The problem of the paper focused on the role of the learning organization in the crisis management strategy, and the extent of the actual interest in both the learning organization and the crisis management and aimed at diagnosing and analyzing that and surrounding questions. The Statistical Package for the Social Sciences (SPSS) program was used to calculate the results and the correlation coefficient between the two main variables. The methodology was descriptive and analytical. The case study was followed by a questionnaire that was distributed to a sample of 31 teachers. The paper adopted a seven-dimensional model of systemic thinking that encourages questioning, empowerment, provision of advanced technologies, and strategic lea

The convergence speed is the most important feature of Back-Propagation (BP) algorithm. A lot of improvements were proposed to this algorithm since its presentation, in order to speed up the convergence phase. In this paper, a new modified BP algorithm called Speeding up Back-Propagation Learning (SUBPL) algorithm is proposed and compared to the standard BP. Different data sets were implemented and experimented to verify the improvement in SUBPL.

       In the pandemic era of COVID19, software engineering and artificial intelligence tools played a major role in monitoring, managing, and predicting the spread of the virus. According to reports released by the World Health Organization, all attempts to prevent any form of infection are highly recommended among people. One side of avoiding infection is requiring people to wear face masks. The problem is that some people do not incline to wear a face mask, and guiding them manually by police is not easy especially in a large or public area to avoid this infection. The purpose of this paper is to construct a software tool called Face Mask Detection (FMD) to detect any face that does not wear a mask in a specific

Detection of early clinical keratoconus (KCN) is a challenging task, even for expert clinicians. In this study, we propose a deep learning (DL) model to address this challenge. We first used Xception and InceptionResNetV2 DL architectures to extract features from three different corneal maps collected from 1371 eyes examined in an eye clinic in Egypt. We then fused features using Xception and InceptionResNetV2 to detect subclinical forms of KCN more accurately and robustly. We obtained an area under the receiver operating characteristic curves (AUC) of 0.99 and an accuracy range of 97–100% to distinguish normal eyes from eyes with subclinical and established KCN. We further validated the model based on an independent dataset with

The research aimed to prepare a measure of the importance of enlightenment, academic education, and applied skills for third-stage female students, including teaching methods from their point of view/College of Education and Sports Sciences/University of Baghdad/Al-Jadriyah. The researchers used descriptive description in the comprehensive research procedures, an appropriate methodology in achieving the research objectives, sufficient for interpretations, how important is the academic teacher’s knowledge of teaching methods for student learning, what are the roles that the learners have acquired from the academic teacher. The scale of importance and horror consists of 15 items. The research population includes female students of t

The research aimed to prepare a measure of the importance of enlightenment, academic education, and applied skills for third-stage female students, including teaching methods from their point of view/College of Education and Sports Sciences/University of Baghdad/Al-Jadriyah. The researchers used descriptive description in the comprehensive research procedures, an appropriate methodology in achieving the research objectives, sufficient for interpretations, how important is the academic teacher’s knowledge of teaching methods for student learning, what are the roles that the learners have acquired from the academic teacher. The scale of importance and horror consists of 15 items. The research population includes female students of t

Abstract

That the reduction of costs for products and services provided by economic units is one of the main concerns at the present time to keep pace with competition in the markets, economic units are always striving to stay competitive in a modern business environment and achieve a competitive advantage, (TDABC) in the General Company for Electrical and Electronic Industries / Air cooler engine plant to reduce the costs facing the economic units under the circumstances of the Iraqi environment, especially the industrial, and the need for development events in traditional methods (TDABC) as a technology for reducing costs by relying on time guidelines. The research also concluded that the financial and non-financ

BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.