Big Data Analysis and Computing Visions
Volume:1 Issue: 1, Mar 2022

To lessen the impact of a low student success rate, it's critical to be able to identify students who are in danger of failing early on, so that more targeted remedial intervention may be implemented. Private colleges use a variety of techniques, including increased tuition, expanded laboratory access, and the formation of learning communities. The prompt identification of students in danger of failing a given programme is important to both the students and the institutions with which they are registered, as seen by the debate presented below. Students are classified using artificial neural networks and random forests in this article. A private higher education provider provided a dataset of 2000 students. Artificial neural networks were found to provide the best performing model, with an accuracy of 83.24% percent.

In recent years, industrial advances in human societies have led to the rapid growth of electrical technology and its production and transmission, and this has led to an increase in power networks and the use of high voltages. While the energy from a high voltage power tower is not visible or palpable, it also has effects on human health and even the environment, depending on the intensity of the electromagnetic fields generated and the duration of exposure and human distance from these energy sources. It has a life that is sometimes very destructive. Therefore, the purpose of this study is to identify and evaluate the hazards caused by high voltage power towers in residential areas in order to prioritize and manage hazards to reduce or eliminate them. Therefore, at first, the power transmission process, equipment used in it and the safety, health and environmental hazards resulting from it, were identified and evaluated by the parameters of the Failure Modes and Effects Analysis (FMEA). Also, considering that one of the most important problems in the vicinity of residential areas with high voltage power transmission lines is the effects of magnetic field beams created around it, in order to determine the intensity of the magnetic field, 3D EMF TESTER device was used. Finally, the identified risks were scored based on the parameters of the research method and RPN was calculated for each. Then, with the help of SPSS software, the level of risk was calculated and the identified items were prioritized and analyzed based on it. According to the results, the highest RPN values were related to health risks and all risks in this group were in emergency situations.

In this paper, we present an Additive Slacks-Based Measure (ASBM) model for measuring efficiency Decision-Making Unit (DMU) in the presence of undesirable outputs based on DEA Ratio based (DEA-R) model. In order to obtain a reasonable measure of efficiency, this paper proposes a concept for determining the minimum number of undesirable outputs that a DMU is allowed to generate based on the assertion of weak disposability. We show theeffect of producing excessive amounts of undesirable outputs on efficiency. We propose an alternative form of the ASBM model to measure efficiency based on DEA-R models. In the first stage, we introduce counterpart (hypothetic) units corresponding to each DMUs. We obtain the true efficiency scores and slack variables regarding the input and output components of each of the DMUs. In the second stage, we obtain the efficiency scores in the presence of undesirable outputs based on ASBM-DEA-R model. In the following, we illustrate the proposed approach with a numerical example. At the end, the results of the research are given.

Teachers used to keep student records manually by calling names or distributing an attendance sheet around the classroom. These procedures take time, are prone to errors, and require proxy attendance. Furthermore, digital record assimilation is time-consuming since teachers must manually put in the entries in the database to generate reports. It's also important to keep manual and digital records consistent. Standard biometrics such as fingerprint and iris recognition have been used in automated systems in recent years. These systems are obtrusive by nature and necessitate high-tech equipment. Our proposed solution eliminates redundancy in human records and makes maintaining attendance a simple chore.

In this paper, we consider a Fuzzy Linear Fractional Programming (FLFP) problem under the condition that the objective function and the values of the right-hand side are represented by symmetric trapezoidal fuzzy numbers while the left-hand side constraints are represented by real numbers. Decision variables are characterized by trapezoidal fuzzy numbers and non-negative numbers. Utilizing the ranking function and computation of trapezoidal fuzzy numbers, the FLFP problem is transformed into a Crisp Linear Fractional Programming (CLFP) problem. This paper outfits another idea for diminishing the computational complexity, in any case without losing its viability crisp LFP problem. A modified possibility programming problem, Swarup is utilized to solve this program. Lead from real-life problems, a couple of mathematical models is considered to survey the legitimacy, usefulness and applicability of our method. Finally, some mathematical analysis along with one case study is given to show the novel strategies are superior to the current techniques.

Banks as financial and service-provider institutions in a society have a decisive role in the circulation of money and wealth of a country, so they have a special place in the economy of each country. Considering the importance of lending in quality of banks return and econom-ic decisions and increasing competition in banks, analysis and research in this area is neces-sary. Accordingly, in the present study, a data envelopment analysis model was used to evaluate and select the optimal portfolio of banks' listed loans in Tehran Stock Exchange for 2017. Bank loans were evaluated using data envelopment analysis method and based on a set of banking criteria whith the use Gams software. In this method, banks are ranked based on the highest score and then the most efficient banks are selected. Finally, in order to evaluate the effectiveness and usefulness of the proposed method, a case study has been used in Iranian banks, which the results of performance evaluation of each type of loans and bank has been extracted. The results of the present study indicated that out of all the lending, Pasar-gad, Parsian and Saman Banks had the best performance and the Sarmayeh, Dey and Gardeshgari Banks had the poorest performance.