in wireless networks, mobility is an important issue because Internet connectivity can only be effective if it is available during the movement of a node. To enhance mobility, the IEEE802.16e standard has set procedures to design wireless access systems to operate on the move without any disruption of services. The major difference between mobile WiMAX and fixed WiMAX is mobility support. However, speed and trajectory of nodes are unpredictable and can vary even in identical circumstances. In this paper mobile node trajectory is studied under different codecs schemes in order to evaluate the effect of node movement, towards or away from the base-station, on end to end delay, jitter, mean opinion score and throughput of a VoIP application. The results showed that trajectory inward improves network performance since mobile node gets closer to the base-station and hence signal is improved and less power is required. arabic 12 English 67
I. Almerhag, N. Aboalgasem(5-2017)

LTE’s study phase began in late 2004. The overall goal was to select technology that would keep 3GPP’s Universal Mobile Telecommunications System (UMTS) at the forefront of mobile wireless well into the next decade. Key project objectives were set in the following areas: peak data throughput; spectral efficiency; flexible channel bandwidths; latency; device complexity; and overall system cost. The main decision was whether to pursue the objectives by continuing to evolve the existing W-CDMA air interface (which incorporates HSPA (highspeed packet access) or adopt a new air interface based on OFDM. arabic 5 English 27
Mariam Abojela Msaad, Amer R. Zerek, Fareda A. Elmaryami(1-2014)

: 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)