Division of Electrical, Electronics, and Computer Science (EECS): Recent submissions
Now showing items 161-180 of 1278
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Improved Algorithms for Variants of Bin Packing and Knapsack
We study variants of two classical optimization problems: Bin Packing and Knapsack. Both bin packing and knapsack fall under the regime of "Packing and Covering Problems". In bin packing, we are given a set of input items, ... -
Influence of Soil's Electrical Parameters on Lightning Stroke-current Evolution and Fields in the Close Range
The lightning return stroke forms one of the severest natural sources of electromagnetic interference for ground-based and airborne systems. Many physical fields are involved in this complex physical phenomenon. Several ... -
Investigations on Increasing Linear Modulation Range in Hybrid Multilevel Inverter Fed Induction Machine Drives Regardless of Load Power Factor
Nowadays, multilevel inverters (MLIs) have become a promising alternative to the twolevel inverter in medium voltage high-power applications such as motor drives, active power filters, HVDC, electric vehicles, wind, and ... -
Nonlinear Optical Enhancement Studies in Silicon-based Resonant Metasurfaces
Metasurfaces are two dimensional arrangements of building blocks called meta-atoms which have been found to be useful to manipulate amplitude, phase, polarization of light at the nanoscale. Using these properties, functional ... -
Inverse Problems in 3D Full-wave Electromagnetics
An inverse problem in Electromagnetics (EM) refers to the process of reconstructing the physical system by processing the measured data of its electromagnetic properties. Inverse problems are typically ill-posed, and this ... -
Development of Microneedles for Transdermal and Intradermal Drug Delivery
Transdermal drug delivery has an enormous potential for painless therapeutics. Many drugs designed for systemic action are more efficient when delivered through the skin compared to oral administration as their degradation ... -
Performance Characterization and Optimizations of Traditional ML Applications
Even in the era of Deep Learning based methods, traditional machine learning methods with large data sets continue to attract significant attention. However, we find an apparent lack of a detailed performance characterization ... -
Operating System Support for Efficient Virtual Memory
Computers rely on the virtual memory abstraction to simplify programming, portability, physical memory management and ensure isolation among co-running applications. However, it creates a layer of indirection in the ... -
Perceptual Quality Assessment of Lowlight Restored and Authentically Distorted Images
The capability of hand-held devices to acquire high-definition visual content has led to a tremendous increase in the number of images and videos captured daily. However, camera hardware and pipelines are not perfect and ... -
Explainable and Efficient Neural Models for Natural Language to Bash Command Translation
One of the key goals of Natural Language Processing is to make computers understand natural language. Semantic Parsing has been one of the driving tasks for Natural Language Understanding. It is formally defined as the ... -
Wideband Microstrip Patch Antennas and their Modifications for Practical Applications
Printed antennas play an significant role in satellite, mobile, and other wireless communications networks, military systems and several more emerging applications in- cluding radar sensing and imaging. Several of these ... -
Compression for Distributed Optimization and Timely Updates
The goal of this thesis is to study the compression problems arising in distributed computing systematically. In the first part of the thesis, we study gradient compression for distributed first-order optimization. We ... -
Design of Non-Cartesian k-space Trajectories for Reduced Scan Time in Magnetic Resonance Imaging Systems
Magnetic resonance imaging (MRI) is a non-invasive and safe medical imaging technique. This imaging modality collects samples in the Fourier domain, called as the k-space. The k-space is traversed along continuous trajectories ... -
Machine Learning for Decoding Imagined words and Altered State of Consciousness from EEG
In the first part of the thesis, the results of our studies on the classification of phonological categories in imagined words are presented. We have investigated whether there are any statistically significant differences ... -
Graph Neural Networks with Parallel Local Neighborhood Aggregations
Graph neural networks (GNNs) have become very popular for processing and analyzing graph-structured data in the last few years. Using message passing as their basic building blocks that aggregate information from neighborhoods, ... -
Topics on Safety and Security of Power Systems
In this thesis, we investigate some of the problems concerning the safety and security of power systems. Since the operational safety of the power system itself is a vast area of research, we choose to investigate the ... -
Hardware-based Device Identification for Systems with Commercially Off-the-shelf Components
The Identity of an electronic device is a fundamental property, that bootstraps several applications such as authentication and traceability. For the purpose of device identification, conventional methods generate a unique ... -
Tailoring excitonic complexes in layered materials
Layered transition metal dichalcogenides (TMDCs) host a variety of strongly bound exciton complexes that control the optical properties in these materials. Apart from spin and valley, layer index provides an additional ... -
Medium Index Contrast Guided Mode Resonant Structures for Photonic Applications in the Visible-Near Infrared Wavelength Regime
Guided mode resonant (GMR) structures are interesting from the point of view of enhanced light-matter interaction and find applications in sensing, filtering, and miniaturized photonic components. The Guided mode resonance ... -
Reinforcement Learning in Large and Structured Environments
In a reinforcement learning (RL) problem, a learner takes actions to control the state of an initially unknown environment so as to maximize the sum of the rewards he obtains. This has several applications in many practical ...