The fast development of micro-electromechanical system (MEMS) technology has brought many great ideas in the field of biomedical applications. A biosensor is a chemical sensing device in which a biologically derived recognition analyte coupled to a transducer to allow the quantitative development of biochemical parameter. A biosensor consists of a bio-element and a sensor-element. The bio-element may be an enzyme, antibody, living cells, tissue, etc., and the sensing element may be electric current, electric potential, and so on and specificity of analyte is the important concept in biosensor. In this paper we review the principle of microcantilever, biosensing mechanism and applications of microcantilevers for bio detection for early detection of diseases accurately. Biosensors can have a variety of biomedical, industry, and military applications. The main advantages of MEMS based sensors are specificity, portability, simplicity, high sensitivity, potential ability for real-time and on-site analysis coupled with the high speed and low cost.
In Content Based Image Retrieval system images from the database are processed and their features are extracted. These features are such that they describe some properties of the image. The features of the images are indexed to determine the similarity between them. However, the retrieved image is the one having maximum similarity with the input image. Several research papers were studied in order to understand the evolution and evaluation techniques of CBIR. In this paper we present the pixel level features for content based image retrieval. We classify the feature extraction methods used and identify some promising techniques for Content Based Image Retrieval according to standard principles.
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