Habitual Booking System for LPG with Leakage and Fire Sensing Sanctuary

The design of a wireless LPG leakage monitoring system is proposed for home safety. The aim of this paper is to monitor for LPG leakage to avoid fire accidents providing house safety feature where security has been an important issue and alerts the consumer about the leak by SMS and as an emergency measure the system will turn off the power supply, while activating the alarm. In this paper we proposed the additional advantage of the system is that it continuously monitors the level of the LPG present in the cylinder using load sensor and if the gas level reaches below the threshold limit of gas around 2kg so that the user can replace the old cylinder with new in time and automatically books the cylinder using a GSM module. The device ensures safety and prevents suffocation and explosion due to gas leakage. We have also included DC battery in the system to operate even when the power goes off due to the power cut

Analysis of SPWM Technique for Solar Inverter

Reactive power control is necessary to maintain power system stable. In a three phase grid connected PV system, the inverter should regulate the reactive power. Low Voltage Ride Through has to be done to ensure the system stability in fault conditions. Fault current has to be limited. In this paper, we propose a control strategy for grid connected solar PV inverter. The system study is done under LVRT condition. The strategy is based on current loop under single axis dq rotating coordinate system. Grid connected PV systems has a three phase inverter fed by DC-DC converter which will take care of maximum power point. In this project, a 100kW PV system is studied. The entire system is simulated and analysed using MATLAB Simulink software

Towards a Practical Cluster Analysis over Encrypted Data

Cluster analysis is one of the most significant unsupervised machine learning tasks, and it is utilized in various fields associated with privacy issues including bioinformatics, finance and image processing. In this paper, we propose a practical solution for privacy-preserving cluster analysis based on homomorphic encryption~(HE). Our work is the first HE solution for the mean-shift clustering algorithm. To reduce the super-linear complexity of the original mean-shift algorithm, we adopt a novel random sampling method called dust sampling which perfectly fits in HE and achieves the linear complexity. We also substitute non-polynomial kernels by a new polynomial kernel so that it can be efficiently computed in HE. The HE implementation of our modified mean-shift clustering algorithm based on the approximate HE scheme HEAAN shows prominent performance in terms of speed and accuracy. It takes about $30$ minutes with $99\%$ accuracy over several public datasets with hundreds of data, and even for the dataset with $262,144$ data it takes only $82$ minutes applying SIMD operations in HEAAN. Our results outperform the previously best known result (SAC 2018) over $400$ times