Haoxuan Li

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The success of applying dry sensor technology in measuring electroencephalogram (EEG) signals will have a significant impact on a wider adoption of brain activity monitoring in ambulatory as well as real life solutions. The presence of motion artifacts is the major obstacle in applying dry sensors for long-term EEG monitoring. In this paper we assess the(More)
A new method for automatically fitting the Liljencrants-Fant (LF) model to the time domain waveform of the glottal flow derivative is presented in this paper. By applying an extended Kalman filter (EKF) to track the LF-model shape-controlling parameters and dynamically searching for a globally minimal fitting error, the algorithm can accurately fit the(More)
Although copper (Cu) is an essential micronutrient for plants, a slight excess of Cu in soil can be harmful to plants. Unfortunately, Cu contamination is a growing problem all over the world due to human activities, and poses a soil stress to plant development. As one of the most important biological processes, seed germination is sensitive to Cu stress.(More)
Properties are used to describe entities, a part of which are likely to be clustered together to constitute an aspect. However, existing automated approaches to property clustering remain far from satisfactory for an open domain like Linked Data. In this paper, we firstly investigated the relatedness between properties using five different measures. Then,(More)
A new approach to robust tracking of glottal LF-model parameters is presented. The approach does not rely on a new glottal source estimation algorithm, but instead introduces a new extensible multi-estimate fusion framework. Within this framework several existing algorithms are applied in parallel to extract glottal LF-model parameter estimates which are(More)
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