This paper describes the enhancement of Power quality in a power system by reducing the harmonics using various modulation techniques in D-STATCOM. D-STATCOM (Distribution Static Compensator) is a shunt device which is generally used for maintaining constant distribution voltage and mitigating harmonics in a distribution network. Voltage Source Converters (VSC) are widely used as a basic component in DSTATCOM. Application of power electronic equipments and nonlinear loads in recent years leads to harmonic interference problems in a power system. The harmonic currents generated by the loads will cause a voltage drop across source impedance which causes decrease in power quality. Converters produce voltage harmonics due to switching operation of power electronic devices. The harmonics in the output voltage of power electronic converters can be reduced using various Pulse-Width Modulation (PWM) switching techniques. In this paper, SPWM,ISPWM,TISPWM,SISPWM switching techniques have been developed for controlling of VSC based inverters which has lower Total Harmonic Distortion (THD) than conventional techniques and they are also used for power quality enhancement

This project presents a novel low-power logic family, called asynchronous fine-grain power-gated logic (AFPL).Each pipeline stage in the AFPL circuit is comprised of efficient charge recovery logic (ECRL) gates, which implement the logic function of the stage, and a handshake controller, which handles handshaking with the neighboring stages and provides power to the ECRL gates which reduces power by using protocols.

For implementing transposed direct-form FIR filters Multiple Constant Multiplications (MCM) are widely used. Constant multiplication methods are widely used for reducing computational complexity of implementation of FIR filters. In MCM the main focus has been on more on common sub expression elimination, the optimization of adder-trees, which sum up the computed sub-expressions for each coefficient, is largely omitted. In this paper it is identified that problem in the scheduling of adder-tree operations for the MCM block, and presented a mixed integer programming (MIP) based algorithm for more efficient MCM-based implementation of FIR filters.

Prediction of exchange rate with large amount data set of attributes values using artificial neural network is more preferable than other techniques. The information processing system of artificial neural network is similar to the biological nervous system of brain like process information. This research is going to make one level ahead prediction of US dollar/ Indian rupee exchange rate. Artificial Neural Network (ANN) is an efficient model to do such kind of Forecasting which works with the Neurons. Basically these Neurons have Learning ability. Artificial neural network have the capability of abstract major useful from huge set of data attributes. This paper brings some type of traditional methods for analysis and forecast currency exchange rate. A methodology is proposed for forecasting US dollar/ Indian rupee exchange rate. In this paper currency exchange rate is going to predict by choosing data of longer period of some parameters whose change in values highly impact the exchange rate and also compare the RMSE, MAPE and MAE values

This research work represents a detailed study of experimental and Computational analysis of properties of the Heat Affected Zone in a Corten A588 steel when it is welded in Gas Metal Arc Welding (GMAW) without the edge preparation process and the ER70S-6 is used as filler wire. The model is subjected to Tensile and Hardness tests to study the effectiveness of the weld under these circumstances. Further, a Finite Element Method analysis is carried out to study the thermal distribution over the model and the deformation caused by the residual stress due to the thermal loads that are applied on the specimen during the welding process. The model is created in CREO and the analysis is carried out in ANSYS.

This project presents built-in testing (BIT) architecture and its implementation for On-Chip Spectral characteristics to analyze with low complexity. It enables the frequency response and harmonic distortion characterizations of an integrated device-under-test (DUT) through reconfigurable coherent sampling rate. This accurate FFT analysis approach is based on coherent sampling, but it requires a significantly smaller number of points to make the FFT realization more suitable for on-chip built-in testing and calibration applications that require area and power efficiency. External analog instrumentation is avoided, reducing test time and cost. The proposed on-chip testing scheme use Fast Fourier Transform (FFT) algorithm with fixed size and a simple signal generator synchronized with a modified ADC resolution and the overall accuracy is limited by the ADCs resolution. A general methodology for the use of this structure in the functional verification of a DUT is also provided. The technique was assessed by comparing the simulation results from the proposed method of single and multiple tones with the simulation results obtained from the FFT of coherently sampled tones. The results indicate that the proper selection of test tone frequencies can avoid spectral leakage even with multiple narrowly spaced tones.

As much as Wireless Sensor Networks (WSNs) have found vast use in all aspects of life, continuous efforts are made every day to make them more energy efficient. Clustering the nodes to avoid redundancy of data is a way to go. Further, numerous routing protocols have been proposed which select optimum path for data routing. In reality, nodes have many levels of energy, thereby constituting a heterogeneous network. We propose and evaluate Enhanced Balanced Energy-Efficient Network Integrated Super Heterogeneous (EBEENISH) Protocol for Wireless Sensor Network. It assumes that WSN has five levels of energy and clusters them into groups accordingly. Node with maximum amount of residual energy within the cluster is elected as a cluster head. The scenario is simulated using MATLAB, and the results clearly show that the protocol we proposed is an improvement on already existing routing protocols. We achieve significant improvement in network lifetime and stability.

Retinal images are useful in several applications, such as in ocular fundus operations as well as in human recognition. The accurate segmentation of the retinal blood vessels is often an essential prerequisite step in the identification of retinal anatomy and pathology. In this study, an automated approach for blood vessel extraction using curvelet transform, guided filtering and multistucture elements morphology is described. Initially, enhancement of the retinal image is carried out using modification of the curvelet transform coefficients. It is found that the fusion of curvelet transform based contrast enhancement result with some other ordinary contrast enhancement technique provides better result. Since the blood vessels are distributed in various directions, morphology processing with multidirectional structuring elements is used to extract the blood vessels from the retinal images. Afterwards, morphological opening by reconstruction using multistructure elements eliminates the ridges not belonging to the vessel tree. An improved filtering operation called guided filtering is used to remove noisy areas. Finally, length filtering is applied using connected component analysis so that all residual ridges are refined from the images. Experimental results show that the blood vessels are extracted from the retinal images with better PSNR and accuracy of about 97%

We owe a great many thanks to a great many people who helped and supported during the writing of this synopsis. My deepest thanks to assistant professor Mr. V N Salke, the Guide of the project for guiding and correcting various documents with attention and care. She has taken pain to go through the project and make necessary correction as and when needed. We express our thanks to the Principal of Padmabhushan Vasantdada Patil Pratishthan’s College of Engineering, for extending his support.