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Oily Wastewater Treatment Using Expanded Beds of Activated Carbon and Zeolite
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Two types of adsorbents were used to treat oily wastewater, activated carbon and zeolite. The removal efficiencies of these materials were compared to each other. The results showed that activated carbon performed some better properties in removal of oil. The experimental methods which were employed in this investigation included batch and column studies. The former was used to evaluate the rate and equilibrium of carbon and zeolie adsorption, while the latter was used to determine treatment efficiencies and performance characteristics. Expanded bed adsorber was constructed in the column studies. In this study, the adsorption behavior of vegetable oil (corn oil) onto activated carbon and zeolite was examined as a function of the concentration of the adsorbate, contact time, adsorbent dosage and amount of coagulant salt(calcium sulphate) added . The adsorption data was modeled with Freundlich and Langmuir adsorption isotherms. and it was found that the adsorption process on activated carbon and zeolite fit the Freundlich isotherm model. The amount of oil adsorbed increased with increasing the contact time, but longer mixing duration did not increase residual oil removal from wastewater due to the coverage of the adsorbent surface with oil molecules. It was found that as the dosage of adsorbent increased, the percentage of residual oil removal also increased. The effects of adsorbent type and amount of coagulant salt(calcium sulphate) added on the breakthrough curve were studied in details in the column studies. Expanded bed behavior was modeled using the Richardson-Zaki correlation between the superficial velocity of the feed stream and the void fraction of the bed at moderate Reynolds number.

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Publication Date
Fri Feb 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
A Comparison of Parameters Estimation Methods for the Negative Binomial Regression Model under Multicollinearity Problem by Using Simulation
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This study discussed a biased estimator of the Negative Binomial Regression model known as (Liu Estimator), This estimate was used to reduce variance and overcome the problem Multicollinearity between explanatory variables, Some estimates were used such as Ridge Regression and Maximum Likelihood Estimators, This research aims at the theoretical comparisons between the new estimator (Liu Estimator) and the estimators

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Publication Date
Tue Jan 01 2019
Journal Name
Chemical Industry And Chemical Engineering Quarterly
Optimization of dye adsorption process for Albizia lebbeck pods as a biomass using central composite rotatable design model
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Albizia lebbeck biomass was used as an adsorbent material in the present study to remove methyl red dye from an aqueous solution. A central composite rotatable design model was used to predict the dye removal efficiency. The optimization was accomplished under a temperature and mixing control system (37?C) with different particle size of 300 and 600 ?m. Highest adsorption efficiencies were obtained at lower dye concentrations and lower weight of adsorbent. The adsorption time, more than 48 h, was found to have a negative effect on the removal efficiency due to secondary metabolites compounds. However, the adsorption time was found to have a positive effect at high dye concentrations and high adsorbent weight. The colour removal effi

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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Engineering
Calculating the Transport Density Index from Some of the Productivity Indicators for Railway Lines by Using Neural Networks
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The efficiency evaluation of the railway lines performance is done through a set of indicators and criteria, the most important are transport density, the productivity of enrollee, passenger vehicle production, the productivity of freight wagon, and the productivity of locomotives. This study includes an attempt to calculate the most important of these indicators which transport density index from productivity during the four indicators, using artificial neural network technology. Two neural networks software are used in this study, (Simulnet) and (Neuframe), the results of second program has been adopted. Training results and test to the neural network data used in the study, which are obtained from the international in

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Publication Date
Fri Sep 01 2023
Journal Name
Al-khwarizmi Engineering Journal
Removal of Ciprofloxacin Antibiotic from Synthesized Aqueous Solution Using Three Different Metals Nanoparticles Synthesized Through the Green Method
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This study investigates the possibility of removing ciprofloxacin (CIP) using three types of adsorbent based on green-prepared iron nanoparticles (Fe.NPs), copper nanoparticles (Cu. NPS), and silver nanoparticles (Ag. NPS) from synthesized aqueous solution. They were characterized using different analysis methods. According to the characterization findings, each prepared NPs has the shape of a sphere and with ranges in sizes from of 85, 47, and 32 nanometers and a surface area of 2.1913, 1.6562, and 1.2387 m2/g for Fe.NPs, Cu.NPs and Ag.NPs, respectively. The effects of various parameters such as pH, initial CIP concentration, temperature, NPs dosage, and time on CIP removal were investigated through batch experiments. The res

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Publication Date
Fri Mar 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Design of PV Solar Energy Generator using MPPT Technique to Control Single Input/Multiple Outputs (DC-DC) Converter
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The paper presents the design of a system consisting of a solar panel with Single Input/Multiple Outputs (DC-DC) Buck Converter by using Simulink dialogue box tools in MATLAB software package for simulation the system. Maximum Power Point Tracking (MPPT) technique depending on Perturb and Observe (P&O) algorithm is used to control the output power of the converter and increase the efficiency of the system. The characteristics of the MSX-60 PV module is chosen in design of the system, whereas the electrical characteristics (P-V, I-V and P-I curves) for the module are achieved, that is affected by the solar radiation and temperature variations. The proposed design module has been found to be stable for any change in atmospheric tempera

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Publication Date
Wed Mar 02 2022
Journal Name
Journal Of Educational And Psychological Researches
The Effects of Using Educational Moodle Platform to Develop Instructors’ Skills in Designing Electronic Tests at Dhofar University
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With the premise that effective use of online instructional practices is of vital importance in classrooms, the current study aimed to examine the effects of using Moodle applications to develop instructors’ skills in designing electronic tests at Dhofar University. The sample of this study consisted of (25) instructors participated in the experimental group. The researchers implemented a quasi-experimental design with one group pre- and post-test; in addition, an observation card was implemented to measure the target skills related to test design. The research instruments were subjected to validity and reliability measures to ensure valid and reliable data and results. The study results showed that those instructors who participated i

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Publication Date
Thu Dec 24 2020
Journal Name
Advances In Civil Engineering
Analytical study on torsional behavior of concrete beams strengthened with fiber reinforced polymer laminates using softened truss model
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This study aimed at evaluating the torsional capacity of reinforced concrete (RC) beams externally wrapped with fiber reinforced polymer (FRP) materials. An analytical model was described and used as a new computational procedure based on the softened truss model (STM) to predict the torsional behavior of RC beams strengthened with FRP. The proposed analytical model was validated with the existing experimental data for rectangular sections strengthened with FRP materials and considering torque-twist relationship and crack pattern at failure. The confined concrete behavior, in the case of FRP wrapping, was considered in the constitutive laws of concrete in the model. Then, an efficient algorithm was developed in MATLAB environment t

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Publication Date
Thu Jun 01 2017
Journal Name
International Journal Of Applied Engineering Research
A Proposed Method for Generating a Private Key Using Digital Color Image Features
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In this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c

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Publication Date
Wed Aug 05 2015
Journal Name
International Journal Of Current Engineering And Technology
Water Quality Index Assessment using GIS Case study: Tigris River in Baghdad City
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In this study water quality index (WQI) was calculated to classify the flowing water in the Tigris River in Baghdad city. GIS was used to develop colored water quality maps indicating the classification of the river for drinking water purposes. Water quality parameters including: Turbidity, pH, Alkalinity, Total hardness, Calcium, Magnesium, Iron, Chloride, Sulfate, Nitrite, Nitrate, Ammonia, Orthophosphate and Total dissolved solids were used for WQI determination. These parameters were recorded at the intakes of the WTPs in Baghdad for the period 2004 to 2011. The results from the annual average WQI analysis classified the Tigris River very poor to polluted at the north of Baghdad (Alkarkh WTP) while it was very poor to very polluted in t

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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Scopus (11)
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