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Artificial Neural Network Model for the Prediction of Groundwater Quality
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The present article delves into the examination of groundwater quality, based on WQI, for drinking purposes in Baghdad City. Further, for carrying out the investigation, the data was collected from the Ministry of Water Resources of Baghdad, which represents water samples drawn from 114 wells in Al-Karkh and Al-Rusafa sides of Baghdad city. With the aim of further determining WQI, four water parameters such as (i) pH, (ii) Chloride (Cl), (iii) Sulfate (SO4), and (iv) Total dissolved solids (TDS), were taken into consideration. According to the computed WQI, the distribution of the groundwater samples, with respect to their quality classes such as excellent, good, poor, very poor and unfit for human drinking purpose, was found to be 14.9 %, 39.5 %, 22.8 %, 6.1 %, and 16.7 %, respectively. Additionally, to anticipate changes in groundwater WQI, IBM® SPSS® Statistics 19 software (SPSS) was used to develop an artificial neural network model (ANNM). With the application of this ANNM model, the results obtained illustrated high prediction efficiency, as the sum of squares error functions (for training and testing samples) and coefficient of determination (R2), were found to be (0.038 and 0.005) and 0.973, respectively. However, the parameters pH and Cl influenced model prediction significantly, thereby becoming crucial factors in the anticipation carried out by using ANNM model.

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Publication Date
Mon Mar 15 2021
Journal Name
Iraqi National Journal Of Nursing Specialties
Assessment of Health Care Quality through Clients’ Perspectives at Outpatient Consultancy Clinics in Al-Hilla City Hospitals
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Objectives: To assess quality of health care for clients at outpatient consultancy clinics in Al-Hilla City Hospitals, and to find out significant differences between the clients' perspectives toward quality of health care dimensions and their demographic characteristics such as (residence, age, gender, level of education, and occupation ).
Methodology: A descriptive analytic study design was carried out at outpatient consultancy clinics of Al- Hilla city hospital (Al-Hilla and Al-Imam Al-Sadiq general teaching hospital) from April 10 th to June 15 th 2019. Non – probability (purposive) sample of 200 clients who were coming to the Outpatient Consultancy Clinics were selected. Data is collected through used of an assessment tools an

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Publication Date
Wed Nov 22 2017
Journal Name
Farm Machinery And Processes Management In Sustainable Agriculture, Ix International Scientific Symposium
INFLUENCE OF PHYSICAL PROPERTIES OF WATER-ADJUVANT MIXTURE ON THE DROPLET STAINS DEPOSITING ON AN ARTIFICIAL TARGET
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Publication Date
Sun Jun 30 2002
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
A Phase Behavior Compositional Model for Jambour Cretaceous Oil Reservoir
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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
ESTIMATED NON-PARAMETRIC AND SEMI-PARAMETRIC MODEL FOR LONGITUDINAL DATA
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Publication Date
Tue Nov 27 2018
Journal Name
The Iraqi Geological Journal
CHRONOSTRATIGRAPHICALLY BASED RESERVOIR MODEL FOR CENOMANIAN CARBONATES, SOUTHEASTERN IRAQ OILFIELDS
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The Cenomanian – Turronian sedimentary succession in the south Iraq oil fields, including Ahmadi, Rumaila, Mishrif and Khasib formations have undergone into high-resolution reservoir-scale genetic sequence stratigraphic analysis. Some oil-wells from Majnoon and West-Qurna oil fields were selected as a representative case for the regional sequence stratigraphic analysis. The south Iraqi Albian – Cenomanian – Turronian succession of 2nd-order depositional super-sequence has been analyzed based on the Arabian Plate chronosequence stratigraphic context, properly distinguished by three main chrono-markers (The maximum flooding surface, MFS-K100 of the upper shale member of Nahr Umr Formation, MFS-K140 of the upper Mishrif carbonate

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Publication Date
Thu Jun 01 2023
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
An optimized deep learning model for optical character recognition applications
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The convolutional neural networks (CNN) are among the most utilized neural networks in various applications, including deep learning. In recent years, the continuing extension of CNN into increasingly complicated domains has made its training process more difficult. Thus, researchers adopted optimized hybrid algorithms to address this problem. In this work, a novel chaotic black hole algorithm-based approach was created for the training of CNN to optimize its performance via avoidance of entrapment in the local minima. The logistic chaotic map was used to initialize the population instead of using the uniform distribution. The proposed training algorithm was developed based on a specific benchmark problem for optical character recog

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Publication Date
Mon Mar 30 2026
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Adaptive Security Model for Data Protection Using Behavioral User Authentication
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Credential compromise is one of the most widespread security threats, allowing adversaries to bypass traditional authentication measures and impersonate legitimate users. Traditional intrusion detection systems are often based on network-level or macro-behavioral indicators, which can be easily spoofed by an attacker, thus compromising the effectiveness of those mechanisms. This study presents an improved adaptive intrusion detection system to authenticate user behavior based on micro-digital behavioral profiling. It involves the use of timing of keystrokes, micro-mouse, navigation in the application, and interaction rhythm signatures. The proposed system uses a hybrid model consisting of Long Short-Term Memory (LSTM) sequence predi

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Publication Date
Fri Jan 01 2021
Journal Name
Annals Of Pure And Applied Mathematics
Linear Regression Model Using Bayesian Approach for Iraqi Unemployment Rate
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In this paper we used frequentist and Bayesian approaches for the linear regression model to predict future observations for unemployment rates in Iraq. Parameters are estimated using the ordinary least squares method and for the Bayesian approach using the Markov Chain Monte Carlo (MCMC) method. Calculations are done using the R program. The analysis showed that the linear regression model using the Bayesian approach is better and can be used as an alternative to the frequentist approach. Two criteria, the root mean square error (RMSE) and the median absolute deviation (MAD) were used to compare the performance of the estimates. The results obtained showed that the unemployment rates will continue to increase in the next two decade

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Design a supply chain model for Baghdad Soft Drinks Company
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In this paper, a mathematical model was built for the supply chain to reduce production, inventory, and transportation in Baghdad Company for Soft Drink. The linear programming method was used to solve this mathematical model. We reduced the cost of production by reduced the daily work hours, the company do not need the overtime hours to work at the same levels of production, and the costs of storage in the company's warehouses and agents' stores have been reduced by making use of the stock correctly, which guarantees reducing costs and preserving products from damage. The units transferred from the company were equal to the units demanded by the agents. The company's mathematical model also achieved profits by (84,663,769) by re

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Publication Date
Sat Jun 01 2019
Journal Name
Al-nahrain Journal Of Science
THREE DIMENSIONAL EXPLICIT MODEL FOR COMETARY TAIL IONSINTERACTIONSWITH SOLAR WIND
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The different interactions between cometary tail and solar wind ions are studied in the present paper based on three-dimensional Lax explicit method. The model used in this research is based on the continuity equations describing the cometary tail-solar wind interactions. Three dimensional system was considered in this paper. Simulation of the physical system was achieved using computer code written using Matlab 7.0. The parameters studied here assumed Halley comet type and include the particle density , the particles velocity v, the magnetic field strength B, dynamic pressure p and internal energy E. The results of the present research showed that the interaction near the cometary nucleus is mainly affected by the new ions added to the

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