E-learning seeks to create an interactive learning environment between the teacher and the learner through electronic media conveying in more than one direction, regardless of how the environment and its variables are identified. It also develops skills necessary to deal with technology in order to be able to take into account the individual differences between them and helps e-learning teacher and learner to achieve the goals set in advance and identify educational objectives in a clear manner. The research aims to identify e-learning in its benefits and management systems. It has three sections dealt with in the current research. Chapter II concentrates on the research Methodology, which consisted of three sections: The first sections: What is e-learning, its benefits, types, constraints and disadvantages, The second section: the aspects of difference between e-learning and traditional education, and the most important equipment. For the third section, it addressed the e-learning and the management systems. Chapter III presents conclusions, recommendations, and suggestions, which can be summarized as follows: E-learning is directly dependent on the use of ICTs, which means that teacher and learner must be familiar with these techniques for the success of the educational process. E-learning provides a great opportunity for many groups in the society, especially those groups missed opportunities for education regardless of the reasons, whether economic or social. For Recommendations: The need to encourage school administrations to adopt this type of education and encourage teachers to use it. The need to set up training courses for teachers to clarify the importance of e-learning, ICT and qualify them to deal with this technology.
Purpose – measure the relationship between operation management strategies as an independent variable on the customer's delight as an approved variable.
Design/methodology/approach – The research sample vocabulary included sales representatives and customers of the researched markets at a rate of (100%). The recovery rate is (95) Customers and (95) delegates for the products for the factory in neighbourhood (Banooks and Karrada ) regions were randomly chosen from an open community in these two residential areas. Statistical methods were used (arithmetic media, standard deviations, t-test, correlation coefficient (Horst), simple regression analysis).
Findings – The people in charge of the factory management nee
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The advancements in horizontal drilling combined with hydraulic fracturing have been historically proven as the most viable technologies in the exploitation of unconventional resources (e.g., shale and tight gas reservoirs). However, the number of fractures, well timing, and arrangement pattern can have a significant impact on the project economy. Therefore, such design and operating parameters need to be efficiently optimized for obtaining the best production performance from unconventional gas reservoirs. In this study, the process of selecting the optimal number of fractures was conducted on a section of a tight gas reservoir model (based on data from the Whicher Range (WR) tight gas field in Western Australia). Then, the optimal number
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This research aims to build a model to analyze the role of digital transformation (DT) and HR Flexibility in the strategic human resource management outcomes (SHRM outcomes) in the Iraqi Banking Sector. To be more precise, it explores whether HR Flexibility is a mediating factor between digital transformation and bank performance, employee dedication, and talent preservation. The research adopted a quantitative cross-sectional study design. A structured questionnaire will be used to collect data from at least 420 respondents. The method of analysis will be through surveys collected from 420 employees in the private and government banks in Iraq. IBM SPSS will be used to conduct preliminary analysis, and IBM SPSS AMOS will be used for Confirm
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Underwater Wireless Sensor Networks (UWSNs) play a vital role in ocean monitoring and exploration. However, harsh underwater conditions and frequent topology changes caused by node and sink mobility pose significant challenges for reliable routing. Conventional routing protocols that depend on global route reconstruction and static paths generate excessive control overhead and degrade performance in large-scale underwater environments. In this paper, we propose an energy-efficient virtual cell-based mobile-sink adaptive routing (VC-MAR) protocol for UWSNs. The sensing field is logically partitioned into a three-dimensional grid of virtual cells, where a cell-gateway is elected in each cell to construct a low-overhead routing backbon
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Le présent travail aborde la question de l’enseignement de traduction en tant que matière faisant partie du programme élaboré dans des Départements de Français au sein de certaines universités irakiennes, en particulier celle de Bagdad. La méthode d’enseigner suivie constitue une véritable problématique qu’on a bien diagnostiquée à partir de quelques années d’expériences, à la lumière des observations faites dans des cours de traduction professionnelle, et dans la perspective des citations et témoignages établies par des traductologues et pédagogues et principalement par Marianne LEDERER qui a établi la Théorie Interprétative de la traduction. Mais pourquoi l’enseignement lui-même poserait une telle probl
... Show MoreMachine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims
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HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
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