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Evaluating Stack Overflow Usability Posts in Conjunction with Usability Heuristics

Description: This thesis explores the critical role of usability in software development and uses usability heuristics as a cost-effective and efficient method for evaluating various software functions and interfaces. With the proliferation of software development in the modern digital age, developing user-friendly interfaces that meet the needs and preferences of users has become a complex process. Usability heuristics, a set of guidelines based on principles of human-computer interaction, provide a starti… more
This item is restricted from view until June 1, 2024.
Date: May 2023
Creator: Jalali, Hamed

Multiomics Data Integration and Multiplex Graph Neural Network Approaches

Description: With increasing data and technology, multiple types of data from the same set of nodes have been generated. Since each data modality contains a unique aspect of the underlying mechanisms, multiple datatypes are integrated. In addition to multiple datatypes, networks are important to store information representing associations between entities such as genes of a protein-protein interaction network and authors of a citation network. Recently, some advanced approaches to graph-structured data leve… more
This item is restricted from view until June 1, 2025.
Date: May 2023
Creator: Kesimoglu, Ziynet Nesibe

Toward Leveraging Artificial Intelligence to Support the Identification of Accessibility Challenges

Description: The goal of this thesis is to support the automated identification of accessibility in user reviews or bug reports, to help technology professionals prioritize their handling, and, thus, to create more inclusive apps. Particularly, we propose a model that takes as input accessibility user reviews or bug reports and learns their keyword-based features to make a classification decision, for a given review, on whether it is about accessibility or not. Our empirically driven study follows a mixture… more
Date: May 2023
Creator: Aljedaani, Wajdi Mohammed R M., Sr.

Integrating Multiple Deep Learning Models for Disaster Description in Low-Altitude Videos

Description: Computer vision technologies are rapidly improving and becoming more important in disaster response. The majority of disaster description techniques now focus either on identify objects or categorize disasters. In this study, we trained multiple deep neural networks on low-altitude imagery with highly imbalanced and noisy labels. We utilize labeled images from the LADI dataset to formulate a solution for general problem in disaster classification and object detection. Our research integrated an… more
Date: December 2022
Creator: Wang, Haili
open access

Machine Learning Methods for Data Quality Aspects in Edge Computing Platforms

Description: In this research, three aspects of data quality with regard to artifical intelligence (AI) have been investigated: detection of misleading fake data, especially deepfakes, data scarcity, and data insufficiency, especially how much training data is required for an AI application. Different application domains where the selected aspects pose issues have been chosen. To address the issues of data privacy, security, and regulation, these solutions are targeted for edge devices. In Chapter 3, two so… more
Date: December 2022
Creator: Mitra, Alakananda

Registration of Point Sets with Large and Uneven Non-Rigid Deformation

Description: Non-rigid point set registration of significantly uneven deformations is a challenging problem for many applications such as pose estimation, three-dimensional object reconstruction, human movement tracking. In this dissertation, we present a novel probabilistic non-rigid registration method to align point sets with significantly uneven deformations by enforcing constraints from corresponding key points and preserving local neighborhood structures. The registration method is treated as a densit… more
This item is restricted from view until January 1, 2025.
Date: December 2022
Creator: Maharjan, Amar Man
open access

Reliability and Throughput Improvement in Vehicular Communication by Using 5G Technologies

Description: The vehicular community is moving towards a whole new paradigm with the advancement of new technology. Vehicular communication not only supports safety services but also provides non-safety services like navigation support, toll collection, web browsing, media streaming, etc. The existing communication frameworks like Dedicated Short Range Communication (DSRC) and Cellular V2X (C-V2X) might not meet the required capacity in the coming days. So, the vehicular community needs to adopt new technol… more
Date: December 2022
Creator: Dey, Utpal-Kumar

Secure and Decentralized Data Cooperatives via Reputation Systems and Blockchain

Description: This dissertation focuses on a novel area of secure data management referred to as data cooperatives. A data cooperative solution promises its users better protection and control of their personal data as compared to the traditional way of their handling by the data collectors (such as governments, big data companies, and others). However, despite the many interesting benefits that the data cooperative approach tends to provide its users, it suffers from a few challenges hindering its developme… more
This item is restricted from view until January 1, 2025.
Date: December 2022
Creator: Salau, Abiola

Understanding and Addressing Accessibility Barriers Faced by People with Visual Impairments on Block-Based Programming Environments

Description: There is an increased use of block-based programming environments in K-12 education and computing outreach activities to introduce novices to programming and computational thinking skills. However, despite their appealing design that allows students to focus on concepts rather than syntax, block-based programming by design is inaccessible to people with visual impairments and people who cannot use the mouse. In addition to this inaccessibility, little is known about the instructional experience… more
Date: December 2022
Creator: Mountapmbeme, Aboubakar

Understanding and Reasoning with Negation

Description: In this dissertation, I start with an analysis of negation in eleven benchmark corpora covering six Natural Language Understanding (NLU) tasks. With a thorough investigation, I first show that (a) these benchmarks contain fewer negations compared to general-purpose English and (b) the few negations they contain are often unimportant. Further, my empirical studies demonstrate that state-of-the-art transformers trained using these corpora obtain substantially worse results with the instances that… more
This item is restricted from view until January 1, 2025.
Date: December 2022
Creator: Hossain, Md Mosharaf

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

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
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

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

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
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

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

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

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

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
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