Engineering Commons^™

Sliding Markov Decision Processes For Dynamic Task Planning On Uncrewed Aerial Vehicles, Trent Wiens

Department of Mechanical and Materials Engineering: Dissertations, Theses, and Student Research

Mission and flight planning problems for uncrewed aircraft systems (UASs) are typically large and complex in space and computational requirements. With enough time and computing resources, some of these problems may be solvable offline and then executed during flight. In dynamic or uncertain environments, however, the mission may require online adaptation and replanning. In this work, we will discuss methods of creating MDPs for online applications, and a method of using a sliding resolution and receding horizon approach to build and solve Markov Decision Processes (MDPs) in practical planing applications for UASs. In this strategy, called a Sliding Markov Decision …

Bidding Strategy For A Wind Power Producer In Us Energy And Reserve Markets, Anne Stratman

Department of Electrical and Computer Engineering: Dissertations, Theses, and Student Research

Wind power is one of the world's fastest-growing renewable energy resources and has expanded quickly within the US electric grid. Currently, wind power producers (WPPs) may sell energy products in US markets but are not allowed to sell reserve products, due to the uncertain and intermittent nature of wind power. However, as wind’s share of the power supply grows, it may eventually be necessary for WPPs to contribute to system-wide reserves. This paper proposes a stochastic optimization model to determine the optimal offer strategy for a WPP that participates in the day-ahead and real-time energy and spinning reserve markets. The …

Non-Vacuous Generalization Bounds For Adversarial Risk In Stochastic Neural Networks, Mustafa Waleed, Liznerski Philipp, Antoine Ledent, Wagner Dennis, Wang Puyu, Kloft Marius

Research Collection School Of Computing and Information Systems

Adversarial examples are manipulated samples used to deceive machine learning models, posing a serious threat in safety-critical applications. Existing safety certificates for machine learning models are limited to individual input examples, failing to capture generalization to unseen data. To address this limitation, we propose novel generalization bounds based on the PAC-Bayesian and randomized smoothing frameworks, providing certificates that predict the model’s performance and robustness on unseen test samples based solely on the training data. We present an effective procedure to train and compute the first non-vacuous generalization bounds for neural networks in adversarial settings. Experimental results on the widely recognized …

Next-Generation Crop Monitoring Technologies: Case Studies About Edge Image Processing For Crop Monitoring And Soil Water Property Modeling Via Above-Ground Sensors, Nipuna Chamara

Dissertations and Doctoral Documents from University of Nebraska-Lincoln, 2023–

Artificial Intelligence (AI) has advanced rapidly in the past two decades. Internet of Things (IoT) technology has advanced rapidly during the last decade. Merging these two technologies has immense potential in several industries, including agriculture.

We have identified several research gaps in utilizing IoT technology in agriculture. One problem was the digital divide between rural, unconnected, or limited connected areas and urban areas for utilizing images for decision-making, which has advanced with the growth of AI. Another area for improvement was the farmers' demotivation to use in-situ soil moisture sensors for irrigation decision-making due to inherited installation difficulties. As Nebraska …

From Bits To Beds: Design And Implementation Of A Hotel Booking System A Coding Project, Alexa Gilman

University Honors College

This thesis presents a comprehensive hotel booking system designed and implemented to showcase the transition "From Bits to Beds". There are two main motivations behind this project: firstly, to provide users with a user-friendly and efficient platform for booking accommodations. Secondly, it serves as a great learning opportunity, providing hands-on practice with coding, collaboration with teammates, and exposure to real-world challenges. The system utilizes technologies such as JavaScript, Express.js, and HTML/CSS to offer features like browsing hotels, filtering options, user authentication, and booking management. The implementation of this project demonstrates a successful integration of backend and frontend components, ensuring reliability …

Implementation Of Explainable Ai For Bearing Fault Classification, Mohammad Mundiwala

Honors Scholar Theses

It is difficult to overstate the impact of artificial intelligence (AI) over the past decade. The rapid expansion of machine learning has stimulated a race to deploy AI in all facets of life, one such domain being machine health monitoring. There is no doubt that machine learning excels in prediction accuracy, but oftentimes, these models are cryptic and fail to provide valuable insight into their decisions. This paper presents an overview of a neural network and what it means to learn. Next, two distinct Explainable AI (XAI) techniques will be presented: Gradient Class Activation Mapping and SimplEx . Finally, these …

Determining The Viability Of Marine Sensor Construction, Roman Sequeira

Honors College

I intend to determine the viability of building a sensor that can be deployed in marine environments. Viability is defined as a summary of economic affordability, practicality of construction and deployment, knowledge required, and effectiveness. In order to get the best results, our sensor must be able to be modified to suit individual circumstances, constructed out of easy to obtain materials, be robust enough to withstand less than lab grade environments, and most importantly function well enough to be worth the effort of building it. I have built a sensor using the cheapest and most widely available options available. It …

An Adaptive Large Neighborhood Search For The Multi-Vehicle Profitable Tour Problem With Flexible Compartments And Mandatory Customers, Vincent F. Yu, Nabila Yuraisyah Salsabila, Aldy Gunawan, Anggun Nurfitriani Handoko

Research Collection School Of Computing and Information Systems

The home-refill delivery system is a business model that addresses the concerns of plastic waste and its impact on the environment. It allows customers to pick up their household goods at their doorsteps and refill them into their own containers. However, the difficulty in accessing customers’ locations and product consolidations are undeniable challenges. To overcome these issues, we introduce a new variant of the Profitable Tour Problem, named the multi-vehicle profitable tour problem with flexible compartments and mandatory customers (MVPTPFC-MC). The objective is to maximize the difference between the total collected profit and the traveling cost. We model the proposed …

Designed For Life: Unearthing Just And Sustainable Urban Design Through The Daylighting Of Phalen Creek, Corgan R. Archuleta

Geography Honors Projects

This thesis conceptualizes a relational approach to urban design. Often separated from justice, I argue urban design can shape spaces to enable respectful and reciprocal human and more-than- human relationships. Focusing on Phalen Creek in Saint Paul, Minnesota, I illuminate just and sustainable possibilities between ecologically sustainable and socially inclusive design. Phalen Creek was a natural waterway buried in a pipe during 20th century urbanization to be partially reconstructed through daylighting. The Indigenous and Immigrant stories driving restoration expand urban design’s liberatory potential. Combining just sustainabilities with infrastructure theory and Indigenous Knowledges, I contend urban design offers a relational approach …

Measuring Soot In A Novel Configuration For Diffusion Flames Fueled By Ethylene Doped With Iso-Dodecane, Christian Bjork

Honors Scholar Theses

Sustainable Aviation Fuels (SAFs) are seen as the path forward for decarbonizing hard-to-electrify sectors. Using SAFs over traditional fossil fuels abates carbon dioxide emissions but still may present soot emission problems. A milestone in the abatement of soot would be understating its formation mechanisms.

This study aims to quantify soot products resulting from an ethylene flame doped with iso-dodecane, a surrogate SAF component. The burner selected for the investigation is the novel Planar Mixing Layer Flame (PMLF) which allows the tracking of soot formation with the height above the burner (HAB) in a stable diffusion flame. A baseline ethylene-fueled flame …

Optimal Molecular Dynamics System Size For Increased Precision And Efficiency For Epoxy Materials, Khatereh Kashmari, Sagar Patil, Josh Kemppainen, Shankara Gowtham, Gregory Odegard

Michigan Tech Publications, Part 2

Molecular dynamics (MD) simulation is an important tool for predicting thermo-mechanical properties of polymer resins at the nanometer length scale, which is particularly important for efficient computationally driven design of advanced composite materials and structures. Because of the statistical nature of modeling amorphous materials on the nanometer length scale, multiple MD models (replicates) are typically built and simulated for statistical sampling of predicted properties. Larger replicates generally provide higher precision in the predictions but result in higher simulation times. Unfortunately, there is insufficient information in the literature to establish guidelines between MD model size and the resulting precision in predicted …

Gate-Controlled Supercurrent Effect In Dry-Etched Dayem Bridges Of Non-Centrosymmetric Niobium Rhenium, Jennifer Koch, Carla Cirillo, Sebastiano Battisti, Leon Ruf, Zahra Makhdoumi Kakhaki, Alessandro Paghi, Armen Gulian, Serafim Teknowijoyo, Giorgio De Simoni, Francesco Giazotto, Carmine Attanasio, Elke Scheer, Angelo Di Bernardo

Mathematics, Physics, and Computer Science Faculty Articles and Research

The application of a gate voltage to control the superconducting current flowing through a nanoscale superconducting constriction, named as gate-controlled supercurrent (GCS), has raised great interest for fundamental and technological reasons. To gain a deeper understanding of this effect and develop superconducting technologies based on it, the material and physical parameters crucial for the GCS effect must be identified. Top-down fabrication protocols should also be optimized to increase device scalability, although studies suggest that top-down fabricated devices are more resilient to show a GCS. Here, we investigate gated superconducting nanobridges made with a top-down fabrication process from thin films of …

Deep Selenium Donors In Zngep2 Crystals: An Electron Paramagnetic Resonance Study Of A Nonlinear Optical Material, Timothy D. Gustafson, Larry E. Halliburton, Nancy C. Giles, Peter G. Schunemann, Kevin T. Zawilski, J. Jesenovec, Kent L. Averett, Jonathan E. Slagle [*]

Faculty Publications

Zinc germanium diphosphide (ZnGeP₂) is a ternary semiconductor best known for its nonlinear optical properties. A primary application is optical parametric oscillators operating in the mid-infrared region. Controlled donor doping provides a method to minimize the acceptor-related absorption bands that limit the output power of these devices. In the present study, a ZnGeP₂ crystal is doped with selenium during growth. Selenium substitutes for phosphorus and serves as a deep donor. Significant concentrations of native defects (zinc vacancies, germanium-on-zinc antisites, and phosphorous vacancies) are also present in the crystal. Electron paramagnetic resonance (EPR) is used to establish the …

Data Engineering: Building Software Efficiency In Medium To Large Organizations, Alessandro De La Torre

Whittier Scholars Program

The introduction of PoetHQ, a mobile application, offers an economical strategy for colleges, potentially ushering in significant cost savings. These savings could be redirected towards enhancing academic programs and services, enriching the educational landscape for students. PoetHQ aims to democratize access to crucial software, effectively removing financial barriers and facilitating a richer educational experience. By providing an efficient software solution that reduces organizational overhead while maximizing accessibility for students, the project highlights the essential role of equitable education and resource optimization within academic institutions.

Radiative Cooling For Energy-Efficient Power Generation, Rickia Hanna

Celebrating Scholarship and Creativity Day (2018-)

This thesis examined radiative cooling on a small scale using a hybrid photovoltaic/radiative cooling model system, to determine its efficiency for large-scale power generation. Radiative cooling is concerned with heat transfer and this thesis’s main goal is to harness that heat energy to produce electricity. The efficiency of the system was tested using various light sources at different angles and total power output. The testing was done several times and there proved to be a proportional relationship between light intensity and current output. However, due to the performance threshold of the PTEC module, the component of the system used to …

Microplastics Fouling Mitigation In Forward Osmosis Membranes By The Molecular Assembly Of Sulfobetaine Zwitterion, Javad Farahbakhsh, Mitra Golgoli, Mehdi Khiadani, Amir Razmjou, Masoumeh Zargar

Research outputs 2022 to 2026

Forward osmosis (FO) membranes have potential for the efficient water and wastewater treatment applications. However, their development has faced significant challenges due to their fouling propensity. In this study, FO membranes modified with sulfobetaine zwitterions (i.e., [2-(Methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl) ammonium hydroxide) were fabricated and used for the first time to address microplastic (MP) fouling issue. Water flux, reverse salt flux (RSF), fouling, and flux recovery were evaluated for the membranes loaded with different quantities of the zwitterions ranging from 0.25 % to 2 %. The developed membranes were tested over 49 h with feed solutions containing polyethylene MPs and bovine serum albumin …

A Reputation System For Provably-Robust Decision Making In Iot Blockchain Networks, Charles C. Rawlins, Sarangapani Jagannathan, Venkata Sriram Siddhardh Nadendla

Electrical and Computer Engineering Faculty Research & Creative Works

Blockchain systems have been successful in discerning truthful information from interagent interaction amidst possible attackers or conflicts, which is crucial for the completion of nontrivial tasks in distributed networking. However, the state-of-the-art blockchain protocols are limited to resource-rich applications where reliably connected nodes within the network are equipped with significant computing power to run lottery-based proof-of-work (pow) consensus. The purpose of this work is to address these challenges for implementation in a severely resource-constrained distributed network with internet of things (iot) devices. The contribution of this work is a novel lightweight alternative, called weight-based reputation (wbr) scheme, to classify new …

Immersive Japanese Language Learning Web Application Using Spaced Repetition, Active Recall, And An Artificial Intelligent Conversational Chat Agent Both In Voice And In Text, Marc Butler

MS in Computer Science Project Reports

In the last two decades various human language learning applications, spaced repetition software, online dictionaries, and artificial intelligent chat agents have been developed. However, there is no solution to cohesively combine these technologies into a comprehensive language learning application including skills such as speaking, typing, listening, and reading. Our contribution is to provide an immersive language learning web application to the end user which combines spaced repetition, a study technique used to review information at systematic intervals, and active recall, the process of purposely retrieving information from memory during a review session, with an artificial intelligent conversational chat agent both …

Citdet, Jordan A. James, Heather K. Manching, Matthew R. Mattia, Kim D. Bowman, Amanda M. Hulse-Kemp, William J. Beksi

Computer Science and Engineering Datasets

The CitDet dataset is composed of images captured at the USDA Agricultural Research Service Subtropical Insects and Horticulture Research Unit in Fort Pierce, FL, USA. Data was collected between October 2021 and October 2022. 579 images were captured from different sections of the orchard using the open-source application Field Book on Android tablets. While collecting images, we faced the camera in a portrait orientation directly centered on the tree of interest. All images were taken at the edge of the soil in the tree row to simulate a ground-based robot imaging the tree while moving between two rows of trees. …

Uncertainty Analysis In Machine Learning Models, Ayorinde E. Olatunde, Weiqi Yue, Pawan K. Tripathi, Roger H. French, Anirban Mondal

Faculty Scholarship

No abstract provided.

Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy

Computer Science Faculty Research & Creative Works

Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computational efficiency of SNNs has been introduced. This paper studies the feasibility of using a convolutional spiking neural network (CSNN) to detect anticipatory slow cortical potentials (SCPs) related to braking intention in human participants using an electroencephalogram (EEG). Data was collected during an experiment wherein participants operated a remote-controlled vehicle on a testbed …

Expanding Analytical Capabilities In Intrusion Detection Through Ensemble-Based Multi-Label Classification, Ehsan Hallaji, Roozbeh Razavi-Far, Mehrdad Saif

Electrical and Computer Engineering Publications

Intrusion detection systems are primarily designed to flag security breaches upon their occurrence. These systems operate under the assumption of single-label data, where each instance is assigned to a single category. However, when dealing with complex data, such as malware triage, the information provided by the IDS is limited. Consequently, additional analysis becomes necessary, leading to delays and incurring additional computational costs. Existing solutions to this problem typically merge these steps by considering a unified, but large, label set encompassing both intrusion and analytical labels, which adversely affects efficiency and performance. To address these challenges, this paper presents a novel …

Editorial: Emerging On-Demand Passenger And Logistics Systems: Modelling, Optimization, And Data Analytics, Jintao Ke, Hai Wang, Neda Masoud, Maximilian Schiffer, Goncalo H. A. Correia

Research Collection School Of Computing and Information Systems

The proliferation of smart personal devices and mobile internet access has fueled numerous advancements in on-demand transportation services. These services are facilitated by online digital platforms and range from providing rides to delivering products. Their influence is transforming transportation systems and leaving a mark on changing individual mobility, activity patterns, and consumption behaviors. For instance, on-demand transportation companies such as Uber, Lyft, Grab, and DiDi have become increasingly vital for meeting urban transportation needs by connecting available drivers with passengers in real time. The recent surge in door-to-door food delivery (e.g., Uber Eats, DoorDash, Meituan); grocery delivery (e.g., Amazon Fresh, …

10 Meters To Disaster: The Challenges Of Premature Application Of Circular Economy Strategies In Jakarta’S Waste Management Structure, Almira Bowo

Independent Study Project (ISP) Collection

Jakarta's complex issue of waste management encompasses a multitude of challenges that include inefficiencies in infrastructure, a lack of public awareness of the consequences of an inadequate waste system, socioeconomic disparities, and a deficiency in intersectoral collaboration. The urgency for holistic and sustainable solutions that prioritize proactive waste collection is underscored by the complexities of these dynamics. This field study paper argues that the attention that is being drawn towards trending waste management innovations, which are reactive strategies, could bring the waste crisis in Jakarta to an even more critical state. The sections will critically examine current waste management efforts …

Effect Of Fabrication Parameters On The Ferroelectricity Of Hafnium Zirconium Oxide Films: A Statistical Study, Guillermo A. Salcedo, Ahmad E. Islam, Elizabeth Reichley, Michael Dietz, Christine M. Schubert Kabban, Kevin D. Leedy, Tyson C. Back, Weison Wang, Andrew Green, Timothy S. Wolfe, James M. Sattler

Faculty Publications

Ferroelectricity in hafnium zirconium oxide (Hf_1−xZr_xO₂) and the factors that impact it have been a popular research topic since its discovery in 2011. Although the general trends are known, the interactions between fabrication parameters and their effect on the ferroelectricity of Hf_1−xZr_xO₂ require further investigation. In this paper, we present a statistical study and a model that relates Zr concentration (x), film thickness (t_f), and annealing temperature (T_a) with the remanent polarization (P_r) in tungsten (W)-capped Hf_1−xZr_xO₂. …

Cr-Sam: Curvature Regularized Sharpness-Aware Minimization, Tao Wu, Tony Tie Luo, Donald C. Wunsch

Computer Science Faculty Research & Creative Works

The Capacity to Generalize to Future Unseen Data Stands as One of the Utmost Crucial Attributes of Deep Neural Networks. Sharpness-Aware Minimization (SAM) Aims to Enhance the Generalizability by Minimizing Worst-Case Loss using One-Step Gradient Ascent as an Approximation. However, as Training Progresses, the Non-Linearity of the Loss Landscape Increases, Rendering One-Step Gradient Ascent Less Effective. on the Other Hand, Multi-Step Gradient Ascent Will Incur Higher Training Cost. in This Paper, We Introduce a Normalized Hessian Trace to Accurately Measure the Curvature of Loss Landscape on Both Training and Test Sets. in Particular, to Counter Excessive Non-Linearity of Loss Landscape, …

Lrs: Enhancing Adversarial Transferability Through Lipschitz Regularized Surrogate, Tao Wu, Tony Tie Luo, Donald C. Wunsch

Computer Science Faculty Research & Creative Works

The Transferability of Adversarial Examples is of Central Importance to Transfer-Based Black-Box Adversarial Attacks. Previous Works for Generating Transferable Adversarial Examples Focus on Attacking Given Pretrained Surrogate Models While the Connections between Surrogate Models and Adversarial Trasferability Have Been overlooked. in This Paper, We Propose Lipschitz Regularized Surrogate (LRS) for Transfer-Based Black-Box Attacks, a Novel Approach that Transforms Surrogate Models towards Favorable Adversarial Transferability. using Such Transformed Surrogate Models, Any Existing Transfer-Based Black-Box Attack Can Run Without Any Change, Yet Achieving Much Better Performance. Specifically, We Impose Lipschitz Regularization on the Loss Landscape of Surrogate Models to Enable a Smoother …

Will Saf Turbocharge The Corn Ethanol Market?, Richard Perrin, Lilyan Fulginiti, Felipe Miranda De Souza Almeida

Cornhusker Economics

The long-run outlook for the corn ethanol industry is questionable, due to a transition to electric and hybrid vehicles. One source of hope for the long run is the potential demand for producing Sustainable Aviation Fuel (SAF). SAF is a key component in the United States Aviation Climate Action Plan, a path to net-zero greenhouse gas (GHG) emissions in the aviation industry by 2050. Demand for ethanol for SAF offers hope to the ethanol industry, but it depends a great deal on policy decisions that are being made now. Here we sketch out this story.

Based on the information available …

6d Single-Fluorogen Orientation-Localization Microscopy For Elucidating The Architecture Of Beta-Sheet Assemblies And Biomolecular Condensates, Tingting Wu, Weiyan Zhou, Jai S. Rudra, Rohit V. Pappu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

We develop six-dimensional single-molecule orientation-localization microscopy (SMOLM) to measure the 3D positions and 3D orientations simultaneously of single fluorophores. We show how careful optimization of phase and polarization modulation components can encode phase, polarization, and angular spectrum information from each fluorescence photon into a microscope’s dipole-spread function. We used the transient binding and blinking of Nile red (NR) to characterize the helical structure of fibrils formed by designed amphipathic peptides, KFE8^L and KFE8^D, and the pathological amyloid-beta peptide Aβ42. We also deployed merocyanine 540 to uncover the interfacial architectures of biomolecular condensates.

Highly Efficient Dopamine Sensing With A Carbon Nanotube-Encapsulated Metal Chalcogenide Nanostructure, Harish Singh, Jiandong Wu, Kurt A.L. Lagemann, Manashi Nath

Chemical and Biochemical Engineering Faculty Research & Creative Works

Carbon nanotube-encapsulated nickel selenide composite nanostructures were used as nonenzymatic electrochemical sensors for dopamine detection. These composite nanostructures were synthesized through a simple, one-step, and environmentally friendly chemical vapor deposition method, wherein the CNTs were formed in situ from pyrolysis of a carbon-rich metallo-organic precursor. The composition and morphology of these hybrid NiSe2-filled carbon nanostructures were confirmed by powder X-ray diffraction, Raman, X-ray photoelectron spectroscopy, and high-resolution transmission electron microscopy images. Electrochemical tests demonstrated that the as-synthesized hybrid nanostructures exhibited outstanding electrocatalytic performance toward dopamine oxidation, with a high sensitivity of 19.62 μA μM-1 cm-2, low detection limit, broad linear …