—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)

Abstract The dynamic model of the heat process trainer PT326 is obtained experimentally by using the Ziegler–Nichols approximation and the system identification MATLAB toolbox. The interfacing data acquisition card is developed in two different designs the first design by using analog to digital, digital to analog IC's (ADC and DAC) and the parallel port, and the other design by using microcontroller and serial port. These two designs were tested in the department and give good results. The velocity PID controller is implemented through the developed cards in real time control system. An adapted neural network algorithm using the backpropagation approximation is tested on real time in the heat process trainer PT326. This research gives a good background for any control and computer engineer in the area of data acquisition and real time control system. The simulation results are the same as the online results of the real time Heat process control system.
نوري احمد عقاب (2010)

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)