Thomas R. Gardos

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We describe an approach to modeling diagnostic problems that is based on a passive observation of a diagnostician’s work-flow and recording their findings and final diagnosis, from which the model can be modified directly, or improved by learning from cases so acquired. While the probabilistic model of a system under diagnosis is necessarily simplified,(More)
Today’s Information Technology (IT) organizations face significant challenges in delivering business value in these times of rapid architectural evolution as well as challenges in their ability to manage, provision, trust, and integrate the various elements of IT systems. An important aspect of these challenges is the impact IT has on the user and the(More)
Formal diagnostic methods are emerging from the machine-learning research community and beginning to find application in Intel. In this paper we give an overview of these methods and the potential they show for improving diagnostic procedures in operational environments. We present an historical overview of Bayes networks and discuss how they can be applied(More)
In this paper we discuss the implementation of receiver-driven rate adaptation using multicast and SNR scalability as supported by Version 2 of ITU-T Recommendation H.263 -Video Coding for Low Bit Rate Communication. We compare the layered bit stream approach to receiver-driven rate adaptivity to the approach using multiple independent bit streams. We show(More)
Communication is vital in any workplace. However, as workers become less tied to their desktops and computers, the need to provide them with a flexible, easy to use, mobile method of communication becomes more necessary. This is particularly true in "non-traditional" workplaces like factories or hospitals. Cell phones, PDA's, and walkie-talkies provide the(More)
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