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Predicting COVID-19 in Iraq using Frequent Weighting for Polynomial Regression in Optimization Curve Fitting
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     The worldwide pandemic Coronavirus (Covid-19) is a new viral disease that spreads mostly through nasal discharge and saliva from the lips while coughing or sneezing. This highly infectious disease spreads quickly and can overwhelm healthcare systems if not controlled. However, the employment of machine learning algorithms to monitor analytical data has a substantial influence on the speed of decision-making in some government entities.        ML algorithms trained on labeled patients’ symptoms cannot discriminate between diverse types of diseases such as COVID-19. Cough, fever, headache, sore throat, and shortness of breath were common symptoms of many bacterial and viral diseases.

This research focused on the numerous tendencies and projected expansion of the Iraq pandemic to encourage people and governments to take preventive measures. This work is an established basic benchmark for demonstrating machine learning's capabilities for pandemic prediction.

The suggested approach for forecasting the number of COVID-19 cases can assist governments in taking safeguards to avoid the disease's spread. We have demonstrated the effectiveness of our strategy using publicly available datasets and models. A polynomial network is trained on this premise, and the parameters are optimized using frequent weighting. When compared to linear models, the polynomial model predicts better and is more effective in forecasting COVID-19 new confirmed cases. As well, it aims to analyze the spread of COVID-19 in Iraq and optimize polynomial regression. In time series-based models, curve fitting using frequent weighting to implement models such as linear regression and polynomial regression is utilized to estimate the new daily infection number. The datasets were collected from March 13, 2020, to December 12, 2021. The continuous COVID-19 pandemic puts both human lives and the economy at risk. If AI could forecast the next daily hospitalization number, it may be a useful tool in combating this pandemic sickness.

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Publication Date
Sun Jan 30 2022
Journal Name
Iraqi Journal Of Science
The Dynamics of Modified Leslie-Gower Predator-Prey Model Under the Influence of Nonlinear Harvesting and Fear Effect
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A modified Leslie-Gower predator-prey model with fear effect and nonlinear harvesting is developed and investigated in this study. The predator is supposed to feed on the prey using Holling type-II functional response. The goal is to see how fear of predation and presence of harvesting affect the model's dynamics. The system's positivity and boundlessness are demonstrated. All conceivable equilibria's existence and stability requirements are established. All sorts of local bifurcation occurrence conditions are presented. Extensive numerical simulations of the proposed model are shown in form of Phase portraits and direction fields. That is to guarantee the correctness of the theoretical results of the dynamic behavior of the system and t

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
Human recognition by utilizing voice recognition and visual recognition
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Audio-visual detection and recognition system is thought to become the most promising methods for many applications includes surveillance, speech recognition, eavesdropping devices, intelligence operations, etc. In the recent field of human recognition, the majority of the research be- coming performed presently is focused on the reidentification of various body images taken by several cameras or its focuses on recognized audio-only. However, in some cases these traditional methods can- not be useful when used alone such as in indoor surveillance systems, that are installed close to the ceiling and capture images right from above in a downwards direction and in some cases people don't look straight the cameras or it cannot be added in some

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Self-Localization of Guide Robots Through Image Classification
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The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Reinforcement Learning-Based Television White Space Database
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Television white spaces (TVWSs) refer to the unused part of the spectrum under the very high frequency (VHF) and ultra-high frequency (UHF) bands. TVWS are frequencies under licenced primary users (PUs) that are not being used and are available for secondary users (SUs). There are several ways of implementing TVWS in communications, one of which is the use of TVWS database (TVWSDB). The primary purpose of TVWSDB is to protect PUs from interference with SUs. There are several geolocation databases available for this purpose. However, it is unclear if those databases have the prediction feature that gives TVWSDB the capability of decreasing the number of inquiries from SUs. With this in mind, the authors present a reinforcement learning-ba

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Publication Date
Tue Jan 01 2019
Journal Name
Opcion
Enhancing islamic concepts through English children’s literature: Al-Ibtila, the test of patience
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Allah, in his Holy Quran introduced great prophet stories so as to learn from. The greatness of these stories lies in Allah himself being the author. He portrays his characters, lays the plot, defines the tests and Al- Ibtilla, provides ways of being patient, using Duaa to end all hard tests and generously describing the greatness of his rewards to all those who are patient. The purpose of this research is to study selected English prophet stories for children on three levels, the stories ability to convey lessons and Islamic teachings to children who do not speak Arabic, the stories portray the Islamic concept of patience, the teaching and learning styles andstrategies that Allah uses with each prophet. The concept of patience is defined a

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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
The Extent to Which Future Skills are Employed During Teaching from the Viewpoint of Students of Islamic Studies and their Relationship to Students' Attitude towards Future Profession
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The research aims to identify the relationship between employing future skills during teaching from the viewpoint of students of Islamic studies at the Northern Border University, as well as their attitudes towards future professions. The researcher employed the correlational descriptive approach. The tools were a questionnaire for employing future skills, and a scale for the attitude towards the future profession. The two research tools were applied to a random sample of (242) male and female students from the department of Islamic Studies, College of Education and Arts. The findings showed that the total level of employing future skills and their three axes during teaching was average. It was also found that the attitude towards future

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Publication Date
Sun Jul 31 2022
Journal Name
Iraqi Journal Of Science
Deep Learning and Machine Learning via a Genetic Algorithm to Classify Breast Cancer DNA Data
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       This paper uses Artificial Intelligence (AI) based algorithm analysis to classify breast cancer Deoxyribonucleic (DNA). Main idea is to focus on application of machine and deep learning techniques. Furthermore, a genetic algorithm is used to diagnose gene expression to reduce the number of misclassified cancers. After patients' genetic data are entered, processing operations that require filling the missing values using different techniques are used. The best data for the classification process are chosen by combining each technique using the genetic algorithm and comparing them  in terms of accuracy.

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Publication Date
Sun Feb 01 2015
Journal Name
Journal Of Engineering
Non-Linear Analysis of Laminated Composite Plates under General Out-Of-Plane Loading
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The theoretical analysis depends on the Classical Laminated Plate Theory (CLPT) that is based on the Von-K ráman Theory and Kirchhov Hypothesis in the deflection analysis during elastic limit as well as the Hooke's laws of calculation the stresses. New function for boundary condition is used to solve the forth degree of differential equations which depends on variety sources of advanced engineering mathematics. The behavior of composite laminated plates, symmetric and anti-symmetric of cross-ply angle, under out-of-plane loads (uniform distributed loads) with two different boundary conditions are investigated to obtain the central deflection for mid-plane by using the Ritz method. The computer programs is built using Ma

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Publication Date
Sun Oct 18 2015
Journal Name
International Journal Of Pure And Applied Mathematics
A MODIFIED FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING TO SOLVE AGGREGATE PRODUCTION PLANNING
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This paper develops a fuzzy multi-objective model for solving aggregate production planning problems that contain multiple products and multiple periods in uncertain environments. We seek to minimize total production cost and total labor cost. We adopted a new method that utilizes a Zimmermans approach to determine the tolerance and aspiration levels. The actual performance of an industrial company was used to prove the feasibility of the proposed model. The proposed model shows that the method is useful, generalizable, and can be applied to APP problems with other parameters.

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Publication Date
Wed Jul 20 2022
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On the Growth of Solutions of Nonhomogeneous Higher order Complex Linear Differential Equations
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The nonhomogeneous higher order linear complex differential equation (HOLCDE) with meromorphic (or entire) functions is considered in this paper. The results are obtained by putting some conditions on the coefficients to prove that the hyper order of any nonzero solution of this equation equals the order of one of its coefficients in case the coefficients are meromorphic functions. In this case, the conditions were put are that the lower order of one of the coefficients dominates the maximum of the convergence exponent of the zeros sequence of it, the lower order of both of the other coefficients and the nonhomogeneous part and that the solution has infinite order. Whiles in case the coefficients are entire functions, any nonzero solutio

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