No abstract

No abstract

This paper describes the performance of the Aperture Coupled Microstrip Planar Array in C-band. The basic concept of aperture coupling is to achieve the wide frequency bandwidth & low back radiation. The enhancement of the bandwidth in the present case is achieved by coupling to the microstrip antenna on one substrate from the microstrip line feed on another parallel substrate through an aperture in the ground plane, which separates the two substrates. A design procedure for aperture coupled microstrip antennas based on transmission line model is presented. The novel coaxial to microstrip line transition is devised and implemented to feed the aperture coupled microstrip antenna elements in planar array to achieve the wide impedance and pattern bandwidth. The experimental results of Return loss plot & Radiation pattern for aperture coupled microstrip planar array antenna are presented.

K mean clustering is a very popular clustering algorithm for clustering numerical data. . It is popular due to its simplicity of understanding and linear algorithmic complexity measure. But it has the serious limitation of clustering numerical only data. Therefore several researchers tried to improve the k mean algorithm to cluster not only numerical but also categorical dataset. In this work an effort have been made to put forward a proposed FCV mean algorithm which is a modified version of the traditional k-mean algorithm and is able to cluster objects having mixed type attributes i.e. numerical and categorical. For categorical data fuzzy set similarity is used and for numerical data differences from maximum dissimilarity is used. Experiment shows that the mixed data are highly clustered with high accuracy compared to other approach in literature. General TermsPattern Recognition

No abstract