Division of Electrical, Electronics, and Computer Science (EECS): Recent submissions
Now showing items 301-320 of 1311
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Checking Observational Purity of Procedures
We provide two static analysis approaches(using theorem proving) that check if a given (recursive) procedure behaves as if it were stateless, even when it maintains state in global variables. In other words, we check if ... -
Bayesian Techniques for Joint Sparse Signal Recovery: Theory and Algorithms
This thesis contributes new theoretical results, solution concepts, and algorithms concerning the Bayesian recovery of multiple joint sparse vectors from noisy and underdetermined linear measurements. The thesis is written ... -
Price of Privacy of Smart Meter Data
Smart meter data can be used by the utility for billing the consumers timely along with power theft detection, demand side management, distribution network planning, consumer segmentation, load forecasting, fault detection, ... -
Disruptive Approaches to Address Performance & Reliability Challenges in 2-Dimentional (2D) Material Based Transistors & Memories
In 2020, Apple introduced its most advanced laptop that has the A14 Bionic processor. The very first processor, Intel’s 4004, was launched in 1971 and had a transistor (the basic building block of a processor) density of ... -
Design and Evaluation of Parallel Coded Systems
In this computer era, we all live in a place where the demand for data and computing is increasing day by day. Since the need for faster data retrieval and faster computation brings us a reliability as the solution, we ... -
Design of Privacy Protection Schemes for Mobile Adhoc Networks using Rough Set Theory
MANET is a self-con guring, decentralized and infrastructure-less mobile wireless network, where autonomous mobile nodes (such as laptops, smartphones, sensors, etc.) communicate over the wireless channels. Thus, MANETs ... -
Synthesis of Conformal Antenna Arrays on Polygonal Cross-Sectional Cylindrical Conductors for 360 Degree Azimuth Coverage Applications
Antenna arrays are one of the most important part of any RF communications system nowadays. Ranging from military to communication applications, the versatility they provide in selectively enhancing and rejecting signals ... -
Design and Analysis of Full-duplex Systems for Next-generation Wireless Communication Systems
To cater to the ever-growing demand for higher data rates, cellular networks and wireless local area networks (WLANs) need to adopt innovative technologies. Full-duplex (FD) is one such technology that promises to double ... -
nuKSM: NUMA-aware Memory De-duplication for Multi-socket Servers
An operating system's memory management has multiple goals, e.g. reducing memory access latencies, reducing memory footprint. These goals can conflict with each other when independent subsystems optimize them in silos. ... -
Design and Development of Opto-ThermoAcoustic (OTA) Measurement System to Differentiate Cancer from Adjacent Normal Breast Biopsy Tissue
Breast cancer is the most common cancer accounting for almost 11.7% of all cancer incidences and 6.9% of cancer-related deaths globally in 2020, as per Globocan 2020 report. Diagnosis of breast cancer requires microscopic ... -
Solving Inverse Problems Using a Deep Generative Prior
In an inverse problem, the objective is to recover a signal from its measurements, given the knowledge of the measurement operator. In this thesis, we address the problems of compressive sensing (CS) and compressive phase ... -
A Novel Neural Network Architecture for Sentiment-oriented Aspect-Opinion Pair Extraction
Over the years, fine-grained opinion mining in online reviews has received great attention from the NLP research community. It involves different tasks such as Aspect Term Extraction (ATE), Opinion Term Extraction (OTE), ... -
Addressing Energy and Performance Related Challenges in Networked Embedded Systems
Networked Embedded Systems comprise of spatially and functionally distributed nodes that are interconnected with one another and with the environment to achieve certain goals. The nodes are connected to one another through ... -
Approximation Algorithms for Geometric Packing Problems
We study approximation algorithms for the geometric bin packing problem and its variants. In the two-dimensional geometric bin packing problem (2D GBP), we are given n rectangular items and we have to compute an axis-parallel ... -
A Framework for Privacy-Compliant Delivery Drones
We present Privaros, a framework to enforce privacy policies on drones. Privaros is designed for commercial delivery drones, such as the ones that will likely be used by Amazon Prime Air. Such drones visit a number of host ... -
Locally Reconstructable Non-malleable Secret Sharing
Non-malleable secret sharing (NMSS) schemes, introduced by Goyal and Kumar (STOC 2018), ensure that a secret m can be distributed into shares m1,...,mn (for some n), such that any t (a parameter <= n) shares can be ... -
Structured Sparse Signal Recovery for mmWave Channel Estimation: Intra-vector Correlation and Modulo Compressed Sensing
This thesis contributes new theoretical results and recovery algorithms for the area of sparse signal recovery motivated by applications to the problem of channel estimation in mmWave communication systems. The presentation ... -
Scaling Blockchains Using Coding Theory and Verifiable Computing
The issue of scalability has been restricting blockchain from its widespread adoption. The current transaction rate of bitcoin is around seven transactions/second while its size has crossed the 300 GB mark. Although many ... -
New Algorithmic and Hardness Results in Learning, Error Correcting Codes and Constraint Satisfaction Problems
Approximation algorithms are a natural way to deal with the intractability barrier that is inherent in many naturally arising computational problems. However, it is often the case that the task of solving the approximation ... -
Knowledge-driven training of deep models for better reconstruction and recognition
This thesis aims to efficiently solve many interesting and challenging problems by incorporating appropriate image processing techniques in a deep learning framework. We have proposed, implemented and tested efficient ...