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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
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Fri Mar 31 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The Chages in Sex Hormones in Female Working in Battries Manufacturing Plant
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Lead has toxic effects on reproduction of both male and female.  It can cause decreased sex drive ,  infertility and abnormal menstrual cycle  in women.  This study was designed to evaluate the effect of exposure to lead in batteries female workers on sex hormones level in the serum.Thirty nine (39) female workers (volunteers) in Iraqi Batteries Manufacturing Plants, Al-Waziriya / Baghdad  were participated in this study. They are classified into 3 groups,  first group included fourteen (14) female that  have been employed for 1-7 years ,  second  group  included thirteen (13) female that have been employed for 8-14 years , third  grou

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Sun Jan 01 2023
Journal Name
Phyton
Toxic and Antifeedant Effects of Different Pesticidal Plant Extracts against Beet Armyworm (&lt;i&gt;Spodoptera exigua&lt;/i&gt;)
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The beet armyworm (BAW), Spodoptera exigua (Lepidoptera: Noctuidae) is a highly destructive pest of vegetables and field crops. Management of beet armyworm primarily relies on synthetic pesticides, which is threatening the beneficial community and environment. Most importantly, the BAW developed resistance to synthetic pesticides with making it difficult to manage. Therefore, alternative and environment-friendly pest management tactics are urgently required. The use of pesticidal plant extracts provides an effective way for a sustainable pest management program. To evaluate the use of pesticidal plant extracts against BAW, we selected six plant species (Lantana camara, Aloe vera, Azadirachta indica, Cymbopogon citratus, Nicotiana tabacum ,

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Publication Date
Sat Jun 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of some methods for estimating the parameters of the binary logistic regression model using the genetic algorithm with practical application
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Abstract

   Suffering the human because of pressure normal life of exposure to several types of heart disease as a result of due to different factors. Therefore, and in order to find out the case of a death whether or not, are to be modeled using binary logistic regression model

    In this research used, one of the most important models of nonlinear regression models extensive use in the modeling of applications statistical, in terms of heart disease which is the binary logistic regression model. and then estimating the parameters of this model using the statistical estimation methods, another problem will be appears in estimating its parameters, as well as when the numbe

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Publication Date
Sat Dec 11 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Anastrozole Loaded Nanostructured Lipid Carriers : Preparation and Evaluation
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Anastrozole (ANZ) is considered constitute of the fourth –generation of Non–steroidal aromatase blockage, ANZ has use for hormone receptor positive breast cancer in postmenopausal women. The serious side effects of ANZ including, vaginal dryness, hot flashes, irritability, breast tenderness and un–stability in circulation.

Nanostructured lipid carriers (NLCs) have recently emerged as a multifunctional platform for drug delivery in cancer therapy.

Five formula were composed of (200 mg of glyceryl monostearate, 40 mg of oleic acid , 1% (w/w) Tween 80, 1% (w/w) Poloxamer 407, 1% (w/w) soy lecithin and Vitamin E Polyethylene Glycol Succinate.

The mean particle size, polydispersity index, zeta potential, entrapme

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Publication Date
Thu Oct 31 2019
Journal Name
Al-kindy College Medical Journal
Assessment of efficacy and safety of dapsone gel 5% in the treatment of acne vulgaris
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ABSTRACTBackground : Acne vulgaris is a
common skin disease, affecting more than 85% of
adolescents and often continuing into adulthood.
People between 11 and 30 years of age and up to
5% of older adults. For most patients acne remains
a nuisance with occasional flares of unsightly
comedones, pustules and nodules. For other less
fortunate persons, the sever inflammatory response
to Propionibacterium acnes (P.acnes) results in
permanent
Methods: Disfiguring scars. (1, 2) Stigmata of sever
acne cane lead to social ostracism, withdrawal
from society and severe psychologic
depression (1-4).
Result Pathogenesis of acne Traditionally, acne
has been thought of as a multifactorial disease of
the fo

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Publication Date
Sat Jan 01 2011
Journal Name
Journal Of Engineering
FILTRATION MODELING USING ARTIFICIAL NEURAL NETWORK (ANN)
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In this research Artificial Neural Network (ANN) technique was applied to study the filtration process in water treatment. Eight models have been developed and tested using data from a pilot filtration plant, working under different process design criteria; influent turbidity, bed depth, grain size, filtration rate and running time (length of the filtration run), recording effluent turbidity and head losses. The ANN models were constructed for the prediction of different performance criteria in the filtration process: effluent turbidity, head losses and running time. The results indicate that it is quite possible to use artificial neural networks in predicting effluent turbidity, head losses and running time in the filtration process, wi

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Determination of Copper and Lead and Study their Poisonous Effects in Drinking Water in Baghdad
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The objective of this study is to determine the concentration of copper and lead (mg/L) in drinking water by using absorption spectrophotometic and Atomic Absorption spectrophotometric method from different area in Baghdad and with different intervals , The results show that the concentration of copper and Lead ( mgL) in tap water which remains motionless in plumbing system for following periods one hours, 3 hours, 6 hours, 12 hours, 24 hours, 7 days and 14 days are (1 , 2.2 , 4 , 5.3 , 7.5 , 10 and 16 mgL copper ) & ( 0.3, 0.5 , 0.8 , 1 , 2.5 , 3 , 3.8 mg /L lead ) respectively .from these results its clear that high levels of copper & Lead occur if tap water comes in contact with copper - lead plumbing and copper lead -containing fix

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Publication Date
Wed Oct 01 2008
Journal Name
2008 First International Conference On Distributed Framework And Applications
A strategy for Grid based t-way test data generation
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