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Modeling, Analysis and Control of Reconfigurable Battery/Grid Tied Solar Photo-Voltaic Inverter
Grid reliability and power outages are key concerns today, due to the ever-increasing energy
demand. Traditionally, Uninterruptible Power Supplies (UPS) with battery storage have been
employed to contend with grid outages. ...
Performance improvement of meshless methods for practical time domain electromagnetic analyses.
Solution of Maxwell's equations for practical antennas, filters, waveguides and other
microwave devices requires use of numerical methods. Popular numerical methods include
the finite difference time domain method (FDTD), ...
Hardware Emulation of a Long Transmission Line by High Frequency Power Electronic Converter for the study of Switching Transients
To ensure smooth functioning of the grid, the reliability and robustness of the power
system equipment needs to be precisely evaluated during their development process.
But direct on- eld tests of most of the equipment ...
Robust Algorithms for recovering planted structures in Semi-random instances
In this thesis, we study algorithms for three fundamental graph problems. These are NP-hard problems which have not been understood completely as there is a signifiicant gap between the algorithmic and the hardness fronts ...
First-principles based study of graphene inserted tellurene-metal interface
Atomically thin two-dimensional (2D) materials have attracted extensive research interest
since the journey started with the successful isolation of graphene in 2004. 2D materials have
shown remarkable advancement in the ...
Energy-Efficient Data Fusion Techniques for Wireless Sensor Networks
Wireless sensor networks (WSNs) are finding increasing use in applications such as environmental monitoring, military surveillance, and healthcare due to their low cost and ease of deployment. However, the nodes in a ...
Stochastic Approximation with Markov Noise: Analysis and applications in reinforcement learning
Stochastic approximation algorithms are sequential non-parametric methods for finding a zero
or minimum of a function in the situation where only the noisy observations of the function
values are available. Two time-scale ...
Learning to Adapt Policies for uSD card
Machine Learning(ML) for Systems is a new and promising research area where performance
of computer systems is optimized using machine learning methods. ML for Systems has outperformed
traditional heuristics methods in ...
Achieving Fairness in the Stochastic Multi-Armed Bandit Problem
The classical Stochastic Multi-armed Bandit (MAB) problem provides an abstraction for many
real-world decision making problems such as sponsored-search auctions, crowd-sourcing, wireless
communication, etc. In this work, ...
Experiences in using Reinforcement Learning for Directed Fuzzing
Directed testing is a technique to analyze user-specified target locations in the program. It reduces
the time and effort of developers by excluding irrelevant parts of the program from testing and
focusing on reaching ...