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Determination of Best Location for Elevated Tank in Branched Network
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The research focuses on determination of best location of high elevated tank using the required head of pump as a measure for this purpose. Five types of network were used to find the effect of the variation in the discharge and the node elevation on the best location. The most weakness point was determined for each network. Preliminary tank locations were chosen for test along the primary pipe with same interval distance. For each location, the water elevation in tank and pump head was calculated at each hour depending on the pump head that required to achieve the minimum pressure at the most weakness point. Then, the sum of pump heads through the day was determined. The results proved that there is a most economical location where the energy consumption is minimum. This location joined with the branched line that containing the most weakness point. The best location didn’t join with the highest demand location unless this location containing the most weakness point.  The results indicated that the moving of tank away from best location in pump direction result in pump head increasing that exceed the increasing in pump head when the tank moves in the opposite direction. The location of tank beside the pump station was the worst location. Also, the results showed that as the distance between the pump and the highest demand become shorter, the required pump head become less. The uniform demand distribution required the least amount of pump head, it required minimum head of (554)m while the networks, that have highest demand at distance 200m,400m, and 1000m from the pump station,  required minimum head of 651m, 682m, and 726m respectively.

 

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Publication Date
Tue Feb 01 2022
Journal Name
Webology
Efficient Eye Recognition for Secure Systems using Convolutional Neural Network
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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Application Or Innovation In Engineering & Management (ijaiem)
Probabilistic Neural Network for User Authentication Based on Keystroke Dynamics
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Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

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Publication Date
Tue Nov 01 2022
Journal Name
Journal Of Engineering
Artificial Neural Network Model for Wastewater Projects Maintenance Management Plan
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Wastewater projects are one of the most important infrastructure projects, which require developing strategic plans to manage these projects. Most of the wastewater projects in Iraq don’t have a maintenance plan. This research aims to prepare the maintenance management plan (MMP) for wastewater projects. The objective of the research is to predict the cost and time of maintenance projects by building a model using ANN. The research sample included (15) completed projects in Wasit Governorate, where the researcher was able to obtain the data of these projects through the historical information of the Wasit Sewage Directorate. In this research artificial neural networks (ANN) technique was used to build two models (cost

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Publication Date
Wed Mar 15 2023
Journal Name
Journal Of Medicinal And Chemical Sciences
Simple Spectrophotometric Method for Determination of Drug Lisinopril in Pure Form and Pharmaceutical Formulations
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Publication Date
Thu Nov 23 2017
Journal Name
Brazilian Journal Of Analytical Chemistry
Microvolume-DLLME for the Spectrophotometric Determination of Clidinium Bromide in Drug, Urine, and Serum
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The present study combines UV-Vis spectrophotometry and dispersive liquid-liquid microextraction (DLLME) for the preconcentration and determination of trace level clidinium bromide (Clid) in pharmaceutical preparation and real samples. The method is based on ion-pair formation between Clid and bromocresol green in aqueous solution using citrate buffer (pH = 3). The colored product was first extracted using a mixture of 800 µL acetonitrile and 300 µL chloroform solvents. Then, a spectrophotometric measurement of sediment phase was performed at λ = 420 nm. The important parameters affecting the efficiency of DLLME were optimized. Under the optimum conditions, the calibration graphs of standard -1 (Std.), drug, urine and serum were ranged

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Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Spectrophotometric Kinetic Methods for the Determination of Paracetamol in Pure Form and Pharmaceutical Preparations
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Simple and sensitive kinetic methods are developed for the determination of Paracetamol in pure form and in pharmaceutical preparations. The methods are based on direct reaction (oxidative-coupling reaction) of Paracetamol with o-cresol in the presence of sodium periodate in alkaline medium, to form an intense blue-water-soluble dye that is stable at room temperature, and was followed spectrophotometriclly at λmax= 612 nm. The reaction was studied kinetically by Initial rate and fixed time (at 25 minutes) methods, and the optimization of conditions were fixed. The calibration graphs for drug determination were linear in the concentration ranges (1-7 μg.ml-1) for the initial rate and (1-10 μg.ml-1) for the fixed time methods at 25 min.

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Publication Date
Mon Mar 07 2016
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Determination of mercury level in skin whitening creams: Determination of mercury level in skin whitening creams
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This study included the determination of mercury level in twelve samples of skin whitening cream available in local market in Baghdad by atomic absorption spectrophotometer ,all the samples analyzed was contained a detectable amount of mercury. The lowest concentration of mercury in the sample C (Top Shirley) was 0.482 μg/g, and the higher concentration was 29.54 μg/g in the sample J (Norseen) .It was also noted that the samples H (whitening speckle removing day cream) and K (whitening speckle removing night cream) did not mention in the label significance the name of the country of origin and date of the validity of the product.

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Publication Date
Tue Jan 01 2019
Journal Name
Journal Of Communications
SDN Implementation in Data Center Network
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Publication Date
Thu May 04 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Design Feed Forward Neural Network to Determine Doses of the Decongestant for Cold Pills
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The aim of this paper is to design feed forward neural network to determine the effects of
cold pills and cascades from simulation the problem to system of first order initial value
problem. This problem is typical of the many models of the passage of medication throughout
the body. Designer model is an important part of the process by which dosage levels are set.
A critical factor is the need to keep the levels of medication high enough to be effective, but
not so high that they are dangerous.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Artificial Neural Network and Latent Semantic Analysis for Adverse Drug Reaction Detection
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Adverse drug reactions (ADR) are important information for verifying the view of the patient on a particular drug. Regular user comments and reviews have been considered during the data collection process to extract ADR mentions, when the user reported a side effect after taking a specific medication. In the literature, most researchers focused on machine learning techniques to detect ADR. These methods train the classification model using annotated medical review data. Yet, there are still many challenging issues that face ADR extraction, especially the accuracy of detection. The main aim of this study is to propose LSA with ANN classifiers for ADR detection. The findings show the effectiveness of utilizing LSA with ANN in extracting AD

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