been devoted to make theoretical predictions comparably accurate. Unfortunately, as far as D, 3 He and 7 Li are concerned, the theoretical uncertainty on their primordial abundances is greatly dominated by a poor knowledge of many nuclear reactions involved in their production. On the contrary, the 4

more accurate predictions. We argue that most problems to which supervised learning is currently applied are really prediction problems of the sort to which temporal-difference methods can be applied to advantage.

Because of the increasing gap between the data from sequencing and structural genomics, the accurate prediction of the structural class of a protein domain solely from the primary sequence has remained a challenging problem in structural biology. Traditional sequence-based predictors generally

are deployed, it is challenging and sometimes even impossible to change batteries. As a result, erroneous lifetime prediction causes high costs and may render a sensor network useless before its purpose is fulfilled. In this paper, we present AEON (Accurate Prediction of Power Consumption), a novel evaluation

simple, light-weight algorithm that assigns synthetic coordinates to hosts such that the distance between the coordinates of two hosts accurately predicts the communication latency between the hosts.

In this paper, we propose to use coordinates-based mechanisms in a peer-to-peer architecture to predict Internet network distance (i.e. round-trip propagation and transmission delay) . We study two mechanisms. The first is a previously proposed scheme, called the triangulated heuristic, which

This work proposes an accurate crosstalk noise estimation method in the presence of multiple RC lines for use in design automation tools. The method correctly models the loading effects of non switching aggressors and aggressor tree branches using resistive shielding effect and realistic

Recent studies have demonstrated that specificity is an im-portant characterization of texts potentially beneficial for a range of applications such as multi-document news summa-rization and analysis of science journalism. The feasibility of automatically predicting sentence specificity from a rich

We propose that sharp stability estimates are essential for evaluating the predictive capability of atomistic-to-continuum coupling methods up to the limit load for atomistic instabilities such as fracture, dislocation movement, or crack tip propagation. Using rigorous analysis, asymptotic methods

retransmit events. Our measurements demonstrate that our model is able to more accurately predict TCP throughput and is accurate over a wider range of loss rates. This material is based upon work supported by the National Science Foundation under grants NCR-95-08274, NCR-95-23807 and CDA-95-02639. Any