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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
Fri Nov 09 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Organization Structure as Component of Quality Improvement for Maternal and Child Health Promotion in Baghdad City’s Primary Health Care Centers
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A descriptive evaluation study is conducted on primary health care centers in Baghdad City in order to
evaluate the organization structure as component of quality improvement of maternal and child health promotion
from April 10th 2012 to May20th 2013. A total of (22) primary health care centers. Study instrument was
comprised of three questionnaires and overall items included in these questionnaire were (65) items. Data are
collected through the utilization of the developed questionnaire and the interview technique as means of data
collection. Data are analyzed through the application of descriptive statistical data analysis methods which
includes the measurement of the frequencies, percentages, and computation of mean

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Publication Date
Sun Mar 26 2023
Journal Name
Wasit Journal Of Pure Sciences
Covid-19 Prediction using Machine Learning Methods: An Article Review
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The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

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Publication Date
Fri Apr 01 2016
Journal Name
Journal Of Engineering
The Use of the Artificial Damped Outrigger Systems in Tall R.C Buildings Under Seismic Loading
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This paper studies the combination of fluid viscous dampers in the outrigger system to add supplementary damping into the structure, which purpose to remove the dependability of the structure to lower variable intrinsic damping. This optimizes the accuracy of the dynamic response and by providing higher level of damping, basically minimizes the wanted stiffness of the structure while at the same time optimizing the achievement.

     The modal considered is a 36 storey square high rise reinforced concrete building. By constructing a discrete lumped mass model and using frequency-based response function, two systems of dampers, parallel and series systems are studied. The maximu

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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Publication Date
Sun Sep 01 2019
Journal Name
2019 11th Computer Science And Electronic Engineering (ceec)
ANN based Measurement for No-Reference Video Quality of Experience Metric
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Publication Date
Mon Oct 28 2013
Journal Name
Desalination And Water Treatment
Groundwater protection from cadmium contamination by zeolite permeable reactive barrier
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This work studies the performance of zeolite permeable reactive barrier in removing cadmium from a contaminated shallow aquifer. Batch tests have been performed to characterize the equilibrium sorption properties of the zeolite in cadmium-containing aqueous solutions. A 1D numerical finite difference model has been developed to describe pollutant transport within groundwater taking pollutant sorption on the permeable reactive barrier (PRB), which is performed by Langmuir equation, into account. Numerical results show that the PRB starts to saturate after a period of time (~120 h) due to reduction of the retardation factor, indicating a decrease in the percentage of zeolite functionality. However, a reasonable agreement between model predict

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Publication Date
Mon Apr 30 2018
Journal Name
Journal Of Theoretical And Applied Information Technology
An efficient artificial fish swarm algorithm with harmony search for scheduling in flexible job-shop problem
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Flexible job-shop scheduling problem (FJSP) is one of the instances in flexible manufacturing systems. It is considered as a very complex to control. Hence generating a control system for this problem domain is difficult. FJSP inherits the job-shop scheduling problem characteristics. It has an additional decision level to the sequencing one which allows the operations to be processed on any machine among a set of available machines at a facility. In this article, we present Artificial Fish Swarm Algorithm with Harmony Search for solving the flexible job shop scheduling problem. It is based on the new harmony improvised from results obtained by artificial fish swarm algorithm. This improvised solution is sent to comparison to an overall best

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Publication Date
Sat Apr 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Spatial Distribution of Soil Quality and Health Index for the Umm Al-Naaj Marsh in Maysan
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The Umm Al-Naaj Marsh was chosen in Maysan province, and it is one of the sections of Mar Al-Hawza, which is one of the most prominent Iraqi marshes in the south. The marshes are located between latitudes 30 35 and 32 45 latitudes and longitudes 13 46 and 48 00. The area of the study area is 76479.432142 hectares to evaluate soil quality and health index and their spatial distribution based on measuring physical, chemical, biological and fertility traits and calculating the total quality index for those characteristics. Using an auger drilling machine, we collected 50 randomly selected surface samples, evenly distributed across the study region, from Al-Aq 0.0–0.30 m, noting their precise locations along the way. Soil health and quality w

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Publication Date
Wed Jun 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
A proposed model for disclosing the role of the collective intelligence system in improving joint auditing
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This research aims to present a proposed model for disclosure and documentation when performing the audit according to the joint audit method by using the questions and principles of the collective intelligence system, which leads to improving and enhancing the efficiency of the joint audit, and thus enhancing the confidence of the parties concerned in the outputs of the audit process. As the research problem can be formulated through the following question: “Does the proposed model for disclosure of the role of the collective intelligence system contribute to improving joint auditing?”   

The proposed model is designed for the disclosure of joint auditing and the role

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
A Comparative Study for Estimate Fractional Parameter of ARFIMA Model
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      Long memory analysis is one of the most active areas in econometrics and time series where various methods have been introduced to identify and estimate the long memory parameter in partially integrated time series. One of the most common models used to represent time series that have a long memory is the ARFIMA (Auto Regressive Fractional Integration Moving Average Model) which diffs are a fractional number called the fractional parameter. To analyze and determine the ARFIMA model, the fractal parameter must be estimated. There are many methods for fractional parameter estimation. In this research, the estimation methods were divided into indirect methods, where the Hurst parameter is estimated fir

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