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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
Thu Oct 01 2020
Journal Name
Heliyon
Inter-personal versus content: assessment of communication skills in Iraqi physicians
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Publication Date
Sat Feb 02 2019
Journal Name
Journal Of The College Of Education For Women
content Analysis for Some Type of Pillows used in Iraqi houses
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content Analysis for Some Type of Pillows used in Iraqi houses

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Thu Nov 08 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Evaluation of some mechanical properties of dental alginate impression materials after fluoride addition
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Objective:Fluorid-containing dental alginate impression materials can exert a considerable reduction in
enamel solubility. The objective was to evaluate the effect of fluoride addition on the setting time and
compressive strength of alginate impression materials.
Methodology: 60 samples were constructed from alginate impression material (30 samples for setting
time test and 30 samples for compressive strength test).Specimens of each test divided into three
subgroup. Group A: 10 specimens of alginate were mixed with distilled water [control], Group B: 10
specimens of alginate were mixed with100-ppm fluoride and Group C:10 specimens of alginate were
mixed with 2%Naf.
Results: the result of setting time test showed t

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Wed May 09 2018
Journal Name
International Journal Of Advanced Computer Science And Applications
New Techniques to Enhance Data Deduplication using Content based-TTTD Chunking Algorithm
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Publication Date
Fri Mar 01 2024
Journal Name
Iaes International Journal Of Artificial Intelligence (ij-ai)
Analyzing the behavior of different classification algorithms in diabetes prediction
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<span lang="EN-US">Diabetes is one of the deadliest diseases in the world that can lead to stroke, blindness, organ failure, and amputation of lower limbs. Researches state that diabetes can be controlled if it is detected at an early stage. Scientists are becoming more interested in classification algorithms in diagnosing diseases. In this study, we have analyzed the performance of five classification algorithms namely naïve Bayes, support vector machine, multi layer perceptron artificial neural network, decision tree, and random forest using diabetes dataset that contains the information of 2000 female patients. Various metrics were applied in evaluating the performance of the classifiers such as precision, area under the c

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Compare Prediction by Autoregressive Integrated Moving Average Model from first order with Exponential Weighted Moving Average
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The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

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Publication Date
Mon Jul 28 2025
Journal Name
Al–bahith Al–a'alami
News in Brief and Their Role in Public Understanding of News Content in Iraqi Satellite TV
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News feeds are at the forefront of news forms that are close to the public's attention for their rapid news content in two directions:

  1. its speed in summarizing events in one or two sentences easy to be understood and realized.
  2. highlight the most important contents of screenings or news broadcast.

The researchers felt that the importance of these brief news compared to news broadcast, breaking news and news subtitle are still ambiguous, as well as their contents.

The researchers selected the city of Baghdad as a community to research and prepare a questionnaire form containing (11) questions.

The questionnaires were distributed to a non-relative stratified

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Assessment of water quality in the shatt Al-Hillah river
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