Visual information processing is not only an important research direction in fields of psychology,neuroscience and artificial intelligence etc,but also the research base on biological recognition theory and technology...Visual information processing is not only an important research direction in fields of psychology,neuroscience and artificial intelligence etc,but also the research base on biological recognition theory and technology realization.Visual information processing in existence,e.g.visual information processing facing to nerve calculation,visual information processing using substance shape distilling and wavelet under high yawp,ANN visual information processing and etc,are very complex in comparison.Using qualitative Mapping,this text describes the specific attributes in the course of visual information processing and the results are more brief and straightforward.So the software program of vision recognition is probably easier to realize.展开更多
Video watermark is the main method to protect the copyright of digital video. In this paper, a blind video watermarking scheme based on independent component analysis （ICA） and shot segmentation is presented. In thi...Video watermark is the main method to protect the copyright of digital video. In this paper, a blind video watermarking scheme based on independent component analysis （ICA） and shot segmentation is presented. In this scheme, the global histogram comparison approach is used to segment the video, and ICA is performed on each obtained segment to get its independent component frames （ICFs）. The copyright information is embedded into the principal independent component frames （PICFs） according to the single watermark embedding （SWE） scheme. The content-based shot segmentation for video sequences is used here to improve the robustness to temporal desynchronization. The watermark embedded in PICFs provides better robustness to intra-video collusion attack. And blind detection is achieved by using the SWE scheme. The simulations show the feasibility and validity of this scheme. It can resist most of the common frame-based and video-based attacks. The watermark can be detected blindly. And it is robust to temporal desynchronization and intra-video collusion.展开更多
Data warehouse （DW） modeling is a complicated task, involving both knowledge of business processes and familiarity with operational information systems structure and behavior. Existing DW modeling techniques suffer ...Data warehouse （DW） modeling is a complicated task, involving both knowledge of business processes and familiarity with operational information systems structure and behavior. Existing DW modeling techniques suffer from the following major drawbacks -- data-driven approach requires high levels of expertise and neglects the requirements of end users, while demand-driven approach lacks enterprise-wide vision and is regardless of existing models of underlying operational systems. In order to make up for those shortcomings, a method of classification of schema elements for DW modeling is proposed in this paper. We first put forward the vector space models for subjects and schema elements, then present an adaptive approach with self-tuning theory to construct context vectors of subjects, and finally classify the source schema elements into different subjects of the DW automatically. Benefited from the result of the schema elements classification, designers can model and construct a DW more easily.展开更多
This paper proposes a complementary novel idea, called MiniTasking to further reduce the number of cache misses by improving the data temporal locality for multiple concurrent queries. Our idea is based on the observa...This paper proposes a complementary novel idea, called MiniTasking to further reduce the number of cache misses by improving the data temporal locality for multiple concurrent queries. Our idea is based on the observation that, in many workloads such as decision support systems （DSS）, there is usually significant amount of data sharing among different concurrent queries. MiniTasking exploits such data sharing to improve data temporal locality by scheduling query execution at three levels： query level batching, operator level grouping and mini-task level scheduling. The experimental results with various types of concurrent TPC-H query workloads show that, with the traditional N-ary Storage Model （NSM） layout, MiniTasking significantly reduces the L2 cache misses by up to 83%, and thereby achieves 24% reduction in execution time. With the Partition Attributes Across （PAX） layout, MiniTasking further reduces the cache misses by 65% and the execution time by 9%. For the TPC-H throughput test workload, MiniTasking improves the end performance up to 20%.展开更多
文摘Visual information processing is not only an important research direction in fields of psychology,neuroscience and artificial intelligence etc,but also the research base on biological recognition theory and technology realization.Visual information processing in existence,e.g.visual information processing facing to nerve calculation,visual information processing using substance shape distilling and wavelet under high yawp,ANN visual information processing and etc,are very complex in comparison.Using qualitative Mapping,this text describes the specific attributes in the course of visual information processing and the results are more brief and straightforward.So the software program of vision recognition is probably easier to realize.
文摘Video watermark is the main method to protect the copyright of digital video. In this paper, a blind video watermarking scheme based on independent component analysis （ICA） and shot segmentation is presented. In this scheme, the global histogram comparison approach is used to segment the video, and ICA is performed on each obtained segment to get its independent component frames （ICFs）. The copyright information is embedded into the principal independent component frames （PICFs） according to the single watermark embedding （SWE） scheme. The content-based shot segmentation for video sequences is used here to improve the robustness to temporal desynchronization. The watermark embedded in PICFs provides better robustness to intra-video collusion attack. And blind detection is achieved by using the SWE scheme. The simulations show the feasibility and validity of this scheme. It can resist most of the common frame-based and video-based attacks. The watermark can be detected blindly. And it is robust to temporal desynchronization and intra-video collusion.
基金Supported by the National Natural Science Foundation of China under Grant No. 60403041, the Project of National ＂10th Five-Year Plan＂ of China under Grant No. 2001BA102A01, and the National Grand Fundamental Research 973 Program of China under Grant No. 1999032705. Acknowledgements The first author is very thankful to Jian Liu, Bo Yu, Peng Zhang and Ling-Fu Li for their valuable suggestions on this paper. The authors are also grateful to anonymous reviewers for their insightful comments on this paper, which have helped to improve the manuscript.
文摘Data warehouse （DW） modeling is a complicated task, involving both knowledge of business processes and familiarity with operational information systems structure and behavior. Existing DW modeling techniques suffer from the following major drawbacks -- data-driven approach requires high levels of expertise and neglects the requirements of end users, while demand-driven approach lacks enterprise-wide vision and is regardless of existing models of underlying operational systems. In order to make up for those shortcomings, a method of classification of schema elements for DW modeling is proposed in this paper. We first put forward the vector space models for subjects and schema elements, then present an adaptive approach with self-tuning theory to construct context vectors of subjects, and finally classify the source schema elements into different subjects of the DW automatically. Benefited from the result of the schema elements classification, designers can model and construct a DW more easily.
文摘This paper proposes a complementary novel idea, called MiniTasking to further reduce the number of cache misses by improving the data temporal locality for multiple concurrent queries. Our idea is based on the observation that, in many workloads such as decision support systems （DSS）, there is usually significant amount of data sharing among different concurrent queries. MiniTasking exploits such data sharing to improve data temporal locality by scheduling query execution at three levels： query level batching, operator level grouping and mini-task level scheduling. The experimental results with various types of concurrent TPC-H query workloads show that, with the traditional N-ary Storage Model （NSM） layout, MiniTasking significantly reduces the L2 cache misses by up to 83%, and thereby achieves 24% reduction in execution time. With the Partition Attributes Across （PAX） layout, MiniTasking further reduces the cache misses by 65% and the execution time by 9%. For the TPC-H throughput test workload, MiniTasking improves the end performance up to 20%.
