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Water Quality Assessment and Sodium Adsorption Ratio Prediction of Tigris River Using Artificial Neural Network
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Sodium adsorption ratio (SAR) is considered as a measure of the water suitability for irrigation usage. This study examines the effect of the physicochemical parameters on water quality and SAR, which included Calcium(Ca+2), Magnesium(Mg+2), Sodium (Na+), Potassium (K), Chloride (Cl-), Sulfate(SO4-2), Carbonate (CO3-2), Bicarbonate (HCO3-), Nitrate (NO3-), Total Hardness (TH), Total Dissolved Salts (TDS), Electrical Conductivity (EC), degree of reaction (DR), Boron (B) and the monthly and annually flow discharge (Q). The water samples were collected from three stations across the Tigris River in Iraq, which flows through Samarra city (upstream), Baghdad city (central) and the end of Kut city (downstream) for the periods of 2016-2018. Results showed that the water quality of the Tigris River water is within the world health organization (WHO) specifications for drinking water except for Sulfate concentration. An artificial neural network (ANN) was used to develop the model for the three locations to predict SAR. The sum of the squared error function and the coefficient of determination (R2) were used to evaluate the amount of error in predicting values of SAR and performance evaluation of the model. The results showed that the highest value of the coefficient of determination was 0.992, 0.986, and 0.955 for Samarra, Baghdad, and Kut, respectively and the ANN analysis indicated that the prediction of SAR was effected by Sodium for three stations. Thus, the ANN model has been found to provide SAR prediction tool that can be used effectively to describe the suitability of river water quality for irrigation purposes.

Publication Date
Mon Oct 05 2020
Journal Name
International Journal Of Pharmaceutical Research
Adsorption and Kinetic of para-Nitroaniline on Iraqi Siliceous Rocks
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UV-Vis technique has been used to study the adsorption of para-nitroaniline (PNA) on Iraqi siliceous rocks powder. Adsorption isotherms were investigated, temperature effect on adsorption was calculated, Results showed that the adsorption was an exothermic process and the thermodynamic functions were calculated. The effect of the pH on adsorption was studied and the ionic strength effect on adsorption was studied, It was found that adsorption increases with the presence of sodium chloride ions. The kinetic study of adsorption before equilibrium showed that the adsorption was pseudo first order according to according (Lagergren equation).

Publication Date
Thu Sep 08 2022
Journal Name
Al-khwarizmi Engineering Journal
Performance Prediction in EDM Process for Al 6061 Alloy Using Response Surface Methodology and Genetic Algorithm
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The Electric Discharge (EDM) method is a novel thermoelectric manufacturing technique in which materials are removed by a controlled spark erosion process between two electrodes immersed in a dielectric medium. Because of the difficulties of EDM, determining the optimum cutting parameters to improve cutting performance is extremely tough. As a result, optimizing operating parameters is a critical processing step, particularly for non-traditional machining process like EDM. Adequate selection of processing parameters for the EDM process does not provide ideal conditions, due to the unpredictable processing time required for a given function. Models of Multiple Regression and Genetic Algorithm are considered as effective methods for determ

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Publication Date
Mon Nov 01 2021
Journal Name
Journal Of Engineering
Assessing of the Morphology and Sediment Transport of Diyala River
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Diyala River is one of the important rivers that provide water for the Governorate of Diyala. In this research, the morphology and sediment transport of this river were studied using HEC-Ras software. The selected length of the river in the present study is 193 km and extended from Diyala Weir to the confluence of Tigris River and Diyala River. The fieldwork period extended from June 2020 till August 2020, where suspended-load and bed-load samples were collected and surveyed some cross-sections. The one-dimensional sediment transport model has been calibrated for five years, from 2014 to 2019. The results were compared with the measured cross-sections in 2019,  and the suitable value of (maximum depth

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Publication Date
Mon Feb 18 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Auditing Quality According To Artificial Intelligence: Applied Research on A Sample of Regulatory Bodies Working In The Federal Board of Supreme Audit
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The Evolution Of Information Technology And The Use Of Computer Systems Led To Increase Attention To The Use Of Modern Techniques In The Auditing Process , As It Will Overcome Some Of The Human Shortcomings In The Exercise Of Professional Judgment, Then It Can Improve The Efficiency And Effectiveness Of The Audit Process, Where The New Audit Methodologies Espouse The Concept Of Risk Which Includes Strategic Dimension With Regard To The Capacity Of The Entity To Achieve Its Goals, Which Requires Auditors To Rely On Advanced Technology That Can Identify The Factors Which Prevent The Entity From Achieving Its Objectives. The Idea Of Research Is To Preparing An Electronic Program Fer All Audit Work From Planning Through Sampling And Document

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Simultaneous Ratio Derivative Spectrophotometric Determination of Paracetamol, Caffeine and Ibuprofen in Their Ternary Form
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A new, accurate, precise and economic two spectrophotometric methods for determination of Paracetamol (Par), Ibuprofen (Ibu), and Caffeine (Caf) were suggested. Those methods were the first and second ratio derivative spectrum using a double devisor. Par, Ibu, and Caf showed many useful peaks for their quantified determination. The validity of all analysis modes for determination of the three compounds, peak to baseline, peak area and peak to peak were according to ICH. The linearity of two methods was between 5 µg/ml as a lower concentration and 50 µg/ml as the highest concentration for three compounds. Recovery percentage was around 100% and relative standard deviation was less than 2.6%. The methods were applied successfully in the

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Publication Date
Thu Oct 01 2020
Journal Name
Journal Of Taibah University Medical Sciences
Preparing polycaprolactone scaffolds using electrospinning technique for construction of artificial periodontal ligament tissue
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Objectives The strategies of tissue-engineering led to the development of living cell-based therapies to repair lost or damaged tissues, including periodontal ligament and to construct biohybrid implant. This work aimed to isolate human periodontal ligament stem cells (hPDLSCs) and implant them on fabricated polycaprolactone (PCL) for the regeneration of natural periodontal ligament (PDL) tissues. Methods hPDLSCs were harvested from extracted human premolars, cultured, and expanded to obtain PDL cells. A PDL-specific marker (periostin) was detected using an immunofluorescent assay. Electrospinning was applied to fabricate PCL at three concentrations (13%, 16%, and 20% weight/volume) in two forms, which were examined through field emission

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Publication Date
Sun Jun 30 2013
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Extraction of Oil from Eucalyptus Camadulensis Using Water Distillation Method
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This work was conducted to study the extraction of eucalyptus oil from natural plants (Eucalyptus camaldulensis leaves) using water distillation method by Clevenger apparatus. The effects of main operating parameters were studied: time to reach equilibrium, temperature (70 to100°C), solvent to solid ratio (4:1 to 8:1 (v/w)), agitation speed (0 to 900 rpm), and particle size (0.5 to 2.5 cm) of the fresh leaves, to find the best processing conditions for achieving maximum oil yield. The results showed that the agitation speed of 900 rpm, temperature 100° C, with solvent to solid ratio 5:1 (v/w) of particle size 0.5 cm for 160 minute give the highest percentage of oil (46.25 wt.%). The extracted oil was examined by HPLC.

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Publication Date
Tue Sep 08 2020
Journal Name
Baghdad Science Journal
Turbid of Water By Using Fuzzy C- Means and Hard K- Means
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In this research two algorithms are applied, the first is Fuzzy C Means (FCM) algorithm and the second is hard K means (HKM) algorithm to know which of them is better than the others these two algorithms are applied on a set of data collected  from the Ministry of Planning on the water turbidity of five areas in Baghdad to know which of these areas are less turbid in clear water to see which months during the year are less turbid in clear water in the specified area.

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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)
ROLE OF SERUM ZINC AND COPPER AND ZINC/ COPPER RATIO IN ALOPECIA AREATA
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Alopecia areata is considered as a major health problem, its importance is attributed to its
recent increased incidence in our population. Till now, there is no exact cause for alopecia areata
although researchers thought it's an autoimmune disease.
This clinical study was designed to evaluate the role of trace elements (zinc and copper) in patients
with alopecia areata. Twenty patients were diagnosed as having alopecia areata with an age range
(10-40 years) were involved in this study. Normal subjects of the same age group were also
evaluated as control. The level of serum Zn and Cu were measured by flame atomic absorption
spectrophotometry in both control and patient group. And the ratio of Zn/Cu was also estimated

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Publication Date
Fri Aug 12 2022
Journal Name
Future Internet
Improved DDoS Detection Utilizing Deep Neural Networks and Feedforward Neural Networks as Autoencoder
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Software-defined networking (SDN) is an innovative network paradigm, offering substantial control of network operation through a network’s architecture. SDN is an ideal platform for implementing projects involving distributed applications, security solutions, and decentralized network administration in a multitenant data center environment due to its programmability. As its usage rapidly expands, network security threats are becoming more frequent, leading SDN security to be of significant concern. Machine-learning (ML) techniques for intrusion detection of DDoS attacks in SDN networks utilize standard datasets and fail to cover all classification aspects, resulting in under-coverage of attack diversity. This paper proposes a hybr

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