Due to usefitlness in recognition and identification biometric systems have become a major part of research. Paper proposes a multimodal biometric system using face modality combined with palm print and palm vein modality. The proposed methodology uses Local Statistical method in which pre-defined block of DCT coefficient were used to calculate standard deviation and store them as feature vector. Matching is done using distance between foature vector of testing and training data set. Results show that the Genuine Acceptance Rate (GAR) of foature level fusion is J 00% which is better than, that of uni-modal systems, hence having multimodality is advantageous. For testing and training database of J 00 students of College of Engineering Pune.

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Nozzle guide vanes (NGVs) at the inlet of the turbine is the first component that comes in contact with the hot gases. Acceleration of hot gases coming from the combustion chamber are done by the convergent shape of vanes. Aim is to get the higher efficiency from turbine by less exhaust gas emission and low fuel consumption. But for higher efficiency engine has to operate at peak temperature. At high temperature nozzle guide vanes can get fails due to thermal stresses induced in it. Leakage or blocking of cooling passages are also the major cause of failure of nozzle guide vanes. The reasons for the thermal failure of NGVs varies the change in temperature. Failure of analysis of NGVs of aero gas turbine engine are discussed.

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Motion estimation algorithms used in video encoders are based on three important issues: selection of good initial search points, choice of appropriate search pattern and effective early termination criteria at different stages in algorithm.Motion vector prediction is also treated as initial search point prediction, in which possibility of good match block is predicted. Prediction is based on prior data from co-located and/or adjacent macroblocks from reference frame or current video frame respectively.Different search patterns contribute in achieving near accurate motion estimation. Different types of motion in real time videos can be tracked using different types of patterns. Early termination criteria at different stages in algorithm, avoid search at further possible locations which are pre-decided by pattern of search. This in turns reduces computations and motion estimation time.Proposed algorithm is combination of two concepts, content awareness and initial point prediction.Contents of video data is in terms of homogeneity coefficients. Initial search point prediction is used to avoid the search trapping into local minima.The algorithm is implemented on Reference Software of JM18.4 of H.264/AVC revised on 5th May 2011. The results of the implemented algorithm show that the total time taken for encoding and motion estimation time are less as compared with other algorithms for the videos of different resolutions.