This paper proposes a new method for finding principal curves from complex distribution dataset. Motivated by solving the problem, which is that existing methods did not perform well on finding principal curve in comp...
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ISBN:
(数字)9783642162480
ISBN:
(纸本)9783642162473
This paper proposes a new method for finding principal curves from complex distribution dataset. Motivated by solving the problem, which is that existing methods did not perform well on finding principal curve in complex distribution dataset with high curvature, high dispersion and self-intersecting, such as spiral-shaped curves, Firstly, rudimentary principal graph of data set is created based on the thinning algorithm, and then the contiguous vertices are merged. Finally the fitting-and-smoothing step introduced by Kegl is improved to optimize the principal graph, and Kegl's restructuring step is used to rectify imperfections of principal graph. Experimental results indicate the effectiveness of the proposed method on finding principal curves in complex distribution dataset.
Passive sensor networks can achieve accurate detection of target under complex environment. In order to adapt to different communication demands of sensor networks in different environments, this paper designed and im...
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Indentification of informative gene subsets responsible for discerning between available samples of gene expression data is an important task in bioinformatics. Reducts, from rough sets theory, corresponding to a mini...
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service-oriented computing is a new software development paradigm that allows application developers to select available services from the Internet and to form new web services. A main problem is how to efficiently de...
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This paper deals with the problem of task allocation (i.e,;to which processor should each task of an application be assigned) in heterogeneous distributed computingsystems with the goal of maximizing the system relia...
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In this paper, we proposed a novel network coding method called local-directed network coding to improve the throughput of the vehicular ad-hoc network. Different from other vehicular network coding methods, we consid...
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In this paper, we proposed a novel network coding method called local-directed network coding to improve the throughput of the vehicular ad-hoc network. Different from other vehicular network coding methods, we consider the direction of packet transmission. In detail, the intermediate node selects one main packet and some sub-packets from forwards and backwards sending queues, and then encodes these packets into one packet to broadcast. Simulation results show that our approach can efficiently improve the throughput of application layer in vehicular networks.
Hybrid sensor network technology is a key component of future ITS applications. In this paper, we propose a hybrid architecture that combined VANETs and roadside WSNs for intelligent navigation. Different from traditi...
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Hybrid sensor network technology is a key component of future ITS applications. In this paper, we propose a hybrid architecture that combined VANETs and roadside WSNs for intelligent navigation. Different from traditional ITS application, Sensors in WSNs and VANETs are used to perceive and exchange roadside and vehicular information to support the intelligent navigating decision process. We firstly give the system and protocol architecture, and then we discuss the scenarios and use cases of our system in intelligent navigation. After that, we describe the software and hardware implementation of our prototype, conduct a simulation on the discussed scenarios, and present a detailed data communication experimental result to prove the feasibility of our prototype.
Statistical background subtraction has proved to be a robust and effective approach for segmenting and extracting objects without any prior information of the foreground objects. This paper presents two contributions ...
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Statistical background subtraction has proved to be a robust and effective approach for segmenting and extracting objects without any prior information of the foreground objects. This paper presents two contributions on this topic. The first contribution of this paper proposes a novel approach which introduces the motion mask into the Gaussian Mixture Models to reduce the errors of classical GMMs, which always classifies the moving objects as background incorrectly, and affects the accuracy of the steps followed by, when the objects are still in long periods. The second contribution regards the connected component labeling based on the contour tracking algorithm. Experimental results validate the effectiveness of the proposed approach.
Skyline query processing has recently received a lot of attention in database *** a set of multi-dimensional objects,the skyline query finds the objects that are not dominated by *** the best of our knowledge,the exis...
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Skyline query processing has recently received a lot of attention in database *** a set of multi-dimensional objects,the skyline query finds the objects that are not dominated by *** the best of our knowledge,the existing researches mainly focus on how to efficiently return the whole skyline ***,as the cardinality and dimensionality of input dataset increase,the number of skylines grows exponentially,and hence this "huge" skyline set is completely useless to *** by the above fact,in this paper,we present a novel type of l-SkyDiv query,which only returns l skylines having maximum diversity,to improve the usefulness of skyline ***,we prove that the l-SkyDiv query belongs to the NP-Hard problem theoretically,and propose three efficient heuristic algorithms whose time complexities are polynomial to fast implement the proposed ***,we present detailed theoretical analyses and extensive experiments,demonstrating that our algorithms are both efficient and effective.
Oriented to the goal of high-quality banking softwares, trustworthiness is emerging to be important property. This paper studies how to apply formal methods into the trustworthy property preservation of evolutionary c...
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