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CNN have been utilized in many domains and have revolutionized the field of computer vision, natural language processing and vehicular network management. CNNs are loaded with a number of advantages over the current methods of controlling vehicular networks. For instance, they can effectively handle the dynamic behavior of vehicular network due to their ability to learn recognition patterns. Additionally, CNNs are equipped with the capability to perform feature extraction along with its learning and integrating abilities, which can be highly advantageous for vehicular network management. Furthermore, they enable for parametric optimization thus increasing the speed of convergence with low-cost computational resources. Thus, CNNs are a promising approach for highly reliable communication and control of vehicular networks. [ABSTRACT FROM AUTHOR]

One of the promising alternative energy sources is the renewable energy sources like wind, solar, etc. Out of the various renewable energy sources, wind energy sector has grown very significantly in India. Generation, utilization and grid penetration of wind energy into the electrical grid is increasing worldwide. As the wind power is fluctuating in nature, it causes stability problems. This paper presents a comparative study on the voltage control capabilities of fixed speed and variable speed induction generators during system disturbance and grid faults. Simulation results show that the DFIG has the capability to control grid voltages and thus is capable of stabilizing the system. [ABSTRACT FROM AUTHOR]