Physical Sciences and Mathematics Commons^™

The Model 2.0 And Friends: An Interim Report, Garrison W. Cottrell, Martha Gahl, Shubham Kulkarni, Shashank Venkatramani, Yash Shah, Keyu Long, Xuzhe Zhi, Shivaank Agarwal, Cody Li, Jingyuan He, Thomas Fischer

MODVIS Workshop

Last year, I reported on preliminary results of an anatomically-inspired deep learning model of the visual system and its role in explaining the face inversion effect. This year, I will report on new results and some variations on network architectures that we have explored, mainly as a way to generate discussion and get feedback. This is by no means a polished, final presentation!

We look forward to the group’s suggestions for these projects.

Automated Delineation Of Visual Area Boundaries And Eccentricities By A Cnn Using Functional, Anatomical, And Diffusion-Weighted Mri Data, Noah C. Benson, Bogeng Song, Toshikazu Miyata, Hiromasa Takemura, Jonathan Winawer

MODVIS Workshop

Delineating visual field maps and iso-eccentricities from fMRI data is an important but time-consuming task for many neuroimaging studies on the human visual cortex because the traditional methods of doing so using retinotopic mapping experiments require substantial expertise as well as scanner, computer, and human time. Automated methods based on gray-matter anatomy or a combination of anatomy and functional mapping can reduce these requirements but are less accurate than experts. Convolutional Neural Networks (CNNs) are powerful tools for automated medical image segmentation. We hypothesize that CNNs can define visual area boundaries with high accuracy. We trained U-Net CNNs with ResNet18 …

Toward A Manifold Encoding Neural Responses, Luciano Dyballa, Andra M. Rudzite, Mahmood S. Hoseini, Mishek Thapa, Michael P. Stryker, Greg D. Field, Steven W. Zucker

MODVIS Workshop

Understanding circuit properties from physiological data presents two challenges: (i) recordings do not reveal connectivity, and (ii) stimuli only exercise circuits to a limited extent. We address these challenges for the mouse visual system with a novel neural manifold obtained using unsupervised algorithms. Each point in our manifold is a neuron; nearby neurons respond similarly in time to similar parts of a stimulus ensemble. This ensemble includes drifting gratings and flows, i.e., patterns resembling what a mouse would “see” running through fields.

Regarding (i), our manifold differs from the standard practice in computational neuroscience: embedding trials in neural coordinates. Topology …

How Object Segmentation And Perceptual Grouping Emerge In Noisy Variational Autoencoders, Ben Lonnqvist, Zhengqing Wu, Michael H. Herzog

MODVIS Workshop

Many animals and humans can recognize and segment objects from their backgrounds. Whether object segmentation is necessary for object recognition has long been a topic of debate. Deep neural networks (DNNs) excel at object recognition, but not at segmentation tasks - this has led to the belief that object recognition and segmentation are separate mechanisms in visual processing. Here, however, we show evidence that in variational autoencoders (VAEs), segmentation and faithful representation of data can be interlinked. VAEs are encoder-decoder models that learn to represent independent generative factors of the data as a distribution in a very small bottleneck layer; …

Evaluating Models Of Scanpath Prediction, Matthias Kümmerer, Matthias Bethge

MODVIS Workshop

No abstract provided.

A Dynamical Model Of Binding In Visual Cortex During Incremental Grouping And Search, Daniel Schmid, Daniel A. Braun, Heiko Neumann

MODVIS Workshop

Binding of visual information is crucial for several perceptual tasks. To incrementally group an object, elements in a space-feature neighborhood need to be bound together starting from an attended location (Roelfsema, TICS, 2005). To perform visual search, candidate locations and cued features must be evaluated conjunctively to retrieve a target (Treisman&Gormican, Psychol Rev, 1988). Despite different requirements on binding, both tasks are solved by the same neural substrate. In a model of perceptual decision-making, we give a mechanistic explanation for how this can be achieved. The architecture consists of a visual cortex module and a higher-order thalamic module. While the …

U-No: U-Shaped Neural Operators, Md Ashiqur Rahman, Zachary E Ross, Kamyar Azizzadenesheli

Department of Computer Science Faculty Publications

Neural operators generalize classical neural networks to maps between infinite-dimensional spaces, e.g., function spaces. Prior works on neural operators proposed a series of novel methods to learn such maps and demonstrated unprecedented success in learning solution operators of partial differential equations. Due to their close proximity to fully connected architectures, these models mainly suffer from high memory usage and are generally limited to shallow deep learning models. In this paper, we propose U-shaped Neural Operator (U-NO), a U-shaped memory enhanced architecture that allows for deeper neural operators. U-NOs exploit the problem structures in function predictions and demonstrate fast training, data …

Lpa Guide To Environmental Hurdles, Sarah Everhart, Briana Hope

Purdue Road School

Compliance with the National Environmental Policy Act (NEPA) is a federal requirement when utilizing federal funding for transportation projects. Attendees will learn about environmental hurdles, common schedule challenges, that can be encountered in a project and how to best mange them. Specifically, Section 106 (cultural resources), T&E species, 4(f), Public Involvement, and Environmental Justice.

Design, Collaborate, Thrive: The Broad Ripple Avenue Project, Jessica Hawley, Emily Nelson, Ericka Miller

Purdue Road School

Broad Ripple Avenue (College Avenue to Winthrop Avenue) needed large-scale stormwater improvements. With the help of the Lochmueller Group and the Broad Ripple Village Association, Indianapolis DPW perceptively took this opportunity to also improve pedestrian facilities and regional multi-modal connectivity by combining multiple regional projects into one construction contract. This consolidation allowed for a cohesive public message through proactive public involvement. Presenters will share how consensus was built between invested parties through a successful public and private partnership.

Electro- And Photoactivation Of Silver–Iron Oxide Particles As Magnetically Recyclable Catalysts For Cross-Coupling Reactions, Qi Wang, Zhongxia Shang, Haiyan Wang, Alexander Wei

Department of Chemistry Faculty Publications

Colloidal Ag particles decorated with Fe3O4 islands can be electrochemically or photochemically activated as inverse catalysts for C(sp2)–H heteroarylation. The silver–iron oxide (SIO) particles are reduced into redox-active forms by cathodic charging at mild potentials or by short-term light exposure, and can be reused multiple times by magnetic cycling without further activation. A negative shift in the reduction peak is attributed to an overpotential produced by surface Fe3O4 which separates residual Ag ions or clusters from bulk silver. The catalytic efficiency of SIO is maintained even with acid degradation, which can be countered simply by adding water to the reaction …

U.S. Energy Information Administration Information Resources, Bert Chapman

Libraries Faculty and Staff Presentations

Provides information about the resources produced by U.S. Department of Energy's Energy Information Administration. These resources cover energy statistics for U.S., states, the United States, and foreign countries. They also cover energy products as varied as coal, natural gas, nuclear energy, petroleum, and renewable energy.

Exploring Barriers To The Adoption Of Internet Of Things-Based Precision Agriculture Practices, Gaganpreet Singh Hundal, Chad Laux, Dennis R. Buckmaster, Mathias J. Sutton, Michael Langemeier

Faculty Publications

The production of row crops in the Midwestern (Indiana) region of the US has been facing environmental and economic sustainability issues. There has been an increase in trend for the application of fertilizers (nitrogen & phosphorus), farm machinery fuel costs and decreasing labor productivity leading to non-optimized usage of farm inputs. Literature describes how sustainable practices such as profitability (return on investments), operational cost reduction, hazardous waste reduction, delivery performance and overall productivity might be adopted in the context of precision agriculture technologies (variable rate irrigation, variable rate fertilization, cloud-based analytics, and telematics for farm machinery navigation). The literature review …

Improving Developers' Understanding Of Regex Denial Of Service Tools Through Anti-Patterns And Fix Strategies, Sk Adnan Hassan, Zainab Aamir, Dongyoon Lee, James C. Davis, Francisco Servant

Department of Electrical and Computer Engineering Faculty Publications

Regular expressions are used for diverse purposes, including input validation and firewalls. Unfortunately, they can also lead to a security vulnerability called ReDoS (Regular Expression Denial of Service), caused by a super-linear worst-case execution time during regex matching. Due to the severity and prevalence of ReDoS, past work proposed automatic tools to detect and fix regexes. Although these tools were evaluated in automatic experiments, their usability has not yet been studied; usability has not been a focus of prior work. Our insight is that the usability of existing tools to detect and fix regexes will improve if we complement them …

An Empirical Study Of Pre-Trained Model Reuse In The Hugging Face Deep Learning Model Registry, Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis

Department of Electrical and Computer Engineering Faculty Publications

Deep Neural Networks (DNNs) are being adopted as components in software systems. Creating and specializing DNNs from scratch has grown increasingly difficult as state-of-the-art architectures grow more complex. Following the path of traditional software engineering, machine learning engineers have begun to reuse large-scale pre-trained models (PTMs) and fine-tune these models for downstream tasks. Prior works have studied reuse practices for traditional software packages to guide software engineers towards better package maintenance and dependency management. We lack a similar foundation of knowledge to guide behaviors in pre-trained model ecosystems.

In this work, we present the first empirical investigation of PTM reuse. …

On The Use Of Machine Learning For Causal Inference In Extreme Weather Events, Yuzhe Wang

Discovery Undergraduate Interdisciplinary Research Internship

Machine learning has become a helpful tool for analyzing data, and causal Inference is a powerful method in machine learning that can be used to determine the causal relationship in data. In atmospheric and climate science, this technology can also be applied to predicting extreme weather events. One of the causal inference models is Granger causality, which is used in this project. Granger causality is a statistical test for identifying whether one time series is helpful in forecasting the other time series. In granger causality, if a variable X granger-causes Y: it means that by using all information without …

Polarimetric Radar And Vhf Lightning Observations In A Significantly Tornadic Supercell, Jacob Bruss

The Journal of Purdue Undergraduate Research

No abstract provided.

Redefining Research In Nanotechnology Simulations: A New Approach To Data Caching And Analysis, Darin Tsai, Alan Zhang, Aloysius Rebeiro

The Journal of Purdue Undergraduate Research

No abstract provided.

Agricultural Aerosols: The Impact Of Farming Activity On Ice Nucleating Particles, Joseph Robinson

The Journal of Purdue Undergraduate Research

Farming activities cause particles such as soil dust and plant material to be emitted into the air. Some of these aerosols can become ice nucleating particles (INPs), serving as seeds for ice and mixed-phase clouds. While there have been ground-based studies of these particles in the western Great Plains and a single air-based study in Indiana, there is a distinct lack of ground-based studies in the Midwest. In Indiana, over two-thirds of the state is farmland, with over 75% of land in Tippecanoe County used for agriculture. Despite farming being such an essential part of life in Indiana, the connection …

Processing Of Plastic Film From Potato Starch: Effect Of Drying Methods, Kourtney Collier, Samantha Goins, Austin Chirgwin, Isabelle Stanfield

The Journal of Purdue Undergraduate Research

Starch-based plastics are biodegradable, compostable compounds made of starch and plasticizers from natural sources. Their fabrication involves the starch-plasticizer reaction at 70–100°C followed by cooling and drying. Th e most common drying method is air drying (natural convection), which is effective but slow. Th e objective of this work is to study the effect of fast drying (forced convection) on the quality of the plastic film. Th is work compares the effects of drying conditions and drying rate on warpage, shrinkage rate, and presence of bubbles. Five drying methods are studied: (1) natural convection with uncovered petri dish, (2) natural …

Supporting The Protect Initiative, Josh Lefton, Jackson Murray, Ahmed Thabet, Sriram Baireddy, Prakash Shukla, Mridul Gupta, Reagan Becker, Julie Ertle, Tony Doan, Aerin Yang

Purdue Journal of Service-Learning and International Engagement

Recently, medication dosage errors have received more political and media attention. Dosage errors are the most common medical errors, affecting about 1.5 million people annually.

Furthermore, U.S. poison-control centers reported more than 200,000 cases per year of medication errors. These cases result in medical costs of around $3.5 billion, and children under 6 years old constitute approximately 30% of these cases.

The PROTECT Initiative (Preventing Overdoses and Treatment Errors in Children Taskforce) was launched in 2008 as a collaborative effort between public health agencies and patient advocates to minimize dosage errors.

In alignment with the PROTECT Initiative effort, this project …

Optimizing Cybersecurity Budgets With Attacksimulation, Alexander Master, George Hamilton, J. Eric Dietz

Faculty Publications

Modern organizations need effective ways to assess cybersecurity risk. Successful cyber attacks can result in data breaches, which may inflict significant loss of money, time, and public trust. Small businesses and non-profit organizations have limited resources to invest in cybersecurity controls and often do not have the in-house expertise to assess their risk. Cyber threat actors also vary in sophistication, motivation, and effectiveness. This paper builds on the previous work of Lerums et al., who presented an AnyLogic model for simulating aspects of a cyber attack and the efficacy of controls in a generic enterprise network. This paper argues that …

The Impact Of Service Dogs On Objective And Perceived Sleep Quality For Veterans With Ptsd, Madhuri Vempati, Elise A. Miller, Sarah C. Leighton, Leanne O. Nieforth, Marguerite O’Haire

Discovery Undergraduate Interdisciplinary Research Internship

One in four post-9/11 veterans (Fulton et al., 2015) have been diagnosed with posttraumatic stress disorder (PTSD), facing sleep disruptions as one of their most common symptoms. Service dogs have become an increasingly popular complementary intervention and anecdotes suggest they may impact sleep for veterans with PTSD. There is a need for empirical investigation into these claims through measurement and analysis of sleep quality.

The purpose of this study was to longitudinally investigate the impact of service dogs on sleep quality through both objective and subjective measures.

Participants in the treatment group (n=92) received a service dog after baseline, while …

Copper(I)‒Pyrazolate Complexes As Solid-State Phosphors: Deep- Blue Emission Through A Remote Steric Effect, Yuichiro Watanabe, Benjamin M. Washer, Matthias Zeller, Sergei Savikhin, Lyudmila V. Slipchenko, Alexander Wei

Department of Chemistry Faculty Publications

We describe a novel manifestation of rigidochromic behavior in a series of tetranuclear Cu(I)–pyrazolate (Cu4pz4) macrocycles, with implications for solid-state luminescence at deep-blue wavelengths (<460 nm). The Cu4pz4 emissions are remarkably sensitive to structural effects far from the luminescent core: when 3,5-di-tert-butylpyrazoles are used as bridging ligands, adding a C4 substituent can induce a blue shift of more than 100 nm. X-ray crystal and computational analyses reveal that C4 units influence the conformational behavior of adjacent tert-butyl groups, with a subsequent impact on the global conformation of the Cu4pz4 complex. Emissions are mediated primarily through a cluster-centered triplet (3CC) state; compression of the Cu4 cluster into a nearly close-packed geometry prevents the reorganization of its excited-state structure and preserves the 3CC energy at a high level. The remote steric effect may thus offer alternative strategies toward the design of phosphors with rigid excited-state geometries.

Understanding The Influence Of Perceptual Noise On Visual Flanker Effects Through Bayesian Model Fitting, Jordan Deakin, Dietmar Heinke

MODVIS Workshop

No abstract provided.

A Two-Layer Model Explains Higher-Order Feature Selectivity Of V2 Neurons, Timothy D. Oleskiw, Justin D. Lieber, J. Anthony Movshon, Eero P. Simoncelli

MODVIS Workshop

Neurons in cortical area V2 respond selectively to higher-order visual features, such as the quasi-periodic structure of natural texture. However, a functional account of how V2 neurons build selectivity for complex natural image features from their inputs – V1 neurons locally tuned for orientation and spatial frequency – remains elusive.

We made single-unit recordings in area V2 in two fixating rhesus macaques. We presented stimuli composed of multiple superimposed grating patches that localize contrast energy in space, orientation, and scale. V2 activity is modeled via a two-layer linear-nonlinear network, optimized to use a sparse combination of V1-like outputs to account …

Hhl Algorithm On The Honeywell H1 Quantum Computer, Adrik B. Herbert, Eric A. F. Reinhardt

Discovery Undergraduate Interdisciplinary Research Internship

The quantum algorithm for linear systems of equations (HHL algorithm) provides an efficient tool for finding solutions to systems of functions with a large number of variables and low sensitivity to changes in inputs (i.e. low error rates). For complex problems, such as matrix inversion, HHL requires exponentially less computational time as compared with classical computation methods. HHL can be adapted to current quantum computing systems with limited numbers of qubits (quantum computation bits) but a high reusability rate such as the Honeywell H1 quantum computer. Some methods for improving HHL have been proposed through the combination of quantum and …

Crowd-Machine Partnership On Road Infrastructure Quality Recognition And Resilience, Eric J. Thompson

Discovery Undergraduate Interdisciplinary Research Internship

Public roads are a vital component of modern-day society, as they are necessary for the transportation of people and capital; consequently, it is important that they are regularly and effectively maintained. Unfortunately, this maintenance is difficult to manage due to the sheer area that roads span. It is an arduous task to locate every instance of road damage, as well as to determine the urgency that each bit of damage necessitates. Repairing road damage has high costs in labor, time, and money. To provide a more efficient way to monitor road conditions, we are designing a mobile application that collects …

Climate Justice In Engineering Education, Tyler J. Morgan, Donna Riley, Caroline M. Camfield

Discovery Undergraduate Interdisciplinary Research Internship

The goal of this research is to design a learning module for Purdue first-year engineering (FYE) students to learn climate fundamentals, and the role of engineers in responding to climate justice challenges. There is a lack of climate material within these classes currently, leading to a lack of climate conscious engineers in the future. The project entailed reviewing and synthesizing a wide variety of previous research on climate change education in engineering, including key learning objectives and their assessment. Because one of the key foci of the first-year engineering sequence relates to data analysis and management, we focused our work …

Streamlining Project Development Through Planning & Environmental Linkages, Karen Hadley, Brett Lackey

Purdue Road School

As transportation agencies continue to explore ways to be more efficient in the project development process, they are embracing integrated methodologies like planning and environmental linkages. This tool is practical, yet highly effective and inclusive, and teams across the country are experiencing its value. This presentation will highlight a variety of use cases, discuss lessons learned and best practices, and specifically address how planning and environmental linkages can be applied in Indiana and the Midwest.

A Decade Later – Us 31 Mitigation, Summer R. Elmore

Purdue Road School

Significant transportation projects are designed and built, but that’s not the end of the story. Wetland and stream mitigation efforts, including monitoring and maintenance, may continue for a decade. This presentation will showcase INDOT mitigation sites—from their creation a decade ago to the awesome results—for projects like US-31. We’ll share timelines, photos, quality data, and challenges identified and addressed over the years.