Search Results

Advanced Stochastic Signal Processing and Computational Methods: Theories and Applications

Description: Compressed sensing has been proposed as a computationally efficient method to estimate the finite-dimensional signals. The idea is to develop an undersampling operator that can sample the large but finite-dimensional sparse signals with a rate much below the required Nyquist rate. In other words, considering the sparsity level of the signal, the compressed sensing samples the signal with a rate proportional to the amount of information hidden in the signal. In this dissertation, first, we emplo… more
Date: August 2022
Creator: Robaei, Mohammadreza

Deep Learning Optimization and Acceleration

Description: The novelty of this dissertation is the optimization and acceleration of deep neural networks aimed at real-time predictions with minimal energy consumption. It consists of cross-layer optimization, output directed dynamic quantization, and opportunistic near-data computation for deep neural network acceleration. On two datasets (CIFAR-10 and CIFAR-100), the proposed deep neural network optimization and acceleration frameworks are tested using a variety of Convolutional neural networks (e.g., L… more
This item is restricted from view until September 1, 2024.
Date: August 2022
Creator: Jiang, Beilei

Helping Students with Upper Limb Motor Impairments Program in a Block-Based Programming Environment Using Voice

Description: Students with upper body motor impairments, such as cerebral palsy, multiple sclerosis, ALS, etc., face challenges when learning to program in block-based programming environments, because these environments are highly dependent on the physical manipulation of a mouse or keyboard to drag and drop elements on the screen. In my dissertation, I make the block-based programming environment Blockly, accessible to students with upper body motor impairment by adding speech as an alternative form of in… more
Date: August 2022
Creator: Okafor, Obianuju Chinonye

Autonomic Zero Trust Framework for Network Protection

Description: With the technological improvements, the number of Internet connected devices is increasing tremendously. We also observe an increase in cyberattacks since the attackers want to use all these interconnected devices for malicious intention. Even though there exist many proactive security solutions, it is not practical to run all the security solutions on them as they have limited computational resources and even battery operated. As an alternative, Zero Trust Architecture (ZTA) has become popula… more
Date: May 2022
Creator: Durflinger, James
open access

New Computational Methods for Literature-Based Discovery

Description: In this work, we leverage the recent developments in computer science to address several of the challenges in current literature-based discovery (LBD) solutions. First, LBD solutions cannot use semantics or are too computational complex. To solve the problems we propose a generative model OverlapLDA based on topic modeling, which has been shown both effective and efficient in extracting semantics from a corpus. We also introduce an inference method of OverlapLDA. We conduct extensive experiment… more
Date: May 2022
Creator: Ding, Juncheng
open access

Design of a Low-Cost Spirometer to Detect COPD and Asthma for Remote Health Monitoring

Description: This work develops a simple and low-cost microphone-based spirometer with a scalable infrastructure that can be used to monitor COPD and Asthma symptoms. The data acquired from the system is archived in the cloud for further procuring and reporting. To develop this system, we utilize an off-the-shelf ESP32 development board, MEMS microphone, oxygen mask, and 3D printable mounting tube to keep the costs low. The system utilizes the MEMS microphone to measure the audio signal of a user's exhalati… more
Date: May 2022
Creator: Olvera, Alejandro
open access

An Investigation of Scale Factor in Deep Networks for Scene Recognition

Description: Is there a significant difference in the design of deep networks for the tasks of classifying object-centric images and scenery images? How to design networks that extract the most representative features for scene recognition? To answer these questions, we design studies to examine the scales and richness of image features for scenery image recognition. Three methods are proposed that integrate the scale factor to the deep networks and reveal the fundamental network design strategies. In our f… more
Date: May 2022
Creator: Qiao, Zhinan

Reliability Characterization and Performance Analysis of Solid State Drives in Data Centers

Description: NAND flash-based solid state drives (SSDs) have been widely adopted in data centers and high performance computing (HPC) systems due to their better performance compared with hard disk drives. However, little is known about the reliability characteristics of SSDs in production systems. Existing works that study the statistical distributions of SSD failures in the field lack insights into distinct characteristics of SSDs. In this dissertation, I explore the SSD-specific SMART (Self-Monitoring, A… more
Date: December 2021
Creator: Liang, Shuwen (Computer science and engineering researcher)
open access

Machine-Learning-Enabled Cooperative Perception on Connected Autonomous Vehicles

Description: The main research objective of this dissertation is to understand the sensing and communication challenges to achieving cooperative perception among autonomous vehicles, and then, using the insights gained, guide the design of the suitable format of data to be exchanged, reliable and efficient data fusion algorithms on vehicles. By understanding what and how data are exchanged among autonomous vehicles, from a machine learning perspective, it is possible to realize precise cooperative perceptio… more
Date: December 2021
Creator: Guo, Jingda
open access

SIMON: A Domain-Agnostic Framework for Secure Design and Validation of Cyber Physical Systems

Description: Cyber physical systems (CPS) are an integration of computational and physical processes, where the cyber components monitor and control physical processes. Cyber-attacks largely target the cyber components with the intention of disrupting the functionality of the components in the physical domain. This dissertation explores the role of semantic inference in understanding such attacks and building resilient CPS systems. To that end, we present SIMON, an ontological design and verification framew… more
Date: December 2021
Creator: Yanambaka Venkata, Rohith

Integrating Multiple Deep Learning Models to Classify Disaster Scene Videos

Description: Recently, disaster scene description and indexing challenges attract the attention of researchers. In this dissertation, we solve a disaster-related multi-labeling task using a newly developed Low Altitude Disaster Imagery dataset. In the first task, we realize video content by selecting a set of summary key frames to represent the video sequence. Through inter-frame differences, the key frames are generated. The key frame extraction of disaster-related video clips is a powerful tool that can e… more
Date: December 2021
Creator: Li, Yuan

Online Testing of Context-Aware Android Applications

Description: This dissertation presents novel approaches to test context aware applications that suffer from a cost prohibitive number of context and GUI events and event combinations. The contributions of this work to test context aware applications under test include: (1) a real-world context events dataset from 82 Android users over a 30-day period, (2) applications of Markov models, Closed Sequential Pattern Mining (CloSPAN), Deep Neural Networks- Long Short Term Memory (LSTM) and Gated Recurrent Units … more
Date: December 2021
Creator: Piparia, Shraddha
open access

Improving Memory Performance for Both High Performance Computing and Embedded/Edge Computing Systems

Description: CPU-memory bottleneck is a widely recognized problem. It is known that majority of high performance computing (HPC) database systems are configured with large memories and dedicated to process specific workloads like weather prediction, molecular dynamic simulations etc. My research on optimal address mapping improves the memory performance by increasing the channel and bank level parallelism. In an another research direction, I proposed and evaluated adaptive page migration techniques that o… more
Date: December 2021
Creator: Adavally, Shashank

COVID-19 Diagnosis and Segmentation Using Machine Learning Analyses of Lung Computerized Tomography

Description: COVID-19 is a highly contagious and virulent disease caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). COVID-19 disease induces lung changes observed in lung computerized tomography (CT) and the percentage of those diseased areas on the CT correlates with the severity of the disease. Therefore, segmentation of CT images to delineate the diseased or lesioned areas is a logical first step to quantify disease severity, which will help physicians predict disease prognosis … more
Date: August 2021
Creator: Mittal, Bhuvan
open access

An Extensible Computing Architecture Design for Connected Autonomous Vehicle System

Description: Autonomous vehicles have made milestone strides within the past decade. Advances up the autonomy ladder have come lock-step with the advances in machine learning, namely deep-learning algorithms and huge, open training sets. And while advances in CPUs have slowed, GPUs have edged into the previous decade's TOP 500 supercomputer territory. This new class of GPUs include novel deep-learning hardware that has essentially side-stepped Moore's law, outpacing the doubling observation by a factor of … more
Date: May 2021
Creator: Hochstetler, Jacob Daniel
open access

An Artificial Intelligence-Driven Model-Based Analysis of System Requirements for Exposing Off-Nominal Behaviors

Description: With the advent of autonomous systems and deep learning systems, safety pertaining to these systems has become a major concern. The existing failure analysis techniques are not enough to thoroughly analyze the safety in these systems. Moreover, because these systems are created to operate in various conditions, they are susceptible to unknown safety issues. Hence, we need mechanisms which can take into account the complexity of operational design domains, identify safety issues other than failu… more
Date: May 2021
Creator: Madala, Kaushik
open access

Hybrid Optimization Models for Depot Location-Allocation and Real-Time Routing of Emergency Deliveries

Description: Prompt and efficient intervention is vital in reducing casualty figures during epidemic outbreaks, disasters, sudden civil strife or terrorism attacks. This can only be achieved if there is a fit-for-purpose and location-specific emergency response plan in place, incorporating geographical, time and vehicular capacity constraints. In this research, a comprehensive emergency response model for situations of uncertainties (in locations' demand and available resources), typically obtainable in lo… more
Date: May 2021
Creator: Akwafuo, Sampson E
open access

IoMT-Based Accurate Stress Monitoring for Smart Healthcare

Description: This research proposes Stress-Lysis, iLog and SaYoPillow to automatically detect and monitor the stress levels of a person. To self manage psychological stress in the framework of smart healthcare, a deep learning based novel system (Stress-Lysis) is proposed in this dissertation. The learning system is trained such that it monitors stress levels in a person through human body temperature, rate of motion and sweat during physical activity. The proposed deep learning system has been trained wit… more
Date: May 2021
Creator: Rachakonda, Laavanya
open access

A Method of Combining GANs to Improve the Accuracy of Object Detection on Autonomous Vehicles

Description: As the technology in the field of computer vision becomes more and more mature, the autonomous vehicles have achieved rapid developments in recent years. However, the object detection and classification tasks of autonomous vehicles which are based on cameras may face problems when the vehicle is driving at a relatively high speed. One is that the camera will collect blurred photos when driving at high speed which may affect the accuracy of deep neural networks. The other is that small objects f… more
Date: December 2020
Creator: Ye, Fanjie

Red Door: Firewall Based Access Control in ROS

Description: ROS is a set of computer operating system framework designed for robot software development, and Red Door, a lightweight software firewall that serves the ROS, is intended to strengthen its security. ROS has many flaws in security, such as clear text transmission of data, no authentication mechanism, etc. Red Door can achieve identity verification and access control policy with a small performance loss, all without modifying the ROS source code, to ensure the availability and authentication of … more
Date: December 2020
Creator: Shen, Ziyi

Combinatorial-Based Testing Strategies for Mobile Application Testing

Description: This work introduces three new coverage criteria based on combinatorial-based event and element sequences that occur in the mobile environment. The novel combinatorial-based criteria are used to reduce, prioritize, and generate test suites for mobile applications. The combinatorial-based criteria include unique coverage of events and elements with different respects to ordering. For instance, consider the coverage of a pair of events, e1 and e2. The least strict criterion, Combinatorial Coverag… more
Date: December 2020
Creator: Michaels, Ryan P.

Frameworks for Attribute-Based Access Control (ABAC) Policy Engineering

Description: In this disseration we propose semi-automated top-down policy engineering approaches for attribute-based access control (ABAC) development. Further, we propose a hybrid ABAC policy engineering approach to combine the benefits and address the shortcomings of both top-down and bottom-up approaches. In particular, we propose three frameworks: (i) ABAC attributes extraction, (ii) ABAC constraints extraction, and (iii) hybrid ABAC policy engineering. Attributes extraction framework compris… more
Date: August 2020
Creator: Alohaly, Manar
open access

Kriging Methods to Exploit Spatial Correlations of EEG Signals for Fast and Accurate Seizure Detection in the IoMT

Description: Epileptic seizure presents a formidable threat to the life of its sufferers, leaving them unconscious within seconds of its onset. Having a mortality rate that is at least twice that of the general population, it is a true cause for concern which has gained ample attention from various research communities. About 800 million people in the world will have at least one seizure experience in their lifespan. Injuries sustained during a seizure crisis are one of the leading causes of death in epilep… more
Date: August 2020
Creator: Olokodana, Ibrahim Latunde

Extracting Dimensions of Interpersonal Interactions and Relationships

Description: People interact with each other through natural language to express feelings, thoughts, intentions, instructions etc. These interactions as a result form relationships. Besides names of relationships like siblings, spouse, friends etc., a number of dimensions (e.g. cooperative vs. competitive, temporary vs. enduring, equal vs. hierarchical etc.) can also be used to capture the underlying properties of interpersonal interactions and relationships. More fine-grained descriptors (e.g. angry, rude,… more
Date: August 2020
Creator: Rashid, Farzana
Back to Top of Screen