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Modeling the removal of Cadmium Ions from Aqueous Solutions onto Olive Pips Using Neural Network Technique
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The uptake of Cd(II) ions from simulated wastewater onto olive pips was modeled using artificial neural network (ANN) which consisted of three layers. Based on 112 batch experiments, the effect of contact time (10-240 min), initial pH (2-6), initial concentration (25-250 mg/l), biosorbent dosage (0.05-2 g/100 ml), agitation speed (0-250 rpm) and temperature (20-60ºC) were studied. The maximum uptake (=92 %) of Cd(II) was achieved at optimum parameters of 60 min, 6, 50 mg/l, 1 g/100 ml, 250 rpm and 25ºC respectively.

Tangent sigmoid and linear transfer functions of ANN for hidden and output layers respectively with 7 neurons were sufficient to present good predictions for cadmium removal efficiency with coefficient of correlation equal to 0.99798. The sensitivity analysis for outputs of ANN signified that the relative importance of initial pH equal to 38 % and it is the influential parameter in the treatment process, followed by initial concentration, agitation speed, biosorbent dosage, time and temperature

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Publication Date
Tue Sep 01 2020
Journal Name
Petroleum
Reversible and irreversible adsorption of bare and hybrid silica nanoparticles onto carbonate surface at reservoir condition
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Realistic implementation of nanofluids in subsurface projects including carbon geosequestration and enhanced oil recovery requires full understanding of nanoparticles (NPs) adsorption behaviour in the porous media. The physicochemical interactions between NPs and between the NP and the porous media grain surface control the adsorption behavior of NPs. This study investigates the reversible and irreversible adsorption of silica NPs onto oil-wet and water-wet carbonate surfaces at reservoir conditions. Each carbonate sample was treated with different concentrations of silica nanofluid to investigate NP adsorption in terms of nanoparticles initial size and hydrophobicity at different temperatures, and pressures. Aggregation behaviour and the

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Publication Date
Mon Nov 19 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Study of the impact of foreign direct investment in the Iraqi tax system using the factorial analysis: (principal components)
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The tax system, like any other system, as a set of elements and parts that complement each other and are interrelated and interact to achieve specific goals, and is a natural  reflection of the economic, social and political conditions prevailing in society, and therefore the objectives of tax policy formulated in line with the objectives of economic policy in general, which means that any change in economic policy clearly affects fiscal policy measures and fiscal policy in particular.

The problem of searching for the impact of foreign direct investment in the Iraqi tax system was focused on the study  the of foreign direct investment and therole played in developing and improving the economic reality and its implicatio

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Publication Date
Thu Jul 04 2024
Journal Name
Journal Of Chemical Technology & Biotechnology
Adsorption of bimetal from aqueous solution on plum seed activated carbon synthesized by pyrocarbonic acid microwave method
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Abstract<sec><title>BACKGROUND

This article presents the simultaneous adsorption of bimetal Cu2+ and Zn2+ from an aqueous solution using activated carbon synthesized from a plum seed precursor by sulfuric acid and microwave activation: plum seeds chemically activated by 45% (w/w) sulfuric acid with 2:1 ratio for 4 h, then carbonized for 2 h at 700 °C and the product obtained activated in a microwave oven for 20 min at 700 W for final of activation. Plum seeds and activated carbon produced were characterized in terms of their physical and chemical composition using Brunauer–Emmett–Teller measurements, field emission scanning electr

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Publication Date
Fri Apr 26 2019
Journal Name
Pharmaceutical Developement And Technology
Preparation and characterization of co-processed starch/MCC/chitin hydrophilic polymers onto magnesium silicate
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It was aimed to investigate the compressibility, compactibility, powder flow and tablet disintegration of a new excipient comprising magnesium (Mg) silicate co-processed (5%–85% w/w) onto chitin, microcrystalline cellulose (MCC) and starch as the hydrophilic polymers of interest. Initially, the mechanism of tablet disintegration was studied by measuring water infiltration rate, moisture sorption, swelling capacity and hydration ability. Moreover, the powders compression behavior was carried out by applying Kawakita model of compression analysis in addition to porosity and radial tensile strength measurements. In vitro drug release of compacts made of 400 mg ibuprofen and 300 mg of the hydrophilic polymers containing 30% w/w Mg silicat

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Publication Date
Mon Dec 18 2017
Journal Name
Al-khwarizmi Engineering Journal
Optimization and Prediction of Process Parameters in SPIF that Affecting on Surface Quality Using Simulated Annealing Algorithm
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Incremental sheet metal forming is a modern technique of sheet metal forming in which a uniform sheet is locally deformed during the progressive action of a forming tool. The tool movement is governed by a CNC milling machine. The tool locally deforms by this way the sheet with pure deformation stretching. In SPIF process, the research is concentrate on the development of predict models for estimate the product quality. Using simulated annealing algorithm (SAA), Surface quality in SPIF has been modeled. In the development of this predictive model, spindle speed, feed rate and step depth have been considered as model parameters. Maximum peak height (Rz) and Arithmetic mean surface roughness (Ra) are used as response parameter to assess th

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Publication Date
Sat Oct 10 2026
Journal Name
Adab Al Rafidayn
Measuring the quality of office services using (LibQUAL + ®): the central library of the University of Baghdad as a model
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Libraries, information centers, and everything related to organizing and preparing information need to be periodically re-evaluated in order to stand on the level of quality, which means improving the general reality of these institutions to ensure sufficient satisfaction from beneficiaries of the services provided. This is what was worked on in this research, as one of the most important quality standards in libraries and information centers, LibQUAL+®, was applied in one of the most important and oldest central university libraries, namely the Central Library of the University of Baghdad at its two locations, Al-Jadriya and Al-Waziriya. The sample of beneficiaries to whom the questionnaire was distributed reached 75 beneficiaries distrib

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Publication Date
Mon Sep 28 2020
Journal Name
Journal Of Physical Education
The Effect of Increasing Rehabilitation Program Using Electric Stimulation On Rehabilitating Knee Joint Working Muscles Due to ACL Tear In Athletes
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The research aimed at designing a rehabilitation program using electric stimulation for rehabilitating knee joint working muscles as a result of ACL tear using an apparatus developed by the researchers that stimulate the muscle vibration and work as well as the ability to rehabilitate the join in shorter periods. In addition to that, it aimed at identifying the effect of this program on rehabilitating the knee joint working muscles. The researchers used the experimental method on Baghdad clubs’ players who suffer from complete knee joint ACL tear aged (19 – 24) years old. The results showed that the training program developed the working muscles significantly achieving normal levels of activity.

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Thu Nov 01 2018
Journal Name
International Journal Of Science And Research (ij
Mathematical Models for Predicting of Organic and Inorganic Pollutants in Diyala River Using AnalysisNeural Network
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Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourte

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Publication Date
Tue Dec 01 2020
Journal Name
Baghdad Science Journal
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

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