Journal Of AL-Turath University College

Coronavirus disease is considered a serious disease because of its devastating impact on the health and life of the world and its significant impact on the deterioration of the economic and commercial situation in the world. In this paper, we presented a technique for diagnosing the Coronavirus disease based on deep learning and discrete wavelet transform. The discrete wavelet transform used in the pre-processing stage to reduce the complexity witch led to increasing the speed of the proposed technique while the deep learning used in the feature extraction and classification stage. Unlike the other methods in this domain, the proposed technique evaluates the noise impact on the accuracy of the proposed technique by considering two type of the noise namely: pepper & Salt noise and Gaussian Noise. Furthermore, the proposed technique evaluates the effect of the rotation on the accuracy by taken different rotation angles. The analysis of the extensive experiments that carried out on the dataset refer that the proposed technique achieve high accuracy (99%) with less computation time, as well as it robust against the noise and rotation variations.

The spread and spread of the COVID-19 virus, infecting societies and causing many deaths, led to social, economic and political problems, and this prompted the extraction of human efforts to preserve the human race from extinction. It is known that the sources of medical images such as (X-rays, tomography, resonance imaging) suffered and is still suffering from the noise sources that it is exposed to during imaging or treatment. The (BRISK, HARRIS) technique came to treat and try to identify the injury or not, and this topic has a future impact, relying on it to set the healing mechanism. Where (200) images of infected and non-infected people with COVID-19 were taken, and the (BRISK, HARRIS) method was applied for the purpose of extracting image features, finding and maintaining pure image qualities and excluding noise.
Experimental results showed the ability to interpret and extract the injured from the non-affected, as well as excluding other associated effects. Other methods such as Binary big and hybrid models can be adopted and results are compared.

The rapid development of computing platforms and Internet technologies has had a major impact on modern educational systems in universities and scientific institutions that are facing continually new technological challenges. The usage of the virtual environment takes many formats, for example, the teaching-learning system, which is available online. The spread of mobile devices recently has created the technological sphere for the teacher. Therefore, a student can get an advantage from the various online information, communication, collaboration, and sharing with others.This paper investigates and evaluates the outcomes of adopting e-assessment and e-exams integrated into blended learning. examining scholarly research benefits along with usage LMS platform(DoceboLMS) based on Cloud and HTML5 technology, by (122) undergraduate students’ feedback according to (18) different questionnaires. The analysis of results from the survey reveals that more than half of the students (59.0%) are fans and are willing to use mobile devices as a learning tool. They have the motive to learn via online learning tools, which make existing electronic-examine content more accessible (29) Multiple Choice questions, as well as summative evaluations at the end of each course, could be used to assess their learning.

Chronic kidney disease still has a great burden with its negative impact on human life. Increasing incidence has become a global problem, and a major challenge for the health sector in terms of efforts and costs in their quest to save the lives of many patients1. A person cannot live without his kidneys for only 18 days or less, after which he needs dialysis. Here lies the importance of biostatistical methods for their ability to predict or classify patients in the early stages of this type of disease to which humans are exposed. These predictions help and enable the medical team to make the best-case management decision. These methods include Logistic Regression, CART (Classification and Regression Tree) and Random Forest (RF). The study was based on a sample of medical data consisting of 153 healthy and healthy patients and (11) independent variables to classify who has kidney disease or is healthy. The data was divided into two parts, 70% for the training and model development stage, and 30% for testing the strength of the models for the three methods. The criteria (Accuracy, sensitivity and specificity and Area under the curve ROC) were used to evaluate the three models in the testing phase. The results were: (86%, 89% and 86%) accuracy (100%, 91%, and 92%) sensitivity, and (67%, 86% and 78%) specificity and (70.6%, 73.4% and 81.1%) AUC of ROC, respectively. Based on the results of the research, the study concluded that the RF method achieved preference among the three methods, and the most important variables that have a clear effect on chronic kidney patients are albumin and urea.

The study aims to develop an ordinal logistic regression (OLR) model to identify the issues that face students, academic teachers, with blended learning with Coivd-19. Additionally, to explore the factors that influence the adoption of (BL) in Northern Technical University (NTU). Finally, to provide an analytical model to facilitate the task for university strategies and their decision-making for solving the problem and to deal with the present suggestions. An e-questioner study of the opinions of teachers and students were used to collect data. The data includes 214 that come from the e-questionnaire that was designed and distributed to the appropriate samples of educational groups. Then, ordinal logistic regression was used to develop 4 models of the effectiveness of each axis. It can be concluded that BL is a useful style of learning. However, it is still suffering from several impediments. One of the biggest obstacles students and staff are facing is the weakness of the internet network because of the inability to connect to fibreoptic Internet. Alongside it, the high prices of internet subscription and the lack of student’s modern devices (computer and mobile) to connect to the platform. Another disadvantage is the drop of opportunities for excellence and creative students due to online assessments that allows other students to check the internet for solutions and answers. According to the data, poor connection was the main issue of BL that is facing students and staff. Additionally, the difficulty to get devices and facilities by students was another limitation of BL (cost effectiveness).

The research seeks to show the impact of total quality management on the competitive policy adopted in the prefabricated building factory, and to reach the goal of the research, the main hypothesis was adopted that “TQM is linked to a positive moral relationship with the competitive policy represented by (product policy, pricing policy, promotion policy, policy of Pricing, policy of development and innovation, policy of product differentiation and quality improvement, after-sales services) in the ready-made construction factory.” The productivity of the (30) individuals, their answers were adopted after analyzing and interpreting them to reach a set of conclusions that were the basis for submitting proposals that we hope will be valuable and useful for the researched company.

Creating highly efficient university outputs requires innovative behavior on the part of those output makers. The process of developing innovative behavior in organizations is largely related to the personal traits and competencies of employees. In this paper, we seek to investigate the effect of proactive personalities along with creative self-efficacy in the emergence of innovative behavior in the workplace. The current study attempts to explore the importance of the personal aspect of the teachers at the Southern Technical University in building knowledge and human capital and investing it in the educational service industry processes. A random sample of 256 teachers in multiple and diverse specializations was targeted. The results obtained indicate that there is a large role for the proactive personality to predict innovative behavior in the workplace. Creative self-efficacy also serves as the fuel that pushes the proactive personality-creative behavior related to a more explanatory place. The results were discussed and a number of recommendations were proposed that serve as a guiding guide for senior administrations in educational institutions on how to invest knowledge capital in aspects of performance and organizational effectiveness.