An one-way hash chain generated by the iterative use of a one-way hash function on a secret value has recently been widely employed to develop many practical cryptographic solutions, especially electronic micropayment...
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This report presents preliminary results from our project on creating distributed expertise for teaching computer organization & architecture course(s) in the undergraduate computerscience curriculum. We present ...
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ISBN:
(纸本)9781450373586
This report presents preliminary results from our project on creating distributed expertise for teaching computer organization & architecture course(s) in the undergraduate computerscience curriculum. We present the details of an online survey designed to gather information from faculty on the current state of teaching this course. The survey also tries to identify specific areas of need for creating distributed expertise as reported by various faculty. We also present several resources that have been identified that are available for use by faculty teaching the course(s). This report represents a mid-point of an ongoing two-year study. Following a discussion of the currently identified needs, we discuss ways to address them and conclude the report with a plan of action that will follow in the next phase of the project.
Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.
ISBN:
(纸本)9781581132700
Our results demonstrate that our novel application development environment provides both ease-of-use and high performance for large-scale, I/O-intensive scientific applications.
This paper provides a brief survey on recent research in the area of design rationale. The study of Design Rationale spans a number of diverse disciplines, touching on concepts from research communities in Mechanical ...
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Digital video databases in compressed form are becoming widely available. In applications such as video browsing, and picture in picture, for a lower bitrate there is a need to down-sample the video before transmissio...
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Digital video databases in compressed form are becoming widely available. In applications such as video browsing, and picture in picture, for a lower bitrate there is a need to down-sample the video before transmission. The conventional approach to downscale a compressed video sequence is to decompress it at the video server, perform the down-sampling in the pixel domain and recompress it again for efficient delivery. This process is computationally expensive due to the motion estimation process needed during the recompression phase. In the alternative compressed domain based approach the downscaled motion vectors are computed directly from the original ones. We propose a method to improve the process of downscaling in the compressed domain by better selecting the motion prediction type of P and B frame macroblocks. Simulations suggest that the proposed scheme improves the compressed domain down-sampling quality by up to 2.2 dB without any substantial increase in computation.
Digital video databases in compressed form are becoming widely available. In applications such as video browsing, and picture in picture, for a lower bitrate, there is a need to down-sample the video before transmissi...
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Digital video databases in compressed form are becoming widely available. In applications such as video browsing, and picture in picture, for a lower bitrate, there is a need to down-sample the video before transmission. The conventional approach to downscale a compressed video sequence is to decompress it at the video server, perform the down-sampling in the pixel domain and then recompress it for efficient delivery. This process is computationally intensive due to the motion estimation process required during the recompression phase. In the alternative compressed domain approach, the motion vectors of the downscaled video sequence are computed directly from the motion vectors of the original full size stream. In this paper we propose a compressed domain technique that generates a better estimate for the downscaled motion vectors. Simulations suggest that the performance achieved with the proposed method is superior by up to 1 dB to the current compressed domain techniques.
Often, images or datasets have to be compared to facilitate choices of visualization and simulation parameters respectively. Common comparison techniques include side-by-side viewing and juxtaposition, in order to fac...
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ISBN:
(纸本)078035897X
Often, images or datasets have to be compared to facilitate choices of visualization and simulation parameters respectively. Common comparison techniques include side-by-side viewing and juxtaposition, in order to facilitate visual verification of verisimilitude. We propose quantitative techniques which accentuate differences in images and datasets. The comparison is enabled through a collection of partial metrics which, essentially, measure the lack of correlation between the datasets or images being compared. That is, they attempt to expose and measure the extent of the inherent structures in the difference between images or datasets. Besides yielding numerical attributes, the metrics also produce images which can visually highlight differences. Our metrics are simple to compute and operate in the spatial domain. We demonstrate the effectiveness of our metrics through examples for comparing images and datasets.
Often, images or datasets have to be compared, to facilitate choices of visualization and simulation parameters respectively. Common comparison techniques include side-by-side viewing and juxtaposition, in order to fa...
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ISBN:
(纸本)9780780358973
Often, images or datasets have to be compared, to facilitate choices of visualization and simulation parameters respectively. Common comparison techniques include side-by-side viewing and juxtaposition, in order to facilitate visual verification of verisimilitude. In this paper, we propose quantitative techniques which accentuate differences in images and datasets. The comparison is enabled through a collection of partial metrics which, essentially, measure the lack of correlation between the datasets or images being compared. That is, they attempt to expose and measure the extent of the inherent structures in the difference between images or datasets. Besides yielding numerical attributes, the metrics also produce images, which can visually highlight differences. Our metrics are simple to compute and operate in the spatial domain. We demonstrate the effectiveness of our metrics through examples for comparing images and datasets.
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