CADRE Conference Presentations


Recent Submissions

  • Publication
    Technology in the age of a pandemic: Challenges and solutions for a statewide COVID-19 response
    (Oklahoma State University, 2021-04-14) Taylor, Jared D.
  • Publication
    Performance metric distribution characteristics of medical school exam items
    (Oklahoma State University, 2021-04-14) Sajjadi, Nicholas B.; Terry, Lindsay; Price, Joseph, III
    Exams are used to measure student progress and subject mastery. Exam item performance can be assessed by Item Difficulty, Discrimination Index (DI), and Point Biserial (PB). A previous investigation descriptively characterized these metrics for 61 exams at the Oklahoma State University College of Osteopathic Medicine, however, the distribution characteristics remain unknown. The primary objective of this study was to determine the normality of the item Difficulty, DI, and PB for these 61 exams. Using the software suite R (version 4.0.2) and RStudio (Version 1.3.959) we performed graphical and numerical analysis of normality using both Q-Q plots (ggqqplot), and the Shapiro-Wilk Normality Test (ggpubr) as adjusted using the Benjamini-Hochberg procedure. For item Difficulty, 93.4% of exams had statistically significant deviations from normality. For DI, 63.9% of exams had statistically significant deviations form normality. For PB, 11.5% of exams had statistically significant deviations from normality. Our results suggest that item performance indicators vary drastically in their distribution characteristics within our sample. Our findings support the use of inferential statistics relying the assumption normality for PB but not item Difficulty or DI. These results may be useful for curriculum directors and test-writers.
  • Publication
    OURRstore: The OU and Regional Research Store
    (Oklahoma State University, 2020-04-17) Neeman, Henry
    The data tsunami is upon us: transformative research is increasingly data-intensive, with collections in TB to PB, and Exabytes (EB) coming soon. Projections of research storage growth show that, by 2025, research data will outstrip even YouTube. Yet many institutions are underprepared not only for the "volume, velocity and variety" of data, but especially for stewardship of exponentially growing collections. The University of Oklahoma (OU) has been awarded a National Science Foundation grant that has acquired, and will deploy and maintain, for 8+ years, a large scale storage resource -- the OU & Regional Research Store (OURRstore) -- to enable faculty, staff, postdocs, graduate students and undergraduates to pursue data-intensive research, by building large and growing data collections, to share these datasets with collaborators and even the public, and to provide this capability to all institutions in (a) the Great Plains Network and (b) Established Program to Stimulate Competitive Research (EPSCoR) jurisdictions. Via an innovative, low cost business model, researchers will buy their own tape cartridges, good for 8+ years, and pay zero usage charges (just cartridge and shipping costs). OURRstore is expected to have hundreds of users.
  • Publication
    Graphical user interfaces as chemical engineering educational tools in university and informal learning environments
    (Oklahoma State University, 2020-04-17) Ford Versypt, Ashlee N.
    I will discuss the development and use of graphical user interfaces (GUIs) as cyber-assisted educational tools for instructing and engaging undergraduate chemical engineering students, training graduate students for computational research in science and engineering, and introducing lay audiences to chemical engineering concepts in informal learning environments outside of the classroom. MATLAB and Python both provide excellent user support for rapid development of professional-quality GUIs by engineering educators, academic researchers, and science and engineering undergraduate and graduate students. These GUIs can be distributed and run easily by novice users without any prior programming experience. I will provide examples of customized GUIs from my research lab and courses that demonstrate their use in the undergraduate curriculum, in an interdisciplinary upper division/graduate elective called Applied Numerical Computing for Scientists and Engineers, and in several informal learning environments for science, technology, engineering, and mathematics (STEM) outreach. The informal learning environments where my team has utilized these GUIs include a pre-college program for incoming engineering freshmen, a summer camp for children of university alumni and the campers’ grandparents, and a hands-on science fair featuring interactive demonstration booths for middle school and high school girls and their teachers.
  • Publication
    Data workshops in support of researchers at the University of Oklahoma
    (Oklahoma State University, 2020-04-17) Schilling, Amanda; Laufersweiler, Mark; Curry, Claire; Tweedy, Brent
    OU Libraries is in their third semester of offering research data workshops that focus on the skills and tools needed by students, staff, and faculty who are involved in research. We developed curriculum based on The Carpentries lessons in order to offer shorter, 1 – 2.5-hour workshops more frequently than the typical two-day Carpentries workshops. We organized the workshops into three categories to reflect researcher needs: Survival Skills to teach research data basics (such as backups, data formatting, and file organization); Better Practices to teach data practices that many researchers will use but may not be applicable to all individuals (such as version control and data management plans); and Workflow Tools to teach specific beginner and intermediate tools (such as graphing in R and Python and formatting documents in LaTeX). Slides, instructor notes, and workshop materials are available to the community at OU and beyond through Open Science Framework with a CC-BY license to facilitate curriculum sharing. This poster will outline the various workshops we offer, campus participation thus far, and some feedback from learners.
  • Publication
    Comprehensive study of mobility related function in clinical notes
    (Oklahoma State University, 2020-04-17) Thieu, Thanh; Camacho Maldonado, Jonathan; Ho, Pei-Shu
    Use of free text in Electronic Health Records (EHRs) for clinical, administrative, and research purposes has proliferated in recent years. Using the Mobility domain of the ICF as a framework, we comprehensively analyze the structure and characteristics of mobility related concepts found in physical therapy notes from the National Institutes of Health’s Clinical Center. The result is a mobility entity framework comprised of 5 entities types, 3 relations, 8 attributes, and 33 attribute values. Two domain experts manually curated a gold standard corpus of 14,281 nested entity mentions from 400 clinical notes. Inter-annotator agreement (IAA) of exact matching averaged 92.3% F1-score on mention text spans, and 96.6% Cohen’s kappa on attributes assignments. A novel ensemble machine learning model for named entity recognition was trained and evaluated using the gold standard corpus. Average F1-score on exact entity matching of our ensemble method (83.31%) outperformed both baseline methods: a probabilistic graphical model (80.4%), and an artificial neural network (81.82%). Overcoming the irregularities and challenges in capturing functioning concepts, this work pioneers a representational framework, an annotated gold standard corpus, and a cutting-edge machine learning model that identify concepts in the Mobility domain of the ICF.
  • Publication
    How data shapes our response to crises
    (Oklahoma State University, 2020-04-17) Sauls, Garrett
    Though data is everywhere, it is often undervalued and underutilized - that is until disaster strikes. Natural disasters, economic downturns and, most recently, global pandemics have a way of bringing data to the front of people's minds. So, how does data (or lack of it) shape our response to these events? With clients in nearly every industry, data consulting firm InterWorks plays a unique role in helping others address these challenges. In this session, InterWorks Communications Manager Garrett Sauls will draw from the collective experience of the global InterWorks team to paint a broad picture of how different organizations are using data to respond to the current Novel Coronavirus (COVID-19) pandemic. He'll also share some useful resources to help you dive into the data on your own.
  • Publication
    TRAIL: Technical Report Archive and Image Library
    (Oklahoma State University, 2020-04-17) Rohrig, Tom; Sare, Laura
    Technical Reports might not be the first information resource people think about when seeking data resources, but many federal agencies have published reports containing data on many different topics. Technical Reports communicate research in science and technology, technical development, and contain valuable information serving specialized audiences of researchers. Scholarly research papers often summarize research findings but technical reports often lay out the detail and data of research. This poster will introduce attendees to the TRAIL (Technical Report Archive and Image Library) Project and why this is a unique source for a variety of topics such as climate studies from research labs and agencies like the Corps of Engineers. Technical reports have always been challenging because of inconsistent and differing dissemination practices, no title level cataloging, and series level records with no holdings making it challenging to get technical reports via ILL. TRAIL is digitizing federal agency technical reports in print and microformats and cataloging them at the item level and depositing them in the HathiTrust and University of North Texas digital repositories where they are viewable to anyone in the world. Attendees can also learn more about Technical Reports and TRAIL and how to publicize this resource to their patrons.
  • Publication
    ACRL Project Outcome
    (Oklahoma State University, 2020-04-17) Davis, Greg
    Project Outcome is a FREE online toolkit designed to help libraries understand and share the impact of digital service initiatives and other essential library programs and services. Project Outcome provides simple surveys and an easy-to-use process for measuring and analyzing outcomes. These outcomes can be analyzed to help digital service providers determine whether and how their programs and services benefit patrons and make an impact on their lives.
  • Publication
    Towards exascale DNS solver for hypersonic boundary-layer receptivity to solid particulates
    (Oklahoma State University, 2020-04-17) Oz, Furkan; Kara, Kursat
    Development in hypersonic vehicles is dependent on the prediction of hypersonic boundary-layer transition location from a laminar to turbulent state because aerodynamic heating, drag force, engine performance, and vehicle operation are highly affected by the boundary-layer transition. To make precise prediction about boundary-layer transition points, it is required to understand the fundamental physics behind it. Although some key mechanisms are enlightened with recent studies, there are still unsolved part of this complex physics. Process of transformation of external disturbances into instability waves which grow in the downstream and causes to turbulence is called as receptivity. Small solid particles suspended in the atmosphere may be a significant source of boundary-layer instabilities. Their sizes in micro scales. Since particulate sizes are very small, fine meshes are used to catch the small disturbances that is induced by these small particulates and this makes parallelizing the solver inevitable. For more complex cases, heterogonous and exascale computing is required to obtain the results in a practical time period. In this poster, progress towards a physics-based parallel direct numerical simulation (DNS) tool to simulate the dynamic interaction of particulates, particulate-induced vortical disturbances, acoustic waves, and surface roughness with boundary-layer from the first principles will be presented.
  • Publication
    Software comparison for clinical Named Entity Recognition (NER): A phase-1 study for developing a computer assisted medical claims billing and coding system
    (Oklahoma State University, 2020-04-17) Chen, Suhao; Thieu, Thanh; Miao, Zhuqi
    Claims billing and coding is non-trivial for health care providers. Accurate coding can help medical providers get reimbursements that they deserve for their professional services. Meanwhile, incorrect coding (e.g. up-coding) is considered by authorities to be one of the most important frauds with severe penalties. Therefore, accurate coding is of great importance to medical professionals. However, claims coding is challenging. Besides the knowledge of the E/M coding system, accurate coding requires an adequate depiction of patient health conditions and treatments, part of which are contained in unstructured clinical notes, e.g. discharge summaries and physician notes. We aim to develop a coding decision support system by leveraging state-of-the-art natural language processing (NLP) techniques and algorithms. The expected result of the project is to build an effective system that can extract essential information for claims coding from real clinical narratives. This phase-1 study compared five popular existing NLP software in named entity recognition based on 108 public available transcribed medical discharge summary notes from Qualitative comparison finds that CLAMP, Amazon Comprehend Medical, and cTAKES are more powerful. Quantitative analysis shows that CLAMP is more accurate and efficient than Amazon Comprehend Medical. Future work includes integrating a section segmentation tool before NER recognition as well as testing and implementation of the system in a clinical scenario.
  • Publication
    How similar are sources of content for courses?
    (Oklahoma State University, 2020-04-17) Price, Joseph A., III
    For course content selection, to establish a measure of consensus on topics of relevance, and to compare sources of content, a novel quantitative method was developed and applied to a medical school course. Sources included texts, board review books, and a listing of topics currently taught in the course. Data mining of topics from sources developed data as binary encoded lists of what was present (among 350 topics) before two classical similarity measures were used to compute relatedness in pairwise comparisons of 13 sources. Relatedness was not always as expected. Total topics included ranged from highest in the course handouts, to lower in all other sources. This quantitative indication is opposed to reliance on subjective impressions, and can help faculty make better choices on content topics to include in a course and to compare texts.