Sharif Digital Repository

Network survivability gauges the ability of a network to support the committed Quality of Services (QoS) continuously in the presence of various failure scenarios. We perceive that both performance and availability are integral components of survivability. Therefore, we propose a composite model for survivability that consists of performance and availability analysis. A analytical technique is presented to find the excess loss due to failure (ELF) when the system is operating in gracefully degraded states. An algorithm is proposed to carry out the availability analysis of the network even when the available paths between nodes are non-disjoint. These two models are combined to construct a... 

Designing an intelligent controller for landing phase of a jet transport aircraft in presence of different wind patterns, in order to expand the flight safety envelope has been considered. There are some dangerous conditions like gusts and downbursts which may occur rarely in service life of aircraft, though, aircraft must be tested for these dangerous conditions. Then it is desired to design a controller that not only acts well in usual conditions but also has an acceptable performance in those hazardous conditions. Four different types of controllers have been designed named PID, Neuro, hybrid Neuro-PID and Anfis-PID (Adaptive Network-based Fuzzy Inference System) controllers. Simulation... 

A continuous growth in nonlinear loads may cause an increment in harmonic distortion and some other important problems in power systems so considering power quality effects in optimal reactive power planning has become more crucial than before. In this paper, optimal reactive power planning based on voltage profile deviation and voltage THD decrement is studied. The planning problem is studied using reactive power injection in each bus bar and genetic algorithm is also used for solving optimization problem. Obtained results for 5-bus and 30-bus IEEE standard networks are also presented. ©2004IEEE  

We propose a general mobility model based on region splitting and mapping each subregion on a multi-server node. By using the theory of multi-class Jackson queueing network with multiserver nodes and employing the product-form solution for such queueing networks, we obtain an analytical form for the spatial traffic distribution in a typical region with specific number of users. To this end, we consider the spatial statistical pattern for new and handoff call arrivals and the ratio between these two types of arrivals. At last, we apply our new model to some simple mobility scenarios and compute the resultant active user's location densities. © 2003 IEEE  

E-learning environments are being used more efficiently by the rapid growth in internet and multimedia technologies. Adaptive learning is a kind of learning environment which provides individual learning. It can customize the learning style according to the individual's personality and characteristics. Although there are a lot of e-learning systems having adaptive learning feature, they do not satisfy all adaptive learning aspects. This paper proposes a new method which tries to help learners find educational contents adapted to their personalities in an efficient manner. Our proposed method has four essential parts: 1) It finds out learner's features by Bayesian networks. 2) Then It tries... 

Ambient Intelligence is the future of computing where devices predict what users need and help them carry out their everyday life activities easier. To make this prediction possible these environments should be aware of the context. Activity recognition is one of the most complex problems in context-aware environments. In this paper we propose a layered Dynamic Bayesian Network (DBN) to recognize activities in an oral presentation. The layered architecture gives us the opportunity to recognize complex activities using the classification results of sensory data in the first layer regardless of the physical environment. Our model is event-driven meaning the classification takes place only when...