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
Mon Jun 30 2025
Journal Name
Ingénierie Des Systèmes D Information
Comparative Analysis of Four Programming Languages for Machine Learning
...Show More Authors

View Publication
Scopus (2)
Scopus Crossref
Publication Date
Sat Oct 20 2018
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the causes of poverty and progress strategy to combat in sudan
...Show More Authors

Abstract:

   The problem of poverty is one of the most important development challenges facing developing countries including Sudan for several decades. Although many efforts have been made to reduce poverty, however, its rates are increasing, and public policies adopted by the government in this regard remain elusive in achievinging its main objectives or making any significant progress. The purpose of the present study is to analyse poverty in Sudan by identifying its measurement, causes and the factors that have contributed to the increasing poverty rates over the past two decades. Also this study aims at investigating the interim poverty reduction strategy in Sudan as well as evaluates that strategy throug

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
The Vertical variations of Atmospheric Methane (CH4) concentrations over selected cities in Iraq based on AIRS data
...Show More Authors

The Atmospheric Infrared Sounder (AIRS) on EOS/Aqua satellite provides diverse measurements of Methane (CH4) distribution at different pressure levels in the Earth's atmosphere. The focus of this research is to analyze the vertical variations of (CH4) volume mixing ratio (VMR) time-series data at four Standard pressure levels SPL (925, 850, 600, and 300 hPa) in the troposphere above six cities in Iraq from January 2003 to September 2016. The analysis results of monthly average CH4VMR time-series data show a significant increase between 2003 and 2016, especially from 2009 to 2016; the minimum values of CH4 were in 2003 while the maximum values were in 2016. The vertical distribution of CH4<

... Show More
View Publication Preview PDF
Scopus (4)
Crossref (2)
Scopus Clarivate Crossref
Publication Date
Wed Feb 10 2016
Journal Name
ألمؤتمر الدولي العلمي الخامس للاحصائيين العرب/ القاهرة
Proposition of Modified Genetic Algorithm to Estimate Additive Model by using Simulation
...Show More Authors

Often phenomena suffer from disturbances in their data as well as the difficulty of formulation, especially with a lack of clarity in the response, or the large number of essential differences plaguing the experimental units that have been taking this data from them. Thus emerged the need to include an estimation method implicit rating of these experimental units using the method of discrimination or create blocks for each item of these experimental units in the hope of controlling their responses and make it more homogeneous. Because of the development in the field of computers and taking the principle of the integration of sciences it has been found that modern algorithms used in the field of Computer Science genetic algorithm or ant colo

... Show More
Preview PDF
Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Face Recognition and Emotion Recognition from Facial Expression Using Deep Learning Neural Network
...Show More Authors
Abstract<p>Face recognition, emotion recognition represent the important bases for the human machine interaction. To recognize the person’s emotion and face, different algorithms are developed and tested. In this paper, an enhancement face and emotion recognition algorithm is implemented based on deep learning neural networks. Universal database and personal image had been used to test the proposed algorithm. Python language programming had been used to implement the proposed algorithm.</p>
View Publication
Scopus (8)
Crossref (2)
Scopus Crossref
Publication Date
Wed Sep 03 2025
Journal Name
Plos One
Effective SMOTE boost with deep learning for IDC identification in whole-slide images
...Show More Authors

Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolut

... Show More
View Publication
Scopus (1)
Crossref (2)
Scopus Crossref
Publication Date
Sun Sep 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
ANALYSIS UNBALANCED FACTORIAL EXPERIMENTS FOR THE RICE CROP
...Show More Authors

Abstract:

           The great importance that distinguish these factorial experiments made ​​them subject a desirable for use and application in many fields, particularly in the field of agriculture, which is considered the broad area for experimental designs applications.

            And the second case for the factorial  experiment, which faces researchers have great difficulty in dealing with the case unbalance we mean that frequencies treatments factorial  are not equal meaning (that is allocated a number unequal of blocks or units experimental per tre

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Jul 01 2014
Journal Name
Political Sciences Journal
Business partnerships analysis of Iraq's 2003 -2013
...Show More Authors

تحليل الشراكات التجارية للعراق 2003-2013

View Publication Preview PDF
Crossref
Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Analysis of the clause relations in the presidential presuasion in a war against Iraq
...Show More Authors

0

View Publication Preview PDF
Publication Date
Wed Jan 01 2025
Journal Name
Iv. International Rimar Congress Of Pure, Applied Sciences
A New Intrusion Detection Approach Based on RNA Encoding and K-Means Clustering Algorithm Using KDD-Cup99 Dataset
...Show More Authors

Intrusion detection systems (IDS) are useful tools that help security administrators in the developing task to secure the network and alert in any possible harmful event. IDS can be classified either as misuse or anomaly, depending on the detection methodology. Where Misuse IDS can recognize the known attack based on their signatures, the main disadvantage of these systems is that they cannot detect new attacks. At the same time, the anomaly IDS depends on normal behaviour, where the main advantage of this system is its ability to discover new attacks. On the other hand, the main drawback of anomaly IDS is high false alarm rate results. Therefore, a hybrid IDS is a combination of misuse and anomaly and acts as a solution to overcome the dis

... Show More
Preview PDF