Support for exploratory interaction with databases in applications such as data mining requires that the first few results of an operation be available as quickly as possible. We study the algorithmic side of what can...
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ISBN:
(纸本)9781581136708
Support for exploratory interaction with databases in applications such as data mining requires that the first few results of an operation be available as quickly as possible. We study the algorithmic side of what can and what cannot be achieved for processing join operations. We develop strategies that modify the strict two-phase processing of the sort-merge paradigm, intermingling join steps with selected merge phases of the sort. We propose an algorithm that produces early join results for a broad class of join problems, including many not addressed well by hash-based algorithms. Our algorithm has no significant increase in the number of I/O operations needed to complete the join compared to standard sort-merge algorithms.
Weighted order statistic (WOS) filters are a generalization of the standard order statistic filters. Usually, they are characterized by a weight vector and a threshold value. Rather than considering individual filters...
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Weighted order statistic (WOS) filters are a generalization of the standard order statistic filters. Usually, they are characterized by a weight vector and a threshold value. Rather than considering individual filters, it is possible to consider the whole set of filters related to a given weight vector as a class of filters by allowing the threshold values vary from 0 to the sum of the weights. A major question is to find out if two weight vectors are equivalent or not as classes of filters. Some equivalent weight vectors as well as discussions on minimal collections of weight vectors are presented in this paper.
In this paper we present an efficient method for interpolating a piecewise-linear surface between two parallel slices, each consisting of an arbitrary number of (possibly nested) polygons that define 'material'...
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In this paper we present an efficient method for interpolating a piecewise-linear surface between two parallel slices, each consisting of an arbitrary number of (possibly nested) polygons that define 'material' and 'nonmaterial' regions. This problem has applications to medical imaging, geographic information systems, etc. Our method is fully automatic and is guaranteed to produce non-self-intersecting surfaces in all cases regardless of the number of contours in each slice, their complexity and geometry, and the depth of their hierarchy of nesting. The method is based on computing cells in the overlay of the slices, that form the symmetric difference between them. Then, the straight skeletons of the selected cells guide the triangulation of these cells. Finally, the resulting triangles are lifted up in space to form an interpolating surface. We provide some experimental results on various complex examples to show the good and robust performance of our algorithm.
Human perception is a complex nonlinear dynamics. On the one hand it is periodic dynamics and on the other hand it is chaotic. Thus, we wish to propose a hybrid - the spatial chaotic dynamics for the associative recal...
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Human perception is a complex nonlinear dynamics. On the one hand it is periodic dynamics and on the other hand it is chaotic. Thus, we wish to propose a hybrid - the spatial chaotic dynamics for the associative recall to retrieve patterns, similar to Walter Freeman's discovery, and the fixed point dynamics for memory storage, similar to Hopfield and Grossberg's discoveries. In this model, each neuron in the network could be a chaotic map, whose phase space is divided into two states: one is periodic dynamic state with period-V, which is used to represent a V-value retrieved pattern;another is chaotic dynamic state. Firstly, patterns are stored in the memory by fixed point learning algorithm. In the retrieving process, all neurons are initially set in the chaotic region. Due to the ergodicity property of chaos, each neuron will approximate the periodic points covered by the chaotic attractor at same inst.nts. When this occurs, the control is activated to drive the dynamic of each neuron to their corresponding stable periodic point. computer simulations confirm the theoretical prediction.
We present an efficient exponentiation algorithm in a finite field GF(qn) using a Gauss period of type (n, 1). Though the Gauss period α of type (n, 1) in GF(qn) is never primitive, a computational evidence says that...
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We present a fast and compact hardware architecture of exponentiation in a finite field GF(2n) determined by a Gauss period of type (n, k) with k ≥ 2. Our construction is based on the ideas of Gao et al. and on the c...
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This paper proposes a new arithmetic unit (AU) in GF(2m) for reconfigurable hardware implementation such as FPGAs, which overcomes the wellknown drawback of reduced flexibility that is associated with traditional ASIC...
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We construct a black box graph traversal problem that can be solved exponentially faster on a quantum computer than on a classical computer. The quantum algorithm is based on a continuous time quantum walk, and thus e...
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We construct a black box graph traversal problem that can be solved exponentially faster on a quantum computer than on a classical computer. The quantum algorithm is based on a continuous time quantum walk, and thus employs a different technique from previous quantum algorithms based on quantum Fourier transforms. We show how to implement the quantum walk efficiently in our black box setting. We then show how this quantum walk solves our problem by rapidly traversing a graph. Finally, we prove that no classical algorithm can solve the problem in subexponential time.
Let P be a set of n points in 3, not all of which are in a plane and no three on a line. We partially answer a question of Scott (1970) by showing that the connecting lines of P assume at least 2n -3 different directi...
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Let P be a set of n points in 3, not all of which are in a plane and no three on a line. We partially answer a question of Scott (1970) by showing that the connecting lines of P assume at least 2n -3 different directions if n is even and at least 2n - 2 if n is odd. These bounds are sharp. The proof is based on a far-reaching generalization of Ungar's theorem concerning the analogous problem in the plane.
In our paper [RM02a] we describe an approach to weak bisimulation for coalgebras and show that parts of the theory of universal coalgebra (with strong bisimulation) can be obtained when considering coalgebras with wea...
In our paper [RM02a] we describe an approach to weak bisimulation for coalgebras and show that parts of the theory of universal coalgebra (with strong bisimulation) can be obtained when considering coalgebras with weak bisimulations and weak homomorphisms. In the present paper we focus on uniformly adapting modal logics that characterise strong bisimulation for coalgebras to several kinds of observation equivalences.
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