Multi Protocol Label Switching (MPLS) is a core networking technology that operates essentially in between Layers 2 and 3 of the OSI model; for this reason, MPLS has been referred to as operating at Layer 2.5. MPLS can overlay existing technologies such as Asynchronous Transfer Mode (ATM) or Frame Relay, or it can operate in an entirely IP native environment; this can allow users to take advantage of existing Customer Premises Equipment (CPE) while making a move towards converging all network traffic, such as data, video and voice, at a pace that users can accommodate and afford. MPLS provides. its users a number of advantageous features such as traffic engineering, network convergence, failure protection, and the ability to guarantee Quality of Service (QoS) over IP. arabic 2 English 27
Mariam Abojela Msaad, Amer R. Zerek , Wesam M. Tohamei(1-2012)

DLFSR is promising for enhancing the security of stream ciphers. However, good inviolability and statistical properties of the DLFSR generator are only achievable when the parameters of the switching algorithm are properly selected. This paper describes a new experimental method for choosing suitable parameters for the algorithm of switching the polynomial in DLFSR. This method was used to enhance the Grain-128 stream cipher. The randomness of the modified Grain was evaluated using the NIST suite, and the results are encouraging. The modified Grain was also compared to the original, and the results indicated that the modified algorithm outperforms the original in several tests. arabic 12 English 82
Fayrouz Aljadi, Ibrahim Almerhag, Fardous Eljadi(3-2019)

: 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)