The literature shows conflicting outcomes, making it difficult to determine how e-learning affects the performance of students in higher education. The effect of e-learning was studied and data has been gathered with the utilization of a variety of qualitative and quantitative methods, especially in relation to students' academic achievements and perceptions in higher education, according to literature review that has been drawn from articles published in the past two decades (2000-2020). The development of a sense of community in the on-line environment has been identified to be one of the main difficulties in e-learning education across this whole review. In order to create an efficient online learning community, it could be claimed that both instructors and students must work together to engage in extensive collaboration and engagement with both students and one another. Since educational institutions must be ready for the sustainability regarding e-learning adoption, the presented work argues that there is a requirement for better identification and knowledge of this. The results revealed that a university's competency and capacity for meeting elearning demand stemmed from actual requirement for the implementation of e-learning for specific academic environment hinged on sustainability related to implementation of e-learning. In addition to that, each university's local culture influenced and supported the implementation process, where the inhibiting and driving variables had a substantial effect on the continuity and outcome of the process. The range of digital tools that can successfully encourage social interactions as well as the learning community need to be further researched. With regard to higher education, there is an increase in innovative assessments of variables to assess learning results in the settings of digital learning. Researchers should carefully evaluate their study designs and study subjects in digital learning environments for this reason, as well as how to handle measuring learning.
The present study aims at knowing the reasons of the student of secondary school abstention from participation in the theatrical activity, and to know the reasons that resulted in this abstention. In addition to that, the study aims at knowing the differences according to variables (gender, scholastic stage, and major of study). The sample of the study was chosen from the secondary schools in Baghdad in the random manner from Al-Karakh and Al-Rusafa districts of (147) students. The questionnaire was used to collected data.
The result showed that all the items are intense, the item of (Students do not know how to use their leisure time) obtained the hi
... Show MoreThe elements of theater formation that fall within the spatial experience of the scenography of the show, which the directors work in in the imaginary theater, are important and have an aesthetic, intellectual and cognitive dimension, working to highlight reality in an aesthetic image surrounding space and space. And its relationship to the distinct, multiple and variable spaces above the stage, to produce theatrical signals and endless meanings through the possibility of infinite reconfiguration of the theater's space and its public and private space through the distribution of a group of blocks within the scenic image.
I dealt with in the first chapter (the methodological framework), which includes the research problem identified
Churning of employees from organizations is a serious problem. Turnover or churn of employees within an organization needs to be solved since it has negative impact on the organization. Manual detection of employee churn is quite difficult, so machine learning (ML) algorithms have been frequently used for employee churn detection as well as employee categorization according to turnover. Using Machine learning, only one study looks into the categorization of employees up to date. A novel multi-criterion decision-making approach (MCDM) coupled with DE-PARETO principle has been proposed to categorize employees. This is referred to as SNEC scheme. An AHP-TOPSIS DE-PARETO PRINCIPLE model (AHPTOPDE) has been designed that uses 2-stage MCDM s
... Show MoreDuring COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve
... Show MoreIn this paper, an eco-epidemiological prey-predator system when the predator is subjected to the weak Allee effect, and harvesting was proposed and studied. The set of ordinary differential equations that simulate the system’s dynamic is constructed. The impact of fear and Allee’s effect on the system's dynamic behavior is one of our main objectives. The properties of the solution of the system were studied. All possible equilibrium points were determined, and their local, as well as global stabilities, were investigated. The possibility of the occurrence of local bifurcation was studied. Numerical simulation was used to further evaluate the global dynamics and understood the effects of varying parameters on the asymptotic behavior of t
... Show MoreTight oil reservoirs have been a concerned of the oil industry due to their substantial influence on oil production. Due to their poor permeability, numerous problems are encountered while producing from tight reservoirs. Petrophysical and geomechanical rock properties are essential for understanding and assessing the fracability of reservoirs, especially tight reservoirs, to enhance permeability. In this study, Saadi B reservoir in Halfaya Iraqi oil field is considered as the main tight reservoir. Petrophysical and geomechanical properties have been estimated using full-set well logs for a vertical well that penetrates Saadi reservoir and validated with support of diagnostic fracture injection test data employing standard equations
... Show MoreThe research aims to determine the impact of Human Resources Accounting (HRA) on employee’s performance. The research’s problem was embodied in the lack of interest in HRA, which was reflected on the performance of employees in the Ministry of Education; the research adopted the descriptive-analytical approach, and the research community included the directors of departments and people at the headquarters of the Ministry of Education. The sample size was (224) individuals from the total community of 533. The questionnaire was adopted as the main tool for collecting data and information, as well as the interviews that were conducted by the researcher. In order to analyze t
... Show MoreBackground: urethrocutaneous fistula after hypospadias surgery repair is the most common complication and remains a frustrating problem for surgeon and the patient. The problem is exacerbated because the urethrocutaneous fistula may recur which adds more demands surgery. Objectives: The purpose of this study is to evaluate of the use of oral mucosal graft for management of recurrent urethrocutaneous fistula after hypospadias repair. Patients and Methods: twelfth patients with age ranging from 4 year to 15 years were presented with history of recurrent fistula. Most of fistula were located in proximal penile and penoscrotal region (58.3%) . those patients were repaired by using oral mucosal graft with mean postoperative follow up period up t
... Show MoreAdvanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m
... Show More