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Parallelization of the Discrete Wavelet Transform (DWT) oriented to linear algebra applications, specially the solution of large linear systems, is studied in this paper. We propose that for parallel applications using linear algebra and wavelets, it can be advantageous to use directly the two-dimensional block cyclic distribution (2DBC), used in ScaLAPACK [1]. Although the parallel computation of...
At present, qualitative spatial reasoning has become the hot issues in many research fields. The most popular models of spatial topological relations are Region Connection Calculus (RCC) and 9-inter-section model. However, there are few contributions on topological relations of concave regions in which the representative model is Cohn’s RCC23. There are some limitations of RCC23 especially in practical...
Traditionally in speech emotion recognition, feature selection(FS) is implemented by considering the features from all classes jointly. In this paper, a hybrid system based on all-class FS and pairwise-class FS is proposed to improve speech emotion classification performance. Besides a subset of features obtained from an all-class structure, FS is performed on the available data from each pair of...
This paper presents a knowledge-based kernel classification model for binary classification of sets or objects with prior knowledge. The prior knowledge is in the form of multiple polyhedral sets belonging to one or two classes, and it is introduced as additional constraints into a regularized knowledge-based optimization problem. The resulting formulation leads to a least squares problem that can...
The method of the convective heat transfer coefficient identification in a three-phase inverse design Stefan problem is presented in this paper. The convective heat transfer coefficient will be sought in the form of a continuous function, non-linearly dependent on the parameters sought. A genetic algorithm was used to determine these parameters. The direct Stefan problem was solved via a generalized...
Clustering algorithms incorporated with prior knowledge have been widely studied and many nice results were shown in recent years. However, most existing algorithms implicitly assume that the prior information is complete, typically specified in the form of labeled objects with each category. These methods decay and behave unstably when the labeled classes are incomplete. In this paper a new type...
By the development of Semantic Web, increasing demands for vague and distributed information representation have triggered a mass of theoretical and applied researches of fuzzy and distributed ontologies, whose main logical infrastructures are fuzzy and distributed description logics. However, current solutions are proposed respectively on one of these two aspects. By integrating -connection...
In this paper we present an effective pattern similarity match algorithm for multidimensional sequence data sets such as video streams and various analog or digital signals. To approximate a sequence of data points we introduce a trend vector that captures the moving trend of the sequence. Using the trend vector, our method is designed to filter out irrelevant sequences from a database and to find...
The computing power and programmability of graphics processing units (GPUs) has been successfully exploited for calculations unrelated to graphics, such as data processing, numerical algorithms, and secret key cryptography. In this paper, a new variant of the Montgomery exponentiation algorithm that exploits the processing power and parallelism of GPUs is designed and implemented. Furthermore, performance...
Hierarchical ( )-matrices approximate full or sparse matrices using a hierarchical data sparse format. The corresponding -matrix arithmetic reduces the time complexity of the approximate -matrix operators to almost optimal while maintains certain accuracy. In this paper, we represent a scheme to solve the saddle point system arising from the control of...
The Evolutionary Geometric Near-neighbor Access Tree (EGNAT) is a recently proposed data structure that is suitable for indexing large collections of complex objects. It allows searching for similar objects represented in metric spaces. The sequential EGNAT has been shown to achieve good performance in high-dimensional metric spaces with properties (not found in others of the same kind) of allowing...
In this paper, an efficient algorithm and its parallelization to compute PageRank are proposed. There are existing algorithms to perform such tasks. However, some algorithms exclude dangling nodes which are an important part and carry important information of the web graph. In this work, we consider dangling nodes as regular web pages without changing the web graph structure and therefore fully preserve...
To accelerate the query performance, diverse continuous que- ry index schemes have been proposed for stream data processing systems. In general, a stream query contains the range condition. Thus, by using range conditions, the queries are indexed. In this paper, we propose an efficient range query index scheme QUISIS using a modified Interval Skip Lists to accelerate search time. QUISIS utilizes a...
With the rapidly increasing popularity of XML as a data format, there is a large demand for efficient techniques in structural matching of XML data. We propose a novel filtering technique to speed up the structural matching of XML data, which is based on an auxiliary data structure called suffix bitmap. The suffix bitmap captures in a packed format the suffix tag name list of the nodes in an XML document...
Querying on XML data is a computational-expensive process due to the complex nature of both the XML data and the query. In this paper, we propose an approach to expedite XML query processing by caching the results of a specific class of queries, namely the maximal frequent queries. We mine the maximal frequent query patterns from user-issued queries and cache the results of such queries. We propose...
In this paper, we discuss the main problems of inductive query languages and optimisation issues. We present a logic-based inductive query language and illustrate the use of aggregates and exploit a new join operator to model specific data mining tasks. We show how a fixpoint operator works for association rule mining and a clustering method. A preliminary experimental result shows that fixpoint operator...
Quantum-behaved particle swarm optimization (QPSO) is employed to deal with multiprocessor scheduling problem (MSP), which speeds the convergence and has few parameters to control. We combine the QPSO search technique with list scheduling to improve the solution quality in short time. At the same time, we produce the solution based on the problem-space heuristic. Several benchmark instances are tested...
Optimized event-driven particle collision simulation is on demand to study the behavior of systems consisted of moving objects. This paper discusses the design and implementation issues of such simulation systems with various optimizations such as discrete event handling, Lazy Determination Strategy (LDS), and optimal cell number/size selection to overcome the delay caused by dynamical dependencies...
Based on the previously introduced Quantum-behaved Particle Swarm Optimization (QPSO), a revised QPSO with Gaussian disturbance on the mean best position of the swarm is proposed. The reason for the introduction of this novel method is that the disturbance can effectively prevent the stagnation of the particles and therefore make them escape the local optima and sub-optima more easily. Before proposing...
We evaluate the effectiveness of neural networks as a tool for predicting whether a particular combination of preconditioner and iterative method will correctly solve a given sparse linear system Ax = b. We consider several scenarios corresponding to different assumptions about the relationship between the systems used to train the neural network and those for which the neural network is expected...
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