Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Singapore Management University (9368)
- Missouri University of Science and Technology (7203)
- City University of New York (CUNY) (3690)
- University of Nevada, Las Vegas (3619)
- Brigham Young University (2703)
-
- University of South Florida (2433)
- University of New Mexico (1991)
- University of Texas at Arlington (1989)
- University of Central Florida (1818)
- University of South Carolina (1789)
- Portland State University (1483)
- Syracuse University (1144)
- Chulalongkorn University (1139)
- University of Nebraska - Lincoln (961)
- University at Albany, State University of New York (862)
- Washington University in St. Louis (741)
- TÜBİTAK (645)
- The Texas Medical Center Library (540)
- Claremont Colleges (430)
- Loma Linda University (399)
- University of Denver (376)
- Old Dominion University (367)
- Utah State University (314)
- University of Kentucky (309)
- Wright State University (268)
- California State University, Monterey Bay (265)
- Regis University (260)
- Louisiana State University (257)
- Western Kentucky University (243)
- SIT Graduate Institute/SIT Study Abroad (238)
- Keyword
-
- Machine learning (745)
- Mathematics (481)
- 2014 International Conference on Hydroinformatics HIC (464)
- Artificial intelligence (428)
- Deep learning (399)
-
- Humans (352)
- Machine Learning (348)
- Climate change (262)
- College for Professional Studies (253)
- Chemistry (242)
- Sustainability (239)
- School of Computer & Information Science (236)
- Education (234)
- Agriculture (230)
- Deep Learning (216)
- Artificial Intelligence (215)
- College of Natural Science and Mathematics (209)
- Natural language processing (208)
- Security (206)
- Chemistry and Biochemistry (196)
- Mathematics Research (195)
- Algorithms (194)
- Statistics (194)
- Computer Science (193)
- Natural resources (183)
- Optimization (181)
- Geology (180)
- Privacy (167)
- Atmospheric chemistry (166)
- Early California maps (165)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (8548)
- Theses and Dissertations (3384)
- Physics Faculty Research & Creative Works (1959)
- Faculty Publications (1607)
- Electronic Theses and Dissertations (1404)
-
- Publications and Research (1351)
- UNLV Theses, Dissertations, Professional Papers, and Capstones (1270)
- Dissertations and Theses (1251)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (1117)
- Chemistry Faculty Research & Creative Works (939)
- Masters Theses (938)
- Computer Science Faculty Research & Creative Works (907)
- International Journal of Speleology (906)
- Dissertations, Theses, and Capstone Projects (836)
- Doctoral Dissertations (743)
- Legacy Theses & Dissertations (2009 - 2024) (741)
- Branch Mathematics and Statistics Faculty and Staff Publications (712)
- USF Tampa Graduate Theses and Dissertations (628)
- Physics - All Scholarship (554)
- Faculty, Staff and Student Publications (525)
- Open Educational Resources (473)
- International Conference on Hydroinformatics (464)
- Mathematics and Statistics Faculty Research & Creative Works (461)
- Arts & Sciences Graduate Student Theses and Dissertations (426)
- Computer Science Technical Reports (411)
- Loma Linda University Electronic Theses, Dissertations & Projects (399)
- Computer Science and Engineering Theses - Archive (365)
- School of Geosciences Faculty and Staff Publications (350)
- Mathematics Technical Papers - Archive (343)
- Earth and Planetary Sciences ETDs (317)
- Publication Type
Articles 1861 - 1890 of 58521
Full-Text Articles in Entire DC Network
Uc-1207 Ai Driven Resident Inquiry Processing, Ben Moran, Sahil Sachwani, Thomas Ashe, Sean Johnson
Uc-1207 Ai Driven Resident Inquiry Processing, Ben Moran, Sahil Sachwani, Thomas Ashe, Sean Johnson
C-Day Computing Showcase
The AI Driven Resident Inquiry Processing System is designed to enhance the National Housing Compliance (NHC) ability to process resident inquiries using artificial intelligence(AI). NHC is a 501(c)(4) not-for-profit corporation who provides training and compliance services to the affordable housing industry. Each month NHC receives over 200 inquiries from residents via phone and email. These inquiries range from general questions to urgent, life-threatening concerns. Efficiently processing and responding to these inquiries is often critical to resident safety and well being. This project uses AI to automate resident inquiries as they are received, extract and classify key information, and display this …
Uc-1226 Iknowit: Multilingual Smartphone Tutorial Platform, Jacqueline Juarez, David Bazan, Julissa Rivera
Uc-1226 Iknowit: Multilingual Smartphone Tutorial Platform, Jacqueline Juarez, David Bazan, Julissa Rivera
C-Day Computing Showcase
Digital literacy challenges affect millions of adults who struggle with basic smartphone use due to rapidly changing technology and limited support. iKnowIT is a dynamic, web-based learning platform designed to provide clear, visual, and multilingual tutorials that guide users through essential device functions. The goal of iKnowIT is to bridge the digital divide and empower users to engage confidently with modern technology
Mobile Computer Vision Application For Agricultural Disease Detection Of Pepper Diseases Using Two-Stage Deep Learning System, Carlos Jose Estevez, Mai Dang, Ryan Bass
Mobile Computer Vision Application For Agricultural Disease Detection Of Pepper Diseases Using Two-Stage Deep Learning System, Carlos Jose Estevez, Mai Dang, Ryan Bass
SMU Data Science Review
Plant diseases pose a significant threat to food security, particularly in developing countries where farmers often lack the resources and infrastructure for early detection. In nations like Mexico and the Dominican Republic, the spread of harmful plant diseases impacts key agricultural commodities, such as habanero peppers, leading to substantial yield losses. This study presents a computer vision system based on Convolutional Neural Networks (CNNs) and an object detection model (YOLO) to help farmers detect pepper diseases efficiently. The system uses a two-stage approach: YOLOv11n first detects pepper leaves in images, then a lightweight MobileNetV3Small model classifies whether the detected leaves …
A Decolonial Approach To International Education: Insights From A Cal Poly Global Program In Palermo, Sicily., Elvira Pulitano, Iyad Jamaly
A Decolonial Approach To International Education: Insights From A Cal Poly Global Program In Palermo, Sicily., Elvira Pulitano, Iyad Jamaly
csuglobaljournal
This article presents a critical intervention in the current debates about decolonizing international education. It is based on a Global Program in Palermo, Sicily, offered by Cal Poly San Luis Obispo in summer 2023. As both program creator/director and student participant in the program, the authors rely on their personal experience and insights along with expertise in coloniality and decolonial theories. The article focuses on a series of pedagogical activities led by a young group of migrants and refugees who, in the city of Palermo, have come together to form two associations designed and structured to offer new contemporary models …
When Scripts Diverge: Strengthening Low-Resource Neural Machine Translation Through Phonetic Cross-Lingual Transfer, Ammon Shurtz
When Scripts Diverge: Strengthening Low-Resource Neural Machine Translation Through Phonetic Cross-Lingual Transfer, Ammon Shurtz
Theses and Dissertations
Multilingual Neural Machine Translation (MNMT) models enhance translation quality for low-resource languages by exploiting cross-lingual similarities during training--a process known as knowledge transfer. This transfer is particularly effective between languages that share lexical or structural features, often enabled by a common orthography. However, languages with strong phonetic and lexical similarities but distinct writing systems experience limited benefits, as the absence of a shared orthography hinders knowledge transfer. To address this limitation, we propose an approach based on phonetic information that enhances token-level alignment across scripts by leveraging transliterations. We systematically evaluate several phonetic transcription techniques and strategies for incorporating phonetic …
Privacy In Flux: A 35-Year Review Of Trends, Legal Evolution, And Emerging Challenges, Kong Phang, Jihene Kaabi
Privacy In Flux: A 35-Year Review Of Trends, Legal Evolution, And Emerging Challenges, Kong Phang, Jihene Kaabi
Research & Publications
Privacy harms have expanded alongside rapid technological change, challenging the adequacy of existing regulatory frameworks. This systematic review (1990–2025) systematically maps documented privacy harms to specific legal mechanisms and observed enforcement outcomes across jurisdictions, using PRISMA-guided methods and ROBIS risk-of-bias assessment. We synthesize evidence on major regimes (e.g., GDPR, COPPA, CCPA, HIPAA, GLBA) and conduct comparative legal analysis across the U.S., E.U., and underexplored regions in Asia, Latin America, and Africa. Key findings indicate increased recognition of data subject rights, persistent gaps in cross-border data governance, and emerging risks from AI/ML/LLMs, IoT, and blockchain, including data breaches, algorithmic discrimination, and …
Stars And Shapes: An Investigation Of Stripped Envelope Supernovae Structures Using Spectropolarimetry Observations And Hydrodynamic Models, Sabrina Desoto
Stars And Shapes: An Investigation Of Stripped Envelope Supernovae Structures Using Spectropolarimetry Observations And Hydrodynamic Models, Sabrina Desoto
Electronic Theses and Dissertations
Supernovae (SNe) are the energetic deaths of massive stars, dispersing heavy elements throughout the galaxies and shaping cosmic evolution across the universe. However, understanding the connections between the evolution of massive stars, their catastrophic demises, and the myriad of observed SNe, remains a fundamental challenge in astrophysics. My work aims to narrow this gap by integrating extensive observational data with advanced hydrodynamical simulations to better interpret SNe observations and understand the origin of their geometry. The observational component utilizes the largest spectropolarimetry dataset of stripped-envelope (SE) core-collapse supernovae (CCSNe) gathered by the SNSPOL project. Analyzing nine Type Ib and eleven …
Principal Quandles, Jesse Parrish
Principal Quandles, Jesse Parrish
Electronic Theses and Dissertations
This thesis concerns principal quandles and, as a special case, Alexander quandles. A principal quandle is a coset quandle, Q(G,H, f), in which the subgroup H is trivial. If in addition the group G is abelian, then the coset quandle is called an Alexander quandle. The isomorphism types of Alexander quandles were classified [16], and some progress was made on describing the isomorphism types of principal quandles in [14] and [13]. The first part of this thesis applies the ideas used in Holmes’ paper to give a classification of the isomorphism types of principal quandles. The second …
Exploring The Impact Of Statistics Course Modality On Student Learning: A Mixed Methods Approach, Becky Kelleman
Exploring The Impact Of Statistics Course Modality On Student Learning: A Mixed Methods Approach, Becky Kelleman
Electronic Theses and Dissertations
The importance of statistical literacy has become increasingly evident, as individuals grapple with interpreting statistics to inform critical decisions. Despite the recognized significance of statistical literacy, challenges persist in both educators’ and students’ efforts to navigate the complexities of statistics education. The purpose of this study is to explore the impact of different course modalities on undergraduate students’ academic performance in introductory statistics courses. Using Social Cognitive Theory (SCT) as a theoretical framework, this research aims to shed light on the complex dynamics influencing statistical literacy attainment. By addressing gaps and inconsistencies in the current literature, this study seeks to …
High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology., Salah Ahmed Abdullah Eltief
High Frequency Dc-Dc Converter Design Optimization, Modeling And Control Based-Wbg Technology., Salah Ahmed Abdullah Eltief
Electronic Theses and Dissertations
The performance of DC-DC power converters is a cornerstone of modern electric vehicle (EV) powertrains, directly governing overall system efficiency, size, cost, and reliability. This dissertation presents a comprehensive performance analysis and optimization of DC-DC converter topologies to determine the most suitable design for high voltage EV applications. The evaluation rigorously compares efficiency, power losses, and physical size under a range of harsh operating conditions. A primary objective is to leverage Wide Bandgap (WBG) semiconductors, specifically Silicon Carbide (SiC), to push the performance boundaries of power conversion. While SiC devices are known for their superior material properties, a clear understanding …
Controls On Speleothem Carbon Isotopes, Paloma Marcos
Controls On Speleothem Carbon Isotopes, Paloma Marcos
Undergraduate Research Symposium Posters
The Sistema Huautla cave system is the deepest known in the Western Hemisphere. It is located in the Sierra Mazateca Mountain Ranges near Jiménez de Huautla, Oaxaca. There are over 29 separately discovered entrances into this karst environment making it the 28th longest cave system in the world. It can be considered by some as one of the most complex vertical drainage systems on Earth. This extensive study site has been an area of interest among cavers and scientific researchers for nearly 6 decades. Speleothem samples from the study sites have been found to be over 433,000 years old. The …
Non-Invasive Infection Detection Framework: Smartphone-Based Hematologic And Thermal Biomarker Monitoring, Nafi Us Sabbir Sabith
Non-Invasive Infection Detection Framework: Smartphone-Based Hematologic And Thermal Biomarker Monitoring, Nafi Us Sabbir Sabith
Dissertations (1934 -)
Infectious diseases remain one of the leading global causes of illness and death in both community and hospital settings. Infections lead to lasting health issues, such as life-threatening chronic conditions or even cancer. Early detection is crucial for timely intervention, such as isolation and treatment. Hematology originated from the Greek word haima, meaning blood. It is a unique discipline in medicine that involves the study of blood and its contents. White blood cells (WBC) are at the forefront of the body’s immune system. WBCs are categorized into five main subtypes: neutrophils, lymphocytes, monocytes, eosinophils, and basophils. Monitoring the total WBC …
Simulation Of Fluid Flow Based On Navier Stokes Equations, Ricardo Marquez, Javier Perez
Simulation Of Fluid Flow Based On Navier Stokes Equations, Ricardo Marquez, Javier Perez
Undergraduate Research Symposium Posters
This work presents a computational study of incompressible flow based on the Navier-Stokes equations using finite element method. The Crank-Nicolson approximation is used for discretizing the time derivative. The study consists of investigating the effect of the choice of finite elements and the size of the time step in obtaining the numerical velocity and pressure. This is illustrated with FreeFEM++ simulations of the von Karman benchmark flow problem. Profiles of drag, lift and pressure drop will be presented in time.
The Mathematics Of Motion: Applying Derivatives To Fluid Systems, Sayla Daily
The Mathematics Of Motion: Applying Derivatives To Fluid Systems, Sayla Daily
Undergraduate Research Symposium Posters
Mathematical modeling through differential equations provides a basis for understanding change in physical and engineering systems. My project explores the transition from single-variable derivatives to multivariable partial derivatives and their applications in describing engineering applications. Beginning with the Fundamental Theorem of Calculus, derivatives are introduced as measures of change, quantifying relationships such as velocity and acceleration. The study then extends to partial derivatives, which represents systems influenced by multiple variables, including spatial and temporal factors. These principles are applied to model fluid motion, and pressure gradients, including the Navier–Stokes equations governing fluid dynamics. By linking mathematics with engineering applications, this …
Doughnut Economics And Strong Sustainability: Rethinking The Role Of Financial Investment, Isabelle Pierotti
Doughnut Economics And Strong Sustainability: Rethinking The Role Of Financial Investment, Isabelle Pierotti
Electronic Theses and Dissertations
This thesis investigates how private investment could align doughnut economic framework. Doughnut economics is a strong sustainability economic framework where the economy operates within planetary boundaries while ensuring social equity. Theories of sustainable development, weak sustainability, and strong sustainability are discussed to provide theoretical context for doughnut economics and mainstream economics. The analysis concludes that conventional, profit maximizing private investment does not support a doughnut economics system by supporting the depletion of natural resources and exacerbating social issues. Sustainable mainstream investment also fails to support a doughnut framework. Lastly, while impact investment is theoretically committed to social and financial returns, …
Archaeological Predictive Meta-Modeling In Pre-Columbian Mexico, Peter Stamm
Archaeological Predictive Meta-Modeling In Pre-Columbian Mexico, Peter Stamm
Electronic Theses and Dissertations
Archaeological Predictive Modeling stands firmly as an important tool for Archaeologists to predict undiscovered sites from civilizations all across the globe. While powerful, this methodology is not without its own set of qualms. Striking a balance between pure a data-driven approach while also observing leading expert theories can be a complicated task. Going further, deciding on the specific domain of features to emphasize or overlook can be a challenge within itself, as one misstep can drastically change the output of model, sometimes for the worst. In addition, creating models that can expose their reasoning process can be rather difficult to …
Exploring Inorganic And Organometallic Chemistry, W. Christopher Boyd Phd
Exploring Inorganic And Organometallic Chemistry, W. Christopher Boyd Phd
MSL Academic Endeavors eBooks
This textbook, Exploring Inorganic and Organometallic Chemistry, covers the fundamentals of inorganic and organometallic chemistry for undergraduate and graduate students. Both theories of structure and bonding and reaction chemistry are covered, with applications to the catalysis of organic reactions, biochemistry, and drug design. A modular approach allows for basic materials of each chapter to be covered in an undergraduate course, with more advanced material suitable for M.S. and Ph.D. students."
Enhancing Recommendation Performance Via Stacking Ensemble And Synthetic Data Augmentation, Zahraa Yaareb Hani, Mohsin Hasan Hussein
Enhancing Recommendation Performance Via Stacking Ensemble And Synthetic Data Augmentation, Zahraa Yaareb Hani, Mohsin Hasan Hussein
Karbala International Journal of Modern Science
Recommendation systems are essential tools that primarily aim to help users navigate through a large volume of information. They simplify the decision-making process by suggesting relevant items based on users’ historical behaviour. However, their performance is often affected by common problems such as data sparsity. This work proposes a stacking-based ensemble recommendation system that integrates multiple machine learning models to enhance the model’s predictive performance. A new synthetic data augmentation technique is introduced to address the sparsity issue in the user–item rating matrix. This method uses the Naïve Bayes algorithm to predict additional ratings for each user. These are then …
Safety, Security, And… Beavers? An Engineer's Low-Tech Climate Strategy, Matt Mullins
Safety, Security, And… Beavers? An Engineer's Low-Tech Climate Strategy, Matt Mullins
University College: Environmental Policy and Management Capstones
Colorado’s headwaters are the source of drinking water to millions and are a key pillar of the state’s tourism industry. Consequently, they are some of the most vulnerable areas to natural disasters including wildfires, droughts and flooding. Climate change will increase the severity and frequency of these natural disasters. This project focuses on some of the most vulnerable areas from an economic and climate change perspective of Colorado’s headwaters including the Big Thompson River, and the Colorado River. These headwaters located in and around Estes Park, Grand Lake and Rocky Mountain National Park are currently severely impaired. Low-tech process-based restoration …
Creating An Iot User Centric Security And Privacy Label, Luke Joseph Gleba
Creating An Iot User Centric Security And Privacy Label, Luke Joseph Gleba
Theses and Dissertations
Concerns for cybersecurity awareness and training in the public have been rising at astronomical rates over the past few years. People globally have entered a critical intersection with computers. Computers are being used in everyday life, and users do not have an easy way to understand their own cyber risk. Consumers deserve to know how secure their new Internet of Things (IoT) system is in a quick, efficient way before they purchase the device and while they own it. The following research looks to improve on ideas for the criteria and the development of a security label. Few prototypes currently …
Synergistic Doping And Coating Strategy For Boosting Na0.7mno2 Cathode Performance In Sodium-Ion Batteries, Ahmad Helaley, Han Yu, Manashi Nath, Xinhua Liang
Synergistic Doping And Coating Strategy For Boosting Na0.7mno2 Cathode Performance In Sodium-Ion Batteries, Ahmad Helaley, Han Yu, Manashi Nath, Xinhua Liang
Chemistry Faculty Research & Creative Works
Advancing sodium-ion battery (SIB) technology requires novel approaches to optimize cathode materials for improved electrochemical performance. In this study, we employ atomic layer deposition (ALD) to precisely modify the surface of P2-type Na0.7MnO2 cathodes with different coating materials including ZnO, NiO, and Al2O3, followed by post-annealing at 750°C for 10 hours. The strategic combination of ALD and thermal treatment can achieve thin film coating on particle surface and promote element doping into the near-surface lattice, as confirmed by electron energy loss spectroscopy (EELS) analysis. The incorporation of Zn, Al, and Ni results in …
Unraveling Hydration- And Temperature-Induced Structural Transformations Of Linear Poly(Ethylenimine) Using Raman Microscopy And Numerical Unmixing, Miharu Koh, Jay P. Kitt, Andrew D. Pendergast, Joel M. Harris, Shelley D. Minteer, Carol Korzeniewski
Unraveling Hydration- And Temperature-Induced Structural Transformations Of Linear Poly(Ethylenimine) Using Raman Microscopy And Numerical Unmixing, Miharu Koh, Jay P. Kitt, Andrew D. Pendergast, Joel M. Harris, Shelley D. Minteer, Carol Korzeniewski
Chemistry Faculty Research & Creative Works
Linear poly(ethylenimine) (LPEI) is a hydration-sensitive polymer of interest for its breadth of application in areas that include medicine, energy, and materials science. To facilitate advances, this work demonstrates in situ Raman microscopy and self-modeling curve resolution (SMCR) analysis as an approach for investigating changes in LPEI structure during melting and crystallization under controlled heating and cooling conditions. With focus on neutral (freebase) LPEI, SMCR analysis of Raman data sets showed that the melting transition of anhydrous LPEI was well described by a pair of spectral vectors representing anhydrous crystalline and amorphous states. However, the transition from the melted to …
The Relationship Between Lineaments And Cave Passages In Unfaulted Gently-Folded Strata, Snail Shell Cave, Central Tennessee, Usa, Mark Abolins, Joseph Firkaly-Paciera, Blake King, Cris Ocasio-Valentin, Jackson Slighter, Teagan Sullivan, Justin Whited
The Relationship Between Lineaments And Cave Passages In Unfaulted Gently-Folded Strata, Snail Shell Cave, Central Tennessee, Usa, Mark Abolins, Joseph Firkaly-Paciera, Blake King, Cris Ocasio-Valentin, Jackson Slighter, Teagan Sullivan, Justin Whited
International Journal of Speleology
Near Snail Shell Cave in central Tennessee, USA, seven image interpreters independently mapped lineaments using a 3DEP LiDAR DTM, revealing geomorphic and structural differences in and near different parts of the cave. MANOVA comparison of lineament and cave passage trend for Western, Central, and Eastern Snail Shell caves reveals statistically significant differences (p <0.05). The Western cave (mean depth 44 m) is in the gently-dipping limb of the Snail Shell anticline, and the Central cave (mean depth 31 m) is in the anticline hinge. In contrast, many Eastern cave passages (mean depth 40 m) cut across the anticline hinge and part of the limb of the Overall syncline. For both the Western and Central caves, a post-hoc Tukey’s HSD test fails to show that lineament trend within 235 m of the cave differs significantly from passage trend, and the test fails to show that the two differ significantly within 235 and 433 m of the Eastern cave. Additional statistical testing fails to show a difference between Western passage trend and bed strike, indicating the likelihood that lineaments and passages developed within strike-joints. However, testing shows a statistically significant difference between passage trend and bed strike for the Central and Eastern caves. The strike of joints inside the Eastern cave shows that it is within a joint zone which penetrates to depths of at least 80 m and is expressed at the surface as an ~4.2 km-long belt of elevated lineament line density. The lack of a statistically significant difference between Eastern passage trend and the trend of a nearby topographic escarpment suggests that many joints are stress release fractures formed during relatively recent erosion. For the Eastern cave, intersections between lineaments and structures would be attractive targets for groundwater exploration at depths typical of wells in carbonates.
A Bioarchaeological Study Of The Individuals From The Városfalva Burial Mound In Transylvania, Romania (15th-19th Century), Vanessa C. Reeves
A Bioarchaeological Study Of The Individuals From The Városfalva Burial Mound In Transylvania, Romania (15th-19th Century), Vanessa C. Reeves
USF Tampa Graduate Theses and Dissertations
This study explores the lives and deaths of the Szekler people recovered from a burial mound in the Transylvanian village of Városfalva. The Transylvanian plateau is located in present day Romania, and is protected on the east and the south by the Carpathian Mountains. The Szekler people arrived in this area around 1000 CE, and were a nomadic group originating in the Asian Steppes region who later intermarried with various migratory groups as they moved across the Eurasian plains. The Szeklers eventually banded together with the proto-Hungarian Magyar peoples and settled in the Carpathian Basin, the easternmost frontier of the …
Quality Assessment Of Pathology Board-Exam-Style Mcqs Produced By Chatgpt3.5: A Comparative Study, Arianna B. Morton, Zunaira Naeem, Allison F. Goldberg, Alexis R. Peedin, Joanna Chan
Quality Assessment Of Pathology Board-Exam-Style Mcqs Produced By Chatgpt3.5: A Comparative Study, Arianna B. Morton, Zunaira Naeem, Allison F. Goldberg, Alexis R. Peedin, Joanna Chan
Department of Pathology, Anatomy, and Cell Biology Faculty Papers
Residents preparing for pathology board exams frequently use multiple-choice questions (MCQs) from question banks (QBs) like PathDojo and PathPrimer, which can be costly. ChatGPT, a free tool, has been used to generate MCQs for other tests like the SAT. This study compared the quality of pathology MCQs created by ChatGPT versus commercially available study questions for the American Board of Pathology’s (ABPath) certifying exams. A rubric adapted from the National Board of Medical Examiners’ (NBME) question writing guide was validated by two pathologists using commercially available pathology board exam questions. This rubric was then used to evaluate MCQs from commercially …
Preparing For The Artificial Intelligence (Ai) Economy In The Mountain West, 2025, Kian Parikh, Taylor Volk, Maisoon Faris, Kristian Thymianos, William E. Brown Jr.
Preparing For The Artificial Intelligence (Ai) Economy In The Mountain West, 2025, Kian Parikh, Taylor Volk, Maisoon Faris, Kristian Thymianos, William E. Brown Jr.
Economic Development & Workforce
This fact sheet presents data from the Brainly report, “Here Are the States Most (and Least) Prepared to Win the AI Race in 2025” for the five Mountain West states of Arizona, Colorado, New Mexico, Nevada, and Utah. This fact sheet highlights the national and individual rankings of four key metrics for each Mountain West state: the fixed percentage of businesses using artificial intelligence (AI); the number of AI jobs per 1,000 workers; the number of AI-related degrees per 10,000 people ages 20-24; and federal funding for small business technology innovation per $1 million of gross domestic product (GDP).
Speculative Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja
Speculative Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja
Publications and Research
Efficiency is essential to support ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code---supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the "best of both worlds," using them effectively requires subtle considerations. Our key insight is that, while DL programs typically execute sequentially, hybridizing imperative DL code resembles parallelizing sequential code in traditional systems. Inspired by this, we …
Constraints On Inner Core Composition From Seismicanisotropy: The Importance Of Light Elements And Nickel, Jada Bollmeyer, Daniel A. Frost, Prajna Paramita Das
Constraints On Inner Core Composition From Seismicanisotropy: The Importance Of Light Elements And Nickel, Jada Bollmeyer, Daniel A. Frost, Prajna Paramita Das
Faculty Publications
The inner core is seismically anisotropic, with PKIKP waves traversing the inner core parallel to the rotation axis faster than those in the equatorial plane. This anisotropy increases with depth into the inner core and may result from alignment of iron crystals deformed during inner core growth. Using previously calculated elastic properties of iron, we seek to determine the most likely iron-light element alloy (FeC, FeO, FeS, or FeSi). For each FeX alloy, we interpolate elastic tensors across the pressure and temperature range of the inner core and model the anisotropy resulting from flow during core growth. Lastly, we compare …
Speculative Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja
Speculative Automated Refactoring Of Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian Ph.D., Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja
Publications and Research
Efficiency is essential to support ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code---supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the "best of both worlds," using them effectively requires subtle considerations. Our key insight is that, while DL programs typically execute sequentially, hybridizing imperative DL code resembles parallelizing sequential code in traditional systems. Inspired by this, we …
Connected-Component Labeling Using Hls For High-Energy Particle Physics Instruments, Nick Song, Marion Sudvarg, Roger Chamberlain
Connected-Component Labeling Using Hls For High-Energy Particle Physics Instruments, Nick Song, Marion Sudvarg, Roger Chamberlain
Computer Science Faculty Research & Creative Works
Many instruments used in high-energy particle physics observations, e.g., gamma-ray telescopes, use FPGAs for front-end signal processing of raw sensor data. The use of high-level synthesis (HLS) to express the signal processing algorithms has the potential to significantly reduce development time for new instruments of this type. We describe our experience with one of the computational stages in the signal processing pipeline, island detection, exploring its implementation across multiple configurations: 1D versus 2D islands, and 4-way versus 8-way connected-component labeling (CCL) in the 2D configuration. We report resource usage and performance for both configurations of 2D island detection, including the …