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Prediction of Monthly Fluoride Content in Tigris River using SARIMA Model in R Software
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The need to create the optimal water quality management process has motivated researchers to pursue prediction modeling development. One of the widely important forecasting models is the sessional autoregressive integrated moving average (SARIMA) model. In the present study, a SARIMA model was developed in R software to fit a time series data of monthly fluoride content collected from six stations on Tigris River for the period from 2004 to 2014. The adequate SARIMA model that has the least Akaike's information criterion (AIC) and mean squared error (MSE) was found to be SARIMA (2,0,0) (0,1,1). The model parameters were identified and diagnosed to derive the forecasting equations at each selected location. The correlation coefficient between the actual and predicted values for fluoride concentration at the six locations, Al-Karakh, East Tigris, Al-Wathbah, AL-Karamah, Al-Rashid and Al-Wahda WTP intakes, was 0.93, 0.82, 0.86, 0.90, 0.83 and 0.89, respectively. Model verification results indicated that the model forecasting outputs rationally estimated the actual monthly fluoride content in the selected locations.

Publication Date
Tue Apr 04 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
BIOACCUMULATION OF HEAVY METALS IN Sesarma boulengeri COLLECTED FROM SHATT AL- ARAB RIVER.: BIOACCUMULATION OF HEAVY METALS IN Sesarma boulengeri COLLECTED FROM SHATT AL- ARAB RIVER.
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Concentrations of heavy metals (Copper Cu, Iron Fe, Manganese Mn, Cadmium Cd, and Lead Pb) have been studied in river crab Sesarma boulengeri (Outer part of the shield and interior tissues) which caught from two stations in Shatt Al – Arab river (Salhia and Aldeir areas). Elements concentrations were measured by Flame Atomic Absorption Spectrophotometer, concentration of heavy metals in the internal tissues was higher than in the outer shield in both of the stations with the highest value of the elements was to iron 95.21 mg\ kg during the spring as well as copper was 55 mg\kg and manganese was 39.09 mg\kg. The study showed the presence of seasonal changes in the studied heavy metals concentrations values in the tissues of river crab;

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Publication Date
Mon Oct 01 2018
Journal Name
Journal Of Engineering
Modeling and Simulation of Solar Module performance using Five Parameters Model by using Matlab in Baghdad City
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This work presents the modeling of the electrical response of monocrystalline photovoltaic module by using five parameters model based on manufacture data-sheet of a solar module that measured in stander test conditions (STC) at radiation 1000W/m² and cell temperature 25 . The model takes into account the series and parallel (shunt) resistance of the module. This paper considers the details of Matlab modeling of the solar module by a developed Simulink model using the basic equations, the first approach was to estimate the parameters: photocurrent Iph, saturation current Is, shunt resistance Rsh, series resistance Rs, ideality factor A at stander test condition (STC) by an ite

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Monitoring the Vegetation and Water Content of Al-Hammar Marsh Using Remote Sensing Techniques
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The object of the presented study was to monitor the changes that had happened in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To fulfill this goal, different satellite images had been used in different times, MSS 1973, TM 1990, ETM+ 2000, 2002, and MODIS 2009, 2010. A new technique of the unsupervised classification called (Color Extracting Technique) was used to classify the satellite images. MATLAP programming used the technique and separated Al-Hammar Marsh from other water features (rivers, irrigated lands, etc.) when calculated the changes in the water content of the study region. ArcGIS 9.3 (arcMAP, arcToolbox) were used to achieve this work and calculate area of each class.

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Publication Date
Thu May 14 2026
Journal Name
Univesity Of Thi-qar Journal
Analysis of Heavy Metals in Water Samples of Euphrates River in Nasiriya City, Iraq
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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Sol- Gel Synthesis of Hematite Nanoparticles and Photo Degradation of Cibacron Red FN-R Dye
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This paper describes the synthesis of ?- Fe2O3 nanoparticles by sol-gel route using carboxylic acid(2-hydroxy benzoic acid) as gelatin media and its photo activity for degradation of cibacron red dye . Hematite samples are synthesized at different temperatures: 400, 500, 600, 700, 800 and 900 ?C at 700 ?C the ?-Fe2O3 nanoparticles are formed with particle size 71.93 nm. The nanoparticles are characterized by XRD , SEM, AFM and FTIR . The 0.046 g /l of the catalyst sample shows high photo activity at 3x10-5M dye concentration in acidic medium at pH 3.

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Environment and lifestyle Fish Qattan in the Euphrates River in central Iraq
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Studied the environment and fish life Qattan in the Euphrates River in central Iraq for the period from September 2002 until 2003 recorded the lowest temperature of the water during the month of January during the month of August ranged salinity ranges between 068

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Publication Date
Tue Aug 15 2023
Journal Name
Sumer 1
The effect of silver diamine fluoride on the microleakage of glass ionomer restoration in primary teeth at different time intervals
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Silver diamine fluoride (SDF) has shown effectiveness in hardening tooth structure and killing bacteria. Therefore, it can be used to prevent and arrest dental caries. Riva Star (SDF) treatment alone will stop cavities but will not reverse the cavitation. The Silver Modified Atraumatic Procedure, often known as Smart, is the optimum technique for regaining the tooth's structure and function. Glass ionomer was introduced in (1972) as a new material that has become one of the most widely used materials in restorative dentistry. By releasing fluoride ions, this material has a therapeutic impact on the surrounding tooth structure. Microleakage is the ingress of bacteria, its byproducts, toxins, chemicals, oral fluids, and ions between t

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Publication Date
Thu Oct 01 2020
Journal Name
Bulletin Of Electrical Engineering And Informatics
Traffic management inside software-defined data centre networking
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In recent years, data centre (DC) networks have improved their rapid exchanging abilities. Software-defined networking (SDN) is presented to alternate the impression of conventional networks by segregating the control plane from the SDN data plane. The SDN presented overcomes the limitations of traditional DC networks caused by the rapidly incrementing amounts of apps, websites, data storage needs, etc. Software-defined networking data centres (SDN-DC), based on the open-flow (OF) protocol, are used to achieve superior behaviour for executing traffic load-balancing (LB) jobs. The LB function divides the traffic-flow demands between the end devices to avoid links congestion. In short, SDN is proposed to manage more operative configur

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Publication Date
Sun Jul 25 2021
Journal Name
Natural Resources Research
Effect of Water Flooding on Oil Reservoir Permeability: Saturation Index Prediction Model for Giant Oil Reservoirs, Southern Iraq
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Publication Date
Thu Jan 03 2019
Journal Name
International Journal Of Civil Engineering And Technology (ijciet)
Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the

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