Integral imaging, also known as Holoscopic imaging to be promising approach for glassless 3D and Its methodology uses the principle of “Fly’s eye” and hence allows natural viewing of objects (i.e. fatigue free viewing), In this paper, the main objective is to provide a new plug-in tools for full parallax computer generated 3D Holoscopic content, based mainly on 3D Virtual Reality Modeling Language parser to enable 3D integral images content and rendering to be produced from VRML file format, and displayed on auto-stereoscopic. In the proposed system, the 3D content is either captured by a single camera with a micro lens, cylindrical lens array or computer generated to allow for mixed 3D video generation. Multiprocessor ray tracing system is adapted to be able to generate 3D integral images that containing 3D IIVRML integral images content parser modules; new 3D IIVRML file format is created by uses 3D unidirectional camera parameters in order to import/accept into ray tracer renderer software. Experimental results show validation of the new plug-in software tool and tests on such Tie scene and Cessna scene . Consequently, 3D integral images frames and short time 3D II movie are generated and displayed without a glass on PC screen, LCD and the HoloVizio.
Dr. Mahmoud Geat Eljadid, Prof. Amar Aggoun(1-2018)

This paper describes a proposal for FAT tree based Network-on- Chip system based on MPLS forwarding mechanism. The FAT tree includes processing nodes and communication switches. IP node (processing nodes) has a message generator unit which randomly generates messages to different destinations with different packet lengths and buffering. The switch is based on MPLS technique and consists of the following units: crossbar switch, input/output link controllers and routing and arbitration units. A simulator has been developed in C++ to analyze the proposed architecture. A comparison with wormhole switch is provided to show the efficiency of the MPLS designed switch arabic 12 English 65
Azeddien M. Sllame, Nagwa Abobaker Salama(1-2016)

: 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 9 English 55
Mariam Abojela Msaad, Zakaria Suliman Zubi(1-2011)