Dynamic Bayesian networks (DBNs) are a powerful and exible methodology for representing and computing with probabilistic models of stochastic processes. In the past decade, there has been increasing interest in applying them to practical problems, and this thesis shows that they can be used eeectively in the eld of automatic speech recognition. A principle characteristic of dynamic Bayesian net...

state estimation is the foundation of any control and decision making in power networks. the first requirement for a secure network is a precise and safe state estimator in order to make decisions based on accurate knowledge of the network status. this paper introduces a new estimator which is able to detect bad data with few calculations without need for repetitions and estimation residual cal...

triple helix model (th) collaborations involving university, industry and government provide a networked infrastructure for shaping the dynamic fluxes of knowledge base of innovations locally and these fluxes remain emergent within the domains. in this article first the knowledge-based economy, national system of innovation, and three models of uig relations which represent different triple hel...

Mobile ad hoc Network (MANET) has a challenging task because of the dynamic and infrastructure less nature of the network. This dynamic nature leads to the difficulty in handoff, addressing, routing and data delivering process. For getting good QoS, better flexibility, effective and efficient handoff process in this dynamic network need better handoff mechanism for avoiding any discontinuity, p...

Markov decision processes (MDPs) have proven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, state-based specifications and computations. To alleviate the combinatorial problems associated with such methods, we propose new representational and computational techniques for MDPs that exploit certain types of prob...

We propose a dynamic program to find the shortest path in a network having gamma probability distributions as arc lengths. Two operators of sum and comparison need to be adapted for the proposed dynamic program. Convolution approach is used to sum two gamma probability distributions being employed in the dynamic program.