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Articles 1 - 30 of 102
Full-Text Articles in Physical Sciences and Mathematics
Design And Implementation Of A Vision-Based Deep-Learning Protocol For Kinematic Feature Extraction With Application To Stroke Rehabilitation, Juan Diego Luna Inga
Design And Implementation Of A Vision-Based Deep-Learning Protocol For Kinematic Feature Extraction With Application To Stroke Rehabilitation, Juan Diego Luna Inga
Master's Theses
Stroke is a leading cause of long-term disability, affecting thousands of individuals annually and significantly impairing their mobility, independence, and quality of life. Traditional methods for assessing motor impairments are often costly and invasive, creating substantial barriers to effective rehabilitation. This thesis explores the use of DeepLabCut (DLC), a deep-learning-based pose estimation tool, to extract clinically meaningful kinematic features from video data of stroke survivors with upper-extremity (UE) impairments.
To conduct this investigation, a specialized protocol was developed to tailor DLC for analyzing movements characteristic of UE impairments in stroke survivors. This protocol was validated through comparative analysis using peak …
Data Engineering: Building Software Efficiency In Medium To Large Organizations, Alessandro De La Torre
Data Engineering: Building Software Efficiency In Medium To Large Organizations, Alessandro De La Torre
Whittier Scholars Program
The introduction of PoetHQ, a mobile application, offers an economical strategy for colleges, potentially ushering in significant cost savings. These savings could be redirected towards enhancing academic programs and services, enriching the educational landscape for students. PoetHQ aims to democratize access to crucial software, effectively removing financial barriers and facilitating a richer educational experience. By providing an efficient software solution that reduces organizational overhead while maximizing accessibility for students, the project highlights the essential role of equitable education and resource optimization within academic institutions.
Citdet, Jordan A. James, Heather K. Manching, Matthew R. Mattia, Kim D. Bowman, Amanda M. Hulse-Kemp, William J. Beksi
Citdet, Jordan A. James, Heather K. Manching, Matthew R. Mattia, Kim D. Bowman, Amanda M. Hulse-Kemp, William J. Beksi
Computer Science and Engineering Datasets
The CitDet dataset is composed of images captured at the USDA Agricultural Research Service Subtropical Insects and Horticulture Research Unit in Fort Pierce, FL, USA. Data was collected between October 2021 and October 2022. 579 images were captured from different sections of the orchard using the open-source application Field Book on Android tablets. While collecting images, we faced the camera in a portrait orientation directly centered on the tree of interest. All images were taken at the edge of the soil in the tree row to simulate a ground-based robot imaging the tree while moving between two rows of trees. …
Knowledge Commons Past, Present, And Future, Michael J. Madison
Knowledge Commons Past, Present, And Future, Michael J. Madison
Articles
The project now known as Governing Knowledge Commons, or GKC, was launched more than 15 years ago on the intuition that skepticism of intellectual property law and information exclusivity was grounded in anecdote and ideology rather than in empiricism. Structured, systematic, empirical research on mechanisms of knowledge sharing was needed. GKC aimed to help scholars produce it. Over multiple books, case studies, and other work, the scope of GKC has expanded considerably, from innovation to governance; from invention and creativity to data, privacy, and markets; and from social dilemmas focused on things to governance strategies directed to communities and collectives. …
Infusing Machine Learning And Computational Linguistics Into Clinical Notes, Funke V. Alabi, Onyeka Omose, Omotomilola Jegede
Infusing Machine Learning And Computational Linguistics Into Clinical Notes, Funke V. Alabi, Onyeka Omose, Omotomilola Jegede
Mathematics & Statistics Faculty Publications
Entering free-form text notes into Electronic Health Records (EHR) systems takes a lot of time from clinicians. A large portion of this paper work is viewed as a burden, which cuts into the amount of time doctors spend with patients and increases the risk of burnout. We will see how machine learning and computational linguistics can be infused in the processing of taking clinical notes. We are presenting a new language modeling task that predicts the content of notes conditioned on historical data from a patient's medical record, such as patient demographics, lab results, medications, and previous notes, with the …
Delivering Healthcare To The Underserved, Edward Booty
Delivering Healthcare To The Underserved, Edward Booty
Asian Management Insights
Non-profits, governments, and businesses need to come together and use a data-driven approach to improve local basic healthcare access.
Cybersecurity Safeguards: What Cybersecurity Safeguards Could Have Prevented The Intelligence/Data Breach By A Member Of The Air National Guard, Christopher Curtis Royal
Cybersecurity Safeguards: What Cybersecurity Safeguards Could Have Prevented The Intelligence/Data Breach By A Member Of The Air National Guard, Christopher Curtis Royal
Cyber Operations and Resilience Program Graduate Projects
Jack Teixeira, a 21-year-old IT specialist Air National Guard found himself on the wrong side of the US law after sharing what is considered classified and extremely sensitive information about USA's operations and role in Ukraine and Russia war. Like other previous cases of leakage of classified intelligence, the case of Teixeira raises concerns about the weaknesses and vulnerability of federal agencies' IT systems and security protocols governing accessibility to classified documents. Internal leakages of such classified documents hurt national security and can harm the country, especially when such secretive intelligence finds its way into the hands of enemies. Unauthorized …
Fintech Data Infrastructure For Esg Disclosure Compliance, Randall E. Duran, Peter Tierney
Fintech Data Infrastructure For Esg Disclosure Compliance, Randall E. Duran, Peter Tierney
Research Collection School Of Computing and Information Systems
Regulations related to the disclosure of environmental, governance, and social (ESG) factors are evolving rapidly and are a major concern for financial compliance worldwide. Information technology has the potential to reduce the effort and cost of ESG disclosure compliance. However, comprehensive and accurate ESG data are necessary for disclosures. Currently, the availability and quality of underlying data for ESG disclosures vary widely and are often deficient. The process involved with obtaining ESG data is also often inefficient and prone to error. This paper compares the models used and the evolution of Fintech data infrastructure developed to support financial services with …
Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan
Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan
Computer Science Senior Theses
We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …
Nviz: Unraveling Neural Networks Through Visualization, Kevin Hoffman
Nviz: Unraveling Neural Networks Through Visualization, Kevin Hoffman
Mathematics and Computer Science Presentations
The growing utility of artificial intelligence (AI) is attributed to the development of neural networks. These networks are a class of models that make predictions based on previously observed data. While the inferential power of neural networks is great, the ability to explain their results is difficult because the underlying model is automatically generated. The AI community commonly refers to neural networks as black boxes because the patterns they learn from the data are not easily understood. This project aims to improve the visibility of patterns that neural networks identify in data. Through an interactive web application, NVIZ affords the …
Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp
Development Of Sensing And Programming Activities For Engineering Technology Pathways Using A Virtual Arduino Simulation Platform, Murat Kuzlu, Vukica Jovanovic, Otilia Popescu, Salih Sarp
Engineering Technology Faculty Publications
The Arduino platform has long been an efficient tool in teaching electrical engineering technology, electrical engineering, and computer science concepts in schools and universities and introducing new learners to programming and microcontrollers. Numerous Arduino projects are widely available through the open-source community, and they can help students to have hands-on experience in building circuits and programming electronics with a wide variety of topics that can make learning electrical prototyping fun. The educational fields of electrical engineering and electrical engineering technology need continuous updating to keep up with the continuous evolution of the computer system. Although the traditional Arduino platform has …
Big Data Analytics Of Medical Data, Ashwin Rajasankar
Big Data Analytics Of Medical Data, Ashwin Rajasankar
Culminating Experience Projects
Data has become a huge part of modern decision making. With the improvements in computing performance and storage in the past two decades, storing large amounts of data has become much easier. Analyzing large amounts of data and creating data models with them can help organizations obtain insights and information which helps their decision making. Big data analytics has become an integral part of many fields such as retail, real estate, education, and medicine. In the project, the goal is to understand the working of Apache Spark and its different storage methods and create a data warehouse to analyze data. …
Data Vu: Why Breaches Involve The Same Stories Again And Again, Woodrow Hartzog, Daniel Solove
Data Vu: Why Breaches Involve The Same Stories Again And Again, Woodrow Hartzog, Daniel Solove
Shorter Faculty Works
In the classic comedy Groundhog Day, protagonist Phil, played by Bill Murray, asks “What would you do if you were stuck in one place and every day was exactly the same, and nothing that you did mattered?” In this movie, Phil is stuck reliving the same day over and over, where the events repeat in a continual loop, and nothing he does can stop them. Phil’s predicament sounds a lot like our cruel cycle with data breaches.
Every year, organizations suffer more data spills and attacks, with personal information being exposed and abused at alarming rates. While Phil …
Mapping The Covid-19 Pandemic In Staten Island, Vincenzo Mezzio
Mapping The Covid-19 Pandemic In Staten Island, Vincenzo Mezzio
Student Theses
COVID-19 has had diverging effects in New York City. Out of the five boroughs, Staten Island has one of the largest percentages of COVID-19 cases relative to population. This research examines key social and spatial factors that contribute to the increase in COVID-19 cases in Staten Island). It asks: Which parts of Staten Island have higher rates of transmission of COVID-19? Which parts of the borough have higher population who are more vulnerable to COVID-19? What is the relationship between the location of vaccination centers with the rates of COVID-19 cases? Using Geographic Information Systems (GIS), this research examines the …
Performance Improvements In Inner Product Encryption, Serena Riback
Performance Improvements In Inner Product Encryption, Serena Riback
Honors Scholar Theses
Consider a database that contains thousands of entries of the iris biometric. Each entry identifies an individual, so it is especially important that it remains secure. However, searching for entries among an encrypted database proves to be a security problem - how should one search encrypted data without leaking any information to a potential attacker? The proximity searchable encryption scheme, as discussed in the work by Cachet et al., uses the notions of inner product encryption developed by Kim et al.. In this paper, we will focus on the efficiency of these schemes. Specifically, how the symmetry of the bilinear …
Building Capacity For Data-Driven Scholarship, Jamie Rogers
Building Capacity For Data-Driven Scholarship, Jamie Rogers
Works of the FIU Libraries
This talk provides an overview of "dLOC as Data: A Thematic Approach to Caribbean Newspapers," an initiative developed to increase access to digitized Caribbean newspaper text for bulk download, facilitating computational analysis. Capacity building for future research in Caribbean Studies being a crucial aspect of this initiative, a thematic toolkit was developed to facilitate use of the project data as well as provide replicable processes. The toolkit includes sample text analysis projects, as well as tutorials and detailed project documentation. While the toolkit focuses on the history of hurricanes and tropical cyclones of the region, the methodologies and tools used …
The Mathematics Of Risk: An Introduction To Guaranteed Data De-Identification, Kristi Thompson
The Mathematics Of Risk: An Introduction To Guaranteed Data De-Identification, Kristi Thompson
Western Libraries Presentations
This webinar is devoted to the mathematical and theoretical underpinnings of guaranteed data anonymization. Topics covered include an overview of identifiers and quasi-identifiers, an introduction to k-anonymity, a look at some cases where k-anonymity breaks down, and anonymization hierarchies. The presenter will describe a method to assess a survey dataset for anonymization using standard statistical software and consider the question of "anonymization overkill". Much of the academic material looking at data anonymization is quite abstract and aimed at computer scientists, while material aimed at data curators does not always consider recent developments. This webinar is intended to help bridge the …
Outvoice: Bringing Transparency To Healthcare, Autumn Clark
Outvoice: Bringing Transparency To Healthcare, Autumn Clark
Undergraduate Honors Theses
Industries are not incentivized to price reasonably and spend responsibly if consumers do not have the ability to shop around within that industry, and shopping around is not possible without pricing transparency (knowing how much a good or service costs before purchasing it). But in the healthcare industry, we typically default to whichever clinic or hospital is closest, with no prior knowledge of what costs we can expect to incur at that particular institution. According to a poll published by Harvard University, nine out of ten Americans feel the healthcare industry is too opaque and greater transparency is needed.
We …
Membership Application Subscription Based, Vlera Zhubi, Medina Shamolli
Membership Application Subscription Based, Vlera Zhubi, Medina Shamolli
UBT International Conference
I
t's no secret: Units wanting from small businesses, both public and private, to large businesses, are facing new challenges in hiring and managing members and payments. The membership application is an application that provides businesses, associations, clubs and functional organizations looking to manage their members. A membership application is an online subscription-based business where people pay for regular access to exclusive content. Online memberships and courses have continued to grow as people are willing to pay for convenience, exclusivity, knowledge and community. They are structured in such a way as to meet the special needs of the members at …
Public Interest Technology – Exploring Covid-19 Health Data, Sarah Zelikovitz
Public Interest Technology – Exploring Covid-19 Health Data, Sarah Zelikovitz
Open Educational Resources
This module is part of a Introduction to Data Science course that covers the different parts of the data science process: data acquisition, cleaning, exploratory data analysis, and modeling. The COVID-19 pandemic has created much interest in public health data, as well as interest in visualization of all types of data. Public health data has a set of challenges that is unique to health data, with HIPAA laws, and real time collection of data. With COVID-19, the challenges are particularly amplified, as data collection and statistics collected are constantly changing in response to feedback from labs, hospitals, drug companies, and …
Law Library Blog (January 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law
Law Library Blog (January 2021): Legal Beagle's Blog Archive, Roger Williams University School Of Law
Law Library Newsletters/Blog
No abstract provided.
A Data-Based Guiding Framework For Digital Transformation, Zakaria Maamar, Saoussen Cheikhrouhou, Said Elnaffar
A Data-Based Guiding Framework For Digital Transformation, Zakaria Maamar, Saoussen Cheikhrouhou, Said Elnaffar
All Works
This paper presents a framework for guiding organizations initiate and sustain digital transformation initiatives. Digital transformation is a long-term journey that an organization embarks on when it decides to question its practices in light of management, operation, and technology challenges. The guiding framework stresses out the importance of data in any digital transformation initiative by suggesting 4 stages referred to as collection, processing, storage, and dissemination. Because digital transformation could impact different areas of an organization for instance, business processes and business models, each stage suggests techniques to expose data. 2 case studies are adopted in the paper to illustrate …
Security Against Data Falsification Attacks In Smart City Applications, Venkata Praveen Kumar Madhavarapu
Security Against Data Falsification Attacks In Smart City Applications, Venkata Praveen Kumar Madhavarapu
Doctoral Dissertations
Smart city applications like smart grid, smart transportation, healthcare deal with very important data collected from IoT devices. False reporting of data consumption from device failures or by organized adversaries may have drastic consequences on the quality of operations. To deal with this, we propose a coarse grained and a fine grained anomaly based security event detection technique that uses indicators such as deviation and directional change in the time series of the proposed anomaly detection metrics to detect different attacks. We also built a trust scoring metric to filter out the malicious devices. Another challenging problem is injection of …
Data, Stats, Go: Navigating The Intersections Of Cataloging, E-Resource, And Web Analytics Reporting, Rachel S. Evans, Wendy Moore, Jessica Pasquale, Andre Davison
Data, Stats, Go: Navigating The Intersections Of Cataloging, E-Resource, And Web Analytics Reporting, Rachel S. Evans, Wendy Moore, Jessica Pasquale, Andre Davison
Presentations
Do you trudge through gathering statistics at fiscal or calendar year-end? Do you wonder why you track certain things, thinking many seem outdated or irrelevant? Many places seem to keep counting certain statistics because "that's what they've always done." For e-resources, how do you integrate those with physical counts and reconcile the variations (updated e-resources versus re-cataloged physical items)? What about repository downloads and other web traffic? The quantity of stats that libraries track is staggering and keeps growing. This program will encourage attendees to stop and evaluate what and why they're gathering data and help identify possible alternatives to …
Big Data In Single Player Games, Mohammad Khaldoun Farhan Aldaboubi
Big Data In Single Player Games, Mohammad Khaldoun Farhan Aldaboubi
Computer Science and Engineering Theses
Improving video games can be exponentially more efficient by utilizing big data. Big data plays a big part in modern gaming, especially for multiplayer games like poker, first person shooter games. Utilizing the data gathered from video games can be used in ways that will improve the player experience massively and can be eye-opening to find issues, player pattern, and improve the game in ways that will be hard to pin point without gathering data of how the players are playing the game. However, while big data is being utilized in multiplayer games, it’s not utilized as much in single …
Context Aware Data Generation Through Domain Specific Language, Caleb Druckemiller
Context Aware Data Generation Through Domain Specific Language, Caleb Druckemiller
Other Student Works
No abstract provided.
Data Governance And The Emerging University, Michael J. Madison
Data Governance And The Emerging University, Michael J. Madison
Book Chapters
Knowledge and information governance questions are tractable primarily in institutional terms, rather than in terms of abstractions such as knowledge itself or individual or social interests. This chapter offers the modern research university as an example. Practices of data-intensive research by university-based researchers, sometimes reduced to the popular phrase “Big Data,” pose governance challenges for the university. The chapter situates those challenges in the traditional understanding of the university as an institution for understanding forms and flows of knowledge. At a broad level, the chapter argues that the new salience of data exposes emerging shifts in the social, cultural, and …
A Machine Learning Approach To The Perception Of Phrase Boundaries In Music, Evan Matthew Petratos
A Machine Learning Approach To The Perception Of Phrase Boundaries In Music, Evan Matthew Petratos
Senior Projects Fall 2020
Segmentation is a well-studied area of research for speech, but the segmentation of music has typically been treated as a separate domain, even though the same acoustic cues that constitute information in speech (e.g., intensity, timbre, and rhythm) are present in music. This study aims to sew the gap in research of speech and music segmentation. Musicians can discern where musical phrases are segmented. In this study, these boundaries are predicted using an algorithmic, machine learning approach to audio processing of acoustic features. The acoustic features of musical sounds have localized patterns within sections of the music that create aurally …
Complex Systems Analysis In Selected Domains: Animal Biosecurity & Genetic Expression, Luke Trinity
Complex Systems Analysis In Selected Domains: Animal Biosecurity & Genetic Expression, Luke Trinity
Graduate College Dissertations and Theses
I first broadly define the study of complex systems, identifying language to describe and characterize mechanisms of such systems which is applicable across disciplines. An overview of methods is provided, including the description of a software development methodology which defines how a combination of computer science, statistics, and mathematics are applied to specified domains. This work describes strategies to facilitate timely completion of robust and adaptable projects which vary in complexity and scope. A biosecurity informatics pipeline is outlined, which is an abstraction useful in organizing the analysis of biological data from cells. This is followed by specific applications of …
A Data Analysis Of The World Happiness Index And Its Relation To The North-South Divide, Charles Alba
A Data Analysis Of The World Happiness Index And Its Relation To The North-South Divide, Charles Alba
Undergraduate Economic Review
In this document, we perform a detailed data analysis on the World Happiness Report with its relation to the socio-economic North-South Divide. In order to do so, we perform some extensive data cleaning and analysis before querying on the World Happiness Report. Our results based on Hypothesis Testing determines the happiness of the Global North is greater than that of the Global South. Furthermore, our queries show that the mean happiness score for the Global North significantly outweighing that of the South. Likewise, the 10 'Happiest' nations all belong to the Global North whereas the 10 'least happy' nations belong …