The Determinant of Cubic-Matrix of order 2 and order 3: Some basic Properties and Algorithms

Based on geometric intuition, in this paper we are trying to give an idea and visualize the meaning of the determinants for the cubic-matrix. In this paper we have analyzed the possibilities of developing the concept of determinant of matrices with three indexed 3D Matrices. We define the concept of determinant for cubic-matrix of order 2 and order 3, study and prove some basic properties for calculations of determinants of cubic-matrix of order 2 and 3. Furthermore we have also tested several square determinant properties and noted that these properties also are applicable on this concept of 3D Determinants.Comment: 21 pages, 1 figures, 30 reference

A Review of Algorithms for Credit Risk Analysis

The interest collected by the main borrowers is collected to pay back the principal borrowed from the depositary bank. In financial risk management, credit risk assessment is becoming a significant sector. For the credit risk assessment of client data sets, many credit risk analysis methods are used. The assessment of the credit risk datasets leads to the choice to cancel the customer\u27s loan or to dismiss the customer\u27s request is a challenging task involving a profound assessment of the information set or client information. In this paper, we survey diverse automatic credit risk analysis methods used for credit risk assessment. Data mining approach, as the most often used approach for credit risk analysis was described with the focus to various algorithms, such as neural networks. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</p

A method to calculate determinants, with computer algorithm interpretation

In this paper we present the new algorithm to calculate determinants of nth order using Salihu’s method of reducing the order of determinants to second order. We have implemented the Dodgson’s algorithm within Salihu’s method to calculate submatrices. Within the paper we have also developed the computer algorithm to calculate the determinant using this new method. While comparing the computer execution time with the well-known methods, we have seen that this new algorithm presented is executed faster

Computer Function of Sarus Rule for Calculating Determinants of nth Order

In this paper, we present the calculation of the determinants based on Sarus rule. It is observed that the Sarus rule for third-order can be used even for higher orders, but the rule for the placement of the sign “+” or “-“ is different from what is currently used for the third order. During the calculations, it is noted that the rule of the placement of the mark is repeated the same pattern for each 4k order. Also, there are presented the computer functions to calculate the nth order determinants using Sarus rule

Comparison of Computer Execution Time of Determinant Calculation

Based on the fact that determinants and matrices have extensive application in scientific researches, and based on the fact that at the time of technology almost all different researches and simulations are made using computer systems. Therefore, within this paper, we have presented the comparison of the duration of calculating determinants through computer systems. In this paper, we have developed the computer function of calculating determinants using the Laplace expansion method, as well as the computational function for calculating determinants using the Salihu\u27s method. Within this paper, we have compared the duration of the execution of these functions of the calculation of the final result of the determinant. The duration analysis is done for different orders and the duration of both methods is compared

A Review of Algorithms for Credit Risk Analysis

The interest collected by the main borrowers is collected to pay back the principal borrowed from the depositary bank. In financial risk management, credit risk assessment is becoming a significant sector. For the credit risk assessment of client data sets, many credit risk analysis methods are used. The assessment of the credit risk datasets leads to the choice to cancel the customer\u27s loan or to dismiss the customer\u27s request is a challenging task involving a profound assessment of the information set or client information. In this paper, we survey diverse automatic credit risk analysis methods used for credit risk assessment. Data mining approach, as the most often used approach for credit risk analysis was described with the focus to various algorithms, such as neural networks. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.</p

The Effect of Strengths/Opportunities and Weaknesses/Challenges on Online Learning during the COVID -19 Pandemic

This paper researched the effect of strengths, opportunities and weaknesses or challenges on the online learning process during the COVID-19 pandemic. The research approach focuses on curriculum implementation and teaching quality using information technology systems (online teaching platforms). The research included 146 teachers (lower secondary and upper secondary school level), from whose responses we identified the strengths and opportunities as well as the weaknesses and challenges of online learning. While analyzing the data, we tested the construct reliability and noticed that Cronbach’s Alpha turned out to be at an acceptable level. From the paired sample t-test data analysis, it has also been concluded that, in the online learning process, strengths and opportunities are more considerable than weaknesses and challenges. Furthermore, linear regression indicated that the adjusted R-square of this model is 0.353, which signifies that the independent variables, strengths and opportunities and weaknesses or challenges, have an effect of 35.30% on the dependent variables, the curriculum implementation and the teaching quality, when using the information technology systems. As a result, we reached the conclusion that the positive effect of strengths and opportunities is higher than the negative effect of weaknesses or challenges

Perception of Customers on Electronic Banking Services Problems, and their improvements

The use of technology in banking services has facilitated many daily banking operations. However, the use of technology in electronic banking services has its problems as well. The aim of this research is to look at the effect of security and ease of use in the problems of electronic banking services. After the comprehensive literature review, this research presents a statistical analysis through a distributed questionnaire to look at the effect of security and ease of use in reducing the problems of electronic banking services. Regression analysis shows that security and ease of use of electronic banking services have a negative effect on problems of electronic banking services, which means that with the increase of securityand/or ease of use, their problems are reduced

The Effect of Fingerprint Authentication, Security and Ease of Use on using the Banking Cards

ATM Bank Cards have greatly influenced the changing of traditional banking practice and the evolving development of Information and Communication Technology has brought many changes to nearly all aspects of life. The purpose of this research is to investigate the impact of fingerprint authentication, ease of use and security in using the banking cards. After a comprehensive literature review, this study provides statistical analysis, by means of a questionnaire distributed to study the effect of the fingerprint authentication, the ease of use and the security on the usage of the banking cards. As regards the results obtained from the questionnaire, all of Cronbach\u27s Alpha values are within an acceptable level. While regarding the correlation, the usage, fingerprint authentication and ease of use are strongly correlated, but the correlation of security and other variables is weak. In the regression analysis, the positive effect on the use of bank cards was observed in all independent variables

A Review on Sorting Algorithms: Performance and Complexity

The use of computer systems in almost every field has led to an increase in the volume of digital data. However, a large number of digital data has also created the problem of their management, one of the main problems is sort-ing of data. Several different sorting algorithms have been developed for this issue. Therefore in this paper, we have analyzed the main sorting algorithms in relation to time and space complexity, as well as their performance. Also in this paper are identified some of the advantages and disadvantages of dif-ferent sorting algorithms