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This paper studies transcutaneous energy transmission system (TETS) for artificial anal sphincter (AAS). The AAS is a solution to treat the severe fecal incontinence. It is designed to be implanted in the body of a patient who lose his anal sphincter. The AAS helps the patient to consciously open or close his anus to prevent fetal incontinence. The TETS is an optimal choice to provide energy for the...
In order to optimize signal detection in non-Gaussian environments, the work is addressed to provide realistic modeling of a generic noise probability density. The model depends on few parameters which can be estimated quickly and easily, and so general to be able to describe many kinds of noise such as symmetric or asymmetric. To this end, a new model is introduced, which derives from the generalized...
This article presents a novel integrated approach to object of interest extraction, including learning to define target pattern and extracting by combining detection and segmentation. The learning stage captures both shape sketch and appearance information of target pattern as prior knowledge. The extraction stage utilizes a stochastic Markov Chain Monte Carlo (MCMC) algorithm under the Bayesian framework...
To automatically register foreground target in cluttered images, we present a novel hierarchical graph representation and a stochastic computing strategy in Bayesian framework. The graph representation, which contains point-(image primitives), seedgraph-, and subgraph- three levels, are built up following the primal sketch theory to capture geometric, topological, and spatial information both in local...
This paper introduces a novel surface-modeling method to stochastically distribute features on arbitrary topological surfaces. The generated distribution of features follows the Poisson disk distribution, so we can have a minimum separation guarantee between features and avoid feature overlap. With the proposed method, we not only can interactively adjust and edit features with the help of the proposed...
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