Informatics Publishing Limited

J. Rajeswari ¹, S. P. Umayal ¹

Affiliations
1 Sethu Institute of Technology, Virudhunagar, IN

Abstract

In the present existing power scenario to meet out the demand, multi-level inverter technology has emerged recently as a very important alternative in the area of high-power medium-voltage applications. This paper presents a complementary switching multi-level inverter using wave shift modulation control technique which combines both the level shift and phase shift modulation techniques. A 31 level inverter is designed to increase the quality of the output waveform to sinusoidal. This complementary switching reduces the number of switches thus reducing losses and total harmonic distortion (THD) in comparison with conventional multi-carrier based pulse width modulation (PWM) schemes, phase-shift (PSHM) and level-shift (LSHM) modulations. To analyze the performance of proposed technique, a 31 Level cascaded multi-level inverter is designed and simulated. In this new topology half H-bridge multilevel inverter with binary logic is used to achieve 2n levels per leg. THD and efficiency of the proposed technique is analyzed for 2kw MLI. The proposed concept is verified by using MatLab/Simulink.

Keywords

Wave Shift Multi Carrier Modulation, Complementary Switching, Cascade Multilevel Inverter, Binary Logic.

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J. Rajeswari

Abstract

The project presents multi focus image fusion using stationary wavelet transform with local directional pattern and spatial frequency analysis. Multi focus image fusion in wireless visual sensor networks is a process of fusing two or more images to obtain a new one which contains a more accurate description of the scene than any of the individual source images. In this project, the proposed model utilizes the multi scale decomposition done by stationary wavelet transform for fusing the images in its frequency domain. It decomposes an image into two different components like structural and textural information. It doesn’t down sample the image while transforming into frequency domain. So it preserves the edge texture details while reconstructing image from its frequency domain. It is used to reduce the problems like blocking, ringing artifacts occurs because of DCT and DWT.

Keywords

DWT, Spatial Frequency, MRI and CT

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A. Saranya ¹, J. Rajeswari ¹

Affiliations
1 Department of Information Technology, Adhiparasakthi Engineering College, IN

Abstract

Predicting college and school dropouts is a major problem in educational system and has complicated challenge due to data imbalance and multi dimensionality, which can affect the low performance of students. In this paper, we have collected different database from various colleges, among these 500 best real attributes are identified in order to identify the factor that affecting dropout students using neural based classification algorithm and different mining technique are implemented for data processing. We also propose a Dropout Prediction Algorithm (DPA) using fuzzy logic and Logistic Regression based inference system because the weighted average will improve the performance of whole system. We are experimented our proposed work with all other classification systems and documented as the best outcomes. The aggregated data is given to the decision trees for better dropout prediction. The accuracy of overall system 98.6% it shows the proposed work depicts efficient prediction.

Keywords

Data Mining, Fuzzy Inference System, Logistic Regression, Decision Trees, Student Dropout.

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