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<p>The need for elucidating the effects of environmental factors in the determination of the novel corona virus (COVID-19) is very vital. This study is a methodological study to compare three different test models (1. Artificial neural networks (ANN), 2. Adaptive neuro fuzzy inference system (ANFIS), 3. A linear classical model (MLR)) used to determine the relationship between COVID-19 spread and environmental factors (temperature, humidity and wind). These data were obtained from the studies (Pirouz, Haghshenas, Haghshenas, &amp; Piro, 2020) with confirmed COVID-19 patients in Wuhan, China, using temperature, humidity and wind as the independent variables. The measured and the predicted results were checked based on three different performance indices; Root mean square error (RMSE), determination coefficient (R2) and correlation coefficient (R). The results showed that ANFIS and ANN are more promising over the classical MLR models having an average R-values of 0.90 in both calibration and verification stages. The findings indicated that ANFIS outperformed MLR and ANN. In addition, their performance skills boosted up to 25% and 9% respectively based on the determination coefficient for the prediction of confirmed COVID-19 cases in Wuhan city of China. Overall, the results depict the reliability and ability of AI-based models (ANFIS and ANN) for the simulation of COVID-19 using the effects of various environmental variables. </p>

In this paper we present a new method to compute the determinants of square matrices of order 5 and 6. To prove the main results we have combined the Farhadian's Duplex Fraction method and Salihu's method to reduce the order of determinants to second order. Hence, this paper gives the possibility to develop a general method to compute the determinants of higher order.

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In this paper, we present an approach for the calculation of rectangular determinants, where in addition to the mathematical formula, we also provide a computer algorithm for their calculation. Firstly, we present a method similar to Sarrus method for calculating the rectangular determinant of the order 2 × 3.  Secondly, we present an approach for calculating the rectangular determinants of order m ×n by adding a row with all elements equal to one (1) in any row, as well as an application of Chio’s rule for calculating the rectangular determinants. Thirdly, we find the time complexity and comparison of the computer execution time of calculation of the rectangular determinant based on the presented algorithms and comparing them with the algorithm based on the Laplace method.

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The purpose of this study is to analyse the impact of the risk significance of audit results, the quality of the recommendations given on how easy it is to implement them, and the added benefit to the organization in implementing the recommendations. After a comprehensive literature review, the study provides a statistical analysis through a questionnaire that has been distributed to investigate the effect of Risk Significance, Ease of Implementation, and the Added Value on the implementation of the recommendations within organizations. Regarding the results obtained from the questionnaire, all Cronbach’s Alpha values are within the acceptable level, whereas the first three variables (Implementation of Recommendations, Risk Significance and Ease of Implementation) have a strong positive correlation between each other. There is a weak positive correlation between Added Value of Recommendations with other variables. In the regression analysis was found that all independent variables have a positive effect on the depended variable.