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Cloud storage systems frequently have a large user base that requires huge cloud resources. Sometimes, cloud devices become overloaded because of an imbalance in input/output (I/O) or space demand. How can data with different popularity be distributed over heterogeneous devices? The key to resolving this problem is to balance the workload of multi-dimension resources. A consistent hash-aware cloud...
Video behavior analysis is both meaningful and challenging in computer vision. As the monitoring equipment become readily cheaper and available, massive video data have been generated. As abnormal behaviors are rare, manual surveillance may drastically increase the chances of false positives or false negatives. It is hence useful to achieve automatic surveillance. Abnormal behaviors are usually complex...
Web news articles play an important role in stock market. Sentiment classification of news articles can help the investors make investment decisions more efficiently. In this paper, we implemented an approach of Chinese new words detection by using N-gram model and applied the result for Chinese word segmentation and sentiment classification. Appraisal theory was introduced into sentiment analysis...
Performance monitoring using wireless sensors is now common practice in building operation and maintenance and generates a large amount of building specific data. However, it is difficult for occupants, owners and operators to explore such data and understand underlying patterns. This is especially true in buildings which involve complex interactions, such as ventilation, solar gains, internal gains...
As the information on the Internet increases dramatically, the Web search engine has become an indispensable tool to search and locate the required information. Web snippets clustering can classify the search results and help users to narrow the search scope. This paper presents an online clustering algorithm for Chinese web snippets using common substrings. The algorithm firstly preprocesses the...
In lung cancer image classification, the label concepts are usually given out for the whole image but not for a single cell, which leads to a low predict accuracy if we use supervised learning methods on cell-level. In this paper, we model lung cancer image classification as a multi-class multi-instance learning problem. A lung cancer image is treated as a bag. Each bag contains a set of instances...
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