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Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. The artificial neural networks show a high coefficient of determination between the predicted and observed domestic solid waste, with R2 value reaching to 0.91, 0.828 and 0.827 for Al-Karkh, 0.9986,0. 9903 and 0.9903 for Rusafa side, and 0.9989, 0.9878 and 0.9847 in Baghdad city, and also, these models were used to estimate the generation of municipal solid waste for short period with highly efficient which assistance in planning to design landfills sites.

 

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Engineering
Optimization of Dye Removal Using Waste Natural Material and Polymer Particles
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In this paper waste natural material (date seed) and polymer particles(UF) were used for investigation of  removal dye of the potassium permanganate. Also study effect some variables such as pH, dye concentration and adsorbent concentration on dye removal. 15 experimental runs were done using  the itemized conditions designed established on the Box-Wilson design employed to optimize dye removal. The optimum conditions for the dye removal were found: (pH) 12, (dye con.) 2.38 ppm, (adsorbant con.) 0.0816 gm for date seed with 95.22% removal and for UF (pH) 12, (dye con.) 18 ppm, (adsorbant con.) 0.2235 gm with 91.43%. The value of R-square was 85.47%  for Date seed  and (88.77%) for UF.

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Publication Date
Thu Dec 13 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of Women's Knowledge and Personal Preference about The Place of Delivery in Baghdad City
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Objective: The study aim to evaluate of women's knowledge and personal preference about the place
of delivery in Baghdad City
Methodology:
descriptive study conducted in baghdad city on the mothers for the period from the 14th of December,
2015 to the 14th of April 2016. The sample of study included 500 mothers who were attending to
primary health care centers have been chosen sample of 26 primary health care center by a multi-stage
Simple random sampling Data was collected through a constructed questionnaire, validity Data was
analyzed by using of descriptive and inferential data analysis methods .
Results: The results indicated that approximately (29.4%) of the mothers in the age group (20-24) and
the average

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Publication Date
Thu Jan 22 2026
Journal Name
Univesity Of Thi-qar Journal
Analysis of Heavy Metals in Water Samples of Euphrates River in Nasiriya City, Iraq
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Publication Date
Thu Jun 23 2022
Journal Name
American Scientific Research Journal For Engineering, Technology, And Sciences
A Review of TCP Congestion Control Using Artificial Intelligence in 4G and 5G Networks
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In recent years, the field of research around the congestion problem of 4G and 5G networks has grown, especially those based on artificial intelligence (AI). Although 4G with LTE is seen as a mature technology, there is a continuous improvement in the infrastructure that led to the emergence of 5G networks. As a result of the large services provided in industries, Internet of Things (IoT) applications and smart cities, which have a large amount of exchanged data, a large number of connected devices per area, and high data rates, have brought their own problems and challenges, especially the problem of congestion. In this context, artificial intelligence (AI) models can be considered as one of the main techniques that can be used to solve ne

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Detection and Removal of Polycyclic Aromatic Hydrocarbon from Selected Areas in Tigris River in Baghdad City
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Aromatic hydrocarbons present in Iraqi national surface water were believed to be raised principally from combustion of various petroleum products, industrial processes and transport output and their precipitation on surface water.
Polycyclic aromatic hydrocarbons (PAHs) were included in the priority pollutant list due to their toxic and carcinogenic nature. The concern about water contamination and the consequent human exposure have encouraged the development of new methods for
PAHs detection and removal.
PAHs, the real contaminants of petroleum matter, were detected in selected sites along Tigris River within Baghdad City in summer and winter time, using Shimadzu high performance liquid chromatography (HPLC) system.
Analysi

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Publication Date
Tue Jun 11 2019
Journal Name
Al-kindy College Medical Journal
Evaluation of Application of Nutritional Status Assessment for Children Under 5 years by Using IMCI Program in a Sample of Primary Health Care Centers in Baghdad City
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Background: World Health Organization (WHO) and United Nation International Children Fund (UNICEF) developed a strategy known as Integrated Management of Childhood Illness (IMCI); which aims to reduce less than five years children morbidity and mortality in developing countries.

Objective: To assess the completion of the IMCI format status in primary health care centers, Baghdad.

Methods:  A cross sectional study with analytic element was conducted during the period from 15th  of January till 15th  May 2016 in selected Primary health centers in Baghdad, Iraq. The sample consists of form of child files less than 2 months and form from 2

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Publication Date
Mon Nov 11 2019
Journal Name
Spe
Modeling Rate of Penetration using Artificial Intelligent System and Multiple Regression Analysis
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Abstract<p>Over the years, the prediction of penetration rate (ROP) has played a key rule for drilling engineers due it is effect on the optimization of various parameters that related to substantial cost saving. Many researchers have continually worked to optimize penetration rate. A major issue with most published studies is that there is no simple model currently available to guarantee the ROP prediction.</p><p>The main objective of this study is to further improve ROP prediction using two predictive methods, multiple regression analysis (MRA) and artificial neural networks (ANNs). A field case in SE Iraq was conducted to predict the ROP from a large number of parame</p> ... Show More
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Publication Date
Sun Mar 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Prepare Maps For Greenhouse Gases With Some Weather Elements For Baghdad City Using Data Observation And Arc-GIS Techniques
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Abstract<p>Air pollution refers to the release of pollutants into the air that are detrimental to human health and the planet as a whole.In this research, the air pollutants concentration measurements such as Total Suspended Particles(TSP), Carbon Monoxides(CO),Carbon Dioxide (CO2) and meteorological parameters including temperature (T), relative humidity (RH) and wind speed & direction were conducted in Baghdad city by several stations measuring numbered (22) stations located in different regions, and were classified into (industrial, commercial and residential) stations. Using Arc-GIS program ( spatial Analyses), different maps have been prepared for the distribution of different pollutant</p> ... Show More
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Publication Date
Wed Aug 17 2022
Journal Name
Applied Sciences
Predicting Fruit’s Sweetness Using Artificial Intelligence—Case Study: Orange
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The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

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Publication Date
Mon Dec 16 2024
Journal Name
International Journal Of Computing And Digital Systems
Digital Intelligence for University Students Using Artificial Intelligence Techniques
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The research problem arose from the researchers’ sense of the importance of Digital Intelligence (DI), as it is a basic requirement to help students engage in the digital world and be disciplined in using technology and digital techniques, as students’ ideas are sufficiently susceptible to influence at this stage in light of modern technology. The research aims to determine the level of DI among university students using Artificial Intelligence (AI) techniques. To verify this, the researchers built a measure of DI. The measure in its final form consisted of (24) items distributed among (8) main skills, and the validity and reliability of the tool were confirmed. It was applied to a sample of 139 male and female students who were chosen

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