Abstract: High speed communication and data movement is the key for mobile technologies and systems evolutions, which requires broadband communications and intelligent networking. The 5G mobile infrastructure enables development of many mobile technologies to fully use new technologies such as AI, mobile edge computing, M2M and data analytics. 5G/IMT-2020 will provide new applications and services for both developed and developed countries. Applications such as smart transport systems, e-health, education, smart grid, agriculture and disaster relief. In this paper we simulate and evaluate the mobile system related to its mobile application by using suitable queuing models to provide best performance based on its QoS.
Abdussalam Nuri Baryun, Khaled BenHamed(11-2021)

Deoxyribonucleic acid (DNA) micro-arrays present a powerful means of observing thousands of gene terms levels at the same time. They consist of high dimensional datasets, which challenge conventional clustering methods. The data’s high dimensionality calls for Self Organizing Maps (SOMs) to cluster DNA micro-array data. The DNA micro-array dataset are stored in huge biological databases for several purposes . The proposed methods are based on the idea of selecting a gene subset to distinguish all classes, it will be more effective to solve a multi-class problem, and we will propose a genetic programming (GP) based approach to analyze multi-class micro-array datasets. This biological dataset will be derived from multiple biological databases. The procedure responsible for extracting datasets called DNA-Aggregator. We will design a biological aggregator, which aggregates various datasets via DNA micro-array community-developed ontology based upon the concept of semantic Web for integrating and exchanging biological data. Our aggregator is composed of modules that retrieve the data from various biological databases. It will also enable queries by other applications to recognize the genes. The genes will be categorized in groups based on a classification method, which collects similar expression patterns. Using a clustering method such as k-mean is required either to discover the groups of similar objects from the biological database to characterize the underlying data distribution. arabic 10 English 60
Mariam Abojela Msaad, Zakaria Suliman Zubi(1-2010)

3D Integral Imaging (also referred to as 3D Holoscopic imaging) methodology uses the principle of “Fly’s eye” and hence allows natural viewing of objects (i.e. fatigue free viewing); 3D-holoscopic technology produces images that are true optical models. This technology is based on physical principles with duplication of light fields. In this paper, a new method of visualization medical 3D integral images is proposed. Digital Imaging and Communications in Medicine data images (DICOM) taken from CT, MRI, PET and US images that produced by 3D-Doctor software to generate medical 3D integral images visualization of anatomy without glass in natural light. The method is mainly based on multiprocessor ray tracing system as renderer. The medical 3D content is captured in real time with the content viewed by multiple viewers independently of their position, without the needs of 3D eyewear. Experimental results show validation of the new algorithm and demonstrated that medical 3D integral images content can be displayed on commercially available multi-view auto-stereoscopic display. Medical 3D integral images content is parsed into multiprocessor ray tracing system, consequently, short time of medical 3D integral images movie of such pelvis scene is generated and displayed on PC screen, LCD and Holovizio display.
Dr. Mahmoud Geat Mahmoud Eljadid, Prof. Amar Aggoun(5-2016)