Abstract Applications of cooperative multicast communication techniques for emerging broadband multimedia services, such as Internet Protocol TV (IPTV), over WiMAX air interface have an important and attractive feature of reducing the network resource consumption, by broadcasting the data once to multiple users (e.g., TV channel group members) simultaneously independently of their number, using a common shared downlink channel. But users distributed around the cell face different channel conditions due to fading, user location, mobility, and other related characteristics. Several schemes were reported in the literature that attempt to introduce cooperative multicasting reliably and efficiently, some of which utilize subscribers with good-channel as relay agents (RA) to provide coverage for subscribers with bad-channel but fail to consider the huge amount of energy consumed in the process. In this thesis, we propose energy-efficient cooperative multicasting schemes by properly selecting RAs based on their location, channel condition and coverage. By exploiting the channel state information (CSI) and the location based service (LBS) techniques, protocol based on nearest neighbor, transmission distance and subscriber-subscriber interlink instantaneous CSI were proposed and implemented in order to achieve much improvement in the system performance. The number of RAs was varied in accordance to channel conditions and treated on a frame-per-frame basis. This approach considerably reduces the amount of energy consumed as proven by analysis and simulation models, providing a lower cost coverage solution with no dereliction in achieving high throughput for all group members.
سارة مفتاح الربيعي (2010)

Scientific Computing is an exciting and growing area that provides an important link between Computer Science and the Engineering and Physical Sciences. Today, computer graphics and geometric modeling are used routinely in science, engineering, business; and entertainment. In this thesis we develop object-oriented techniques and software for computing and visualizing implicitly defined manifolds ("surfaces") that arise a wide range of applications. The software differs from existing software for computing such manifolds in its software architecture. Furthermore, its algorithms are based on numerical continuation methods, rather than on subdivision techniques, which allows its practical application to the computation of two-dimensional manifolds in high-dimensional Euclidean spaces. The overall software provides a graphical user interface, algorithms for computing two-dimensional manifolds in higher-dimensional spaces, and graphics routines to visualize the manifolds.
Youssef Omran Gdura(6-2001)

—Predicting the groundwater level has recently become very important research topic especially with the rise of population density and consequently increasing the water demand. This paper uses the Random Forest and linear regression neural network models to predict the groundwater level of Wadi-Alshaty district in the South West part of Libya. The results are compared with that obtained using the hydrologic long-term forecasting graphical approach. One of the most important findings of this study is the effectiveness of the neural network models to investigate the fluctuation of the groundwater levels over time (20 years)
Amna Elhawil, Alarabi Naji, Malak Nuesry, Almabruk Sanossi(12-2021)