<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>
The deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
... Show MoreABSTRACT Possible interference of vamin nutritional solution with the activity of several B-lactam antibiotics against E.coli was evaluated in vitro.In Minimal basal salts-glucose medium rapid growth inhibition of sensitive E. coli was induced by 4 µg/ml of ampicillin / cloxaillin, 8 µg/ml of ampicillin, 6 µg/ml of carbencillin, hostacillin, and cephalotin, and by 32 µg/ml of penicillin G and cloxacillin. Significant inactivation of up to 32 µg/ml of carbencillin, cephalotin, penicillin G, and hostacillin was induced by addition of 1:20 v/v vamin. This inactivation was due to the presence of specific amino acids in the mixture. Deletions of amino acids revealed that valine, leucine, isoleucine, tyrosine, tryptophan, phenylalanine, cys
... Show MoreThe preparation of the title compound, C26H25N, was achieved by the condensation of an ethanolic mixture of benzaldehyde, cyclohexanone and ammonium acetate in a 2:1:1 molar ratio. There are two crystallographically independent molecules in the asymmetric unit. The two cyclohexyl rings adopt an
The research aimed at designing a teaching aid for learning backswing into handstand as well as identifying its effect on learning skill performance. The researchers hypothesized statistical differences between pre and post-tests in favor of the research group. They used the experimental method on six (13 – 16) year–old Baghdad club gymnasts. The researchers used the one group design in which all players perform pretests followed by special tests on the teaching aid than are tested posttests. The researchers conclude that the teaching aid positively affected learning the skill as well as the teaching aid was very good and endured the performance of all gymnasts. The researcher recommended making simi
... Show MoreThe aim of this study to identity using Daniel's model and Driver’s model in learning a kinetic chain on the uneven bars in the artistic gymnastics for female students. The researchers used the experimental method to design equivalent groups with a preand post-test, and the research community was identified with the students of the third stage in the college for the academic year 2020-2021 .The subject was, (3) class were randomly selected, so (30) students distributed into (3) groups). has been conducted pretesting after implementation of the curriculum for (4) weeks and used the statistical bag of social sciences(SPSS)to process the results of the research and a set of conclusions was reached, the most important of which is t
... Show MoreThis study aimed at isolating uropathogenic Escherichia coli from urinary tract infections (UTIs) of human and cattle to examine the molecular diversity and phylogenetic relationship of the isolates. A total of 100 urine samples were collected from UTIs of human and cattle. The isolates identification was done using routine diagnostic methods and confirmed by Vitek2. Antimicrobial susceptibility was tested against 10 antimicrobials. Random amplified polymorphic DNA (RAPD)-polymerase chain reaction (PCR) was applied to identify the genetic diversity among E. coli isolates from human and animal origin by using five different octamer primers. The gelJ software for the phylogenetic analysis created Dendrograms. Out of 50 human urine samples, E.
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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