Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
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Publication Date
Mon Oct 01 2018
Journal Name
Conference: First International Conference On Water Resources
Modeling BOD of the Effluent from Abu-Ghraib Diary Factory using Artificial Neural Network
October 2018
BOD
ANN
wastewater
The proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A
... Show MorePublication Date
Wed Dec 18 2024
Journal Name
Bmc Medical Education
Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Ecological Engineering
Heavy Metals Removal from Simulated Wastewater using Horizontal Subsurface Constructed Wetland
This study aimed to assess the efficiency of Nerium oleander in removing three different metals (Cd, Cu, and Ni) from simulated wastewater using horizontal subsurface flow constructed wetland (HSSF-CW) system. The HSSF-CW pilot scale was operated at two hydraulic retention times (HRTs) of 4 and 7 days, filled with a substrate layer of sand and gravel. The results indicated that the HSSF-CW had high removal efficiency of Cd and Cu. A higher HRT (7 days) resulted in greater removal efficiency reaching up to (99.3% Cd, 99.5% Cu, 86.3% Ni) compared to 4 days. The substrate played a significant role in removal of metals due to adsorption and precipitation. The N. oleander plant also showed a good tolerance to the uptake of Cd, Cu, and Ni ions fr
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(14)
Publication Date
Wed Sep 01 2021
Journal Name
Journal Of Ecological Engineering
Heavy Metals Removal from Simulated Wastewater using Horizontal Subsurface Constructed Wetland
This study aimed to assess the efficiency of Nerium oleander in removing three different metals (Cd, Cu, and Ni) from simulated wastewater using horizontal subsurface flow constructed wetland (HSSF-CW) system. The HSSF-CW pilot scale was operated at two hydraulic retention times (HRTs) of 4 and 7 days, filled with a substrate layer of sand and gravel. The results indicated that the HSSF-CW had high removal efficiency of Cd and Cu. A higher HRT (7 days) resulted in greater removal efficiency reaching up to (99.3% Cd, 99.5% Cu, 86.3% Ni) compared to 4 days. The substrate played a significant role in removal of metals due to adsorption and precipitation. The N. oleander plant also showed a good tolerance to the uptake of Cd, Cu, and Ni ions fr
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(14)
Publication Date
Sun Jul 01 2012
Journal Name
Journal Of Computer Science
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(1)
Publication Date
Wed Jan 29 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Measuring the efficiency of quality health services in the province of Karbala: Models using the Data envelopment analysis (DEA)
The research aims to measure the efficiency of health services Quality in the province of Karbala, using the Data Envelopment analysis Models in ( 2006). According to these models the degree of efficiency ranging between zero and unity. We estimate Scale efficiency for two types of orientation direction, which are input and output oriented direction.
The results showed, according Input-oriented efficiency that the levels of Scale efficiency on average is ( 0.975), in the province of Karbala. While the index of Output-oriented efficiency on average is (o.946).
Publication Date
Sat Jul 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Predicting of heavy metals in some areas of Iraq using spectral analysis techniques
Abstract<p>Soil that has been contaminated by heavy metals is a serious environmental problem. A different approach for forecasting a variety of soil physical parameters is reflected spectroscopy is a low-cost, quick, and repeatable analytical method. The objectives of this paper are to predict heavy metal (Ti, Cr, Sr, Fe, Zn, Cu and Pb) soil contamination in central and southern Iraq using spectroscopy data. An XRF was used to quantify the levels of heavy metals in a total of 53 soil samples from Baghdad and ThiQar, and a spectrogram was used to examine how well spectral data might predict the presence of heavy metals metals. The partial least squares regression PLSR models performed well in pr</p>
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(1)
Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p>
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(4)
Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Intelligent Systems
Trip generation modeling for a selected sector in Baghdad city using the artificial neural network
Abstract<p>This study is planned with the aim of constructing models that can be used to forecast trip production in the Al-Karada region in Baghdad city incorporating the socioeconomic features, through the use of various statistical approaches to the modeling of trip generation, such as artificial neural network (ANN) and multiple linear regression (MLR). The research region was split into 11 zones to accomplish the study aim. Forms were issued based on the needed sample size of 1,170. Only 1,050 forms with responses were received, giving a response rate of 89.74% for the research region. The collected data were processed using the ANN technique in MATLAB v20. The same database was utilized to</p>
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(3)
Publication Date
Fri Feb 01 2019
Journal Name
Journal Of The College Of Education For Women
The Intelligence of the Child in Relation to some Variables
The Intelligence of the Child in Relation to some Variables