Estimation of the dynamic error components model is considered using two alternative linear estimators that are designed to improve the properties of the standard firstdifferenced GMM estimator. Both estimators require restrictions on the initial conditions process. Asymptotic efficiency

of data assimilation and predictability. It incorporates all aspects of environmental computer modeling including an historical overview of NWP, equations of motion and their approximations, a modern description of the methods to determine the initial conditions using weather observations and a clear

Clustering data by identifying a subset of representative examples is important for processing sensory signals and detecting patterns in data. Such “exemplars ” can be found by randomly choosing an initial subset of data points and then iteratively refining it, but this works well only

obtain separation results showing the increased value of interactive sanitization mechanisms over non-interactive. 1 Introduction We continue a line of research initiated in [10, 11] on privacy in statistical data-bases. A statistic is a quantity computed from a sample. Intuitively, if the database is a

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vacuum equations with small initial data: (I)

Initial data are the starting point for any numerical simulation. In the case of numerical relativity, Einstein’s equations constrain our choices of these initial data. We will examine several of the formalisms used for specifying Cauchy initial data in the 3+1 decomposition of Einstein’s equations

-randomness in the movement of nodes and exploit such non-randomness to help deliver data. We study two variations of MF, depending on whether ferries or nodes initiate proactive movement. The MF design exploits mobility to improve data delivery performance and reduce energy consumption in nodes. We evaluate the performance

to the design of a data grid, namely, storage systems and metadata management. Next, we explain how these services can be used to develop higher-level services for replica management and replica selection. We conclude by describing our initial implementation of data grid functionality.

Relevance feedback is an automatic process, introduced over 20 years ago, designed to produce improved query formulations following an initial retrieval operation. The principal relevance feedback methods described over the years are examined briefly, and evaluation data are included to demonstrate