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Genetic Algorithm Optimization Model for Central Marches Restoration Flows with Different Water Quality Scenarios
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A Genetic Algorithm optimization model is used in this study to find the optimum flow values of the Tigris river branches near Ammara city, which their water is to be used for central marshes restoration after mixing in Maissan River. These tributaries are Al-Areed, AlBittera and Al-Majar Al-Kabeer Rivers. The aim of this model is to enhance the water quality in Maissan River, hence provide acceptable water quality for marsh restoration. The model is applied for different water quality change scenarios ,i.e. , 10%,20% increase in EC,TDS and BOD. The model output are the optimum flow values for the three rivers while, the input data are monthly flows(1994-2011),monthly water requirements and water quality parameters (EC, TDS, BOD, DO and pH).The objective function adopted in the optimization model is in a form the sum of difference in each of the 5 water quality parameters, resulting from the
mixing equation of the waters of the rivers, from the accepted limits of these parameters , weighted by a penalty factor assigned for each water quality parameter according to its importance. The adopted acceptable limits are 1500,1000, 6,4 and 7, while the penalty factors are 1,0.8,0.8,0.8,and 0.2 for EC,TDS,BOD,DO,and pH respectively. The constraints adopted on the decision variables which the monthly flows of the three rivers are those that provide the monthly demands downstream each river, and not exceed a maximum monthly flow
limits. The maximum flow limits adopted are for three flow cases, wet, average and dry years. For each flow case three scenarios for the monthly water quality parameters were adopted , the average values(scenario 1),the 10% increase in EC,TDS, and BOD (Scenario
2),and the 20% increase in these three water quality parameters (Scenario 3). Hence nine cases are adopted and for each an optimum monthly flows are found for each river. The genetic optimization model adopt a variable number of population of 100 to 1000 in a step of
100,0.8 and 0.2 cross over and mutation rates, and three iterations to reach the stable optimum solutions. The results indicates that the flow analysis shows a significant decrease in the flow values of the three rives after year 2000,hence, the flow values for the period of (1994-1999), are excluded and the only used values are those for (2000-2011). The estimated monthly demands exhibits low variation. The observed optimum monthly flow values decrease in general as the case flow changed from wet to normal and dry cases. The change in Scenarios from S1 to S2 and S3 , do not necessarily increase all the required optimum monthly flow values. The obtained minimum objective functions do not exhibits a certain trend with the change in the flow cases and/or the change in the scenarios.

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Publication Date
Wed Jan 01 2020
Journal Name
Amultifaceted Review Journal In The Field Of Pharmacy
Zwitterionic ion chromatography coupled with ultraviolet detection for the quantification of 2-deoxyguanosine in human serum
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Publication Date
Thu Feb 11 2016
Journal Name
Journal Of Materials Science: Materials In Electronics
Electrochemical deposition of CdSe-sensitized TiO2 nanotube arrays with enhanced photoelectrochemical performance for solar cell application
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

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Publication Date
Sun Sep 01 2019
Journal Name
Gazi University Journal Of Science
Reliable Iterative Methods for Solving Convective Straight and Radial Fins with Temperature-Dependent Thermal Conductivity Problems
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In our article, three iterative methods are performed to solve the nonlinear differential equations that represent the straight and radial fins affected by thermal conductivity. The iterative methods are the Daftardar-Jafari method namely (DJM), Temimi-Ansari method namely (TAM) and Banach contraction method namely (BCM) to get the approximate solutions. For comparison purposes, the numerical solutions were further achieved by using the fourth Runge-Kutta (RK4) method, Euler method and previous analytical methods that available in the literature. Moreover, the convergence of the proposed methods was discussed and proved. In addition, the maximum error remainder values are also evaluated which indicates that the propo

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Publication Date
Wed Oct 17 2018
Journal Name
Journal Of Economics And Administrative Sciences
The Use Of Some Parametric And Non parametric Methods For Analysis Of Factorial Experiments With Application
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In this search, we examined the factorial experiments and the study of the significance of the main effects, the interaction of the factors and their simple effects by the F test (ANOVA) for analyze the data of the factorial experience. It is also known that the analysis of variance requires several assumptions to achieve them, Therefore, in case of violation of one of these conditions we conduct a transform to the data in order to match or achieve the conditions of analysis of variance, but it was noted that these transfers do not produce accurate results, so we resort to tests or non-parametric methods that work as a solution or alternative to the parametric tests , these method

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Laboratory Testing and Evaluating of Shale Interaction with Mud for Tanuma Shale formation in Southern Iraq
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   Rock failure during drilling is an important problem to be solved in petroleum technology. one of the most causes of rock failure is shale chemical interaction with drilling fluids. This interaction is changing the shale strength as well as its pore pressure relatively near the wellbore wall. In several oilfields in southern Iraq, drilling through the Tanuma formation is known as the most challenging operation due to its unstable behavior. Understanding the chemical reactions between shale and drilling fluid is determined by examining the features of shale and its behavior with drilling mud. Chemical interactions must be mitigated by the selection of suitable drilling mud with effective chemical additives. This study is describing t

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Publication Date
Thu Nov 11 2021
Journal Name
Nano Express
Near-infrared PbS quantum dots functionalized with affibodies and ZnPP for targeted imaging and therapeutic applications
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Abstract<p>We report a new theranostic device based on lead sulfide quantum dots (PbS QDs) with optical emission in the near infrared wavelength range decorated with affibodies (small 6.5 kDa protein-based antibody replacements) specific to the cancer biomarker human epidermal growth factor receptor 2 (HER2), and zinc(II) protoporphyrin IX (ZnPP) to combine imaging, targeting and therapy within one nanostructure. Colloidal PbS QDs were synthesized in aqueous solution with a nanocrystal diameter of ∼5 nm and photoluminescence emission in the near infrared wavelength range. The Z<sub>HER2:432</sub> affibody, mutated through the introduction of two cysteine residues at the C-terminus (</p> ... Show More
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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Finding the Best Route for Connecting Citizens with Service Centers in Baghdad Based on NN Technology
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     A geographic information system (GIS) is a very effective management and analysis tool. Geographic locations rely on data. The use of artificial neural networks (ANNs) for the interpretation of natural resource data has been shown to be beneficial. Back-propagation neural networks are one of the most widespread and prevalent designs. The combination of geographic information systems with artificial neural networks provides a method for decreasing the cost of landscape change studies by shortening the time required to evaluate data. Numerous designs and kinds of ANNs have been created; the majority of them are PC-based service domains. Using the ArcGIS Network Analyst add-on, you can locate service regions around any network

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
Flow Injection Analysis with Turbidity Detection for the Quantitative Determination of Mebeverine Hydrochloride in Pharmaceutical Formulations
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The main objective of this paper is to develop and validate flow injection method, a precise, accurate, simple, economic, low cost and specific turbidimetric method for the quantitative determination of mebeverine hydrochloride (MbH) in pharmaceutical preparations.  A homemade NAG Dual & Solo (0-180º) analyser which contains two identical detections units (cell 1 and 2) was applied for turbidity measurements. The developed method was optimized for different chemical and physical parameters such as perception reagent concentrations, aqueous salts solutions, flow rate, the intensity of the sources light, sample volume, mixing coil and purge time. The correlation coefficients (r) of the developed method were 0.9980 and 0.9986 for

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Publication Date
Sun Mar 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Calculate the sum of squares for parts (vehicles) SSE in 2n global trials with total integration In a suggested manne
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In order to serve the field of knowledge in the field of design and analysis of experiments by adopting formulas and methods that are easy and simple in arithmetic work, especially in experiments that require many calculations for squares, including tests of type
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