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Application of Artificial Neural Network and GeographicalInformation System Models to Predict and Evaluate the Quality ofDiyala River Water, Iraq
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This research discusses application Artificial Neural Network (ANN) and Geographical InformationSystem (GIS) models on water quality of Diyala River using Water Quality Index (WQI). Fourteen water parameterswere used for estimating WQI: pH, Temperature, Dissolved Oxygen, Orthophosphate, Nitrate, Calcium, Magnesium,Total Hardness, Sodium, Sulphate, Chloride, Total Dissolved Solids, Electrical Conductivity and Total Alkalinity.These parameters were provided from the Water Resources Ministryfrom seven stations along the river for the period2011 to 2016. The results of WQI analysis revealed that Diyala River is good to poor at the north of Diyala provincewhile it is poor to very polluted at the south of Baghdad City. The selected parameters were subjected to Kruskal-Wallis test for detecting factors contributing to the degradation of water quality and for eliminating independentvariables that exhibit the highest contribution in p-value. The analysis of results revealed that ANN model was goodin predicting the WQI. The confusion matrix for Artificial Neural Model (NNM) gave almost 96% for training, 85.7%for testing and 100% for holdout. In relation to GIS, six color maps of the river have been constructed to give clearimages of the water quality along the river (PDF) Application of Artificial Neural Network and Geographical Information System Models to Predict and Evaluate the Quality of Diyala River Water, Iraq. Available from: https://www.researchgate.net/publication/346028558_Application_of_Artificial_Neural_Network_and_Geographical_Information_System_Models_to_Predict_and_Evaluate_the_Quality_of_Diyala_River_Water_Iraq [accessed Apr 07 2023].

Publication Date
Sun Apr 26 2020
Journal Name
Iraqi Journal Of Science
Monotone Approximation by Quadratic Neural Network of Functions in Lp Spaces for p<1
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Some researchers are interested in using the flexible and applicable properties of quadratic functions as activation functions for FNNs. We study the essential approximation rate of any Lebesgue-integrable monotone function by a neural network of quadratic activation functions. The simultaneous degree of essential approximation is also studied. Both estimates are proved to be within the second order of modulus of smoothness.

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Publication Date
Fri Aug 28 2020
Journal Name
Iraqi Journal Of Science
A Comparison Between Different Susceptibility Test Methods to Evaluate the Antibacterial Activity of Olibanum and Alum Against the "Red Complex" Periodontal Pathogens
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Testing the sensitivity of periodontal pathogens requires the selection of an easier and more reliable method to be used with such anaerobic bacteria that need a long period of time for growth. Natural materials are a new era of antibacterial agents to control periodontal infections. The aims of the current study were to test the antibacterial activity of two natural agents, namely olibanum and alum, against three types of red complex periodontal pathogens and compare the application of agar diffusion and microdilution methods for testing the susceptibility. Gingival crevicular fluid from pockets with chronic infections was sampled as a source for the three types of bacteria, Porphyromonas gingivalis, Tannerella forsythia

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Publication Date
Tue Jan 19 2016
Journal Name
Journal Of Engineering
Assessing Close Range Photogrammetric Approach to Evaluate Pavement Surface Condition
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The aim of this research is to adopt a close range photogrammetric approach to evaluate the pavement surface condition, and compare the results with visual measurements. This research is carried out on the road of Baghdad University campus in AL-Jaderiyiah for evaluating the scaling, surface texture for Portland cement concrete and rutting, surface texture for asphalt concrete pavement. Eighty five stereo images of pavement distresses were captured perpendicular to the surface using a DSLR camera. Photogrammetric process was carried out by using ERDAS IMAGINE V.8.4. The results were modeled by using a relationship between the photogrammetric and visual techniques and selected the highest coefficient of determination (R2). The first techniqu

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Engineering
Assessing Close Range Photogrammetric Approach to Evaluate Pavement Surface Condition
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The aim of this research is to adopt a close range photogrammetric approach to evaluate the pavement surface condition, and compare the results with visual measurements. This research is carried out on the road of Baghdad University campus in AL-Jaderiyiah for evaluating the scaling, surface texture for Portland cement concrete and rutting, surface texture for asphalt concrete pavement. Eighty five stereo images of pavement distresses were captured perpendicular to the surface using a DSLR camera. Photogrammetric process was carried out by using ERDAS IMAGINE V.8.4.  The results were modeled by using a relationship between the photogrammetric and visual techniques and selected the highest coefficient of determinatio

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Publication Date
Mon Nov 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Evaluating Quality of Control Policies and Procedures for Banking Transactions Using the Non-application Gap Model to Enhance Financial Reporting Requirements Applied Study in an Iraqi Private Bank
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The research aims to enhance the level of evaluation of the performance of banking transactions control policies and procedures. The research is based on the following hypothesis: efficient transactions control policies and procedures contribute enhancing financial reporting, by assessing non-application gap of those policies and procedures in a manner that helps to prevent, discover, and correct material misstatementsThe researchers designed an examination list that includes the control policies and procedures related to the transactions, as a guide to the bank audit program prepared by the Federal Financial Supervision Bureau. The research methodology is

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Publication Date
Sun Oct 22 2023
Journal Name
Iraqi Journal Of Science
A Hybrid Estimation System for Medical Diagnosis using Modified Full Bayesian Classifier and Artificial Bee Colony
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This paper presents a hybrid approach called Modified Full Bayesian Classifier (M-FBC) and Artificial Bee Colony (MFBC-ABC) for using it to medical diagnosis support system. The datasets are taken from Iraqi hospitals, these are for the heart diseases and the nervous system diseases. The M-FBC is depended on common structure known as naïve Bayes. The structure for network is represented by D-separated for structure's variables. Each variable has Condition Probability Tables (CPTs) and each table for disease has Probability. The ABC is easy technique for implementation, has fewer control parameters and it could be easier than other swarm optimization algorithms, so that hybrid with other algorithms to reach the optimal structure. In the

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Publication Date
Sun Mar 04 2018
Journal Name
Iraqi Journal Of Science
Evaluate the climatic conditions for the Karbala
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This study includes determining the climatic conditions and the nature of the reservoirs in the region with the determination of the flow direction of the aquifer. The meteorological data for the Karbala station for the period 1976-2016 showed that the values of the monthly rates of temperature, precipitation, evaporation, relative humidity, wind speed and Sunshine duration are (24.19 C◦), (95.5 mm), (2828.6mm), (46.75%), (2.76 m/sec), and (8.61 h/day) respectively. Thorenthwait method was used to calculate the values of Potential Evapotranspiration (PE) then determine the annual value of WS and WD which equal 28.11mm and 941.94mm respectively. Mean monthly water surplus for the period (1976-2016) was recorded about (9.36mm) in Decembe

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Publication Date
Mon May 15 2023
Journal Name
Iraqi Journal Of Science
Using Linear Local Dependence Measure to Study the factors that are Leading to the Growth of Preferring the Application in Private Universities of Iraq
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In this paper a measure of linear local dependence has been used between two
random variables and a study is conducted for the properties of this measure where
two examples of bivariate probability distributions has been considered, which are
bivariate Gumbel distribution and bivariate Beta-Stacy distribution, and applied on
data collected by using a questionnaire conducted to study the reasons for the
increase of application in private collages in Iraq. Five elements has been considered
as random variables and the dependence has been measured between every two
elements to estimate how correlated these elements are and their effect on the
application in private collages of Iraq generally and Baghdad specifically.<

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Publication Date
Wed Jan 29 2020
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Measuring the efficiency of quality health services in the province of Karbala: Models using the Data envelopment analysis (DEA)
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  The research aims to measure  the efficiency of health services Quality  in the province of Karbala, using the Data Envelopment analysis Models in ( 2006). According to these models the degree of efficiency ranging between zero and unity. We estimate Scale efficiency  for two types of orientation direction, which are input and output oriented direction.

  The results showed, according Input-oriented efficiency that the levels of Scale efficiency on average is ( 0.975), in the province of Karbala. While the index of Output-oriented efficiency on average is (o.946).

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Publication Date
Wed Mar 31 2021
Journal Name
Electronics
Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model
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Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

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