Other Computer Sciences Commons^™

Algorithm-Based Fault Tolerance At Scale, Hayden Estes

Summer Community of Scholars Posters (RCEU and HCR Combined Programs)

No abstract provided.

Implementing Github Actions Continuous Integration To Reduce Error Rates In Ecological Data Collection, Albert Y. Kim, Valentine Herrmann, Ross Barreto, Brianna Calkins, Erika Gonzalez-Akre, Daniel J. Johnson, Jennifer A. Jordan, Lukas Magee, Ian R. Mcgregor, Nicolle Montero, Karl Novak, Teagan Rogers, Jessica Shue, Kristina J. Anderson-Teixeira

Statistical and Data Sciences: Faculty Publications

Accurate field data are essential to understanding ecological systems and forecasting their responses to global change. Yet, data collection errors are common, and data analysis often lags far enough behind its collection that many errors can no longer be corrected, nor can anomalous observations be revisited. Needed is a system in which data quality assurance and control (QA/QC), along with the production of basic data summaries, can be automated immediately following data collection.

Here, we implement and test a system to satisfy these needs. For two annual tree mortality censuses and a dendrometer band survey at two forest research sites, …

Influence Level Prediction On Social Media Through Multi-Task And Sociolinguistic User Characteristics Modeling, Denys Katerenchuk

Dissertations, Theses, and Capstone Projects

Prediction of a user’s influence level on social networks has attracted a lot of attention as human interactions move online. Influential users have the ability to influence others’ behavior to achieve their own agenda. As a result, predicting users’ level of influence online can help to understand social networks, forecast trends, prevent misinformation, etc. The research on user influence in social networks has attracted much attention across multiple disciplines, from social sciences to mathematics, yet it is still not well understood. One of the difficulties is that the definition of influence is specific to a particular problem or a domain, …

Finite Gaussian Neurons: Defending Against Adversarial Attacks By Making Neural Networks Say "I Don’T Know", Felix Grezes

Dissertations, Theses, and Capstone Projects

In this work, I introduce the Finite Gaussian Neuron (FGN), a novel neuron architecture for artificial neural networks aimed at protecting against adversarial attacks.
Since 2014, artificial neural networks have been known to be vulnerable to adversarial attacks, which can fool the network into producing wrong or nonsensical outputs by making humanly imperceptible alterations to inputs. While defenses against adversarial attacks have been proposed, they usually involve retraining a new neural network from scratch, a costly task.

My works aims to:
- easily convert existing models to Finite Gaussian Neuron architecture,
- while preserving the existing model's behavior on real …

Towards Explaining Variation In Entrainment, Andreas Weise

Dissertations, Theses, and Capstone Projects

Entrainment refers to the tendency of human speakers to adapt to their interlocutors to become more similar to them. This affects various dimensions and occurs in many contexts, allowing for rich applications in human-computer interaction. However, it is not exhibited by every speaker in every conversation but varies widely across features, speakers, and contexts, hindering broad application. This variation, whose guiding principles are poorly understood even after decades of entrainment research, is the subject of this thesis. We begin with a comprehensive literature review that serves as the foundation of our own work and provides a reference to guide future …

How Facial Features Convey Attention In Stationary Environments, Janelle Domantay, Brendan Morris

Spectra Undergraduate Research Journal

Awareness detection technologies have been gaining traction in a variety of enterprises; most often used for driver fatigue detection, recent research has shifted towards using computer vision technologies to analyze user attention in environments such as online classrooms. This paper aims to extend previous research on distraction detection by analyzing which visual features contribute most to predicting awareness and fatigue. We utilized the open-source facial analysis toolkit OpenFace in order to analyze visual data of subjects at varying levels of attentiveness. Then, using a Support-Vector Machine (SVM) we created several prediction models for user attention and identified the Histogram of …

Adapting An Online Learning Quality Assurance Framework In A Developing Country Setting: The Case Of A Hei In Malawi, Bennett Kankuzi, Menard Phiri, Robert Chanunkha, Jonathan Makuwira, Paul Makocho

African Conference on Information Systems and Technology

Covid-19 prompted many higher education institutions (HEIs), even in developing countries like Malawi, to abruptly shift from their traditional face-to-face mode of delivery to online learning. However, quality issues with online learning remain one of the greatest challenges to acceptance of online learning by many students and stakeholders. This paper presents an action research based study at the Malawi University of Science and Technology, in which an online learning quality assurance framework is adapted to a developed country setting. The adapted framework builds on the Online Learning Consortium (OLC) Quality Scorecard for the Administration of Online Programs. The contextualization and …

Characterization Of End-Users’ Engagement And Interaction Experience With Social Media Technologies, Yemisi Oyedele, Darelle Van Greunen

African Conference on Information Systems and Technology

People, particularly digital citizens, gain more technological experiences from their frequent usage of social media technologies. Their experience as end-users occurs before, during, and after their engagement and interaction with the technologies and is popularly described using behaviour-related definitions. However, an end-user's experience with technologies goes beyond the 'click-and-type" definition. This prompts the question, "what are the user experience elements that define and characterise end-users' engagement and interaction with social media technologies?". Using a case study-based approach, end-users' engagement and interaction with social media technologies were identified. The study's findings indicated that several user experience elements were characterised by emotions, …

Automated Identification Of Astronauts On Board The International Space Station: A Case Study In Space Archaeology, Rao Hamza Ali, Amir Kanan Kashefi, Alice C. Gorman, Justin St. P. Walsh, Erik J. Linstead

Art Faculty Articles and Research

We develop and apply a deep learning-based computer vision pipeline to automatically identify crew members in archival photographic imagery taken on-board the International Space Station. Our approach is able to quickly tag thousands of images from public and private photo repositories without human supervision with high degrees of accuracy, including photographs where crew faces are partially obscured. Using the results of our pipeline, we carry out a large-scale network analysis of the crew, using the imagery data to provide novel insights into the social interactions among crew during their missions.

X-Ray Vision At Action Space Distances: Depth Perception In Context, Nate Phillips

Theses and Dissertations

Accurate and usable x-ray vision has long been a goal in augmented reality (AR) research and development. X-ray vision, or the ability to comprehend location and object information when such is viewed through an opaque barrier, would be imminently useful in a variety of contexts, including industrial, disaster reconnaissance, and tactical applications. In order for x-ray vision to be a useful tool for many of these applications, it would need to extend operators’ perceptual awareness of the task or environment. The effectiveness with which x-ray vision can do this is of significant research interest and is a determinant of …

Abm Simulation Model Of A Pandemic For Optimizing Vaccination Strategy, Gibeom Park

Theses and Dissertations

This study presents a process-oriented hybrid model for individuals' immune responses and interactions involving vaccination to describe the trend of contagious disease and estimate the future societal cost. The model considers "recovery" as a non-absorbing state and incorporates various infection stage states including two symptomatic states. To model contagiousness to be consistent with the current pandemic and include that the spread of a disease depends on the mobility of people, we developed an Agent-Based Simulator that fitted to the particular model used in this study and can test various what-if scenarios. We improved the simulator considerably by appying data structures …

Artificial Intelligence In The Radiomic Analysis Of Glioblastomas: A Review, Taxonomy, And Perspective, Ming Zhu, Sijia Li, Yu Kuang, Virginia B. Hill, Amy B. Heimberger, Lijie Zhai, Shenjie Zhai

Electrical & Computer Engineering Faculty Research

Radiological imaging techniques, including magnetic resonance imaging (MRI) and positron emission tomography (PET), are the standard-of-care non-invasive diagnostic approaches widely applied in neuro-oncology. Unfortunately, accurate interpretation of radiological imaging data is constantly challenged by the indistinguishable radiological image features shared by different pathological changes associated with tumor progression and/or various therapeutic interventions. In recent years, machine learning (ML)-based artificial intelligence (AI) technology has been widely applied in medical image processing and bioinformatics due to its advantages in implicit image feature extraction and integrative data analysis. Despite its recent rapid development, ML technology still faces many hurdles for its broader applications …

Reduced Fuel Emissions Through Connected Vehicles And Truck Platooning, Paul D. Brummitt

Electronic Theses and Dissertations

Vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) communication enable the sharing, in real time, of vehicular locations and speeds with other vehicles, traffic signals, and traffic control centers. This shared information can help traffic to better traverse intersections, road segments, and congested neighborhoods, thereby reducing travel times, increasing driver safety, generating data for traffic planning, and reducing vehicular pollution. This study, which focuses on vehicular pollution, used an analysis of data from NREL, BTS, and the EPA to determine that the widespread use of V2V-based truck platooning—the convoying of trucks in close proximity to one another so as to reduce air drag …

Feature Analysis Of Indus Valley And Dravidian Language Scripts With Similarity Matrices, Sarat Sasank Barla, Sai Surya Sanjay Alamuru, Peter Revesz

School of Computing: Conference and Workshop Papers

This paper investigates the similarity between the Indus Valley script and the Kannada, Malayalam, Tamil, and Telugu scripts that are used to write Dravidian languages. The closeness of these scripts is determined by applying a feature analysis of each sign of these scripts and creating similarity matrices that describe the similarity of any pair of signs from two different scripts. The feature list that we use for the analysis of these Dravidian language-related scripts includes six new features beyond the thirteen features that were used for the study of Minoan Linear A and related scripts by Revesz. These new features …

Evaluating Privacy Adaptation Presentation Methods To Support Social Media Users In Their Privacy-Related Decision-Making Process, Moses Namara

All Dissertations

Several privacy scholars have advocated for user-tailored privacy (UTP). A privacy-enhancing adaptive privacy approach to help reconcile users' lack of awareness, privacy management skills and motivation to use available platform privacy features with their need for personalized privacy support in alignment with their privacy preferences. The idea behind UTP is to measure users' privacy characteristics and behaviors, use these measurements to create a personalized model of the user's privacy preferences, and then provide adaptive support to the user in navigating and engaging with the available privacy settings---or even implement certain settings automatically on the user's behalf. To this end, most …

Pervasive Healthcare Internet Of Things: A Survey, Kim Anh Phung, Cemil Kirbas, Leyla Dereci, Tam Van Nguyen

Computer Science Faculty Publications

Thanks to the proliferation of the Internet of Things (IoT), pervasive healthcare is gaining popularity day by day as it offers health support to patients irrespective of their location. In emergency medical situations, medical aid can be sent quickly. Though not yet standardized, this research direction, healthcare Internet of Things (H-IoT), attracts the attention of the research community, both academia and industry. In this article, we conduct a comprehensive survey of pervasive computing H-IoT. We would like to visit the wide range of applications. We provide a broad vision of key components, their roles, and connections in the big picture. …

Combining Solution Reuse And Bound Tightening For Efficient Analysis Of Evolving Systems, Clay Stevens, Hamid Bagheri

School of Computing: Conference and Workshop Papers

Software engineers have long employed formal verification to ensure the safety and validity of their system designs. As the system changes—often via predictable, domain-specific operations—their models must also change, requiring system designers to repeatedly execute the same formal verification on similar system models. State-of-the-art formal verification techniques can be expensive at scale, the cost of which is multiplied by repeated analysis. This paper presents a novel analysis technique—implemented in a tool called SoRBoT—which can automatically determine domain-specific optimizations that can dramatically reduce the cost of repeatedly analyzing evolving systems. Different from all prior approaches, which focus on either tightening the …

Classifying Toe Walking Gait Patterns Among Children Diagnosed With Idiopathic Toe Walking Using Wearable Sensors And Machine Learning Algorithms, Rahul Soangra, Yuxin Wen, Hualin Yang, Marybeth Grant-Beuttler

Physical Therapy Faculty Articles and Research

Idiopathic toe walking (ITW) is a gait abnormality in which children’s toes touch at initial contact and demonstrate limited or no heel contact throughout the gait cycle. Toe walking results in poor balance, increased risk of falling, and developmental delays among children. Identifying toe walking steps during walking can facilitate targeted intervention among children diagnosed with ITW. With recent advances in wearable sensing, communication technologies, and machine learning, new avenues of managing toe walking behavior among children are feasible. In this study, we investigate the capabilities of Machine Learning (ML) algorithms in identifying initial foot contact (heel strike versus toe …

Finding Approximate Pythagorean Triples (And Applications To Lego Robot Building), Ronald I. Greenberg, Matthew Fahrenbacher, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

This assignment combines programming and data analysis to determine good combinations of side lengths that approximately satisfy the Pythagorean Theorem for right triangles. This can be a standalone exercise using a wide variety of programming languages, but the results are useful for determining good ways to assemble LEGO pieces in robot construction, so the exercise can serve to integrate three different units of the Exploring Computer Science high school curriculum: "Programming", "Computing and Data Analysis", and "Robotics". Sample assignment handouts are provided for both Scratch and Java programmers. Ideas for several variants of the assignment are also provided.

The Message Design Of Raiders Of The Lost Ark On The Atari 2600 & A Fan’S Map, Quick Start, And Strategy Guide, Miguel Ramlatchan, William I. Ramlatchan

Distance Learning Faculty & Staff Books

The message design and human performance technology in video games, especially early video games have always been fascinating to me. From an instructional design perspective, the capabilities of the technology of the classic game consoles required a careful balance of achievable objectives, cognitive task analysis, guided problem solving, and message design. Raiders on the Atari is an excellent example of this balance. It is an epic adventure game, spanning 13+ distinct areas, with an inventory of items, where those hard to find items had to be used by the player to solve problems during their quest (and who would have …