The work proposed in this paper focuses on providing an effective solution to shortage of power in rural areas with an effective technique implemented in an economically feasible way. The traditional Inverters used for either residential or commercial purposes consume electrical energy from the grid to fulfill the charging and discharging of the battery, which may lead to overloading. The shortcomings of the traditional inverters such as Non-Renewable nature of power sources, increased cost of manufacturing, and multi-stage conversion complexity, are considered by the researchers for improvement. As a result, an attempt has been made to provide a cost effective renewable energy system with single stage topology for AC power applications. Single stage power conversion with allowed shoot through state is used here to avoid additional components and reduce the switching losses. Unlike the traditional inverters, the Quasi Impedance Source Inverter that is brought forward can be utilized as a Standalone system or a capable backup at the time of power outages. Sinusoidal pulse width modulation (SPWM) is applied to attain reduced harmonics which are measured by observing the harmonic pattern in Total Harmonic Distortion (THD) curve. The lab results obtained through MATLAB simulation confirm the noteworthy diminution of THD level in the proposed system compared to the reported one. Usage of Photovoltaic (PV) Panel to tap energy with reduced stochastic fluctuations due to high filtering capacity of the proposed circuit, eliminating the need of additional filters, is the uniqueness of this technique.

The work proposed in this paper focuses on providing an effective solution to shortage of power in rural areas with an effective technique implemented in an economically feasible way. The traditional Inverters used for either residential or commercial purposes consume electrical energy from the grid to fulfill the charging and discharging of the battery, which may lead to overloading. The shortcomings of the traditional inverters such as Non-Renewable nature of power sources, increased cost of manufacturing, and multi-stage conversion complexity, are considered by the researchers for improvement. As a result, an attempt has been made to provide a cost effective renewable energy system with single stage topology for AC power applications. Single stage power conversion with allowed shoot through state is used here to avoid additional components and reduce the switching losses. Unlike the traditional inverters, the Quasi Impedance Source Inverter that is brought forward can be utilized as a Standalone system or a capable backup at the time of power outages. Sinusoidal pulse width modulation (SPWM) is applied to attain reduced harmonics which are measured by observing the harmonic pattern in Total Harmonic Distortion (THD) curve. The lab results obtained through MATLAB simulation confirm the noteworthy diminution of THD level in the proposed system compared to the reported one. Usage of Photovoltaic (PV) Panel to tap energy with reduced stochastic fluctuations due to high filtering capacity of the proposed circuit, eliminating the need of additional filters, is the uniqueness of this technique.

Cardio vascular disease threatens human life with higher mortality rate. Therefore it is quite important to monitor. An arrhythmia is an abnormal heart beat and rhythm which causes the disease. The best tool to find the heart rhythm of heart is Electro Cardiogram (ECG) which provides information about the different types of arrhythmias. This paper aims at proposing an automatic framework by employing multi-domain features to classify ECG signals. Proposed work uses optimum method of feature selection to improvise the efficiency of the classification process. A hybrid optimization algorithm is used for feature selection and proposed to optimize the parameters of the existing Support Vector Machine (SVM) classifier. Proposed hybrid optimization algorithm was developed using Particle Swarm Optimization (PSO) and Migration Modified Biogeography Based Optimization (MMBBO) algorithm. Algorithm provides an improved solution to the optimizing the parameters of ECG signals. Results are evaluated by implementing in MATLAB software and the performance is justified with comparative analysis. The proposed framework enhances the process of automatic prediction of various arrhythmias or rhythm abnormalities which performs in gaining better accuracy. For data sets, the average classification accuracy of this method is 97.89%. This result is an improvement of 4–5% over the comparison of other methods.