Video surveillance system is the most important issue in homeland
security field. It is used as a security system because of its ability to track
and to detect a particular person. To overcome the lack of the conventional
video surveillance system that is based on human perception, we introduce a
novel cognitive video surveillance system (CVS) that is based on mobile agents.
CVS offers important attributes such as suspect objects detection and smart
camera cooperation for people tracking. According to many studies, an
agent-based approach is appropriate for distributed systems, since mobile
agents can transfer copies of themselves to other servers in the system.
Waves are the most important phenomena affecting marine navigation, either in the field of fishing, military or transporting of goods. This paper tries to answer the following important questions: What are the causes and types of waves in the coast of Zuaracity? What are their characteristics? And how do those waves affect the marine navigation and human activities on this coast? The research finds significant results devoted in that: the coast is exposed to on type of waves; wind waves. Zuara coast has never been exposed to waves of Tsunami or landslides. The largest size of the wave forms in winter season due to the wind of north-west which is the fastest wind type that the Libyan coast is exposed to. However, the highest speed is up to 65 knots accompanied with waves reach a height of more than 7 meters. The research also classifies the wind speeds that lead to cancelling ships and boats trips that depend on this work is studying the waves in Zuara coast and the relationship with the waves of Libyan coast and Mediterranean sea. Also, it focuses on the effect of waves on boat speed, design, fuel consumption, and other effects.
Wireless Sensor Network (WSN) is used in various applications. A
main performance factor for WSN is the battery life that depends on energy
consumption on the sensor. To reduce the energy consumption, an energy
efficient transmission technique is required. Cluster Wireless Sensor Network
(CWSN) groups the sensors that have the best channel condition and form a MIMO
system. This leads to enhancing the transmission and hence reducing energy consumed by the sensor. In CWSN systems multiple signals are
combined at the transmitter and transmitted by using multiple
antennas according to channel condition. CWSN requires a good estimation of the
Channel State Information (CSI) to implement a powerful and efficient system.
Channel Estimation technique should be used to better form the CWSN and make
use of the MIMO features. Adaptive Channel Estimation (ACE) is used to enhance
the BER performance of the CWSN by utilizing the retransmission feature devised
in this paper and feeding the CSI obtained to further enhance the clustering
algorithm. We use Particle Swarm Optimization (PSO) algorithm to find the
optimal cluster members according to a fitness function that derived from the
channel condition. Too many calculations and operations are required in exhaustive
search algorithms to form the optimal cluster arrangement. It shows that
optimal cluster formation can be implemented fast and efficiently by using