Engineering Commons^™

Interlayered Thin Film Composite (Itfc) Membranes: The Synthesis And Assembly Of Active Layer From Conjugated Microporous Polymer, Febby Andini

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

The pursuit of advanced materials with well-defined structures at sub-1 nm size, multi-functionalities, and superior chemical stability is essential for enhanced separation performance but technically challenging. Limitations of conventional TFC membranes for use in Organic Solvent Nanofiltration (OSN) can be addressed by manipulating the pore size and chemical properties of the film with novel materials. Conjugated microporous polymers (CMPs) are promising in a few years because of their highly ordered structure and excellent stability. Porphyrin, one of the basic building blocks, can form a conjugated polymer. Herein, poly(5,10,15,20-tetrakis(4-aminophenyl)porphyrin) or PTAPP, is considerably selected as an active layer from CMPs using …

A Robust Platform For Mobile Robotics Teaching And Developing Using Arduino’S Integrated Development Environment (Ide) For Programming The Arduino Mega 2560, Sajjad Alhassan

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

In light of the rapid pace at which development happens with modern technology, mobile robots play an important role in our daily lives. This is due to their great importance in facilitating the affairs of life in various economic, commercial, industrial, scientific, and many other fields. In this research and project, we have restructured the microcontroller and system for one of the mobile robots (CEENBOT) that was designed by the University of Nebraska and replaced it with an Arduino Mega 2560.

The purpose of using the Arduino Mega 2560 robot is to provide alternative programming for the CEENBOT platform to …

An Empirical Study On The Classification Of Python Language Features Using Eye-Tracking, Jigyasa Chauhan

School of Computing: Dissertations, Theses, and Student Research

Python, currently one of the most popular programming languages, is an object-
oriented language that also provides language feature support for other programming
paradigms, such as functional and procedural. It is not currently understood how
support for multiple paradigms affects the ability of developers to comprehend that
code. Understanding the predominant paradigm in code, and how developers classify
the predominant paradigm, can benefit future research in program comprehension as
the paradigm may factor into how people comprehend that code. Other researchers
may want to look at how the paradigms in the code interact with various code smells.
To investigate how …

Semantic Segmentation Based Deep Learning Approaches For Weed Detection, Puranjit Singh

Department of Agricultural and Biological Systems Engineering: Dissertations, Theses, and Student Research

Global increase in herbicide use to control weeds has led to issues such as evolution of herbicide-resistant weeds, off-target herbicide movement, etc. Precision agriculture advocates Site Specific Weed Management (SSWM) application to achieve precise and right amount of herbicide spray and reduce off-target herbicide movement. Recent advancements in Deep Learning (DL) have opened possibilities for adaptive and accurate weed recognitions for field based SSWM applications with traditional and emerging spraying equipment; however, challenges exist in identifying the DL model structure and train the model appropriately for accurate and rapid model applications over varying crop/weed growth stages and environment. In our …

Earlier Snowmelt May Lead To Late Season Declines In Plant Productivity And Carbon Sequestration In Arctic Tundra Ecosystems, Donatella Zona, Peter M. Lafleur, Koen Hufkens, Barbara Bailey, Beniamino Gioli, George Burba, Jordan P. Goodrich, Anna K. Liljedahl, Eugénie S. Euskirchen, Jennifer D. Watts, Mary Farina, John S. Kimball, Martin Heimann, Mathias Göckede, Martijn Pallandt, Torben R. Christensen, Mikhail Mastepanov, Efrén López-Blanco, Marcin Jackowicz-Korczynski, Albertus J. Dolman, Luca Belelli Marchesini, Roisin Commane, Steven C. Wofsy, Charles E. Miller, David A. Lipson, Josh Hashemi, Kyle A. Arndt, Lars Kutzbach, David Holl, Julia Boike, Christian Wille, Torsten Sachs, Aram Kalhori, Xia Song

Daugherty Water for Food Global Institute: Faculty Publications

Arctic warming is affecting snow cover and soil hydrology, with consequences for carbon sequestration in tundra ecosystems. The scarcity of observations in the Arctic has limited our understanding of the impact of covarying environmental drivers on the carbon balance of tundra ecosystems. In this study, we address some of these uncertainties through a novel record of 119 site-years of summer data from eddy covariance towers representing dominant tundra vegetation types located on continuous permafrost in the Arctic. Here we found that earlier snowmelt was associated with more tundra net CO2 sequestration and higher gross primary productivity (GPP) only in June …

Interdisciplinary Design Studio: Programming Document Visioning For A Robotic Demonstration, Research, And Engagement Dairy, Steve(N) Hardy, Nate Bicak, Sarah Alduaylij, Noor Al-Maamari, Devyn Beekman, Kelsey Belgum, Lauren Chubb, Nicholas Forte, Mitchell Hill, Joshua Holstein, Dylan Lambe, Phuong Le, Mia Leriger, Elizabeth Loftus, Josh Lorenzen, Megan Lovci, Alex Martino, Zade Miller, Hannah Morgan, Annabelle Nichols, Collin Shearman, Rebecca Sowl, Nalin Theplikhith, Angela Vu, Shaylee Wagner, Ethan Watermeier, Trever Zelenka

Architecture Program: Student Creative Activity

The 2022 COLLABORATE Design Studio brought together students from various disciplines to address a complex, real-world project which required collaborative input from different perspectives. The studio worked to advance the co-creation of knowledge between external stakeholders, students, and instructors. The course was co-taught by faculty from different disciplines, and areas of expertise. During the semester, Nate Bicak and Steven Hardy worked with students from Architecture and Interior Design in collaboration with students in Dr. Tami Brown-Brandl’s students in Biological Systems Engineering and Animal Science to explore the values, spatial qualities, and area requirements of a Robotic Demonstration, Research, and Engagement …

A Stacking-Based Misbehavior Detection System In Vehicular Communication Networks, Troy Green

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

Over the past few decades communication systems for vehicles have continued to advance. Communications between these vehicles can be classified into safety related and non safety related messages. An example of a safety related message would be one vehicle warning others of an icy road it encountered, where a non safety related communication would be a passenger streaming a movie. In either case it's important to secure the communications so that the system continues to behave as expected. In this thesis we propose a Misbehavior Detection System (MDS), which is a system that monitors messages sent between vehicles, and detects …

Measuring Acoustic Nonlinearity Of Elastic Materials Using Thermal Modulation Of Ultrasonic Waves, Bibo Zhong

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Nonlinear acoustic techniques have been used to determine the nonlinear properties of materials. Existing methods either require complex equipment to measure absolute nonlinear coefficients or can only be used on laboratory-sized specimens. A recently developed thermal modulation method addresses the limitations of existing methods, but further theoretical analysis and validation are required.

In this dissertation, theoretical analyses were first conducted to study the mechanically and thermally induced acoustoelastic effect. Beginning with the wave equation, the relationship of the ultrasonic wave velocity with respect to mechanical strain and the thermal strain was derived in detail. These analyses provided theoretical support for …

Bevers: A General, Simple, And Performant Framework For Automatic Fact Verification, Mitchell Dehaven

School of Computing: Dissertations, Theses, and Student Research

Fact verification has become an important process, primarily done manually by humans, to verify the authenticity of claims and statements made online. Increasingly, social media companies have utilized human effort to debunk false claims on their platforms, opting to either tag the content as misleading or false, or removing it entirely to combat misinformation on their sites. In tandem, the field of automatic fact verification has become a subject of focus among the natural language processing (NLP) community, spawning new datasets and research. The most popular dataset is the Fact Extraction and VERification (FEVER) dataset. In this thesis an end-to-end …

Field Monitoring Of Joint-Less Curved Integral Abutment Bridge In Nebraska, Ramin Ziaei, Yusuf Alhowaidi, Chungwook Sim, Jongwan Eun, Seunghee Kim, Chung Rak Song

Nebraska Department of Transportation: Research Reports

The research objective of this project is to study the behavior of the curved full integral abutment bridge designed in Nebraska through field monitoring and numerical simulation to 1) understand and model the complex short-term and long-term behavior of curved integral abutment bridges, 2) evaluate if the details provided in Nebraska (pile embedment over 4 ft into the abutment) can be expanded for wider design and construction practices (longer spans and larger curvature for curved bridges), and 3) better maintain existing full curved integral bridges in Nebraska based on the findings of this study (revise and optimize design, if needed). …

Low Power Multi-Channel Interface For Charge Based Tactile Sensors, Samuel Hansen

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

Analog front end electronics are designed in 65 nm CMOS technology to process charge pulses arriving from a tactile sensor array. This is accomplished through the use of charge sensitive amplifiers and discrete time filters with tunable clock signals located in each of the analog front ends. Sensors were emulated using Gaussian pulses during simulation. The digital side of the system uses SAR (successive approximation register) ADCs for sampling of the processed sensor signals.

Adviser: Sina Balkır

A Low-Power, Low-Area 10-Bit Sar Adc With Length-Based Capacitive Dac, Zhili Pan

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

A 2.5 V single-ended 10-bit successive-approximation-register analog-to-digital converter (SAR ADC) based on the TSMC 65 nm CMOS process is designed with the goal of achieving low power consumption (33.63 pJ/sample) and small area (2874 µm^2 ). It utilizes a novel length-based capacitive digital-to-analog converter (CDAC) layout to achieve low total capacitance for power efficiency, and a custom static asynchronous logic to free the dependence on a high-frequency external clock source. Two test chips have been designed and the problems found through testing the first chip are analyzed. Multiple improved versions of the ADC with minor variations are implemented on the …

Learnfca: A Fuzzy Fca And Probability Based Approach For Learning And Classification, Suraj Ketan Samal

School of Computing: Dissertations, Theses, and Student Research

Formal concept analysis(FCA) is a mathematical theory based on lattice and order theory used for data analysis and knowledge representation. Over the past several years, many of its extensions have been proposed and applied in several domains including data mining, machine learning, knowledge management, semantic web, software development, chemistry ,biology, medicine, data analytics, biology and ontology engineering.

This thesis reviews the state-of-the-art of theory of Formal Concept Analysis(FCA) and its various extensions that have been developed and well-studied in the past several years. We discuss their historical roots, reproduce the original definitions and derivations with illustrative examples. Further, we provide …

Sequence-Based Bioinformatics Approaches To Predict Virus–Host Relationships In Archaea And Eukaryotes, Yingshan Li

School of Computing: Dissertations, Theses, and Student Research

Viral metagenomics is independent of lab culturing and capable of investigating viromes of virtually any given environmental niches. While numerous sequences of viral genomes have been assembled from metagenomic studies over the past years, the natural hosts for the majority of these viral contigs have not been determined. Different computational approaches have been developed to predict hosts of bacteria phages. Nevertheless, little progress has been made in the virus-host prediction, especially for viruses that infect eukaryotes and archaea. In this study, by analyzing all documented viruses with known eukaryotic and archaeal hosts, we assessed the predictive power of four computational …

Attention In The Faithful Self-Explanatory Nlp Models, Mostafa Rafaiejokandan

School of Computing: Dissertations, Theses, and Student Research

Deep neural networks (DNNs) can perform impressively in many natural language processing (NLP) tasks, but their black-box nature makes them inherently challenging to explain or interpret. Self-Explanatory models are a new approach to overcoming this challenge, generating explanations in human-readable languages besides task objectives like answering questions. The main focus of this thesis is the explainability of NLP tasks, as well as how attention methods can help enhance performance. Three different attention modules are proposed, SimpleAttention, CrossSelfAttention, and CrossModality. It also includes a new dataset transformation method called Two-Documents that converts every dataset into two separate documents required by the …

Immobilized Algae For Produced Water Treatment And Desalination, Shibin Nadersha, Ashraf Aly Hassan

Department of Civil and Environmental Engineering: Faculty Publications

Produced water (PW) is the effluent generated during oil mining and extraction. On average, for every barrel of oil, 4-5 barrels of PW are generated worldwide. The presence of various contaminants in PW makes it toxic. Disposal of untreated PW into oceans and water bodies can cause adverse effects on human health and the environment. Taking into account the large volumes of it being generated, and its effects on the environment, proper treatment is required before reuse or disposal. Microalgal treatment is an effective method for the bioremediation and biodesalination of produced water when acclimatized algal biomass is used for …

Mango Surface Color Features Measurement Using Digital Image Processing, Md Towfiqur Rahman, Goutom Kumar, Md Abdul Momin

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Summary

Postharvest processing of agricultural produce is still done the conventional way in Bangladesh. Manual grading of agricultural produce, especially fruits and vegetables, is laborious and costly due to acute shortage of labor during the peak season, as well as difficulty maintaining the product quality. Machine vision system (MVS) applications are widely used nowadays as a non-destructive and cost-effective technology for automatically grading and sorting large volumes of produce in the packing house according to size, shape, color, texture, and surface defects. In this study, a simple MVS was constructed measuring different color features of mango fruit surface as a …

Framework For The Use Of Extended Reality Modalities In Aec Education, Barbara Oliveira Spitzer, Jae Hoon Ma, Ece Erdogmus, Ben Kreimer, Erica Ryherd, Heidi Diefes-Dux

Department of Agricultural and Biological Systems Engineering: Faculty Publications

The educational applications of extended reality (XR) modalities, including virtual reality (VR), augmented reality (AR), and mixed reality (MR), have increased significantly over the last ten years. Many educators within the Architecture, Engineering, and Construction (AEC) related degree programs see student benefits that could be derived from bringing these modalities into classrooms, which include but are not limited to: a better understanding of each of the subdisciplines and the coordination necessary between them, visualizing oneself as a professional in AEC, and visualization of difficult concepts to increase engagement, self-efficacy, and learning. These benefits, in turn, help recruitment and retention efforts …

High Throughput And Highly Controllable Methods For In Vitro Intracellular Delivery, Justin Brooks, Grayson Minnick, Prithvijit Mukherjee, Arian Jaberi, Lingqian Chang, Horacio D. Espinosa, Ruiguo Yang

Department of Mechanical and Materials Engineering: Faculty Publications

In vitro and ex vivo intracellular delivery methods hold the key for releasing the full potential of tissue engineering, drug development, and many other applications. In recent years, there has been significant progress in the design and implementation of intracellular delivery systems capable of delivery at the same scale as viral transfection and bulk electroporation but offering fewer adverse outcomes. This review strives to examine a variety of methods for in vitro and ex vivo intracellular delivery such as flow-through microfluidics, engineered substrates, and automated probe-based systems from the perspective of throughput and control. Special attention is paid to a …

Multi-Criteria Decision Matrix Method In The Risk Analysis Of Biodiesel Production Processes, Kaylee Alles

Department of Chemical and Biomolecular Engineering: Dissertations, Theses, and Student Research

Renewable fuel technologies aim to mitigate the non-renewability of fossil fuels, challenges with increased energy demand, and the climate impact of fossil fuel emissions. However, before investing in renewable technologies, there need to be decision strategies that assess and identify the best alternatives according to stakeholder priorities. There is also a concern about whether the technologies that are the “most sustainable” effectively meet the acceptable risk requirements of stakeholders. In response to this question, a risk-adapted multi-criteria decision model was developed and compared to a sustainability study that evaluated five renewable diesel technologies, including Green Diesel I, II, and III; …

Empirical Fragility Functions And Numerical Parametric Study For Buckling Of Steel Grain Bins Under High Wind Loads, Andrew Ruder

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

While rural infrastructure is critical to the agricultural industry, it has been historically more susceptible to damage and slower to recover following natural disasters than its urban and suburban counterparts. This has been made evident most recently by the events of the August 10, 2020, derecho in which rural regions in Iowa were among the hardest hit areas with sustained windspeeds exceeding 120 mph. Among the most frequently damaged structures in this event were corrugated steel grain bins, which farmers and co-ops use to dry and store certain commodities. Unlike most other critical structures, steel grain bins are not designed …

Evaluation Of Swelling Pressure And Shear Strength Of Inorganic Microfiber-Reinforced Bentonite For The Engineered Barrier System, Jose Maria Ferdinand Victoria Calaunan

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Nowadays, the permanent disposal of high-level radioactive waste materials has been a primary concern in several countries. The deep geological repository, being the preferred disposal method across the globe, utilizes a network of engineered barriers to prevent the radioactive material from spreading throughout the facility and harming the natural environment. Part of this engineered barrier system (EBS) is the buffer material, which essential function is holding the radioactive waste-containing canister in place. However, the potential generation of desiccation cracks in this buffer material is imminent due to the heat emitted from the radioactive waste. Knowing the capability of inorganic fibers …

Parametric Modeling Of Biomimetic Sharkskin For Wire Edm For Drag Reduction And Hydrophobicity, Joel Maxwell

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

This research sets out to demonstrate the viability of parametric modeling for biomimetic sharkskin in the effort to reduce drag and create a self-cleaning surface. Multiple designs were created to be machined by Wire EDM on stainless steel and titanium and were comparatively tested. Limitations of current manufacturing processes to economically produce naturally occurring structures such as sharkskin, emphasize the need to be able to calculate the most accurate design for a given manufacturing process. By designing a simplified but parametrically consistent model compared to an accurately depicted 3D model of sharkskin, the textured samples produced can be further tested …

Prediction Of Meltpool Depth In Laser Powder Bed Fusion Using In-Process Sensor Data, Part-Level Thermal Simulations, And Machine Learning, Grant King

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

The goal of this thesis is the prevention of flaw formation in laser powder bed fusion additive manufacturing process. As a step towards this goal, the objective of this work is to predict meltpool depth as a function of in-process sensor data, part-level thermal simulations, and machine learning. As motivated in NASA's Marshall Space Flight Center specification 3716, prediction of meltpool depth is important because: (1) it can serve as a surrogate to estimate process status without the need for expensive post-process characterization, and (2) the meltpool depth provides an avenue for rapid qualification of microstructure evolution. To achieve the …

A Pipeline To Generate Deep Learning Surrogates Of Genome-Scale Metabolic Models, Achilles Rasquinha

School of Computing: Dissertations, Theses, and Student Research

Genome-Scale Metabolic Models (GEMMs) are powerful reconstructions of biological systems that help metabolic engineers understand and predict growth conditions subjected to various environmental factors around the cellular metabolism of an organism in observation, purely in silico. Applications of metabolic engineering range from perturbation analysis and drug-target discovery to predicting growth rates of biotechnologically important metabolites and reaction objectives within dierent single-cell and multi-cellular organism types. GEMMs use mathematical frameworks for quantitative estimations of flux distributions within metabolic networks. The reasons behind why an organism activates, stuns, or fluctuates between alternative pathways for growth and survival, however, remain relatively unknown. GEMMs …

Application Of Uas‑Based Remote Sensing In Estimating Winter Wheat Phenotypic Traits And Yield During The Growing Season, Kianoosh Hassani, Hamed Gholizadeh, Saleh Taghvaeian, Victoria Natalie, Jonathan Carpenter, Jamey Jacob

Department of Agricultural and Biological Systems Engineering: Faculty Publications

Phenotyping approaches have been considered as a vital component in crop breeding programs to improve crops and develop new high-yielding cultivars. However, traditional field-based monitoring methods are expensive, invasive, and time-intensive. Moreover, data collected using satellite and airborne platforms are either costly or limited by their spatial and temporal resolution. Here, we investigated whether low-cost unmanned/unoccupied aerial systems (UASs) data can be used to estimate winter wheat (Triticum aestivum L.) nitrogen (N) content, structural traits including plant height, fresh and dry biomass, and leaf area index (LAI) as well as yield during different winter wheat growing stages. To achieve …

Efects Of Non‑Newtonian Viscosity On Arterial And Venous Fow And Transport, Sabrina Lynch, Nitesh Nama, C Alberto Figueroa

Department of Mechanical and Materials Engineering: Faculty Publications

It is well known that blood exhibits non-Newtonian viscosity, but it is generally modeled as a Newtonian fluid. However, in situations of low shear rate, the validity of the Newtonian assumption is questionable. In this study, we investigated differences between Newtonian and non-Newtonian hemodynamic metrics such as velocity, vorticity, and wall shear stress. In addition, we investigated cardiovascular transport using two different approaches, Eulerian mass transport and Lagrangian particle tracking. Non-Newtonian solutions revealed important differences in both hemodynamic and transport metrics relative to the Newtonian model. Most notably for the hemodynamic metrics, in-plane velocity and vorticity were consistently larger in …

Enhanced Electron Correlation And Significantly Suppressed Thermal Conductivity In Dirac Nodal-Line Metal Nanowires By Chemical Doping, Amanda L. Coughlin, Zhiliang Pan, Jeonghoon Hong, Tongxie Zhang, Xun Zhan, Wenqian Wu, Dongyue Xie, Tian Tong, Thomas Ruch, Jean J. Heremans, Jiming Bao, Herbert A. Fertig, Jian Wang, Jeongwoo Kim, Hanyu Zhu, Deyu Li, Shixiong Zhang

Department of Mechanical and Materials Engineering: Faculty Publications

Enhancing electron correlation in a weakly interacting topological system has great potential to promote correlated topological states of matter with extraordinary quantum properties. Here, the enhancement of electron correlation in a prototypical topological metal, namely iridium dioxide (IrO₂), via doping with 3d transition metal vanadium is demonstrated. Single-crystalline vanadium-doped IrO₂ nanowires are synthesized through chemical vapor deposition where the nanowire yield and morphology are improved by creating rough surfaces on substrates. Vanadium doping leads to a dramatic decrease in Raman intensity without notable peak broadening, signifying the enhancement of electron correlation. The enhanced electron correlation is further …

In Vitro Models For The Study Of Liver Biology And Diseases: Advances And Limitations, Savneet Kaur, Srivatsan Kidambi, Martí Ortega-Ribera, Le Thi Thanh Thuy, Natalia Nieto, Victoria C. Cogger, Wei-Fen Xie, Frank Tacke, Jordi Gracia-Sancho

Department of Chemical and Biomolecular Engineering: Faculty Publications

In vitro models of liver (patho)physiology, new technologies, and experimental approaches are progressing rapidly. Based on cell lines, induced pluripotent stem cells or primary cells derived from mouse or human liver as well as whole tissue (slices), such in vitro single- and multicellular models, including complex microfluidic organ-on-a-chip systems, provide tools to functionally understand mechanisms of liver health and disease. The International Society of Hepatic Sinusoidal Research (ISHSR) commissioned this working group to review the currently available in vitro liver models and describe the advantages and disadvantages of each in the context of evaluating their use for the study of …

Exosomes Derived From Differentiated Human Admsc With The Schwann Cell Phenotype Modulate Peripheral Nerve-Related Cellular Functions, Bo Liu, Yunfan Kong, Wen Shi, Mitchell Kuss, Ke Liao, Guoku Hu, Peng Xiao, Jagadesan Sankarasubramanian, Chittibabu Guda, Xinglong Wang, Yuguo Lei, Bin Duan

Department of Mechanical and Materials Engineering: Faculty Publications

Peripheral nerve regeneration remains a significant clinical challenge due to the unsatisfactory functional recovery and public health burden. Exosomes, especially those derived from mesenchymal stem cells (MSCs), are promising as potential cell-free therapeutics and gene therapy vehicles for promoting neural regeneration. In this study, we reported the differentiation of human adipose derived MSCs (hADMSCs) towards the Schwann cell (SC) phenotype (hADMSC-SCs) and then isolated exosomes from hADMSCs with and without differentiation (i.e., dExo vs uExo). We assessed and compared the effects of uExo and dExo on antioxidative, angiogenic, antiinflammatory, and axon growth promoting properties by using various peripheral nerve-related cells. …