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Designing a highly efficient patient care and monitoring system which can handle multiple patients and multiple parametric measurements from every single patient in real time will lead in improvising the data handling capability at Central Nurse Stations (CNS) and Decentralized Nurse Stations (DCNS). The Bio signal Data Acquisition Systems have been designed to suit patients located at CNS and DCNS in a hospital. The RTL design of Bio signal Data Acquisition System was successfully simulated using Model sim. The design was placed and routed using Xilinx ISE 8.2i tool and the bit stream generated is used for downloading into the targeted FPGA. The FPGA used is XC3S400-5ft256, common for both schemes shown. At 50 MHz operation, the system is capable of wireless communication of 32 numbers of Bio signals up to 400,000 bits/s although the maximum frequency of operation of this design is 89 MHz reported by Xilinx ISE tool. This system is truly upgradeable, be it in extending the capabilities to more number of patients or in improving throughput.

There has been a focus on developing image indexing techniques which have the capability to retrieve image based on their contents. The main feature extraction methods are content Based Image Retrieval (CBIR) also known as query by Image content (QBIC). This paper presents a technique to derive the colors, shapes, textures, or any other information that can be derived from a satellite image Using Texture filters and realizing it with artificial neural networks. This image processing technique are been utilized to identify important urban features such as buildings and gardens and rural features such as natural vegetation, water bodies, and fields. Textures are represented by Texel, which are then placed into a number of sets, depending on how many textures are detected in the image.