Our purpose is to ensure that people and institutions better manage information through digital libraries (DLs). Thus we address a fundamental human and social need, which is particularly urgent in the modern Information ...

This paper documents the domain engineering process for much of the conflation algorithms domain. Empirical data on the process and products of domain engineering were collected. Six conflation algorithms of four different ...

Robust design optimization (RDO) uses statistical decision theory and optimization techniques to optimize a design over a range of uncertainty (introduced by the manufacturing process and unintended uses). Since engineering ...

We consider the problem of reducing a potentially very large dataset to a subset of representative prototypes. Rather than searching over the entire space of prototypes, we first roughly divide the data into balanced ...

Locally linear classification by pairwise coupling addresses a nonlinear classification problem by three basic phases: decompose the classes of complex concepts into linearly separable subclasses, learn a linear classifier ...

A partial order or poset P = (X,<) on a (finite) base set X determines the set L(P) of linear extensions of P. The problem of computing, for a poset P, the cardinality of L(P) is #P-complete. A set {P1, P2, . . . , Pk} of ...

There has been much research on the combinatorial problem of generating the linear extensions of a given poset. This paper focuses on the reverse of that problem, where the input is a set of linear orders, and the goal is ...

In this paper, we present an analytical model that characterizes TCP NewReno's goodput as a function of round-trip time, average time duration between handoffs, average number of packets reordered during a handoff, and the ...

This paper is concerned with augmenting genetic algorithms (GAs) to include memory for continuous variables, and applying this to stacking sequence design of laminated sandwich composite panels that involves both discrete ...

This paper presents a novel parallelization and quantitative characterization of various optimization strategies for data-parallel computation on a graphics processing unit (GPU) using NVIDIA's new GPU programming framework, ...