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Performance Evaluation of Al-Karkh Water Treatment Plant Using Model-driven and Data-Driven Models
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Abstract<p>There is a great operational risk to control the day-to-day management in water treatment plants, so water companies are looking for solutions to predict how the treatment processes may be improved due to the increased pressure to remain competitive. This study focused on the mathematical modeling of water treatment processes with the primary motivation to provide tools that can be used to predict the performance of the treatment to enable better control of uncertainty and risk. This research included choosing the most important variables affecting quality standards using the correlation test. According to this test, it was found that the important parameters of raw water: Total Hardness, Calcium, Magnesium, Total Solids, Nitrite, Nitrates, Ammonia, and Silica are to be used to construct the specific model, while pH, Fluoride, Aluminium, Nitrite, Nitrate, Ammonia, Silica, and Orthophosphate of the treated water were eliminated from the analysis. For modeling the coagulation and flocculation process temperature, Alkalinity and pH of raw water were the depended variables of the model. As for the modeling process turbidity of the treated water was used as the output variable. In general, the linear models including model-driven type, (Multivariate multiple regression, MMR and Multiple linear regression, MLR) have slightly higher prediction efficiencies than the, data-driven type (artificial neural network, ANNM). The coefficients of determination (R<sup>2</sup>) reached 66 to 85% for the MMR and MLR models and 65 to 81% for the ANN models.</p>
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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Comparison of Some Suggested Estimators Based on Differencing Technique in the Partial Linear Model Using Simulation
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In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

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Publication Date
Sat Aug 01 2015
Journal Name
Journal Of Bridge Engineering
Torsional Analysis of Multicell Concrete Box Girders Strengthened with CFRP Using a Modified Softened Truss Model
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Publication Date
Thu Sep 01 2016
Journal Name
Journal Of Ocular Pharmacology And Therapeutics
Formulation and<i>In Vitro</i>Evaluation of Cyclosporine-A Inserts Prepared Using Hydroxypropyl Methylcellulose for Treating Dry Eye Disease
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Publication Date
Tue Aug 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
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Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

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Publication Date
Thu Feb 16 2017
Journal Name
Signal, Image And Video Processing
Enhancing Prony’s method by nuclear norm penalization and extension to missing data
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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the method of partial least squares and the algorithm of singular values decomposion to estimate the parameters of the logistic regression model in the case of the problem of linear multiplicity by using the simulation
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

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Publication Date
Wed Oct 26 2022
Journal Name
Petroleum Science And Technology
Building 3D geological model using non-uniform gridding for Mishrif reservoir in Garraf oilfield
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Publication Date
Mon Jun 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Using the Logistic Regression Model in Studding the Assistant Factors to Diagnose Bladder Cancer
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The cancer is one of the biggest health problems that facing the world . And  the bladder cancer has a special place among the most spread cancers in Arab countries specially in Iraq and Egypt(2) . It is one of the diseases which can be treated and cured if it is diagnosed early . This research is aimed at studying the assistant factors that diagnose bladder cancer such as (patient's age , gender , and other major complains of hematuria , burning or pain during urination and micturition disorders) and then determine which factors are the most effective in the possibility of diagnosing this disease by using the statistical model (logistic regression model) and depending on a random sample of (128) patients . After

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Publication Date
Sun Jan 01 2017
Journal Name
Ieee/acm Transactions On Audio, Speech, And Language Processing
Underdetermined Convolutive Source Separation Using GEM-MU With Variational Approximated Optimum Model Order NMF2D
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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Application of levofloxacin and doxycycline in treatment of vaginal chlamydial infection
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Doxycycline and levofloxacin are heterocyclic organic compounds that are now popularly used to treat some bacterial infections. In this study which was conducted on patients from a private clinic, we compared the use of two commonly used antibiotics for the treatment of diagnosed cases with vaginal chlamydial infection: levofloxacin and doxycycline. Vaginal chlamydial infection is considered to be a very common sexually transmitted infection. It may have minimal symptoms which can lead to neglect by the patient until it leads to some important complications among which is the inability to become pregnant. This indicates early diagnosis and treatment of this infection. By comparing the results of treatment we concluded that there is no much

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