One of the important aspects in digital video applications is spatial and temporal characteristic. A very little progress has been achieved on spatio-temporal modeling of video data. In this paper, we present a fuzzy ...
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Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network analysis, from the World Wide Web to ...
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ISBN:
(纸本)9781605581026
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network analysis, from the World Wide Web to stock market analysis. Motivated by this need recently we have seen several new algorithms to tackle this problem based on the (frequent) pattern mining paradigm. A limitation of most of these methods is that they are highly sensitive to parameter settings, rely on exhaustive enumeration with exponential time complexity, and often fail to help the users understand the underlying distribution of components embedded within the host graph. In this article we propose an approximate algorithm, to mine and visualize cohesive subgraphs (dense sub components) within a large graph. The approach, refereed to as Cohesive Subgraph Visualization (CSV) relies on a novel mapping strategy that maps edges and nodes to a multi-dimensional space wherein dense areas in the mapped space correspond to cohesive subgraphs. The algorithm then walks through the dense regions in the mapped space to output a visual plot that effectively captures the overall dense sub-component distribution of the graph. Unlike extant algorithms with exponential complexity, CSV has a complexity of O(V 2logV) when fixing the parameter mapping dimension, where V corresponds to the number of vertices in the graph, although for many real datasets the performance is typically sub-quadratic. We demonstrate the utility of CSV as a stand-alone tool for visual graph exploration and as a pre-filtering step to significantly scale up exact subgraph mining algorithms such as CLAN [33]. Copyright 2008 ACM.
This paper considers the performance of the MAC protocols ALOHA and CSMA in wireless ad hoc networks, where the total system bandwidth may be divided into smaller subbands. In the network model used, the arrival of us...
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We proposed a technique controlling continuously pretilt angle in full range -with high process margin. The proposed method is characterized by tuning thickness of heterogeneous polyimide (PI) layer that homeotropic P...
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We proposed a technique controlling continuously pretilt angle in full range -with high process margin. The proposed method is characterized by tuning thickness of heterogeneous polyimide (PI) layer that homeotropic PI is mixed with planar Pis.
The subject of this work is the model selection of kernels with multiple parameters for support vector machines (SVM), with the purpose of classifying hyperspectral remote sensing data. During the training process, th...
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Due to the rapid growth of graphics processing unit (GPU) processing capability, using GPU as a coprocessor to assist the central processing unit (CPU) in computing massive data becomes essential. In this paper, we pr...
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ISBN:
(纸本)9781424425709
Due to the rapid growth of graphics processing unit (GPU) processing capability, using GPU as a coprocessor to assist the central processing unit (CPU) in computing massive data becomes essential. In this paper, we present an efficient block-level parallel algorithm for the variable block size motion estimation (ME) in H.264/AVC with fractional pixel refinement on a computer unified device architecture (CUDA) platform, developed by NVIDIA in 2007. The CUDA enhances the programmability and flexibility for general-purpose computation on GPU. We decompose the H.264 ME algorithm into 5 steps so that we can achieve highly parallel computation with low external memory transfer rate. Experimental results show that, with the assistance of GPU, the processing time is 12 times faster than that of using CPU only.
A fibre-optic evanescent-wave field absorption sensor based on a meander-shaped sensing probe is described. The influences of the fibre core diameter and the refractive index of the surrounding medium on the sensitivi...
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This is a brief description of audio channel or sound source separation algorithm using spatial cues. Basically inter-channel level difference (ICLD) is used for discriminating sound sources in a spatial grid for each...
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ISBN:
(纸本)9789512295173
This is a brief description of audio channel or sound source separation algorithm using spatial cues. Basically inter-channel level difference (ICLD) is used for discriminating sound sources in a spatial grid for each channel pair and analysis subband. Interchannel cross-correlation (ICC) is also used for determining sound source location area and contribution factor for the considering composite sound source. In this paper, the center and side channel separation of stereophonic music signal using spatial sound source discrimination method is introduced. This is simply implemented by using given information of center channel location and derived spatial cues. The separated center channel signal is well matched with separated side channels when reproduced simultaneously.
A novel ESPRIT based algorithm is proposed to jointly estimate 2-dimensional direction-of-arrivals (2-D DOAs) and frequencies of the incoming superimposed complex sinusoidal signals using a sparse uniform linear array...
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A novel ESPRIT based algorithm is proposed to jointly estimate 2-dimensional direction-of-arrivals (2-D DOAs) and frequencies of the incoming superimposed complex sinusoidal signals using a sparse uniform linear array of electromagnetic vector-sensors. The proposed method is based on a matrix pencil pair of temporally displaced data sets that are collected from the electromagnetic vector sensor array, where the DOA and frequency estimates can be estimated unambiguously from the eigenvectors and eigenvalues of the matrix pencil even when the interelement spacing is more than half wavelength. A second algorithm is proposed to resolve the ambiguity problem in the frequency estimates when the temporal sampling rate is less than half of the Nyquist rate of the signal, i.e. the sampling rate is less than the maximum frequency of the signal. Simulation results support the proposed algorithms and show that the 2-D DOA and frequency estimates are asymptotically unbiased and have a low variance. copyright by EURASIP.
The security of a biometric information system depends partially on the ability of the biometric information sensor to authenticate itself securely to the processing centre it usually interacts with, thus ensuring tha...
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