32640232
AP-Based Borda Voting Method for Feature Extraction in TRECVID-2004
We present a novel fusion method — AP-based Borda voting method (APBB)— for rankings. Due to its adaptive weighting scheme, APBB outperforms many traditional methods. Comparative experiments on TRECVID 2004 data were carried out and showed the robustness and effectiveness of this method.
10396270
Temporal Shot Clustering Analysis for Video Concept Detection
The phenomenon that conceptually related shots appear together in videos is called temporal shot clustering. This phenomenon is a useful cue for video concept detection, which is one of basic steps in content-based video indexing and retrieval. We propose a method, called temporal shot clustering analysis, to improve results of video concept detection by exploiting the temporal shot clustering phenomenon. Two other methods are compared with temporal shot clustering analysis on the TRECVID 2003 dataset. Experiments showed that temporal shot clustering is of much benefit for video concept detection, and that temporal shot clustering method outperforms the other methods.
18536483
Mesh Smoothing Schemes Based on Optimal Delaunay Triangulations
We present several mesh smoothing schemes based on the concept of optimal Delaunay triangulations. We define the optimal Delaunay triangulation (ODT) as the triangulation that minimizes the interpolation error among all triangulations with the same number of vertices. ODTs aim to equidistribute the edge length under a new metric related to the Hessian matrix of the approximated function. Therefore we define the interpolation error as the mesh quality and move each node to a new location, in its local patch, that reduces the interpolation error. With several formulas for the interpolation error, we derive a suitable set of mesh smoothers among which Laplacian smoothing is a special case. The computational cost of proposed new mesh smoothing schemes in the isotropic case is as low as Laplacian smoothing while the error-based mesh quality is provably improved. Our mesh smoothing schemes also work well in the anisotropic case.
8887048
Using a Soft Core in a SoC Design: Experiences with picoJava
Through our experience in synthesis, validation, test, and integration of the picoJava processor core in a system-on-chip (SoC) design we point out the challenges faced and issues to address in efficient reuse of a soft core.
7815226
Peak Load Forecasting Using the Self-organizing Map
This paper aims to study the short-term load forecasting of electricity by using an extended self-organizing map. We first adopt a traditional Kohonen self-organizing map (SOM) to learn time-series load data with weather information as parameters. Then, in order to improve the accuracy of the prediction, an extension of SOM algorithm based on error-correction learning rule is used, and the estimation of the peak load is achieved by averaging the output of all the neurons. Finally, as an implementation example, data of electricity demand from New York Independent System Operator (ISO) are used to verify the effectiveness of the learning and prediction for the proposed methods.
5457020
Identifying metabolic enzymes with multiple types of association evidence
BackgroundExisting large-scale metabolic models of sequenced organisms commonly include enzymatic functions which can not be attributed to any gene in that organism. Existing computational strategies for identifying such missing genes rely primarily on sequence homology to known enzyme-encoding genes.ResultsWe present a novel method for identifying genes encoding for a specific metabolic function based on a local structure of metabolic network and multiple types of functional association evidence, including clustering of genes on the chromosome, similarity of phylogenetic profiles, gene expression, protein fusion events and others. Using E. coli and S. cerevisiae metabolic networks, we illustrate predictive ability of each individual type of association evidence and show that significantly better predictions can be obtained based on the combination of all data. In this way our method is able to predict 60% of enzyme-encoding genes of E. coli metabolism within the top 10 (out of 3551) candidates for their enzymatic function, and as a top candidate within 43% of the cases.ConclusionWe illustrate that a combination of genome context and other functional association evidence is effective in predicting genes encoding metabolic enzymes. Our approach does not rely on direct sequence homology to known enzyme-encoding genes, and can be used in conjunction with traditional homology-based metabolic reconstruction methods. The method can also be used to target orphan metabolic activities.
1426843
Priority based Overlay Multicast with Filtering Mechanism for Distributed Interactive Applications
The "priority-based directed minimum spanning tree" (PST) is designed for distributed interactive applications (DIAs) in which the data are delivered to the receiver node according to their priority; however PST cannot balance the bandwidth usage among the nodes and the system will be unstable when its scale increases. This paper proposes a novel overlay multicast protocol named priority based overlay multicast (POM), which uses the priority, delay and available bandwidth to construct the multicast tree, besides a filtering mechanism is proposed to rebuild the tree when the available bandwidth shortage appears. The effectiveness of our protocol is demonstrated in the simulation results, showing that POM uses the available bandwidth efficiently, besides it keeps the system stable when its scale increases