The ability of using aluminum filings which is locally solid waste was tested as a mono media in gravity rapid filter. The present study was conducted to evaluate the effect of variation of influent water turbidity (10, 20and 30 NTU); flow rate(30, 40, and 60 l/hr) and bed height (30and60)cm on the performance of aluminum filings filter media for 5 hours run time and compare it with the conventional sand filter. The results indicated that aluminum filings filter showed better performance than sand filter in the removal of turbidity and in the reduction of head loss. Results showed that the statistical model developed by the multiple linear regression was proved to be
valid, and it could be used to predict head loss in aluminum filings filter and sand filter with R2 equal to 0.94 and 0.968 respectively.
Therapeutic contact lenses TCLs is an approach used to enhance corneal residence time and reduce frequent instillation, which is a problem with eye drops. The problem with CLs is loading of hydrophobic drugs. In this research the CLs were prepared with molecular imprinting MI to enhance the loading of itraconazole, which is used as antifungal drug for fungal keratitis. CLs using different concentration of hydroxyethyl methacrylate HEMA and methacrylic acid MAA were prepared with and without MI using PEGDA (25 μL) and AIBN (37 mg) as crosslinker and initiator respectively. All the prepared CLs were clear and have good folding endurance. MICLs had significantly higher drug loading compared to conventional CLs. The release of i
... Show MoreThe aim of this work is to evaluate some mechanical and physical
properties (i.e. the impact strength, hardness, flexural strength,
thermal conductivity and diffusion coefficient) of
(epoxy/polyurethane) blend reinforced with nano silica powder (2%
wt.). Hand lay-up technique was used to manufacture the composite
and a magnetic stirrer for blending the components. Results showed
that water had affected the bending flexural strength and hardness,
while impact strength increased and thermal conductivity decreased.
In addition to the above mentioned tests, the diffusion coefficient
was calculated using Fick’s 2nd law.
This study experimentally investigated Free-Fall Gravity Drainage (FFGD) under combination-drive conditions in a two-dimensional Hele-Shaw model representing a water-drive reservoir. An initially high gravity potential from the oil column enabled early oil drainage before aquifer support became dominant. Three water-drive strengths were tested, demonstrating that a stronger aquifer (1.15 psig) accelerated oil recovery to approximately 75% of the original oil in place (OOIP) within 60 minutes, resulting in a final recovery of 79.5%. However, this was accompanied by rapid water breakthrough after 2.5 minutes and high-water cuts exceeding 90%. In contrast, a weaker aquifer (0.725 psig) stabilized the oil–water contact, delaying w
... Show MoreIn this paper, the experiments were carried out in laboratory flotation cell treating solid fines. The effect of variables such as collector oil dosage, pine oil dosage and solid content of the feed slurry have been investigated on the flotation characteristics of low rank coal. Attempts have also been made to develop some empirical Eq. to predict the yield and ash content of concentrate with the operating variables, solids concentration, collector oil dosage, and pine oil dosage, to estimate the recovery at any operating conditions. The calculated results obtained from regression equation by correlating the variables with the yield and ash content of concentrate have been compared to study whether calculated values match closely with th
... Show MoreAS Salman, SK Hameed…, Karbala Journal of Physical Education Sciences, 2020
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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The research aims to identify the factors that affect the quality of the product by using the Failure Mode and Effect Analysis (FMEA) tool and to suggest measures to reduce the deviations or defects in the production process. I used the case study approach to reach its goals, and the air filter product line was chosen in the air filters factory of Al-Zawraa General Company. The research sample was due to the emergence of many defects of different impact and the continuing demand for the product. I collected data and information from the factory records for two years (2018-2019) and used a scheme Pareto Fishbone Diagram as well as an FMEA tool to analyze data and generate results.
Par
... Show MoreDrones play a vital role in the fundamental aspects of Industry 4.0 by converting conventional warehouses into intelligent ones, particularly in the realm of barcode scanning. Various potential issues frequently arise during barcode scanning by drones, specifically when the drone camera has difficulty obtaining distinct images due to certain factors, such as distance, capturing the image whilst flying, noise in the environment and different barcode dimensions. In addressing these challenges, this study proposes an approach that combines a proportional–integral–derivative (PID) controller with image processing techniques. The PID controller is responsible for continuously monitoring the camera’s input, detecting the difference
... Show MoreBootstrap is one of an important re-sampling technique which has given the attention of researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con
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