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This paper presents the implementation of space vector pulse width modulation (SVPWM) for a three-phase voltage source inverter (VSI). SVPWM is a technique used to control the output voltage of VSIs with improved efficiency and precision. The abstract outlines the key steps involved in implementing SVPWM, including reference signal clarification, sector identification, determination of voltage vectors, and switching state calculation. This proposed system provides improved output voltage of the inverter, minimized voltage stress across the switches and reduced total harmonic distortion and electromagnetic interference. The proposed implementation aims to enhance the performance of three-phase VSIs in various applications, such as motor drives, renewable energy systems, and power converters. The simulation results of proposed system are verified using MATLAB Simulink. [ABSTRACT FROM AUTHOR]

Disease severity index (DIS) is a way of calculating the percentage of infection spread across the field. The percentage of infection in each leaf has been considered at a time stamp is being calculated and based on that disease, severity of disease spread is analyzed. With the advancement in machine learning and deep learning algorithms in the field of computer vision, identification and classification of diseases is effortless. Percentage of infection in a particular leaf, disease index (DI) is calculated using image processing techniques like Otsu threshold method. With this DI and scales, grading the severity of the infection across the field can be achieved. In this paper various scales used for grading severity of infection namely Horsfall-Barratt (H-B scale) quantitative ordinal scale, Amended 20% ordinal scale, and nearest percent estimates (NPEs) in muskmelon is explored, and based on the empirical results Amended 20% ordinal scale is most efficient method of estimating the DIS is to use the midpoint of the severity scope for each class with twenty percent adjusted to ordinal scale. The results show that the density of leaves is directly proportional to spread of diseases in muskmelon plant. [ABSTRACT FROM AUTHOR]