Simulation of the performance of Cognitive Radio Networks with unreliable servers

This paper deals with a Cognitive Radio Network (CRN) which is modeled using a retrial queuing system with two finite-sources. This network includes two non-independent service units treating two types of users: Primary Users (PU) and Secondary Users (SU). The primary unit has priority queue (FIFO) and a second service unit contains an orbit both units are dedicated for the Primary Users and Secondary Users, respectively. The current work highlights the unreliability of the servers as we are assuming that both servers of this network are subject to random breakdowns and repairs. All the inter-event times in this CRN are either exponentially or non-exponentially distributed. The novelty of our investigation is to analyze the effect of several distributions (Gamma, Pareto, Log-normal, HypoExponential and Hyper-Exponential) of the failure and repair times on the main performance measure of the system. By the help of simulation we show some interesting results concerning to sensitivity problems

Simulation of the performance of Cognitive Radio Networks with unreliable servers

This paper deals with a Cognitive Radio Network (CRN) which is modeled using a retrial queuing system with two finite-sources. This network includes two non-independent service units treating two types of users: Primary Users (PU) and Secondary Users (SU). The primary unit has priority queue (FIFO) and a second service unit contains an orbit both units are dedicated for the Primary Users and Secondary Users, respectively. The current work highlights the unreliability of the servers as we are assuming that both servers of this network are subject to random breakdowns and repairs. All the inter-event times in this CRN are either exponentially or non-exponentially distributed. The novelty of our investigation is to analyze the effect of several distributions (Gamma, Pareto, Log-normal, HypoExponential and Hyper-Exponential) of the failure and repair times on the main performance measure of the system. By the help of simulation we show some interesting results concerning to sensitivity problems

Quantum state resolved studies of copper-H₂ system and electronic spectroscopy of Cu(100)

textHydrogen quantum state resolved energy losses upon scattering from copper are studied using molecular beam techniques and quantum state-specific detection methods. Also clean copper and hydrogen and oxygen covered copper surfaces were studied using electron spectroscopy. There are many questions about the nature of molecule-surface dynamics and the processes. The relative role of the different degrees of freedom in the reaction and the importance of non-adiabatic effects have been two of these questions. These two questions motivated this work. Energy loss in the elastic scattering of H₂(v=1. J=1) and H₂(v=0, J=1) molecular quantum states is measured as a function of incident translational energy at two surface temperatures. The energy loss process is shown to agree to the Baule classical model for energy ranges 74-150 meV for the excited vibrationally state and 74-125 for the ground vibrational state. Results suggest that translational energy is more effective that vibrational energy in the observed process. Theoretical models have been able to explain several processes using nonadiabatic models where friction coefficient tensor is included. Results in this thesis suggest that the energy loss in the elastic scattering is a nonadiabatic one. Electron spectroscopy studies showed that the surface plasmon intensity is very sensitive to surface contamination. Using this property, surface-only sensitive virtual temperature programmed desorption (VTPD) is developed. A better understanding of unique behavior of hydrogen covered Cu(100) was gained.Physic

Detailed Analysis of IRIS Recognition Performance

Iris recognition is a well-known biometric identification system which distinguishes authentic and imposter individuals based on the features of their irides. It employs stringent statistical analyses of the features of irides due to the fact that each person has a unique iris, just like a fingerprint. In this work, the approach adopted towards the iris recognition problem is through an exhaustive and careful analysis of the statistical properties of the iris images and the randomness of spurious noise effects. The ability to differentiate two different templates from each other improves with the increase in the number of the degrees of freedom (DOF). The DOF depends on the encoding schemes utilized and moreover, it is hypothesized that the encoding schemes used in themselves could influence the recognition performance. The CASIA (Chinese Academy of Sciences Institute of Automation) version 1 database of iris images used in this study has been modified by the addition of artificial noise in order to simulate practical real life in situ noisy iris capture environments. The classical and state-of-the-art segmentation techniques have been compared, determining whether they are superior to the others under several conditions. The 1D, 2D Gabor filters and the short window implementation were all tested. The conclusion was that the 2D Gabor Filters produce a lower equal error rate (EER), higher accuracy and decidability than by using the one-dimensional log Gabor filter. After modifying the one-dimensional log Gabor filters, a lower EER and higher accuracy was found as the noise level increased. This makes the modified 1D log Gabor Filters a better proposition in noisy conditions. The generated iris templates have a predetermined theoretical value of DOF and from the statistical analysis, an experimental value can be determined. The relation between these values can be used as a metric to compare different databases

Controlling Incoming Macrophages to Implants: Responsiveness of Macrophages to Gelatin Micropatterns under M1/M2 Phenotype Defining Biochemical Stimulations

Adverse immune reactions to implanted devices can seriously hamper the efficacy of implants. Monocyte derived macrophages play a crucial role in both initiation and resolution of the inflammatory response toward foreign bodies. As the surface microtopography is shown to exert significant effects on cell phenotype, it is hypothesized that the presence of micropatterns on implant/medical device surfaces can attenuate the immune response. To this end, enzymatically crosslinked micropatterned gelatin films of varying groove widths (2, 5, 10, 20, and 40 µm) are tested for their effect on incoming monocyte behavior. In order to distinguish the effect of cytokine microenvironment on pattern presence, monocytes are seeded on micropatterned films in normal culture medium or M1/M2 inducing media and their morphology and cytokine secretions are observed for 6 d. The presence of the patterns induces microenvironment-specific changes on the secretions of the attached cells and also on their size. IL-1ß, IL-4, IL-12, TNF-α, and CCL-18 secretions are significantly affected particularly in M1 induction media by pattern presence. It is demonstrated for the first time that micropatterned surfaces can be used to control the initial attachment and cytokine secretion of incoming macrophages if they are linked with a polarization inducing cytokine microenvironment