Mathematics Interdisciplinary Research
Year:2020 | Volume:5 | Issue:1|Papers Count:6

Expressions for the Zagreb indices and coindices of the total graph, semitotal point graph and of semi-total line graph of subdivision graphs in terms of the parameters of the parent graph are obtained, thus generalizing earlier existing results.

In this paper, exact formulas for the dependence, independence, vertex cover and clique polynomials of the power graph and its supergraphs for certain finite groups are presented.

Efficiency evaluation of units has been of interest since many years in different domains such as management, economy, business, banking and many others. Data envelopment analysis is one of the popular operations research methods for measuring the relative efficiency of units, which use multiple inputs to produce multiple outputs. As we know, universities play a key role in many aspects of a country such as industry, economic, training and many others. Therefore, evaluating the efficiency of the faculties of a specific university is vital for effective allocation and utilization of educational resources, and consequently for enhancing its overall performance. In this paper, we try to identify teaching and research strengths and weaknesses of each faculty of the University of Kashan and to provide a powerful tool for a fair comparison. To do this, we first determine the effective input and output variables for each teaching and research components. We then present a DEA model to evaluate both relative teaching and research efficiencies of each faculty of the University of Kashan.

In this paper, we present structure of the fixed point set results for condensing set-valued maps. Also, we prove a generalization of the Krasnosel’ skii-Perov connectedness principle to the case of condensing set-valued maps.

Let G be a simple graph with n vertices and with the Seidel matrix S. Suppose  1;  2; : : :;  n are the Seidel eigenvalues of G. The Estrada index of the Seidel matrix of G is defined as SEE(G) = Σ n i=1 e i. In this paper, we compute the Estrada index of the Seidel matrix of some known graphs. Also, some bounds for the Seidel energy of graphs are given.

In this article, the famous random walk model is exploited as a model of stochastic processes to retrieve some specific words which are used in social media by users. By spreading activation on semantic networking, this model can predict the probability of the words’ activation, including all probabilities in different steps. In fact, the trend of probability in different steps is shown and the result of two different weights, when the steps tend to infinity is compared. In addition, it is shown that the results of the random walk model are aligned with the experimental psychological tests, showing that, as a model for semantic memory, it is a suitable model for retrieving in social media.