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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
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Evaluation Among Choices Of Water Quality Improvement By Using Some Of Total Quality Management Tools Applied Research In Baghdad Governorate Water Directorate
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  Many managers in geometrical and technical organizations prefer to deal with quantitative values ​​to choose between the available options and choose the best alternative to avoid randomization and bias in decision making. One of them Baghdad Water Department, which seeks to develop the quality of its product (drinking water) and achieve its objectives under increasing growing population and the demand for water, Some of TQM tools, especially the statistical, have this ability because there is chance to use historical data and experiment of employees in Application . Two statistical tools were applied: the nominal group technique, matrix data analysis technique as well as the brainstorming tool to search for the best o

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Publication Date
Fri Jul 01 2016
Journal Name
Al–bahith Al–a'alami
Semiotics of Sufi Texts- Poets of Al Qasr and Al-Asr journals as a Model
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In a common language based on interpretation and diagnosis in the symbols and signs, the subject of Sufism and artistic semiotics is manifested in the construction and intensity of the reading of the text and the dismantling of its intellectual systems.
The emergence of Sufism in its religious features and the spiritual revelations related to the divine love of life in absolute reality, And images and language in a stream of intellectual and artistic unique and harmonious communicates with the subject of the themes of the Arab literature and its implications, but it is separated by a special entity signals and symbols related to the mysticism and worship.
    The unleashing of the imagination and the diagnosis,

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Publication Date
Wed Jan 01 2020
Journal Name
Periodicals Of Engineering And Natural Sciences
Comparison between the estimated of nonparametric methods by using the methodology of quantile regression models
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This paper study two stratified quantile regression models of the marginal and the conditional varieties. We estimate the quantile functions of these models by using two nonparametric methods of smoothing spline (B-spline) and kernel regression (Nadaraya-Watson). The estimates can be obtained by solve nonparametric quantile regression problem which means minimizing the quantile regression objective functions and using the approach of varying coefficient models. The main goal is discussing the comparison between the estimators of the two nonparametric methods and adopting the best one between them

Scopus
Publication Date
Mon Nov 11 2019
Journal Name
Journal Of Global Pharma Technology
Using the Water Quality Index as a Powerful Tool to Assess the Water Quality for Drinking Purposes in Al-Salam, Western Region of Baghdad City, Iraq
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Background: Tap waters play an important role in fulfilling the people needs for drinking and domestic purposes. Contaminate the tap water with different pollutants has become an issue of great concern for 90% of people who are depended on the tap water as the main source of drinking. Pollutants can make their way easily into the delivering pipes which suffer from the leaking resulting in decreasing the quality of water. Objective: Therefore, assess the water quality for drinking purpose by calculating the water quality index is an important tool to ascertain whether the water is suitable for human consumption or not. Methods: In the present work, the water quality of the Al-Salam, western region of Baghdad city, Iraq was investigated for 7

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Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
An Embedded Data Using Slantlet Transform
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Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and signature image. A scaling factor ? in frequency domain control the quality of the watermarked images. Experimental results of signature image

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of Engineering
Determining and Predicting the Water Demand Dynamic System Model Mapping Urban Crawling and Monitoring Using Remote Sensing Techniques and GIS
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Evaluation of the Physical and Chemical Treatment of Wastewater for the Dairy Industry
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Dairy wastewater generally contains fats, lactose, whey proteins, and nutrients. Casein precipitation causes the effluent to decompose into a dark, strong-smelling sludge. Fluid waste contains soluble organic matter, suspended solids, and gaseous organic matter, which cause undesirable taste and smell, grant tone and turbidity, and advance eutrophication, which plays an essential role in increasing biological oxygen demand (BOD) in water. It also contains detergents and disinfecting agents from the rinses and washing processes, which increase the need for chemical oxygen (COD). One of the characteristics of dairy effluents is their relatively high temperature, high organic contents, and wide pH range, so the discharge of wastewater into

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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Effect of Magnetic Water Treatment on Prevention of CaCO3 Scales
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Permanent magnets of different intensities were used to investigate the effect of a magnetic field in the process of preventing deposits of calcium carbonate. The magnets were fixed on the water line from the tap outside. Then heating a sample of this water in flasks and measuring the amount of sediment in a manner weighted differences. These experiments comprise to the change of the velocity of water flow, which amounted to (0.5, 0.75, 1) m/sec through the magnetic fields that are of magnetic strength (2200, 6000, 9250, 11000) Gauss, and conduct measurements, tests and compare them with those obtained from the use of ordinary water.The results showed the effectiveness of magnetic treatment in reducing the rate of deposition of calcium carb

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Green Engineering
Assessment and modelling of water quality along Al-Gharraf River (Iraq)
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Scopus (11)
Scopus
Publication Date
Mon Mar 09 2026
Journal Name
International Journal Of Inventions In Engineering & Science Technology
Sentiment Analysis of Twitter Users Using Deep Learning Models
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This research suggests a robust and systematic way for Arabic Sentiment Analysis using a vast dataset of 66,666 text reviews. One of the main advantages of this study is that the dataset was perfectly balanced (33,333 positive samples and 33,333 negative samples). In machine learning, this 50/50 split is important because it eliminates class bias and enables the predictive model to treat both sentiment classes equally. As shown in the values of the metrics — overall accuracy, weighted precision, weighted recall, and F1 score — there is great similarity among them, indicating a stable and reliable assessment of the model's real potential throughout the Arabic dataset. Based on data profile, the average word count per review is 42.3

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