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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.

 

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Publication Date
Sun Aug 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the performance of some r- (k,d) class estimators with the (PCTP) estimator that used in estimating the general linear regression model in the presence of autocorrelation and multicollinearity problems at the same time "
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In the analysis of multiple linear regression, the problem of multicollinearity and auto-correlation drew the attention of many researchers, and given the appearance of these two problems together and their bad effect on the estimation, some of the researchers found new methods to address these two problems together at the same time. In this research a comparison for the performance of the Principal Components Two Parameter estimator (PCTP) and The (r-k) class estimator and the r-(k,d) class estimator by conducting a simulation study and through the results and under the mean square error (MSE) criterion to find the best way to address the two problems together. The results showed that the r-(k,d) class estimator is the best esti

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Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Automatic Health Speech Prediction System Using Support Vector Machine
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Classification of Diseases in Oil Palm Leaves Using the GoogLeNet Model
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The general health of palm trees, encompassing the roots, stems, and leaves, significantly impacts palm oil production, therefore, meticulous attention is needed to achieve optimal yield. One of the challenges encountered in sustaining productive crops is the prevalence of pests and diseases afflicting oil palm plants. These diseases can detrimentally influence growth and development, leading to decreased productivity. Oil palm productivity is closely related to the conditions of its leaves, which play a vital role in photosynthesis. This research employed a comprehensive dataset of 1,230 images, consisting of 410 showing leaves, another 410 depicting bagworm infestations, and an additional 410 displaying caterpillar infestations. Furthe

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Quantification of Acrylamide Content in Potato Chips and in Iraqi “Harissa”
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A simple, environmentally benign, sustainable, accurate and cost effective green approach has been developed for the determination of Acrylamide (2-propenamide) in different samples of potato chips collected from the Iraqi market during the year 2012 and a traditional Iraqi meal called Harissa. The method entails a straightforward de-fatting practice with n-hexane, extraction with lukewarm water, and cleanup with solid-phase extraction (SPE) cartridges containing the sorbent bed of the mixed mode ion exchangers (SiliaPrep C8/SCX-2/SAX). The final extracts are directly determined by liquid chromatography-Ultra violet (LC-UV) at a wavelength of 205nm for quantification.  The acrylamide content in the examined potato chips were in the

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Mon Apr 17 2017
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
INVESTIGATION THE CONTENT OF SOME HEAVY METALS IN COLORED PLASTIC TABLE DISHES.: INVESTIGATION THE CONTENT OF SOME HEAVY METALS IN COLORED PLASTIC TABLE DISHES.
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The aim of this study is to investigate the existence of some heavy metals (lead, cadmium, chromium) in colored plastic table dishes and study the migration of these metals to the food meals and the affecting factors in migration , such as storage period and food temperature. Six kinds of colored plastic table dishes were collected from Baghdad markets. The heavy metals in table dishes and in the prepared food meals put in them were estimated using atomic absorption spectrophotometer (Shimadzu A5000). The results indicated the existence of lead in all samples (1.61_1.00 mg/ kg) and chromium in three samples (0.85_0.97 mg/ kg) while other samples are free of chromium, and cadmium. Investigating the migration of these metals to food at dif

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Publication Date
Mon May 21 2007
Journal Name
Journal Of Planner And Development
Using the Input - Output Model in building the economic plan using the computer
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The origin of this technique lies in the analysis of François Kenai (1694-1774), the leader of the School of Naturalists, presented in Tableau Economique. This method was developed by Karl Marx in his analysis of the Departmental Relationships and the nature of these relations in the models of " "He said. The current picture of this type of economic analysis is credited to the Russian economist Vasily Leontif. This analytical model is commonly used in developing economic plans in developing countries (p. 1, p. 86). There are several types of input and output models, such as static model, mobile model, regional models, and so on. However, this research will be confined to the open-ended model, which found areas in practical application.

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Publication Date
Wed Feb 01 2017
Journal Name
International Journal Of Science And Research (ijsr)
A Comparative Study between Computer Textbooks Content in the Secondary Stage and Computer Textbooks Content in the University Stage in Colleges of Education at Baghdad University
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Record, verify, and showcase your peer review contributions in a format you can include in job and funding applications (without breaking reviewer anonymity).

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Publication Date
Mon Dec 14 2020
Journal Name
Baghdad Science Journal
Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks
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To ensure fault tolerance and distributed management, distributed protocols are employed as one of the major architectural concepts underlying the Internet. However, inefficiency, instability and fragility could be potentially overcome with the help of the novel networking architecture called software-defined networking (SDN). The main property of this architecture is the separation of the control and data planes. To reduce congestion and thus improve latency and throughput, there must be homogeneous distribution of the traffic load over the different network paths. This paper presents a smart flow steering agent (SFSA) for data flow routing based on current network conditions. To enhance throughput and minimize latency, the SFSA distrib

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