Multi input-multi output Power electronic interface for hybrid energy resources has gathered much of interest. In this paper, a new configuration for cascade connection of two Z-Impedance networks is presented which is able to extract power from two separate low voltage energy sources such as photovoltaic panels and fuel cell stacks. The required load power can be shared between two sources which may have different low values. The power sharing is controlled by adjusting the shoot through duration and time shifting. The proposed converter includes the features of conventional Z-source converter such as voltage boost and shoot through immunity of the inverter. Steady state operation principles, switching methods and the main relations for power flow from two inputs to the output are derived. A prototype of the converter is built and tested for different operation modes. The results are compared with simulations and theoretical analysis which verify well performance of the system.
With the outbreak and popularity of COVID-19 pandemic worldwide, the volume of patients is increasing rapidly all over the world, which brings a big risk and challenge for the maintenance of public healthcare. In this situation, quick integration and analysis of the medical records of patients in a cloud platform are of positive and valuable significance for accurate recognition and scientific diagnosis of the healthy conditions of potential patients. However, due to the big volume of medical data of patients distributed in different platforms (e.g., multiple hospitals), how to integrate these data for patient clustering and analysis in a time-efficient and scalable manner in cloud platform is still a challenging task, while guaranteeing the capability of privacy-preservation. Motivated by this fact, a time-efficient, scalable and privacy-guaranteed patient clustering method in cloud platform is proposed in this work. At last, we demonstrate the competitive advantages of our method via a set of simulated experiments. Experiment results with competitive methods in current research literatures have proved the feasibility of our proposal.
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