One of interesting hardware solutions proposed to solve the packet classification problem is bit-vector algorithm. Different from other hardware solutions such as ternary CAM, it efficiently utilizes the memories to a...
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ISBN:
(纸本)0780385497
One of interesting hardware solutions proposed to solve the packet classification problem is bit-vector algorithm. Different from other hardware solutions such as ternary CAM, it efficiently utilizes the memories to achieve an excellent performance in medium size policy database;however, it cannot scale up with the policy number increases. In this paper, we proposed an improved bit-vector algorithm named Bit Vector Condensation which can be adapted to large policy databases. Experiments showed that our proposed algorithm drastically improves in the storage requirements and search speed as comp.red to the original algorithm.
MIDAS provides an autonomous delivery management system from client orders to the electronic proof of delivery for the Australian transport industry. To accomp.ish this, MIDAS utilises different technologies, includin...
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MIDAS provides an autonomous delivery management system from client orders to the electronic proof of delivery for the Australian transport industry. To accomp.ish this, MIDAS utilises different technologies, including global positioning system (GPS), wireless technologies (short message service (SMS)/wireless application protocol (WAP)) and the internet. MIDAS overcomes the issue of optimal routing and scheduling and mobile communication within the integrated Australian transport industry. MIDAS supports both static and dynamic scheduling utilising wireless communication channels to keep drivers up-to-date with information in real time when they are off-site. MIDAS also benefits the clients of the transport comp.nies whose orders can be easily placed and traced anywhere, anytime. MIDAS is an advanced e-commerce solution to track and fulfil the orders throughout the entire supply chain.
A Sequential Projection Pursuit Model (SPPM) for unsupervised segmentation of the POLarimetric Synthetic Aperture Radar (POL-SAR) image is proposed in this paper. The features of the high dimension data are extracted ...
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ISBN:
(纸本)0780384075
A Sequential Projection Pursuit Model (SPPM) for unsupervised segmentation of the POLarimetric Synthetic Aperture Radar (POL-SAR) image is proposed in this paper. The features of the high dimension data are extracted out via orthogonal projection and the classification is accomp.ished by the Bayesian decision rule. Also the similarity parameters of POL-data are expressed as the characters of a target and form new target data. The SPPM utilizes new target data to classify the target into various subclasses. Good-segmented results have been obtained for the POL-SAR image processing. The segmented results using the SPPM are better than that of using entropyalpha plane.
This paper proposes a technique for identifying program properties that indicate errors. The technique generates machine learning models of program properties known to result from errors, and applies these models to p...
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This paper proposes a technique for identifying program properties that indicate errors. The technique generates machine learning models of program properties known to result from errors, and applies these models to program properties of user-written code to classify and rank properties that may lead the user to errors. Given a set of properties produced by the program analysis, the technique selects a subset of properties that are most likely to reveal an error. An implementation, the Fault Invariant Classifier, demonstrates the efficacy of the technique. The implementation uses dynamic invariant detection to generate program properties. It uses support vector machine and decision tree learning tools to classify those properties. In our experimental evaluation, the technique increases the relevance (the concentration of fault-revealing properties) by a factor of 50 on average for the C programs, and 4.8 for the Java programs. Preliminary experience suggests that most of the fault-revealing properties do lead a programmer to an error.
The author has proposed a new class of linear phase biorthogonal wavelet filterbanks called BNVF, whose synthesis low-pass filter has dyadic fraction coefficients, which is an attractive feature in the realization of ...
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The author has proposed a new class of linear phase biorthogonal wavelet filterbanks called BNVF, whose synthesis low-pass filter has dyadic fraction coefficients, which is an attractive feature in the realization of multiplication-free discrete wavelet transform. The method of constructing BNVF includes two steps. First is to determine the synthesis low-pass filter coefficients with minimal length, based on the perfect reconstruction condition, given the same degree of vanishing moments for synthesis scaling function and wavelet pair. Second is to determine the analysis low-pass filter coefficients to minimize the error of the reconstructed image after coding and decoding, subject to the linear phase condition. Three filterbanks in this family are verified to have comp.titive comp.ession potential and much lower comp.tational comp.exity to the CDF-9/7 by Cohen, Daubechies et al.
Several studies have demonstrated the effectiveness of the wavelet decomp.sition as a tool for reducing large amounts of data down to comp.ct wavelet synopses that can be used to obtain fast, accurate approximate answ...
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ISBN:
(纸本)9781581138580
Several studies have demonstrated the effectiveness of the wavelet decomp.sition as a tool for reducing large amounts of data down to comp.ct wavelet synopses that can be used to obtain fast, accurate approximate answers to user queries. While conventional wavelet synopses are based on greedily minimizing the overall root-mean-squared (i.e., L2-norm) error in the data approximation, recent work has demonstrated that such synopses can suffer from important problems, including severe bias and wide variance in the quality of the data reconstruction, and lack of non-trivial guarantees for individual approximate answers. As a result, probabilistic thresholding schemes have been recently proposed as a means of building wavelet synopses that try to probabilistically control other approximation-error metrics, such as the maximum relative error in data-value reconstruction, which is arguably the most important for approximate query answers and meaningful error guarantees. One of the main open problems posed by this earlier work is whether it is possible to design efficient deterministic wavelet-thresholding algorithms for minimizing non-L2 error metrics that are relevant to approximate query processing systems, such as maximum relative or maximum absolute error. Obviously, such algorithms can guarantee better wavelet synopses and avoid the pitfalls of probabilistic techniques (e.g., "bad" coin-flip sequences) leading to poor solutions. In this paper, we address this problem and propose novel, comp.tationally efficient schemes for deterministic wavelet thresholding with the objective of optimizing maximum-error metrics. We introduce an optimal low polynomial-time algorithm for one-dimensional wavelet thresholding - our algorithm is based on a new Dynamic-Programming (DP) formulation, and can be employed to minimize the maximum relative or absolute error in the data reconstruction. Unfortunately, directly extending our one-dimensional DP algorithm to multi-dimensional wavelets
Resolution in Optical Coherence Tomography is often degraded due to sidelobes of the point response. Frequently, the spectrum of the low-coherence source is unable to be changed to reduce sidelobes. We present a metho...
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Recently, China software industry has entered a rapid increasing phase and software comp.ny need to improve product quality under the pressure of market. Software Quality Management (SQM) is a very hot branch in Softw...
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Recently, China software industry has entered a rapid increasing phase and software comp.ny need to improve product quality under the pressure of market. Software Quality Management (SQM) is a very hot branch in Software Engineering. In this paper, the existing problems and reasons of small and medium sized software comp.ny are analyzed. Three key problems are presented on SQM, and the responding relationship of three key points, quality management and software process is discussed. Small and medium sized software comp.ny can continuously improve SQM and product quality by resolving these three key problems step by step.
Recently, Kuwakado and Tanaka proposed a transitive signature scheme for directed trees. In this letter, we show that Kuwakado-Tanaka scheme is insecure against.a forgery attack, in which an attacker is able to forge ...
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Recently, Kuwakado and Tanaka proposed a transitive signature scheme for directed trees. In this letter, we show that Kuwakado-Tanaka scheme is insecure against.a forgery attack, in which an attacker is able to forge edge signatures by comp.sing edge signatures provided by a signer.
In this article three interesting special topics of pervasive comp.ting as treated within the conference PERVASIVE 2004 are described. The set of topics consists of the recognition of activities, reliability and secur...
In this article three interesting special topics of pervasive comp.ting as treated within the conference PERVASIVE 2004 are described. The set of topics consists of the recognition of activities, reliability and security of wireless technology and innovative interfaces, which together define key technologies for pervasive comp.ting. The goal of this article is to provide a short introduction to typical problems of these fields, together with new solutions as described at the conference.
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