In wireless ad hoe networks, network partition, a large-scale topology change, would occur unexpectedly and disrupt the on-going routing paths as well as application connections. By observing the group mobility patter...
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ISBN:
(纸本)0780379543
In wireless ad hoe networks, network partition, a large-scale topology change, would occur unexpectedly and disrupt the on-going routing paths as well as application connections. By observing the group mobility patterns that are aggregated from the movement of mobile nodes, the prospective network partitioning can be predicted and therefore we can reduce the amount of disruptions. In this paper, we proposed a group mobility model that uses mobility parameters, such as distance, velocity and acceleration for network partition prediction. We then demonstrate how to predict network partition with these parameters, and illustrate how to apply the prediction to routing protocols. We also propose a group-id based clustering algorithm, which exactly determines the mobility groups as well as elects the clusterheads.
Word sense and word dependency benefit many *** constructed lexicon usually serves as a source for word sense and word ***,there always requires very expensive work and extensive time consumption to compile it,simulta...
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ISBN:
(纸本)0780379020
Word sense and word dependency benefit many *** constructed lexicon usually serves as a source for word sense and word ***,there always requires very expensive work and extensive time consumption to compile it,simultaneously senses and relationships among words in these kinds of lexica are always *** compilied lexica are under developing,the main obstacle is to discover multi-senses and multi-dependencies among words. In this paper,we propose a new method combining an improved ISODATA clustering algorithm with Association Rule mining to answer the question. With the recursively clustering algorithm lower frequency senses are *** well a approach for refinement is put forward to improve the *** indicate that the approach presented here provides preferable outputs.
A variety of techniques and tools exist to parallelize software systems on different parallel architectures (SIMD, MIMD). With the advances in high-speed networks, there has been a dramatic increase in the number of c...
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A variety of techniques and tools exist to parallelize software systems on different parallel architectures (SIMD, MIMD). With the advances in high-speed networks, there has been a dramatic increase in the number of client/server applications. A variety of client/server applications are deployed today, ranging from simple telnet sessions to complex electronic commerce transactions. Industry standard protocols. like Secure Socket Layer (SSL), Secure Electronic Transaction (SET), etc., are in use for ensuring privacy and integrity of data, as well as for authenticating the sender and the receiver during message passing. Consequently, a majority of applications using parallel processing techniques are becoming synchronization-centric, i.e., for every message transfer, the sender and receiver must synchronize. However, more effective techniques and tools are needed to automate the clustering of such synchronization-centric applications to extract parallelism. In this paper, we present a new clustering algorithm to facilitate the parallelization of software systems in a multiprocessors environment. The new clustering algorithm achieves traditional clustening objectives (reduction in parallel execution time, communication cost, etc.). Additionally, our approach 1) reduces the performance degradation caused by synchronizations, and 2) avoids deadlocks during clustering. The effectiveness of our approach is depicted with the help of simulation results.
We present a new face detection algorithm based on a first-order reduced Coulomb energy (RCE) classifier. The algorithm locates frontal views of human faces at any degree of rotation and scale in complex scenes. The f...
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We present a new face detection algorithm based on a first-order reduced Coulomb energy (RCE) classifier. The algorithm locates frontal views of human faces at any degree of rotation and scale in complex scenes. The face candidates and their orientations are first determined by computing the Hausdorff distance between simple face abstraction models and binary test windows in an image pyramid. Then, after normalizing the energy, each face candidate is verified by two subsequent classifiers: a binary image classifier and the first-order RCE classifier. While the binary image classifier is employed as a preclassifier to discard nonfaces with minimum computational complexity, the first-order RCE classifier is used as the main face classifier for final verification. An optimal training method to construct the representative face model database is also presented. Experimental results show that the proposed algorithm yields a high detection ratio while yielding no false alarm.
In this paper,we propose a cluster-based and brute-correcting grammatical rules learning method which is based on some conclusions of the cognitive ***,instances of grammatical category are mapped to graphic vectors a...
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ISBN:
(纸本)0780379020
In this paper,we propose a cluster-based and brute-correcting grammatical rules learning method which is based on some conclusions of the cognitive ***,instances of grammatical category are mapped to graphic vectors and distance between two vectors is *** set of vectors and the defined distance are proved to form a distance space. Next,this space is mapped to Euclidean space and a simple clustering algorithm is applied to acquire ***,grammatical rules are learned to describe the ***,brute-correcting progress helps to refine the *** describing the method we compare the brute-correcting progress with Eric Brill's transformation-based learning approach[E. Brill,1995]informally and present an application in Chinese named entity recognition.
Video information processing has been one of great challenging areas in the database community since it needs huge amount of storage space and processing power. In this paper. we investigate the problem of clustering ...
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Video information processing has been one of great challenging areas in the database community since it needs huge amount of storage space and processing power. In this paper. we investigate the problem of clustering large video data sets that are collections of video clips as foundational work for the subsequent processing such as video retrieval. A video clip, a sequence of video frames, is represented by a multidimensional data sequence, which is partitioned into video segments considering temporal relationship among frames, and then similar segments of the clip are grouped into Video clusters. We present the effective video segmentation and clustering algorithm which guarantees the clustering quality to such an extent that satisfies predefined conditions., and show its effectiveness via experiments on various video data sets. (C) 2002 Elsevier Science Inc. All rights reserved.
In medical visualization, multiple isosurfaces are usually extracted from medical volume image and used to represent (approximate) the boundary surfaces of different structures in the image. In this paper, we will dis...
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ISBN:
(纸本)0819444294
In medical visualization, multiple isosurfaces are usually extracted from medical volume image and used to represent (approximate) the boundary surfaces of different structures in the image. In this paper, we will discuss the approximating problem of the boundary surface (contained within volume image) by isosurface. It is quite common that a medical volume image can contain multiple interesting structures;we present a novel approach for the selection of multiple isosurfaces to approximate the boundary surfaces of these multiple structures. With this approach, the discrete sampling points of the gray values of the boundary surfaces within volume image are computed first. Then by identifying appropriate clusters from the discrete sampling points and computing the mean of each cluster, we can determine the corresponding isosurfaces for approximating these multiple boundary surfaces.
The main target of the present study is an objective and automated regionalization of Rayleigh wave dispersion data for the Mediterranean basin, without a priori seismotectonic constraints, and to determine the corres...
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The main target of the present study is an objective and automated regionalization of Rayleigh wave dispersion data for the Mediterranean basin, without a priori seismotectonic constraints, and to determine the corresponding regional shear-velocity structures. The database used is formed by almost 200 Rayleigh wavetrains corresponding to 42 regional events, with surface-wave magnitude greater than 4.5, recorded at the MedNet very-broad-band stations in the Mediterranean area. Path-averaged group velocities for the Rayleigh wave fundamental mode are derived for each available epicentre-station trajectory crossing the Mediterranean basin. After this, a principal component analysis and a clustering process are applied to local group velocities, obtained for 13 different periods from 10 to 70 s, in order to classify the Mediterranean basin into several homogeneous regions. The stochastic inversion of the averaged group velocity dispersion curve obtained for each region provides the respective shear-velocity structures, down to a depth of 150-160 km. The characteristics of these areas and their possible correlation with the main seismotectonic features of the Mediterranean region are discussed. The regional models reveal significant lateral changes in the elastic structure, with the main differences concerning particularly the upper 35-40 km. Within this depth range, low shear velocities, varying from 2.8 to 3.9 km s(-1), characterize the Eastern Mediterranean, whereas higher velocities, ranging from 3.0 to 4.2 km s(-1), are deduced for the Western Mediterranean, These results suggest a thicker rust in the eastern Dart, but with a greater thickness of sedimentary layers. However, for depths of between 80 and 110 km, lower shear velocities are obtained in the Western part, while higher shear velocities are derived for the Eastern Mediterranean Sea, in the Aegean Sea, Greece, the south of Italy, Sicily and Tunisia. This velocity pattern suggests an averaged thicker lithosp
This correspondence presents a linear assignment algorithm for solving the clustering problem. By use of the most dissimilar data as cluster representatives, a linear assignment algorithm is developed based on a linea...
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This correspondence presents a linear assignment algorithm for solving the clustering problem. By use of the most dissimilar data as cluster representatives, a linear assignment algorithm is developed based on a linear assignment model for clustering multivariate data. The computational results evaluated using multiple performance criteria show that the clustering algorithm is very effective and efficient, especially for clustering a large number of data with many attributes.
A method of dynamically assembling molecular building blocks - DycoBlock - has been proposed and tested by Liu et al. [1]. This method is based on multiple-copy stochastic dynamics simulation in the presence of a rece...
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A method of dynamically assembling molecular building blocks - DycoBlock - has been proposed and tested by Liu et al. [1]. This method is based on multiple-copy stochastic dynamics simulation in the presence of a receptor molecule. In this method, a novel algorithm was used to dynamically assemble the molecular building blocks to form candidate compounds. Currently, some new improvements have been incorporated into DycoBlock to make it more efficient. In the new version of DycoBlock, the binding energy and solvent accessible surface area (SASA) can be used to screen the resulting compounds. A simple clustering algorithm based on molecular similarity was developed and used to classify the remaining compounds. The revised DycoBlock was tested by breaking SC-558 - a selective inhibitor of cyclooxygenase-2 (COX-2) - into building blocks and reassembling them in the active site of the enzyme. The accuracy of recovery grew to 58.8% while it was only 16.7% in the previous version. Then, thirty-three kinds of molecular building blocks were used in the design of novel inhibitors and the investigation of diversity. As a result, a total of 1441 compounds was generated with high diversity. After the first screening procedure, there remained 864 reasonable compounds. The results from clustering indicate that the structural motifs in the diarylheterocycle class of COX-2-selective inhibitors [2] have been generated using the revised DycoBlock, and their binding modes were investigated.
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