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River Water Salinity Impact on Drinking Water Treatment Plant Performance Using Artificial neural network
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The river water salinity is a major concern in many countries, and salinity can be expressed as total dissolved solids. So, the water salinity impact of the river is one of the major factors effects of water quality. Tigris river water salinity increase with streamline and time due to the decrease in the river flow and dam construction from neighboring countries. The major objective of this research to developed salinity model to study the change of salinity and its impact on the Al-Karkh, Sharq Dijla, Al-Karama, Al-Wathba, Al-Dora, and Al-Wihda water treatment plant along Tigris River in Baghdad city using artificial neural network model (ANN). The parameter used in a model built is (Turbidity, Ec, T.s, S.s, and TDS in) to predict the salinity TDSout.  Results showed that the effectiveness of the artificial neural network model to predicting the salinity is a good agreement between observed and the predicted value of the TDS, through the determination coefficient of the model is (0.998, 0.966, 0.997, 0.998, 0.996, and 0.996) for Al. Karkh, Sharq Dijla, Al.Karama, Al.Wathba, Al.Dora and Al.Wihda respectively. From this value can be shown that ANN is a successful tool for predicting the nonlinear equation of the salinity under different and complicated environmental case along the river.

 

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Publication Date
Wed Dec 09 2015
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
Effect of Sodium sulfite treatment on the trypsin inhibitors activity, protein isolate and protein solubility of complete and dehulling white bean seeds Phaseolus vulgaris.: Effect of Sodium sulfite treatment on the trypsin inhibitors activity, protein isolate and protein solubility of complete and dehulling white bean seeds Phaseolus vulgaris.
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The study aimed to increase the biological value of white bean. The effect of different concentrations 0.01 ,0.02,0.03,and 0.04 M of sodium sulfite solutions for 1hr at 70 ºC on the trypsin inhibitors activity, protein isolate and protein solubility of complete and dehulling white bean flour were studied.Trypsin inhibitors activity were reduced by 42.97, 58.69, 68.59 and 69.58% in complete white bean flour at 0.01 ,0.02, 0.03, 0.04 M respectively, while the corresponding values were 50.43, 61.00, 75.61 and 85.66% respectively in dehulling white bean flour .Protein isolate value was 13.41% and protein solubility was 2.2% in control sample, Furthermore, the using of chemical treatment showed that protein isolate was reduced gradually and

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Publication Date
Thu Nov 21 2019
Journal Name
Journal Of Engineering
A Neural Networks based Predictive Voltage-Tracking Controller Design for Proton Exchange Membrane Fuel Cell Model
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In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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Publication Date
Sat Oct 01 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to
perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance
Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of
identification strategy consists of a feed-forward neural network with a modified activation function that
operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have
been trained online and offline have been used, without requiring any previous knowledge about the
system to be identified. The activation function that is used in the hidden layer in FFNN is a modified
version of the wavelet func

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Publication Date
Mon Oct 17 2011
Journal Name
Journal Of Engineering
MODIFIED TRAINING METHOD FOR FEEDFORWARD NEURAL NETWORKS AND ITS APPLICATION in 4-LINK SCARA ROBOT IDENTIFICATION
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In this research the results of applying Artificial Neural Networks with modified activation function to perform the online and offline identification of four Degrees of Freedom (4-DOF) Selective Compliance Assembly Robot Arm (SCARA) manipulator robot will be described. The proposed model of identification strategy consists of a feed-forward neural network with a modified activation function that operates in parallel with the SCARA robot model. Feed-Forward Neural Networks (FFNN) which have been trained online and offline have been used, without requiring any previous knowledge about the system to be identified. The activation function that is used in the hidden layer in FFNN is a modified version of the wavelet function. This approach ha

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Performance Series Performance Metrics (*) A case study in the General Company for Cotton Industries
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The problem of the research is focused on importance limited of Iraq industrial companies in application of scientific measurements of supply chains performance,  The research sought to achieve a group of goals, the most important are , identifying the strengths and weaknesses in the reality of supply chain in General Company for Cotton Industries, The data and information required are gathered from the dependence company, records through the field observations and personal interviews, the research used some quantitative indicators to measure of supply chain performance, The research reached to many conclusions , the most outstanding among them is the existence of a strong inverse correlatio

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Publication Date
Mon Jun 20 2022
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MORPHOLOGICAL, ANATOMICAL AND CHEMICAL STUDY OF AN EXOTIC PLANT JATROPHA INTEGERRIMA JACQ. 1763 (EUPHORBIACEAE) IN IRAQ
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Jatropha L. is an exotic genus to Iraq and it has been cultivated in gardens for ornamental purposes because of the shiny red color of the flowers. The plant adapted to environmental conditions and succeeded in growing and blooming, which is why the species was interested to study. The species Jatropha integerrima Jacq. was examined and diagnosed for the first time in Iraq. Morphological and anatomical characteristics for leaves (considering that the variations are the most reliable and taxonomically important) were provided. The Phytochemical screening showed the presence of alkaloids, flavonoids, terpenes, tannins and saponins. The qualitative analysis by TLC indicated the presence of alkaloids and flavonoid that was detected by specia

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Publication Date
Sun Jul 09 2023
Journal Name
Journal Of Engineering
Comparative Study for Risk Criteria of Al-Qudus Plant between the Present and Planning of MOE
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The main function of a power system is to supply the customer load demands as economically as possible. Risk criterion is the probability of not meeting the load. This paper presents a methodology to assess probabilistic risk criteria of Al-Qudus plant before and after expansion; as this plant consists of ten generating units presently and the Ministry Of Electricity (MOE) is intending to compact four units to it in order to improve the performance of Iraqi power system especially at Baghdad region. The assessment is calculated by a program using Matlab programming language; version 7.6. Results show that the planned risk is (0.003095) that is (35 times) less than that in the present plant risk; (0.1091); which represents respectable imp

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Publication Date
Fri Feb 03 2023
Journal Name
Nano Hybrids And Composites
Synthesis and Characterization of Nanoparticles Extracted from <i>Catharanthus roseus</i> Plant
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The Catharanthus roseus plant was extracted and converted to nanoparticles in this work. The Soxhlet method extracted alkaloid compounds from the plant Catharanthus roseus and converted them to the nanoscale. Chitosan polymer was used as a linking material and converted to Chitosan nanoparticles using Sodium TriPolyPhosphate (STPP). The extracted alkaloids were linked with Chitosan nanoparticles CSNPs by maleic anhydride to get the final product (CSNPs- Linker- alkaloids). The synthesized (CSNPs- Linker- alkaloids) was characterized using SEM spectroscopy UV–Vis., Zeta Potential, and HPLC High-Performance Liquid Chromatography. Scanning electron microscope (SEM) analysis shows that the Chitosan nanoparticles (CSNPs) have small dim

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Publication Date
Tue Jan 01 2019
Journal Name
Plant Archive
The enhancement of drought tolerance for plant onion (allium cepa l.) inoculated by arbuscular mycorrhizal fungi
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Scopus (6)
Scopus
Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Effect of crude extracts of the plant local wolf riding in the growth of some fungi
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Make a search on the vegetative parts of the plant local horse guilt of some elements in the Haj Omran area in northern Iraq has included recognition of certain nutrients

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