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Fluid deformations around a cylinder combined with an applied electric field are used to enhance the kinetics rate and the response time of heterogeneous immunosensors in microfluidic systems. The insertion of an obstacle in the microchannel as well as the application an applied electric field are used to change the fluid motion topology that improves the transport of diffusion-limited proteins. The response time is affected by various parameters such as the inlet flow velocity, the initial analyte concentration and the obstacle position. The effects of the parameters related to the kinetics reaction on the sensitivity and the performance of the biosensor have been studied numerically. Numerical results reveal that an appropriate choice of the inlet analyte and inlet flow velocity with applied electric field may reduce considerably the response time and enhance the microfluidic sensor performance.

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Optimising computing times of applications is an increasingly important task in many different areas such as scientific and industrial applications. Graphics processing unit (GPU) is considered as one of the powerful engines for computationally demanding applications since it proposes a highly parallel architecture. In this context, the authors introduce an algorithm to optimise the computing time of feature extraction methods for the colour image. They choose generalised Fourier descriptor (GFD) and generalised colour Fourier descriptor (GCFD) models, as a method to extract the image feature for various applications such as colour object recognition in real-time or image retrieval. They compare the computing time experimental results on central processing unit and GPU. They also present a case study of these experimental results descriptors using two platforms: a NVIDIA GeForce GT525M and a NVIDIA GeForce GTX480. Their experimental results demonstrate that the execution time can considerably be reduced until 34× for GFD and 56× for GCFD.