Topological Method for a Study of Discriminating Three Categories of Banks and its use in Attributes Reduction

This work approaches the problem of knowledge extraction within the banking domain using rough set, rough set theory can be considered as a topological method. Our main goal is to separate of the accounting attributes to discriminate between Islamic, mixed, and conventional banks. To this end, we have used the positive region in the rough set framework is traditional uncertainty measurements, used usually as in attribute reduction. Attributes banks will be separated and we are classified with a given decision, then we theoretically analyze the variance of the rough set. In the actual application, we used the financial semantics based on the domain expertise of experts to determine between the competing approaches. The results show the value of shared financial information for distinguishing between the three types of banks with certain attributes. These results are helping us offer a new view of attribute reduction in knowledge. We used MATLAB for our applications in computing.

Development of multi-systems for measurement of radionuclide absolute activity

The development of a multi-systems triple-to-double coincidence ratio (TDCR) and coincidence 4pb-g methods, based on liquid scintillation to radionuclide standardization is presented in this work. The adjustments of multi-systems were made using standards of 3H and 14C and 60Co. The initial stage was performing measurements of pure beta-emitters 3H, 63Ni, and 90Sr90Y standard solutions by TDCR. The results were consistent within the standard uncertainty. Measurements will be performed with a beta-gamma 60Co in a comparison to the SIR / BIPM to assess the multi-system's performance.

A Method of Uncertainty Measurements for Multidimensional Z-number and Their Applications

Z-number provides the reliability of evaluation information, and it is widely used in many fields. However, people usually describe things from various aspects, so multidimensional Z-number has more advantages over traditional Z-number in describing evaluation information. In view of the uncertainty of the multidimensional Z-number, the entropy of multidimensional Z-number is defined and an entropy formula of multidimensional Z-number is established. Furthermore, the entropy is used to construct an average operator of multidimensional Z-numbers. In addition, a novel distance measure is introduced to measure the distance between two multidimensional Z-numbers. Moreover, the group decision model in the multidimensional Z-number environment is constructed by combining the average operator with the TOPSIS decision-making method. Finally, an illustrative example is given to verify the feasibility and effectiveness of the proposed method.