Entropy define as uncertainty measure has been transfared by using the cumulative distribution function and reliability function for the Burr type – xii. In the case of data which suffer from volatility to build a model the probability distribution on every failure of a sample after achieving limitations function, probabilistic distribution. Has been derived formula probability distribution of the new transfer application entropy on the probability distribution of continuous Burr Type-XII and tested a new function and found that it achieved the conditions function probability, been derived mean and function probabilistic aggregate in order to be approved in the generation of data for the purpose of implementation of simulation

This study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big

Abstract

The current research aims to identify the level of E-learning among middle school students, the level of academic passion among middle school students, and the correlation between e-learning and academic passion among middle school students. In order to achieve the objectives of the research, the researcher developed two questionnaires to measure the variables of the study (e-learning and study passion) among students, these two tools were applied to the research sample, which was (380) male and female students in the first and second intermediate classes. The research concluded that there is a relationship between e-learning and academic passion among students.

After the information revolution that occurred in the Western world, and the developments in all fields, especially in the field of education and e-learning, from an integrated system based on the effective employment of information and communication technology in the teaching and learning processes through an environment rich in computer and Internet applications, the community and the learner were able to access information sources and learning at any time and place, in a way that achieves mutual interaction between the elements of the system and the surrounding environment. After the occurrence of the phenomenon of Covid 19, it led to a major interruption in all educational systems that had never happened before, and the disrupt

The primary purpose of this paper is to introduce the, N-coprobabilistic normed space, coprobabilistic dual space of N-coprobabilistic normed space and give some facts that are related of them.

E-learning is a necessity imposed by the Corona pandemic, which has disrupted various educational institutions in the world, but some of these institutions have not been affected and education has continued with them, due to their flexible educational system that was able to employ technology in the continuity of the educational process in the so-called e-learning, because It has characteristics that make it the most suitable alternative to avoid the consequences of the Corona pandemic and its damage to the educational process, as e-learning is one of the modern methods that contribute to enhancing the effectiveness of the learner, and enabling him to assume greater responsibility compared to traditional education, so the learner becomes

     The current issues in spam email detection systems are directly related to spam email classification's low accuracy and feature selection's high dimensionality. However, in machine learning (ML), feature selection (FS) as a global optimization strategy reduces data redundancy and produces a collection of precise and acceptable outcomes. A black hole algorithm-based FS algorithm is suggested in this paper for reducing the dimensionality of features and improving the accuracy of spam email classification. Each star's features are represented in binary form, with the features being transformed to binary using a sigmoid function. The proposed Binary Black Hole Algorithm (BBH) searches the feature space for the best feature subsets,

The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

The aim of this research is to diagnose the impact of competitive dimensions represented by quality, cost, time, flexibility on the efficiency of e-learning, The research adopted the descriptive analytical method by identifying the impact of these dimensions on the efficiency of e-learning, as well as the use of the statistical method for the purpose of eliciting results. The research concluded that there is an impact of the competitive dimensions on the efficiency of e-learning, as it has been proven that the special models for each of the research hypotheses are statistically significant and at a level of significance of 5%, and that each of these dimensions has a positive impact on the dependent variable, and the research recommended