Michael Brown

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This paper presents an extensive study of the software implementation on workstations of the NIST-recommended elliptic curves over prime fields. We present the results of our implementation in C and assembler on a Pentium II 400 MHz workstation. We also provide a comparison with the NIST-recommended curves over binary fields.
We present a method for condensing the information in multiple alignments of proteins into a mixture of Dirichlet densities over amino acid distributions. Dirichlet mixture densities are designed to be combined with observed amino acid frequencies to form estimates of expected amino acid probabilities at each position in a profile, hidden Markov model or(More)
The Air Travel Information System (ATIS) domain serves as the common evaluation task for ARPA"spoken language system developers. 1 To support this task, the Multi-Site ATIS Data COllection Working group (MADCOW) coordinates data collection activities. This paper describes recent MADCOW activities. In particular, this paper describes the migration of the(More)
A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein family or the columns of a multiple alignment of that family is introduced. This method uses Dirichlet mixture densities as priors over amino acid distributions. These mixture densities are determined from examination of previously(More)
The market for Personal Digital Assistants (PDAs) is growing at a rapid pace. An increasing number of products, such as the PalmPilot, are adding wireless communications capabilities. PDA users are now able to send and receive email just as they would from their networked desktop machines. Because of the inherent insecurity of wireless environments, a(More)
The modeling of power and thermal behavior of processors requires challenging validation processes, which may be complex and undependable. In order to ameliorate some of the difficulties associated with the validation of power and thermal models, this paper describes an infrared measurement setup that simultaneously captures run-time power consumption,(More)
Stochastic context-free grammars (SCFGs) can be applied to the problems of folding, aligning and modeling families of homologous RNA sequences. SCFGs capture the sequences' common primary and secondary structure and generalize the hidden Markov models (HMMs) used in related work on protein and DNA. This paper discusses our new algorithm, Tree-Grammar EM,(More)
We present a method for condensing the information in multiple alignments of proteins into a mixture of Dirichlet densities over amino acid distributions. Dirichlet mixture densities are designed to be combined with observed amino acid frequencies to form estimates of expected amino acid probabilities at each position in a pro le, hidden Markov model, or(More)