Computer Sciences Commons^™

Learned Dual-View Reflection Removal, Simon Niklaus, Xuaner Cecilia Zhang, Jonathan T. Barron, Neal Wadhwa, Rahul Garg, Feng Liu, Tianfan Xue

Computer Science Faculty Publications and Presentations

Traditional reflection removal algorithms either use a single image as input, which suffers from intrinsic ambiguities, or use multiple images from a moving camera, which is inconvenient for users. We instead propose a learning-based dereflection algorithm that uses stereo images as input. This is an effective trade-off between the two extremes: the parallax between two views provides cues to remove reflections, and two views are easy to capture due to the adoption of stereo cameras in smartphones. Our model consists of a learning-based reflection-invariant flow model for dual-view registration, and a learned synthesis model for combining aligned image pairs. Because …

Fact-Checking Of Claims From The English Wikipedia Using Evidence In The Wild, Aalok Sathe

Honors Theses

Automated fact checking is a task in the domain of Natural Language Processing that deals with the verification of claims using evidence. Fact checking is becoming increasingly important as large amounts of human-generated information accumulate online. In the recent past, our society has witnessed large-scale spread of disinformation via the internet that has time and again led to noticeable disruptions in the fabric of society. Fact-checking would help mitigate the spread of disinformation by allowing large magnitudes of content to be automatically evaluated for disinformation. In this work, we construe and tackle multiple subtasks of fact checking using labeled data …

Making The Easy Accessibility Package, Aaron G. Trudeau

Honors Projects

The Easy Accessibility Package is a code package for Unity (a game engine bundled with game development software) that is meant to help video game developers quickly and easily make their games accessible to disabled gamers. The two main features I include in the project were remappable controls (changing which button performs which in-game action) and screen reader support (reading on screen text or game status aloud), both of which are vital to making games accessible.

The repository for the project at the time of submission can be found here: https://github.com/trudeaua21/EasyAccessibilityPackage/tree/v0.1-alpha

The up-to-date repository for the project can be found …

Multi-Robot Coordination With Environmental Disturbances, Adem Coskun

Theses and Dissertations

Multi-robot systems are increasingly deployed in environments where they interact with humans. From the perspective of a robot, such interaction could be considered a disturbance that causes a well-planned trajectory to fail. This dissertation addresses the problem of multi-robot coordination in scenarios where the robots may experience unexpected delays in their movements.

Prior work by Čáp, Gregoire, and Frazzoli introduced a control law, called RMTRACK, which enables robots in such scenarios to execute pre-planned paths in spite of disturbances that affect the execution speed of each robot while guaranteeing that each robot can reach its goal without collisions and without …

The Role Of Privacy Within The Realm Of Healthcare Wearables' Acceptance And Use, Thomas Jernejcic

Masters Theses & Doctoral Dissertations

The flexibility and vitality of the Internet along with technological innovation have fueled an industry focused on the design of portable devices capable of supporting personal activities and wellbeing. These compute devices, known as wearables, are unique from other computers in that they are portable, specific in function, and worn or carried by the user. While there are definite benefits attributable to wearables, there are also notable risks, especially in the realm of security where personal information and/or activities are often accessible to third parties. In addition, protecting one’s private information is regularly an afterthought and thus lacking in maturity. …

Sistemi I Menaxhimit Të Laboratorit Mjekësor, Gramos Feka

Theses and Dissertations

Jeta po bëhet shumë e vështirë për të bërë takime mjekësore personalisht dhe për të mbajtur një kujdes të duhur shëndetësor. Ideja kryesore e kësaj pune është të sigurojë lehtësi dhe rehati për pacientët gjatë caktimit së terminit dhe gjithashtu zgjidh problemet me të cilat pacientët duhet të përballen gjatë caktimit të terminit. Ai u mundëson ofruesve të kujdesit shëndetësor të përmirësojnë efektivitetin operacional, të ulin kostot, të zvogëlojnë gabimet mjekësore, të zvogëlojnë konsumin e kohës dhe të përmirësojnë ofrimin e cilësisë së kujdesit. Ky sistem ndihmon në zvogëlimin e problemeve që ndodhin kur përdorni sistemin manual dhe ndihmon pacientët …

Sfidat E Kujdesit Shëndetësorë Dhe Roli I Teknologjisë Informative Në Të, Maltisa Dërmaku

Theses and Dissertations

Teknologjia informative ka ndryshuar jetët tona në shumë aspekte. Jemi të vetëdijshëm së pa të do ktheheshim mbrapa në kohë me ngecje në shumë procese.

Jo vetëm bizneset, por individët, studentët, pacientët dhe secili prej nesh përdorë aplikacionet për ta bërë jetën më të lehtë dhe më të përshtatshme të cilat janë larg nesh vetem një klikim të një butoni.

Teknologjia e informacionit po na ndihmon të përparojmë me shpejtësi të madhe.

Ky punim kryesisht fokusohet në rolin e teknologjisë informative në industrinë e shëndetësisë. Më saktësisht, në zhvillimin e sistemeve shëndetësore për ruajtjen e të dhënave, ku paraqitet e …

Krahasimi Në Mes Të Amazon Web Services Dhe Microsoft Azure, Albert Gojani

Theses and Dissertations

Shërbimet e teknologjisë Cloud në shekullin të cilin jetojmë e kanë lehtësuar shumë mënyrën se si shumë biznese ose individ operojnë në fushën e IT-së. Realizimi i një mjedisi klasik në një kompani është shumë i kushtueshëm duke marrë parasysh se ju duhet të siguroni pajisje të ndryshme të IT-së, server, disqe për ruajtjen e të dhënave në bazë të kapaciteteve të nevojshme, fuqi procesuese, trajnim të stafit, punësim i ndonjë eksperti i cili po ashtu ka kosto etj. Të gjitha këto të cilat u cekën më lartë ofrohen nga disa kompani që janë liderë në tregun e teknologjisë Cloud …

Sistemi Për Menaxhimin E Shitjeve Së Librave Në Internet, Ahmat Mehmeti

Theses and Dissertations

Objektivi kryesor i projektit është krijimi i një dyqani online librash që lejon përdoruesit të kërkojnë dhe blejnë një libër në internet bazuar në titullin, autorin dhe subjektin. Në procesin e përmirësimit të standardit të jetesës së njerëzve, kërkesat e njerëzve për cilësinë dhe efikasitetin e jetës janë më të larta. Një shqetësim rreth librarisë tradicionale është shfaqur gradualisht kur libraria online gradualisht ka filluar të përdoret në publik. Libraria në internet është një revolucion i industrisë së librit. Koha, adresa dhe hapësira e funksionimit të librarive tradicionale është e kufizuar, kështu që llojet e librave dhe gjetja e tyre …

Përmirësimi I Metodës Së Mësimit Përmes Përsëritjeve Së Kohëpaskohshme - Memoapp, Edin Mehmeti

Theses and Dissertations

Të mësosh diçka të re dhe të mos e harrosh atë është një aftësi që çdokush e dëshiron. Ka të atillë që e kanë këtë aftësi dhe arrijnë të mbajnë në mend për një kohë të gjatë atë që kanë mësuar, por ka edhe të atillë që pas një kohe të shkurtër harrojnë atë që sapo kanë mësuar. Me anë të përsëritjeve të kohëpaskohshme, të rilexojnë pas një kohe të caktuar atë që kanë mësuar, këta të fundit mund të përmirësojnë metodën e tyre të mësimit dhe në këtë mënyrë gjërat e reja të sapomësuara mund t’i mbajnë në mend …

Dallimi Mes Databazave Relacionale (Sql) Dhe Jorelacionale (Nosql), Vesa Kelmendi

Theses and Dissertations

Databazat relacionale mund të konsiderohen tipike tradicionale për rolin dhe përdorueshmërinë që zotërojnë aktualisht. Pavarësisht që janë përdorur dhe vazhdojnë të përdoren për zgjidhje të problemeve të ndryshme, përdorimi i tyre po zbehet dhe mbulohet nga përdorimi i databazave jorelacionale, NoSQL, të cilat kanë fleksibilitet dhe kapacitet më të madh për t’u përgjigjur në kërkesat gjithnjë në rritje të teknologjisë, biznesit, apo fushave tjera.

Aktualisht, shohim tendencë të qartë të përdorimit të databazave në kohë reale (real-time databases) të cilat kanë mundësuar zgjidhjen e problemeve me të dhënat të cilat ndryshojnë në mënyrë dinamike. Këto të dhëna përpunohen dhe transmetohen …

Privacyprimer: Towards Privacy-Preserving Episodic Memory Support For Older Adults, Thivya Kandappu, Vigneshwaran Subbaraju, Qianli Xu

Research Collection School Of Computing and Information Systems

Built-in pervasive cameras have become an integral part of mobile/wearable devices and enabled a wide range of ubiquitous applications with their ability to be "always-on". In particular, life-logging has been identified as a means to enhance the quality of life of older adults by allowing them to reminisce about their own life experiences. However, the sensitive images captured by the cameras threaten individuals' right to have private social lives and raise concerns about privacy and security in the physical world. This threat gets worse when image recognition technologies can link images to people, scenes, and objects, hence, implicitly and unexpectedly …

Multi-Domain Dialogue State Tracking With Recursive Inference, Lizi Liao, Tongyao Zhu, Le Hong Long, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Multi-domain dialogue state tracking (DST) is a critical component for monitoring user goals during the course of an interaction. Existing approaches have relied on dialogue history indiscriminately or updated on the most recent turns incrementally. However, in spite of modeling it based on fixed ontology or open vocabulary, the former setting violates the interactive and progressing nature of dialogue, while the later easily gets affected by the error accumulation conundrum. Here, we propose a Recursive Inference mechanism (ReInf) to resolve DST in multi-domain scenarios that call for more robust and accurate tracking capability. Specifically, our agent reversely reviews the dialogue …

Cybersecurity Risk Assessment Using Graph Theoretical Anomaly Detection And Machine Learning, Goksel Kucukkaya

Engineering Management & Systems Engineering Theses & Dissertations

The cyber domain is a great business enabler providing many types of enterprises new opportunities such as scaling up services, obtaining customer insights, identifying end-user profiles, sharing data, and expanding to new communities. However, the cyber domain also comes with its own set of risks. Cybersecurity risk assessment helps enterprises explore these new opportunities and, at the same time, proportionately manage the risks by establishing cyber situational awareness and identifying potential consequences. Anomaly detection is a mechanism to enable situational awareness in the cyber domain. However, anomaly detection also requires one of the most extensive sets of data and features …

Feature Extraction And Design In Deep Learning Models, Daniel Perez

Computational Modeling & Simulation Engineering Theses & Dissertations

The selection and computation of meaningful features is critical for developing good deep learning methods. This dissertation demonstrates how focusing on this process can significantly improve the results of learning-based approaches. Specifically, this dissertation presents a series of different studies in which feature extraction and design was a significant factor for obtaining effective results. The first two studies are a content-based image retrieval system (CBIR) and a seagrass quantification study in which deep learning models were used to extract meaningful high-level features that significantly increased the performance of the approaches. Secondly, a method for change detection is proposed where the …

Predictions Of Knee Joint Contact Forces Using Only Kinematic Inputs With A Recurrent Neural Network, Kaileigh Elisabeth Estler

Human Movement Studies & Special Education Theses & Dissertations

BACKGROUND: Knee joint contact (bone on bone) forces are commonly estimated using surrogate measures such as external knee adduction moments (with limited success) or musculoskeletal modeling (more successful). Despite its capabilities, modeling is not optimal for clinicians or persons with limited experience and knowledge. Therefore, the purpose of this study was to design a novel prediction method for knee joint contact forces that is equal or more accurate than modeling, yet simplistic in terms of required inputs. METHODS: This study included all six subjects’ (71.3±6.5kg, 1.7±0.1m) data from the opensource “Grand Challenge” datasets (simtk.org) and two subjects from the "CAMS" …

Investigating Pre-Service Teachers’ Perceptions Of The Virginia Computer Science Standards Of Learning: A Qualitative Multiple Case Study, Valerie Sledd Taylor

Educational Leadership & Workforce Development Theses & Dissertations

Computer science education is being recognized globally as necessary to better prepare students in all grade levels, K-12, for future success. As a result of this focus on computer science education in the United States and around the world, there is an increased demand for highly qualified teachers with content and pedagogical knowledge to successfully support student learning. As a result, there is a call to include and improve the computer science training offered to pre-service teachers in their educator preparation programs from methods courses to practicum and student teaching experiences. Thus, it is important to understand how pre-service teachers …

Learning And Simulation Algorithms For Constraint Physical Systems, Shuqi Yang

Dartmouth College Master’s Theses

This thesis explores two computational approaches to learn and simulate complex physical systems exhibiting constraint characteristics. The target applications encompass both solids and fluids. On the solid side, we proposed a new family of data-driven simulators to predict the behaviors of an unknown physical system by learning its underpinning constraints. We devised a neural projection operator facilitated by an embedded recursive neural network to interactively enforce the learned underpinning constraints and to predict its various physical behaviors. Our method can automatically uncover a broad range of constraints from observation point data, such as length, angle, bending, collision, boundary effects, and …

Kennesaw State University Research Computing Facilities And Resources, Tom Boyle, Ramazan Aygun

Training Materials, User Guides, and Documentation

The Kennesaw State University High Performance Computing (HPC) resources represent the University’s commitment to research computing. This resource contains verbiage for users of Kennesaw State University's HPC resources to include in their grants and publications. Please use the recommended citation rather than including the listed authors in the your citations.

The current version was published Fall 2023. Previous versions can be found below.

Predicting Bus Travel Times In Washington, Dc Using Artificial Neural Networks (Anns), Stephen Arhin, Babin Manandhar, Hamdiat Baba Adam, Adam Gatiba

Mineta Transportation Institute

Washington, DC is ranked second among cities in terms of highest public transit commuters in the United States, with approximately 9% of the working population using the Washington Metropolitan Area Transit Authority (WMATA) Metrobuses to commute. Deducing accurate travel times of these metrobuses is an important task for transit authorities to provide reliable service to its patrons. This study, using Artificial Neural Networks (ANN), developed prediction models for transit buses to assist decision-makers to improve service quality and patronage. For this study, we used six months of Automatic Vehicle Location (AVL) and Automatic Passenger Counting (APC) data for six Washington …

Using Machine Learning For Detection Of Covid-19, Justin Rickert

Honors Projects

Currently, the most widely used diagnostic tool for COVID-19 is the RT-PCR nasal swab test recommended by the CDC. However, some studies have shown that chest CT scans have the potential to be more accurate and are also capable of detecting the virus in its earlier stages. Unfortunately, CT results are not instantaneously available as it may be days before a radiologist can review the scan. This delay is one of the factors preventing the widespread use of CT scans for COVID detection. To address the delay, this project investigated Convolutional Neural Networks, an advanced form of machine learning used …

An Automated Framework For Connected Speech Evaluation Of Neurodegenerative Disease: A Case Study In Parkinson's Disease, Sai Bharadwaj Appakaya

USF Tampa Graduate Theses and Dissertations

Neurodegenerative diseases affect millions of people around the world. The progressive degeneration worsens the symptoms, heavily impacting the quality of life of the patients as well as the caregivers. Speech production is one of the physiological processes affected by neurodegenerative diseases like Alzheimer’s disease, amyotrophic lateral sclerosis (ALS) and Parkinson’s disease (PD). Speech is the most basic form of communication, and the effect of neurodegeneration degrades speech production, thereby reducing social interaction and mental well-being. PD is the second most common neurodegenerative disease affecting speech production in 90% of the diagnosed individuals. Speech analysis methods for PD in clinical methods …

Public Discourse Against Masks In The Covid-19 Era: Infodemiology Study Of Twitter Data, Mohammad A. Al-Ramahi, Ahmed El Noshokaty, Omar El-Gayar, Tareq Nasralah, Abdullah Wahbeh

Computer Information Systems Faculty Publications (Archived)

Background:

Despite scientific evidence supporting the importance of wearing masks to curtail the spread of COVID-19, wearing masks has stirred up a significant debate particularly on social media.

Objective:

This study aimed to investigate the topics associated with the public discourse against wearing masks in the United States. We also studied the relationship between the anti-mask discourse on social media and the number of new COVID-19 cases.

Methods:

We collected a total of 51,170 English tweets between January 1, 2020, and October 27, 2020, by searching for hashtags against wearing masks. We used machine learning techniques to analyze the data …

A Comprehensive Mapping And Real-World Evaluation Of Multi-Object Tracking On Automated Vehicles, Alexander Bassett

Doctoral Dissertations and Master's Theses

Multi-Object Tracking (MOT) is a field critical to Automated Vehicle (AV) perception systems. However, it is large, complex, spans research fields, and lacks resources for integration with real sensors and implementation on AVs. Factors such those make it difficult for new researchers and practitioners to enter the field.

This thesis presents two main contributions: 1) a comprehensive mapping for the field of Multi-Object Trackers (MOTs) with a specific focus towards Automated Vehicles (AVs) and 2) a real-world evaluation of an MOT developed and tuned using COTS (Commercial Off-The-Shelf) software toolsets. The first contribution aims to give a comprehensive overview of …

Somewhere Over The Rainbow: Exploring The Sense For Relevance In Children, Monica Landoni, Theo Huibers, Emiliana Murgia, Mohammad Aliannejadi, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

We explore the facets of relevance that guide children when assessing materials retrieved by search engines when looking for information in the classroom. We involved children in a collaborative exercise and asked them to design innovative icons to point their peers towards useful results. We also asked them to complete a survey meant to capture explicit motivators guiding their design. This resulted in a rich set of metaphors. Analysis of the emerging metaphors is what allowed us to identify and discuss the many interpretations of relevance children naturally assign to resources they find in response to school-related information discovery …

Estimation Of Fair Ranking Metrics With Incomplete Judgments, Ömer Kırnap, Fernando Diaz, Asia Biega, Michael Ekstrand, Ben Carterette, Emine Yilmaz

Computer Science Faculty Publications and Presentations

There is increasing attention to evaluating the fairness of search system ranking decisions. These metrics often consider the membership of items to particular groups, often identified using protected attributes such as gender or ethnicity. To date, these metrics typically assume the availability and completeness of protected attribute labels of items. However, the protected attributes of individuals are rarely present, limiting the application of fair ranking metrics in large scale systems. In order to address this problem, we propose a sampling strategy and estimation technique for four fair ranking metrics. We formulate a robust and unbiased estimator which can operate even …

Spellchecking For Children In Web Search: A Natural Language Interface Case-Study, Casey Kennington, Jerry Alan Fails, Katherine Landau Wright, Maria Soledad Pera

Computer Science Faculty Publications and Presentations

Given the more widespread nature of natural language interfaces, it is increasingly important to understand who are accessing those interfaces, and how those interfaces are being used. In this paper, we explore spellchecking in the context of web search with children as the target audience. In particular, via a literature review we show that, while widely used, popular search tools are ill-designed for children. We then use spellcheckers as a case study to highlight the need for an interdisciplinary approach that brings together natural language processing, education, human-computer interaction to address a known information retrieval problem: query misspelling. We conclude …

Dijkstra’S Pathfinder, Taylor F. Malamut

Honors Theses

Dijkstra’s algorithm has been widely studied and applied since it was first published in 1959. This research shows that Dijkstra’s algorithm can be used to find the shortest path between two stations on the Washington D.C. Metro. After exploring different types of research and applying Dijkstra’s algorithm, it was found that the algorithm will always yield the shortest path, even if visually a shorter path was initially expected.

Ai Use In Claims Processing And Utilization Review, Robert Rosenthal Dds

The Journal of the Michigan Dental Association

This paper investigates the use of artificial intelligence (AI) in claims processing and utilization review in the dental industry. This article aims to explore the potential benefits of AI in this area, such as increased efficiency, accuracy, and fraud detection. The paper begins by providing an overview of the current state of claims processing and utilization review in the dental industry. It then discusses the potential applications of AI in this area, such as automated claims adjudication, predictive analytics, and image recognition. The paper then presents a case study of P&R Dental Strategies, LLC, a leading business intelligence solutions provider …

The Emergence Of Artificial Intelligence In Dental Care Delivery, Robert A. Faiella D.M.D., M.M.Sc., M.B.A., Shaju Puthussery M.S.

The Journal of the Michigan Dental Association

This comprehensive review explores the transformative role of Artificial Intelligence (AI) in the evolution of dental care delivery. As oral health specialists, dentists continually seek to enhance their ability to prevent, diagnose, and manage oral diseases while maintaining and improving patient oral health. The integration of AI offers unprecedented opportunities to revolutionize dental practice and patient care.

AI is rapidly advancing in healthcare, including dental care, with a projected global healthcare AI market value of $45.2 billion by 2026. This technology can potentially revolutionize prevention, diagnosis, treatment planning, and treatment outcomes.

Aspects of AI in dentistry include:

· Diagnostic Accuracy …