Background: In a parallel processor, the pipeline cannot fetch the conditional instructions with the next clock cycle, leading to a pipeline stall. So, conditional instructions create a problem in the pipeline because the proper path can only be known after the branch execution. To accurately predict branches, a significant predictor is proposed for the prediction of conditional branch instruction. Method: In this paper, a single branch prediction and a correlation branch prediction scheme are applied to the different trace files by using the concept of saturating counters. Further, a hybrid branch prediction scheme is proposed, which uses both global and local branch information, providing more accuracy than the single and correlation branch prediction schemes. Results: Firstly, a single branch prediction and correlation branch prediction technique are applied to the trace files using saturating counters. By comparison, it can be observed that a correlation branch prediction technique provides better results by enhancing the accuracy rate of 2.25% than the simple branch prediction. Further, a hybrid branch prediction scheme is proposed, which uses both global and local branch information, providing more accuracy than the single and correlation branch prediction schemes. The obtained results suggest that the proposed hybrid branch prediction schemes provide an increased accuracy rate of 3.68% and 1.43% than single branch prediction and correlation branch prediction. Conclusion: The proposed hybrid branch prediction scheme gives a lower misprediction rate and higher accuracy rate than the simple branch prediction scheme and correlation branch prediction scheme.

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Image compression is one of the best method which can reduce the storage space of images, videos and helpful to increase storage space and transmission process's performance. With pace of time medical imaging it become one of the most crucial sub-fields in the world of science and technology and Medical images are used to diagnose a variety of illness can't make any compromise in the quality. Developing some new algorithm and with the help of various de-noising method plays a major role in image processing. In this paper, Discrete wavelet transform(DWT) image decomposed into eight subbands and after that bilateral filter and thresholding methods are used. In this research work using second level DWT is used and approximation coefficient are obtained from DWT filtered using bilateral filter and the detail coefficients are subjected to Wavelet Thresholding. Image is reconstructed by the inverse wavelet transform(IDWT) of the resultant coefficients and the filtered using bilateral filter. Use of IDWT twice as using second level DWT in process and its main motive to achieve better result as compared to base paper. Various types of images Can use as datasets for quantitative validation. The Peak Signal to Noise Ratio (PSNR), Mean square error (MSE) parameters are calculated with respect to bilateral parameters

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An optimization program is employed to design the inter-digital transducer (IDT) structure of the surface acoustic wave (SAW) transducer to aim at improvement in the transducer characteristics and to improve the frequency response of SAW filter. In this paper, Genetic algorithm is used to optimize the response of a SAW filter. Then, the comparison of the response of SAW filter is done by using GA and without GA. The goal of optimization is to find best value for each variable in order to achieve minima or maxima of an objective function within the given constraints. In present study, three design variables of SAW filter i.e. number of finger pairs in input IDT (Np 1 ), number of finger pairs in `output IDT (Np 2 ), center to center distance between two electrodes in a finger pair (d), are optimized. After getting the optimized parameters of SAW filter, the frequency response of bandpass SAW filter is obtained, which is better as compared to the frequency response of SAW filter getting from other methods in terms of bandwidth and ripples amplitude.