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Prediction of Smear Effect on the Bearing Capacity of Driven Piles
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This paper deals with prediction the effect of soil remoulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity
according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil remoulding due to actual pile driving. The results of the tests exhibited that the pile might loss 14% of its ultimate capacity when it is loaded immediately after installation. Also, it was concluded that the pile may regain of about 9% of its original capacity after 30days of its installation.

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Publication Date
Mon Oct 03 2016
Journal Name
International Journal Of Civil Engineering
Development of Excess Pore Water Pressure around Piles Excited by Pure Vertical Vibration
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Publication Date
Wed Sep 01 2021
Journal Name
Iop Conference Series: Earth And Environmental Science
Response of Piles Group embedded in Sandy Soil with Cavities to Seismic Loading
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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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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
The Prediction of COVID 19 Disease Using Feature Selection Techniques
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Abstract<p>COVID 19 has spread rapidly around the world due to the lack of a suitable vaccine; therefore the early prediction of those infected with this virus is extremely important attempting to control it by quarantining the infected people and giving them possible medical attention to limit its spread. This work suggests a model for predicting the COVID 19 virus using feature selection techniques. The proposed model consists of three stages which include the preprocessing stage, the features selection stage, and the classification stage. This work uses a data set consists of 8571 records, with forty features for patients from different countries. Two feature selection techniques are used in </p> ... Show More
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Publication Date
Mon Dec 24 2018
Journal Name
Civil Engineering Journal
Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be

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Publication Date
Thu Dec 27 2018
Journal Name
International Journal Of Hydrogen Energy
Compressional wave velocity of hydrate-bearing bentheimer sediments with varying pore fillings
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A potential alternative energy resource to meet energy demands is the vast amount of gas stored in hydrate reserves. However, major challenges in terms of exploration and production surround profitable and effective exploitation of these reserves. The measurement of acoustic velocity is a useful method for exploration of gas hydrate reserves and can be an efficient method to characterize the hydrate-bearing sediments. In this study, the compressional wave velocity (P-wave velocity) of consolidated sediments (Bentheimer) with and without tetrahydrofuran hydrate-bearing pore fillings were measured using the pulse transmission method. The study has found that the P-wave velocity of consolidated sediments increase with increasing hydrate format

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Evaluation the Biosorption Capacity of Water Hyacinth (Eichhornia crassipes) Root for Some Heavy Metals
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Heavy metals especially lead (Pb), cadmium (Cd), chromium (Cr) and copper (Cu) are noxious pollutants with immense health hazards on living organisms, these pollutants enter aquatic environment in Iraq mainly Tigris and Euphrates rivers via waste water came from different anthropological activities, This study investigated capacity of dried and ground root of water hyacinth (Eichhornia crassipes) in removing the heavy metals from their aqueous solutions. Effects of initial concentrations of the heavy metals and pH of their aqueous solutions were studied. Results of this study revealed excellent biosorption capacity of water hyacinth root in general, removal of Pb was the highest and Cr was lowest. The results showed that the Pb, Cu and C

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
The predictive capacity of Coronavirus Impacts with Psychological Adjustment among University Students in Oman
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The present study was designed to determine the predictive capacity of Coronavirus’s impact, as well as, the psychological adjustment among university students in Oman. A total of (566) male and female students were employed to form the swtudy sample. The descriptive method was used. The findings showed that there is a significantly university student affected by Coronavirus; the dimensions of scale were arranged as follows: the Academic requirements of pandemic came first, the social communication came second, and the academic future stress came in third. The results also showed that Psychological Adjustment among University Students was affected by the Coronavirus pandemic, the average was low. Also, the result showed that the Corona

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Publication Date
Tue Mar 31 2015
Journal Name
Al-khwarizmi Engineering Journal
Experimental Study of the Thermal Diffusivity and Heat Capacity Concerning Some Duplex Stainless Steel
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Abstract

In the present work, thermal diffusivity and heat capacity measurements have been investigated in temperature range between RT and 1473 K for different duplex stainless steel supplied by Outokumpu Stainless AB, Sweden. The purpose of this study is to get a reliable thermophysical data of these alloys and to study the effect of microstructure on the thermal diffusivity and heat capacity value. Results show the ferrite content in the duplex stainless steel increased with temperature at equilibrium state. On the other hand, ferrite content increased with increasing Cr/Ni ratio and there is no significant effect of ferrite content on the thermal diffusivity value at room temperature. Furthermore, the heat capacity of all sam

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Pharmaceutical Negative Results
Total Oxidants, Lipid Peroxidation and Antioxidant Capacity in the Serum of Rheumatoid Arthritis Patients
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