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As a bridge between social media and physical space, location information will potentially make the internet smarter, and release the real power of social media to address the serious and significant problems in the real world. However, in terms of privacy and security, most of the users are unwilling to make their locations public. To address the problem, an algorithm is necessary to predict the...
The location information in social media often provides insight on the repercussions of events and is becoming more and more vital to the applications such as localized search, local news recommendation and emergency detection. However, for the security and privacy concerns, most users in social media are unwilling to publish their location, and they may post non-existing places or submit unspecific...
Identifying and classifying different network applications is very important for trend analysis, dynamic access control, network security and traffic engineering, while traffic classification is able to classify applications effectively. Current popular methods of traffic classification mainly include machine learning algorithm based on supervised or unsupervised and the method based load. In practical...
This study want to find electrophysiological evidence to test whether face capture more attention than object, and whether the attention capture of face automatically or controllably. Fifteen subjects were tested on a three-stimulus visual oddball task, in which faces and objects as distractor stimuli were presented in different blocks separately. Face as task-irrelevant stimuli elicited earlier,...
An observational study on dust-storm is performed according to the ground-based integrated monitoring system at a semi-arid site. For the automatic sun-tracking photometer, which has widely-acceptable retrieval accuracy, cloud influence stays still a problem for vertical atmosphere remote sensing. Multimodal distribution of optical depth thus appears during dust-storm event and brings out difficulty...
The baseline system PRLM has the best performance on NIST language recognition evaluation tasks. But this system needs orthographically or phonetically transcribed utterances which can not be easily obtained from Chinese dialects and minority languages. So, the PRLM system is not used to these languages. To overcome this limitation, we present the Gaussian mixture model recognizer followed by language-dependent...
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