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Category Archive: LATEST NS2 PROJECTS

Exploiting Moving Objects: Multi-Robot Simultaneous Localization and Tracking

Cooperative localization has been proved to effectively outperform single-robot localization. While most of the state-of-the-art multi-robot localization systems either treat moving objects as outliers or accomplish moving object tracking separately from localization, we argue that augmenting moving objects into the localization estimation can further enhance localization performance and is indeed the key to solve several […]

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Glucose-tracking: A postprandial glucose prediction system for diabetic self-management

Up to today, there are around 400 million diabetics in the world. In China, there are more than 100 million diabetics. How to help them track and manage real-time glucose level is significant to control diabetic progression. As well known, the glucose level is directly related with food, while the conventional tracking glucose is depending […]

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Heart murmur detection and classification using wavelet transform and Hilbert phase envelope

Detection and classification of heart murmurs play an important role in accurate diagnosis of different types of heart dysfunctions. In this paper, we present a noise-robust method for detection and classification of heart murmurs using stationary wavelet transform (SWT) and Hilbert phase envelope. The proposed method consists of five major stages: SWT based PCG signal […]

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Disambiguating Stereoscopic Transparency Using a Thaumatrope Approach

Volume rendering is a popular visualization technique for scientific computing and medical imaging. By assigning proper transparency, it allows us to see more information inside the volume. However, because volume rendering projects complex 3D structures into the 2D domain, the resultant visualization often suffers from ambiguity and its spatial relationship could be difficult to recognize […]

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Cumulative Distribution Function of Bivariate Gamma Distribution With Arbitrary Parameters and Applications

In this letter, we consider bivariate gamma distributions with arbitrary parameters and obtain closed-form expressions for the cumulative distribution function for scenarios where the difference between the shape parameters of the marginal distributions is an integer.

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