the most common mathematical way of monitoring water characteristics due to the reasons for the water parameters to identify the type of water and the validity of its use, whether for drinking, agricultural, or industrial purposes. The water arithmetic indicator method was used to evaluate the drinking water of the Al-Muthana project, where the design capacity was (40000) m3/day, and it consists of traditional units used to treat raw water. Based on the water parameters (Turb, TDS, TH, SO4, NO2, NO3, Cl, Mg, and Ca), the evaluation results were that the quality of drinking water is within the second category of the requirements of the WHO (86.658%) and the first category of the standard has not

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Scopus (5)
Crossref (3)
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Publication Date
Thu Jun 01 2023
Journal Name
Ifip Advances In Information And Communication Technology
Rapid Thrombogenesis Prediction in Covid-19 Patients Using Machine Learning
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Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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