Mid-Range Wireless Power Transfer and Its Application to Body Sensor Networks

It has been reported that, through the evanescent near fields, the strongly coupled magnetic resonance is able to achieve an efficient mid-range Wireless Power Transfer (WPT) beyond the characteristic size of the resonator. Recent studies on of the relay effect of the WPT allow more distant and flexible energy transmission. These new developments hold a promise to construct a fully wireless Body Sensor Network (wBSN) using the new mid-range WPT theory. In this paper, a general optimization strategy for a WPT network is presented by analysis and simulation using the coupled mode theory. Based on the results of theoretical and computational study, two types of thin-film resonators are designed and prototyped for the construction of wBSNs. These resonators and associated electronic components can be integrated into a WPT platform to permit wireless power delivery to multiple wearable sensors and medical implants on the surface and within the human body. Our experiments have demonstrated the feasibility of the WPT approach.

An Improved Non-Parametric Method for Multiple Moving Objects Detection in the Markov Random Field

Detecting moving objects in the stationary background is an important problem in visual surveillance systems.However,the traditional background subtraction method fails when the background is not completely stationary and involves certain dynamic changes.In this paper,according to the basic steps of the background subtraction method,a novel non-parametric moving object detection method is proposed based on an improved ant colony algorithm by using the Markov random field.Concretely,the contributions are as follows:1)A new nonparametric strategy is utilized to model the background,based on an improved kernel density estimation;this approach uses an adaptive bandwidth,and the fused features combine the colours,gradients and positions.2)A Markov random field method based on this adaptive background model via the constraint of the spatial context is proposed to extract objects.3)The posterior function is maximized efficiently by using an improved ant colony system algorithm.Extensive experiments show that the proposed method demonstrates a better performance than many existing state-of-the-art methods.

A WAVELET TRANSFORM BASED POCS SUPERRESOLUTION ALGORITHM

Research interest in multi-frame Superresolution has risen substantially in recent years. This paper presents a modified Projection Onto Convex Set （POCS） superresolution method based on wavelet transform. The method analyzes the image formation model from wavelet multiresolution analysis point of view and defines an closed convex set and its corresponding projection based on wavelet transform. An iterative procedure is utilized to reduce the estimated errors of the result image, and this guarantees the estimated image to lay in the intersection of different convex sets, thus produces a high resolution image with a reduced error. The effectiveness of the algorithm is demonstrated bv experimental results.