18,749 research outputs found

    Linear-Space Data Structures for Range Mode Query in Arrays

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    A mode of a multiset SS is an element a∈Sa \in S of maximum multiplicity; that is, aa occurs at least as frequently as any other element in SS. Given a list A[1:n]A[1:n] of nn items, we consider the problem of constructing a data structure that efficiently answers range mode queries on AA. Each query consists of an input pair of indices (i,j)(i, j) for which a mode of A[i:j]A[i:j] must be returned. We present an O(n2−2ϵ)O(n^{2-2\epsilon})-space static data structure that supports range mode queries in O(nϵ)O(n^\epsilon) time in the worst case, for any fixed ϵ∈[0,1/2]\epsilon \in [0,1/2]. When ϵ=1/2\epsilon = 1/2, this corresponds to the first linear-space data structure to guarantee O(n)O(\sqrt{n}) query time. We then describe three additional linear-space data structures that provide O(k)O(k), O(m)O(m), and O(∣j−i∣)O(|j-i|) query time, respectively, where kk denotes the number of distinct elements in AA and mm denotes the frequency of the mode of AA. Finally, we examine generalizing our data structures to higher dimensions.Comment: 13 pages, 2 figure

    Integration of geometric modeling and advanced finite element preprocessing

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    The structure to a geometry based finite element preprocessing system is presented. The key features of the system are the use of geometric operators to support all geometric calculations required for analysis model generation, and the use of a hierarchic boundary based data structure for the major data sets within the system. The approach presented can support the finite element modeling procedures used today as well as the fully automated procedures under development

    Digital Image Access & Retrieval

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    The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio
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