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A Modified Circular Patch Antenna for 4.8 GHz Wi Fi Applications
The necessity for wireless devices is increasing day by day for both personal and business applications. This also increases the need for research in designing and developing advanced communication devices, especially antennas. Therefore, in this paper modified circular patch antenna is presented for 4.8 GHz Wi-Fi applications. In this research work FR4 substrate with dielectric permittivity of 4.4 and height of the substrate is 1.6 mm is used for manufacturing the proposed antenna. The proposed antenna has a novel modified circular patch structure made of copper material. The proposed antenna has 40 mm length and 30 mm width dimension. The proposed antenna is designed and developed with an integral based solver simulation software called CST Microwave studio v2020 and obtained VSWR < 1.5, Return loss of -27.93 dB and Bandwidth of 260 MHz, gain of 5.78 dBi. The proposed antenna is well suitable for 4.8 GHz Wi-Fi applications.
An Effective Content – Based Image Retrieval Classification Techniques for Medical Images Based on Neural Network and Fuzzy Algorithm
C RAMESH BABU DURAI
Medical information systems are going to play an important role in clinically related decisions in future by rendering similar pathological conditions in a medical image and thereby helping physicians view noteworthy images to form improved decisions. In human perception, the Content Based Image Retrieval (CBIR) can be used to replace the conventional method of text based retrieval systems. The image content contains number of dominant important characteristics like color, texture, shape etc. All these features to be analyzed on the content basis for the classification purpose. These different descriptor or characteristics for the images can form a combined feature vector. Content-Based Image Retrieval (CBIR) consists of retrieving the most visually similar images to a given query image from a database of images. CBIR is used to retrieve images successfully from the databases based on an input query, which could be either an anatomical region or a pathological image. Methods suggested for CBIR include features of low-level image like color, histogram, texture and analysis in the frequency domain. To predict optimum performance characteristics and to minimize the feature dimensionality for making system real-time, for selecting the feature based on Genetic Algorithm (GA) may be used. To improve the system's retrieval performance, multi- feature similarity score is expected. In this work the Neural network and Genetic Algorithm are applied for the classification of images and produces good comparison result in compared with other classification process.