Biometrics technologies have been around for quite some time and many have been deployed for different applications all around the world, ranging from small companies' time and attendance systems to access control systems for nuclear facilities. Biometrics offer a reliable solution for the establishment of the distinctiveness of identity based on "who an individual is", rather than what he or she knows or carries. Biometric Systems automatically verify a person's identity based on his anatomical and behavioral characteristics. Biometric traits represent a strong and undeviating link between a person and his identity, these traits cannot be easily lost or forgotten or faked. Since biometric systems require the user to be present at the time of authentication. Some biometric systems are more reliable than others, yet biometric systems are neither secure nor accurate, all biometrics have their strengths and weaknesses. Although some of these systems have shown reliability and solidarity, work still has to be done to improve the quality of service they provide. In this paper we present the most common and reliable known biometric systems suitable for Multimodal Biometrics Fusion, providing highly efficient and secure systems, showing their strengths and weaknesses and also presenting technologies in which may have great benefits for security applications in the near future.
Abdulmonam Omar Ahmed Alaswad, Ihab Meftah Elfituri, Fawzia Elhashmi Mohamad(0-2014)

Agent-Based Models (ABM) have become popular as tools for epidemiological simulations due to their ability to model real life phenomena at individual entity levels. ABM is a relatively new area for modelling as compared to the classical modelling methods. Many different fields use agentbased models including ecology, demography, geography, political science and epidemiology. Recently, an abundance of literature has presented applications of agent-based modeling in the biological systems. In this paper, the authors present an agent-based model attempts to simulate an epidemiological disease known as Cutaneous Leishmaniasis (CL). The model is developed to investigate the ability of ABM in modelling a disease that keeps speeding in Libya. The methodology used for describing and designing CL model is derived from nature of the disease mechanism. The ABM model involves three types of agents: Human, Rodent and Sand-fly. Each agent has its own properties, in addition to other global parameters which affect the human infection processes. The main parameter used for monitoring the model's performance is the number of people infected. The model experiments are designed to investigate ABM’s performance in modeling CL disease. Simulation results show that human infection rate is increasing or decreasing dependent on number of sand-fly vectors, number of host rodents, and human population awareness level arabic 7 English 62
Rudwan A. Husain, Hala Shaar, Marwa Solla, Hassan A. H. Ebrahem(3-2019)

Holoscopic 3D imaging (H3D) technology also known as integral imaging is a true 3D imaging technology. It offers the simplest form that is capable of recording and replaying the true light field 3D scene in the form of a planar intensity distribution, by employing Microlens array. Despite it uses the same characteristics of holographic, it records the 3D information in 2D form and display in full 3D with optical component, without the need of coherent light source and confine dark fine. In addition, it facilitates postproduction processing such as refocusing. This makes it more practical approach for real-time 3D image capture and display. In this paper, a new method of extract 3D integral images data from raster maps. The R2V is an advanced raster to vector conversion software system is mainly used in order to generate geographical 3D integral images. Experimental results are extremely satisfactory and for the first time it is proved that, Geographic 3D Integral Images is generated. It means that, a new certain approach enables GIS applications of using 3D integral images is now established.
Dr. Mahmoud Geat Eljadid(12-2021)