Physical Sciences and Mathematics Commons^™

Implication Of Generative Ai On Education And Research, Riddhi Gupta

The Journal of Purdue Undergraduate Research

No abstract provided.

A Meteorological Investigation Of A Tornado- Producing, “Hybrid” Supercell-Multicell Storm Near Delphi, Indiana, On May 8, 2023, Evelyn Rose K. Girardi

The Journal of Purdue Undergraduate Research

No abstract provided.

Where To Build Food Banks: A Machine Learning Approach, Gavin Ruan

The Journal of Purdue Undergraduate Research

Over 44 million Americans currently suffer from food insecurity, of whom 13 million are children. Food insecurity has been shown to cause a wide range of both physical and developmental issues. Across the United States, thousands of food banks and pantries serve as vital sources of food and other forms of aid for food-insecure families. By optimizing food bank locations, food banks and their resources would become more accessible to families who desperately require it. The aim of this paper is to build a machine learning framework that is able to optimize food bank locations and to consider factors such …

Security At Too High An Environmental Cost?: The European Union's Energy Independence Strategy And Its Environmental Implications For Air Quality In Poland And Hungary, Stephanie P. Peterson

The Journal of Purdue Undergraduate Research

After Russia’s invasion of Ukraine in 2022, the European Union worked to secure liquified natural gas (LNG) deals with third countries to abolish its dependence on Russian gas. In this article, I sought to determine the environmental implications of the European Union’s new LNG deals on the air quality in Hungary and Poland, two former communist states. Despite LNG being a cleaner fossil fuel, I hypothesized that it posed a threat to Hungary’s and Poland’s air quality as both countries endured rapid industrialization under Soviet control that forwent environmental protections. To prove this, I used qualitative data from before the …

Predictive Maintenance Analysis Of Turbofan Engine Sensor Data, Stanley A. Melkumian

The Journal of Purdue Undergraduate Research

Predictive maintenance in aviation and aerospace applications is among the most explored problems in machine learning (ML) and artificial intelligence (AI), and datasets such as NASA’s C-MAPPS turbofan engine degradation simulation data have proven invaluable, helping researchers explore numerous questions on engine performance, maintenance, and failure. The purpose of this study was to extend the current research on predicting the remaining useful life (RUL) of engines and their risk classification. Starting with simple yet under-investigated nonlinear survival and random forest models, the analysis implemented eXtreme Gradient Boosting (XGBoost) and long short-term memory (LSTM) from TensorFlow’s Keras library. For both regression …

The Influence Of Soil Properties And Land Management On Soil Porewater Chemistry, Bethany Kettleborough

The Journal of Purdue Undergraduate Research

Soil water dynamics influence vegetation health, soil geochemical reactions, and stream chemistry. Water dynamics can be controlled by soil type and land management. It is important to understand water movement due to its influence on soil weathering, microbial activity, and nutrient transport. Water movement can be investigated using water stable isotope variability as a tracer. The purpose of this ongoing study was to analyze stable isotopes and dissolved ions in prairie and agricultural land management sites in Nebraska and Illinois. Prairies typically contain deep-rooted grasses, while agricultural lands contain shallow-rooted row crops. Root depth is considered a major control on …

The Computational Eye. Deconstructing Style In Digital Art History, Paul Guhennec, Ellen Charlesworth

Artl@s Bulletin

With the aim of grounding digital methods in the art historic tradition, this paper uses the discussions around style as a springboard to ask how digital art history can extend beyond providing quantitative confirmation of known trends to enrich our current understanding of visual cultures. Drawing from the examples throughout this issue, we explore how an analysis of computational ways of seeing—or the ‘computational eye’—can expose the underlying preoccupations and priorities of our own research.

Afin de mieux ancrer les méthodes numériques dans la tradition de l’histoire de l’art, cet article se sert des discussions récentes autour du concept de …

Statistical Downscaling Of Climate Datasets With Deep Generative Model And Bayesian Inference, Guiye Li, Guofeng Cao

I-GUIDE Forum

Facing the challenges of global climate change, precise and high spatial resolution climate data are crucial and in pressing need for scientific research and analysis. However, most existing datasets are only available with very coarse spatial resolution and demand large-scale resolution enhancement. Meanwhile, climate datasets own much more intricate textures than natural images. Statistical downscaling or super-resolution (SR) with the deep-learning-based generative model might be a promising approach to address these challenges. It is worth noting that a learned Bayesian reconstruction with generative models (L-BRGM) method was proposed recently. The proposed Bayesian deep learning framework employs a single pre-trained generative …

Typology Of Atmospheric Conditions Leading To Dam Overtopping In The Eastern Us, Hodo I. Orok, Deanna Hence

I-GUIDE Forum

Statistical characterization of reanalysis datasets during over 300 hydrologic dam incidents between 2003 and 2022 will create a detailed typology of weather systems associated with dam overtopping in the eastern United States. Dam overtopping poses significant risks to infrastructure and public safety, necessitating a comprehensive understanding of the multi-scale atmospheric conditions that lead to such events. To better account for the natural flow of water to the affected dams, we will adopt a watershed-focused Principal Component Analysis (PCA) on regional atmospheric data collected from ERA5 alongside USGS streamflow and Stage IV precipitation observations to enhance understanding of high-risk weather conditions. …

Tradeoffs Of Generalization, Kyra M. Abrams, Peter T. Darch

I-GUIDE Forum

Models used in geospatial data science are often built and optimized for a specific local context, such as a particular location at a point in time. However, upon publication, these models may be generalized beyond this context, reused in research simulating or predicting other times and places. Without sufficient information or documentation, bias embedded in these models can in turn result in bias in the reuser’s research outputs. Drawing on a long-term qualitative case study of aging dams researchers and developers of models used by these researchers, we find significant documentation gaps. We combine a literature-based genealogy with interviews with …

Inter-Provincial Spatial Coupling Of Paddy Fields In China Has Accelerated The Water Consumption, Wenguang Chen, Wencai Zhang, Ming Lei, Ruqian Zhang, Zhenting Zhao, Enyi Xie, Jing Zhao, Xiangbin Kong

I-GUIDE Forum

Rice trade has played a significant role in ensuring global rice consumption security. However, the spatial coupling of paddy fields based on rice trade can also transfer ecological environmental effects and threaten the sustainability of local systems. As the largest rice producer and consumer in the world, as well as one of the countries with the lowest per capita water resources, studying the inter-provincial rice flow in China and its water resource utilization efficiency is of great significance for ensuring national rice security and water resource security. Research has found that, China's rice consumption decreased by 11.97 Mt from 2000 …

What Does A Scientist Look Like? Children's Perceptions Of Scientist Gender And Skin Tone, Angelina Joy, Channing J. Mathews, Adam Hartstone-Rose, Kelly Lynn Mulvaney

Purdue Center for Early Learning Faculty and Staff Publications

When asked to draw a scientist, children typically draw a gender stereotypical male representation; however, research has not yet assessed these representations in terms of scientist stereotypical skin tone. The current study examined children's (N = 69, 66.7% female, Mage = 7.60, SD = 2.13) scientist perceptions by analyzing both the gender and skin tone of their scientist drawings as well as stereotypical features represented (lab coats, scientific instruments, etc.). This study also examined how these perceptions as reflected in the drawings were related to children's explicit gender stereotypes and their science growth mindset. Boys were less likely …

Smart Airports: Artificial Intelligence–Enabled Internet Of Things Networks Using Blockchain Technology, Edwin Ongola

Journal of Aviation Technology and Engineering

This article provides a perspective on how an internet of heterogeneous self-service airport terminal systems can be used for data collection, which is stored on a private or consortium blockchain depending on the ownership or operations of an airport or both. Such a setup would help to increase efficiency, reduce costs, and improve traveler experience at airport terminals. Moreover, it would allow airports to gather data directly from passengers as opposed to waiting to receive the same data from airlines. Subsequently, this data, now on a blockchain system, becomes a data source for other applications such as machine learning. In …

Fusing Classic Motion Energy Models And Deep Learning For Coarse-To-Fine Moving Object Segmentation, Matthias Tangemann, Matthias Kümmerer, Matthias Bethge

MODVIS Workshop

Classic motion energy models are able to predict a wide range of physiological and behavioral aspects of motion perception in humans. Whether these models can be used as a basis for higher-level tasks, such as moving object segmentation, has however hardly been explored yet. Here, we present a model that combines a motion energy representation with recent computer vision approaches for figure-ground segmentation of naturalistic stimuli. We find that unlike established motion segmentation models but similar to humans, our model generalizes to random-dot stimuli when only trained on RGB videos.

Local Geometry Of Elementary Visual Computations, Peter Neri

MODVIS Workshop

Visual operators (e.g. edge detectors) are classically modelled using small circuits involving canonical computations, such as template-matching and gain control. Circuit models explain many aspects of the empirical descriptors that are used to characterize local visual operators, from sensitivity to classification images. Notwithstanding their utility, these models fail to provide a unified framework encompassing the variety of effects observed experimentally, such as the impact of contrast, SNR, and attention on the above descriptors. My goal is to start with a simple, plausible geometrical representation of the perceptual operation carried out by the observer, and to show that this representation is …

Photodynamic Treatment Of Staphylococcus Aureus With Non-Iron Hemin Analogs In The Presence Of Hydrogen Peroxide, Badhu Prashanthika Sivasubramaniam, Benjamin M. Washer, Yuichiro Watanabe, Kathryn E. Ragheb, J. Paul Robinson, Alexander Wei

Department of Chemistry Faculty Publications

Bacteria subjected to antiseptic or antibiotic stress often develop tolerance, a trait that can lead to permanent resistance. To determine whether photodynamic agents could be used to counter tolerance, we evaluated three non-iron hemin analogs (M-PpIX; M = Al, Ga, In) as targeted photosensitizers for antimicrobial photodynamic inactivation (aPDI) following exposure to sublethal H2O2. Al-PpIX is an active producer of ROS whereas Ga- and In-PpIX are more efficient at generating singlet oxygen. Al- and Ga-PpIX are highly potent aPDI agents against S. aureus and methicillin-resistant strains (MRSA) with antimicrobial activity (3 log reduction in colony-forming units) at nanomolar concentrations. The …

Türkiye's Sustainable Tourism Transformation: An Overview, Mustafa Sogut

GSTC Academic Symposium - In conjunction with the GSTC Global Conference

Türkiye has initiated a paradigm shift in its tourism industry, marked by a collaboration with the Global Sustainable Tourism Council (GSTC), renowned for setting robust sustainability standards. The agreement, initiated in 2022, prioritizes sustainability commitment, commencing with formulating national program criteria and certification bodies training. The initial phase is targeted for completion by the end of 2023, with subsequent stages progressively implemented by 2025, ultimately aiming to meet all international standards by 2030.

This strategic move aims to position Turkey prominently in sustainable tourism, aligning with the goals of The Paris Agreement. Turkey has proactively steered its tourism industry towards …

Self-Consistent Atmosphere Representation And Interaction In Photon Monte Carlo Simulations, J. R. Peterson, G. Sembroski, A. Dutta, C. Remocaldo

Purdue University Libraries Open Access Publishing Fund

We present a self-consistent representation of the atmosphere and implement the interactions of light with the atmosphere using a photon Monte Carlo approach. We compile global climate distributions based on historical data, self-consistent vertical profiles of thermodynamic quantities, spatial models of cloud variation and cover, and global distributions of four kinds of aerosols. We then implement refraction, Rayleigh scattering, molecular interactions, and Tyndall–Mie scattering to all photons emitted from astronomical sources and various background components using physics first principles. This results in emergent image properties that include: differential astrometry and elliptical point spread functions (PSFs) predicted completely to the horizon, …

The Escape Of Fast Radio Burst Emission From Magnetars, Maxim Lyutikov

Purdue University Libraries Open Access Publishing Fund

We reconsider the escape of high-brightness coherent emission of fast radio bursts (FRBs) from magnetars’ magnetospheres, and conclude that there are numerous ways for the powerful FRB pulse to avoid non-linear absorption. Sufficiently strong surface magnetic fields, more than or equal to 10 percent of the quantum field, limit the waves’ non-linearity to moderate values. For weaker fields, the electric field experienced by a particle is limited by a combined ponderomotive and parallel-adiabatic forward acceleration of charges by the incoming FRB pulse along the magnetic field lines newly opened during FRB/coronal mass ejection. As a result, particles surf the weaker …

Geospatial Analysis Of Agricultural Potential In The United States, Diana Febrita

Graduate Industrial Research Symposium

Traditionally, the agriculture sector is responsible for providing food and crop products. However, the role of agriculture has expanded beyond its traditional function. It is the main sector that contributes to the provision of food, income, employment, environmental protection, and local economic development. Reflecting on the roles of agriculture, understanding the potential of agriculture in the United States is crucial to discovering the prospects and challenges. This study will briefly discuss the agricultural potential in the United States based on the five assets, including natural capital, financial capital, human capital, physical capital, and social capital. To identify the states with …

Accuracy Of Nitrate Hysteresis And Flushing For Agricultural Watersheds In The Midwest, Noah Rudko, Sara K. W. Mcmillian, Jane Frankenberger, François Birgand

Graduate Industrial Research Symposium

Storm event-based metrics, such as hysteresis (HI) and flushing (FI), are used to differentiate nitrate pathways and sources, which is essential for watershed management. Estimations of these event-based metrics typically use high frequency (15-minute – hourly) measurements, but daily data are also used due to their greater availability. To date, there has been no study assessing how using lower frequency samples affect the accuracy of HI and FI, which could skew interpretation of potential nutrient pathways and sources. We used continuous measurements of nitrate collected at 9 watersheds throughout the Midwest spanning 448 storms. HI and FI were estimated from …

Comparative Life Cycle Assessment Of Copper Production, Xiaohan Wu

Graduate Industrial Research Symposium

Copper demand will surge significantly in the context of global renewable energy technology implementation, but its production is an energy-intensive process. It is crucial to choose the best production method to reduce environmental damage in terms of the enormous copper supply. This research develops a multi-criteria life cycle assessment model for the three main copper production routes- pyrometallurgy, hydrometallurgy, and bioleaching. We complied material and energy flow data to assess each route's life cycle greenhouse gas (GHG) emissions, cost, and resource efficiency. Results indicate bioleaching emits the least GHG emissions (4.09 kg-CO2 eq/kg copper) among the three routes. Hydrometallurgy is …

Characterization Of Biological Particles Using An Integrated Hyperspectral Imaging And Machine Learning, Kaeul Lim, Arezoo Ardekani

Graduate Industrial Research Symposium

Hyperspectral imaging (HSI) is a promising modality in medicine with many potential applications. This study focuses on developing a label-free lipid nanoparticle characterization method using a convolutional neural network (CNN) analysis of HSI images. The HSI data, hypercube, consists of a series of images acquired at different wavelengths for the same field of view, providing continuous spectra information for each pixel. Three distinct liposome samples were collected for analysis. Advanced image preprocessing and classification methods for HSI data were developed to differentiate liposomes based on their material compositions. Our machine learning-based classification method was able to distinguish different liposome types …

Sepsis Treatment: Reinforced Sequential Decision-Making For Saving Lives, Dipesh Tamboli, Jiayu Chen, Kiran Pranesh Jotheeswaran, Denny Yu, Vaneet Aggarwal

Graduate Industrial Research Symposium

Sepsis, a life-threatening condition triggered by the body's exaggerated response to infection, demands urgent intervention to prevent severe complications. Existing machine learning methods for managing sepsis struggle in offline scenarios, exhibiting suboptimal performance with survival rates below 50%. Our project introduces the "PosNegDM: Reinforcement Learning with Positive and Negative Demonstrations for Sequential Decision-Making" framework utilizing an innovative transformer-based model and a feedback reinforcer to replicate expert actions while considering individual patient characteristics. A mortality classifier with 96.7% accuracy guides treatment decisions towards positive outcomes. The PosNegDM framework significantly improves patient survival, saving 97.39% of patients and outperforming established machine learning …

Online Class-Incremental Learning For Real-World Food Image Classification, Siddeshwar Raghavan, Jiangpeng He, Fengqing Zhu

Graduate Industrial Research Symposium

Food image classification is essential for monitoring health and tracking dietary in image-based dietary assessment methods. However, conventional systems often rely on static datasets with fixed classes and uniform distribution. In contrast, real-world food consumption patterns, shaped by cultural, economic, and personal influences, involve dynamic and evolving data. Thus, it requires the classification system to cope with continuously evolving data. Online Class Incremental Learning (OCIL) addresses the challenge of learning continuously from a single-pass data stream while adapting to the new knowledge and reducing catastrophic forgetting. Experience Replay (ER) based OCIL methods store a small portion of previous data and …

Modelling The "Bottom-Up" Development Pattern Of Tar Spot Disease In Corn, Brenden Lane, Joaquín Guillermo Ramírez-Gil, Carlos Góngora-Canul, Mariela Sofia Fernandez Campos, Andres Cruz-Sancan, Fidel E. Jiménez-Beitia, Alex G. Acosta-Guatemal, Wily Sic, C. D. Cruz

Graduate Industrial Research Symposium

In 2015, the corn-infecting pathogen Phyllachora maydis (causal agent of tar spot disease) was reported for the first time in the United States. The disease has since spread across the US, causing major yield losses. In 2021 alone, 5.88 million metric tons (231.3 million bushels) of US corn yield were lost to this disease, costing an estimated US$1.25 billion. Though fungicides can protect against these agroeconomic losses, application timing can be difficult to optimize because our understanding of tar spot dynamics is still evolving. The current view is that tar spot typically develops bottom-up through a repeating infection cycle. Because …

A Machine Learning Model Of Perturb-Seq Data For Use In Space Flight Gene Expression Profile Analysis, Liam F. Johnson, James Casaletto, Lauren Sanders, Sylvain Costes

Graduate Industrial Research Symposium

The genetic perturbations caused by spaceflight on biological systems tend to have a system-wide effect which is often difficult to deconvolute it into individual signals with specific points of origin. Single cell multi-omic data can provide a profile of the perturbational effects, but does not necessarily indicate the initial point of interference within the network. The objective of this project is to take advantage of large scale and genome-wide perturbational datasets by using them to train a tuned machine learning model that is capable of predicting the effects of unseen perturbations in new data. Perturb-Seq datasets are large libraries of …

Eocene (50–55 Ma) Greenhouse Climate Recorded In Nonmarine Rocks Of San Diego, Ca, Usa, Adrian P. Broz, Devin Pritchard-Peterson, Diogo Spinola, Sarah Schneider, Gregory Retallack, Lucas C.R. Silva

Purdue University Libraries Open Access Publishing Fund

Nonmarine rocks in sea cliffs of southern California store a detailed record of weathering under tropical conditions millions of years ago, where today the climate is much drier and cooler. This work examines early Eocene (~ 50–55 million-year-old) deeply weathered paleosols (ancient, buried soils) exposed in marine terraces of northern San Diego County, California, and uses their geochemistry and mineralogy to reconstruct climate and weathering intensity during early Eocene greenhouse climates. These Eocene warm spikes have been modeled as prequels for ongoing anthropogenic global warming driven by a spike in atmospheric CO2. Paleocene-Eocene thermal maximum (PETM, ~ 55 Ma) kaolinitic …

Digitizing Delphi: Educating Audiences Through Virtual Reconstruction, Kate Koury

The Journal of Purdue Undergraduate Research

Implementing a 3D model into a virtual space allows the general public to engage critically with archaeological processes. There are many unseen decisions that go into reconstructing an ancient temple. Analysis of available materials and techniques, predictions of how objects were used, decisions of what sources to reference, puzzle piecing broken remains together, and even educated guesses used to fill gaps in information often go unobserved by the public. This work will educate users about those choices by allowing the side-by-side comparison of conflicting theories on the reconstruction of the Tholos at Delphi, which is an ideal site because of …

Promises And Risks Of Applying Ai Medical Imaging To Early Detection Of Cancers, And Regulation For Ai Medical Imaging, Yiyao Zhang

The Journal of Purdue Undergraduate Research

No abstract provided.