<p>There is an Increasing demand for the education in the field of E-learning specially the higher education, and to keep contiuity between the user and the course director in any place and time. This research presents a proposed and simulation multimedia network design for distance learning utilizing ATM technique. The propsed framework determines the principle of ATM technology and shows how multimedia can be integrated within E- learning conteext. The first part of this research presents a theoretical design for the Electricity Department, university of technology. The purpose is to illustrate the usage of the ATM and Multimedia in distance learning process. In addition, this research composes two entities: Software entity by using image, sound and a mix between them to be transfered across the ATM network.. The MATLAB was used to validate the implementation of the required design objectives: (hardware entity) where a prototype is designed (experimental trial) , which aims to carry out the connectivity process between the user and course director, where multiple PCs are connected via unshielded twisted pair (UTP) and a web camera with microphone have been attached to PCs. To finalize this stage, an interface is implemented to show the data transmission process for multimedia by the ATM network and it has been realized through the Visual Basic language. Finally, to validate the level of success by using the ATM technique, some important factors have been determined through the analysis phase, which are: time delay, throughput and efficiency. The propsed design manages to minimize the impat of noise and improve the throuput ratio by 30% while minizing the delay with a ratio of 22%.</p>
Suffer most of the industrial sector companies from high Kperfi magnitude of the costs of industrial indirect, lack of equitable distribution of these costs on the objectives of cost, increased competition, and the lack of proper planning in line and changes faced by the industrial sector (general) and sample (private), as well as the difficulty in re- directing efforts to improve profitability and in-depth analysis of activities, and to identify untapped resource activities, then link these activities to the final products The research aims to apply the technology review and evaluate programs with the method (ABC) through the application stages of planning, scheduling and control and a comparison to get to the products of dev
... Show MoreAugmented reality technology is a modern technique used in all fields, including: medicine, engineering and education, and has received attention from officials in the educational process at present; The focus of this research is on the degree of use of augmented reality among field experience students in the project's optimal investment program for teaching staff and their difficulties, applied to a sample of 75 students, through a questionnaire prepared by the researcher as a tool to determine the degree of use, as well as difficulties. The researcher addressed the subject through two main axes to determine the degree of use, as well as the difficulties preventing teachers and learners from using this technique. The results of the rese
... Show MorePractical application is an effective tool for preparing qualified scientific and technical cadres if applied correctly and efficiently. In addition to being the complementary part of everything that has been studied in the years of study, it is a scientific linking tool between theory and application. Here lies the importance of this research in clarifying the central and important role that practical application plays in general in raising the scientific level of the student, and the extent of the suitability of the curriculum and means of practical application and the extent and needs of the students applying at the Institute of Administration - Rusafa - Department of Information Technology and Libraries. This research attempted to answe
... Show MoreGenome sequencing has significantly improved the understanding of HIV and AIDS through accurate data on viral transmission, evolution and anti-therapeutic processes. Deep learning algorithms, like the Fined-Tuned Gradient Descent Fused Multi-Kernal Convolutional Neural Network (FGD-MCNN), can predict strain behaviour and evaluate complex patterns. Using genotypic-phenotypic data obtained from the Stanford University HIV Drug Resistance Database, the FGD-MCNN created three files covering various antiretroviral medications for HIV predictions and drug resistance. These files include PIs, NRTIs and NNRTIs. FGD-MCNNs classify genetic sequences as vulnerable or resistant to antiretroviral drugs by analyzing chromosomal information and id
... Show MoreAchieving the Book of Return to the End of the Book of Alimony from the Manuscript of the Forum of the Abhar of the Sheikh (Abraham Bin
Muhammad ibn Ibrahim al-Halabi (d. 956 AH), who was a member of the Hanafi sect, was a long man
Fiqh, interpretation, modernity, Arab sciences, and readings
Hanafi as well as that he was Abid Zahid and the reason for his claim to this book that asked him some
He asked him to take advantage of it
Al-Hanafiya said, mentioning the sources from which he was taken, and presented his opinion and evidence on the correct
He mentioned the issues of the Hanafi jurisprudence in his book according to the chapters of the jurisprudence
Reaction is done to what you have achieved previously in the h
HM Al-Dabbas, RA Azeez, AE Ali, IRAQI JOURNAL OF COMPUTERS, COMMUNICATIONS, CONTROL AND SYSTEMS ENGINEERING, 2023
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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