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open access

Framework for Evaluating Dynamic Memory Allocators Including a New Equivalence Class Based Cache-conscious Allocator

Description: Software applications’ performance is hindered by a variety of factors, but most notably by the well-known CPU-memory speed gap (often known as the memory wall). This results in the CPU sitting idle waiting for data to be brought from memory to processor caches. The addressing used by caches cause non-uniform accesses to various cache sets. The non-uniformity is due to several reasons, including how different objects are accessed by the code and how the data objects are located in memory. Memor… more
Date: August 2013
Creator: Janjusic, Tomislav
open access

Automated Real-time Objects Detection in Colonoscopy Videos for Quality Measurements

Description: The effectiveness of colonoscopy depends on the quality of the inspection of the colon. There was no automated measurement method to evaluate the quality of the inspection. This thesis addresses this issue by investigating an automated post-procedure quality measurement technique and proposing a novel approach automatically deciding a percentage of stool areas in images of digitized colonoscopy video files. It involves the classification of image pixels based on their color features using a new… more
Date: August 2013
Creator: Kumara, Muthukudage Jayantha
open access

Detection of Temporal Events and Abnormal Images for Quality Analysis in Endoscopy Videos

Description: Recent reports suggest that measuring the objective quality is very essential towards the success of colonoscopy. Several quality indicators (i.e. metrics) proposed in recent studies are implemented in software systems that compute real-time quality scores for routine screening colonoscopy. Most quality metrics are derived based on various temporal events occurred during the colonoscopy procedure. The location of the phase boundary between the insertion and the withdrawal phases and the amount … more
Date: August 2013
Creator: Nawarathna, Ruwan D.
open access

Design and Analysis of Novel Verifiable Voting Schemes

Description: Free and fair elections are the basis for democracy, but conducting elections is not an easy task. Different groups of people are trying to influence the outcome of the election in their favor using the range of methods, from campaigning for a particular candidate to well-financed lobbying. Often the stakes are too high, and the methods are illegal. Two main properties of any voting scheme are the privacy of a voter’s choice and the integrity of the tally. Unfortunately, they are mutually exclu… more
Date: December 2013
Creator: Yestekov, Yernat
open access

Real-time Rendering of Burning Objects in Video Games

Description: In recent years there has been growing interest in limitless realism in computer graphics applications. Among those, my foremost concentration falls into the complex physical simulations and modeling with diverse applications for the gaming industry. Different simulations have been virtually successful by replicating the details of physical process. As a result, some were strong enough to lure the user into believable virtual worlds that could destroy any sense of attendance. In this research, … more
Date: August 2013
Creator: Amarasinghe, Dhanyu Eshaka
open access

Simulating the Spread of Infectious Diseases in Heterogeneous Populations with Diverse Interactions Characteristics

Description: The spread of infectious diseases has been a public concern throughout human history. Historic recorded data has reported the severity of infectious disease epidemics in different ages. Ancient Greek physician Hippocrates was the first to analyze the correlation between diseases and their environment. Nowadays, health authorities are in charge of planning strategies that guarantee the welfare of citizens. The simulation of contagion scenarios contributes to the understanding of the epidemic beh… more
Date: December 2013
Creator: Gomez-Lopez, Iris Nelly
open access

Boosting for Learning From Imbalanced, Multiclass Data Sets

Description: In many real-world applications, it is common to have uneven number of examples among multiple classes. The data imbalance, however, usually complicates the learning process, especially for the minority classes, and results in deteriorated performance. Boosting methods were proposed to handle the imbalance problem. These methods need elongated training time and require diversity among the classifiers of the ensemble to achieve improved performance. Additionally, extending the boosting method to… more
Date: December 2013
Creator: Abouelenien, Mohamed
open access

Scalable Next Generation Blockchains for Large Scale Complex Cyber-Physical Systems and Their Embedded Systems in Smart Cities

Description: The original FlexiChain and its descendants are a revolutionary distributed ledger technology (DLT) for cyber-physical systems (CPS) and their embedded systems (ES). FlexiChain, a DLT implementation, uses cryptography, distributed ledgers, peer-to-peer communications, scalable networks, and consensus. FlexiChain facilitates data structure agreements. This thesis offers a Block Directed Acyclic Graph (BDAG) architecture to link blocks to their forerunners to speed up validation. These data block… more
Date: July 2023
Creator: Alkhodair, Ahmad Jamal M
open access

Improving Communication and Collaboration Using Artificial Intelligence: An NLP-Enabled Pair Programming Collaborative-ITS Case Study

Description: This dissertation investigates computational models and methods to improve collaboration skills among students. The study targets pair programming, a popular collaborative learning practice in computer science education. This research led to the first machine learning models capable of detecting micromanagement, exclusive language, and other types of collaborative talk during pair programming. The investigation of computational models led to a novel method for adapting pretrained language model… more
Date: July 2023
Creator: Ubani, Solomon
open access

A Platform for Aligning Academic Assessments to Industry and Federal Job Postings

Description: The proposed tool will provide users with a platform to access a side-by-side comparison of classroom assessment and job posting requirements. Using techniques and methodologies from NLP, machine learning, data analysis, and data mining: the employed algorithm analyzes job postings and classroom assessments, extracts and classifies skill units within, then compares sets of skills from different input volumes. This effectively provides a predicted alignment between academic and career sources, b… more
Date: July 2023
Creator: Parks, Tyler J.

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.

Deep Learning Methods to Investigate Online Hate Speech and Counterhate Replies to Mitigate Hateful Content

Description: Hateful content and offensive language are commonplace on social media platforms. Many surveys prove that high percentages of social media users experience online harassment. Previous efforts have been made to detect and remove online hate content automatically. However, removing users' content restricts free speech. A complementary strategy to address hateful content that does not interfere with free speech is to counter the hate with new content to divert the discourse away from the hate. In … more
This item is restricted from view until June 1, 2025.
Date: May 2023
Creator: Albanyan, Abdullah Abdulaziz

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

Blockchain for AI: Smarter Contracts to Secure Artificial Intelligence Algorithms

Description: In this dissertation, I investigate the existing smart contract problems that limit cognitive abilities. I use Taylor's serious expansion, polynomial equation, and fraction-based computations to overcome the limitations of calculations in smart contracts. To prove the hypothesis, I use these mathematical models to compute complex operations of naive Bayes, linear regression, decision trees, and neural network algorithms on Ethereum public test networks. The smart contracts achieve 95\% predict… more
Date: July 2023
Creator: Badruddoja, Syed
open access

Deep Learning Approaches to Radio Map Estimation

Description: Radio map estimation (RME) is the task of predicting radio power at all locations in a two-dimensional area and at all frequencies in a given band. This thesis explores four deep learning approaches to RME: dual path autoencoders, skip connection autoencoders, diffusion, and joint learning with transmitter localization.
Date: July 2023
Creator: Locke IV, William Alexander
open access

Paradigm Shift from Vague Legal Contracts to Blockchain-Based Smart Contracts

Description: In this dissertation, we address the problem of vagueness in traditional legal contracts by presenting novel methodologies that aid in the paradigm shift from traditional legal contracts to smart contracts. We discuss key enabling technologies that assist in converting the traditional natural language legal contract, which is full of vague words, phrases, and sentences to the blockchain-based precise smart contract, including metrics evaluation during our conversion experiment. To address the c… more
Date: July 2023
Creator: Upadhyay, Kritagya Raj
open access

Reinforcement Learning-Based Test Case Generation with Test Suite Prioritization for Android Application Testing

Description: This dissertation introduces a hybrid strategy for automated testing of Android applications that combines reinforcement learning and test suite prioritization. These approaches aim to improve the effectiveness of the testing process by employing reinforcement learning algorithms, namely Q-learning and SARSA (State-Action-Reward-State-Action), for automated test case generation. The studies provide compelling evidence that reinforcement learning techniques hold great potential in generating tes… more
Date: July 2023
Creator: Khan, Md Khorrom
open access

Modeling and Simulation of the Vector-Borne Dengue Disease and the Effects of Regional Variation of Temperature in the Disease Prevalence in Homogenous and Heterogeneous Human Populations

Description: The history of mitigation programs to contain vector-borne diseases is a story of successes and failures. Due to the complex interplay among multiple factors that determine disease dynamics, the general principles for timely and specific intervention for incidence reduction or eradication of life-threatening diseases has yet to be determined. This research discusses computational methods developed to assist in the understanding of complex relationships affecting vector-borne disease dynamics. A… more
Date: August 2016
Creator: Bravo-Salgado, Angel D
open access

Object Recognition Using Scale-Invariant Chordiogram

Description: This thesis describes an approach for object recognition using the chordiogram shape-based descriptor. Global shape representations are highly susceptible to clutter generated due to the background or other irrelevant objects in real-world images. To overcome the problem, we aim to extract precise object shape using superpixel segmentation, perceptual grouping, and connected components. The employed shape descriptor chordiogram is based on geometric relationships of chords generated from the pa… more
Date: May 2017
Creator: Tonge, Ashwini
open access

Probabilistic Analysis of Contracting Ebola Virus Using Contextual Intelligence

Description: The outbreak of the Ebola virus was declared a Public Health Emergency of International Concern by the World Health Organisation (WHO). Due to the complex nature of the outbreak, the Centers for Disease Control and Prevention (CDC) had created interim guidance for monitoring people potentially exposed to Ebola and for evaluating their intended travel and restricting the movements of carriers when needed. Tools to evaluate the risk of individuals and groups of individuals contracting the disease… more
Date: May 2017
Creator: Gopalakrishnan, Arjun
open access

A Data-Driven Computational Framework to Assess the Risk of Epidemics at Global Mass Gatherings

Description: This dissertation presents a data-driven computational epidemic framework to simulate disease epidemics at global mass gatherings. The annual Muslim pilgrimage to Makkah, Saudi Arabia is used to demonstrate the simulation and analysis of various disease transmission scenarios throughout the different stages of the event from the arrival to the departure of international participants. The proposed agent-based epidemic model efficiently captures the demographic, spatial, and temporal heterogeneit… more
Date: May 2019
Creator: Alshammari, Sultanah
open access

Extracting Temporally-Anchored Spatial Knowledge

Description: In my dissertation, I elaborate on the work that I have done to extract temporally-anchored spatial knowledge from text, including both intra- and inter-sentential knowledge. I also detail multiple approaches to infer spatial timeline of a person from biographies and social media. I present and analyze two strategies to annotate information regarding whether a given entity is or is not located at some location, and for how long with respect to an event. Specifically, I leverage semantic roles o… more
Date: May 2019
Creator: Vempala, Alakananda
open access

Networking of UAVs Using 802.11s

Description: The thesis simulates the problem of network connectivity that occurs due to the dynamic nature of a network during flight. Nine nodes are provided with initial positions and are flown based on the path provided by leader-follower control algorithm using the server-client model. The application layer provides a point to point connection between the server and client and by using socket programming in the transport layer, a server and clients are established. Each node performs a neighbor discove… more
Date: May 2019
Creator: Polumuru, Pushpa
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