Preferred Language
Articles
/
bsj-8504
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
...Show More Authors

The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA molecule. A sequence DL model based on a bidirectional gated recurrent unit (GRU) is implemented. The model is applied to the Stanford COVID-19 mRNA vaccine dataset to predict the mRNA sequences deterioration by predicting five reactivity values for every base in the sequence, namely reactivity values, deterioration rates at high pH, at high temperature, at high pH with Magnesium, and at high temperature with Magnesium. The Stanford COVID-19 mRNA vaccine dataset is split into the training set, validation set, and test set. The bidirectional GRU model minimizes the mean column wise root mean squared error (MCRMSE) of deterioration rates at each base of the mRNA sequence molecule with a value of 0.32086 for the test set which outperformed the winning models with a margin of (0.02112). This study would help other researchers better understand how to forecast mRNA sequence molecule properties to develop a stable COVID-19 vaccine.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Tue Dec 27 2022
Journal Name
2022 3rd Information Technology To Enhance E-learning And Other Application (it-ela)
Diabetes Prediction Using Machine Learning
...Show More Authors

Diabetes is one of the increasing chronic diseases, affecting millions of people around the earth. Diabetes diagnosis, its prediction, proper cure, and management are compulsory. Machine learning-based prediction techniques for diabetes data analysis can help in the early detection and prediction of the disease and its consequences such as hypo/hyperglycemia. In this paper, we explored the diabetes dataset collected from the medical records of one thousand Iraqi patients. We applied three classifiers, the multilayer perceptron, the KNN and the Random Forest. We involved two experiments: the first experiment used all 12 features of the dataset. The Random Forest outperforms others with 98.8% accuracy. The second experiment used only five att

... Show More
View Publication
Scopus (6)
Crossref (5)
Scopus Crossref
Publication Date
Wed Jun 07 2023
Journal Name
Journal Of Educational And Psychological Researches
Developing the Skill of Friendship for Kindergarten Children in the Light of Bandura's Theory Social Learning: Ministry of Education / Baghdad Directorate of Education, Al/Rusafa
...Show More Authors

The current research aims to identify the effect of the program to develop the skill of friendship among kindergarten children, as well as the scope of the impact of the program on the sample. To achieve the objectives of the research, the researcher hypothesizes there is no significant difference between the average scores of the sample members on the friendship skill scale for the dimensional scale according to the experimental and control group. The research sample consisted of (60) girl and boy with age ranges (4-6) who were randomly selected from the Kindergarten Unity at Baghdad city/ Rusafa 1. The children were distributed into an experimental and control group, each group consists of (30) girl and boy. The two groups were chosen

... Show More
View Publication Preview PDF
Publication Date
Tue Sep 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Evaluating the quality of educational services according to the modified Servqual modelStudy of a sample of students of the Faculty of Management and Economics / University of Baghdad
...Show More Authors

The research aims to apply a modified SERVQUAL model to evaluate the quality of the educational services via conducting exploratory research for students from the College of Administration and Economics- Department of Business Administration- Evening studies at the University of Baghdad. Questionnaire of two parts was distributed to a sample of (72) students out of (720) students of the 2nd.,3rd. and 4th. year in the beginning of the second semester of the year 2008-2009 to measure the expectations and perceptions to the quality of the educational services. Five major dimensions were analyzed to see the gaps for (22) variables. The study concluded that there were (13) variables confirmed that the

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Oct 13 2025
Journal Name
Journal Of Studies And Researches Of Sport Education
The impact of the V-shape strategy on learning basic skills in a breaststroke
...Show More Authors

View Publication
Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role & Mechanism of Market Makers in Iraqi Stock Market: "Proposal Frame"
...Show More Authors

This researchable paper aims to focus of the role & mechanism of market makers in Iraqi stock market through analyzing its role in other Arabian as well as global stock ones, especially in current period through activate the use of bonds, shares, and trying to create a continued price balance. Then decreasing the opportunity having gaps between highest and lowest level without reasonable causes. In addition trying to deactivate the common decision without supported information. Moreover, this paper aims to explain the rules of increasing liquidity and having balance to lead the market into positive direction.  Thus, for achieving the above-mentioned requirements, such conditions should be underlined by market makers as well as t

... Show More
View Publication
Crossref
Publication Date
Thu Dec 15 2022
Journal Name
Journal Of Petroleum Research And Studies
Selection of an Optimum Drilling Fluid Model to Enhance Mud Hydraulic System Using Neural Networks in Iraqi Oil Field
...Show More Authors

In drilling processes, the rheological properties pointed to the nature of the run-off and the composition of the drilling mud. Drilling mud performance can be assessed for solving the problems of the hole cleaning, fluid management, and hydraulics controls. The rheology factors are typically termed through the following parameters: Yield Point (Yp) and Plastic Viscosity (μp). The relation of (YP/ μp) is used for measuring of levelling for flow. High YP/ μp percentages are responsible for well cuttings transportation through laminar flow. The adequate values of (YP/ μp) are between 0 to 1 for the rheological models which used in drilling. This is what appeared in most of the models that were used in this study. The pressure loss

... Show More
View Publication
Crossref (2)
Crossref
Publication Date
Fri Oct 14 2022
Journal Name
المجلة العراقية لعلوم التربة
REVIEW: USING MACHINE VISION AND DEEP LEARINING IN AUTOMATED SORTING OF LOCAL LEMONS
...Show More Authors

Sorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.

Publication Date
Sun Jun 06 2021
Journal Name
Materials
Strengthening of Continuous Reinforced Concrete Deep Beams with Large Openings Using CFRP Strips
...Show More Authors

To accommodate utilities in buildings, different sizes of openings are provided in the web of reinforced concrete deep beams, which cause reductions in the beam strength and stiffness. This paper aims to investigate experimentally and numerically the effectiveness of using carbon fiber reinforced polymer (CFRP) strips, as a strengthening technique, to externally strengthen reinforced concrete continuous deep beams (RCCDBs) with large openings. The experimental work included testing three RCCDBs under five-point bending. A reference specimen was prepared without openings to explore the reductions in strength and stiffness after providing large openings. Openings were created symmetrically at the center of spans of the other specimens

... Show More
Scopus (24)
Crossref (24)
Scopus Clarivate Crossref
Publication Date
Tue Sep 01 2020
Journal Name
Baghdad Science Journal
A Comparative Study on the Active Constituents, Antioxidant Capacity and Anti-Cancer Activity of Cruciferous Vegetable Residues
...Show More Authors

This study is pointed out to estimate the effectiveness of two solvents in the extraction and evaluating the active ingredients and their antioxidant activity as well as anti-cancer efficiency. Therefore, residues from four different Brassica vegetables viz. broccoli, Brussels sprout, cauliflower, and red cherry radish were extracted using two procedures methods: methanolic and water crude extracts. Methanol extracts showed the highest content of total phenolic (TP), total flavonoids (TF), and total tannins (TT) for broccoli and Brussels sprouts residues. Methanolic extract of broccoli and Brussels sprouts residues showed the highest DPPH· scavenging activity (IC50 = 15.39 and 18.64 µg/ml). The methanol and water ex

... Show More
View Publication Preview PDF
Scopus (10)
Crossref (4)
Scopus Clarivate Crossref
Publication Date
Mon Oct 02 2023
Journal Name
Journal Of Engineering
Skull Stripping Based on the Segmentation Models
...Show More Authors

Skull image separation is one of the initial procedures used to detect brain abnormalities. In an MRI image of the brain, this process involves distinguishing the tissue that makes up the brain from the tissue that does not make up the brain. Even for experienced radiologists, separating the brain from the skull is a difficult task, and the accuracy of the results can vary quite a little from one individual to the next. Therefore, skull stripping in brain magnetic resonance volume has become increasingly popular due to the requirement for a dependable, accurate, and thorough method for processing brain datasets. Furthermore, skull stripping must be performed accurately for neuroimaging diagnostic systems since neither no

... Show More
View Publication Preview PDF
Crossref