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We present Mantis, a framework for predicting the computational resource consumption (CRC) of Android applications on given inputs accurately, and efficiently. A key insight underlying Mantis is that program codes often contain features that correlate with performance and these features can be automatically computed efficiently. Mantis synergistically combines techniques from program analysis and...
The modeling and simulation of bicycle conflict avoidance behaviors with other vehicles (motor-car\other bicycles\pedestrians) and the obstacle (safety island, fence etc.) at non-signalized intersections is of great importance in junction analysis. However, it is very difficult to simulate the conflict avoidance behaviors of individual bicycle because of the great variations in the cycling behaviors,...
The problem of session variability in text-independent speaker verification has been tackled actively for a few years. Factor analysis has successfully been applied for this problem. However, efficient implementation of factor analysis is also a challenge. In this paper we propose a novel GMM mixture pre-selection based factor analysis model for speaker verification and show how it successfully implemented...
In this paper, a multiphase level set method with multi dynamic shape models is proposed to segment the kidneys on the abdominal computed tomography (CT) images. Comparing with the original Chan-Vese model three changes are made to improve the segmentation result. The first is using shape model to help the segmentation. The second is using dynamic shape model to deal with the variation of the kidneys...
In this paper, a level set method with shape model is proposed for image segmentation. Because the level set model proposed by Chan and Vese can not work well on some specific shape, this paper adds the shape knowledge into the segmentation method. The Chan-Vese level set model is applied to get initial segmentation. And then the position and the size of the pre-segmented region will be calculated...
In this paper, we develop some new aggregation operators such as 2-tuple linguistic geometric averaging (TGA) operator, 2-tuple linguistic weighted averaging (TWGA) operator, 2-tuple linguistic ordered weighted geometric averaging (TOWGA) operator and 2-tuple linguistic hybrid geometric averaging (THGA) operator, which can be utilized to aggregate preference information taking the form of linguistic...
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