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Micro-Bubble Flotation for Removing Cadmium Ions from Aqueous Solution: Artificial Neural Network Modeling and Kinetic of Flotation
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In this work, microbubble dispersed air flotation technique was applied for cadmium ions removal from wastewater aqueous solution. Experiments parameters such as pH (3, 4, 5, and 6), initial Cd(II) ions concentration (40, 80, and 120 mg/l)  contact time( 2, 5, 10 , 15, and 20min), and surfactant (10, 20and 40mg/l) were studied in order to optimize the best conditions .The experimental results indicate that microbubbles were quite effective in removing cadmium ions and the anionic surfactant SDS was found to be more efficient than cationic CTAB in flotation process. 92.3% maximum removal efficiency achieved through 15min at pH 5, SDS surfactant concentration 20mg/l, flow rate250 cm3/min and at 40mg/l Cd(II) ions initial concentration. The removal efficiency of cadmium ion was predicted through 11 neurons hidden layer, with a correlation coefficient of 0.9997 between ANN outputs and the experimental data and through sensitivity analysis, pH was found to be most significant parameter (25.13 %).The kinetic flotation order for cadmium ions almost first order and the removal rate constant (k) increases with decreasing the initial metal concentration.

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Publication Date
Sun Apr 03 2016
Journal Name
Journal Of Educational And Psychological Researches
The effect of the differences in the correlation pattern of the micro blogging in the educational attainment of computer science curriculum for 12th grade students
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The object of this research is to determine the effect in the differences of the correlation pattern of the micro blogging on the educational attainment of computer science curriculum for 12th grade students. I will try to test the best suited correlation and I might use the demo curriculum as well to achieve its objectives , The research method that will be used in this research is the quantitative method where we will use a sample of 60 students divided into two groups ( correlate the micro blogging - adopted the sequence pattern of relating the micro blogging) As a result, we found out that there are quantitative differences among the two groups' median , The differences goes back to the main effect of the correlation pattern of the m

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Publication Date
Sat Oct 05 2024
Journal Name
Apos Trends In Orthodontics
Novel cytotoxicity of nano-coated orthodontic micro-implants: An <i>in vitro</i> study
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Objectives:

Many attempts have been made to modify the surface of orthodontic micro-implants and prevent the development of microbes by coating them with antimicrobial nanoparticles (NPs). The purpose of the present study was to evaluate the cytotoxicity of different NPs, namely, TiO2 and zinc oxide (ZnO) NPs, that are used to coat titanium orthodontic micro-implants.

Material and Methods:

Thirty orthodontic micro-implants were included in this study. Those were divided into three groups: control group without coating, TiO2-coated orthodontic micro-implants, and TiO2- and ZnO-coated orthodontic micro-implants. Scann

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Publication Date
Sun Dec 07 2008
Journal Name
Baghdad Science Journal
Spectrophotometric micro determination of drug promethazine hydrochloride in some pharmaceutical by chelating with Rhodium
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The drug promethazine hydrochloride (PRZH) forms with rhodium (II) a colored chelate (?max = 472 nm) complex at (pH = 2.1) which is extractable with benzyl alcohol as organic solvent. Under the appropriate experimental conditions a calibration plot was set up from which some analytical parameter were derived and deduced by regression. Standard addition procedure was also adopted. It has been estimated that the concentration of the drug PRZH to be 24.89 mg per unit and 24.19 mg per unit for both calibrations. Under optimal conditions, the developed method has been achieved the following characteristics: LDR (30 – 150 µg ml-1 ) PRZH , RSD % ( 0.6 – 2.47 ) , sandell sensitivity( 0.0844 µg. cm -2 ) , LOD ( 1.66 µgml-1 ) , recovery

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
An Analytical Solution for the Maximum Tensile Stress and Stress Concentration Factor Investigations for Standard, Asymmetric fillets, Asymmetric Pressure Angle and Profile Shifted Helical and Spur Gears
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This research introduces a developed analytical method to determine the nominal and maximum tensile stress and investigate the stress concentration factor. The required tooth fillets parametric equations and gears dimensions have been reformulated to take into account the asymmetric fillets radiuses, asymmetric pressure angle, and profile shifting non-standard modifications. An analytical technique has been developed for the determination of tooth weakest section location for standard, asymmetric fillet radiuses, asymmetric pressure angle and profile shifted involute helical and spur gears. Moreover, an analytical equation to evaluate gear tooth-loading angle at any radial distance on the involute profile of spur and hel

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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)
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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

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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
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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

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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
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Publication Date
Sun Mar 31 2013
Journal Name
Inventi Impact: Artificial Intelligence
SIMULATION OF IDENTIFICATION AND CONTROL OF SCARA ROBOT USING MODIFIED RECURRENT NEURAL NETWORKS
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This paper presents a modified training method for Recurrent Neural Networks. This method depends on the Non linear Auto Regressive (NARX) model with Modified Wavelet Function as activation function (MSLOG) in the hidden layer. The modified model is known as Modified Recurrent Neural (MRN). It is used for identification Forward dynamics of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot. This model is also used in the design of Direct Inverse Control (DIC). This method is compared with Recurrent Neural Networks that used Sigmoid activation function (RS) in the hidden layer and Recurrent Neural Networks with Wavelet activation function (RW). Simulation results shows that the MRN model is bett

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Publication Date
Thu Jan 01 2026
Journal Name
Malaysian Journal Of Nursing
Pediatric Nursing Students and Artificial Intelligence: A Cross-Sectional Study
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Background: The rapid integration of Artificial Intelligence (AI) into healthcare necessitates that nursing education evolves to equip students with essential technological competencies. Objectives: To explore pediatric nursing students' perceptions of AI in nursing and analyze associations with sociodemographic factors and prior AI knowledge. Methods: A descriptive cross-sectional study was conducted from December 2024 to March 2025 across five universities in Baghdad. A non-probability sample of 500 pediatric nursing students completed the Shinners Artificial Intelligence Perception (SAIP) tool. Data were analyzed using descriptive statistics and inferential comparisons (t-tests/ANOVA) via SPSS. Results: Participants had a mean ag

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Publication Date
Fri Aug 01 2008
Journal Name
2008 International Symposium On Information Technology
Generating pairwise combinatorial test set using artificial parameters and values
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