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Mathematical Models for Predicting of Organic and Inorganic Pollutants in Diyala River Using AnalysisNeural Network
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Diyala river is the most important tributaries in Iraq, this river suffering from pollution, therefore, this research aimed to predict organic pollutants that represented by biological oxygen demand BOD, and inorganic pollutants that represented by total dissolved solids TDS for Diyala river in Iraq, the data used in this research were collected for the period from 2011-2016 for the last station in the river known as D17, before the river meeting Tigris river in Baghdad city. Analysis Neural Network ANN was used in order to find the mathematical models, the parameters used to predict BOD were seven parameters EC, Alk, Cl, K, TH, NO3, DO, after removing the less importance parameters. While the parameters that used to predict TDS were fourteen parameters pH, DO, BOD, PO4, NO3,Ca, Mg, TH, K, Na, SO4,Cl, EC, Alk. The results indicated that the best correlation coefficient is 86.5% for BOD, and the most important parameter is Chloride Cl, and the best correlation coefficient is 95.4% for TDS and the most important parameters are total hardness TH and electrical conductivity EC, according to direct relation between these parameters and TDS.

Publication Date
Sat Dec 02 2023
Journal Name
Journal Of Engineering
Performance Assessment of Pile Models Chemically Grouted by Low-Pressure Injection Laboratory Device for Improving Loose Sand
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The complexity and partially defined nature of jet grouting make it hard to predict the performance of grouted piles. So the trials of cement injection at a location with similar soil properties as the erecting site are necessary to assess the performance of the grouted piles. Nevertheless, instead of executing trial-injected piles at the pilot site, which wastes money, time, and effort, the laboratory cement injection devices are essential alternatives for evaluating soil injection ability. This study assesses the performance of a low-pressure laboratory grouting device by improving loose sandy soil injected using binders formed of Silica Fume (SF) as a chemical admixture (10% of Ordinary Portland Cement OPC mass) to di

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Publication Date
Sat Jul 01 2017
Journal Name
Diyala Journal For Pure Science
Correlated Hierarchical Autoregressive Models Image Compression
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Publication Date
Wed Oct 18 2023
Journal Name
Ieee Access
A New Imputation Technique Based a Multi-Spike Neural Network to Handle Missing Data in the Internet of Things Network (IoT)
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Publication Date
Tue Aug 24 2021
Journal Name
Agronomy
Impact of Nitrogen Rate in Conventional and Organic Production Systems on Yield and Bread Baking Quality of Soft Red Winter Wheat
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Soft red winter wheat (SRW) is characterized by high yield and relatively low protein content. In Kentucky, there is growing demand from local artisan bread bakers for regionally produced flour, requiring production of grain with increased protein content and/or strength. The objective of this two-year field experiment was to evaluate the effect of nitrogen (N) management on five cultivars of winter wheat on yield and bread baking quality traits of modern and landrace SRW cultivars (Triticum aestivum L.). All five cultivars were evaluated using two N application rates in conventional and organic production systems. All traits measured were significantly affected by the agricultural production system and N rate, although plant height

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Publication Date
Mon Jun 22 2015
Journal Name
Photonic Sensors
Capacitive-resistive measurements of cobalt-phthalocyanine organic humidity sensors
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Publication Date
Mon Jun 22 2015
Journal Name
Photonic Sensors
Capacitive-resistive measurements of cobalt-phthalocyanine organic humidity sensors
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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Time Series Analysis of Total Suspended Solids Concentrations in Euphrates River in Al-Nasria Province
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The monthly time series of the Total Suspended Solids (TSS) concentrations in Euphrates River at Nasria was analyzed as a time series. The data used for the analysis was the monthly series during (1977-2000).

The series was tested for nonhomogenity and found to be nonhomogeneous. A significant positive jump was observed after 1988. This nonhomogenity was removed using a method suggested by Yevichevich (7). The homogeneous series was then normalized using Box and Cox (2) transformation. The periodic component of the series was fitted using harmonic analyses, and removed from the series to obtain the dependent stochastic component. This component was then modeled using first order autoregressive model (Markovian chain). The above a

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Publication Date
Sat Jan 01 2022
Journal Name
Indian Journal Of Ecology
Effect of Mycorrhiza, Cytokinin and Organic Fertilizer on the Growth and Yield of Chamomile Plant L)
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The experiment was carried out in College of Agricultural Engineering Sciences, University of Baghdad during November 1, 2019 to June 1, 2020. The experiment was designed according to a randomized complete block design. Each block contained 18 experimental units that included the three study factors. The first factor interaction between two inoculum densities and application methods, three levels control, treatment of seeds inoculation with 5g plant and treatment of seedlings inoculation whith 30g plant . The second factor was three -1 -1concentrations of spraying of kinetin 0, 75 and 150 mg L , and third factor include two levels of organic manure) and addition of fertilizer 2% of -1 the weight of the soil (O2). The results showed a signif

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Publication Date
Tue Feb 28 2012
Journal Name
Arabian Journal Of Geosciences
Hydrochemistry and pollution probability of selected sites along the Euphrates River, Western Iraq
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Publication Date
Mon Aug 28 2023
Journal Name
Journal Of Planner And Development
Estimation of urban land price within holly cities by using integrated GIS-regression models: case study Al-Kufa city- Iraq
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        Urban land price is the primary indicator of land development in urban areas. Land prices in holly cities have rapidly increased due to tourism and religious activities. Public agencies are usually facing challenges in managing land prices in religious areas. Therefore, they require developed models or tools to understand land prices within religious cities. Predicting land prices can efficiently retain future management and develop urban lands within religious cities. This study proposed a new methodology to predict urban land prices within holy cities. The methodology is based on two models, Linear Regression (LR) and Support Vector Regression (SVR), and nine variables (land price, land area,

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