In the wake of the outbreak of the new coronavirus, the countries in the world have fought to combat the spread of infection and imposed preventive measures to compel the population to social distancing, which led to a global crisis. Important strategies must be studied and identified to prevent and control the spread of coronavirus COVID-19 disease 2019. In this paper, the effect of preventive strategies on COVID-19 spread was studied, a model based on supervised data mining algorithms was presented and the best algorithm was suggested on the basis of accuracy. In this model, three classifiers (Naive Bayes, Multilayer Perceptron and J48) depended on the questionnaires filled out by Basra City respondents. The questionnaires consisted of 25 questions that covered fields most related to and that affect the prevention of COVID-19 spread, including demographic, psychological, health management, cognitive, awareness and preventive factors. A total of 1017 respondents were collected. This model was developed using Weka 3.8 tool. Results showed that quarantine played an important role in controlling the spread of the disease. By comparing the accuracy of the algorithms used, the best algorithm was found to be J48.
The problem of unemployment is one of the most important problems faced by most countries of the world, and it is one of the intractable problems in developing countries, and in Iraq unemployment occupies great importance due to its high rates. This problem in itself is a serious condition, because it results from mismanagement and the structure of the economy, and despite its great importance, it has not been carefully monitored. There are studies and strategies that deal with the analysis and study of those causes that lead to this problem, such as traditional statistical methods, various mathematical and statistical methods, in this research proposed a method uses machine learning methods to find the factors that affect the causes of this problem, as well as the multiple linear regression method.
The pandemic outbreak of COVID-19 created panic all over the world. The mathematical principle in developing forecasting models aims to predict the number of future infections is considered crucial at this stage. The present investigation aims to analyze the time series using the Box-Jenkins method (Diagnostic, The Estimate, and selection, Forecasting) to find the best ARIMA model (Autoregressive Integrated Moving Average) for predicting the numbers of people infected with Covid-19 disease in Iraq. The data used were collected in the period between 1 -March and 31-July. The results showed that the appropriate forecasting model is ARIMA (2,1,5). Depending on this model, they predict the numbers of those infected with COVID-19 daily and for thirty days. Predictive values are consistent with original series values, indicating the efficiency of the model.
This research was devoted to a test of the relationship between knowledge about the disease COVID -19 and the personal preventive measures by Pearson correlation and regression analysis. Data collection was carried out through a questionnaire distributed in Basra governorate and the number of participants was 1000 individuals. Cronbach Alpha coefficient to ensure the reliability of the was calculated and its value (0.735) indicates the reliability of the research tools. The demographic data and responses of the participants were statistically described and the null hypothesis was tested (there is no effect of knowledge about COVID-19 on people’s commitment with preventive protocol) using the spss program. The Pearson correlation coefficient was found to be 0.6 indicating positive correlation between the test variables. Regression analysis showed that the dependent variable ( Yi3 : Avoid touching the face, nose and eye with unclean hands or after touching surfaces and objects. ) is the most affected one in the personal prevention factors by the variables listed in the disease knowledge factor.
In an educational foundation whose objective is to contribute to the enhancement of the finest education, the improvement of quality in an educational institution is verified by providing the best services which are better meeting each student’s need. General, in preparatory school in Iraq—especially in Basra—the students’ ability in mathematical courses is low levels based General, in preparatory school in Iraq—especially in Basra—the students’ ability in mathematical courses is low levels based. In this study, we discussed the effect of diverse factors on student failure and success using real data collected in many of the schools in Basra. These data were analyzed using SPSS version 0.23. At the end of the study, we identified the factors that could have affected the students’ capabilities (e.g., teachers’ ability, student effect factors, and institutional ability).
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