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This paper addresses the problem of tracking and diagnosing complex systems with mixtures of discrete and continuous variables. This problem is a difficult one, particularly when the system dynamics are nondeterministic, not all aspects of the system are directly observed, and the sensors are subject to noise. In this paper, we propose a new approach to(More)
An important subclass of hybrid Bayesian networks are those that represent Conditional Linear Gaussian (CLG) distributions-a distribution with a multivari­ ate Gaussian component for each instantiation of the discrete variables. In this paper we explore the prob­ lem of inference in CLGs, and provide complexity re­ sults for an important class of CLGs,(More)
In this paper we present a comprehensive ythrough system which generates photo-realistic images in true real-time. The high performance is due to an innovative rendering algorithm based on a discrete ray casting approach, accelerated by ray coherence and multiresolu-tion traversal. The terrain as well as the 3D objects are represented by a textured mapped(More)
Many real life domains contain a mixture of discrete and continuous variables and can be modeled as hybrid Bayesian Networks (BNs). An important sub-class of hybrid BNs are conditional linear Gaussian (CLG) networks, where the conditional distribution of the continuous variables given an assignment to the discrete variables is a multivariate Gaussian.(More)
We present a methodology and a formal toolset for verifying fault-tolerant systems, based upon the temporal veriication system STeP. Our test case is the modeling and veriication of a parameterized fault-tolerant leader-election algorithm recently proposed in 9]. Our methods settle the general N-process correctness for the algorithm, which had been(More)
The Reverse Water Gas Shift system (RWGS) is a complex physical system designed to produce oxygen from the carbon dioxide atmosphere on Mars. If sent to Mars, it would operate without human supervision , thus requiring a reliable automated system for monitoring and control. The RWGS presents many challenges typical of real-world systems, including: noisy(More)
The clique tree algorithm is the standard method for doing inference in Bayesian networks. It works by manipulating clique potentials — distributions over the variables in a clique. While this approach works well for many networks, it is limited by the need to maintain an exact representation of the clique potentials. This paper presents a new unified(More)
Air pollution has a proven impact on public health. Currently, pollutant levels are obtained by high-priced, sizeable, stationary Air Quality Monitoring (AQM) stations. Recent developments in sensory and communication technologies have made relatively low-cost, micro-sensing units (MSUs) feasible. Their lower power consumption and small size enable mobile(More)