A numerical model has been developed to analyze and optimize the run-time performance of a disk drive spindle motor. A field-circuit coupled time-stepping finite element method is used for the analysis of the motor op...
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A strong demand for quality of service (QoS) to subscribers of VPNs has emerged. Weighted proportional fair rate allocation (WPFRA) provides a QoS method for one VPN model, the customer-pipe model. However, constructi...
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A strong demand for quality of service (QoS) to subscribers of VPNs has emerged. Weighted proportional fair rate allocation (WPFRA) provides a QoS method for one VPN model, the customer-pipe model. However, constructing large-scale VPNs with the customer-pipe model is difficult because of an exponential increase in required bandwidth. In future VPNs, a new model, the hose model, is useful to improve the scalability. We present an adaptive bandwidth allocation method for providing QoS in the hose model. Our method is evaluated quantitatively through simulations.
Moving point object data can be analyzed through the discovery of patterns. We consider the computational efficiency of detecting four such spatio-temporal patterns, namely flock, leadership, convergence, and encounte...
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Moving point object data can be analyzed through the discovery of patterns. We consider the computational efficiency of detecting four such spatio-temporal patterns, namely flock, leadership, convergence, and encounter, as defined by Laube et al., 2004. These patterns are large enough subgroups of the moving point objects that exhibit similar movement in the sense of direction, heading for the same location, and/or proximity. By the use of techniques from computational geometry, including approximation algorithms, we improve the running time bounds of existing algorithms to detect these patterns. Copyright 2004 ACM.
We introduce TLHaar, an n-bit to n-bit reversible trans-form similar to the S-transform, TLHaar uses lookup tables that approximate the S-transform, but reorder the co-efficients so they fit into n bits. TLHaar is sui...
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We introduce TLHaar, an n-bit to n-bit reversible trans-form similar to the S-transform, TLHaar uses lookup tables that approximate the S-transform, but reorder the co-efficients so they fit into n bits. TLHaar is suited for loss-less compression in fixed-width channels, such as digital video channels and graphics hardware frame buffers. Tests indicate that when the incoming image data has lines or hard edges TLHaar coefficients compress better than S-transform coefficients. For other types of image data TL-Haar coefficients compress up to 2.5% worse than those of the S-transform, depending on the data and the compression method used.
We introduce the piecewise-linear Haar (PLHaar) transform, a reversible n-bit to n-bit transform that is based on the Haar wavelet transform. PLHaar is continuous, while all current n-bit to n-bit methods are not, and...
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We introduce the piecewise-linear Haar (PLHaar) transform, a reversible n-bit to n-bit transform that is based on the Haar wavelet transform. PLHaar is continuous, while all current n-bit to n-bit methods are not, and is therefore uniquely usable with both lossy and lossless methods (e.g. image compression). PLHaar has both integer and continuous (i.e. non-discrete) forms. By keeping the coefficients to n bits PLHaar is particularly suited for use in hardware environments where channel width is limited, such as digital video channels and graphics hardware.
The complementary relationship between familiarity and SNR in word intelligibility test is discussed. A regression plane was calculated to examine the complementary relationship between the two. A logistic regression ...
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The complementary relationship between familiarity and SNR in word intelligibility test is discussed. A regression plane was calculated to examine the complementary relationship between the two. A logistic regression model was fitted to the data. Word intelligibility and correlation of determination were found. Results show that a difference of 1.0 in the familiarity value is almost equivalent to a 2 dB difference of SNR.
This article is a short supplement to our previously published paper, in which we proved that each semialgebraic set can be represented as a projection of a solution set of some system of interval linear equations wit...
This article is a short supplement to our previously published paper, in which we proved that each semialgebraic set can be represented as a projection of a solution set of some system of interval linear equations with dependent coefficients. The new result says that interval occurring can be chosen as narrow as wanted. The new result is proved by a simple linear transformation.
The Beowulf class of parallel computing machine started as a small research project at NASA Goddard Space Flight Center's Center of Excellence in Space data and informationsciences (CESDIS). From that work evolve...
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This paper surveys various complexity results on different forms of logic programming. The main focus is on decidable forms of logic programming, in particular propositional logic programming and datalog, but we also ...
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This paper surveys various complexity results on different forms of logic programming. The main focus is on decidable forms of logic programming, in particular propositional logic programming and datalog, but we also mention general logic programming with function symbols. Next to classical results on plain logic programming (pure Horn clause programs), more recent results on various important extensions of logic programming are surveyed. These include logic programming with different forms of negation, disjunctive logic programming, logic programming with equality, and constraint logic programming. The complexity of the unification problem is also addressed.
We present a fairly general method for finding deterministic constructions obeying what we call k-restrictions; this yields structures of size not much larger than the probabilistic bound. The structures constructed b...
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We present a fairly general method for finding deterministic constructions obeying what we call k-restrictions; this yields structures of size not much larger than the probabilistic bound. The structures constructed by our method include (n,k)-universal sets (a collection of binary vectors of length n such that for any subset of size k of the indices, all 2/sup k/ configurations appear) and families of perfect hash functions. The near-optimal constructions of these objects imply the very efficient derandomization of algorithms in learning, of fixed-subgraph finding algorithms, and of near optimal /spl Sigma/II/spl Sigma/ threshold formulae. In addition, they derandomize the reduction showing the hardness of approximation of set cover. They also yield deterministic constructions for a local-coloring protocol, and for exhaustive testing of circuits.
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